Abstract
Sarcomas are rare malignant tumors of mesenchymal origin with a high misdiagnosis rate due to their heterogeneity and low incidence. Conventional diagnostic techniques, such as Fluorescence In Situ Hybridization (FISH) and Next-Generation Sequencing (NGS), have limitations in detecting structural variations (SVs), copy number variations (CNVs), and predicting clinical behavior. Optical genome mapping (OGM) provides high-resolution genome-wide analysis, improving sarcoma diagnosis and prognosis assessment. This study analyzed 53 sarcoma samples using OGM. Ultra-high molecular weight (UHMW) DNA was extracted from core and resection biopsies, and data acquisition was performed with the Bionano Saphyr platform. Bioinformatic pipelines identified structural variations, comparing them with known alterations for each sarcoma subtype. OGM successfully analyzed 62.3% of samples. Diagnostic-defining alterations were found in 95.2% of cases, refining diagnoses and revealing novel oncogenic and tumor suppressor gene alterations. The challenges included DNA extraction and quality issues from some tissue samples. Despite these limitations, OGM proved to be a powerful diagnostic and predictive tool for bone and soft tissue sarcomas, surpassing conventional methods in resolution and scope, enhancing the understanding of sarcoma genetics, and enabling better patient stratification and personalized therapies.