GSE158317
Immune determinants for the mesenchymal identity of ovarian cancer via exosome-mediated microRNA transfer
Ovarian cancer is a heterogeneous disease that constitutes great menace to female health and poses tremendous clinical challenge. Based on unsupervised classification of whole-genome gene expression profiles, four molecular subtypes of ovarian cancer were recently identified. However, currently it is still unelucidated on the immune infiltration pattern of different molecular subtypes of ovarian cancer. we used a computational approach (CIBERSORT) to bulk gene expression profiles of ovarian cancer datasets to infer the proportions of 22 subsets of immune cells in the four subtypes. We found that plasma cells are enriched in the mesenchymal subtype of ovarian cancer and the content of plasma cells was correlated with the density of mesenchymal cells in clinical specimens of ovarian cancer. Co-culture of non-mesenchymal subtype ovarian cancer cell lines with plasma cells could induce a mesenchymal phenotype and enhance the metastatic potential of ovarian cancer cells. Mechanistically, this phenotypic switch was mediated by the transfer of miR-330-3p-containing exosomes to the non-mesenchymal ovarian cancer cells.miR-330-3p, which subsequently activate gene transcription of junctional adhesion molecule B(JAM2) epigenetically as an enhancer trigger. Collectively, our work identifies an immune-associated cellular, molecular, and clinical network that highlights the defining role of plasma cells in the mesenchymal identify of ovarian cancer. Overall design: For Small RNA Sequencing, small RNA was isolated from three groups of plasma cells cultured medium. For RNA Sequenceing, total RNA was isolated after that the cells transfected with control miRNA mimic or miR-330-3p mimic in OVTOKO and OVCAR3 cell lines. Gene expression profiles were analyzed.