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

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 (KMT2DLOF) 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.