| Autor: |
Yuka Takemon, Erin D. Pleasance, Alessia Gagliardi, Christopher S. Hughes, Veronika Csizmok, Kathleen Wee, Diane L. Trinh, Ryan D. Huff, Andrew J. Mungall, Richard A. Moore, Eric Chuah, Karen L. Mungall, Eleanor Lewis, Jessica Nelson, Howard J. Lim, Daniel J. Renouf, Steven JM. Jones, Janessa Laskin, Marco A. Marra |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Genome Medicine, Vol 16, Iss 1, Pp 1-31 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
1756-994X |
| DOI: |
10.1186/s13073-024-01401-9 |
| Popis: |
Abstract Background Loss-of-function (LOF) alterations in tumour suppressor genes cannot be directly targeted. Approaches characterising gene function and vulnerabilities conferred by such mutations are required. Methods Here, we computationally map genetic networks of KMT2D, a tumour suppressor gene frequently mutated in several cancer types. Using KMT2D loss-of-function (KMT2D LOF) mutations as a model, we illustrate the utility of in silico genetic networks in uncovering novel functional associations and vulnerabilities in cancer cells with LOF alterations affecting tumour suppressor genes. Results We revealed genetic interactors with functions in histone modification, metabolism, and immune response and synthetic lethal (SL) candidates, including some encoding existing therapeutic targets. Notably, we predicted WRN as a novel SL interactor and, using recently available WRN inhibitor (HRO761 and VVD-133214) treatment response data, we observed that KMT2D mutational status significantly distinguishes treatment-sensitive MSI cell lines from treatment-insensitive MSI cell lines. Conclusions Our study thus illustrates how tumour suppressor gene LOF alterations can be exploited to reveal potentially targetable cancer cell vulnerabilities. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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