LTMI is a tool to explore cross talk in the lung-tumor microenvironment through correlation and functional enrichment analysis. We performed RNA-seq profiling of human primary non-small-cell lung tumors in both bulk and flow-sorted malignant cells, endothelial cells, immune cells, and fibroblasts. We mapped the cell-specific differential expression of prognostically-associated secreted factors and cell surface genes, and computationally reconstructed cross-talk between these cell types.
The same strategy was used, except that Fibroblasts were sorted using FAP instead of CD10
Professor of Biomedical Data Science and of Radiology
Stanford University School of Medicine, Stanford CA 94305
sylvia.plevritis@stanford.edu
Assistant Professor (Research) of Medicine (Biomedical Informatics) and, by courtesy, of Biomedical Data Science
Stanford University School of Medicine, Stanford CA 94305
andrewg@stanford.edu
Associate Professor of Radiation Oncology (Radiation Therapy)
Stanford University School of Medicine, Stanford CA 94305
diehn@stanford.edu