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Updated: Jun 24, 2025
Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
Published on: April 4, 2018
Open-Source Bioinformatic Pipeline to Improve PMS2 Genetic Testing Using Short-Read NGS Data.
Elisabet Munté1, Lídia Feliubadaló2, Jesús Del Valle2
1Hereditary Cancer Program, Catalan Institute of Oncology, L'Hospitalet de Llobregat, Spain; Hereditary Cancer Group, Molecular Mechanisms and Experimental Therapy in Oncology Program, Institut d'Investigació Biomèdica de Bellvitge, L'Hospitalet de Llobregat, Spain.
Accurate PMS2 gene sequencing for mismatch repair-deficient cancers is challenging due to pseudogenes. A refined bioinformatics pipeline improves variant detection, doubling the estimated prevalence of pathogenic PMS2 variants in hereditary cancer patients.
Area of Science:
- Genetics
- Bioinformatics
- Oncology
Background:
- Molecular diagnosis of mismatch repair-deficient cancer syndromes is hindered by challenges in sequencing the PMS2 gene, primarily due to the PMS2CL pseudogene.
- Standard next-generation sequencing pipelines struggle with unambiguous mapping of short reads, impacting variant calling accuracy for PMS2.
Purpose of the Study:
- To develop a refined bioinformatics pipeline for accurate PMS2 mutational analysis.
- To determine the prevalence of PMS2 germline pathogenic variants in an unselected hereditary cancer cohort.
Main Methods:
- Optimized PMS2 mutational analysis using two cohorts: 192 unselected hereditary cancer patients and 13 samples with known PMS2 variants.
- Developed a refined pipeline forcing read alignment to PMS2 reference, with specific handling for exon 11.
- Validated the pipeline in 40 patients and screened 5619 hereditary cancer patients.
Main Results:
- The refined PMS2_vaR pipeline demonstrated increased technical sensitivity (0.956) compared to the routine pipeline (0.853) in the validation cohort.
- The pipeline successfully identified all previously detected PMS2 pathogenic variants.
- Fifteen hereditary cancer patients (0.285%) carried a pathogenic PMS2 variant, suggesting a doubled prevalence in the general population.
Conclusions:
- The refined open-source bioinformatics approach significantly improves PMS2 mutational analysis accuracy.
- This enhanced pipeline can be integrated into routine next-generation sequencing workflows for streamlined PMS2 screening.
- The study identified a higher prevalence of pathogenic PMS2 variants in hereditary cancer patients, impacting genetic counseling and clinical management.
