Adenomas from individuals with pathogenic biallelic variants in the MUTYH and NTHL1 genes demonstrate base excision repair tumour mutational signature profiles similar to colorectal cancers, expanding potential diagnostic and variant classification applications.

Background: Colorectal cancers (CRCs) from people with biallelic germline likely pathogenic/pathogenic variants in MUTYH or NTHL1 exhibit specific single base substitution (SBS) mutational signatures, namely combined SBS18 and SBS36 (SBS18+SBS36), and SBS30, respectively. The aim was to determine if adenomas from biallelic cases demonstrated these mutational signatures at diagnostic levels.

Methods: Whole-exome sequencing of FFPE tissue and matched blood-derived DNA was performed on 9 adenomas and 15 CRCs from 13 biallelic MUTYH cases, on 7 adenomas and 2 CRCs from 5 biallelic NTHL1 cases and on 27 adenomas and 26 CRCs from 46 non-hereditary (sporadic) participants.

Polygenic score distribution differences across European ancestry populations: implications for breast cancer risk prediction.

Background: The 313-variant polygenic risk score (PRS) provides a promising tool for clinical breast cancer risk prediction. However, evaluation of the PRS across different European populations which could influence risk estimation has not been performed.

Methods: We explored the distribution of PRS across European populations using genotype data from 94,072 females without breast cancer diagnosis, of European-ancestry from 21 countries participating in the Breast Cancer Association Consortium (BCAC) and 223,316 females without breast cancer diagnosis from the UK Biobank.

Menopausal hormone therapy: assessing associations with breast and colorectal cancers by familial risk.

Menopausal users of hormone replacement therapy (HRT) are at increased breast cancer risk and decreased colorectal cancer (CRC) risk compared with individuals who have never used HRT, but these opposing associations may differ by familial risk of breast cancer and CRC. We harmonized data from 3 cohorts and generated separate breast cancer and CRC familial risk scores based on cancer family history. We defined moderate or strong family history as a risk score of 0.

Artificial intelligence improves mammography-based breast cancer risk prediction.

Artificial intelligence (AI) is enabling us to delve deeply into the information inherent in a mammogram and identify novel features associated with high risk of a future breast cancer diagnosis. Here, we discuss how AI is improving mammographic density-associated risk prediction and shaping the future of screening and risk-reducing strategies.