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Kieffer, Y.

Publications and source records attributed to Kieffer, Y..

2 recordsLinked to original sources

Cancer-associated fibroblasts produce matrix-bound vesicles that influence endothelial cell function

Intercellular communication between different cell types in solid tumors contributes to tumor growth and metastatic dissemination. The secretome of cancer-associated fibroblasts (CAFs) plays major roles in these processes. Using human mammary CAFs, we unveil a mechanism of cell-cell communication between CAFs with myofibroblast phenotype and endothelial cells (ECs) based on intercellular protein transfer through extracellular vesicles (EVs). CAFs transfer proteins to ECs, including plasma membrane receptors, which we have identified by using mass spectrometry- based proteomics. Using THY1 as an example of transferred plasma membrane-bound protein, we show that CAF-derived proteins can influence how ECs interact with other cell types. Here, we show that CAFs produce high amounts of matrix-bound EVs that have a key role in protein transfer. Hence, our work paves the way for further studies to understand how CAF-derived matrix-bound EVs influence tumor pathology by regulating functions of neighboring cancer, stromal and immune cells. One sentence summaryCAFs with a myofibroblastic-like phenotype transfer proteins to ECs, including plasma membrane receptors, through matrix-bound EVs

cancer biology↗

ICELLNET: a transcriptome-based framework to dissect intercellular communication

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).

systems biology↗