Update on prognostic and predictive biomarkers of breast cancer.

Abstract

Breast cancer represents a heterogeneous group of human cancer at both histological and molecular levels. Estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) are the most commonly used biomarkers in clinical practice for making treatment plans for breast cancer patients by oncologists. Recently, PD-L1 testing plays an important role for immunotherapy for triple-negative breast cancer. With the increased understanding of the molecular characterization of breast cancer and the emergence of novel targeted therapies, more potential biomarkers are needed for the development of more personalized treatments. In this review, we summarized several main prognostic and predictive biomarkers in breast cancer at genomic, transcriptomic and proteomic levels, including hormone receptors, HER2, Ki67, multiple gene expression assays, PD-L1 testing, mismatch repair deficiency/microsatellite instability, tumor mutational burden, PIK3CA, ESR1 andNTRK and briefly introduced the roles of digital imaging analysis in breast biomarker evaluation.

• Authors: Yanjun Hou, Yan Peng, Zaibo Li
• Journal: Seminars in diagnostic pathology (Semin Diagn Pathol) Vol. 39 Issue 5 Pg. 322-332 (Sep 2022) ISSN: 0740-2570 [Print] United States
• PMID: 35752515 (Publication Type: Journal Article, Review)
• Copyright: Copyright © 2022. Published by Elsevier Inc.

Chemical References

• B7-H1 Antigen
• Biomarkers, Tumor
• Receptors, Estrogen
• Receptor, ErbB-2

Topics

• B7-H1 Antigen (metabolism)
• Biomarkers, Tumor (genetics)
• Breast Neoplasms (genetics, pathology)
• Female
• Humans
• Prognosis
• Proteomics
• Receptor, ErbB-2 (genetics, metabolism)
• Receptors, Estrogen (genetics, metabolism)
• Triple Negative Breast Neoplasms (metabolism, pathology)