Integrative Multiomic Classification Reveals Distinct Origins and Evolutionary Trajectories of Thymic Epithelial Tumors.

Abstract

Thymic epithelial tumors (TET), comprising various histologic types of thymomas and thymic carcinomas, originate from thymic epithelial cells (TEC). Each histologic type is typically associated with a distinct immune cell composition and clinical manifestation. A better understanding of the cellular origins and molecular pathways underlying this heterogeneity is needed to improve patient stratification and treatment. In this study, we conducted an integrated genomic and transcriptomic analysis of 124 thymomas and 13 thymic carcinomas, including 20 newly sequenced cases, combined with 117 cases from publicly available datasets. Single-cell transcriptomic data from murine thymic tissues across developmental stages were incorporated to further investigate potential cells of origin. This approach stratified TETs into three subgroups with different possible origins: GTF2I-mutant (GTF2I-type) thymomas, copy number-altered (CN-type) thymomas, and thymic carcinomas. GTF2I-type thymomas, carrying hotspot GTF2I mutations, displayed transcriptional profiles resembling thymic epithelial progenitors. In contrast, CN-type thymomas, characterized by frequent copy-number alterations and IRS4 oncogene transcriptional activation, showed expression patterns similar to differentiated TECs. Thymic carcinomas, with high mutational burdens, exhibited profiles comparable with thymic tuft cells. The three subgroups also differed markedly in transcriptional programs, including lipid metabolism and immune phenotypes. Early acquisition of chromosomal copy-number alterations in CN-type thymomas further supported different evolutionary paths among subgroups. Together, these findings provide insights into the cellular origins and tumorigenic processes of TETs and underscore the value of integrative genomics for accurate cancer classification. Thymic epithelial tumors can be classified into three subgroups based on genomic features and potential cells of origin, highlighting the importance of integrative analyses for accurate classification and therapeutic discovery.