ARTICLE ABSTRACT
Li-Fraumeni syndrome (LFS) is an autosomal dominant cancer-predisposition disorder. Approximately 70% of individuals who fit the clinical definition of LFS harbour a pathogenic germline variant in the TP53 tumour suppressor gene. However, the remaining 30% of patients lack a TP53 variant and even among variant TP53 carriers, approximately 20% remain cancer-free. Understanding the variable cancer penetrance and phenotypic variability in LFS is critical to developing rational approaches to accurate, early tumour detection and risk-reduction strategies. We leveraged family-based whole-genome sequencing and DNA methylation to evaluate the germline genomes of a large, multi-institutional cohort of LFS patients (n=396) with variant (n=374) or wildtype TP53 (n=22). We identified alternative cancer-associated genetic aberrations in 8/14 wildtype TP53 carriers who developed cancer. Among variant TP53 carriers, 19/49 who developed cancer harboured a pathogenic variant in another cancer gene. Modifier variants in the WNT signaling pathway were associated with decreased cancer incidence. Furthermore, we leveraged the non-coding genome and methylome to identify inherited epimutations in genes including ASXL1, ETV6 and LEF1 that confer increased cancer risk. Using these epimutations, we built a machine learning model that can predict cancer risk in LFS patients with an AUROC of 0.725 [0.633-0.810].
