Open-Source Bioinformatic Pipeline to Improve PMS2 Genetic Testing Using Short-Read NGS Data

Abstract

The molecular diagnosis of mismatch repair- de fi cient cancer syndromes is hampered by difficulties fi culties in sequencing the PMS2 gene, mainly owing to the PMS2CL pseudogene. Next-generation sequencing short reads cannot be mapped unambiguously by standard pipelines, compromising variant calling accuracy. This study aimed to provide a refined fi ned bioinformatic pipeline for PMS2 mutational analysis and explore PMS2 germline pathogenic variant prevalence in an unselected hereditary cancer (HC) cohort. PMS2 mutational analysis was optimized using two cohorts: 192 unselected HC patients for assessing the allelic ratio of paralogous sequence variants, and 13 samples enriched with PMS2 (likely) pathogenic variants screened previously by long-range genomic DNA PCR amplification. fi cation. Reads were forced to align with the PMS2 reference sequence, except those corresponding to exon 11, where only those intersecting gene-specific fi c invariant positions were considered. Afterward, the refined fi ned pipeline's accuracy was validated in a cohort of 40 patients and used to screen 5619 HC patients. Compared with our routine diagnostic pipeline, the PMS2_vaR pipeline showed increased technical sensitivity (0.853 to 0.956, respectively) in the validation cohort, identifying all previously PMS2 pathogenic variants found by long-range genomic DNA PCR amplification. fi cation. Fifteen HC cohort samples carried a pathogenic PMS2 variant (15 of 5619; 0.285%), doubling the estimated prevalence in the general population. The refined fi ned open-source approach improved PMS2 mutational analysis accuracy, allowing its inclusion in the routine next-generation sequencing pipeline streamlining PMS2 screening. (J Mol Diagn 2024, 26: 727-738; https://doi.org/10.1016/j.jmoldx.2024.05.005)