DNA methylation-based profiling of uterine neoplasms: a novel tool to improve gynecologic cancer diagnostics

Uterine neoplasms comprise a broad spectrum of lesions, some of which may pose a diagnostic challenge even to experienced pathologists. Recently, genome-wide DNA methylation-based classification of central nervous system tumors has been shown to increase diagnostic precision in clinical practice when combined with standard histopathology. In this study, we describe DNA methylation patterns of a diverse set of uterine neoplasms and test the applicability of array-based DNA methylation profiling.

A multicenter cohort including prototypical epithelial and mesenchymal uterine neoplasms was collected. Tumors were subject to pathology review and array-based DNA methylation profiling (Illumina Infinium HumanMethylation450 or EPIC [850k] BeadChip). Methylation data were analyzed by unsupervised hierarchical clustering and t-SNE analysis.

After sample retrieval and pathology review the study cohort consisted of 49 endometrial carcinomas (EC), 5 carcinosarcomas (MMMT), 8 uterine leiomyomas (ULMO), 7 uterine leiomyosarcomas (ULMS), 15 uterine tumor resembling ovarian sex cord tumors (UTROSCT), 17 low-grade endometrial stromal sarcomas (LGESS) and 9 high-grade endometrial stromal sarcomas (HGESS). Analysis of methylation data identified distinct methylation clusters, which correlated with established diagnostic categories of uterine neoplasms. MMMT clustered together with EC, while ULMO, ULMS and UTROSCT each formed distinct clusters. The LGESS cluster differed from that of HGESS, and within the branch of HGESS, we observed a notable subgrouping of YWHAE- and BCOR-rearranged tumors.

Herein, we describe distinct DNA methylation signatures in uterine neoplasms and show that array-based DNA methylation analysis holds promise as an ancillary tool to further characterize uterine neoplasms, especially in cases which are diagnostically challenging by conventional techniques.