ICELLNET v2: a versatile method for cell-cell communication analysis from human transcriptomic data.

Summary: Several methods have been developed in the past years to infer cell-cell communication networks from transcriptomic data based on ligand and receptor expression. Among them, ICELLNET is one of the few approaches to consider the multiple subunits of ligands and receptors complexes to infer and quantify cell communication. In here, we present a major update of ICELLNET.

Large-scale analysis of cell-cell communication reveals angiogenin-dependent tumor progression in clear cell renal cell carcinoma.

Cellular crosstalk in the tumor microenvironment (TME) is still largely uncharacterized, while it plays an essential role in shaping immunosuppression or anti-tumor response. Large-scale analyses are needed to better decipher cell-cell communication in cancer. In this work, we used original and publicly available single-cell RNA sequencing (scRNAseq) data to characterize in-depth the communication networks in human clear cell renal cell carcinoma (ccRCC).

Meta-Analysis of Human Cancer Single-Cell RNA-Seq Datasets Using the IMMUcan Database.

Unlabelled: The development of single-cell RNA sequencing (scRNA-seq) technologies has greatly contributed to deciphering the tumor microenvironment (TME). An enormous amount of independent scRNA-seq studies have been published representing a valuable resource that provides opportunities for meta-analysis studies. However, the massive amount of biological information, the marked heterogeneity and variability between studies, and the technical challenges in processing heterogeneous datasets create major bottlenecks for the full exploitation of scRNA-seq data.

Differentiation of exhausted CD8 T cells after termination of chronic antigen stimulation stops short of achieving functional T cell memory.

T cell exhaustion is associated with failure to clear chronic infections and malignant cells. Defining the molecular mechanisms of T cell exhaustion and reinvigoration is essential to improving immunotherapeutic modalities. Here we confirmed pervasive phenotypic, functional and transcriptional differences between memory and exhausted antigen-specific CD8 T cells in human hepatitis C virus (HCV) infection before and after treatment.

Dissection of intercellular communication using the transcriptome-based framework ICELLNET.

Cell-to-cell communication can be inferred from ligand-receptor expression in cell transcriptomic datasets. However, important challenges remain: global integration of cell-to-cell communication; biological interpretation; and application to individual cell population transcriptomic profiles. We develop ICELLNET, a transcriptomic-based framework integrating: 1) an original expert-curated database of ligand-receptor interactions accounting for multiple subunits expression; 2) quantification of communication scores; 3) the possibility to connect a cell population of interest with 31 reference human cell types; and 4) three visualization modes to facilitate biological interpretation.