PT  - JOURNAL ARTICLE
AU  - Floriane Noël
AU  - Lucile Massenet-Regad
AU  - Irit Carmi-Levy
AU  - Antonio Cappuccio
AU  - Maximilien Grandclaudon
AU  - Coline Trichot
AU  - Yann Kieffer
AU  - Fatima Mechta-Grigoriou
AU  - Vassili Soumelis
TI  - ICELLNET: a transcriptome-based framework to dissect intercellular communication
AID  - 10.1101/2020.03.05.976878
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.03.05.976878
4099  - http://biorxiv.org/content/early/2020/03/05/2020.03.05.976878.short
4100  - http://biorxiv.org/content/early/2020/03/05/2020.03.05.976878.full
AB  - Cell-to-cell communication can be inferred from ligand-receptor expression in cell transcriptomic datasets. However, important challenges remain: 1) global integration of cell-to-cell communication, 2) biological interpretation, and 3) application to individual cell population transcriptomic profiles. We developed 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 (BioGPS), and 4) three visualization modes to facilitate biological interpretation. We applied ICELLNET to uncover different communication in breast cancer associated fibroblast (CAF) subsets. ICELLNET also revealed autocrine IL-10 as a switch to control human dendritic cell communication with up to 12 other cell types, four of which were experimentally validated. In summary, ICELLNET is a global, versatile, biologically validated, and easy-to-use framework to dissect cell communication from single or multiple cell-based transcriptomic profile(s).