# Case Report: A combination of CHEK2 and high polygenic risk score leads to early-onset male breast cancer

## TL;DR

A 42-year-old man with a high polygenic risk score and a CHEK2 mutation developed early-onset male breast cancer, showing how genetic factors can contribute to rare cancers.

## Contribution

This case report demonstrates the combined impact of a CHEK2 mutation and high polygenic risk score in causing early-onset male breast cancer.

## Key findings

- A pathogenic CHEK2 nonsense variant and a high polygenic risk score were identified in a 42-year-old man with breast cancer.
- Tumor sequencing confirmed the presence of germline variants but showed no evidence of MSH6-related tumor instability.
- The case highlights the potential of polygenic risk scores in assessing early-onset male breast cancer risk.

## Abstract

Male breast cancer (MBC) is a rare disease, accounting for about 1% of all breast cancer cases worldwide. Compared to female breast cancer (FBC), MBC shows a higher prevalence of hormone receptor positivity and distinct germline predispositions, most frequently pathogenic variants in BRCA2 and CHEK2. The contribution of mismatch repair (MMR) genes such as MSH6 to MBC risk remains, however, unclear. In addition, polygenic risk scores (PRS) have emerged as promising tools for breast cancer risk prediction but are not yet used in routine care. We report the case of a 42-year-old man diagnosed with invasive carcinoma of no special type, strongly estrogen receptor–positive, HER2-negative, and with a family history of breast and prostate cancer. Genetic testing revealed a pathogenic CHEK2 nonsense variant (p.Trp411*), a likely pathogenic MSH6 frameshift variant, and a breast cancer PRS in the 99th percentile. Tumor sequencing confirmed both germline variants but showed microsatellite stability and no loss of heterozygosity, arguing against a causal role of MSH6. This case illustrates how PRS, in combination with moderate-risk variants, like those in CHEK2, may drive early-onset MBC and highlights the need to incorporate polygenic models into risk assessment and counseling.