Investigation of the Relationship Between DNA Mismatch Repair Genes and Microsatellite Instability in Solid Tumors

Year 2024, Volume: 34 Issue: 5, 689 - 695, 30.10.2024

Ozkan Bagci

https://doi.org/10.54005/geneltip.1510108

Abstract

Aim: In this study, we aimed to detect the MSI status and somatic mutations in MMR genes (MSH2, MSH6, MLH1, PMS2) of a total of 55 solid tumors diagnosed with colorectal, endometrium and ovarian cancer by NGS method and to reveal the relationship between them.
Material and Method: DNA isolation was performed by taking 10-micron sections from paraffin-embedded tissue samples of 55 patients diagnosed with kolorektal, endometrium ve ovarian solid tümörlerinin and Kapa NGS DNA extraction kit was used for sequence analysis. The purity and concentration of the DNA obtained was measured by Qubit fluoremeter, and NadPrep DNA Universal Library Preparation Kit was used for high quality library preparation. Bioinformatics analyses were performed on the Genomize Seq platform. The MSI value was analysed by Roche Navify Mutation Caller software and percentage MSI values were determined using the MSIsensor2 pipeline for secondary analysis of NGS.
Results: All ovarian tumors were in the MSI-Stable category. The average MSI value was 2.01. One sample had an MSI of zero. In addition, no mutations in the MSH2 and MLH1 genes were detected in any of the ovarian tumors. 3 of 4 endometrial tumors were in the MSI-Stable category, and 1 tumor was in the MSI-low (MSI value: 13.2) category. No variants were detected in the MSH2 and PMS2 genes in endometrial tumors. 2 of the 41 colorectal tumors (Case4, Case16) were in the MSI-High category. No variants were detected in the MMR genes in 19 tumors.
Conclusion: Although frame-shift and stop-gain mutations were detected in 23 tumors that would cause protein deficiency in MMR genes, MSI-H was not detected, as expected, except for two colorectal tumors. Therefore, the results of our study emphasise the need to define new predictive biomarkers clinically within the framework of algorithms to predict response to immunotherapy and determine prognosis.

Keywords

Colorectal cancer, Endometrium cancer, Ovarian cancer, MMR, MSI

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