Academic Background and Problem Statement

Loss-of-Function (LOF) mutations in Tumor Suppressor Genes (TSGs) are prevalent in cancer. However, therapeutic strategies directly targeting these mutations are challenging due to the loss or reduction of encoded protein function, which in normal states plays a role in inhibiting aberrant cell proliferation or genomic instability. As most traditional drugs target active functions of oncogenic proteins, innovative approaches are needed to uncover vulnerabilities conferred by these LOF mutations and identify potential therapeutic targets. KMT2D, a tumor suppressor gene widely mutated in various cancers, is closely implicated in cancer initiation and progression. Despite this relevance, the functional network of KMT2D and the vulnerabilities associated with its LOF mutations remain underexplored.

This study aimed to computationally map KMT2D’s genetic interaction networks, uncover its functional associations, and identify cancer cell vulnerabilities, particularly through Synthetic Lethality (SL) interactions. SL refers to a scenario in which the concurrent inactivation of two genes results in cell death, while the disruption of either gene individually does not affect cell viability. By applying this concept, the authors hoped to identify dependencies in KMT2D-mutant cancer cells, providing new opportunities for cancer treatment.

Source and Author Information

This research was conducted by Yuka Takemon et al. and involved multiple research institutions, including the BC Cancer Research Centre and the Genome Sciences Centre, Canada. The paper was published in the journal Genome Medicine in 2024, titled “Mapping in silico genetic networks of the KMT2D tumour suppressor gene to uncover novel functional associations and cancer cell vulnerabilities.”

Research Workflow and Methods

1. Development of KMT2D Knockout Cell Lines

The researchers developed KMT2D knockout HEK293A cell lines (KMT2DKO) using Zinc Finger Nuclease (ZFN) technology targeting exon 39 of the KMT2D gene. The functional knockout was validated via immunoblotting and DNA sequencing.

2. Chromatin Immunoprecipitation-Mass Spectrometry (ChIP-MS)

To investigate KMT2D’s protein interaction network, the authors performed ChIP-MS. Using SILAC (Stable Isotope Labeling by Amino acids in Cell Culture) labeling, they compared protein interactions between wild-type and KMT2D knockout cell lines and identified 532 potential chromatin-associated protein interactors.

3. Computational Genetic Network Mapping

The researchers utilized their custom R software tool, GRETTA, to systematically map KMT2D’s genetic network using CRISPR-Cas9 screening data from the Cancer Dependency Map (DepMap). By analyzing knockout effects of 18,333 genes across 739 cancer cell lines, they identified potential synthetic lethal and alleviating lethality interactions.

4. Candidate Gene Prioritization

The team applied differential lethality analyses and classified 4,396 genetic interactions (GIs). These interactions were ranked based on statistical significance and drug target tractability, leading to the identification of several high-confidence therapeutic targets, including MDM2, TUB1B, NDUFB5, and WRN.

Key Findings

1. Functional Associations in KMT2D’s Genetic Network

KMT2D LOF mutations were associated with genes involved in histone modifications, metabolism, and immune responses. Of particular note, WRN was predicted as a novel synthetic lethal target. Experimental validation confirmed that MSI cancer cell lines with KMT2D mutations were significantly more sensitive to WRN inhibitors compared to MSI cell lines without KMT2D mutations.

2. Enrichment of DNA Replication and Repair Functions

KMT2D’s protein interaction network revealed significant enrichment for DNA replication and repair functions. These findings indicate that, beyond its role in histone modification, KMT2D may also play a role in maintaining genomic stability.

3. Identification and Validation of Novel Synthetic Lethal Targets

The computational analyses identified several promising synthetic lethal targets, including MDM2, TUB1B, NDUFB5, and WRN. These targets are either currently under therapeutic development or associated with well-known cancer vulnerabilities, reinforcing their potential in treating KMT2D-mutant cancers.

Conclusion and Significance

This study demonstrates the utility of computational and experimental methods in uncovering cancer vulnerabilities caused by tumor suppressor gene LOF mutations. By identifying candidate synthetic lethal targets, this work highlights actionable opportunities for therapeutic intervention in KMT2D-mutant cancers, particularly through the targeting of WRN, which holds promise for MSI cancers.

Research Highlights

1. Innovative Methodology: The integration of computational and experimental approaches enabled the systematic mapping of KMT2D’s genetic networks and the identification of associated synthetic lethal vulnerabilities.
2. Novel Synthetic Lethal Targets: The study identified several targets, most notably WRN, which shows potential for therapeutic advancements in MSI cancers.
3. Broad Applicability: The framework developed in this study could be adapted to investigate vulnerabilities and therapeutic targets associated with other tumor suppressor gene mutations.

Summary

This research systematically revealed vulnerabilities associated with KMT2D LOF mutations and proposed multiple promising synthetic lethal targets. By characterizing the genetic and protein interaction networks of KMT2D, the study provided novel insights into cancer biology and highlighted potential drug development opportunities, with significant scientific and clinical implications.