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Large-scale analysis of KMT2 mutations defines a distinctive molecular subset with treatment implication in gastric cancer

Abstract

Frequent mutations of genes in the histone-lysine N-methyltransferase 2 (KMT2) family members were identified in gastric cancers (GCs). Understanding how gene mutations of KMT2 family affect cancer progression and tumor immune microenvironment may provide new treatment strategies. A total of 1245 GCs were analyzed using next-generation sequencing, whole transcriptome sequencing, immunohistochemistry (Caris Life Sciences, Phoenix, AZ). The overall mutation rate of genes in the KMT2 family was 10.6%. Compared to KMT2-wild-type GCs, genes involved in epigenetic modification, receptor tyrosine kinases/MAPK/PI3K, and DNA damage repair (DDR) pathways had higher mutation rates in KMT2-mutant GCs (p < 0.05). Significantly higher rates of high tumor mutational burden, microsatellite instability-high/mismatch-repair deficiency (dMMR), and PD-L1 positivity were observed in KMT2-mutant GCs (p < 0.01), compared to KMT2-wild-type GCs. The association between PD-L1 positivity and KMT2 mutations remained significant in the proficient-MMR and microsatellite stable subgroup. Based on transcriptome data from the TCGA, cell cycle, metabolism, and interferon-α/β response pathways were significantly upregulated in KMT2-mutant GCs than in KMT2-wild-type GCs. Patients with KMT2 mutation treated with immune checkpoint inhibitors had longer median overall survival compared to KMT2-wild-type patients with metastatic solid tumors (35 vs. 16 months, HR = 0.73, 95% CI: 0.62–0.87, p = 0.0003). In conclusion, this is the largest study to investigate the distinct molecular features between KMT2-mutant and KMT2-wild-type GCs to date. Our data indicate that GC patients with KMT2 mutations may benefit from ICIs and drugs targeting DDR, MAPK/PI3K, metabolism, and cell cycle pathways.

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Fig. 1: Overview of KMT2 mutations in GC.
Fig. 2: Molecular characteristics of KMT2-MT vs. KMT2-WT GC in the CARIS database.
Fig. 3: Genomic and transcriptomic characteristics of KMT2-MT vs. KMT2-WT GCs in the TCGA database.
Fig. 4: The association of KMT2 mutations with the efficacy of ICIs based on the MSKCC database.

Data availability

Selected subset of analyzed data from CARIS are available on reasonable request and through collaborative investigations. The clinical information and tumor DNA/RNA sequencing data about TCGA and MSKCC cohort are available from websites (http://www.cbioportal.org, https://tcga.xenahubs.net).

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Acknowledgements

We would like to thank the staff members of the TCGA Research Network and MSKCC and the cBioportal; as well as all the authors for making their valuable research data public.

Funding

This work was supported by the National Cancer Institute [P30CA 014089 to H-JL], Gloria Borges WunderGlo Foundation, Dhont Family Foundation, Victoria and Philip Wilson Research Fund, San Pedro Peninsula Cancer Guild, the V Foundation for Cancer Research, Eddie Money Research Fund.

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Contributions

Conception and design: JW, JX, YB, WMK, and H-JL. Development of methodology: JW, JX, YB, WZ, and H-JL. Acquisition of data (carried out experiments, acquired, and managed patients, provided facilities, etc.): JW, JX, YB, BS, RMG, PAP, AS, JJH, AFS, JLM, IA, ACL, ZG, WMK, FB, HA, NK, SS, WZ, and H-JL. Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): JW, JX, YB, WZ, WMK, and H-JL. Writing, review, and/or revision of the manuscript: JW, JX, BS, WMK, FB, HA, NK, SS, WZ, JM, and H-JL. Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): JW, JX, and H-JL. Study supervision: H-JL.

Corresponding author

Correspondence to Heinz-Josef Lenz.

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Conflict of interest

H-JL reports receiving honoraria from consultant/advisory board membership for Merck Serono, Bayer, and Genentech. JX, YB, ZG, and WMK are employees of Caris Life Sciences. AFS reports funding for research, travel, and the speakers bureau from Caris Life Sciences. All remaining authors have declared no conflicts of interest.

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Wang, J., Xiu, J., Baca, Y. et al. Large-scale analysis of KMT2 mutations defines a distinctive molecular subset with treatment implication in gastric cancer. Oncogene 40, 4894–4905 (2021). https://doi.org/10.1038/s41388-021-01840-3

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