Insights into breast cancer phenotying through molecular omics approaches and therapy response

Abstract

Breast cancer is the most common cancer in the world. Despite advances in early detection and understanding of the molecular bases of breast cancer biology, approximately 30% of all patients with early-stage breast cancer have metastatic disease. Breast cancers are comprised of molecularly distinct subtypes that respond differently to pathway-targeted therapies and neoadjuvant systemic therapy. However, no tumor response is observed in some cases and development of resistance is most commonly seen in patients with heterogeneous breast cancer subtype. To offer better treatment with increased efficacy and low toxicity of selecting therapies, new technologies that incorporate clinical and molecular characteristics of intratumoral heterogeneity have been investigated. This short review provides some examples of integrative omics approaches (genome, epigenome, transcriptome, immune profiling) and mathematical/computational analyses that provide mechanistic and clinically relevant insights into underlying differences in breast cancer subtypes and patients'responses to specific therapies.

Keywords: Breast cancer; ERBB/HER; endocrine and targeted therapy; epigenomics; estrogen receptor; genomics; progesterone receptor; proteomics.

Figure 1

Kaplan-Meier curves of time for distant metastasis (A) and overall survival (B) among five breast cancer subtypes in two patient cohorts. This figure is quoted with permission from Sorlie et al.^[33]

Figure 2

Heatmap of RNA expression (z-scores) of the PAM50 gene set in 1904 breast tumors samples from METABRIC cohort. The visual representation of clustered gene patterns associated with subtypes Basal, Luminal B, luminal A, HER-enriched and Normal-like (left to right order). Each rows correspond to a gene and each column to a patient sample. The data of BAG1, PPR160 and TMEM45B were not included. The heatmap was generated using cBioPortal tools (https://www.cbioportal.org/)