Cancer-driving mutations are enriched in genic regions intolerant to germline variation

Abstract

Large reference datasets of protein-coding variation in human populations have allowed us to determine which genes and genic sub-regions are intolerant to germline genetic variation. There is also a growing number of genes implicated in severe Mendelian diseases that overlap with genes implicated in cancer. Here, we hypothesized that mitotically mutable genic sub-regions that are intolerant to germline variation are enriched for cancer-driving mutations. We introduce a new metric, OncMTR, which uses 125,748 exomes in the gnomAD database to identify genic sub-regions intolerant to germline variation but enriched for hematologic somatic variants. We demonstrate that OncMTR can significantly predict driver mutations implicated in hematologic malignancies. Divergent OncMTR regions were enriched for cancer-relevant protein domains, and overlaying OncMTR scores on protein structures identified functionally important protein residues. Finally, we performed a rare variant, gene-based collapsing analysis on an independent set of 394,694 exomes from the UK Biobank and find that OncMTR dramatically improves genetic signals for hematologic malignancies. Our web app enables easy visualization of OncMTR scores for each protein-coding gene (https://astrazeneca-cgr-publications.github.io/OncMTR-Viewer/).

The frequency of somatic mutations in cancer predicts the phenotypic relevance of germline mutations

“…Thus the frequency with which a gene is somatically mutated in cancer is associated to IPA independently of whether such mutations contribute to oncogenesis. It should be noted that driver status was the strongest predictor of IPA in this model, in agreement with the overlap between cancer drivers and disease genes found in previous studies (Kaplanis et al, 2020;Vitsios et al, 2022).…”

“…Therefore, the deep relationship we found between tumor somatic mutations and genetic diseases is different and complementary to that investigated in works, such as (Kaplanis et al, 2020;Vitsios et al, 2022), which consider only driver mutations. While the relationship between cancer-driving mutations and genetic diseases is likely rooted in gene function, the predictive power of total somatic mutations is likely rooted in their ability to represent which mutations are compatible with the survival of the cell, and hence can be observed and have phenotypic effects in human subjects.…”

“…This observation extends to other cancer related genes, such as ATRX and KDM5C involved in X-linked mental disability (Gibbons et al, 1995), KMT2D and KDM6A in Kabuki syndrome (Ng et al, 2010;Lederer et al, 2012), SQSTM1 in Paget disease (Ralston and Albagha, 2014), and DMNT3A in Tatton-Brown-Rahman syndrome (Tatton-Brown et al, 2014), while mutations of chromatin remodelers play crucial roles in both cancer and neurodevelopmental disorders (Ronan et al, 2013). Recently, a significant overlap was found between 285 newly identified genes associated to developmental delay and cancer drivers (Kaplanis et al, 2020), and cancer-driving mutations were found to be enriched in genomic regions intolerant of variation (Vitsios et al, 2022). Here, we set out to investigate systematically the extent to which the mutational spectrum of cancer and that of genetic disorders overlap.…”

A novel syndrome caused by the constitutional gain-of-function variant p.Glu1099Lys in NSD2

“…On a variant level, there is a significant overlap between somatic driver mutations in (hematologic) malignancies and ( de novo ) germline variants causing NDD. Both de novo missense variants identified in large NDD cohorts and somatic driver variants in cancer 17 are enriched in constrained genomic regions. These observations seem plausible, because many of the overlapping genes are central to cellular processes and similar mutational mechanisms affect both somatic and germline cells.…”

“…On a variant level, there is a significant overlap between somatic driver mutations in (hematologic) malignancies and (de novo) germline variants causing NDD. Both de novo missense variants identified in large NDD cohorts and somatic driver variants in cancer 17 Prominent examples for cancer associated genes with two distinct associated NDD entities based on different molecular alterations caused by the underlying variants include epigenetic regulators like DNMT3A (OMIM #618724, "Heyn-Sproul-Jackson syndrome"; OMIM #615879, "Tatton-Brown-Rahman syndrome" 18 ) and SETD2 (OMIM #616831, "Luscan-Lumish syndrome"; a clinically distinguishable disorder associated with GoF missense variants at AA position Arg1740 recently described by Rabin and colleagues 19 ). Likely further similar entities caused by distinct functional effects of disease-causing variants in the same gene are to be discovered.…”