Genetic analysis of prostate tumors demands robust methods capable of detecting large structural variants (SVs), which are often missed by short-read Next-Generation Sequencing (NGS) technologies. Long-read sequencing, though effective, presents cost constraints. Optical Genome Mapping (OGM) emerges as a high-resolution DNA imaging technique offering a cost-effective alternative and complement to sequencing technologies. Here, we present a comprehensive workflow utilizing OGM for identifying somatic SVs in prostate tumours.
A cohort of 28 tumor-blood pairs, including samples from diverse ethnic backgrounds (11 European & African), underwent analysis. DNA concentrations ranged from 40 to 150 ng/μl, with effective coverage spanning 60X to 450X. Results revealed tumor-specific SVs categorized by mutation types, samples, and mutation counts. Notably, the Tumor-Germline variant annotation pipeline facilitated the detection of tumor-specific SVs and copy number variations (CNVs). Common mutations on chromosomes 9, X, and Y were observed among prostate cancer patients.
Key genes implicated in prostate cancer pathogenesis were identified, including RNPC3, TET3, FNBP1P1, PLGLB2, CCDC148, UGDH-AS1, STAU2, MAMDC2, FOLH1, and GOLGA6L1. These genes play diverse roles, from RNA processing and DNA methylation regulation to potential therapeutic targeting and Golgi function modulation.
This study underscores the utility of OGM in enabling rapid genetic interrogation of prostate cancer patients, strengthening clinical decision-making and treatment planning. By offering a comprehensive view of somatic SVs, OGM has the potential to accelerate diagnostic processes and enhance treatment efficacy. Furthermore, the identification of key genes implicated in prostate cancer provides valuable insights into disease mechanisms and potential therapeutic targets, paving the way for personalized treatment approaches. OGM emerges as a promising tool for advancing precision oncology in prostate cancer management.