Insights into Molecular Classifications of Triple-Negative Breast Cancer: Improving Patient Selection for Treatment

Abstract

Triple-negative breast cancer (TNBC) remains the most challenging breast cancer subtype to treat. To date, therapies directed to specific molecular targets have rarely achieved clinically meaningful improvements in outcomes of patients with TNBC, and chemotherapy remains the standard of care. Here, we seek to review the most recent efforts to classify TNBC based on the comprehensive profiling of tumors for cellular composition and molecular features. Technologic advances allow for tumor characterization at ever-increasing depth, generating data that, if integrated with clinical-pathologic features, may help improve risk stratification of patients, guide treatment decisions and surveillance, and help identify new targets for drug development. SIGNIFICANCE: TNBC is characterized by higher rates of relapse, greater metastatic potential, and shorter overall survival compared with other major breast cancer subtypes. The identification of biomarkers that can help guide treatment decisions in TNBC remains a clinically unmet need. Understanding the mechanisms that drive resistance is key to the design of novel therapeutic strategies to help prevent the development of metastatic disease and, ultimately, to improve survival in this patient population.

Conflict of interest statement

Disclosure of Potential Conflicts of Interest: K.P. is a Scientific Advisory Board member of Mitra Biotech. N.U.L. receives research funding from Pfizer, Genentech, Kadmon, Novartis, Array Biopharma, and she is also a consultant to Genentech, Novartis, Seattle Genetics, and Daichii. No potential conflict of interest was disclosed by A.C.G.C.

©2019 American Association for Cancer Research.

Figures

Figure 1.

Overview of the complex interactions between molecular classifications of TNBC based on genomic, transcriptomic, proteomic, epigenomic and immune characterization of the tumor and its microenvironment. ER: estrogen receptor; PR: progesterone receptor; CNA: copy number alterations; AR: androgen receptor; HRD: homologous recombination deficiency; IHC: immunohistochemistry; TIL: tumor-infiltrating lymphocytes.

Figure 2.

Distribution of intrinsic subtypes among TNBC and distribution of TNBC among basal-like breast cancer. A, Comparison of distribution of intrinsic subtypes defined by PAM50 and PAM50+Claudin-low in TCGA and METABRIC datasets in triple-negative breast cancer (TNBC). TNBC was defined as clinical ER, PR and HER2 negative testing per IHC. In TCGA, 88 TNBC samples had available PAM50 data. The distribution of intrinsic subtypes was: basal-like (86%), HER2-enriched (6%), luminal-A (5%), luminal-B (1%), and normal-like (2%). In METABRIC, 320 TNBC samples had available intrinsic subtype data. When including claudin-low in the PAM50 predictor, the distribution of subtypes was: basal-like (49%), claudin-low (37%), HER2-enriched (9%), normal-like (4%), luminal-A (1%), and luminal-B (0%). When excluding the 119 samples with claudin-low subtype, the distribution of subtypes was: basal-like (78%), HER2-enriched (15%), normal-like (5%), luminal-A (2%), and luminal-B (0%). B, Comparison of distribution of breast cancer subtype according to receptor status defined by IHC in TCGA and METABRIC datasets in basal-like breast cancer. Of 98 basal-like breast cancers in TCGA, 78% were TNBC per IHC. Of 209 basal-like breast cancers (PAM50+Claudin-low classifier) in METABRIC, 75% were TNBC. Figures generated by re-analysis of publicly available (22,36,37) using cBioPortal (150,151).