Available online 18 June 2022

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 hormonal receptors, HER2, Ki67, multiple gene expression assays, PD-L1 testing, mismatch repair deficiency/microsatellite instability, tumor mutational burden, PIK3CA, ESR1, NTRK and briefly introduced the roles of digital imaging analysis in breast biomarker evaluation.

Introduction

Breast cancer is the most common cancer in women worldwide and is still the second leading cause of cancer-related death in developed countries despite advances in diagnoses and treatment1. In 2021, the newly diagnosed female breast cancer and number of female breast cancer death were estimated to be 281,550 and 43,600 in the United States, respectively2.

Breast cancer represents a heterogeneous group of human cancer at both histological and molecular levels. Traditionally, breast cancer was evaluated upon the tumor characteristics such as its histopathologic type, grade, size, lymph nodal status and distant metastasis. Advancements in tumor biology and prognostic and predictive biomarkers have led to increased diagnostic accuracy and more personalized treatments. The 8th edition of American Joint Committee on Cancer (AJCC) Staging Manual integrates traditional anatomic staging with biological factors including ER, PR, HER2 and multigene assays to create a Clinical Prognostic Stage Group3. Other than prognosis, some biomarkers also serve as predictive markers aiding in determining therapeutic plans for individual patients4,5. With the increased understanding of the molecular characterization of breast cancer and the emergency of novel targeted therapies, more biomarkers have been extensively studied. In this review, we summarized several main prognostic and predictive biomarkers in breast cancer at genomic, transcriptomic and proteomic levels.

Section snippetsHormone receptors (HRs)

ER, PR and androgen receptor (AR) belong to the steroid receptor superfamily. After binding to the corresponding hormone, these receptors are activated and behave as transcription factors by binding to the promoters of their target genes. In the absence of the hormone, they can alternatively be activated through phosphorylation by kinases6.

Breast development is regulated by hormones. Consequently, breast cancer is often hormone-dependent. Endocrine therapies are efficacious and have relatively

Estrogen receptor (ER)

ER is the earliest breast cancer biomarker studied and is expressed in about 70-84% of breast cancer4,7, 8, 9, 10. ER positive breast cancer tend to be better differentiated, less aggressive and have a better prognosis and overall survival (OS) compared to ER negative breast cancer11. ER is the most important predictive biomarker for all endocrine-based therapies in early and advanced stage of ER positive breast cancer5,12. The application of adjuvant tamoxifen-based therapy showed a 29%

Progesterone receptor (PR)

PR is an ER-regulated gene which is critical for the mammary gland development31. PR is expressed in 75% of ER positive breast cancer4,32. Both ER and PR function in mammary gland development and tumorigenesis. Assessing them together will guide the hormonal therapy response33.

PR status is evaluated through IHC. Based on the ASCO/CAP guidelines, it is considered positive if ≥ 1% of tumor cell nuclei are immunoreactive22. A cut off value of 20% is recommended by the European Society for Medical

Androgen receptor (AR)

AR is expressed in 70-85% of breast cancer and is more frequently expressed in ER positive breast cancer5,42. There is no universal threshold for defining AR positivity in breast cancer and most studies with IHC defined positivity in ≥1% or 10% of tumor cells43, 44, 45. The effect of AR varies significantly based on the concomitant expression of ER and HER2. AR expression is associated with a better prognosis in breast cancer when all subtypes included or in ER positive breast cancer. The

Human epidermal growth factor receptor 2 (HER2)

HER2 is a transmembrane glycoprotein with tyrosine kinase activity. HER2 belongs to the human epidermal growth factor receptor (HER/EGFR/ERBB) family. The HER2 protein has the capability to form heterodimers with HER1, HER3 or HER4 and homodimers when its expression level is high. Dimerization of HER2 results in phosphorylation of the tyrosine in the cytoplasmic domain and initiates signaling through PI3K/AKT and Ras/Raf/MEK/MAPK signal pathways, thus is involved in cell proliferation,

Ki67

Ki67 is a marker of cell proliferation and is expressed in all cell-cycle phases except in G068. It is scored as percentage of tumor cells stained by the antibodies. Ki67 expression level is often associated with tumor grade and biologic behavior68,69. Most studies demonstrated that high Ki67 conferred a worse prognosis70, 71, 72, while other studies showed no significant relationship between Ki67 and DFS and OS68,73. Several clinical trials do not support Ki67 as a predictive factor for the

Digital imaging analysis of breast biomarkers

Breast biomarkers are routinely evaluated by pathologists’ manual estimation under microscopy. Inter-observer variability commonly occurs during manual evaluation of breast biomarkers such as ER/PR76, 77, 78, 79, 80, 81, 82, 83, 84 and HER2 IHC55,85,86. Recent widespread implementation of whole slide imaging (WSI) has promoted more pathologists to adopt digital image analysis (DIA) to evaluate breast biomarkers, which has been proven to provide objective reproducible results87, 88, 89. (Figure 4

Oncotype DX and other gene expression assays

Multiple commercially available gene expression assays have been developed and validated for HR-positive, HER2-negative, early-stage breast cancer. These assays analyze multiple gene RNA expression levels to generate scores to predict recurrence risk and benefit from adjuvant therapy, and therefore, to guide decision making for the use of adjuvant therapy.

Others

Other gene expression assays with similar indications are commercially available, including MammaPrint (BluePrint), Prosigna Breast Cancer Prognostic Gene Signature Assay (PAM50), Breast Cancer Index (BCI) and EndoPredict (EPclin).

The MammaPrint assay (Agendia, Amsterdam, the Netherlands) is a 70-Gene genomic test, measuring genes involved in tumor proliferation, metastasis, angiogenesis, and other disease processes, to provide a genomic risk score (categorized into low or high risk) for

PD-L1 (SP142 and 22C3) IHC testing

PD-L1 IHC testing is an emerging predictive biomarker to select patients with triple negative breast cancer (TNBC) for immunotherapy. Two PD-L1 assays, namely SP142 and 22C3, were approved by the FDA as companion diagnostics to select patients for use of specific checkpoint inhibitors atezolizumab (monoclonal anti-PD-L1 antibody) and pembrolizumab (monoclonal anti-PD-1 antibody), respectively134, 135, 136, 137, 138.

In SP142 assay (Roche Ventana, Tucson, AZ), PD-L1 expression is evaluated by

Summary

In the era of precision medicine, pathologists and oncologists should have knowledge of appropriate biomarker tests for different clinical contexts. We have discussed current breast cancer prognostic and/or predictive biomarkers and their related clinical implications. With the increased understanding of the molecular characterization of breast cancers, novel targeted therapies with potential biomarkers are also warranted for developing more personalized treatments for breast cancer patients.

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