Abstract
Mesothelioma is a lethal cancer. Despite promising outcomes associated with immunotherapy, durable responses remain restricted to a minority of patients, highlighting the need for improved strategies that better predict outcome. Here, we described the development of a mesothelioma-specific gene signature that accurately predicts survival. Comprehensive gene expression analysis of asbestos exposed MexTAg Collaborative Cross mouse tumors revealed distinct tumor clusters characterized by epithelial mesenchymal transition/extracellular matrix, or immune infiltrate related gene expression profiles. Weighted gene co-expression network analysis (WGCNA) identified 20 hub genes that drove differential gene expression. Human homologues of these 20 hub genes were refined through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses to identify a six-gene mesothelioma-specific prognostic signature that accurately predicted patient survival across four independent human mesothelioma datasets. Furthermore, this six-gene signature demonstrated the potential to predict treatment response, thus advancing the management of this challenging malignancy.
Keywords:
Biological sciences; Cancer; Genetics.