Obesity, metabolic changes, and intestinal microbiota disruption significantly affect tumorigenesis and metastasis in colorectal cancer (CRC). However, the relationships among these factors remain poorly understood. In this study, we found that a high-fat diet (HFD) promoted gut barrier dysfunction and inflammation in the colorectum and liver. We further investigated gut microbiota changes through 16S rRNA sequencing of faecal samples from HFD-fed rats and CRC hepatic metastasis patients and found an abundance of Desulfovibrio (DSV). DSV could also induce barrier dysfunction in the colorectum and inflammation in the colorectum and liver, suggesting that it contributes to the formation of a microenvironment conducive to CRC tumorigenesis and metastasis. These findings highlight that HFD-induced microbiota dysbiosis, especially DSV abundance, could promote CRC initiation and metastasis.

Background. Inflammation within areas of interstitial fibrosis and tubular atrophy (IF/TA) is associated with kidney allograft failure. The aim of this study was to reveal new diagnostic markers of IF/TA based on bioinformatics analysis. Methods. Raw data of IF/TA samples after kidney transplantation and control samples after kidney transplantation were extracted from the Gene Expression Omnibus (GEO) database (GSE76882 and GSE120495 datasets), and genes that were differentially expressed between the two groups (DEGs) were screened. Gene Set Enrichment Analysis (GSEA), ESTIMATE and single sample GSEA (ssGSEA), least absolute shrinkage and selection operator (LASSO) regression analysis, and competing endogenous RNA (ceRNA) network were used to analyze the data. Results. The results of GSEA revealed that multiple immune-related pathways were enriched in the IF/TA group, and subsequent immune landscape analysis also showed that the IF/TA group had higher immune and stromal scores and up to 15 types of immune cells occupied them, such as B cells, cytotoxic cells, and T cells. LASSO regression analysis selected 6 (including ANGPTL3, APOH, LTF, FCGR2B, HLA-DQA2, and EGF) out of 14 DE-IRGs as diagnostic genes to construct a diagnostic model. Then, receiver operating characteristic (ROC) curve analysis showed the powerful diagnostic value of the model, and the area under the curve (AUC) of a single diagnostic gene was greater than 0.75. The results of ingenuity pathway analysis (IPA) also indicated that DEGs were involved in the immune system and kidney disease-related pathways. Finally, we found multiple miRNAs that could regulate diagnostic genes from the ceRNA network. Conclusion. This study identified 6 IF/TA-related genes, which might be used as a new diagnosis model in the clinical practice.