Bayesian Inference of Cell Composition and Gene Expression Reveals Tumor-Microenvironment Interactions
作者： Tinyi Chu , Charles G. Danko
DOI: 10.1101/2020.01.07.897900
关键词: Melanoma 、 Infiltration (medical) 、 Cell type 、 Cancer research 、 Gene expression 、 Gene 、 Tumor microenvironment 、 Head and neck squamous-cell carcinoma 、 Stromal cell 、 Biology
摘要: Understanding the dynamic interactions between malignant cells and tumor stroma is a major goal of cancer research. Here we developed Bayesian model that jointly infers both cellular composition gene expression in each cell type, including heterogeneous cells, from bulk RNA-seq using scRNA-seq as prior information. We conducted an integrative analysis 85 single-cell 1,412 datasets primary human glioblastoma, head neck squamous carcinoma, melanoma. identified types correlated with clinical outcomes explored regional heterogeneity state stromal composition. redefined common molecular subtypes after excluding confounding non-malignant types. Finally, genes whose infiltration macrophages, T-cells, fibroblasts, endothelial across multiple Our work provides new lens used to measure statistically powered cohort three malignancies.
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