Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer

TLDR

Molecular similarities among histologically or anatomically related cancer types provide a basis for focused pan‑cancer analyses that may inform future therapeutic development. We performed comprehensive integrative molecular analyses of the complete set of ~10,000 TCGA tumors representing 33 cancer types. Clustering of multi‑omics data from these tumors revealed that histology, tissue type, or anatomic origin—particularly cell‑of‑origin patterns—predominantly drive molecular groupings, with DNA‑methylation clustering remaining strongly tissue‑specific even after removing known tissue‑type sites.

Abstract

We conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA hypermethylation, mRNA, and miRNA expression levels and reverse-phase protein arrays, of which all, except for aneuploidy, revealed clustering primarily organized by histology, tissue type, or anatomic origin. The influence of cell type was evident in DNA-methylation-based clustering, even after excluding sites with known preexisting tissue-type-specific methylation. Integrative clustering further emphasized the dominant role of cell-of-origin patterns. Molecular similarities among histologically or anatomically related cancer types provide a basis for focused pan-cancer analyses, such as pan-gastrointestinal, pan-gynecological, pan-kidney, and pan-squamous cancers, and those related by stemness features, which in turn may inform strategies for future therapeutic development.