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Title: | Cancer-driving mutations are enriched in genic regions intolerant to germline variation. | Austin Authors: | Vitsios, Dimitrios;Dhindsa, Ryan S;Matelska, Dorota;Mitchell, Jonathan;Zou, Xuequing;Armenia, Joshua;Hu, Fengyuan;Wang, Quanli;Sidders, Ben;Harper, Andrew R;Petrovski, Slavé | Affiliation: | General Medicine Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK.. Bioinformatics and Data Science, Research, and Early Development, Oncology R&D, AstraZeneca, Cambridge, UK.. Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA.. |
Issue Date: | 26-Aug-2022 | Date: | 2022 | Publication information: | Science Advances 2022; 8(34): eabo6371 | Abstract: | Large reference datasets of protein-coding variation in human populations have allowed us to determine which genes and genic subregions 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. We hypothesized that cancer-driving mutations might be enriched in genic subregions that are depleted of germline variation relative to somatic variation. We introduce a new metric, OncMTR (oncology missense tolerance ratio), which uses 125,748 exomes in the Genome Aggregation Database (gnomAD) to identify these genic subregions. 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. Last, 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 markedly improves genetic signals for hematologic malignancies. | URI: | https://ahro.austin.org.au/austinjspui/handle/1/30797 | DOI: | 10.1126/sciadv.abo6371 | ORCID: | 0000-0002-8939-5445 0000-0002-8965-0813 0000-0003-0798-3479 0000-0002-1756-7551 0000-0003-2733-3078 0000-0002-1527-961X |
Journal: | Science Advances | PubMed URL: | 36026442 | Type: | Journal Article |
Appears in Collections: | Journal articles |
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