CODEFACS and LIRICS: Computation Tools for Identifying Cell-Type Specific Gene Expression Levels in Tumors and Other Types of Samples

The tumor microenvironment (TME) is a complex mixture of cell types whose interactions affect tumor growth and clinical outcome. Recent studies using fluorescence-activated cell sorting (FACS) and single-cell RNA sequencing (RNAseq) to elucidate tissue composition and cell-cell interactions in the TME led to improved biomarkers of patient response and new treatment opportunities. However, the use of FACS is limited to simultaneously measuring the expression of a few protein markers, whereas the use of single-cell RNAseq has been limited due to cost and scarcity of fresh tumor biopsies. In contrast, bulk tumor gene expression from preserved biopsies accompanied by clinical outcome metadata is abundant. Several algorithms have shown promise in accurately reconstructing cell-type-specific gene expression profiles from bulk gene expression.   Researchers at National Cancer Institute (NCI) have developed CODEFACS (COnfident DEconvolution For All Cell Subsets), a transcriptomics computation tool that can confidently estimate cell type abundance and deconvolve cell-type-specific gene expression profiles of individual cancer patients from bulk gene expression measurements. A complementary, second software tool LIRICS (LIgand-Receptor Interaction between Cell Subsets) prioritizes clinically relevant ligand-receptor interactions between cell types from the deconvolved data. These tools uncovered TME ligand-receptor interactions associated with improved patient survival and high sensi...
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