Prognostic and predictive biomarkers with therapeutic targets in breast cancer: A 2022 update on current developments,evidence,and recommendations

Abstract

Objective

To evaluate and validate the recent and emerging data for prognostic and predictive biomarkers with therapeutic targets in breast cancer.

Data sources

A literature search from January 2015 to March 2022 was performed using the key terms breast cancer, clinical practice guidelines, gene mutations, genomic assay, immune cancer therapy, predictive and/or prognostic biomarkers, and targeted therapies.

Study selection and data extraction

Relevant clinical trials, meta-analyses, seminal articles, and published evidence- and consensus-based clinical practice guidelines in the English language were identified, reviewed and evaluated.

Data synthesis

Breast cancer is a biologically heterogeneous disease, leading to wide variability in treatment responses and survival outcomes. Biomarkers for breast cancer are evolving from traditional biomarkers in immunohistochemistry (IHC) such as estrogen receptor (ER), progesterone receptor (PR) and epidermal growth factor receptor type 2 (HER2) to genetic biomarkers with therapeutic implications (e.g. breast cancer susceptibility gene 1/2 [BRCA1/2], estrogen receptor α [ESR1] gene mutation, HER2 gene mutation, microsatellite instability [MSI], phosphatidylinositol 3-kinase catalytic subunit 3Cα [PIK3CA] gene mutation, neurotrophic tyrosine receptor kinase [NTRK] gene mutation). In addition, current data are most robust for biomarkers in immunotherapy (e.g. programmed cell death receptor ligand-1 [PD-L1], microsatellite instability-high [MSI-H] or deficient mismatch repair [dMMR]). Oncotype DX assay remains the best validated gene expression assay that is both predictive and prognostic whereas MammaPrint is prognostic for genomic risk.

Conclusions

Biomarker-driven therapies have the potential to confer greater therapeutic advantages than standard-of-care therapies. The purported survival benefits associated with biomarker-driven therapies should be weighed against their potential harms.