Mapping in silico genetic networks of the KMT2D tumour suppressor gene to uncover novel functional associations and cancer cell vulnerabilities.

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.