Different gut microbiota is implicated in different diseases, including cancer. However, gut microbiota differences between individuals with clear cell renal cell carcinoma (ccRCC) and healthy individuals are unclear. Here, we analyzed gut microbiota composition in 51 ccRCC patients and 40 healthy controls using 16S rRNA sequencing analysis. We observed that Blautia, Streptococcus, [Ruminococcus]_torques_group, Romboutsia, and [Eubacterium]_hallii_group were dominant and positively associated with ccRCC. We isolated and cultured Streptococcus lutetiensis to characterize specific gut microbiota that promotes ccRCC and found that it promoted in vitro ccRCC proliferation, migration, and invasion via the TGF-signaling pathway. Interactions identified between the gut microbiota and ccRCC suggest the gut microbiota could serve as a potential non-invasive tool for predicting ccRCC risk and also function as a cancer therapy target.

Background: Numerous epidemiological studies have confirmed that diabetes can promote the development of malignant tumors. However, the relationship between renal cell carcinoma (RCC) and diabetic nephropathy (DN) is still controversial. This study aimed to investigate the genes that are coexpressed in DN and RCC in order to gain a better understanding of the relationship between these diseases, and to identify potential biomarkers and targets for the treatment of DN-related RCC.Methods: We evaluated the differentially expressed genes (DEGs) that are co-expressed in DN and RCC using a wide range of target prediction and analysis methods. Twenty-four genes were identified by intersecting the differential genes of 3 DN datasets and 2 RCC datasets. We predicted the micro-ribonucleic acids (miRNAs) of these genes that may be controlled using the miRNA Data Integration Portal (mirDIP) database, and rated them according to each data forecast based on the Comparative Toxicogenomics Database (CTD) and the StarBase database.Results: Four genes were associated with DN and RCC patients: the predicted miRNAs hsa-miR-200b-3p and hsa-miR-429 of fibronectin 1 (FN1); the predicted miRNA hsa-miR-29c-3p of collagen type 1 alpha 2 (COL1A2); the predicted miRNA hsa-miR-29c-3p of collagen type 3 alpha 1 (COL3A1); and the predicted miRNA hsa-miR-29a-3p and hsa-miR-200c-3p of glucose-6-phosphatase catalytic subunit (G6PC). These genes may serve as potential biomarkers or specific targets in the treatment of DN-related RCC.Conclusions: A significant correlation was identified between DN and RCC. The FN1, COL1A2, COL3A1, and G6PC genes could be novel biomarkers of DN-related RCC.

Background: Ferroptosis is a potential target for cancer therapy, and lncRNAs can also affect ferroptosis by regulating related genes. The pathogenesis of clear cell renal cell carcinoma (ccRCC) regarding the regulation of ferroptosis by lncRNAs is still unknown.Methods: We constructed a risk model based on data in ccRCC patients obtained from the TCGA database and validated the diagnostic and prognostic value of the model. In addition, immune function and immune checkpoint variability analysis validated the association of ferroptosis with ccRCC tumor immunity.Results: The characteristics of ferroptosis-related lncRNAs (FRLs) were significantly correlated with the prognosis of ccRCC patients. The prognostic characteristics of FRLs were independent prognostic factors in ccRCC patients. Gene function in the high-risk group was associated with oxygen metabolic processes and immune pathways. Immune checkpoint variability analysis showed that HAVCR2, NRP1, and HHLA2 were upregulated in the low-risk group, while CD44, TNFRSF18, TNFSF14, TNFRSF8, CD276, and TNFRSF25 were upregulated in the high-risk group.Conclusions: The prognostic characteristics of FRLs can effectively predict the prognosis of ccRCC patients and provide a new direction for clinical treatment.