PDPN/CCL2/STAT3 feedback loop alter CAF heterogeneity to promote angiogenesis in colorectal cancer.

Colorectal cancer (CRC) is one of the common clinical malignancies and the fourth leading cause of cancer-related death in the world. The tumor microenvironment (TME) plays a crucial role in promoting tumor angiogenesis, and cancer-associated fibroblasts (CAFs) are one of the key components of the tumor microenvironment. However, due to the high heterogeneity of CAFs, elucidating the molecular mechanism of CAF-mediated tumor angiogenesis remained elusive. In our study, we found that there is pro-angiogenic functional heterogeneity of CAFs in colorectal cancer and we clarified that Podoplanin (PDPN) can specifically label CAF subpopulations with pro-angiogenic functions. We also revealed that PDPN + CAF could maintain CAF heterogeneity by forming a PDPN/CCL2/STAT3 feedback loop through autocrine CCL2, while activate STAT3 signaling pathway in endothelial cells to promote angiogenesis through paracrine CCL2. We demonstrated WP1066 could inhibit colorectal cancer angiogenesis by blocking both the PDPN/CCL2/STAT3 feedback loop in CAFs and the STAT3 signaling pathway in endothelial cells. Altogether, our study suggests that STAT3 could be a potential therapeutic target for blocking angiogenesis in colorectal cancer. We provide theoretical basis and new therapeutic strategies for the clinical treatment of colorectal cancer.

Identification of Hub Genes for Psoriasis and Cancer by Bioinformatic Analysis.

Psoriasis increases the risk of developing various cancers, including colon cancer. The pathogenesis of the co-occurrence of psoriasis and cancer is not yet clear. This study is aimed at analyzing the pathogenesis of psoriasis combined with cancer by bioinformatic analysis. Skin tissue data from psoriasis (GSE117239) and intestinal tissue data from colon cancer (GSE44076) were downloaded from the GEO database. One thousand two hundred ninety-six common differentially expressed genes and 688 common shared genes for psoriasis and colon cancer were determined, respectively, using the limma R package and weighted gene coexpression network analysis (WGCNA) methods. The results of the GO and KEGG enrichment analyses were mainly related to the biological processes of the cell cycle. Thirteen hub genes were selected, including AURKA, DLGAP5, NCAPG, CCNB1, NDC80, BUB1B, TTK, CCNB2, AURKB, TOP2A, ASPM, BUB1, and KIF20A. These hub genes have high diagnostic value, and most of them are positively correlated with activated CD4 T cells. Three hub transcription factors (TFs) were also predicted: E2F1, E2F3, and BRCA1. These hub genes and hub TFs are highly expressed in various cancers. Furthermore, 251 drugs were predicted, and some of them overlap with existing therapeutic drugs for psoriasis or colon cancer. This study revealed some genetic mechanisms of psoriasis and cancer by bioinformatic analysis. These hub genes, hub TFs, and predicted drugs may provide new perspectives for further research on the mechanism and treatment.