Csf1r mediates enhancement of intestinal tumorigenesis caused by inactivation of Mir34a

CSF-1R in Cancer: More than a Myeloid Cell Receptor

Colony-stimulating factor 1 receptor (CFS-1R) is a myeloid receptor with a crucial role in monocyte survival and differentiation. Its overexpression is associated with aggressive tumors characterized by an immunosuppressive microenvironment and poor prognosis. CSF-1R ligands, IL-34 and M-CSF, are produced by many cells in the tumor microenvironment (TME), suggesting a key role for the receptor in the crosstalk between tumor, immune and stromal cells in the TME. Recently, CSF-1R expression was reported in the cell membrane of the cancer cells of different solid tumors, capturing the interest of various research groups interested in investigating the role of this receptor in non-myeloid cells. This review summarizes the current data available on the expression and activity of CSF-1R in different tumor types. Notably, CSF-1R+ cancer cells have been shown to produce CSF-1R ligands, indicating that CSF-1R signaling is positively regulated in an autocrine manner in cancer cells. Recent research demonstrated that CSF-1R signaling enhances cell transformation by supporting tumor cell proliferation, invasion, stemness and drug resistance. In addition, this review covers recent therapeutic strategies, including monoclonal antibodies and small-molecule inhibitors, targeting the CSF-1R and designed to block the pro-oncogenic role of CSF-1R in cancer cells.

The role of CD14 and CSF1R in osteoarthritis and gastritis

Osteoarthritis (OA) is a non-inflammatory degenerative joint disease that mainly involves articular cartilage damage and involves the whole joint tissue. Gastritis is a common stomach disorder, typically referring to inflammation or lesions of the gastric mucosa. However, the relationship between CD14 and colony stimulating factor-1 receptor (CSF1R) and these 2 diseases is not yet clear. OA datasets GSE46750, GSE82107 and gastritis datasets GSE54043 profiles were downloaded from gene expression omnibus databases generated by GPL10558 and GPL570.The R package limma was used to screen differentially expressed genes (DEGs). Weighted gene co-expression network analysis was performed. The construction and analysis of protein-protein interaction network, functional enrichment analysis, gene set enrichment analysis and comparative toxicogenomics database analysis were performed. TargetScan was used to screen miRNAs regulating central DEGs. A total of 568 DEGs were identified. According to the gene ontology (GO) and biological processes analysis, they were mainly enriched in ATP metabolism negative regulation, toll-like receptor TLR1:TLR2 signaling pathway, and intracellular transport. The enrichment terms for OA and gastritis were similar to the GO and Kyoto encyclopedia of gene and genome enrichment terms of DEGs, mainly enriched in ATP metabolism negative regulation, secretion granules, transmembrane receptor protein kinase activity, cytokine-cytokine receptor interaction, Toll-like receptor signaling pathway, MAPK signaling pathway, and TGF-β signaling pathway. In the Metascape enrichment projects, GO enrichment projects showed functions related to cell-cell receptor interaction, cell secretion, and growth. Two core genes were identified through the construction and analysis of the protein-protein interaction network. The core genes (CD14 and CSF1R) exhibited high expression in OA and gastritis samples and low expression in normal samples. Comparative toxicogenomics database analysis revealed associations between core genes (CD14 and CSF1R) and diseases such as OA, osteoporosis, gastritis, juvenile arthritis, diarrhea, and inflammation. CD14 and CSF1R are highly expressed in OA and gastritis, making them potential therapeutic targets for both diseases.

Meta-analysis of miR-34 target mRNAs using an integrative online application

Members of the microRNA-34/miR-34 family are induced by the p53 tumor suppressor and themselves possess tumor suppressive properties, as they inhibit the translation of mRNAs that encode proteins involved in processes, such as proliferation, migration, invasion, and metastasis. Here we performed a comprehensive integrative meta-analysis of multiple computational and experimental miR-34 related datasets and developed tools to identify and characterize novel miR-34 targets. A miR-34 target probability score was generated for every mRNA to estimate the likelihood of representing a miR-34 target. Experimentally validated miR-34 targets were strongly enriched among mRNAs with the highest scores providing a proof of principle for our analysis. We integrated the results from the meta-analysis in a user-friendly METAmiR34TARGET website (www.metamir34target.com/) that allows to graphically represent the meta-analysis results for every mRNA. Moreover, the website harbors a screen function, which allows to select multiple miR-34-related criteria/analyses and cut-off values to facilitate the stringent and comprehensive prediction of relevant miR-34 targets in expression data obtained from cell lines and tumors/tissues. Furthermore, information on more than 200 miR-34 target mRNAs, that have been experimentally validated so far, has been integrated in the web-tool. The website and datasets provided here should facilitate further investigation into the mechanisms of tumor suppression by the p53/miR-34 connection and identification of potential cancer drug targets.