Abstract
Breast cancer is a heterogeneous disease and patients are managed clinically based on ER, PR, HER2 expression, and key risk factors. We sought to characterize the molecular landscape of high-risk breast cancer patients enrolled onto an adjuvant chemotherapy study to understand how disease subsets and tumor immune status impact survival. DNA and RNA were extracted from 861 breast cancer samples from patients enrolled onto the United States Oncology trial 01062. Samples were characterized using multiplex gene expression, copy number, and qPCR mutation assays. HR+ patients with a PIK3CA mutant tumor had a favorable disease-free survival (DFS; HR 0.66, P=0.05), however, the prognostic effect was specific to luminal A patients (Luminal A: HR 0.67, P=0.1; Luminal B: HR 1.01, P=0.98). Molecular subtyping of triple-negative breast cancers (TNBCs) suggested that the mesenchymal subtype had the worst DFS, whereas the immunomodulatory subtype had the best DFS. Profiling of immunologic genes revealed that TNBC tumors (n=280) displaying an activated T-cell signature had a longer DFS following adjuvant chemotherapy (HR 0.59, P=0.04), while a distinct set of immune genes was associated with DFS in HR+ cancers. Utilizing a discovery approach, we identified genes associated with a high risk of recurrence in HR+ patients, which were validated in an independent data set. Molecular classification based on PAM50 and TNBC subtyping stratified clinical high-risk patients into distinct prognostic subsets. Patients with high expression of immune-related genes showed superior DFS in both HR+ and TNBC. These results may inform patient management and drug development in early breast cancer.
Highlights
Breast cancer can be molecularly classified into luminal A and luminal B subgroups that are mostly comprised of hormone-receptorpositive (HR+) breast cancers; a basal-like subgroup that is mostly comprised of triple-negative breast cancers (TNBC); a HER2-enriched subgroup that is mostly comprised of HER2+ breast cancers and a normal-like subgroup that has been proposed to be mostly comprised of the contaminating tumor-surrounding stroma.[6]
Molecular profiling of the USO 01062 patient population To profile the molecular heterogeneity of patients enrolled onto this study, we developed a custom 800-gene expression panel that is comprised of various gene and pathway signatures relevant to breast cancer biology, a 35-gene copy-number alteration (CNA) panel and a targeted mutation panel
A key question in this patient population is the molecular definition of high-risk characteristics in order to identify patients who may benefit from cytotoxic therapy, and to identify predictors of poor prognosis that can be targeted therapeutically
Summary
Breast cancer is a heterogeneous disease that is categorized clinically by immunohistochemical (IHC) staining of the three receptors; estrogen receptor (ER), progesterone receptor (PR), and the human epidermal growth factor receptor-2 (ERBB2/HER2).[1]Seminal studies in the early 2000s demonstrated that gene expression signatures could classify breast cancers into distinct and reproducible molecular subgroups.[2,3,4,5] In essence, breast cancer can be molecularly classified into luminal A and luminal B subgroups that are mostly comprised of hormone-receptorpositive (HR+) breast cancers; a basal-like subgroup that is mostly comprised of triple-negative breast cancers (TNBC); a HER2-enriched subgroup that is mostly comprised of HER2+ breast cancers and a normal-like subgroup that has been proposed to be mostly comprised of the contaminating tumor-surrounding stroma.[6]. Large genomic analyses have provided crucial insights into the genetic landscape of breast cancer.[8,9,10,11,12,13,14] For example, a high prevalence of PIK3CA mutations and cyclin D1 amplification are observed in the luminal subtypes, whereas a high prevalence of mutation in TP53 and alterations in DNA repair enzymes are observed in the basal-like subtype of breast cancer These findings suggest that breast cancer is a complex and heterogeneous disease wherein distinct subtypes have diverse biological drivers. Recent advances in the area of cancer immunotherapy have shown that tumors with tumor infiltrating lymphocytes (TILs) have a higher pathological complete response (pCR) rate in the Received 24 November 2015; revised 3 June 2016; accepted 10 June 2016
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