Hidden RNA profiles of cells in the tumor microenvironment accurately revealed by malignant cell fraction-informed deconvolution

Abstract Deconvolution of bulk RNA profiles can identify hidden cell fractions and functional states in the tumor microenvironment. The malignant cells however, are commonly the most abundant cell type and impair deconvolution by profound interpatient heterogeneity. We developed a malignant cell fraction-informed RNA deconvolution method by Bayesian integration of DNA-derived malignant fraction estimates, OncoBLADE. We evaluated OncoBLADE experimentally using bulk RNA profiles with 19 CyTOF determined cell fractions from blood of 46 individuals, and in silico using 180,177 single-cell RNA profiles from 73 lung tumors. Using malignant cell fractions, OncoBLADE achieved improved accuracy in cell fraction and cell type-specific RNA profile estimation. We tested OncoBLADE on real bulk profiles of 50 adeno- and 50 squamous lung cancer samples, revealing hidden RNA profiles of malignant cells and fibroblasts that distinguished two histological subtypes. In conclusion, multimodal deconvolution utilizing bulk DNA and RNA data accurately unveils hidden RNA profiles within the tumor microenvironment.