The molecular landscape of high-risk early breast cancer: comprehensive biomarker analysis of a phase III adjuvant population

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.

Genomic Alterations Associated with Recurrence and TNBC Subtype in High-Risk Early Breast Cancers

“…S7A), it was significantly prognostic in the entire breast cancer population, where high expression was associated with good prognosis (Supplementary Fig. S7), and this association was most pronounced in TNBCs (P ¼ 0.041), as previously observed (12). High CD8 gene expression weakly trended with better DFS in the HR þ and HER2 þ subgroups, but this effect was not statistically significant.…”

“…In order to define the genomic landscape of a clinically defined, high-risk early breast cancer population, we profiled the primary breast cancers of patients who experienced a DFS event following adjuvant chemotherapy within the USO01062 study (15). Of the 2,611 enrolled patients, 1,181 patients had tumor tissue available for genomic profiling (12). Of the 1,181 patients, 145 patients experienced a DFS event and were selected for NGS profiling ( Supplementary Fig.…”

“…Interestingly, TNBC cell lines classified according to Lehmann and colleagues displayed different sensitivities to chemotherapeutics and/or targeted therapies, suggesting that different genomic alterations may drive each subtype. Additional work from other groups, including our own, has shown that the TNBC subtypes have implications for pathologic complete response rates following neoadjuvant therapy (10,11) and for disease-free survival (DFS) following adjuvant chemotherapy (12). To date, the mutational and copy-number profiles associated with the TNBC subtype have not been fully characterized.…”

Tumor-Infiltrating Lymphocytes in Patients Receiving Trastuzumab/Pertuzumab-Based Chemotherapy: A TRYPHAENA Substudy

“…Sample processing and RNA extraction for gene expression profiling are described in the Supplementary Methods (available online). Gene expression data from the NanoString nCounter assay (previously reported custom designed 800-gene panel tailored for breast cancer [12]) were analyzed after quality control filtering and normalization using the R package NanoStringQCPro (version 0.99.8.3). As recommended, the mean of the positive probes and the housekeeping genes were used in order to account for differences in sample input.…”

Association of single nucleotide polymorphisms in FGF-RAS/MAP signalling cascade with breast cancer susceptibility

“…Large studies of genomic modifications and protein expression involved in breast tumorigenic pathways identified several differently penetrating polymorphisms associated with this disease and provided an increasing number of targets for drugs which significantly improve patient prognosis (Easton et al 2007;Fachal and Dunning 2015;Michailidou et al 2015). Emerging evidence from clinical trials has proven also that specific genetic background and molecular landscapes significantly influence the sensitivity and resistance profile (Wilson et al 2016;Zardavas and Piccart-Gebhart 2016;Miller et al 2017;Toss et al 2017). Moreover, identification of molecular signatures and gene expression profiling is increasingly inevitable for full understanding of the tumorigenesis, especially in personalised targeted medicine (Ellsworth et al 2010;Pereira et al 2016).…”