A cell-of-origin epigenetic tracer reveals clinically distinct subtypes of high grade serous ovarian cancer

Abstract

High grade serous ovarian cancer (HGSOC) is a major unmet need in oncology. The persistent uncertainty on its originating tissue has contributed to hamper the discovery of oncogenic pathways and effective therapies. Here we define the DNA methylation print that distinguishes the human fimbrial (FI) and ovarian surface epithelia (OSE) and develop a robust epigenetic cell-of-origin tracer that stratifies HGSOC in FIand OSE-originated tumors across all available cohorts. We translate this origin-based stratification into a clinically actionable transcriptomic signature, demonstrating its prognostic impact on patients' survival and identifying novel network level dysregulations specific for the two disease subtypes.

DNA methylation reveals distinct cells of origin for pancreatic neuroendocrine carcinomas (PanNECs) and pancreatic neuroendocrine tumors (PanNETs)

“…Methylation patterns are now considered as a robust method to identify tumor cell-of-origins across tissues 51 , and in different cancer types 47,[52][53][54][55] . In addition, they have been used for characterization of subgroups within a tumor entity, for example in central nervous system tumors 56 , breast cancer 53 , ovarian cancer 57 as well as tissue origin of cell-free DNA (cfDNA) in disease 48 . Furthermore, methylation analysis has shown the significance of hypermethylation during the transition of committed cells to a naive stem cell state 44 .…”

“…Using the 10K most variable probes identified by determining row (probe) standard deviation first obtaining a dissimilarity matrix using an Euclidean algorithm and then performing the clustering using complete linkage.. Hierarchical clustering was done using the R package "Stats" and tSNE was done using the "Rtsne" package under the perplexity=8. Genes associated with the 10K most variable probes were evaluated for GO pathway 57 biological processes term enrichment using the enrichGO() function in the clusterprofiler R package. The analysis was done under the following parameters: pAdjustMethod = "BH" (Benjamini and Hochberg), pvalueCutoff = 0.01, qvalueCutoff = 0.05.…”

Exploiting epigenetic dependencies in ovarian cancer therapy

“…In short, the key step forward in ovarian cancer treatment, and indeed cancer treatment in general, is to profile and define the specific mutational background of cells within individual tumors. Additionally, fully characterizing the cell‐of‐origin of the various subtypes, through techniques such as OriPRINT, 10 will allow proper molecular characterization and identification of subtype‐specific vulnerabilities. The burgeoning fields of organoid modeling, single‐cell technologies and epigenetic characterization can guide us through this complex area (Figure 3).…”

“…A highly aggressive malignancy, its cell of origin is often unclear, there has been ambiguity as to whether it has originated from ovarian surface epithelium or tubal epithelium, with recent data suggesting that it can arise from both (Figure 1). 3,10 Emerging technologies in cell of origin tracing, such as OriPRINT, 10 and patient‐derived organoids for normal tissue comparative analysis, 11 we are closer to tracking the specific dysregulation driving tumorigenesis.…”