Highlights d HCC and iCCA have a varying degree of transcriptomic diversity d Tumor transcriptomic diversity is associated with patient outcomes d Tumor-derived VEGF drives microenvironmental reprogramming d T cells derived from higher heterogeneous tumors showed lower cytolytic activities

Although cellular behaviors are dynamic, the networks that govern these behaviors have been mapped primarily as static snapshots. Using an approach called differential epistasis mapping, we have discovered widespread changes in genetic interaction among yeast kinases, phosphatases, and transcription factors as the cell responds to DNA damage. Differential interactions uncover many gene functions that go undetected in static conditions. They are very effective at identifying DNA repair pathways, highlighting new damage-dependent roles for the Slt2 kinase, Pph3 phosphatase, and histone variant Htz1. The data also reveal that protein complexes are generally stable in response to perturbation, but the functional relations between these complexes are substantially reorganized. Differential networks chart a new type of genetic landscape that is invaluable for mapping cellular responses to stimuli.One of the most basic approaches to understanding gene function relies on the identification of genetic interactions, which occur when the phenotypic effects of one gene depend on the presence of a second. Recently, a number of technologies have been developed to systematically map genetic interaction networks over large sets of genes in budding yeast (1-3) and other model organisms (4,5 To gain insight into how genetic networks are altered by stress, we assembled a large genetic interactome with and without perturbation by the DNA-damaging agent methyl methane-sulfonate (MMS). Using the technique of epistatic miniarray profiles (E-MAP) (8), genetic interactions were interrogated among a set of 418 yeast genes selected to provide broad coverage of the cellular signaling and transcriptional machinery, including nearly all yeast kinases, phosphatases, and transcription factors, as well as known DNA repair factors ( fig. S1 and table S1). About 80,000 double-mutant strains were generated from all pairwise mutant combinations of the 418 genes, in which mutations were complete gene deletions (nonessential genes) or hypomorphic alleles (essential genes) as appropriate. Double-mutant combinations were grown with or without 0.02% MMS, and their colony sizes were analyzed statistically to compute a genetic interaction score (S score) in each condition (9), which indicates whether the strain was healthier or sicker than expected (positive or negative S, respectively) (10).From established score thresholds for positive and negative interactions (S ≥ +2.0, S ≤ −2.5) (9) we identified two genetic networks: a set of 1905 interactions for the untreated condition, and a set of 2297 interactions under MMS. Analysis of these "static" genetic maps showed strong associations with physical interaction networks of various kinds. For example, gene pairs with either positive or negative genetic interactions were highly enriched for proteins known to physically interact. In addition, both maps were enriched for known kinase-and phosphatase-substrate pairs, as well as transcription factor-target pairs ( fig. S2). The correspondence to physical...

Summary Reversible protein phosphorylation is a signaling mechanism involved in all cellular processes. To create a systems view of the signaling apparatus in budding yeast, we generated an E-MAP (epistatic miniarray profile) comprised of 100,000 pair-wise, quantitative genetic interactions, including virtually all protein kinases and phosphatases and key cellular regulators. Quantitative genetic interaction mapping reveals factors working in compensatory pathways (negative genetic interactions; e.g. synthetic lethality) or those operating in linear pathways (positive genetic interactions; e.g. suppression). Within kinases, phosphatases, and their substrates, we found an enrichment of positive genetic interactions. To develop a global view of the signaling apparatus, we isolated “triplet genetic motifs” and assembled these into a higher-order map. The resulting network view provides new insights into signaling pathway regulation, and revealed a link between the cell cycle kinase, Cak1, the Fus3 MAP kinase, and a pathway that regulates chromatin integrity during transcription by RNA polymerase II.

Our work provides unique perspectives into the biodiversity of CSC subpopulations, whose molecular heterogeneity further highlights their role in tumor heterogeneity, prognosis, and hepatic CSC therapy. (Hepatology 2018;68:127-140).