XDec-CHI reveals immunosuppressive interactions in pancreatic ductal adenocarcinoma

iScience. 2022 Sep 29;25(10):105249. doi: 10.1016/j.isci.2022.105249. eCollection 2022 Oct 21.

Abstract

Most cancers harbor a diverse collection of cell types including a typically heterogeneous cancer cell fraction. To reconstruct cell-intrinsic and heterotypic interactions driving tumor progression, we combine the XDec deconvolution method with cell-type-specific gene expression correlation analysis into the XDec-CHI method. XDec-CHI identifies intra- and inter-cellular pathways using correlation and places them in the context of specific tumor subtypes, as defined by the state of constituent cancer cells. We make the method web-accessible for analysis of publicly accessible pancreatic ductal adenocarcinoma, breast, head and neck, glioblastoma, and glioma tumors. We apply the method to TCGA and ICGC datasets to identify immune-suppressive interactions within PDAC tumors that are relevant for immunotherapies targeting PD-L1. Subtype-specific interactions derived from correlative analyses validated in co-culture experiments suggest PDAC subtypes have distinct therapeutic weaknesses, with Basal-like and MSLN-high Classical B tumors most likely to respond to therapies targeting PD-L1.

Keywords: Biocomputational method; Bioinformatics; High-performance computing in bioinformatics; Omics; Transcriptomics.