Genomic Characteristics of Triple-Negative Breast Cancer Nominate Molecular Subtypes That Predict Chemotherapy Response

Abstract

The heterogeneity of triple-negative breast cancer (TNBC) poses difficulties for suitable treatment and leads to poor outcome. This study aimed to define a consensus molecular subtype (CMS) of TNBC and thus elucidate genomic characteristics and relevant therapy. We integrated the expression profiles of 957 TNBC samples from published datasets. We identified genomic characteristics of subtype by exploring the pathway activity, microenvironment, and clinical relevance. In addition, drug response (DR) scores (n = 181) were computationally investigated using chemical perturbation gene signatures and validated in our own patient with TNBC (n = 38) who received chemotherapy and organoid biobank data (n = 64). Subsequently, cooperative functions with drugs were also explored. Finally, we classified TNBC into four CMSs: stem-like; mesenchymal-like; immunomodulatory; luminal-androgen receptor. CMSs also elucidated distinct tumor-associated microenvironment and pathway activities. Furthermore, we discovered metastasis-promoting genes, such as secreted phosphoprotein 1 by comparing with primary. Computational DR scores associated with CMS revealed drug candidates (n = 18), and it was successfully evaluated in cisplatin response of both patients and organoids. Our CMS recapitulated in-depth functional and cellular heterogeneity encompassing primary and metastatic TNBC. We suggest DR scores to predict CMS-specific DRs and to be successfully validated. Finally, our approach systemically proposes a relevant therapeutic prediction model as well as prognostic markers for TNBC. IMPLICATIONS: We delineated the genomic characteristic and computational DR prediction for TNBC CMS from gene expression profile. Our systematic approach provides diagnostic markers for subtype and metastasis verified by machine-learning and novel therapeutic candidates for patients with TNBC.