triple negative breast cancer case study

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New study finds triple-negative breast cancer tumors with an increase in immune cells have lower risk of recurrence after surgery

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By Kelley Luckstein

A new multicenter, international study suggests that people who have early-stage  triple-negative breast cancer  (TNBC) and high levels of immune cells within their tumors may have a lower risk of recurrence and better survival rates even when not treated with chemotherapy. The  study  was published today in the Journal of American Medical Association (JAMA).

TNBC is a breast cancer subtype that does not respond to drugs that target the estrogen receptor or the HER2 protein. It grows rapidly, is more likely to spread beyond the breast before diagnosis and is more likely to recur than other breast cancers. TNBC represents about 15% of all breast cancers and is more common in younger people and in women of African American, Hispanic and Indian descent. Immune cells, also known as tumor-infiltrating lymphocytes, or TILs, are naturally existing immune system cells that can move from the bloodstream into a tumor and can recognize and destroy cancer cells.

"This is an important finding because it highlights that the abundance of TILs in breast tissue is a prognostic biomarker in people with early-stage triple-negative breast cancer, even when chemotherapy is not administered," says  Roberto Leon-Ferre, M.D. , a breast medical oncologist at  Mayo Clinic Comprehensive Cancer Center  and first author of the study. "The study's findings may inspire future clinical trials to explore whether patients with a favorable prognosis (high TILs) can avoid intensive chemotherapy regimens."

"This meta-analysis confirms robustly the prognostic value of TILs that we have previously reported in TNBC patients treated with chemotherapy and expands it to patients treated without chemotherapy," says Sarah Flora Jonas, Ph.D., a statistician at  Gustave Roussy  and co-first author of the study. "Future studies may allow the use of this biomarker along with standard clinicopathological factors to inform treatment decisions in TNBC patients."

"Of interest, the first report suggesting that an increased number of immune cells being associated with better prognosis in breast cancer patients was described by doctors at Mayo Clinic more than 100 years ago," says Roberto Salgado, M.D., co-chair of the International Immuno-Oncology Biomarker Working Group; co-lead of the study; and pathologist from the Peter MacCallum Cancer Centre, Melbourne, Australia, and ZAS Hospitals, Antwerp, Belgium. "It took a global effort and a century later to reexamine this biomarker and bring it closer to application in patient care."

"TILs are not currently measured or reported in the routine examination of tissue samples of breast cancer," says co-senior author,  Matthew Goetz, M.D. , a medical oncologist at Mayo Clinic Comprehensive Cancer Center and the Erivan K. Haub Family Professor of Cancer Research Honoring Richard F. Emslander, M.D. "While prior studies have focused on measuring TILs in people treated with chemotherapy, this is the largest study to comprehensively demonstrate that the presence of TILs influences the natural behavior of breast cancer in people who have surgery and/or radiation with no additional medical treatment."

For this study, Mayo Clinic and Gustave Roussy researchers, in collaboration with the International Immuno-Oncology Biomarker Working Group, led 11 additional groups to collect data on 1,966 participants with early-stage TNBC who only underwent surgery with or without radiation therapy but did not receive chemotherapy. The participants had been followed for a median of 18 years. The results showed that higher levels of TILs in breast cancer tissue were associated with lower recurrence rates among participants with early-stage TNBC.

"Five years after surgery, 95% of participants with small tumors, stage 1 TNBC, and whose tumors had high TILs were alive, compared to 82% of patients whose tumors had low TILs. Importantly, the breast cancer recurrence rate was significantly lower among patients whose tumors had high TILs," says co-senior author,  Stefan Michiels, Ph.D. , head of Oncostat team, Gustave Roussy, Inserm U1018, University Paris-Saclay. "With nearly 2,000 participants involved in the study, we have now assembled the largest international cohort across three continents of people with TNBC in which the primary treatment was surgery without chemotherapy."

"The results of this study could lead to a recommendation to include TILs in the pathology reports of early-stage TNBC worldwide, as it has the potential to inform clinicians and patients when they discuss treatment options," says Dr. Salgado.

Furthermore, this biomarker would only require a visual evaluation by a pathologist looking through a microscope, meaning there are no additional costs associated with identifying the presence of immune cells. This could be particularly beneficial to regions with limited resources, adds Dr. Leon-Ferre.

Most people with early-stage TNBC undergo chemotherapy either before or after surgery, including people with stage 1 breast cancer. Most people receive multiple chemotherapy drugs in combination, which can cause significant side effects. Currently, the main factors considered to determine the course of chemotherapy treatment for each person are the tumor size and whether the cancer has spread to the lymph nodes. However, the authors identified that the number of TILs further influences the risk of future recurrence.

The researchers plan to evaluate TILs as biomarkers in prospective clinical trials evaluating chemotherapy selection based on TIL levels. Ongoing efforts to conduct additional research with other potential biomarkers are underway.

For a complete list of authors, disclosures and funding, see the full paper  here .

Learn more about breast cancer and find a clinical trial at Mayo Clinic.

Join the Breast Cancer Support Group on Mayo Clinic Connect , an online community moderated by Mayo Clinic for patients and caregivers.

Also, read these articles:

• Understanding triple-negative breast cancer and its treatment
• 17-gene signature linked to remission after triple-negative breast cancer treatment

A version of this article was originally published as a press release on the Mayo Clinic News Network .

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• Open access
• Published: 05 January 2024

A real-world study of the effectiveness and safety of apatinib-based regimens in metastatic triple-negative breast cancer

• Weiwei Huang 1 , 2 , 3   na1 ,
• Chenxi Wang 4   na1 ,
• Yangkun Shen 4   na1 ,
• Qi Chen 4 ,
• Zhijian Huang 5 ,
• Jian Liu 2 ,
• Xiaoyan Lin 1 , 3 ,
• Lili Wang 2 ,
• Xinhua Chen 2 ,
• Nani Li 2 ,
• Yi Hong 2 ,
• Mulan Chen 2 ,
• Jieyu Li 6 &
• Chuanzhong Huang 6  

BMC Cancer volume  24 , Article number:  39 ( 2024 ) Cite this article

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A Correction to this article was published on 25 March 2024

This article has been updated

This investigation sought to examine the efficacy and safety of low-dose apatinib used alongside chemotherapy in the clinical management of patients with metastatic triple-negative breast cancer (TNBC) within a real-world setting, whilst comparing the outcomes with those treated solely with chemotherapy.

This case series study analyzed clinical data and treatment outcomes of 163 patients with metastatic TNBC who underwent rescue treatment at the Medical Oncology Department of Clinical Oncology, Fujian Cancer Hospital, School of Fujian Medical University, China, between October 2011 and January 2023. All the patients underwent rescue treatment with either chemotherapy alone or apatinib (250 mg/day) combined with chemotherapy. The study’s primary outcome was progression-free survival (PFS), whereas the secondary outcomes included overall survival (OS), objective response rate (ORR), disease control rate (DCR), and safety profiles.

The study was designed to compare two groups [ 1 ]. Out of the 163 TNBC patients who participated in the study, 107 individuals (65.6%) received treatment based on chemotherapy, whereas 56 patients (34.4%) were given treatment based on a combination of low-dose apatinib (250 mg/day) and other treatments, including chemotherapy. After propensity score matching (PSM), the objective response rate (ORR) and disease control rate (DCR) of patients with advanced triple-negative breast cancer (TNBC) who received apatinib-based treatment were 50.0 and 90.0%, respectively, while they were 6.7 and 20.0%, respectively, for the chemotherapy-based group (P < 0.001). The group that received apatinib-based treatment showed superior results in both PFS and OS compared to the group that received chemotherapy. The median PFS and OS for the apatinib-based group were 7.8 and 20.3 months, respectively, while they were only 2.2 months and 9.0 months, respectively, for the chemotherapy-based group (P < 0.001) [ 2 ]. Patients who were administered combo therapies, including PD-1 inhibitors, were excluded. In total, 97 patients received chemotherapy alone, while 34 patients were treated with apatinib in combination with chemotherapy. After propensity score matching (PSM), the ORR and DCR for the total group who received combo therapies were 44.4 and 81.5%, respectively, while they were 11.1 and 22.2%, respectively, for the chemotherapy alone group (P < 0.001). The group receiving both apatinib and chemotherapy displayed notable advantages over the group solely receiving chemotherapy in regards to PFS and OS for the entirety of the population. The PFS was found to be 7.8 months in comparison to 2.1 months (P < 0.001) and the OS was 21.1 months in contrast to 9.0 months (P < 0.001). Apatinib combined with chemotherapy induced grade 3/4 hematological toxicities, including neutropenia (8.8%) and thrombocytopenia (2.9%). Additionally, non-hematological toxicities were commonly observed, such as Hand-foot syndrome (35.3%), proteinuria (26.5%), hypertension (61.8%), higher alanine aminotransferase levels (26.5%), and fatigue (35.3%). The most frequent non-hematological grade 3/4 toxicities were Hand-foot syndrome (2.9%) and hypertension (5.9%). The study did not report any fatal adverse effects.

Conclusions

The combination of low-dose apatinib with chemotherapy has proven to be more effective than chemotherapy alone in treating metastatic triple-negative breast cancer (TNBC). Additionally, the occurrence of grade 3/4 non-hematologic toxicities was significantly lower compared to the recommended dose of apatinib.

Peer Review reports

Introduction

Breast cancer is the most common cancer among women in China and has been persistently increasing with time in the world [ 1 ]. Roughly 15–25% of all breast cancers are categorized “triple-negative breast cancers” (TNBC), which is a subtype of breast cancer that tests negatively for progesterone, estrogen, and “human epidermal growth factor-2” (HER-2) [ 2 ]. This subtype is more prevalent in young women and typically comes with a poor prognosis and a high risk of metastasis [ 3 ]. Currently, there is no established standard treatment approach strategy for TNBC. While targeted drugs, immune checkpoint inhibitors, and antibody-conjugated drugs are obtainable, chemotherapy continues to be the primary treatment for TNBC [ 4 ]. Anthracyclines and taxanes are generally utilized as the first-line treatment, either sequentially or in combination. However, the addition of platinum, capecitabine, or gemcitabine to anthracycline and taxane treatments that have failed has demonstrated unsatisfactory efficacy [ 5 ].

Vascular endothelial growth factor(VEGF) binds to its receptor and promotes the growth and spread of tumors [ 6 ]. Those with TNBC demonstrate higher levels of VEGF expression compared to those without TNBC. As a result, anti-angiogenic drugs, such as apatinib and bevacizumab, are effective in inhibiting tumor development [ 7 ]. The addition of bevacizumab to standard capecitabine or anthracycline/taxane protocols led to an increase in “median progression-free survival” (mPFS) among patients suffering from locally recurrent or metastatic TNBC, with acceptable tolerability, according to the results of phase III clinical study (RIBBON-1) [ 8 ]. Evidence points towards increased OS with further research showing that the mPFS in TNBC patients significantly improved with the addition of bevacizumab (6.0 vs. 2.7 months; P < 0.001) [ 9 ]. The combination of bevacizumab and chemotherapy also prolonged PFS in 621 TNBC patients in 2010, according to the meta-analysis of three trials (E2100, AVADO, and RIBBON-1), although it did not enhance OS. The approval of bevacizumab for the treatment of breast cancer was revoked by the FDA in 2011 due to safety concerns and cost-effectiveness. Further clinical studies are required to assess the effectiveness and safety of anti-angiogenic treatment.

Apatinib is an orally administered, phosphorylated VEGFR2-targeting tyrosine kinase inhibitor (TKI) of the second generation. According to preclinical studies, apatinib effectively inhibits the growth of solid tumors and leukemia [ 10 ]. Its application successfully halted xenograft tumor growth, reversed medication resistance, and prevented the proliferation of tumor stem cells and the production of tumor microspheres. It can also prevent the migration of tumor cells and the formation of human umbilical vein endothelial cell tubes [ 11 ].

The mechanism of action of apatinib against malignant tumors is intricate. According to the prevailing perspective, apatinib specifically inhibits the “ATP-binding site” of VEGFR-2 located inside the cell, which subsequently obstructs signal transduction downstream [ 12 ]. Furthermore, therapeutic effects can be achieved through blocking and inhibiting the phosphorylation of VEGFR-2(pVEGFR2) and downstream extracellular signal-related kinases, as well as preventing the activation of tyrosine kinases, including PDGFRβ, c-Kit, c-SRC, and Ret, which are associated with tumor development [ 13 ]. In this way, tumor angiogenesis can be inhibited through multiple targets and tumor inhibition can be induced by promoting apoptosis in tumor cells.

Aptatinib was approved and authorized by the former “China Food and Drug Administration” in 2014 for treating adenocarcinoma of the gastroesophageal junction or progressive gastric cancer in the third and later lines. Currently, clinical trials are underway to evaluate its efficacy as a targeted anti-tumor angiogenesis drug for treating breast cancer, non-small cell lung cancer, and other tumors. In an investigation of single-agent apatinib for advanced TNBC, 25 patients were included in phase IIa; the median progression-free survival (mPFS) and median overall survival (mOS) were 4.6 and 8.3 months, respectively. Out of the 22 evaluated patients,the partial response (PR) rate was 36.4% and the stable disease (SD) rate was 22.7% [ 14 ]. Aptatinib treatment may provide benefits to individuals suffering from advanced TNBC. Nevertheless, administering large doses of the drug is not well-tolerated as it leads to significant proteinuria, high blood pressure, and hand-foot syndrome. Following this, further studies have been conducted to explore the use of low-dose apatinib (250 mg/day) with chemo and immune system checkpoint blockers. This retrospective study aimed to investigate the safety and efficacy of low-dose apatinib in patients with TNBC at the single center of " Medical Oncology Department of Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital “, in addition to assessing the clinical benefits of combining low-dose apatinib with chemotherapy in comparison to chemotherapy alone. The objective of this retrospective study, conducted in a single center and in compliance with the “Helsinki Declaration and Good Clinical Practise Guidelines” is to evaluate the efficacy and safety of the combined use of apatinib and chemotherapy in treating patients with metastatic or unresectable recurrent TNBC.

This study comprised patients with metastatic or unresectable recurrent TNBC who underwent apatinib-based therapy at the Medical Oncology Department of Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital from October 2011 to January 2023. Some patients included in the retrospective data received simultaneous chemotherapy and apatinib as a part of a clinical study initiated by the researchers. Patients compared between groups receiving apatinib-based therapy versus chemo-based therapy, or apatinib plus Chemotherapy versus chemotherapy alone, were matched for age, ECOG PS, menopausal status, and metastasis site or locations. These patients received written informed consent and approval from the institutional ethics committee. Only patients between the ages of 18 and 70 were included. HER2/neu-negative was defined as either immunohistochemistry (IHC) 0–1 + or IHC 2 + fluorescence in situ hybridization (FISH)-negative, while TNBC (ER/PR-negative) was defined as ER/PR staining less than 1%. According to the Response Evaluation Criteria in Solid Tumors (RECIST v1.1), all patients included in the study had detectable lesions and were administered oral apatinib at a dosage of 250 mg/day for a minimum of 30 days. The patient ceased apatinib-based therapy upon refusal, worsening of symptoms, or intolerable side effects. The study utilized RECIST v1.1 to assess efficacy and NCI-CTCAE 5.0 to report adverse events. The primary outcomes centered on PFS. The secondary outcomes considered were the OS, ORR, DCR, and safety profiles. To reduce the risk of selection bias and other confounding factors, propensity score matching (PSM) was utilized. The PSM model included the following factors: patient age, Eastern Co-operative Oncology Group Performance Score (ECOG PS), menopausal status, prior surgery, TNBC at initial onset, Ki67 status, metastasis site or locations, perioperative treatment, combination therapy type and line of therapy. Matched pairs were then formed using a 1-to-1 nearest-neighbor with a caliper width of 0.2. Between-group differences were compared using a Student’s t-test or the chi-squared test. OS and PFS were calculated with the Kaplan–Meier method and compared using the log-rank test. Any factors that were statistically significant (p < 0.10) in the univariate analysis were candidates for entry into a multivariable Cox proportional-hazards model. All p-values were 2-sided, with p-values < 0.05 considered significant. In this study, the prognostic model was built to assess the contribution of variables, which was formed from a training set of 70% (114) and a test set of the remaining 30% (49) randomly, derived from the original data. Shapley additive explanations (SHAP) were used to explain the model. “survival”, “shapviz” and “xgboost” R packages were used to perform the SHAP analysis. R version 4.2.3 was used for all statistical analyses.

Initially, 273 patients who consented to the rescue treatment plan underwent screening. Following the elimination of individuals with missing data or lost follow-up, 163 eligible patients with TNBC were selected for investigation. Of these, 56 patients (34.4%) underwent apatinib-based treatment, while the remaining 107 patients (65.6%) received chemotherapy-based rescue treatment. Thirty-four patients were administered apatinib in combination with chemotherapy, excluding those who received combination treatment containing PD-1 inhibitors (18 cases of apatinib + PD-1 inhibitor + chemotherapy), apatinib monotherapy (2 cases), apatinib with PD-1 inhibitor (1 case), and apatinib with PARP inhibitor (1 case). Ninety-seven patients received chemotherapy alone, except for four cases of chemotherapy with a PD-1 inhibitor, one case of chemotherapy with HER2-targeted therapy, three cases of Chemotherapy combined with endocrine therapy containing CDK4/6 inhibitors, one case of chemotherapy with bevacizumab, and one case of chemotherapy with PARP inhibitor.

The study was designed to compare two groups: (1) a group that received apatinib (n = 56) versus a group that did not (n = 107); (2) a group that received apatinib in combination with chemotherapy (n = 34) versus a group that received only chemotherapy (n = 97). After PSM, the two comparison cohorts were as follows; apatinib-based treatment (n = 30) versus chemotherapy-based treatment (n = 30), apatinib combined with chemotherapy treatment (n = 27) versus chemotherapy alone treatment (n = 27). The detailed information regarding treatment is shown in Fig.  1 .

Population attrition after applying inclusion/exclusion criteria and propensity score matching. Cap, capecitabine; Gem, gemcitabine; NVB, vinorelbine; 5fu, 5-fluorouracil; EADM, epirubicin

Baseline characteristics and disease characteristics pre- and post-PSM for the apatinib-based treatment versus chemotherapy-based treatment, apatinib combined with chemotherapy treatment versus chemotherapy alone treatment are shown in Tables  1 and 2 , respectively. Table  3 and Table  4 , as well as Figs.  2 , 3 , 4 and 5 , illustrate the efficacy data.

Progression-free survival ( A ) and overall survival outcomes. Kaplan-Meier analysis of survival showing progression-free survival ( A ) and overall survival ( C ) in cohort 1, and progression-free survival ( B ) and overall survival ( D ) in cohort 2. Kaplan-Meier estimates of progression-free survival by Response Evaluation Criteria in Solid Tumors version 1.1. HR = hazard ratio

Forest plots. Showing the association between risk factors and progression-free survival or overall survival in cohort 1. (Cox regression, HR, and 95% CI). P value was calculated with a 2-sided log-rank test. Any factors that were statistically significant at P < 0.1 in the univariate analysis were candidates for entry into a multivariable Cox analysis

Forest plots. Showing the association between risk factors and progression-free survival or overall survival in cohort 2. (Cox regression, HR, and 95% CI). P value was calculated with a 2-sided log-rank test. Any factors that were statistically significant at P < 0.1 in the univariate analysis were candidates for entry into a multivariable Cox analysis

Summary plots for SHAP values. ( A ) Progression-free survival. ( B ) Overall survival. For each predictor, one point corresponds to a single patient, and the x-axis represents the impact of the feature on the model’s output for the specific patient. A positive SHAP value contributes to disease progression or death, while a negative value contributes to OS or PFS. Predictors are arranged along the y-axis based on their ranking: the higher the feature is positioned in the plot, the more significant it is in the model

Effectiveness evaluation

Apatinib-based versus chemotherapy-based therapy.

After PSM, the group receiving apatinib-based(n = 30) was compared with the group receiving chemotherapy-based rescue treatment (n = 30). Results showed that after receiving apatinib, statistically significant improvements in ORR and DCR were observed in the overall population, as well as in the first-line and second-and later-line advanced TNBC populations (Table  3 ). In addition, The PFS of the group receiving apatinib-based treatment showed a substantial improvement (7.8 vs. 2.2 months; HR = 0.21, p < 0.001) (Fig.  2 A). The OS of the entire population was significantly improved (20.3 vs. 9.0 months; HR = 0.20, p < 0.001) (Fig.  2 C).

The results of the univariate and multivariate analyses for PFS and OS are shown in Fig.  3 . The results showed that the age (less than 50 vs. greater than or equal to 50, HR = 0.66; 95% CI: 0.44–0.99, p = 0.045), ECOG score (0 vs. 1–2, HR = 0.42; 95% CI: 0.21–0.85, p = 0.016), combination therapy with apatinib (HR = 0.41; 95% CI: 0.27–0.65, p < 0.001) and clinical benefit profile (CR + PR + SD vs. PD/UKN, HR = 0.18; 95% CI: 0.11–0.31, p < 0.001) were independent predictors of longer PFS. In addition, combination therapy with apatinib (HR = 0.39; 95% CI: 0.23–0.68, p = 0.001) and clinical benefit profile (CR + PR + SD vs. PD/UKN, HR = 0.26; 95% CI: 0.15–0.45, p < 0.001) were independent predictors for longer OS.

Apatinib combined with chemotherapy versus chemotherapy alone therapy

After PSM, the group receiving apatinib combined with chemotherapy (n = 27) was compared with the group receiving chemotherapy alone rescue treatment (n = 27). The study showed that receiving a combination of chemotherapy and apatinib resulted in a statistically significant improvement in DCR in all populations studied, including the first-line and second- and later-line advanced TNBC populations, as well as a significant difference in ORR in the overall, second-line, and above populations. However, no significant difference in ORR was observed in the first-line population (Table  4 ). In addition, The PFS of the group receiving apatinib combined with chemotherapy treatment showed a substantial improvement (7.8 vs. 2.1 months; HR = 0.16, p < 0.001) (Fig.  2 B). The OS of the entire population was significantly improved (21.1 vs. 9.0 months; HR = 0.16, p < 0.001) (Fig.  2 D).

The results of the univariate and multivariate analyses for PFS and OS are shown in Fig.  4 . The results showed that the ECOG score (0 vs. 1–2, HR = 0.34; 95% CI: 0.16–0.76, p = 0.008), combination therapy with apatinib (HR = 0.39; 95% CI: 0.24–0.64, p < 0.001) and clinical benefit profile (CR + PR + SD vs. PD/UKN, HR = 0.21; 95% CI: 0.12–0.37, p < 0.001) were independent predictors of longer PFS. In addition, combination therapy with apatinib (HR = 0.32; 95% CI: 0.17–0.62, p = 0.001) and clinical benefit profile (CR + PR + SD vs. PD/UKN, HR = 0.24; 95% CI: 0.13–0.46, p < 0.001) were independent predictors for longer OS.

Feature importance

The summary plots of the SHAP values for the top 10 most significant predictors of PFS and OS are shown in Fig.  5 A and B, respectively. The apatinib treatment was considered the most significant variable both in predicting PFS and OS (patients treated with apatinib had lower risk scores, while those who were not received apatinib had a higher risk score), followed by age, ECOG PS and other chemotherapy in predicting PFS, and eribulin, other chemotherapy, ECOG PS and age in predicting OS (Fig.  5 ).

Adverse reactions

Grade 3/4 hematological side effects, such as thrombocytopenia (5.4%) and leukopenia (12.5%), were observed in the apatinib-containing group during this trial. Additionally, PD-1 inhibitors and other therapies were administered. The non-hematological toxicities that were common included hand-foot syndrome (39.3%), proteinuria (23.2%), hypertension (58.9%), elevated ALT levels (33.9%), and fatigue (48.2%). Of these, hand-foot syndrome (1.8%), proteinuria (0%), hypertension (5.4%), elevated ALT levels (3.6%), and fatigue (1.8%) were identified as grade 3/4 non-hematological toxicities.

Thrombocytopenia (2.9%) and leukopenia (8.8%) were observed as the grade 3/4 hematological toxicities within the apatinib coupled with the chemotherapy group without PD-1 inhibitor. Hand-foot syndrome (35.3%), proteinuria (26.5%), hypertension (61.8%), elevated ALT levels (26.5%), and fatigue (35.3%) were identified as prevalent non-hematological toxicities. Notably, hand-foot syndrome (2.9%) and hypertension (5.9%) were categorized as grade 3/4 non-hematological toxicities, while no instances of severe proteinuria, elevated ALT levels, or fatigue were observed (refer to Tables  5 and 6 ).

The combination of chemotherapeutic agents and apatinib is an emerging area of research for the treatment of advanced TNBC. There is already evidence of a substantial potential therapeutic effect, but this evidence is not yet comprehensive and adequate. The prescribed apatinib doses for phases IIa and IIb in clinical trial for metastatic TNBC following multiline treatment was 750 mg/day and 500 mg/day, correspondingly [ 14 ]. The ORR and DCR for the 56 patients who could be evaluated during the phase IIb trial were 10.7% and 25.0%, respectively. The PFS and OS were 3.3 (95% CI 1.7-5.0) and 10.6 (95% CI 5.6–15.7) months. In the phase IIa trial, the ORR and DCR for the 22 patients who were evaluable were 36.4% and 59.1%, respectively. The median PFS and OS were 4.6 (95% CI 2.1–7.1) and 8.3 (95% CI 4.1–12.4) months, respectively. In the phase IIa trial, the most frequent grade 3/4 hematologic toxicities were thrombocytopenia (8.0%), leukopenia (8.0%), granulocytopenia (4.0%), and anemia (4.0%). The most prevalent grade 3/4 non-hematologic effects were hand-foot syndrome (24.0%), proteinuria (4.0%), hypertension (36.0%), increased ALT (4.0%), and tiredness (8.0%). The recommended dose of apatinib is 500 mg daily, based on safety and efficacy [ 14 ]. A trial conducted on advanced non-TNBC patients after multiline treatment, using apatinib 500 mg/day, resulted in an ORR of 16.7% (6/36), and median PFS and OS of 4.0 and 10.3 months, respectively. Out of the total 38 participants in the study, one exhibited complete remission while five had partial remission. Proteinuria (5.1%), hand-foot syndrome (10.3%), and hypertension (20.5%) were the most frequent grade 3/4 treatment-related toxicities [ 15 ]. Another retrospective study used capecitabine and 500 mg/day of apatinib as the third-line therapy for metastatic TNBC. When capecitabine was administered alone, the ORR was 13.4% and the DCR was 31.8% among 22 patients. However, when the same 22 patients were treated with combination treatment, the ORR was 40.9% and the DCR was 68.2%, indicating better outcomes than with capecitabine alone (P = 0 0.042;0 0.016). The mean PFS for the combined therapy group was 5.5 months, compared to 3.5 months for the capecitabine group, indicating a notable advantage (P = 0.001). There was no significant difference in the adverse effects of hematological toxicity (reduced white blood cell and granulocyte counts) and non-hematological toxicity (hypertension, fatigue, hand-foot syndrome, vomiting). The combination of apatinib and capecitabine may result in greater efficacy and comparable side effects compared to the capecitabine regimen [ 16 ].

Current published regimens of apatinib monotherapy or combination therapy have exhibited efficacy and safety, when compared to other TKI anti-angiogenic drugs like sunitinib and sorafenib, that have displayed inadequate efficacy as monotherapy. Nevertheless, the recommended 500 mg/day dose of apatinib can cause side effects, including hand-foot syndrome, hypertension, and proteinuria, which could hinder future studies. In this study, we investigated the efficacy of administering a low dosage of apatinib (250 mg/day) in combination with chemotherapy for the treatment of advanced TNBC, which had proven resistant to previous therapies. Additionally, we aimed to investigate whether this therapy could decrease the incidence of hypertension, proteinuria, and hand-foot syndrome, and concurrently lead to advancements in PFS and/or OS.Our study demonstrated that after conducting PSM, patients who received apatinib-based treatment (n = 30) had an ORR of 50.0% and a DCR of 90.0%, compared to 6.7% and 20.0%, respectively, for the chemotherapy-based group (n = 30) (P < 0.001). Notably, statistically significant improvements in ORR and DCR were observed in both the first-line and second-and later-line advanced TNBC populations after receiving apatinib (Table  3 ). The cohort that was administered apatinib-based treatment exhibited better outcomes than the cohort that received chemotherapy. The PFS and OS periods for the apatinib-based group were 7.8 and 20.3 months, respectively, as opposed to 2.2 and 9.0 months respectively, for the chemotherapy-based group (P < 0.001) (Fig.  2 A and C).

The efficacy and safety of the combination group (n = 27) of apatinib and chemotherapy were compared against the chemotherapy alone group (n = 27) using PSM analysis, while considering other phase II trials on TNBC, in order to eliminate any bias created by other therapies. The study showed that there was a substantial improvement in DCR for all populations studied who received a combination of apatinib and chemotherapy, including first-line and second- and later-line advanced TNBC populations. Additionally, there was a noteworthy difference in ORR in the second-line and above populations. However, no substantial difference in ORR was observed in the first-line population (Table  4 ). The group receiving both apatinib and chemotherapy displayed notable advantages over the group solely receiving chemotherapy in regards to PFS and OS for the entirety of the population. The PFS was found to be 7.8 months in comparison to 2.1 months (P < 0.001) and the OS was 21.1 months in contrast to 9.0 months (P < 0.001) (Fig.  2 B and D).

The study showed that the first-line apatinib-based regimen group had a limited sample size and an immature number of PFS and OS events, so statistically significant differences in PFS and OS were not observed for first-line treatments comparing apatinib-based regimens with chemotherapy-based regimens. After excluding treatment factors such as PD1, the sample size of the first-line treatment in the apatinib combined with chemotherapy group was insufficient for statistically significant analyses. Therefore, while there was a tendency towards an ORR benefit in the first-line apatinib combined with chemotherapy group compared to the chemotherapy-only group, no statistically significant difference was found. These limitations are expected to be addressed by conducting prospective, controlled studies on a larger sample size in the future. Despite the small sample size, the study showed that the combination of apatinib and chemotherapy significantly improved ORR, DCR, PFS and OS in comparison to the chemotherapy alone cohort in the overall population. In brief, illustrating that tumor regression was evident, a significant proportion of patients with CBR could ultimately achieve a substantial survival benefit in terms of PFS and OS. This suggests that apatinib combination chemotherapy can facilitate long-term survival through tumor shrinkage or stabilization.

Multivariate analyses revealed that in both cohort1 and cohort2, ECOG score (0 versus 1–2), use of apatinib and clinical benefit profile were independent PFS predictors. However, except for age (less than 50 years versus greater than or equal to 50 years), which was an independent prognostic factor for PFS in cohort1. Additionally, the multivariate analyses indicated that apatinib combination therapy and clinical benefit profile served as independent predictors for prolonged OS in both cohort1 and cohort2.This study suggests that a favourable ECOG score, administration of apatinib, and a positive clinical benefit profile may lead to improved PFS in patients with advanced TNBC. The combined treatment of apatinib and standard therapy may result in a greater decrease in tumour burden and therefore contribute to increased OS. The SHAP values’ summary plots for the leading ten significant predictors of PFS and OS are demonstrated in Fig.  5 A and B, correspondingly. The most significant predictor of both PFS and OS was apatinib treatment, followed by age, ECOG PS and other chemotherapy in predicting PFS, and eribulin, other chemotherapy, ECOG PS and age in predicting OS (Fig.  5 ).

Hypertension, proteinuria, and hand-foot syndrome are the primary side effects of anti-angiogenic medications which can be managed by adjusting the dosage. In the apatinib combination chemotherapy group, the most common grade 3/4 haematological toxic reactions were thrombocytopenia (2.9%) and neutropenia (8.8%). Notably, the incidence of neutropenia was higher in the chemotherapy group (26.8%) than in the apatinib combination chemotherapy group (8.8%) (Table  6 ). This difference is likely due to the higher proportion of patients in the chemotherapy group receiving Paclitaxel and/or Docetaxel (35.1% in the chemotherapy alone group compared to 5.9% in the apatinib combination chemotherapy group, p = 0.002) (Table  2 ).The most prevalent non-hematologic toxicities were hand-foot syndrome (35.3%), proteinuria (26.5%), hypertension (61.8%), increased alanine aminotransferase (26.5%), and fatigue (35.3%). In terms of grade 3/4 non-hematologic toxicities, hand-foot syndrome (2.9%) and hypertension (5.9%) were the most commonly observed, nevertheless, fatigue, increased alanine aminotransferase, or proteinuria were not seen(see Tables  5 and 6 ). According to the phase IIb study of apatinib in TNBC, hand-foot syndrome (17.0%), proteinuria (13.6%), hypertension (11.9%), increased alanine aminotransferase (11.9%), and fatigue (3.4%) were the most frequent grade 3/4 non-hematologic effects 14 . In contrast to the recommended single-agent apatinib dose of500 mg/day, our study shows that low-dose apatinib (250 mg/day) administered alongside chemotherapy significantly reduces grade 3/4 non-hematologic toxicities such as hand-foot syndrome, proteinuria, and hypertension, improving long-term medication compliance. Patients with hypertension should regularly monitor their blood pressure and take prescribed medication. Those with grade 3 or 4 hypertension should cease taking apatinib and adjust their treatment plan based on their blood pressure readings and symptoms. Additionally, if severe hypertension recurs after adjusting the dose of apatinib or prescribing medication for high blood pressure, apatinib use should be discontinued. To alleviate hand-foot syndrome, it may be appropriate to administer vaseline ointment topically and celecoxib for pain management. Temporary cessation of apatinib is necessary along with symptomatic treatment for cases of grade 3/4. Additionally, discontinuation of apatinib is warranted due to the worsening of hand-foot syndrome following dose adjustment and medication use. The study showed that most non-haematological adverse events (AEs) were of mild-to-moderate severity and were manageable with supportive treatment and/or dose modification. Low-dose apatinib enhances long-term drug adherence.

The comparative study shows that even administering low-dose apatinib (250 mg/day) in combination with chemotherapy may be superior to chemotherapy alone, dramatically increasing both short- and long-term efficacy. Additionally, evidence suggests that using the lower dose of apatinib (250 mg/day) in combination with chemotherapy could be more effective than utilizing the higher dose of single-agent apatinib (500 mg/day), while also reducing non-hematologic side effects such as proteinuria, hand-foot syndrome, and hypertension and improving long-term medication adherence. These findings have important implications for the management of metastatic TNBC and require further research to establish their clinical relevance.

Although our study could not stratify the population with a PD-L1 advantage because of the small number of patients receiving PD-1 inhibitors, we aimed to explore whether combining apatinib with a PD-1 inhibitor treatment mode could raise the efficacy. Earlier studies have shown the synergistic mechanism and therapeutic benefits of combining apatinib with a PD-1 inhibitor. Based on previous studies, apatinib has the potential to improve the efficacy of camrelizumab, a PD-1 inhibitor, through a synergistic effect. In a mouse model, apatinib was found to enhance the sensitivity of PD-1 inhibitors by normalising blood vessels, increasing CD8 + T cell and B cell infiltration, and boosting PD-1 expression on immune cells, thus increasing its effectiveness [ 17 ]. A phase II study has demonstrated the synergistic impact of apatinib and camrelizumab on advanced TNBC. Patients with metastatic TNBC who had undergone up to the second-line chemotherapy were treated with camrelizumab (200 mg every three weeks) and apatinib (250 mg/day).The study determined an ORR of up to 43.3% and a median PFS of 3.7 months [ 18 ]. In a further phase II trial, chemotherapy was combined in a bid to enhance the effect. The approach involved the administration of camrelizumab, a 200 mg dose on day 1, as well as low-dose apatinib, 250 mg daily, while eribulin was given at 1.4 mg/m2 on days 1 and 8 every 21 days. The trial was aimed at 46 previously treated advanced TNBC patients, revealing significant benefits with an ORR of 37.0% and a DCR of 87.0%. Despite the median treatment line being the third line, the median PFS was notably long, amounting to 8.1 months, which was better than the standard treatment typically offered to advanced TNBC patients later in the treatment cycle. The triple combination of camrelizumab, apatinib, and eribulin has been reported to have potential anti-tumor activity in patients resistant to prior immune checkpoint inhibitors (ICIs). This study evaluated 8 patients (17.4%) who had received prior chemotherapy and PD-1/PD-L1 inhibitors, with 2 achieving partial remission (PR) and 5 maintaining stable disease (SD) [ 19 ].

Our study’s results revealed the therapeutic advantages of utilizing low-dose apatinib in conjunction with chemotherapy. Notably, our retrospective study used real-world data that may not have undergone the rigor of randomized controlled trials. Furthermore, the lengthy follow-up period, small sample size, and lack of essential clinical criteria such as combination therapy imply that some bias may be present. According to earlier research,pVEGFR2 in breast cancer tissue is reported to be higher compared to normal controls [ 20 ], the increased activated protein form of tumor cell pVEGFR2 expression (but not the total VEGFR2),was associated with a significantly improved CBR(81.8 vs. 38.5% among pVEGFR2 higher vs. lower expression patients) and PFS (6.44 vs. 1.97 months).The potential correlation linking greater expression of pVEGFR2 in tumour tissue with apatinib efficacy is significant and requires urgent confirmation in forthcoming studies of TNBC treated with apatinib or similar pVEGFR2-targeting TKI [ 14 ]. Unfortunately, we were unable to obtain tumor samples from other hospitals, so we cannot determine the difference in overall pVEGFR2 between the apatinib and non-apatinib groups. Nevertheless, other research shows that apatinib enhances the anti-tumor effect of PTX on TNBC cells through the molecular pathway of PI3K/p65/Bcl-xl. This combination of apatinib and microtubule inhibitor shows promise in the treatment of TNBC [ 21 ]. In our research, after PSM, almost 40% of patients in the apatinib group received microtubule inhibitors, and the percentage of patients who received microtubule inhibitors (including Paclitaxel/Docetaxel, nab-paclitaxel, eribulin) was higher than that of the chemotherapy alone group, which may contribute to the higher efficacy observed in the apatinib group. We are presently undertaking an exploratory clinical study of apatinib mesylate, in combination with nab-paclitaxel, for the second-line treatment of advanced triple-negative breast cancer. This study is investigator-initiated and has been approved by both the Ethics Committee of Fujian Cancer Hospital (ethic code: K2021-122-01) and the Chinese Ethics Committee of Registering Clinical Trials (ethic code: CHiECRCT20210338). We will evaluate the effectiveness of combining apatinib and nab-paclitaxel in the treatment of triple-negative breast cancer tumors transplanted in mice. The objective is to reinforce the effectiveness of apatinib in combination with chemotherapy for salvage therapy in triple-negative breast cancer and investigate the correlation between pVEGFR2 expression in tumor tissue and response prediction. Therefore, to comprehensively examine the potential advantages of this approach, forthcoming clinical randomized controlled trials should strive to amplify the sample size whilst considering other parameters including pVEGFR2.

Our research reveals that combining low-dose apatinib (250 mg per day) with chemotherapy yields a superior Disease Control Rate (DCR) benefit compared to chemotherapy alone, accompanied by favorable Progression-Free Survival (PFS) and Overall Survival (OS) advantages. Moreover, the administration of low-dose apatinib significantly reduces the incidence of hypertension, proteinuria, and hand-foot syndrome. The majority of non-hematological adverse events are of mild to moderate severity and can be managed through supportive measures or dosage adjustments. Notably, this reduced apatinib dosage demonstrates increased treatment adherence compared to the previously recommended 500 mg/day dosage in prior studies. Consequently, a lower dose of apatinib (250 mg/day) combined with chemotherapy may be as effective as the recommended 500 mg/day dose, warranting further exploration of this combined treatment approach. Additionally, it is crucial to investigate which chemotherapeutic agents exhibit superior synergistic effects when used with apatinib and to verify whether tumor pVEGFR2 expression can serve as an efficacy predictor for apatinib chemotherapy.

Data availability

The datasets used and/or analyzed in the study are available from the corresponding author on reasonable request.

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25 march 2024.

A Correction to this paper has been published: https://doi.org/10.1186/s12885-024-12150-8

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Acknowledgements

The authors acknowledge the contribution of all participants in the study and thank them for their time and effort.

This study was supported by Wu JiePing Medical Foundation Special Fund for Clinical Research [grant fund number: 320.6750.2021-14-6], Natural Science Foundation of Fujian Province [grant fund number: 2023J011275, 2021J01440], and Fujian Provincial Clinlical Research Center for Cancer Radiotherapy and Immunotherapy [grant/award number: 2020Y2012].

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Weiwei Huang and Chenxi Wang contributed equally to this work.

Authors and Affiliations

Department of Medical Oncology, Fujian Medical University Union Hospital, No.29, Xinquan Road, Gulou District, Fuzhou, Fujian province, 350001, China

Weiwei Huang & Xiaoyan Lin

Department of Medical Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No.91, Fuma Road, Jin’an District, Fuzhou, Fujian province, 350014, China

Weiwei Huang, Jian Liu, Lili Wang, Fan Wu, Xinhua Chen, Nani Li, Yi Hong & Mulan Chen

Fujian Key Laboratory of Translational Cancer Medicine, Fujian Cancer Hospotial, No.91, Fuma Road, Jin’an District, Fuzhou, Fujian province, 350014, China

Fujian Key Laboratory of Innate Immune Biology, Biomedical Research Center of South China, Fujian Normal University Qishan Campus, College Town, Fuzhou, Fujian Province, 350117, PR China

Chenxi Wang, Yangkun Shen & Qi Chen

Department of Breast Surgical Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No. 91, Fuma Road, Jin’an District, Fuzhou, Fujian province, 350014, China

Zhijian Huang

Laboratory of Immuno-Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No.91, Fuma Road, Jin’an District, Fuzhou, Fujian province, 350014, China

Jieyu Li & Chuanzhong Huang

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Conceptualization, WW.H., CX.W. and XY.L.; methodology, Q.C., YK.S. and CX.W.; software, YK.S. and CX.W.; validation, ZJ.H., J.L. and XY.L.; formal analysis, LL.W., F.W. and Xh.C.; investigation, NN.L., Y.H. and ML.C.; resources, JY.L. and CZ.H.; data curation, Jy.L. and CZ.H.; writing—original draft preparation, WW.H.; writing—review and editing, WW.H. and XY.L.; visualization, CX.W.; supervision, WW.H.; project administration, WW.H. and XY.L; funding acquisition, WW.H. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Xiaoyan Lin .

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Huang, W., Wang, C., Shen, Y. et al. A real-world study of the effectiveness and safety of apatinib-based regimens in metastatic triple-negative breast cancer. BMC Cancer 24 , 39 (2024). https://doi.org/10.1186/s12885-023-11790-6

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CASE REPORT article

Case report: a case study documenting the activity of atezolizumab in a pd-l1-negative triple-negative breast cancer.

• 1 Translational Genomics and Targeted Therapies in Solid Tumors, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
• 2 Department of Medical Oncology, Hospital Clínic of Barcelona, Barcelona, Spain
• 3 Cancer Genomics Group, Vall d’Hebron Institute of Oncology, Barcelona, Spain
• 4 Department of Oncology and Hematology, Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain
• 5 Department of Pathology, Hospital Clínic de Barcelona, Barcelona, Spain
• 6 Department of Pharmacy, Hospital Clínic of Barcelona, Barcelona, Spain
• 7 Department of Radiology, Hospital Clínic of Barcelona, Barcelona, Spain
• 8 Molecular Biology Core, Hospital Clinic of Barcelona, Barcelona, Spain
• 9 Vall d’Hebron University Hospital and Vall d’Hebron Institute of Oncology (VHIO), Medical Oncology Service, Barcelona, Spain
• 10 SOLTI Cooperative Group, Barcelona, Spain
• 11 Department of Oncology, Institut Oncològic Baselga (IOB) Institute of Oncology, Quironsalud Group, Barcelona, Spain
• 12 Department of Medicine, University of Barcelona, Barcelona, Spain

The immune checkpoint inhibitor atezolizumab is approved for PD-L1-positive triple-negative breast cancer (TNBC). However, no activity of atezolizumab in PD-L1-negative TNBC has been reported to date. Here, we present the case study of a woman with TNBC with low tumor infiltrating lymphocytes and PD-L1-negative disease, which achieved a significant response to atezolizumab monotherapy and durable response after the combination of atezolizumab and nab-paclitaxel. The comprehensive genomic analysis that we performed in her tumor and plasma samples revealed high tumor mutational burden (TMB), presence of the APOBEC genetic signatures, high expression of the tumor inflammation signature, and a HER2-enriched subtype by the PAM50 assay. Some of these biomarkers have been shown to independently predict response to immunotherapy in other tumors and may explain the durable response in our patient. Our work warrants further translational studies to identify biomarkers of response to immune checkpoint inhibitors in TNBC beyond PD-L1 expression and to better select patients that will benefit from immunotherapy.

Introduction

Triple-negative breast cancer (TNBC) lacks expression of estrogen receptor (ER), progesterone receptor (PR), and the human epidermal growth factor receptor 2 (HER2); accounts for 15%–20% of all breast cancers; affects young women; and is highly aggressive. While targeted therapies are available for ER-positive (ER+) and HER2-positive (HER2+) breast cancer, chemotherapy remains the standard of care for TNBC. Among the different subtypes, TNBC is the most immunogenic and has the highest median number of tumor-infiltrating lymphocytes (TILs), PD-L1 expression, and tumor mutational burden (TMB), all of which are associated with immune activity ( 1 ). In this context, immunotherapy with atezolizumab, an anti-PD-L1 drug antibody, has been approved for PD-L1-positive (PD-L1+) (i.e., ≥1% PD-L1+ tumor-infiltrating immune cells) advanced TNBC in combination with nab-paclitaxel ( 2 ). On the other side, activity of pembrolizumab monotherapy in patients with pre-treated metastatic breast cancer with high TMB has recently been reported ( 3 ). However, no activity of immune checkpoint inhibitors in PD-L1-negative TNBC has been observed to date, and the predictive value of TMB beyond PD-L1 expression is still unknown.

Here, we describe a case of a woman with an initial diagnosis of HER2+ localized tumor treated with curative therapy that relapsed 9 years later being an ER+/HER2-negative metastatic breast cancer. She progressed to first-line endocrine therapy and palbociclib, a CDK4/6 inhibitor, and whose tumor became then triple-negative. Molecular characterization of her metastatic TNBC observed absence of PD-L1 expression, but high TMB, presence of the Apolipoprotein B mRNA Editing Catalytic Polypeptide-like (APOBEC) genetic signatures, high expression of the tumor inflammation signature (TIS), and a HER2-enriched subtype by the PAM50 assay. Based on this tumor profile, Hospital Clinic Molecular Tumor Board indicated one cycle of atezolizumab followed by atezolizumab in combination with nab-paclitaxel. Plasma circulating tumor DNA (ctDNA) and radiological imaging were used to assess treatment efficacy. The patient presented in this report has given her consent for publication.

Case Presentation

A 44-year-old white Spanish woman with no significant familiar or medical history was initially diagnosed with a left breast cancer in 2008 (pT2N3M0). The pathology report revealed an ER+, PR-positive, and HER2+ invasive carcinoma of the breast. She underwent surgery in October 2008 and received adjuvant anti-HER2-based chemotherapy, followed by locoregional radiotherapy and endocrine therapy.

In April 2018, the patient was diagnosed with right supraclavicular and axillary positive lymph nodes (17 mm and 3 mm) by ultrasound. Bone metastasis was detected by PET/CT scan. A core biopsy of the right supraclavicular lymph nodes was performed and revealed an ER+ and HER2-negative invasive lobular carcinoma. In this tumor biopsy, an amplicon-based DNA sequencing panel of pan-cancer genes showed the presence of a PIK3CA E545K (18% mutant allelic frequency [MAF]) and 726F (16% MAF) somatic mutations. As a first-line treatment, she received fulvestrant and palbociclib (125 mg daily, 3 weeks on, 1 week off) until May 2019 (13 months of treatment), when bone and lymph node progressions were observed.

Two new biopsies of the right breast and axillary node were performed and revealed a TNBC lobular carcinoma. In the breast lesion, the tumor had a Ki67 of 18% and less than 1% TILs and was PD-L1-negative by immunohistochemistry (Ventana PD-L1 antibody clone SP142). Intrinsic subtype by PAM50/Prosigna ® revealed a HER2-enriched subtype with low levels of ERBB2 mRNA. A DNA sequencing panel of 431 genes showed PIK3CA E545K and TP53 Q331* mutations, a high TMB of 38.5 mutations per megabase (mut/Mb) and an APOBEC-mutational profile, including signatures S2 and S13. Guardant360 74-gene panel confirmed the presence of multiple somatic mutations, including PIK3CA E545K mutation with a variant allele fraction of 12.2%.

Based on these results, the clinical case was presented at our weekly multidisciplinary Tumor Board at Hospital Clinic of Barcelona. Since activity of immunotherapy in patients with breast cancer with high TMB has been reported ( 3 ), a regimen of single-agent immunotherapy combined with chemotherapy was planned. More specifically, in July 2019, the patient received one dose of 1200 mg atezolizumab monotherapy and after 3 weeks continued with 1200 mg atezolizumab (day 1) plus weekly 100 mg/m 2 nab-paclitaxel. In August 2021 (24 months of treatment), the patient continues on treatment presenting a maintained partial response and an excellent performance status. The treatment history is summarized in Figure 1A .

Figure 1 Patient treatment timeline and DNA alterations. (A) Patient treatment timeline. (B) Mutant Allelic Frequency (MAF; %) in T1 (sample of 2008), T2 (sample of 2018), and T2-PD (sample of 2019) determined using the VHIO-300 panel. Variants classified as pathogenic or likely pathogenic are highlighted in bold; variants matching APOBEC DNA-sequence signature are underlined. (C) Overlap of somatic mutations between T1, T2, and T2-PD using the VHIO-300 panel and whole-exome sequencing (WES). (D) TMB expressed as mutations/megabase in T1, T2, and T2-PD using the VHIO-300 panel and WES. (E) COSMIC mutational signatures of age, APOBEC defect (APOBEC), defective mismatch repair/microsatellite instability (dMMR/MSI) reflected as small insertions and deletions (INDELs), ultraviolet light (UV), polymerase E defect (POLE), and aflotoxin effect in T1, T2, and T2-PD determined by WES. (F) MAF distribution for APOBEC-related and other mutations in T1, T2, and T2-PD determined by WES.

Genomic Analyses

Analysis of the DNA from the three tumor specimens and a buffy coat blood sample by next-generation sequencing using the VHIO-300 capture-based panel of 431 pan-cancer related genes and whole-exome sequencing (WES) revealed an independent genetic origin of samples from 2008 and 2018, while the tumor from 2019 clearly was a progression (PD) of the 2018 lesion. Thus, samples were relabeled as T1 (breast sample, 2008), T2 (lymph node sample, 2018), and T2-PD (breast sample, 2019). Genomic analyses revealed a completely different mutational profile of T1 versus T2 and T2-PD; the vast majority of mutations in T2 were also present in T2-PD, while none of them were present in T1, and 34 somatic variants were found exclusively in T2-PD (e.g., RB1 S567* and a nonsense NF1 mutation in residue Q315*) ( Figures 1B, C ). In addition, TMB was low in T1 compared to T2 and T2-PD ( Figure 1D ). Analysis of COSMIC mutational signatures from the WES results showed a dominant pattern related to age in T1, while the high TMB in T2 and T2-PD was linked to a sequence context preference of cytosine mutations caused by APOBEC enzymes ( 4 ) ( Figure 1E ). Finally, a study of MAF distribution showed a clonal peak for APOBEC-related mutations in T2, with increased average MAF % in T2-PD, plus a second peak of subclonal mutations also linked to APOBEC defect in the T2-PD ( Figure 1F ).

RNA from T2 and T2-PD were analyzed at the nCounter Breast Cancer 360 Panel. ESR1 expression was decreased in T2-PD compared to T2, consistent with the immunohistochemistry results. Both T2 and T2-PD were classified as HER2-enriched and showed high expression of immune signatures (i.e., MHC-II, IFN-gamma, TIS, antigen presenting machinery) ( Figure 2A ). PD-L1 and PD1 mRNA expression was low.

Figure 2 Gene expression and molecular and clinical response to atezolizumab and nab-paclitaxel. (A) The Wheel Plots depict the relative expression of each signature for T2 and T2-PD samples determined using the Breast Cancer 360 nCounter-based gene expression panel. Signatures are grouped based on the biological process in which they belong. The Luminal A, Luminal B, HER2-enriched, and Basal-like subtype correlation scores are shown as a radial arc. Signature scores (0–16, low to high) are represented as radial projections. (B) Guardant360 Tumor Response Map showing the highest variant allele fraction (%) and MAF (%) assessed in ctDNA using Guardant360 results before treatment, after 3 weeks of atezolizumab monotherapy, and after combining atezolizumab and nab-paclitaxel. (C) CT scan. Red arrows indicate lesions on the soft tissue of the chest wall (top) and a mammary node (middle) and bone (bottom) during treatment.

Since ctDNA can be a surrogate of response to therapy and long-term outcome ( 5 ), liquid biopsies were collected before atezolizumab, after 3 weeks of atezolizumab monotherapy and after 3 weeks of atezolizumab plus nab-paclitaxel. Plasma samples were sequenced using the standardized Guardant360 assay. Mutations in 37 genes were identified in the plasma sample before immunotherapy and highest variant allele frequency (VAF) was 12.2%. After atezolizumab monotherapy, the only detectable mutation was PDGFRA D691E (VAF = 0.1%). After 1 month of atezolizumab plus nab-paclitaxel, the only mutation detected was ALK R1061Q (VAF = 0.5%) ( Figure 2B ), and after 2 months, a chest CT scan confirmed a partial response as observed on the soft tissue of the chest wall and a mammary node, and in December 2020, the patient continued in clinical and radiological response ( Figure 2C ). Bone metastasis was followed up by CT scan every 3 months, with stable disease as the best response.

Acquisition of genomic alterations and changes in gene expression profiles may lead to treatment failure and disease progression. Here, we report a patient diagnosed of ER+/HER2-negative metastatic breast cancer who progressed to first-line endocrine therapy in combination with CDK4/6 inhibition, and the progressive disease lost ER expression and became TNBC; it was PD-L1-negative and benefited from atezolizumab in combination with nab-paclitaxel. Although our study cannot identify the main cause of the patient’s response to atezolizumab alone and in combination with nab-paclitaxel, the extensive molecular characterization performed could provide clues about the features associated with immunotherapy benefit in PD-L1-negative TNBC.

The genomic analysis performed revealed that the pre-treatment ER+/HER2-negative tumors and the progression tumor samples after endocrine therapy and palbociclib had the following features: (1) high TMB, (2) presence of the APOBEC genetic signatures, (3) HER2-enriched, and (4) high expression of immune gene signatures such as TIS or interferon-gamma but not PD-L1 or PD1 mRNA. However, some molecular features were different between the two time points. For example, NF1 and RB1 mutations and lower expression of ER were identified in the progression sample, which also had a higher TMB score. Consistently, loss of ER and acquisition of NF1 mutations have been associated with resistance to endocrine therapy ( 6 ), while acquisition of RB1 mutations, APOBEC signatures, and the HER2-enriched subtype has been associated with resistance to palbociclib ( 7 , 8 ). Moreover, the APOBEC genetic signatures have been previously associated with the HER2-enriched subtype and high TILs ( 9 , 10 ). Indeed, APOBEC genetic signatures contribute to the acquisition of subclonal mutations, leading to genomic instability and potential neoantigens expression, which could induce immune response ( 11 ). The genetic origin of the APOBEC signatures in this case remains unknown. Among the possible explanations, we excluded germline loss of APOBEC3B ( 12 ). Unfortunately, we were not able to study the expression levels of APOBEC3B ( 13 ).

Currently, three biomarkers have been clinically validated as predictors of response to immune checkpoint blockade in TNBC [i.e., PD-L1 ( 2 )] and across cancer types (i.e., TMB ( 3 , 14 ) and mismatch repair deficiency ( 15 ). Indeed, the immunotherapy drug pembrolizumab for the treatment of patients with TMB-high tumors is approved by the Food and Drug Administration (FDA) ( 14 ). In TNBC, a modest benefit of immune checkpoint blockade has been observed in patients who are PD-L1-positive ( 2 ), which has led to the approval of the combination of atezolizumab plus nab-paclitaxel in PD-L1+ TNBC by the FDA. Other suggested predictive factors of response to immune checkpoint blockade include the TIS score ( 16 ), the APC signature ( 17 ), PD1 mRNA expression ( 18 ), and a T cell–inflamed gene expression profile ( 19 ). Some of these biomarkers have been shown to independently predict response to immunotherapy and may capture distinct features of neoantigenicity. Therefore, composite biomarkers may help better identify those patients that benefit to immune checkpoint inhibition and warrant further translational studies to improve patient selection.

To conclude, we present the case study of a TNBC with low TILs and PD-L1-negative disease, which achieved a significant response to atezolizumab monotherapy and durable response after the combination of atezolizumab and nab-paclitaxel, possibly explained by the APOBEC signatures, the high TMB, the high TIS score, and the HER2-enriched subtype, or the combination of several of these features. Moreover, the addition of chemotherapy could have helped turn the cold tumor microenvironment into hot, recruiting more T cells and improving response to atezolizumab ( 20 ). After 24 months, the patient continues in clinical and radiological response.

Patient Perspective

After progression to first-line treatment (palbociclib + ET), the patient is really satisfied with a 24-month response to a well-tolerated scheme of atezolizumab plus weekly nab-paclitaxel with just alopecia G1 (she is using a cold cap to prevent it) and hepatotoxicity G2 that has been recovered just to delay treatment 1–2 weeks three times during these 2 years. She maintains an active life with ECOG 0.

Data Availability Statement

The original contributions presented in the study are included in the article. Further inquiries can be directed to the corresponding authors.

Ethics Statement

The studies involving human participants were reviewed and approved by Comité de Ética de la Investigación con medicamentos del Hospital Clínic de Barcelona. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

Author Contributions

Experimental study design: FB-M, MiS, AP, and AV. Provision of study materials or patients: FB-M, MiS, NC, DM, BG-F, ES, LG, EC, JG-C, MaS, DS, VP, CS, MM, AP, and AV. Data analysis and interpretation: FB-M, MiS, NC, MM, AP, and AV. Writing of the manuscript FB-M, MiS, AP, and AV. Revision of the manuscript: FB-M, MiS, NC, DM, BG-F, ES, LG, EC, JG-C, MaS, DS, VP, P-J, CS, MM, AP, and AV. Supervision: AP and AV. All authors contributed to the article and approved the submitted version.

This study has received funding from Instituto de Salud Carlos III—PI19/01846 (to AP), Breast Cancer Now—2018NOVPCC1294 (to AP), Breast Cancer Research Foundation-AACR Career Development Awards for Translational Breast Cancer Research 19-20-26-PRAT (to AP), Fundació La Marató TV3 201935-30 (to AP), the European Union’s Horizon 2020 research and innovation programme H2020-SC1-BHC-2018-2020 (to AP), Asociación de Cáncer de Mama Metastásico CMM_CHIARAG19_001 (to AP), Pas a Pas (to AP), Save the Mama (to AP), Fundación Científica Asociación Española Contra el Cáncer AECC_Postdoctoral17-1062 (to FB-M) and INVES19056SANS (to MiS), FERO-ghd 2020 breast cancer award (MS), and Generalitat de Catalunya Peris PhD4MD 2019 SLT008/18/00122 (to NC).

Conflict of Interest

Potential conflicts of interest are the following: AP reports consulting fees from Nanostring Technologies, Roche, Pfizer, Novartis, AstraZeneca, Foundation Medicine, Guardant Health, and Daiichi Sankyo outside the submitted work. AV reports consulting fees from Sysmex, Novartis, Merck, Bristol Meyers Squibb, Guardant Health, and Incyte; research funding from Bristol Meyers Squibb; and royalties from Ferrer outside the submitted work. VP has received fees as consultant, participated in advisory boards, or received travel grants from Sysmex, Roche, MSD, AstraZeneca, Bayer, and Exact Sciences outside the submitted work. CS has declared personal fees as consultant and advisory board or travel grants of AstraZeneca, Daiichi Sankyo, Eisai, Exact Sciences, Exeter Pharma, F. Hoffmann–La Roche Ltd, MediTech, Merck Sharp & Dohme, Novartis, Pfizer, Philips, Piere Fabre, Puma, Roche Farma, Sanofi-Aventis, SeaGen, and Zymeworks and institutional financial interests from AstraZeneca, Daiichi Sankyo, Eli Lilly and Company, Genentech, Immunomedics, Macrogenics, Merck, Sharp and Dhome España S.A., Novartis, Pfizer, Piqur Therapeutics, Puma, Roche, Synthon, and Zenith Pharma. CS and AP are Board Members of SOLTI Cooperative Group and are employed by Institut Oncològic Baselga (IOB), Quironsalud Group.

The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: immunotherapy, breast cancer, biomarkers, ctDNA, case report

Citation: Brasó-Maristany F, Sansó M, Chic N, Martínez D, González-Farré B, Sanfeliu E, Ghiglione L, Carcelero E, Garcia-Corbacho J, Sánchez M, Soy D, Jares P, Peg V, Saura C, Muñoz M, Prat A and Vivancos A (2021) Case Report: A Case Study Documenting the Activity of Atezolizumab in a PD-L1-Negative Triple-Negative Breast Cancer. Front. Oncol. 11:710596. doi: 10.3389/fonc.2021.710596

Received: 16 May 2021; Accepted: 31 August 2021; Published: 20 September 2021.

Reviewed by:

Copyright © 2021 Brasó-Maristany, Sansó, Chic, Martínez, González-Farré, Sanfeliu, Ghiglione, Carcelero, Garcia-Corbacho, Sánchez, Soy, Jares, Peg, Saura, Muñoz, Prat and Vivancos. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Aleix Prat, [email protected] ; Ana Vivancos, [email protected]

† These authors have contributed equally to this work

‡ These authors share senior authorship

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Case Study: Metastatic Triple-Negative Breast Cancer

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In the final case study of the discussion, moderator Adam M. Brufsky, MD, PhD, describes a 58 year-old Caucasian woman with a 4 cm infiltrating ductal carcinoma in her right breast. Following a core biopsy, the primary tumor was found to be ER, PR, and HER2-negative by IHC and FISH. The patient received four cycles of adjuvant Adriamycin plus cyclophosphamide followed by 12 cycles of weekly paclitaxel.

After approximately 14 months, the patient developed shortness of breath and multiple bilateral pulmonary nodules were found by PET-CT scan, the largest of which was approximately 2 cm in diameter. One of these nodules was biopsied and revealed triple-negative histology consistent with the primary tumor, Brufsky notes.

This patient is at high-risk for brain metastases, believes Andrew D. Seidman, MD. At this point, regardless of symptoms, Seidman recommends conducting a brain MRI. Unfortunately, there is not a hard set standard of care for patients with triple-negative breast cancer (TNBC), although several agents are under investigation, including PARP inhibitors, platinum-based agents, and angiogenesis inhibitors. At this point, the patient may benefit from the re-administration of a taxane, believes Seidman.

Clinical data from the TBCRC009 trial provides support for the idea that patients with basal-like TNBC benefit from platinum-based treatment, believes Joyce A. O'Shaughnessy, MD. In this study, patients received single-agent cisplatin or carboplatin with a secondary mutational analysis looking at BRCA mutations. All patients on the trial were long-term survivors who had been off therapy until being treated in the first-line metastatic setting in the trial. In addition to these findings, O'Shaughnessy notes, observationally, a small group of patients with TNBC appear to experience long remissions when treated with platinum-based therapy.

A combination of gemcitabine and carboplatin is commonly utilized to treat TNBC but has yet to demonstrate superiority to other therapies in clinical trials, believes Seidman. Despite this, Rugo believes that patients are more likely to respond to the gemcitabine and carboplatin combination than a taxane. However, the TBCRC009 trial suggests that single-agent platinum-based therapy may be sufficient.

Inavolisib Plus Palbociclib/Fulvestrant Earns FDA Priority Review for Advanced HR+/HER2–, PIK3CA+ Breast Cancer

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Inavolisib Regimen Wins FDA Priority Review for PIK3CA Breast Cancer

3D rendering of tumor in breast tissue: © peterschreiber.media - stock.adobe.com

• The FDA has granted priority review to the new drug application (NDA) of inavolisib (GDC-0077) plus palbociclib (Ibrance) and fulvestrant for the treatment of hormone receptor (HR)-positive, HER2-negative, PIK3CA-mutated breast cancer.
• · The designation is supported by data from the phase 3 INAVO120 trial (NCT04191499).
• · The Prescription Drug User Fee Act (PDUFA) target action date is November 27, 2024.

The NDA of inavolisib, an investigational, oral treatment, in combination with palbociclib and fulvestrant for the treatment of patients with HR-positive, HER2-negative breast cancer with a PIK3CA mutation has been granted priority review by the FDA. A PDUFA target action date of November 27, 2024, has been set. 1

The priority review designation directs more resources and attention to applications for drugs that would provide significant improvements to the safety or effectiveness of treatments. Roche is also filing submissions with other global health authorities.

The PIK3CA mutation occurs in approximately 40% of HR-positive metastatic breast cancers, highlighting the need for a targeted therapy.

“The addition of inavolisib to standard of care treatment significantly delayed disease progression in the first-line setting and has the potential to extend survival for people with metastatic breast cancers that harbor  PIK3CA  mutations,” said Levi Garraway, MD, PhD, chief medical officer and head of global product development at Roche, in a press release. “We welcome the FDA’s priority review designation for inavolisib, which underscores the urgency to bring this potential best-in-class treatment option to patients as quickly as possible.”

The priority review is supported by findings from the phase 3 INAVO120 study. In the study, inavolisib plus palbociclib and fulvestrant reduced the risk of disease progression or death by 57% vs palbociclib and fulvestrant alone, delivering a progression-free survival (PFS) of 15.0 months vs 7.3 months, respectively (HR, 0.43; 95% CI, 0.32-0.59; P <.0001). While overall survival (OS) data were not mature at the time of analysis, a positive trend was observed (stratified HR, 0.64; 95% CI, 0.43-0.97;  P  =.0338), and follow-up for OS will continue.

On May 21, 2024, the FDA granted a breakthrough therapy designation to the regimen in this intent-to-treat population.

About INAVO120

The phase 3, randomized, double-blind, placebo-controlled INAVO120 study enrolled 325 patients with  PIK3CA -mutant, HR-positive, HER2 negative, locally advanced or metastatic breast cancer who experienced disease progression during or within 12 months of completing adjuvant endocrine therapy. 2

The study’s primary end point is PFS, and secondary end points include objective response rate, best overall response rate, duration of response, clinical benefit rate, time to deterioration (TTD) in pain, TTD in physical function, TTD in role function, TTD in global health status, and incidence of adverse events.

Patients were randomized to receive inavolisib or placebo on days 1 to 28 in combination with palbociclib on days 1 to 21 of a 28-day cycle plus fulvestrant every 4 weeks.

Patients with measurable disease per RECIST v1.1, an ECOG performance status of 0 or 1, a life expectancy of at least 6 months, and adequate hematologic and organ function were eligible for participation. Those with metaplastic breast cancer, history of leptomeningeal disease or carcinomatous meningitis, known or untreated active central nervous system metastases, who received prior systemic therapy for metastatic breast cancer, or who are pregnant or breastfeeding were not eligible for study enrollment.

The study has an anticipated completion date of September 30, 2030.

REFERENCES:

1. fda grants priority review to roche’s inavolisib for advanced hormone receptor-positive, her2-negative breast cancer with a pik3ca mutation. news release. roche. may 29, 2024. accessed may 29, 2024. https://tinyurl.com/yhrfrccw, 2. a study evaluating the efficacy and safety of inavolisib + palbociclib + fulvestrant vs placebo + palbociclib + fulvestrant in patients with  pik3ca -mutant, hormone receptor-positive, her2-negative, locally advanced or metastatic breast cancer (inavo120). clinicaltrials.gov. updated april 26, 2024. accessed may 29, 2024.  https://clinicaltrials.gov/study/nct04191499.

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Quantitative assessment of the immune microenvironment in African American Triple Negative Breast Cancer: a case-control study

Affiliations.

• 1 Department of Pathology, Yale University School of Medicine, 310 Cedar Street, BML 116, P.O. Box 208023, New Haven, CT, 06520-8023, USA.
• 2 Genetics Branch, National Cancer Institute (NCI), National Institute of Health (NIH), Bethesda, MD, USA.
• 3 Department of Internal Medicine, Section of Medical Oncology, Yale School of Medicine, New Haven, CT, USA.
• 4 Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA.
• 5 Department of Surgery, Yale School of Medicine, New Haven, CT, USA.
• 6 Department of Pathology, Yale University School of Medicine, 310 Cedar Street, BML 116, P.O. Box 208023, New Haven, CT, 06520-8023, USA. [email protected].
• 7 Department of Internal Medicine, Section of Medical Oncology, Yale School of Medicine, New Haven, CT, USA. [email protected].
• 8 Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA. [email protected].
• PMID: 34906209
• PMCID: PMC8670126
• DOI: 10.1186/s13058-021-01493-w

Purpose: Triple negative breast cancer (TNBC) is more common in African American (AA) than Non-AA (NAA) population. We hypothesize that tumor microenvironment (TME) contributes to this disparity. Here, we use multiplex quantitative immunofluorescence to characterize the expression of immunologic biomarkers in the TME in both populations.

Patients and methods: TNBC tumor resection specimen tissues from a 100-patient case: control cohort including 49 AA and 51 NAA were collected. TME markers including CD45, CD14, CD68, CD206, CD4, CD8, CD20, CD3, Ki67, GzB, Thy1, FAP, aSMA, CD34, Col4, VWF and PD-L1 we quantitatively assessed in every field of view. Mean expression levels were compared between cases and controls.

Results: Although no significant differences were detected in individual lymphoid and myeloid markers, we found that infiltration with CD45 + immune cells (p = 0.0102) was higher in TNBC in AA population. AA TNBC tumors also had significantly higher level of lymphocytic infiltration defined as CD45 + CD14 - cells (p = 0.0081). CD3 + T-cells in AA tumors expressed significantly higher levels of Ki67 (0.0066) compared to NAAs, indicating that a higher percentage of AA tumors contained activated T-cells. All other biomarkers showed no significant differences between the AA and NAA group.

Conclusions: While the TME in TNBC is rich in immune cells in both racial groups, there is a numerical increase in lymphoid infiltration in AA compared to NAA TNBC. Significantly, higher activated T cells seen in AA patients raises the possibility that there may be a subset of AA patients with improved response to immunotherapy.

Keywords: African American; Immune cells; Quantitative immunofluorescence; Triple-negative breast cancer; Tumor microenvironment.

© 2021. The Author(s).

Publication types

• Research Support, N.I.H., Extramural
• Research Support, Non-U.S. Gov't
• Biomarkers, Tumor
• Black or African American
• Case-Control Studies
• Triple Negative Breast Neoplasms* / pathology
• Tumor Microenvironment

Grants and funding

• R01 CA219647/CA/NCI NIH HHS/United States
• TL1 TR001864/TR/NCATS NIH HHS/United States
• UL1 TR001863/TR/NCATS NIH HHS/United States
• R01-CA219647/CA/NCI NIH HHS/United States

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• Published: 27 May 2024

A novel combinatorial approach using sulforaphane- and withaferin A-rich extracts for prevention of estrogen receptor-negative breast cancer through epigenetic and gut microbial mechanisms

• Mohammad Mijanur Rahman 1 ,
• Huixin Wu 1 , 2 &
• Trygve O. Tollefsbol 1 , 3 , 4 , 5 , 6 , 7  

Scientific Reports volume  14 , Article number:  12091 ( 2024 ) Cite this article

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• Breast cancer
• Cancer prevention
• Cancer therapy
• Microbial communities
• Epigenetics
• Molecular biology

Estrogen receptor-negative [ER(−)] mammary cancer is the most aggressive type of breast cancer (BC) with higher rate of metastasis and recurrence. In recent years, dietary prevention of BC with epigenetically active phytochemicals has received increased attention due to its feasibility, effectiveness, and ease of implementation. In this regard, combinatorial phytochemical intervention enables more efficacious BC inhibition by simultaneously targeting multiple tumorigenic pathways. We, therefore, focused on investigation of the effect of sulforaphane (SFN)-rich broccoli sprouts (BSp) and withaferin A (WA)-rich Ashwagandha (Ash) combination on BC prevention in estrogen receptor-negative [ER(−)] mammary cancer using transgenic mice. Our results indicated that combinatorial BSp + Ash treatment significantly reduced tumor incidence and tumor growth (~ 75%) as well as delayed (~ 21%) tumor latency when compared to the control treatment and combinatorial BSp + Ash treatment was statistically more effective in suppressing BC compared to single BSp or Ash intervention. At the molecular level, the BSp and Ash combination upregulated tumor suppressors (p53, p57) along with apoptosis associated proteins (BAX, PUMA) and BAX:BCL-2 ratio. Furthermore, our result indicated an expressional decline of epigenetic machinery HDAC1 and DNMT3A in mammary tumor tissue because of combinatorial treatment. Interestingly, we have reported multiple synergistic interactions between BSp and Ash that have impacted both tumor phenotype and molecular expression due to combinatorial BSp and Ash treatment. Our RNA-seq analysis results also demonstrated a transcriptome-wide expressional reshuffling of genes associated with multiple cell-signaling pathways, transcription factor activity and epigenetic regulations due to combined BSp and Ash administration. In addition, we discovered an alteration of gut microbial composition change because of combinatorial treatment. Overall, combinatorial BSp and Ash supplementation can prevent ER(−) BC through enhanced tumor suppression, apoptosis induction and transcriptome-wide reshuffling of gene expression possibly influencing multiple cell signaling pathways, epigenetic regulation and reshaping gut microbiota.

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Introduction.

Breast cancer (BC) is a global health burden for women's health. In the United States, BC was the second leading cause of cancer mortality with the highest incidence rate in women according to cancer statistics, 2023 1 . Among the types of BC, estrogen receptor-negative [ER(−)] triple negative/basal like (TNBC) BC is the most aggressive type, posing the highest threat to BC patients due to poor prognosis and a lack of targeted therapy 2 . Conventional therapeutic options against ER(−) BC often lead to undesirable short-term or long-term side effects, which has led to intensive investigation for safe and effective approaches for the prevention and treatment of BC 3 , 4 . Further, diet has been identified as a key factor explaining geographical and racial variations in BC incidence worldwide. Several epidemiological studies and meta-analyses also suggest a strong association of high fruit and vegetable consumption with an overall reduction in BC incidence 5 , 6 . Therefore, investigating dietary intervention for ER(−) BC at the molecular level constitutes an important scientific goal to explore novel and safe therapeutic as well as preventive strategies against BC.

Sulforaphane (SFN) is an isothiocyanate with potent histone deacetylase (HDAC) inhibitory activity and is enriched in cruciferous vegetables (e.g., broccoli sprouts, cabbage, cauliflower, kale). Previous studies from our laboratory demonstrated a profound anti-BC effect of SFN-rich broccoli sprouts (BSp) diet in vivo 7 . Interestingly, we have observed a stronger anti-BC effect in vivo and in vitro by combining SFN-rich BSp with other compounds with complementary epigenetic mechanism targeting ability 8 , 9 . It is worth mentioning that the anti-BC effect of a combinatorial BSp supplement was partially attributed to gut microbiota reshuffling, in addition to the direct targeting of epigenetic mechanisms 9 . On the other hand, withaferin A (WA) is a steroidal lactone abundant in Ashwagandha ( Withania somnifera ) and is known to be a DNA methyltransferases (DNMT) inhibitor 10 , 11 . WA exhibits potent anti-BC effect in both chemoprevention and therapeutic settings 12 . WA molecular targets have been well characterized including p53, FOXO3a, STAT3, ERα, ERK, JAK, IAP and NF-κB in BC 13 . Additionally, we have shown that SFN and WA combination targets multiple epigenetic pathways to induce cell cycle arrest and apoptosis in MCF-7 and MDA-MD-231 BC cells in vitro 14 , 15 .

Since breast tumorigenesis involves numerous combinations of genetic and epigenetic alterations, BC can be classified as an epigenetic disease. Increasing evidence suggests a global reshuffling of DNA methylation, histone acetylation, and histone methylation throughout the neoplastic transformation and progression of BC 7 . Several other studies have documented epigenetic abnormalities neutralizing capability of dietary phytochemicals to prevent BC. In this context, our laboratory has reported that interfering with epigenetic mechanisms including DNA methylation and histone deacetylation through dietary interventions can contribute to BC prevention possibly through the direct targeting of epigenetic mechanisms, alteration of regulatory non-coding RNA expression and shifting gut microbiome community in BC 16 . Notably, nutritional compounds may help to reshape gut microbial community while the gut microbiota plays a crucial role in synthesizing metabolites important for metabolic homeostasis 17 , 18 . For example, gut microbiota can ferment dietary fibers to produce short-chain fatty acids (SCFAs) such as butyrate, acetate, and propionate. Several of these SCFAs have been identified to alter epigenetic regulation and immune response in host cells 18 . However, past investigations from our laboratory, along with others, have successfully developed a novel strategy of combining two or more dietary phytochemicals to target BC 7 . Since the human food commonly consists of multiple nutritional ingredients, combinatorial dietary approach offers a practical and feasible therapeutic strategy for BC prevention by directly and/or indirectly targeting epigenetic mechanisms. Additionally, combinatorial approach offers advantage over single-agent therapeutic methods by effectively tackling tumor diversity, broadening the therapeutic window, and overcoming therapeutic resistance 8 , 19 , 20 . In this context, we investigated anti-BC effect of a novel combination of SFN-rich BSp and WA-rich Ashwagandha in this present study.

In this current investigation, we hypothesized that consumption of combinatorial SFN-rich BSp and WA-rich Ashwagandha (Ash) diets could effectively counteract BC development and progression in a spontaneous mammary cancer transgenic mice model. Therefore, we examined the impact of BSp and Ash administration, both individually and in combination, on tumor growth and development in a transgenic mouse model C3(1)-SV40 Tag (C3), with a comprehensive investigation into the molecular and epigenetic mechanisms associated with the anti-tumor effect. Additionally, we explored how the gut microbial community was influenced by the combinatorial dietary intervention both before and after tumor development. Our findings suggest that the combined administration of BSp and Ash was efficient in preventing ER(−) BC mammary tumors, partly due to a synergistic interaction between BSp and Ash. Combinatorial BSp and Ash treatment enhanced the expression of tumor suppressors associated with cell cycle regulation and apoptosis-associated proteins. Moreover, combined BSp and Ash administration altered the expression of several epigenetic machinery alongside reshuffling the gene expression profile in mammary tumors, and also altered the composition of gut microbiota.

Early life BSp and/or Ash treatment prevents ER-negative breast tumor development in C3 mice

In the current study, we used C3(1)-SV40 Tag (C3) transgenic mouse models that can spontaneously develop mammary tumors due to SV40 large T antigen (Tag) overexpression in epithelium of mammary grand in their early lifespan 21 . Functional inactivation of tumor suppressor p53 and retinoblastoma (Rb) by Tag lead to initiation of mammary hyperplasia around 8 weeks of age in hemizygous female mice in a hormone-independent manner that further develops to mammary intraepithelial neoplasia which resembles human ductal carcinoma in situ (DCIS) by around the 15th week of age 22 , 23 . Since the molecular and histological features exhibited in C3 mammary tumor model resembles TNBC, C3 mouse models have been successfully applied in many BC studies 22 . First, we were interested to evaluate the anti-tumorigenic effect of single and combined BSp and/or Ash treatment on breast tumor growth and development in C3 mice. We observed a delay in tumor development initiation in both the single compound treated groups (BSp: 13 weeks; Ash: 13 weeks) and combined BSp + Ash group (14 weeks) mice compared to the control group (12 weeks) mice (Fig.  1 A,B). We also found an overall decrease in tumor incidence in BSp or Ash treated group as well as combined BSp + Ash treated group mice over time. Only combinatorial BSp + Ash treated mice exhibited a statistically significant reduction in tumor incidence from 19 to 21 weeks of age (Fig.  1 A,B). In the case of tumor latency, a statistically significant increase in tumor latency (19.2 weeks) was observed only in combinatorial intervention group mice although single-compound interventions led to increased tumor latency (BSp: 17.9 weeks; Ash: 18.4 weeks) compared to control group mice (15.8 weeks) (Fig.  1 C). The ratio of extended tumor latency for BSp, Ash and BSp + Ash group was 13.3%, 16.5% and 21.5% of control treatment respectively (Supplementary Table S1). Additionally, an additive interaction between BSp and Ash was predicted for extended tumor latency by combination treatment from combination index calculation (Supplementary Fig. S1). In the case of tumor volume, every single compound and combinatorial treatment led to a global reduction in tumor volume over time when compared to the control group. We also found a statistically significant decline in tumor volume only upon combinatorial treatment at 21 weeks of age and thereafter (Fig.  1 D). Concordant with tumor volume reduction, combinatorial BSp + Ash administration resulted in a statistically significant reduction in tumor weight due to a synergistic interaction between BSp and Ash (Fig.  1 E; Supplementary Fig. S1). The calculated tumor growth inhibition rate for BSp, Ash, and BSp + Ash group was respectively 27.5%, 29.4%, and 75.1% (Supplementary Table S1). Importantly, we observed no detrimental effects of BSp and/or Ash supplementation on mouse growth performance and hepatic function in C3 mice (Supplementary Fig. S2). In summary, combined BSp + Ash treatment was statistically more effective in suppressing tumor growth and development, as manifested by a delayed onset of tumors, lower tumor incidence, smaller tumor size, and lighter tumor weight in comparison to the outcomes seen in the BSp and Ash treatment groups. The anti-tumorigenic impact of the BSp + Ash combination can be attributed in part to the synergistic interaction between BSp and Ash.

Early life BSp and/or Ash treatment prevents ER-negative breast tumor development in C3 mice. Effect of different single and combined administration of BSp and Ash on tumor incidence ( A ), tumor latency ( B ), tumor growth volume ( C , D ) and tumor weight measured at the termination point ( E ). Values are means ± SEMs. The significances of tumor incidence were analyzed using the chi-square test. Means that do not share a common superscript are significantly different at p ≤ 0.05. Significances of tumor volume among treatments were determined using two-way repeated measures ANOVA considering time and treatment as factors. Values are means ± SE, n = 10. Means that do not share a common superscript are significantly different at p ≤ 0.05. Tumor latency and tumor weight comparisons among the dietary groups were performed with One-way ANOVA analysis and Tukey’s HSD. Values are means ± SEM, n = 8–10. Means that do not share a common superscript are significantly different at p ≤ 0.05. Here, BSp: Broccoli sprouts; Ash: Ashwagandha; BSp + Ash: Broccoli sprouts and Ashwagandha combination.

Dietary BSp and/or Ash treatment increases tumor suppressor expression in C3 mice

We were next interested in investigating the molecular mechanisms responsible for the cancer inhibiting effects of BSp + Ash combination. We first analyzed the protein expression level of several tumor suppressors in the mammary tumor tissue samples from each treatment group (Fig.  2 ). Transcription factor p53 can transactivate genes including p21 to induce cell cycle arrest and/or apoptosis in response to DNA damage 24 . Cip/Kip family members (i.e., p21, p27, and p57) control cell cycle by inhibiting various cyclin-dependent kinases (CDKs) in addition to their role in apoptosis induction 25 . p16 is an Ink4 family member that inhibits CDK4 and CDH6 in order to prevent Rb phosphorylation and subsequently trigger G1 arrest 26 . Tumor suppressor phosphatase and tensin homologue (PTEN) negatively regulate PI3K signaling for cell survival and proliferation besides regulating p53-dependent cell senescence 27 . According to our result, BSp alone treatment upregulated the expression of p53, p21 and p27 while Ash alone treatment enhanced p53 and p27 expression when compared to the control treatment (Fig.  2 A,B). Feeding mice with combined BSp + Ash diet increased the expression of p53, p57, p21, p16 and p27. Furthermore, expressional upregulation of p53 and p57 in BSp + Ash-fed mice was statistically significant (Fig.  2 B) compared to control as well as singly BSp or Ash treated mice. A synergistic drug-drug interaction was predicted between BSp and Ash on upregulating p57 and p53 expression in mammary tissue of combinatorial BSp + Ash treated mice (Supplementary Fig. S3). Together, combinatorial BSp + Ash treatment was more efficient in increasing tumor suppressor p53 and p57 in C3 mice than BSp or Ash treatment alone.

Expressional changes of key tumor suppressors proteins in the mammary tumor of single and combined BSp and Ash treated mice. The top panel shows the cropped images from an imaging system. The bottom panel shows the statistical analysis of band intensity calculated on the images using ImageJ. Graphs represent β-actin normalized protein expression level with each bar representing the mean ± SE (n = 3). Means that do not share a common superscript are significantly different at p ≤ 0.05 upon One-way ANOVA and Tukey’s post-hoc analysis. Here, BSp: Broccoli sprouts; Ash: Ashwagandha; BSp + Ash: Broccoli sprouts and Ashwagandha combination.

Dietary BSp and/or Ash treatment enhances apoptosis in C3 mice

We next measured the expression of apoptosis-associated proteins BAX, Bcl-2 and PUMA in mammary tumor tissue from each group in order to determine the impact of single and combined BSp and/or Ash administration on apoptosis induction in mammary tumor (Fig.  3 ). The results of western blot analysis suggested statistically significant upregulation of pro-apoptotic BAX protein expression as a result of singly administered BSp and Ash group mice compared to the control group mice. Singly administered BSp and Ash also increased the expression of PUMA and BAX:Bcl-2 ratio slightly without any statistically significant impact on anti-apoptotic Bcl-2 expression (Fig.  3 A,B). In the case of combinatorial BSp + Ash-fed mice, we found a statistically significant upregulation of BAX, PUMA expression as well as BAX:Bcl-2 ratio (Fig.  3 B). Additionally, we uncovered a synergistic interaction between BSp and Ash that led to a stronger uplifting of BAX:Bcl-2 ratio and PUMA expression in BSp + Ash fed mice compared to the effects observed in singly BSp and Ash administered mice (Supplementary Fig. S4). Taken together, BSp + Ash combinatorial treatment was more potent in enhancing apoptosis in C3 mice compared to single dietary interventions.

Expressional changes of key apoptosis-associated proteins in the mammary tumor of single and combined BSp and Ash treated mice. The top panel shows the cropped images from an imaging system. The bottom panel shows the statistical analysis of band intensity calculated on the images using ImageJ. Graphs represent β-actin normalized protein expression level with each bar representing the mean ± SE (n = 3). Means that do not share a common superscript are significantly different at p ≤ 0.05 upon One-way ANOVA and Tukey’s post-hoc analysis. Here, BSp: Broccoli sprouts; Ash: Ashwagandha; BSp + Ash: Broccoli sprouts and Ashwagandha combination.

Dietary BSp and/or Ash treatment alters the expression of epigenetic machinery in C3 mice

Earlier, overexpression of class-1 HDAC isoenzymes (i.e., HDAC1, HDAC2, HDAC3, HDAC4) have been reported in BC 28 . Additionally, DNMTs exhibited stage-specific overexpression, with maintenance methyltransferase DNMT1 overexpression observed in the metastatic BC and de novo methyltransferases (i.e., DNMT3A, DNMT3B) overexpression detected in the primary stage of BC 29 . Since SFN in BSp and WA in Ash are respectively known for their HDAC and DNMT inhibitory effect, we analyzed the expression class I HDACs, de novo methyltransferases and maintenance methyltransferase on the tumor tissue from all treatment groups (Fig.  4 ). As demonstrated by the result, both single compound interventions resulted in insignificant reduction of several class I HDACs including HDAC2, HDAC3, HDAC8 for BSp treatment and HDAC1, HDAC2, HDAC8 for Ash treatment (Fig.  4 A,B). Notably, combinatorial BSp and Ash administration resulted in a significant reduction of HDAC1. On the other hand, DNMT1 and DNMT3A were slightly decreased in BSp-fed mice while Ash treatment reduced the expression of DNMT3A to some extent. However, combinatorial BSp and Ash administration significantly reduced the expression of DNMT3A (Fig.  4 B). We also computed synergistic interaction between the BSp and Ash for HDAC1 and DNMT3A downregulation by combined diet that resulted in a robust effect compared to the BSp and Ash treatment alone (Supplementary Fig. S5).

Expressional changes of key epigenetics modification-related proteins in the mammary tumor of single and combined BSp and Ash treated mice. The top panel shows the cropped images from an imaging system. The bottom panel shows the statistical analysis of band intensity calculated on the images using ImageJ. Graphs represent β-actin normalized protein expression level with each bar representing the mean ± SE (n = 3). Means that do not share a common superscript are significantly different at p ≤ 0.05 upon One-way ANOVA and Tukey’s post-hoc analysis. Here, BSp: Broccoli sprouts; Ash: Ashwagandha; BSp + Ash: Broccoli sprouts and Ashwagandha combination.

Dietary BSp and/or Ash treatment induce alteration of transcriptome in mammary tumor of C3 mice

Since dietary BSp and/or Ash treatment altered the expression of a several key molecular players associated with transcriptional regulation, apoptosis, and epigenetic regulation, we further aimed at investigating the impact of combinatorial BSp and Ash on the transcriptome changes by RNA sequencing analysis. We started with total RNA extraction from mammary tissue harvested at the termination point of the study and subsequently prepared RNA-seq pair-end library. Raw mRNA-seq data was first processed for quality check and eventually used for differential gene expression analysis. From the unsupervised principal component analysis (PCA), we observed a clear separation of control group samples from combinatorial group samples along the first component (73%). Control group samples further clustered separately in different clades from the combinatorial group samples in hierarchical cluster dendrogram (Supplementary Fig. S6A,B). Next, we performed differential gene expression analysis with DESeq2 package utilizing raw count matrix obtained after read alignment and counting. Our inspection on model fitness suggested a good fitting of DESeq2 model to our current data set (Supplementary Fig. S6C). We selected a 5% false discovery rate (FDR < 0.05) and a fold-change (|log2(FoldChange)|> 1) cutoff greater than 1 to determine the significance of a differentially expressed (DE) mRNA. Overall, we identified 477 differentially expressed mRNA in mammary tumor of combinatorial BSp + Ash treated mice compared to control group mice. Out of these differentially expressed mRNAs, 97 mRNAs were upregulated, and 380 mRNAs were downregulated. We plotted all differentially expressed mRNAs due to combinatorial treatment in a heatmap to better visualize overall mRNA expressional changes (Fig.  5 A) across control and combinatorial treatment group. A comprehensive list of DE mRNAs is available in Supplementary Table S2. Generation of volcano plot besides heatmap further enhanced our understating on the expression level changes of DE mRNAs (Fig.  5 B). Finally, we performed gene ontology (GO) analysis to ascribe biological theme to DE mRNAs and identified significantly affected themes (adj p < 0.05) in the categories of biological processes, molecular function, and cellular components. Interestingly, GO analysis revealed that activated DE mRNAs category were associated with DNA modification, transcription factor activity and negative regulation of cell adhesion while suppressed DE mRNAs category were enriched with cell junction component, integral plasma membrane component (Fig.  5 C). In the functional category, DE mRNAs were associated with channel activity, passive transmembrane transporter, gated channel activity, structural constituent of synapse, phosphoric ester hydrolase activity, metal ion transmembrane transporter, calcium-dependent phospholipid binding and cyclase activity (Supplementary Fig. S6D). Pathway enrichment analysis further indicated that combinatorial BSp and Ash treatment could impact multiple signaling pathways including Hipo-, chemical carcinogenesis-, TNF- and estrogen-signaling pathway influencing multiple molecular components (Supplementary Fig. S6E,F). We finally evaluated the expression of several candidate genes by qRT-PCR (Fig.  5 D) for validation of our genome-wide analysis including multiple candidates from the upregulated and downregulated gene lists. Consistent with our genome-wide analysis, we found significant upregulations of SALL1 and NTN4 and downregulation of HOXA 6, HDAC 9, HOTAIRM1 and WNT 6 in C3 mice because of combinatorial BSp and Ash treatment. In this regard, SALL1 acts as a tumor suppressor by recruiting nucleosome remodeling and deacetylase complex to trigger tumor cell senescence in BC 30 . The expression of NTN4 is downregulated in BC, whereas NTN4 overexpression inhibits migration and invasion of MDA-MB-231 cells 31 . Conversely, the oncogene HOXA 6 has been reported to aggravate cancer metastasis 32 , 33 . Overexpression of Class II a HDAC 9 promotes cell proliferation and therapeutic resistance against HDAC inhibitors in BC 34 . Downregulation of long non-coding RNA HOTAIRM1 promotes tamoxifen resistance in ER + BC cells 35 . WNT6 is overexpressed in BC and promote cell proliferation and migration 36 .

Dietary BSp and/or Ash treatment induce alteration of transcriptome in mammary tumor of C3 mice. ( A ) Heatmap representing differentially expressed mRNAs in C3 mice due to combinatorial BSp and Ash treatment. Each row represents differentially expressed mRNA, and each column represents biological replicates. Here, Ctl indicates control diet treated control group samples (n = 3) while BA indicated combinatorial BSp + Ash treated test group samples (n = 3). Blue color denotes downregulation and red color denotes upregulation. ( B ) The volcano plot shows distribution of DEGs in C3 mice as a result combinatorial BSp + Ash treatment. Here, gray dots indicate mRNAs that were not significantly expressed, blue dots represent downregulated mRNAs and red dots indicate upregulated mRNAs [Benjamini–Hochberg FDR < 0.05 and |log2(fold-change) |> 1). ( C ) The dot plot representing the gene ontology enrichment terms for the differentially expressed mRNAs in C3 mice. The dot size represents the number of enriched genes while the dot color represents activated (blue) and suppressed (red) genes. ( D ) Validation of differentially expressed mRNA with qRT-PCR. Graphs represent β-actin-normalized expression level of corresponding mRNA with each bar representing the mean ± standard error (SE) of three biological replicates (n = 3). The asterisks indicate statistical significance (* p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001, **** p ≤ 0.0001) upon unpaired T-test. Here, BSp + Ash indicates broccoli sprouts and Ashwagandha combination treatment.

Early life BSp and/or Ash treatment alters gut microbial composition before and after the tumor development

Dietary supplements were digested and utilized by gut microbial species before their by-products and metabolites are transported to other parts of the body 9 . Previous research indicated an association between dietary phytochemicals and SCFA-producing gut microbiota 37 . Here, we also investigated the changes in gut microbial composition of C3 mice due to single or combinatorial dietary supplements. Fecal samples were collected before and after the onset of tumor, since tumor development has been found to have an impact on gut microbiota. According to the results of gut microbiota analysis before tumor onset, combinatorial treatment significantly increased alpha diversity compared to the control group (Fig.  6 A). The Bray Curtis beta diversity analysis, as shown in the 3D PCA plot, demonstrated that individual samples in each group were clustered distinctly against control group samples which were statistically significant (Fig.  6 B). Both BSp and combination groups had higher relative abundance of Firmicutes and lower relative abundance of Bacteroidetes and Verrucomicrobia. Ash group had substantially higher relative abundance of Verrucomicrobia and lower abundance of Firmicutes and Bacteroidetes (Fig.  6 C). These results suggest that the combinatorial group had higher microbial diversity and distinct microbial composition before the tumor onset. Additionally, numerous significantly different bacterial taxa were identified compared to the control group, BSp (n = 12, at species level), Ash (n = 3, at family level), and combinatorial group (n = 14, at species level). BSp group had significantly higher relative abundance of Ruminococcus , Muribaculaceae , and Lachnospiraceae xylanophilum group (Supplementary Table S7). The Ash group had lower relative abundance of Rikenellaceae (Supplementary Table 8). The combinatorial group had significantly higher relative abundance of Lachnospiraceae bacterium COE1 , Ruminococcus , Coprostanoligenes group , Lachnospiraceae xylanophilum group , and Muribaculaceae (Supplementary Table S9/Table S6). Overall, differences of bacterial composition were found in all dietary treatment groups among which the combinatorial group had more significant abundance of bacterial genus or species than single treatment groups when compared to the control group.

Gut microbial composition changes in dietary treatment groups before and after tumor onset. ( A ) Alpha-diversity before tumor onset: observed species, PD whole tree, Shannon and Simpson diversity. The asterisk indicates statistical significance (*p ≤ 0.05, **p ≤ 0.01) upon One-way ANOVA and Tukey’s post-hoc analysis. Here, BSp: Broccoli sprouts; Ash: Ashwagandha; BSp + Ash: Broccoli sprouts and Ashwagandha combination. ( B ) Bray Curtis 3D-PCoA plot before tumor onset. The red dots indicate control group samples, green dots indicate BSp group samples, yellow dots indicate Ash group samples, blue dots indicate combinatorial BSp + Ash group samples. Statistical analysis of Bray–Curtis and weighed Unifrac tests of beta diversity was performed using permutational multivariate analysis of variance (PERMANOVA). Statistical significance: control-BSp (p = 0.007), control-Ash (p = 0.043), control-combination (p = 0.003); and with weighed Unifrac control-BSp (p = 0.462), control-Ash (p = 0.042), control-combination (p = 0.002). ( C ) Phylum level changes of microbial community in dietary treated groups before tumor onset. The top 10 abundant phyla in respective groups are represented in pie charts. D ) Alpha-diversity after tumor onset: observed species, PD whole tree, Shannon and Simpson diversity. The asterisk indicates statistical significance (*p ≤ 0.05) upon One-way ANOVA and Tukey’s post-hoc analysis. Here, BSp: Broccoli sprouts; Ash: Ashwagandha; BSp + Ash: Broccoli sprouts and Ashwagandha combination. ( E ) Bray Curtis 3D-PCoA plot after tumor onset. The red dots indicate control group samples, green dots indicate BSp group samples, yellow dots indicate Ash group samples, blue dots indicate combinatorial BSp + Ash group samples. Statistical analysis of Bray–Curtis and weighed Unifrac tests of beta diversity was performed using permutational multivariate analysis of variance (PERMANOVA). Statistical significance: control-BSp (p = 0.007), control-Ash (p = 0.043), control-combination (p = 0.003); and with weighed Unifrac control-BSp (p = 0.462), control-Ash (p = 0.042), control-combination (p = 0.002). ( F ) Phylum level changes of microbial community in dietary treated groups after tumor onset. The top 10 abundant phyla in respective groups are represented in pie charts.

Gut microbial composition analysis after tumor development suggested that combinatorial treatment group also had significantly higher alpha diversity compared to the control group (Fig.  6 D). We also observed differential clustering of individual samples against control group in the Bray Curtis beta diversity analysis (Fig.  6 E) with statistical significance. We observed a higher relative abundance of Proteobacteria and Verrucomicrobia in control and Ash group respectively. BSp group mice had higher Firmicutes to Bacteroidetes ratio compared to control. The combinatorial group had relative abundance of both Firmicutes and Bacteroidetes, but lower abundance of Verrucomicrobia (Fig.  6 F). The Kruskal–Wallis test suggested no significant difference of bacterial community was found in BSp and Ash groups compared to control (Supplementary Table S10-11). The combinatorial group had significantly abundant bacterial taxa (n = 3, at class level). Coriobacteriia, Bacterioidia, and Saccharimonadia decreased compared to the control group (Supplementary Table S12). Collectively, these data indicate that the combinatorial dietary treatment may have had greater impact on gut microbiota during mammary tumor progression. Additionally, longitudinal studies suggested that when comparing the gut microbiota composition between two different time points within each treatment group and the control group, no significant differences of relative abundant genus or species were found in control or treatment groups (n = 0, at genus or species level) (Supplementary Table S13-16). In conclusion, the gut microbiota composition within each treatment group was constantly shaped by BSp, Ash, and combinatorial dietary interventions, among which the combinatorial intervention had the most promising effect of BC inhibition in the current transgenic mouse model.

Many studies on breast cancer prevention have focused on individual compound interventions, despite the fact that the human diet typically includes a variety of nutritional components. Additionally, the effectiveness of single dietary interventions in BC management might be compromised by the risks of toxicity, incomplete therapeutic range, narrow targeting, and therapeutic resistance 8 , 19 , 20 . On the other hand, recent research suggests that a combinatorial therapeutic approach can yield promising efficacy in breast cancer chemoprevention due to potential anticancer properties and differential molecular targeting 7 , 38 , 39 . In this regard, we have reported that combination of SFN and WA can induce cell cycle arrest and apoptosis in MCF-7 and MDA-MD-231 BC cells in vitro. We also found that SFN and WA combination targets multiple epigenetic pathways including DNA methylation, histone deacetylation to exert their anti-BC effect 14 , 15 . Therefore, we were interested in examining if the in vitro findings with WA and SFN combination would be translatable to an in vivo scenario through a comprehensive investigation of molecular and epigenetic mechanisms.

We started our investigation by examining the impact of combinatorial broccoli sprout (BSp), a well-known source of SFN, and WA-rich Ashwagandha extract (Ash) diets on the latency, incidence, and progression of triple-negative BC. We selected C3(1)-SV40 Tag (C3) transgenic mouse model in the current investigation since C3 transgenic mouse is a widely used mouse model that develops mammary neoplasia spontaneously in female mice in a hormone-independent manner. The gene expression profile and histological features of mammary neoplasia in C3 mouse model resembles human basal-like triple-negative aggressive cancers 22 , 23 . Additionally, our lab has demonstrated dysregulation of multiple epigenetic pathways in C3 model which makes this mouse model suitable for studying both anti-BC and epigenetic mechanisms at the molecular level 8 , 40 . With respect to dose selection, we opted for 26% BSp because the safety and efficacy of 26% BSp diet, especially in a combinatorial scenario, has been proven in several investigations in our laboratory 8 , 9 , 41 . Likewise, we selected 0.16% Ash considering the in vitro dose safe evaluation and reported pharmacological safety evaluation data 42 , 43 . Furthermore, this dietary combinatorial regimen is physiologically attainable by consuming ∼ 234 g of BSp and ∼ 185 mg of Ashwagandha extract powder (6% WA) by an adult per day, respectively 44 , 45 , 46 .

Our phenotypic results from breast tumor development demonstrated a significant decrease in tumor incidence and extended tumor latency due to combined BSp and Ash administration. Additionally, we observed a noteworthy inhibition of tumor growth, as evidenced by smaller tumor volume and lower tumor weight resulting from BSp + Ash treatment. Our findings highlight that the combination of BSp and Ash was more effective in suppressing tumor growth and development, even though individually administered BSp and Ash exhibited anti-breast cancer effects to some extent. Overall, the tumor phenotypic data indicate that the combinatorial treatment has the ability to interfere with tumor growth kinetics in C3 mice. Since delayed tumor growth kinetics has been linked to prolonged tumor doubling times and surface shrinkage of the tumor mass at the growing edge, we propose that dietary BSp + Ash treatment may interfere with tumor growth kinetics by altering cell cycle regulation as well as inducing apoptosis.

We then focused on investigating the impact of combinatorial BSp and Ash treatment on the expression of several cell cycle associated tumor suppressors and apoptosis-associated proteins in mammary tumor tissue. Our results suggested a significant upregulation of p53 and p57 upon combined BSp and Ash treatment only. Both p53 and the Cip/Kip family member p57 have been reported to trigger cell cycle arrest at multiple stages, including G1 and G2/M phases in breast cancer 47 , 48 . We also found that expressional upregulation of p53 was concomitant with transcriptional down-regulation of CCND1 and CDK4 in BC cells due to combined SFN and WA treatment in vitro 13 . Additionally, p53 has also been implicated in apoptosis induction through the transactivation of Bcl2 family proapoptotic genes, including BAX, BID and PUMA. In line with this, we observed a significant upregulation of pro-apoptotic BAX, PUMA, and the BAX:Bcl-2 ratio due to combinatorial treatment. Indeed, the balance between Bcl-2 and Bax expression acts as a regulator for cell survival in response to apoptotic stimuli by altering the apoptotic threshold for cancer cells 49 . PUMA can further potentiate apoptotic threshold by inhibiting Bcl2 family antiapoptotic proteins 50 . Combinatorial treatment-induced BAX and PUMA upregulation; therefore, mechanistically decreased cellular resistance to apoptotic stimuli by lowering the apoptotic threshold and consequential increase apoptotic cell death in mammary tumor.

Earlier we reported the HDAC and DNMT inhibitory activity of SFN and WA in BC cells 14 . We took the findings into account to further study the impact of BSp and Ash diet on class I HDACs and DNMTs expression in mammary tissue. As anticipated, the combined BSp + Ash diet significantly declined the expression of HDAC1 and DNMT3A in mammary tumors. Importantly, SFN-rich in BSp has been proposed to trigger the kinase signaling pathway for cytoplasmic translocation and subsequent ubiquitination and/or Pin1-directed HDAC degradation 51 . On the other hand, WA available in Ash may impact the expression of multiple chromatin-modifying enzymes that may lead to expressional downregulation of DNMT 52 . Our previous in vitro study also demonstrated that down-regulation of HDAC1 and DNMT3A activity was associated with expression changes of p53, decreased Rb phosphorylation and elevated BAX:Bcl-2 ratio in BC cells 15 . Indeed, HDACs and DNMTs both play critical roles in regulating cell cycle progression and apoptosis as epigenetic regulators. Mechanistically, HDAC inhibition can interfere with cell cycle progression by abolishing Rb phosphorylation besides influencing the expression of cell cycle modulators, including p53, E2F, p21, and p27 53 . The expressions of p21 and p27 have been reported to be dysregulated by DNA methylation and histone deacetylation in multiple hematologic and solid cancers, including BC 54 , 55 . Furthermore, apoptosis regulator BAX and BCL-2 could undergo hypermethylation-mediated silencing in neoplastic situations 56 . Overall, our current results together with previous findings indicated that combinatorial BSp and Ash may influence epigenetic regulation to exert its anti-BC effect in ER(−) BC.

Our differential gene expression analysis revealed a global reshuffling of transcriptome due to BSp + Ash treatment. According to GO analysis, differentially expressed genes were associated with DNA modification, transcription factor activity, cell adhesion, cell junction and other processes. We further demonstrated transcriptional downregulation of HDAC9 and Hotairm1 by BSp + Ash treatment. HDAC9 is associated with enhanced cell proliferation and invasiveness of breast cancer 57 , 58 . On the other hand, Hotairm1 is a long non-coding RNA that has been reported to promote tamoxifen resistance in breast cancer by enhancing HOXA1 upregulation. Mechanistically, HOTAIRM1 halts PRC2 complex mediated H3K27me3 deposition on the HOXA1 promoter by direct interaction with epigenetic modifier EZH2 35 . These findings, together with expressional down-regulation of HDAC1 and DNMT3A due to combinatorial treatment, reinforce our assumption that BSp + Ash-induced expressional change in epigenetic molecules may be linked to the observed alteration in the transcriptome.

We have identified several signaling pathways from our pathway enrichment analysis including Hippo-signaling, TNF-signaling, chemical carcinogenesis-signaling and estrogen signaling that are influenced by the combinatorial treatment mediated transcriptional alteration. Several of these influenced pathways have significant impact on the expression of genes associated with cell proliferation, cell cycle, cell adhesion, cell migration, cell invasion, cell survival, apoptosis, transcription factors, cell adhesion molecule, cell membrane components and leukocyte recruitment. This finding aligns closely with our experimental findings where we have demonstrated expression alteration of multiple genes associated with cell cycle and apoptosis. Additionally, pathway analysis enabled us to extrapolate on the molecular mechanisms that might be orchestrated by the combinatorial to BSp + Ash treatment to exert its anti-BC effect. Overall, further investigation could shed light on the signaling pathways that may be involved with the observed anti-BC effect of combinatorial BSp + Ash treatment.

Earlier it was reported that the BC patients have different breast and gut microbial composition compared to healthy controls 59 , 60 . Gut microbiota plays an important role in releasing metabolites such as SCFAs that are known to modulate epigenetic regulations and immune responses. Here, the gene expression analysis revealed that HDACs, WNT, and HOTAIRM1-HOXA1 were significantly decreased by BSp and Ash combinatorial treatment. Previous findings suggested that SCFA inhibited the expression of HDACs and WNT signaling. Therefore, we investigated potential association of gut microbiota including SCFA-producers that were shaped by the dietary supplements with tumor prevention and latency 61 , 62 . Technically, our study compared gut microbial community between treatment groups and the control group at two time points, before and after the tumor onset. Increased alpha diversity and beta-diversity were observed in combinatorial treatment group both before and after the tumor onset when compared to the respective control. The results indicated that combinatorial BSp and Ash treatment induced prominent changes of gut microbial composition in our ER(−) BC mouse model. Longitudinal studies further confirmed that dietary supplementation had constant impact on gut microbial composition over time, as the changes of relative abundance of analyzed species are not significantly different when compared longitudinally. Together, these results suggested that the combinatorial BSp and Ash treatment constantly shaped gut microbial composition toward health-benefiting bacterial communities before the tumor onset and during cancer progression.

Our results further indicated several possible mechanisms behind such health-promoting microbiota shift that may play a crucial role in observed anti-BC effect of combinatorial treatment. For example, combinatorial BSp and Ash treatment may shape gut homeostasis by maintaining Firmicutes to Bacteroidetes (F/B) ratio. We have observed an elevated Firmicutes to Bacteroidetes (F/B) ratio before and during BC progression due to BSp and combinatorial treatment whereas lower F/B ratio has been linked to higher risk of breast cancer 63 . However, such health promoting implication of the F/B ratio in inhibiting ER(−) BC needs further investigation. Several organisms that we identified in the combinatorial BSp and Ash treated mice are known as primary contributors of anti-inflammatory metabolites including pro-inflammatory Eubacterium xylanophilum and Muribaculaceae . For example, Muribaculaceae has been reported to decrease pro-inflammatory activity in the host intestine by reducing TNF-α and IL-6 and increase IL-10 64 . Eubacterium xylanophilum group was found to have a strong positive correlation with levels of proinflammatory cytokines 65 . Though we did not conduct any formal investigation on the impact of pro-inflammatory bacteria on observed anti-BC effect, we have identified TNF-signaling as one of the pathways impacted by combinatorial treatment. Thus, further investigation may be warranted to rule out how these pro-inflammatory bacteria contribute to observed anti-BC effect of combinatorial diet. On the other hand, Ruminococcaceae and Muribaculaceae  have been recognized as producers of SCFAs 66 , 67 . Furthermore, a positive correlation has been reported between Ruminococcaceae abundance and butyrate/SCFA ratio in vivo 68 . Interestingly, several recent studies from our laboratory have reported that the gut microbiota can produce SCFAs to impede tumor progression. In this regard, we have reported that combinatorial BSp and green tea polyphenols diet could differentially affect the gut microbial composition with a concomitant rise of serum level of SCFAs including propionate and isobutyrate 18 . In another study, we have reported alteration of gut microbiota due to insulin supplementation with a simultaneous rise of serum propionate level. Furthermore, propionate was able to inhibit cell proliferation as well as HDAC and DNMT enzymes activity in multiple BC cells in vitro 69 . These findings encourage further study to uncover if microbial induction of SCFAs and consequential alteration of epigenetic regulation has any connection to observed anti-BC effect of combinatorial BSp and Ash treatment.

Throughout the investigation, we have observed synergistic interaction between SFN-rich BSp and WA-rich Ash both at the phenotypic (i.e., tumor inhibition) and molecular level which indicates that combined effect of BSp and Ash is more effective than either compound alone. There are multiple factors that may contribute to the observed synergistic interaction between BSp and Ash. Firstly, we designed our combination to target alternative epigenetic pathways. BSp is a well-known source of SFN that functions as a HDAC inhibitor whereas Ash is a rich source of WA which is a pronounced DNMT inhibitor. Crosstalk between epigenetic regulation pathways may be another possible mechanism for synergistic interaction of BSp and Ash combination which could be most impactful in our experimental context. Increasing evidence suggests that DNA methylation could influence the chromatin orientation by influencing histone modifications and vice versa 70 . DNMTs have been documented to engage in physical interactions with HDACs, and they can be jointly enlisted into transcriptional repressor complexes, such as MeCP2, to facilitate transcriptional repression 71 . DNMT and HDAC cooperativity may lead to their concerted efforts in transcriptional regulation. For instance, DNMTs may establish DNA methylation patterns that attract HDACs to further modify histones, creating a repressive chromatin environment with an enhanced suppression of gene activity 72 . Both BSp and Ash are a rich source of antioxidants that neutralize oxidative stress. BSp has been reported to induce Keap1-Nrf2 pathway whereas Ash administration increased levels of multiple antioxidant enzymes including superoxide dismutase and catalase 73 , 74 . Variance in antioxidative defense attained by BSp and Ash administration could lead to a comprehensive protection against oxidative damage and enhanced chemoprevention. Finally, BSp administration has been reported to inhibit NLRP3, IL-1β, IFN-γ, IL-17 and IL-23 IL-12 whereas Ash administration inhibits TNF-α, IL-1β, IL-6, IL-8 and IL-12 75 , 76 . Since immunomodulatory effects of BSp and Ash converge to separate spectrums of effector molecules, synergistic interaction between BSp and Ash may also be partially ascribed to their anti-inflammatory effect.

The present study demonstrated promising findings supporting the potential of combinatorial SFN-rich BSp and WA-rich Ash in inhibiting ER(−) BC. Since we have derived experimental findings utilizing transgenic mice, clinical benefits from this combinatorial treatment should be validated through further investigation on safety and efficacy of this combination. Though our study provides insights into possible molecular mechanisms underlying observed effects, further investigations are warranted to elucidate the molecular interplay between signaling pathways, transcription factors, and epigenetic regulations. While we reported shifting of the gut microbial composition due to combinatorial treatment, the implications of these alterations on cancer inhibition and relevant molecular mechanisms need to be addressed through further investigations.

Mouse model and animal housing

Transgenic mouse models C3(1)-SV40 Tag (FVB-Tg(C3-1-TAg) cJeg/JegJ) (C3) was used in this current investigation. The female mice of C3 mouse model typically develops tumors resembling Ductal Carcinoma in situ (DCIS) within the mammary epithelium at approximately 15 weeks of age due to transgene overexpression 22 , 23 . The breeder mice (~ 4 weeks of age) were obtained from Jackson Laboratory (Bar Harbor, ME). Experimental mice we genotyped (4 weeks of age) for transgene expression. Only transgene expressing female mice were used in this experiment. Mice were housed in the Animal Resource Facility of the University of Alabama at Birmingham (UAB, Birmingham, AL) and were maintained under the following conditions: 12-h dark/light cycle, 24 ± 2º C temperature with 40% to 60% humidity. Sample sizes were determined by a priori power calculation. A sample size of 10 mice/group was applied for detecting the effect of dietary interventions at a significance threshold of 0.05 with 80% power. The animal study was reviewed, approved, and performed in accordance with relevant guidelines and regulations by Institutional Animal Use and Care Committee of the University of Alabama at Birmingham (IACUC; Animal Project Numbers:10088 and 20653).

Dietary treatment and experimental design

Standard AIN-93G diet was available commercially (TestDiet, St. Louis, MO, US). A customized BSp diet was formulated by supplementing AIN-93G with 26% SFN-rich BSp powder (Natural Sprout Co.) (Supplementary Table S3). Standard AIN-93G was supplemented with 0.16% human consumable Ashwagandha (Ash) extract (Shoden® Ashwagandha Extract, Nootropics Depot; ~ 6% WA) to prepare Ash diet (Supplementary Table S4). Combined BSp and Ash diets were prepared by adding 26% SFN-rich BSp powder and 0.16% Ash extract with AIN-93G diet (Supplementary Table S5). All the standard and customized diets were prepared by TestDiet. Transgene positive female C3 mice were randomly distributed into 4 groups (10–12 mice/group) at the age of 5 weeks. Different groups were treated with different dietary regimens starting from 6 weeks of age: (1) Control group: Mice were fed with control AIN93G diet; (2) BSp group: Mice were fed with BSp diet; (3) Ash group: Mice were fed with Ash diet; (4) Combined BSp and Ash diets: Mice were fed with Combined BSp and Ash diets. Detailed specification and nutrient composition of standard and customized diet are available in supplementary files.

Growth performance and tumor observation

We recorded tumor volume and incidence of C3 mouse weekly. We also observed growth performance of experimental mice by monitoring body weight every other week. The formula below was used for calculating tumor volume: tumor volume (cm3) = (length × width2) × 0.523 72 . The experiment was terminated at 24 weeks of age when the mean tumor diameter in the control mice exceeded 1.0 cm. At the termination point, tumors tissue will be removed surgically, weighted, and stored in − 80 °C freezer for further investigation.

Western blotting analysis

About 50 mg of frozen tumors tissue were subjected to total protein extraction with T-PER Tissue Protein Extraction Reagent (Thermo Fisher Scientific, MA, USA) following manufacturer’s protocol. Protein concentration was estimated by bicinchoninic acid assay (BCA) protein assay utilizing Pierce™ BCA Protein Assay Kits (Thermo Fisher Scientific, MA, USA). Protein was mixed with 4 × Laemmli Sample Buffer (Bio-Rad Laboratories, Inc., Hercules, CA, USA) and denatured at 95 °C for 5 min in the presence 2.5% βmercaptoethanol. An equal amount of protein was loaded on 4–15% NuPAGE Tris–HCl precast gels (Thermo Fisher Scientific, MA, USA) for protein separation. Separated proteins were transferred onto nitrocellulose membrane using Trans-Blot Turbo Transfer System (Bio-Rad, Hercules, CA, USA). The membranes were then blocked with 1% non-fat dry milk (Cell Signaling Technology, Inc., MA, USA) blocking buffer and probed with primary antibodies against p16, p21, p27, p53, p57, PTEN, BAX, BCL-2, PUMA, HDAC1, HDAC2, HDAC3, HDAC8, DNMT1, DNMT3A and DNMT3B (Cell Signaling Technology, Danvers, MA, USA). β-actin served as an internal control for each membrane. Following the incubation with secondary antibodies, immunoreactive bands were visualized using Clarity MaxTM Western ECL P Blotting Substrates (Bio-Rad, Hercules, CA, USA) using ChemiDocTM Imaging Systems (Bio-Rad, Hercules, CA, USA). Densitometric analysis of protein bands was performed with image analysis software Image J (v1.53e) 77 .

RNA sequencing analysis

Total RNA was extracted from the tumor tissue of control diet and combined BSp and Ash diet treated mice as described previously 78 . Total RNA was used for RNA-seq pair-end library preparation (N Control  = 3, N Combination  = 3) and eventually sequenced on the Illumina Nextseq500 platform at the UAB Genomics Core Laboratories. Quality control and preprocessing of the raw data (FASTQ files) was performed with fastp tool for quality filtering (low quality, too many ns, etc.), length filtering (short reads), adapter trimming, and polyG tail trimming with the default parameter settings. Only clean and high quality fastq reads were aligned to the mouse reference genome GRCm39/mm39 using HISAT2 79 . The gene expression was qualified on aligned and sorted binary alignment and map files utilizing featureCounts. DeSeq2 was used for differential gene expression analysis 80 . The significant criterion of differentially expressed genes (DEGs) was set as |log2(FoldChange)|> 1 and false discovery rate (FDR) < 0.05. Other downstream analyses including principal component analysis (PCA), gene ontology (GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed in R (v.4.1.1).

Quantitative real-time PCR (RT-qPCR)

Validation of RNA sequencing analysis was performed with Quantitative real-time PCR for the target genes of interest including Hotairm1, Hdac9, Wnt6, Hoxa5, Sall1, Ntn4, β-actin. Equal amount of RNA (500 ng) was reverse-transcribed to cDNA using iScript™ cDNA Synthesis Kit (Bio-Rad, Hercules, CA, USA). PCR reactions were performed in triplicate with gene specific primers (Supplementary Table S6) purchased from Integrated DNA Technologies (Coralville, IA, USA) using SsoAdvanced Universal SYBR Green Supermix (Bio-Rad, Hercules, CA, USA). PCR amplification was performed in 20 μL wherein 1 μL of cDNA was used to amplify genes of interest with 500 nM reverse and forward primers and 1 × SYBR green master mix. The real-time PCR was performed using CFX Connect Real Time system (Bio-Rad, Hercules, CA, USA) with GAPDH (Glyceraldehyde 3-phospate dehydrogenase) as an endogenous control. Thermal cycling was initiated for 0.5 min at 95 °C followed by 45 cycles of PCR (94 °C for 15 s; 50 °C for 15 s, 60 °C for 30 s). Relative gene expression was calculated using 2− ΔΔCt method as described previously 81 .

Gut microbiome analysis and 16S rRNA sequencing

Fecal samples (5–8 samples/group) were collected from control, BSp, WA, and combinatorial groups at two time points during the study: (1) Before tumor onset: 10 weeks of age. (2) After tumor onset: 20 weeks of age. Fecal DNA Isolation Kit, Zymo Research (Irvine, CA, USA) was used to extract genomic DNA according to the manufacturer’s instruction. The extracted DNA was quantified by microspectrophotometer (ThermoFisher, Waltham, MA, USA) and stored in fridge − 80 ºC for future analysis. An amplicon library was generated using PCR and barcoded primers from extracted DNA to amplify the 16S rRNA V4 region 82 . The forward and reverse primers (Eurofind Genomics, Inc., Huntsville, AL, USA) were as follows: Forward V4: 5′ AATGATACGGCGACCACCGAGATCTACACTATGGTAATTGTGTGCCAGCMGCCGCGGTAA-3′; Reverse V4: 5′CAAGAGAAGACGGCATACGAGATNNNNNNAGTCAGTCAGCCGGACTACHVGGGTWTCTAAT-3′. PCR products were quantified by PICO green dsDNA Reagent and purified by QIAquick gel Extraction Kit (Qiagen, Germantown, MD, USA) before the sequencing was performed using NextGen Sequencing Illumina MiSeq platform. FASTQ files were de-multiplexed and assessed for quality control using FastQC. Microbiome analysis was performed with the Quantitative Insight into Microbial Ecology (QIIME) data analysis package 83 . Samples were grouped into amplicon sequence variant (ASV) with 97% similarity by Uclust Clustering program that also was used to evaluate phylum level changes. PyNAST was used to generate multiple sequencing alignment 84 . Alpha diversity was analyzed with observed species, PD whole tree, Shannon and Simpson diversity indexes. Beta diversity (Bray–Curtis and weighed Unifrac) was calculated to quantify the dissimilarity between control and treatment groups. Statistical analysis of Bray–Curtis and weighed Unifrac tests of beta diversity was performed using permutational multivariate analysis of variance (PERMANOVA). Taxonomic abundance between groups were investigated using Kruskal Wallis test. Statistical significance after 5% false discovery rate (FDR) adjustment was presented.

Statistical analyses

The sample size was estimated with a priori power calculation to obtain 95% power with a significance threshold of 0.05 utilizing GPower 3.1 85 . Statistical analysis was performed with GraphPad Prism version 10.0 (San Diego, CA, USA). Tumor incidence was analyzed with the Chi-Squared test. Results were represented as means ± standard error (SE) of the mean. The two-group comparisons were analyzed with unpaired t-test. The three or more groups’ comparisons were analyzed with one-way ANOVA and Tukey’s post-hoc test. Means that do not share a common superscript are significantly different at p ≤ 0.05. Combination index analysis with effect-based method (highest single agent model) and calculated with SiCoDEA 86 .

Ethics approval

The animal study was reviewed, approved, and performed in accordance with relevant guidelines and regulations by Institutional Animal Use and Care Committee of the University of Alabama at Birmingham (IACUC; Animal Project Numbers:10088 and 20653). The study was also carried out in compliance with the Animal Research Reporting of In Vivo experiments (ARRIVE) guidelines.

The current study, for the first time, gathers findings on the effect of BSp and Ash combinatorial treatment on any form of cancer in vivo. This investigation also provides compelling evidence that combined BSp and Ash administration may act synergistically against ER(−) BC both at the molecular and phenotypic level. Our results also indicated that combining BSp with Ash enhances targeting molecular components associated with multiple cell signaling pathway as well as epigenetic regulations. Furthermore, combined BSp and Ash intervention may confer health benefits through indirect influence on cellular processes by reshaping gut microbiota. Overall, BSp and Ash combination demonstrated substantial promise to be studied further for developing a novel strategy for inhibiting ER(−) BC through dietary intervention.

Data availability

All data generated or analyzed during this study are included in this published article (and its Supplementary Information files).

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Acknowledgements

This research was funded by grants from the National Institutes of Health (NCI R01 CA178441 and NCI R01 CA204346). The authors also gratefully acknowledge the assistance by Tollefsbol laboratory members.

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Rahman, M.M., Wu, H. & Tollefsbol, T.O. A novel combinatorial approach using sulforaphane- and withaferin A-rich extracts for prevention of estrogen receptor-negative breast cancer through epigenetic and gut microbial mechanisms. Sci Rep 14 , 12091 (2024). https://doi.org/10.1038/s41598-024-62084-1

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Assessment of novel prognostic biomarkers to predict pathological complete response in patients with non-metastatic triple-negative breast cancer using a window of opportunity design

Chitradurga rajashekhar akshatha.

Department of Medical Oncology, JIPMER, Puducherry, India

Dhanapathi Halanaik

Department of Nuclear Medicine, JIPMER, Puducherry, India

Rajesh Nachiappa Ganesh

Department of Pathology, JIPMER, Puducherry, India

Nanda Kishore

Department of Surgery, JIPMER, Puducherry, India

Prasanth Ganesan

Smita kayal, harichandra kumar.

Department of Biostatistics, JIPMER, Puducherry, India

Biswajit Dubashi

Department of Medical Oncology, JIPMER, Dhanvantri Nagar, Puducherry 605006, India

Associated Data

Supplemental material, sj-docx-1-tam-10.1177_17588359241248329 for Assessment of novel prognostic biomarkers to predict pathological complete response in patients with non-metastatic triple-negative breast cancer using a window of opportunity design by Chitradurga Rajashekhar Akshatha, Dhanapathi Halanaik, Rajesh Nachiappa, Nanda Kishore, Prasanth Ganesan, Smita Kayal, Harichandra Kumar and Biswajit Dubashi in Therapeutic Advances in Medical Oncology

Background:

Triple-negative breast cancer (TNBC) includes approximately 20% of all breast cancer and is characterized by its aggressive nature, high recurrence rates, and visceral metastasis. Pathological complete response (pCR) is an established surrogate endpoint for survival. The window of opportunity studies provide valuable information on the disease biology prior to definitive treatment.

Objectives:

To study the association of dynamic change in pathological, imagining, and genomic biomarkers that can prognosticate pCR. The study aims to develop a composite prognostic score.

Clinical, interventional, and prognostic biomarker study using the novel window of opportunity design.

The study aims to enroll 80 treatment-naïve, pathologically confirmed TNBC patients, administering a single dose of paclitaxel and carboplatin during the window period before neoadjuvant chemotherapy (NACT). Tumor tissue will be obtained through a tru-cut biopsy, and positron emission tomography and computed tomography scans will be performed for each patient at two time points aiming to evaluate biomarker alterations. This will be followed by the administration of standard dose-dense NACT containing anthracyclines and taxanes, with the study culminating in surgery to assess pCR.

The study would develop a composite prognostic risk score derived from the dynamic change in the Ki-67, tumor-infiltrating lymphocytes, Standardized Uptake Value (SUV max), Standardized Uptake Value for lean body mass (SUL max), and gene expression level pre- and post-intervention during the window period prior to the start of definitive treatment. This outcome will aid in categorizing the disease biology into risk categories.

Trial registration:

The current study is approved by the Institutional Ethics Committee [Ethics: Protocol. no. JIP/IEC/2020/019]. This study was registered with ClinicalTrials.gov [CTRI Registration: CTRI/2022/06/043109].

Conclusion:

The validated biomarker score will help to personalize NACT protocols in patients in TNBC planned for definitive treatment.

Plain language summary

Precision in action: unveiling predictive biomarkers for enhanced TNBC treatment

We are investigating new ways to predict how well a particular treatment will work in patients with a specific type of breast cancer called triple-negative breast cancer. The study goal is to find biomarkers that change in response to drugs to predict the complete elimination of cancer in patients before it spreads to other parts of the body. To do this, we are using a special research approach called a ‘window of opportunity design.’ This information could be valuable in personalizing and improving cancer treatments.

Introduction

Triple-negative breast cancer (TNBC) includes approximately 20–15% of all breast cancer and is characterized by its aggressive nature, high recurrence rates, and tendency to metastasize to the brain. 1 Although targeted therapies for TNBC are currently limited, around one-third of patients with TNBC can achieve a pCR with standard taxane or anthracycline chemotherapy, which is considered the standard of care. 2 pCR changes significantly among various breast cancer subtypes and is an established surrogate endpoint for survival in triple-negative and her2neu-positive breast cancer individuals. 3 The pCR is identified only after the neoadjuvant therapy is given and surgery performed. 1 The pCR rates in TNBC depend on the drugs used varying from 30% with anthracyclines and taxanes to 45% with the addition of platinum and 60% with the addition of immunotherapy. 2 Ki-67, tumor-infiltrating lymphocytes (TILs), and gene expression studies have been validated in different studies as prognostic markers and their association with pCR. Noninvasive biomarkers like positron emission tomography (PET) scan (SUV max) which exploits the metabolic activity of the tumor have recently been used in breast cancer to predict response to chemotherapy. 4

Several studies stated that patients reaching a pathological complete response (pCR) post-NACT have shown greater outcomes in comparison with those who failed to achieve it. 5 Thus, the convenience of NACT is the rapid determination of tumor response to treatment. 6 The discovery of the taxanes such as paclitaxel and docetaxel and understanding of their cytotoxicity action through cell cycle arrest by tubulin stabilization have reformed breast cancer treatment. 7 In the window of opportunity study design, newly diagnosed cancer patients awaiting neoadjuvant chemotherapy (NACT) followed by surgery receive an interventional drug during the Window of Opportunity (WoO) period which is between diagnosis and before definitive treatment. 8 The WoO studies can give information about the therapeutic efficacy and biological effects of new therapeutic techniques. 9

In the context of NACT, achieving a pCR is a significant indicator of improved survival. However, the identification of reliable biomarkers prior to NACT that can predict which patients are likely to achieve pCR remains a challenge. This proposed study seeks to bridge this by investigating a comprehensive set of pathological, imaging, and molecular biomarkers early in the treatment protocol. By utilizing the window of opportunity design, the study aims to assess how the change in these biomarkers correlates with pCR in TNBC patients and the ultimate goal is to tailor personalized treatment strategies based on a patient’s individual biomarkers profile, thereby enhancing therapeutic efficacy and patient outcome.

Review of literature

The commonly studied baseline and dynamic pathological, molecular, and imaging prognostic biomarkers in terms of response and survival are described in Table 1 .

Prognostic biomarkers in conventional and WoO breast cancer trials.

DFS, disease-free survival; FDG, fluorodeoxyglucose; NACT, neoadjuvant chemotherapy; pCR, pathological complete response; SUV, Standardized Uptake Value; TNBC, triple-negative breast cancer; TIL, tumor-infiltrating lymphocytes; VPA, valproic acid; WoO, Window of Opportunity.

Ki-67 expression is strongly associated with aggressive tumor biology and tumor proliferation, and recognition has grown for Ki-67 as an excellent prognostic biomarker. 10 High Ki67 would predict the increased proliferation of breast cancer cells and could be considered a prognostic marker. 11 Penault-Llorca et al. 12 and Breast Cancer International Research Group 001 trial recently reported that high levels of Ki-67 were predictive of benefit from adding docetaxel to fluorouracil and epirubicin chemotherapy as adjuvant treatment for patients with Estrogen receptor (ER)-positive tumors in the PACS01 randomized trial.

Thus, the data on the identification of patients benefiting from chemotherapy require confirmation before the use of Ki-67 reaches clinical utility.

Tumor-infiltrating lymphocytes

Several studies showed that the tumor microenvironment is one of the driving factors of tumor progression and invasion. 13 High TIL counts at baseline and a significant reduction in TIL counts after neoadjuvant therapy are associated with higher pCR rates. 14

Gene expression profiling

Early gene expression studies are crucial for targeting TNBC due to its molecular heterogeneity.The common genes and pathways regulated in breast cancer are described in Table 2 . They identify subtypes and predict treatment response. Early gene expression profiling facilitates the selection of treatments based on individual genetic makeup and tumor characteristics, leading to improved outcomes and reduced side effects. Studies on gene expression offer promising avenues for better patient stratification, advanced targeted therapies, and significant advancements in breast cancer treatment. Molecular profiling is a promising diagnostic approach that has the potential to provide an objective classification of metastatic cancers with an uncertain or unknown tissue of origin and to facilitate more time- and cost-effective diagnostic work-up of cancer patients. 15

Common genes and their regulation in breast cancer.

PET-computed tomography scan

A phase II study by Connolly et al. correlating SUV with pCR to pertuzumab and trastuzumab has demonstrated that early changes in SUV max by D15 of the first cycle in Her2neu-positive breast cancer correlated with pCR. 16

Experimental design

Hypothesis:

Reduction in Ki67 expression & SUV value of the tumor and alteration gene expression profile (GEP) following single dose of paclitaxel and carboplatin prior to neoadjuvant chemotherapy during window of opportunity period may predict pCR in triple negative breast cancer.

• To study the association of change in prognostic biomarkers Ki-67, TILs, FDG PET-computed tomography (CT) scan, and gene expression profiling with pCR in patients with non-metastatic TNBC following single-dose paclitaxel and carboplatin during the window period before NACT.
• To develop a composite prognostic score using the above parameters for the assessment of pCR in TNBC before NACT.

Study design

Intervention.

A single weekly dose of carboplatin (AUC-2) and paclitaxel (80 mg/m 2 ) will be given to patients as an intervention during the WoO period (diagnosis and starting of definite treatment which is usually injection paclitaxel 80 mg/m 2 in 1 unit NS in Glass bottle IV infusion over 1 h using Di(2-ethylhexyl) phthalate (DEHP) free set and 0.2-µ filter. Injection carboplatin AUC 2 was calculated using Calverts’ formula in 1 unit 5% dextrose intravenous (IV) infusion over 1 h. Dose (mg) = (GFR + 25) * 2, GFR is calculated using the Cockcroft–Gault formula.

Study setting

This is an exploratory study that uses the window of opportunity design to identify the chemo sensitiveness of the tumor before starting NACT to assess biomarkers early which can predict pCR post-NACT, thereby tailoring treatment in TNBC. Triple negativity is defined as ER and PR (0 or <1%) or Alred score of 0 and 2 HER 2 neu 0, 1+, if 2+ FISH, HER 2 no amplification. All patients fulfilling the inclusion, and exclusion criteria after obtaining consent will be included in the study. Baseline assessment of Ki-67, TILs, gene expression profiling and will be done on the initial biopsy specimen. A baseline PET scan will be performed. Patients will be receiving a single weekly dose of paclitaxel and carboplatin. On D15 of the chemotherapy, a second biopsy will be obtained to study the Ki-67, TILs, and gene expression. Before the biopsy, a hemogram is obtained the absolute neutrophil count of more than 1500 and platelets of more than 1 lakh would be the prerequisite before the second biopsy. A PET-CT scan will also be performed to study the changes in the SUV and SUL max of the tumor. Patients will then receive NACT with a standard anthracycline and taxane regimen (EC × 3 cycles followed by Doce × 4 cycles), later patients will undergo surgery. The post-surgery pathological response will be studied. pCR is a condition of a complete absence of invasive components in the axilla and breast. The study duration would be 3 years Figure 1 .

Study design.

Study duration and registration: 3 years

Primary endpoint: pCR will be defined as an absence of invasive components in the axilla and breast (yp T0 N0).

Secondary endpoint: Disease-free survival (DFS) will be defined as the duration from cancer diagnosis to relapse or death due to any cause.

The expected outcome from this project is to identify pathological, imaging, and molecular biomarkers that would predict pCR in TNBC patients using the window period before NACT. We would develop a composite prognostic score that will enable us to identify patients who will achieve pCR. This risk score needs to be validated in a larger population. Once validated, we will prospectively use this score in a clinical trial setting to decide on chemotherapy intensity in TNBC patients planned for NACT.

Study population

Eligibility criteria.

Inclusion criteria:

• Age 18–65 years.
• Newly diagnosed TNBC patients, as triple negative defined by - ER and PR score 0, HER2- negative (HER2 0 or 1+ on immunohistochemistry, or 2+ on immunohistochemistry and negative on fluorescence in situ hybridization FISH).
• Early and locally advanced breast cancer (T2/T3/T4b, with or without node-positive).
• ECOG PS 0/1.
• Planned for neo-adjuvant chemotherapy with anthracycline and taxanes.
• Bone marrow function-Hb >9 g%, absolute neutrophil count >1.5/mic L, platelet >1.5 lakhs/mic L.
• Normal renal function with serum creatinine <1.5 mg%.
• Normal liver function with serum bilirubin >1.5 mg%.
• Normal cardiac function LV ejection fraction <50%.

Exclusion criteria:

• Patient is not willing for the second biopsy.
• Previously allergic to paclitaxel and carboplatin.
• Pregnant women.
• Breastfeeding mother.
• Prior history of any other malignancy.
• Bilateral breast cancer patients.
• Patient has active local site infection.

Who will take informed consent?

Each patient diagnosed with TNBC will undergo preoperative screening to determine their eligibility based on specific inclusion and exclusion criteria. An authorized investigator will verbally convey to the patient the objectives of the study, procedures, and potential risks involved, as well as the process of treatment during the window of opportunity period. The patients receive a written informed consent form, the sheet would be provided and sufficient time would be given to the patients/guardians to go through the sheet and ask questions and clarify, which follows ICH guidelines in Good Clinical Practice.

Sample size and sampling strategy

The minimum expected AUC for establishing prognostic accuracy of the biomarkers Ki-67, PET SUV max, and the gene expression profile for estimating the sample size was 0.80 at a 5% level of significance (Software used-SYSTAT 13.2). The null hypothesis value was taken as 0.6. The ratio of non-pCR (negative outcome):pCR (positive outcome) is 70:30. The estimated sample size is 72, considering sample loss an additional 10% is added to the sample size. The ultimate estimated sample size is 80 patients.

Participant timeline

All patients with breast lumps reporting to Surgery OPD at JIPMER Pondicherry and planned for tru-cut biopsy will be screened. Baseline biopsy tissue will be collected in the RNA later. Patients who have been pathologically confirmed to have TNBC are provided with an explanation about the project and asked for their consent. All the baseline investigations will be done for the patient. Based on the report intervention, the date will be planned for the patient on the 14th or 15th day 2nd PET scan will be done in the Department of Nuclear Medicine and 2nd biopsy will be done in the Department of Surgery. Three bits of tissue are collected during 2nd biopsy; two bits are collected in a formalin container for the making FFPE, and one bit will be collected in the RNA later solution for RNA extraction fresh tissues collected from the tru-cut biopsy at two different time points are stored in the RNA later container in the −80 deep freezer FFPE blocks will be made and stored for the histopathological assessment, followed by standard of care and assessment of endpoint pCR-(ypT0N0M0) and non-pCR after obtaining the histopathology report ( Figure 2 ).

Participant timeline.

Recruitment

This study will be conducted among newly diagnosed non-metastatic TNBC patients at the healthcare center. The patients would be solicited to participate in the study. All patients will be screened as per the inclusion–exclusion criteria. If they agree to provide written informed consent, they will be considered for the biomarker study.

Methods followed in biomarker analysis

Pathological biomarkers.

The immunohistochemistry (IHC) assessment of mouse antihuman Ki-67 will be quantified using a visual scoring system. Stained cells will be counted and expressed as a percentage. Nuclear staining will be incorporated into the Ki-67 score, which is defined as the percentage of positively stained cells among the total number of malignant cells scored. The patients will be divided into two groups according to changes in the Ki-67 score namely decreased group who demonstrate a Ki-67 score of at least 1% less in the second biopsy. The no decrease group will be defined as an increase or no change in Ki-67 expression.

TIL counts will be determined on hematoxylin–eosin stained full sections using the scoring guidelines of the International Immuno-Oncology Biomarker Working Group on Breast Cancer. 32 Stromal TIL scores will be defined as the percentage of tumor stroma area that is occupied by mononuclear inflammatory cells. Inflammatory infiltrates in the stroma of noninvasive lesions and normal breast structures will be excluded from TIL counts. 33

Genomic biomarkers

Fresh tissue will be collected and RNA will be extracted using Qiagen kits.

• Phase I: RNA sequencing of 35 patients (70 samples) at two different time points.
• Phase II: Selecting the target gene (top 10 genes) based on phase I results considering the frequency of gene expression and pathways related to breast cancer followed by RT-PCR for analysis of gene expression in the 80 samples.

RNA extraction

RNA purification involves extracting high-quality RNA from biological samples while eliminating contaminants. The RNeasy technology achieves this by combining a silica-based membrane’s selective binding with microspin efficiency. The process starts with sample lysis in a denaturing guanidine–thiocyanate buffer, deactivating RNases. Ethanol is added for optimal binding, and the sample is applied to an RNeasy Mini spin column. Here, RNA (>200 bases) binds to the membrane, and impurities are washed away, followed by elution in water. Notably, RNAs <200 nucleotides are excluded, enriching mRNA. The method’s versatility is evident in tailored protocols for different samples, primarily differing in lysis, homogenization, and binding conditions, while the purification steps remain consistent, ensuring reliable results.

The Dynabeads ® mRNA purification kit streamlines the isolation of mRNA from total RNA samples through the following steps

Preparation of rna.

Begin with 75 μg of total RNA. Adjust its volume to 100 μl using distilled Diethyl pyrocarbonate (DEPC)-treated water or 10 mM Tris–HCl, pH 7.5. Heat the mixture to 65°C for 2 min to disrupt secondary structures, and then cool it on ice.

Preparation of Dynabeads ®

Take 200 μl (1 mg) of well-resuspended Dynabeads ® and place them on a magnet for 30 s to collect them against the tube wall. Remove the supernatant and calibrate the beads with 100 μl binding buffer. Afterward, add 100 μl of binding buffer to the Dynabeads ® . If the RNA is more dilute than 75 μg/100 μl, adjust the volume with binding buffer.

Isolation of mRNA

Mix the total RNA with the Dynabeads ® /binding buffer suspension to allow mRNA to anneal to the oligo(dT)25 on the beads. Rotate the mixture for 3–5 min at room temperature. Place the tube on the magnet until the solution becomes clear and remove the supernatant. Wash the mRNA-bead complex twice with 200 μl washing buffer B. Ensure efficient removal of supernatant using the magnet.

Elution of mRNA

If elution is needed, add 10–20 μl of 10 mM Tris–HCl, pH 7.5. Heat the mixture to 65–80°C for 2 min and immediately place the tube on the magnet. Transfer the eluted mRNA to a new RNase-free tube for downstream applications.

Regeneration and reuse of Dynabeads ® Oligo(dT)25

Resuspend used Dynabeads ® (original volume 200 μl) in 200 μl reconditioning solution and incubate at 65°C for 2 min. Place the tube in a magnetic field to remove the supernatant and repeat the wash with the reconditioning solution twice. Resuspend the Dynabeads ® in storage buffer oligo(dT)25 through a series of washes and magnetic separations. The Dynabeads ® are now ready for reuse in mRNA isolation.

Quality control of RNA sample

• ✓ RNA samples will be subjected to qualification and quantification using 1% agarose gel electrophoresis and Qubit/Nanodrop spectrophotometer, respectively.
• ✓ If received samples fail to meet initial QC parameters, re-sampling will be required.

Phase I : RNA sequencing of 35 patients (70 samples) at two different time points.

Workflow for mRNA sequencing on the Illumina platform

RNA Seq. library construction will be carried out using an Illumina-specific library preparation kit. mRNA will be enriched from total RNA and will be converted to cDNA as per the manufacturer’s protocol. cDNA will be used for library preparation. Fragmentation of cDNA will be carried out using the enzymatic method followed by adapter ligation. Enrichment of adapter-modified DNA fragments by PCR will be performed and quantification of the enriched library will be performed using a qubit fluorometer. Samples will be pooled before sequencing to generate defined data. Sequencing prepared libraries will be sequenced on Illumina HiSeqX/NovaSeq to generate 30 M, 2 × 150 bp reads/sample. Up to 75% of the sequenced bases will be of Q30 value. Sequenced data will be processed to generate FASTQ files and uploaded on the FTP server for download.

Data generation

Data: 4.5 GB/sample.

Platform: Illumina platform.

File format: FASTA.

Bioinformatics workflow

Quality check for raw data- Data will be checked for the bad-quality reads, bases and adapter sequences. If any adapter sequences found in the reads will be removed by appropriately trimming/removing the reads. The analysis will provide an illustrated summary of the quality of the data generated.

Preprocessing of raw data includes adapter sequence removal and contamination sequence removal (tRNA, rRNA): data will be mapped to the human genome, identify reads generated from structural RNA molecules (rRNA/tRNA), and filter them. This is the contamination removal step.

Alignment of preprocessed data to the human reference genome (hg19) using HiSAT2: the quality filtered/contamination/adapter removed data will be mapped to the human genome reference sequence (HG19) using HiSAT. The statistics for data loss at each of the three steps (quality filtering, contamination filtering, and mapping) will be recorded.

Genes expression estimation (raw) using feature counts: feature counts will be used to derive raw read counts mapping to known genes. These read counts will normalized in DESeq2, to assess gene expression levels.

Differential expression analysis will be performed using DESeq2: we use DESeq2 for identifying differentially expressed genes. Table 3 includes the Illumina stranded mRNA preparation.

Illumina stranded mRNA Prep.

FFPE, Formalin-Fixed Paraffin-Embedded; SNP, single nucleotide polymorphisms; UDI, unique dual indexes.

Phase II: Selecting the target gene (top 10 genes) based on phase I results considering the frequency of gene expression and pathways related to breast cancer results followed by RT-PCR for analysis of gene expression in the 80 samples.

Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR)

mRNA expression will be assessed using Qiagen mRNA primer sets. All qPCR reactions will be conducted on the Quant Studio™ 5 Real-Time PCR System (Applied Biosystems, ThermoFisher Scientific, USA). The synthesized cDNA will serve as the template for qPCR, employing the appropriate mRNA-specific primers and probes (QuantiTect RT-PCR Kits, Cat. No. 204443). Cycling conditions will comprise an initial heat activation step at 95°C for 2 minutes, followed by 40 cycles of denaturation at 95°C for 5 seconds and annealing/extension at 56°C for 30 seconds. Relative mRNA concentration will be determined using the relative cycle threshold method. Expression differences will be evaluated through relative quantification, normalizing the mean Ct values of the target genes to the mean Ct values of suitable endogenous controls.

Imaging biomarker

Pet-ct scan.

Participants will undergo a PET scan at baseline (post-biopsy) and D14 before the (second biopsy). All patients undergoing whole-body fluorine-18 fluorodeoxyglucose (PET/CT) (F-18 FDG PET/CT) study will be instructed to be on fasting for 4–5 h and avoid any strenuous exercises 24 h before the study. Patients will be checked for fasting blood sugar to be less than 180 mg/dl before F-18 FDG administration. F-18 FDG dose of 0.1 mCi per kg body weight is administered intravenously and image acquisition is performed after 45 min in the ‘Discovery MI digital-ready PET/CT’ model from Wipro GE Healthcare Pvt limited. A whole-body F-18 FDG PET/CT study will be performed from the base of the skull to the mid-thigh level. The images will be processed and displayed in AW 4.7 workstation (Advanced workstation from GE Healthcare Private Limited). SUV max and SUL max of the primary breast tumor will be recorded.

Biomarker analysis – Proposed method of analysis is mentioned in the Table 4 .

Biomarker analysis.

IHC, immunohistochemistry; PET-CT, positron emission tomography-computed tomography; PCR, polymerase chain reaction; TIL, tumor-infiltrating lymphocyte.

The Table 5 provides a structured timeline for when each parameter is assessed throughout the screening, intervention, and post-intervention phases, as well as during neoadjuvant chemotherapy and surgery.

Assessment schedule.

CBC, complete blood count; pCR, pathological complete response; PET-CT, positron emission tomography-computed tomography; TIL, tumor-infiltrating lymphocyte.

Project implementation

The developed composite prognostic score can be used for grouping patients based on their level of risk for the assessment of pCR in TNBC which would also help to decide chemotherapy intensity in patients planned for NACT thus, personalizing therapy.

Composite prognostic score

The composite prognostic score is a combination of multiple biomarkers and clinical parameters that have been identified as predictive factors for pCR. These could include gene expression profiles, TIL count, Ki-67 levels, and other relevant molecular and clinical features.

Grouping patients by risk

The composite prognostic score allows the grouping of TNBC patients into different risk categories based on their likelihood of achieving pCR after NACT. Patients with higher scores are likely to achieve pCR, while those with lower scores may have a lower chance of complete response.

Tailoring chemotherapy intensity

With the knowledge of the patient’s risk category, oncologists can tailor the intensity of chemotherapy accordingly. Patients at higher risk of not achieving pCR may require more aggressive and personalized chemotherapy regimens to improve their chances of a complete response.

Personalizing therapy

The composite prognostic score enables personalized therapy by guiding treatment decisions based on individual patient characteristics. Instead of a one-size-fits-all approach, patients receive treatments that are specifically designed to maximize effectiveness and minimize adverse effects.

Clinical significance

Achieving pCR in TNBC is associated with better long-term outcomes and overall survival. Thus, identifying patients likely to achieve pCR allows for the optimization of treatment strategies and potentially improves patient prognosis.

Reducing overtreatment

By stratifying patients based on their risk of pCR, the composite prognostic score can help avoid unnecessary overtreatment in patients with a high likelihood of achieving pCR. This reduces the risk of drug toxicity and associated costs.

Research and clinical implementation

The development of the composite prognostic score involves rigorous scientific research, including validation in clinical trials. If the score proves to be reliable and robust, it can be integrated into routine clinical practice to aid treatment decisions. Figure 3 depicts the project implementation plan.

Project implementation plan.

Data collection

Patient details will be entered in a standard proforma.

Data entry: Data will be entered into Microsoft Excel as a spreadsheet.

Data extraction: The data extraction process for this exploratory study employing the window of opportunity design entails a comprehensive collection of various data points at distinct junctures throughout the investigation. Initially, baseline data is gathered, encompassing patient demographics, confirmation of triple-negative breast cancer (TNBC) status based on estrogen receptor (ER), progesterone receptor (PR), and HER2/neu expression, along with adherence to inclusion and exclusion criteria. Baseline biomarker assessments, including Ki67 expression levels, tumor-infiltrating lymphocytes (TILs) assessment, and gene expression profiling from the initial biopsy specimen, are meticulously recorded alongside baseline PET scan results. During the chemotherapy phase, meticulous monitoring of treatment administration, patient clinical status, and adverse events occurs, while hemogram results and second biopsy findings, such as Ki67 expression levels, TILs assessment, and gene expression changes, are documented. Additionally, PET CT scan results are analyzed to discern changes in Standardized Uptake Value (SUV) and Standardized Uptake Value of lean body mass (SUL) max of the tumor. Post-surgery, data includes completion of the neoadjuvant chemotherapy regimen, surgical outcomes detailing the type and extent of tumor removal, lymph node involvement, and post-surgery pathological response assessment, particularly focusing on the presence or absence of invasive components in the axilla and breast, as well as evaluation of pathological complete response (pCR) status. Long-term follow-up extends over a duration of 3 years, monitoring for disease recurrence, metastasis, and survival outcomes, all meticulously documented to ensure comprehensive analysis and interpretation while upholding ethical standards and patient confidentiality throughout.

Privacy and confidentiality

Participants in this trial will receive unique identification codes, and all data collected will be de-identified. Identifiable participant information will be stored separately, and patient-reported data will only be used for this study. This approach ensures privacy and confidentiality. During the trial, strict confidentiality measures will be implemented to safeguard all collected information. Personal sensitive data, including full names, contact information, and identification details, will not be included in the clinical research Performa. All data will be processed confidentially to ensure privacy and protect participants’ identities.

Statistical analysis

Statistical methods for primary and secondary outcomes.

The categorical variables such as clinical characteristics, histopathological profile, comorbidity, etc. will be expressed as percentages and frequency. The continuous data such as Ki-67, gene expression, SUV, and age, will be expressed as median with range or mean with standard deviation. The change in the Ki-67, gene expression, and SUV over time will be explored by paired t -test otherwise Wilcoxon signed-rank sum test. The comparison of the change in Ki-67, gene expression, and SUV concerning pCR status will be carried out using a Mann–Whitney U test or independent student’s t -test. The association of the pCR status with different categorical variables mentioned above will be carried out using Fisher’s exact test or chi-square test. Kaplan–Meier curve will be utilized to estimate the survival function and a log-rank test will be done to compare the same between different characteristics. All statistical analysis will be estimated at a 5% level of significance and p value.

The multiple logistic regression analysis will be done to estimate the odds ratio with a 95% confidence interval to investigate the correlation between candidate prognostic markers and pCR. 34 The final selection of prognostic variables will be based on the change in Ki-67, TILs, SUV max and SUL max value, and gene expression profiling. The selected predictors will be given a weightage or a score by multiplying their corresponding regression coefficients (β) by a factor of 10. Further categorization of the derived score (low, moderate, high) will be based on dividing the range of scores into tertiles. Receiver Operating Characteristic (ROC) curve will be plotted and the resulting Area Under the Curve (AUC) value will be used to compare the pCR outcomes based on the derived prognostic score model.

In this study, preoperative setup emphasizes the chance to assess biomarkers change and surrogate endpoints of cancer in vivo in response to the interventional drug. Currently, a potent approach to personalize chemotherapy in the early stages of TNBC does not exist. Regardless of significant response rates in a subgroup of patients, mostly all patients will receive the same number of cycles of chemotherapy. NACT decreases tumor size, improves surgical outcomes, and evaluates chemotherapy response. However, tailored therapies based on the pathological response have not been well established. One of the reasons to lag in tailoring personalized therapy is there are no established biomarkers that have been identified before NACT to identify patients likely to achieve pCR. These biomarkers may be clinical, biological, or imaging. Clinical and demographic features, such as menstrual status, family history, racial disparity, patient’s age, and mammographic breast density, have been associated with pCR in various studies.

Ki-67 expression was considerably associated with tumor proliferation and has been recognized Ki-67 as an excellent biomarker. 35 In meta-analysis study carried out by Wu et al. in the TNBC population stated that the pooled results of 35 studies showed that highly expressing Ki-67 was correlated with overall survival of poor DFS. 17 Arnaout et al. carried out a study in a window of opportunity set up in ER-positive breast cancer patients, where the patient received anastrozole as an interventional drug during the window period and found a statistically significant fall of 48.8% in mean Ki-67 indices while comparing pre-treatment Ki-67 indices with post-treatment. 18

Several studies showed that the tumor microenvironment can be one of the driving factors of tumor invasion and progression. High TIL counts at baseline and a significant reduction in TIL counts after neoadjuvant therapy are associated with higher pCR rates. 36 Elevated expression of CD4+ TIL count significantly correlates with better DFS and OS. 14 Studies reported that a high CD8+ TIL level was associated with better DFS only as no statistical association was found with OS. 19 The increased FOXP3+ TIL level also was correlated only with DFS but not with OS. 37 In TNBC, tumors having the highest TIL score achieved 37% of pCR, and those exhibiting high apoptosis showed 47%. 20 Therapeutic drugs such as pembrolizumab can elevate sTILs, thereby increasing the mean dispersion of TILs in naïve TNBC tumors. 38 A phase II study carried out by Connolly et al. 39 in the breast cancer population to know the correlation of SUV with pCR to trastuzumab and pertuzumab, thereby, found that post-SUL max value and delta SUL max value correlated with pCR. A study conducted in the primary breast cancer population stated that pCR significantly correlates with post-SUV max value. 40

Mostly, primary tumors will be identified based on IHC and morphological assessment; however, these biomarkers exhibit significantly lesser sensitivities in TNBC comparatively ER-positive breast cancer. Molecular profiling is a promising diagnostic approach that is believed to aid in the classification of metastatic cancers with an unknown primary tissue origin. 41 Wang et al. 24 reported a small subgroup of genes from the 90 panel of genes aiding diagnostic utility in the TNBC subgroup, where they found 17 genes were upregulated, 15 genes were downregulated, and recognized as candidate genes to differentiate TNBC from other types of malignancy. Interesting research conducted in a primary breast cancer population of 25 patients found that 125 genes were upregulated, and 116 genes were downregulated at 24 h of NACT followed by 193 genes upregulated, 238 genes downregulated at 48 h of NACT, surprisingly, significant transcriptional response occurred in all patients during therapy which is supporting the hypothesis that genes respond to drugs within the short period. 42

Utilization of a window of opportunity design to assess biomarker changes before NACT and also to check the chemotherapy tolerance in patients. During the waiting period (window of opportunity), patients are administered a single dose of chemotherapy to offset any potential delays in receiving dose-dense chemotherapy. Due to the study intervention involving a single shot and a low dose, the expected toxicity is anticipated to be minimal. Potential to enhance treatment outcomes by predicting pCR and guiding therapy based on individual biomarker profiles. Addressing the need for reliable biomarkers to predict pCR in TNBC patients undergoing NACT contributes to the understanding of biomarkers associated with treatment response in TNBC and may inform future clinical trials.

Personalized treatment: Aim to develop a predictive score for identifying TNBC patients likely to achieve pCR, leading to tailored treatment strategies.

Limitations

Transcriptomic analysis in the current study will be done for only a small sample size which may or may not represent the large population. The primary endpoint of the study is pCR which is only a surrogate endpoint to overall survival which would be ideal.

Supplemental Material

Acknowledgments.

We thank Dr Vijai Joseph, Associate Attending Geneticist, Department of Medicine, MSKCC, Associate Professor of Genetics Research in Medicine, Weill Cornell Medical Center, Cornell University, Associate Director, Bioinformatics, Niehaus Center for Inherited Cancer Genomics, MSKCC and Dr. P. S. Suresh, Assistant Professor, School of Biotechnology, National Institute of Technology, Calicut, Kerala, India for their valuable suggestions in designing the protocol.

Supplemental material: Supplemental material for this article is available online.

Contributor Information

Chitradurga Rajashekhar Akshatha, Department of Medical Oncology, JIPMER, Puducherry, India.

Dhanapathi Halanaik, Department of Nuclear Medicine, JIPMER, Puducherry, India.

Rajesh Nachiappa Ganesh, Department of Pathology, JIPMER, Puducherry, India.

Nanda Kishore, Department of Surgery, JIPMER, Puducherry, India.

Prasanth Ganesan, Department of Medical Oncology, JIPMER, Puducherry, India.

Smita Kayal, Department of Medical Oncology, JIPMER, Puducherry, India.

Harichandra Kumar, Department of Biostatistics, JIPMER, Puducherry, India.

Biswajit Dubashi, Department of Medical Oncology, JIPMER, Dhanvantri Nagar, Puducherry 605006, India.

Declarations

Ethics approval and consent to participate: The current study is approved by the Institutional Ethics Committee [Ethics: Protocol. No. JIP/IEC/2020/019]. This study was registered with ClinicalTrials.gov [CTRI Registration: CTRI/2022/06/043109]. Informed consent was obtained from all participants involved in the study.

Consent for publication: Not applicable.

Author contributions: Chitradurga Rajashekhar Akshatha: Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Project administration; Resources; Software; Validation; Visualization; Writing – original draft; Writing – review & editing.

Rajesh Nachiappa G: Formal analysis; Methodology; Supervision; Validation.

Nanda Kishore Maroju: Investigation; Methodology; Resources; Supervision; Validation.

Prasanth Ganesan: Investigation; Supervision.

Smita Kayal: Investigation; Supervision.

Harichandra Kumar: Data curation; Formal analysis; Methodology.

Biswajit Dubashi: Conceptualization; Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Resources; Software; Supervision; Validation; Visualization; Writing – original draft; Writing – review & editing.

Funding: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The project is funded by the Indian Council of Medical Research-Ad hoc extramural grant award number No.5/13/14/2022/NCD-III and Intramural research fund – JIPMER.

The authors declare that there is no conflict of interest.

Availability of data and materials: No new data were created or analyzed in this study. Data sharing is not applicable to this article.