Methylome Profiling of Cartilage Tumors: A Promising New Diagnostic Tool?

DNA methylation and copy number variation (CNV) profiling has emerged as a promising tool for the classification of bone and soft tissue tumors. We evaluated its utility in cartilage tumors, where distinguishing low-grade from high-grade conventional central chondrosarcoma (CS) as well as atypical cartilaginous tumors (ACT) from enchondromas are frequent diagnostic challenges, particularly on biopsy material. We analyzed 214 chondrogenic tumors, including enchondromas, ACT, conventional central, dedifferentiated, and clear cell chondrosarcomas, and determined their IDH1/2 mutation status. Unsupervised dimensionality reduction of genome-wide DNA methylation patterns revealed four clusters among IDH-mutant tumors (IDH-MUT-1: mostly enchondromas and ACT and some high-grade CS; IDH-MUT-2: predominantly high-grade CS; IDH-MUT-3: largely dedifferentiated CS; IDH-MUT-SB: distinct skull base group with markedly different methylation pattern) and two clusters among IDH-wildtype tumors (IDH-WT-1 and IDH-WT-2: both primarily high-grade CS, with IDH-WT-2 showing higher tumor grade and more extensive CNVs). Clear cell chondrosarcomas formed a separate cluster (CC). The amount of CNVs, including loss of CDKN2A, increased with tumor grade, reflecting increased genomic instability during chondrosarcoma progression. Supervised classifiers trained separately, both on methylation and CNV data, distinguished low- and high-grade cartilaginous tumors with AUC values of 0.87-0.97 and 85-90% accuracy. Furthermore, we tested whether dedifferentiated chondrosarcoma (DDCS) can be distinguished from metastatic carcinomas and other high-grade sarcomas of bone. Across 246 reference samples, a supervised classifier achieved 97.2% accuracy (AUC 99.8%) and correctly identified 30/32 (93.8%) DDCS. These results indicate that DNA methylation and CNV data analysis provide a valuable tool for distinguishing most low- and high-grade chondrosarcomas, with additional utility also in differentiating DDCS from morphologic mimics.