A novel gene signature to predict response to neoadjuvant chemotherapy and endocrine treatment in estrogen receptor-positive breast cancer patients

Author:

Sionakidis Aristeidis1ORCID,Cannings Timothy I.2,Figueroa Jonine D.2ORCID,Sims Andrew H.2

Affiliation:

1. University of Edinburgh

2. The University of Edinburgh

Abstract

Abstract Purpose: Neoadjuvant treatment (NAT) of early breast cancer is increasingly being used to downstage tumors, allowing improved chances of breast-conserving surgery.Here we combine data from multiple studies to identify pre-treatment and on-treatment biomarkers of response to NAT with the potential to lead to more efficient patient stratification. Methods: We pool and analyse 10 independent NAT studies that have publicly available gene expression data (1861 samples, 1020 patients). Differential gene expression analysis was conducted on the pooled samples to derive a NAT response signature (NRS) and two NAT response subtypes. The NRS was then used along with additional variables to train a NAT response classifier. We use an additional 4 studies (418 samples, 258 patients) to further evaluate the performance of our classifier. Results: We identified 166 deferentially expressed genes between responders and non-responders, which are mainly involved in cell cycle and DNA repair pathways. We derive two molecular subtypes associated with NAT response and other clinical predictors. Our NAT response classifier achieves an Area Under the Curve (AUC) of 0.79 on a held-out test set (134 samples). Remarkably, in one external validation study, AUC increased from 0.64 to 0.82 when focusing on the estrogen receptor positive (ER+) samples only. Conclusion: We report a set of markers that are differentially expressed in NAT responders and demonstrate how they can be used to predict response to NAT for ER+ patients with early stage breast cancer, which might allow for improved risk stratification, surveillance or different treatments.

Publisher

Research Square Platform LLC

Reference134 articles.

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4. Arran K Turnbull and Laura M Arthur and Lorna Renshaw and Alexey A Larionov and Charlene Kay and Anita K Dunbier and Jeremy S Thomas and Mitch Dowsett and Andrew H Sims and J Michael Dixon (2015) Accurate prediction and validation of response to endocrine therapy in breast cancer. Journal of Clinical Oncology 33: 2270-2278 https://doi.org/10.1200/JCO.2014.57.8963, https://pubmed.ncbi.nlm.nih.gov/26033813/, American Society of Clinical Oncology, 26033813, 10, Adjuvant,Antineoplastic Agents,Apoptosis Regulatory Proteins / genetics,Aromatase Inhibitors / therapeutic use*,Arran K Turnbull,Biomarkers,Biopsy,Breast Neoplasms / diagnostic imaging,Breast Neoplasms / drug therapy*,Breast Neoplasms / genetics*,Breast Neoplasms / pathology,Chemotherapy,Cytokine Receptor gp130 / genetics,Disease-Free Survival,Female,Gene Expression Profiling* / methods,Gene Expression Regulation,Hormonal / therapeutic use*,Humans,Immunohistochemistry,J Michael Dixon,Kaplan-Meier Estimate,Laura M Arthur,Letrozole,MEDLINE,Minichromosome Maintenance Complex Component 4 / g,NCBI,NIH,NLM,National Center for Biotechnology Information,National Institutes of Health,National Library of Medicine,Neoadjuvant Therapy*,Neoplastic,Nerve Tissue Proteins / genetics,Nitriles / therapeutic use*,Non-U.S. Gov't,Oligonucleotide Array Sequence Analysis,Precision Medicine,Predictive Value of Tests,PubMed Abstract,Reproducibility of Results,Research Support,Reverse Transcriptase Polymerase Chain Reaction,Time Factors,Treatment Outcome,Triazoles / therapeutic use*,Tumor / genetics*,Ultrasonography,Validation Study,doi:10.1200/JCO.2014.57.8963,pmid:26033813, 20, 15277755, Purpose Aromatase inhibitors (AIs) have an established role in the treatment of breast cancer. Response rates are only 50% to 70% in the neoadjuvant setting and lower in advanced disease. Accurate biomarkers are urgently needed to predict response in these settings and to determine which individuals will benefit from adjuvant AI therapy. Patients and Methods Pretreatment and on-treatment (after 2 weeks and 3 months) biopsies were obtained from 89 postmenopausal women who had estrogen receptor-alpha positive breast cancer and were receiving neoadjuvant letrozole for transcript profiling. Dynamic clinical response was assessed with use of three-dimensional ultrasound measurements. Results The molecular response to letrozole was characterized and a four-gene classifier of clinical response was established (accuracy of 96%) on the basis of the level of two genes before treatment (one gene [IL6ST] was associated with immune signaling, and the other [NGFRAP1] was associated with apoptosis) and the level of two proliferation genes (ASPM, MCM4) after 2 weeks of therapy. The four-gene signature was found to be 91% accurate in a blinded, completely independent validation data set of patients treated with anastrozole. Matched 2-week on-treatment biopsies were associated with improved predictive power as compared with pretreatment biopsies alone. This signature also significantly predicted recurrence-free survival (P = .029) and breast cancer -specific survival (P= .009). We demonstrate that the test can also be performed with use of quantitative polymerase chain reaction or immunohistochemistry. Conclusion A four-gene predictive model of clinical response to AIs by 2 weeks has been generated and validated. Deregulated immune and apoptotic responses before treatment and cell proliferation that is not reduced 2 weeks after initiation of treatment are functional characteristics of breast tumors that do not respond to AIs.

5. Yeon Hee Park and Samir Lal and Jeong Eon Lee and Yoon La Choi and Ji Wen and Sripad Ram and Ying Ding and Soo Hyeon Lee and Eric Powell and Se Kyung Lee and Jong Han Yu and Keith A Ching and Jae Yong Nam and Seok Won Kim and Seok Jin Nam and Ji Yeon Kim and Soo Youn Cho and Seri Park and Jinho Kim and Soohyn Hwang and Yu Jin Kim and Vinicius Bonato and Diane Fernandez and Shibing Deng and Shuoguo Wang and Hyuntae Shin and Eun Suk Kang and Woong Yang Park and Paul A Rejto and Jadwiga Bienkowska and Zhengyan Kan (2020) Chemotherapy induces dynamic immune responses in breast cancers that impact treatment outcome. Nature Communications 11 https://doi.org/10.1038/s41467-020-19933-0, https://pubmed.ncbi.nlm.nih.gov/33268821/, Nature Research, 33268821, 10, Anthracyclines / therapeutic use,B7-H1 Antigen / antagonists & inhibitors,B7-H1 Antigen / genetics*,B7-H1 Antigen / immunology,Breast / drug therapy*,Breast / genetics,Breast / immunology,Breast / mortality,Breast Neoplasms / drug therapy*,Breast Neoplasms / genetics,Breast Neoplasms / immunology,Breast Neoplasms / mortality,CD8-Positive T-Lymphocytes / drug effects,CD8-Positive T-Lymphocytes / immunology,CD8-Positive T-Lymphocytes / pathology,Carcinoma,Cell Cycle Proteins / genetics,Cell Cycle Proteins / immunology,Cyclophosphamide / therapeutic use,Disease-Free Survival,Docetaxel / therapeutic use,Ductal,ErbB-2 / genetics,ErbB-2 / immunology,Estrogen Receptor alpha / genetics,Estrogen Receptor alpha / immunology,Female,Gene Expression Profiling,Gene Expression Regulation,Humans,Immunity,Innate,Interferon Regulatory Factors / genetics,Interferon Regulatory Factors / immunology,Longitudinal Studies,Lymphocytes,MEDLINE,NCBI,NIH,NLM,National Center for Biotechnology Information,National Institutes of Health,National Library of Medicine,Neoadjuvant Therapy / methods*,Neoplasm,Neoplastic*,Non-U.S. Gov't,PMC7710739,PubMed Abstract,Receptor,Research Support,Residual,Samir Lal,Trastuzumab / therapeutic use,Treatment Outcome,Tumor Microenvironment / drug effects,Tumor Microenvironment / genetics,Tumor Microenvironment / immunology,Tumor-Infiltrating / drug effects*,Tumor-Infiltrating / immunology,Tumor-Infiltrating / pathology,Yeon Hee Park,Zhengyan Kan,doi:10.1038/s41467-020-19933-0,pmid:33268821, 1, 20411723, To elucidate the effects of neoadjuvant chemotherapy (NAC), we conduct whole transcriptome profiling coupled with histopathology analyses of a longitudinal breast cancer cohort of 146 patients including 110 pairs of serial tumor biopsies collected before treatment, after the first cycle of treatment and at the time of surgery. Here, we show that cytotoxic chemotherapies induce dynamic changes in the tumor immune microenvironment that vary by subtype and pathologic response. Just one cycle of treatment induces an immune stimulatory microenvironment harboring more tumor infiltrating lymphocytes (TILs) and up-regulation of inflammatory signatures predictive of response to anti-PD1 therapies while residual tumors are immune suppressed at end-of-treatment compared to the baseline. Increases in TILs and CD8 + T cell proportions in response to NAC are independently associated with pathologic complete response. Further, on-treatment immune response is more predictive of treatment outcome than immune features in paired baseline samples although these are strongly correlated.

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