A
system for characterizing intercellular communication and heterogeneity in
cancer tumors, and more particularly a method for detecting sub-populations and
receptor-ligand states for providing predictive information in relation to
cancer and
cancer treatment is disclosed. The
system comprises the steps of obtaining from a NGS sequencer, single-
cell RNA-seq for a plurality of cells within a tumor, correlation with a plurality of data sets from a curated
gene list of
receptor-ligand pairs, normalizing their transcript abundance data, assigning states (e.g. 0,1,2,3) to each curated
receptor-ligand pair in each
cell (e.g. depending on {L:R}={0:0, 0:1, 1:0, 1:1}), thereby forming a matrix of receptor-ligand states, extracting sub-groups from the matrix that are not invariant and applying
unsupervised clustering methods to identifying sub-clusters, identifying sub-populations within the set based on pair-wise distances between individual cells and similarity of cellular transcriptomes, identifying expressed ligands and receptors across the sub-populations, cross-referencing against the curated set of receptor-ligand pairs and providing a visually display the results by a mapping module for the clinician. The method can be used to study intercellular communication to elicit the
etiology of diseases, and can be used to measure the disruption of intercellular communication to diagnose similarly disrupted
disease patterns across patients.