Berenguer-Rubio Alejandro, Such Esperanza, Hernández Neus Torres, González-Rojo Paula, Díaz-González Álvaro, Avetisyan Gayane, Gil-Aparicio Carolina, González-López Judith, Pantoja-Borja Nicolay, Rubio-Martínez Luis Alberto, Hernández-Girón Soraya, Valera-Cuesta María Soledad, Ramírez-Fuentes Cristina, Simonet-Redondo María, Díaz-Beveridge Roberto, de la Calva Carolina, Amaya-Valero José Vicente, Ballester-Ibáñez Cristina, Liquori Alessandro, Giner Francisco, Mayordomo-Aranda Empar
Cytogenetic Laboratory, Instituto de Investigación Sanitaria La Fe, 46026 València, Spain.
Department of Hematology, Hospital Universitari i Politècnic La Fe, 46026 València, Spain.
Int J Mol Sci. 2025 Mar 20;26(6):2820. doi: 10.3390/ijms26062820.
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 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.
肉瘤是一种罕见的间充质来源恶性肿瘤,因其异质性和低发病率而误诊率较高。传统诊断技术,如荧光原位杂交(FISH)和新一代测序(NGS),在检测结构变异(SVs)、拷贝数变异(CNVs)以及预测临床行为方面存在局限性。光学基因组图谱(OGM)可提供高分辨率的全基因组分析,改善肉瘤的诊断和预后评估。本研究使用OGM分析了53例肉瘤样本。从核心活检组织和手术切除活检组织中提取超高分子量(UHMW)DNA,并使用该平台进行数据采集。生物信息学流程识别出结构变异,并将其与每种肉瘤亚型的已知改变进行比较。OGM成功分析了62.3%的样本。在95.2%的病例中发现了明确诊断的改变,完善了诊断并揭示了新的致癌基因和抑癌基因改变。挑战包括一些组织样本的DNA提取和质量问题。尽管存在这些局限性,OGM被证明是一种用于骨和软组织肉瘤的强大诊断和预测工具,在分辨率和范围上超越了传统方法,增强了对肉瘤遗传学的理解,并能够实现更好的患者分层和个性化治疗。