MSIMEP: Predicting microsatellite instability from microarray DNA methylation tumor profiles

Deficiency in DNA MMR activity results in tumors with a hypermutator phenotype, termed microsatellite instability (MSI). Beyond its utility in Lynch syndrome screening algorithms, today MSI has gained importance as predictive biomarker for various anti-PD-1 therapies across many different tumor types. Over the past years, many computational methods have emerged to infer MSI using either DNA-or RNA-based approaches. Considering this together with the fact that MSI-high tumors frequently exhibit a hypermethylated phenotype, herein we developed and validated MSIMEP, a computational tool for predicting MSI status from microarray DNA methylation tumor profiles of colorectal cancer samples. We demonstrated that MSIMEP optimized and reduced models have high performance in predicting MSI in different colorectal cancer cohorts. Moreover, we tested its consistency in other tumor types with high prevalence of MSI such as gastric and endometrial cancers. Finally, we demonstrated better performance of both MSIMEP models vis-a-vis a MLH1 promoter methylation-based one in colorectal cancer.

Automated summary

Deficient DNA MMR activity leads to tumors with hypermutator phenotype called microsatellite instability (MSI). MSI has become an important predictive biomarker for anti-PD-1 therapies in various tumor types. In this study, we developed and validated MSIMEP, a computational tool for predicting MSI status from microarray DNA methylation tumor profiles of colorectal cancer samples. We demonstrated the high performance of MSIMEP in predicting MSI in different colorectal cancer cohorts and tested its consistency in other tumor types. The MSIMEP models showed better performance compared to a MLH1 promoter methylation-based model in colorectal cancer.