Moderate-Low Risk Breast Cancer Gene Expression in a Romanian Population

TL;DR

This study examines gene expression in moderate-low risk breast cancer cases in a Romanian population to better understand genetic factors influencing cancer development.

Contribution

The study identifies pathogenic variants in moderate and low-risk genes among a Romanian cohort, emphasizing their relevance in breast cancer risk assessment.

Findings

CHEK2 was the most frequently mutated moderate-risk gene with 13 pathogenic variants.

Only three pathogenic mutations were found in low-risk genes, including MSH1 and MLH1.

Reporting low-risk and insufficient evidence mutations improves understanding of breast cancer risk in diverse populations.

Abstract

Multigene panel testing for hereditary breast and ovarian cancer is becoming a standard in medical care. Recent studies highlight the importance of pathogenic variants in genes with moderate or low penetrance. 255 consecutive breast cancer cases who met the criteria for genetic testing were approached by next-generation sequencing. From 104 pathogenic mutations identified, 21 were in moderate-risk genes, three in low-risk genes and eight in the group with insufficient evidence genes. The most frequent PVs in moderate-risk genes were in the CHEK2 gene—Checkpoint kinase 2 gene (13 cases), the ATM gene—Ataxia-telangiectasia Mutated gene (six cases), BARD1—BRCA1-associated ring domain 1 gene (one case) and RAD 51C–radiation sensitive 51 Paralog C—(one case) genes. Among the low-risk genes, we identified only three pathogenic mutations (two in MSH1 gene—melanocyte-stimulating hormone gene—and one in MLH1 gene—MutL homolog 1 gene). Reporting on low-risk mutations and those with insufficient evidence regarding breast cancer risk is valuable to enable a more comprehensive view of genetic factors influencing disease development and improve screening protocols, tailor diagnostic strategies, and individualize treatment plans. This approach also enhances our understanding of BC risk in various populations, potentially leading to new insights into genetic contributions to cancer and the refinement of risk models for patient care.

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