An Algorithmic Approach for Quantitative Determination of Microsatellite Status in NGS-Based Cancer Diagnostics

PURPOSE: To develop a transparent and adaptable methodological framework for the analysis of microsatellite status using Next Generation Sequencing (NGS), addressing current limitations in clinical implementation. METHODS: Microsatellite status was assessed using NGS with a custom-designed panel. The approach was validated against polymerase chain reaction (PCR) and immunohistochemistry (IHC) results in a cohort of 32 patients with various tumor entities. A Python-based analysis pipeline was developed to process raw sequencing data and quantify mutational burden within microsatellite regions. RESULTS: The proposed method demonstrated 100% concordance with PCR and 90.32% concordance with IHC results. The framework enabled quantitative assessment of microsatellite instability. CONCLUSIONS: This proof-of-concept study demonstrates reliable determination of microsatellite status. The transparent and panel-adaptable framework offers flexibility for clinical implementation and provides a robust foundation for further validation in larger cohorts and across diverse tumor entities.