A Stromal Immune Module Correlated with the Response to Neoadjuvant Chemotherapy, Prognosis and Lymphocyte Infiltration in HER2-Positive Breast Carcinoma Is Inversely Correlated with Hormonal Pathways

RESEARCH ARTICLE A Stromal Immune Module Correlated with the Response to Neoadjuvant Chemotherapy, Prognosis and Lymphocyte Infiltration in HER2-Positive Breast Carcinoma Is Inversely Correlated with Hormonal Pathways a11111 Anne-Sophie Hamy1☯, Hélène Bonsang-Kitzis1,2☯, Marick Lae3, Matahi Moarii4,5, Benjamin Sadacca1,6, Alice Pinheiro1, Marion Galliot1, Judith Abecassis1,4,5, Cecile Laurent1, Fabien Reyal1,2* 1 Institut Curie, PSL Research University, Translational Research Department, INSERM, U932 Immunity and Cancer, Residual Tumor & Response to Treatment Laboratory (RT2Lab), Paris, France, 2 Department of Surgery, Institut Curie, Paris, France, 3 Department of Tumor Biology, Institut Curie, Paris, France, 4 Mines Paristech, PSL-Research University, CBIO-Centre for Computational Biology, Mines ParisTech, Fontainebleau, France, 5 U900, INSERM, Institut Curie, Paris, France, 6 Laboratoire de Mathématiques et Modélisation d’Evry, Université d’Évry Val d’Essonne, Evry, France OPEN ACCESS Citation: Hamy A-S, Bonsang-Kitzis H, Lae M, Moarii M, Sadacca B, Pinheiro A, et al. (2016) A Stromal Immune Module Correlated with the Response to Neoadjuvant Chemotherapy, Prognosis and Lymphocyte Infiltration in HER2Positive Breast Carcinoma Is Inversely Correlated with Hormonal Pathways. PLoS ONE 11(12): e0167397. doi:10.1371/journal.pone.0167397 Editor: William B. Coleman, University of North Carolina at Chapel Hill School of Medicine, UNITED STATES Received: September 19, 2016 Accepted: November 14, 2016 Published: December 22, 2016 Copyright: © 2016 Hamy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: All relevant data are within the paper and its Supporting Information files. Funding: A-S Hamy-Petit was supported by an ITMO-INSERM-AVIESAN cancer translational research grant. Funding was also obtained from the Site de Recherche Intégrée en Cancérologie/ INstitut National du Cancer (InCa-DGOS-4654). The funders had no role in study design, data ☯ These authors contributed equally to this work. * Abstract Introduction HER2-positive breast cancer (BC) is a heterogeneous group of aggressive breast cancers, the prognosis of which has greatly improved since the introduction of treatments targeting HER2. However, these tumors may display intrinsic or acquired resistance to treatment, and classifiers of HER2-positive tumors are required to improve the prediction of prognosis and to develop novel therapeutic interventions. Methods We analyzed 2893 primary human breast cancer samples from 21 publicly available datasets and developed a six-metagene signature on a training set of 448 HER2-positive BC. We then used external public datasets to assess the ability of these metagenes to predict the response to chemotherapy (Ignatiadis dataset), and prognosis (METABRIC dataset). Results We identified a six-metagene signature (138 genes) containing metagenes enriched in different gene ontologies. The gene clusters were named as follows: Immunity, Tumor suppressors/proliferation, Interferon, Signal transduction, Hormone/survival and Matrix clusters. In all datasets, the Immunity metagene was less strongly expressed in ER-positive than in ER-negative tumors, and was inversely correlated with the Hormonal/survival metagene. Within the signature, multivariate analyses showed that strong expression of the PLOS ONE | DOI:10.1371/journal.pone.0167397 December 22, 2016 1 / 19 Immune Module in HER2+ Breast Cancer Is Predictive of Response to Chemotherapy and Prognosis collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. Abbreviations: BC, breast cancer; BCSS, breast cancer-specific survival; BC_CL, breast cancer cell lines; CCLE, Cancer Cell Line Encyclopedia; CGP, Cancer Genome Project; ER, estrogen receptor; GE, gene expression; HER2-positive BC, HER2-positive breast cancer; HER2, human epidermal growth factor receptor 2; PR, progesterone receptor; pCR, pathological complete response; RMA, robust multichip average; TILs, tumor-infiltrating lymphocytes. “Immunity” metagene was associated with higher pCR rates after NAC (OR = 3.71[1.28– 11.91], p = 0.019) than weak expression, and with a better prognosis in HER2-positive/ERnegative breast cancers (HR = 0.58 [0.36–0.94], p = 0.026). Immunity metagene expression was associated with the presence of tumor-infiltrating lymphocytes (TILs). Conclusion The identification of a predictive and prognostic immune module in HER2-positive BC confirms the need for clinical testing for immune checkpoint modulators and vaccines for this specific subtype. The inverse correlation between Immunity and hormone pathways opens research perspectives and deserves further investigation. Introduction HER2-positive breast carcinomas (BCs) are defined by amplification and overexpression of the HER2 tyrosine kinase receptor gene (17q12). The tumors of this subgroup have aggressive pathological features and a high rate of early distant metastatic events. They are routinely treated with a combination of docetaxel plus a monoclonal antibody targeting the HER2 receptor (trastuzumab). Other drugs also appear to be of major interest and will probably be made available for routine treatment in the near future (lapatinib, pertuzumab and T-DM1). HER2-positive BCs constitute a heterogeneous group of tumors differing in histological features, gene expression profiles, clinical behavior, overall prognosis, and response to conventional systemic cytotoxic therapy. Trastuzumab-based treatments have been used for the last decade and have substantially improved outcomes in patients with early or metastatic HER2positive BC. However, some HER2-positive tumors display intrinsic or acquired resistance to trastuzumab. Robust classifiers are required, both to improve our understanding of the molecular basis of HER2-positive BC and to develop novel therapeutic interventions. We developed a two-step biological network-driven gene selection process: 1) identification of the most variable genes displaying highly correlated patterns of expression, 2) direct connection of these genes within known biological networks. This method has been shown to construct molecular signatures efficiently [1–3]. We defined a HER2-positive molecular subtype classification and identified a stromal immune module gene expression profile strongly correlated with predicted response to chemotherapy, prognosis and lymphocytic infiltration. This classification provides considerable biological insight, and has potential for use in the development of therapeutic interventions, such as novel immunotherapies in particular. Material and methods Data normalization and quality control Training, (...truncated)