By leveraging tumorgraft (PDX) RNA-Seq data, researchers at the University of Texas Southwestern Medical Center developed an empirical approach, DisHet, to dissect the tumor microenvironment (eTME). They found that 65% of previously defined immune signature genes are not abundantly expressed in Renal Cell Carcinoma (RCC), and identified 610 novel immune/stromal transcripts. Using eTME, genomics, pathology and medical record data involving >1,000 patients, we established an inflamed pan-RCC subtype (IS) enriched for Tregs, NK cells, Th1 cells, neutrophils, macrophages, B cells, and CD8+ T cells. IS is enriched for aggressive RCCs, including BAP1-deficient clear-cell and type 2 papillary tumors. The IS subtype correlated with systemic manifestations of inflammation such as thrombocytosis and anemia, which are enigmatic predictors of poor prognosis. Furthermore, IS was a strong predictor of poor survival. Our analyses suggest that tumor cells drive the stromal immune response. These data provide a missing link between tumor cells, the TME, and systemic factors.
Simulation analyses show accurate dissection of bulk tumor RNA-Seq data by DisHet
(a) Scatterplot shows high correlation between predicted component proportions (X axis) and simulated component proportions (Y axis). N=35. (b) Scatterplot shows high correlation between predicted (X axis) and simulated (Y axis) average expression of each gene. (c) Distribution of the correlations of the predicted and simulated individual expression levels of each gene across all patients.