A new gene expression signature, the ClinicoMolecular Triad Classification, may improve prediction and prognostication of breast cancer at the time of diagnosis

Introduction When making treatment decisions, oncologists often stratify breast cancer (BC) into a low-risk group (low-grade estrogen receptor-positive (ER+)), an intermediate-risk group (high-grade ER+) and a high-risk group that includes Her2+ and triple-negative (TN) tumors (ER-/PR-/Her2-). None of the currently available gene signatures correlates to this clinical classification. In this study, we aimed to develop a test that is practical for oncologists and offers both molecular characterization of BC and improved prediction of prognosis and treatment response. Methods We investigated the molecular basis of such clinical practice by grouping Her2+ and TN BC together during clustering analyses of the genome-wide gene expression profiles of our training cohort, mostly derived from fine-needle aspiration biopsies (FNABs) of 149 consecutive evaluable BC. The analyses consistently divided these tumors into a three-cluster pattern, similarly to clinical risk stratification groups, that was reproducible in published microarray databases (n = 2,487) annotated with clinical outcomes. The clinicopathological parameters of each of these three molecular groups were also similar to clinical classification. Results The low-risk group had good outcomes and benefited from endocrine therapy. Both the intermediate- and high-risk groups had poor outcomes, and their BC was resistant to endocrine therapy. The latter group demonstrated the highest rate of complete pathological response to neoadjuvant chemotherapy; the highest activities in Myc, E2F1, Ras, β-catenin and IFN-γ pathways; and poor prognosis predicted by 14 independent prognostic signatures. On the basis of multivariate analysis, we found that this new gene signature, termed the "ClinicoMolecular Triad Classification" (CMTC), predicted recurrence and treatment response better than all pathological parameters and other prognostic signatures. Conclusions CMTC correlates well with current clinical classifications of BC and has the potential to be easily integrated into routine clinical practice. Using FNABs, CMTC can be determined at the time of diagnostic needle biopsies for tumors of all sizes. On the basis of using public databases as the validation cohort in our analyses, CMTC appeared to enable accurate treatment guidance, could be made available in preoperative settings and was applicable to all BC types independently of tumor size and receptor and nodal status. The unique oncogenic signaling pathway pattern of each CMTC group may provide guidance in the development of new treatment strategies. Further validation of CMTC requires prospective, randomized, controlled trials.