Bladder cancer (BLCA) is a common malignancy of the urinary system. The gut microbiome produces various metabolites that play functional roles in tumorigenesis and tumor progression. However, the integrative analysis of the gut microbiome and metabolome in BLCA has still been lacking. Thus, the aim of this study was to identify microbial and functional characteristics and metabolites in BLCA in a Chinese population. Metagenomics, targeted metabolomics, bioinformatics, and integrative analysis were used in fecal samples of BLCA patients and healthy individuals. We found gut microbiomes were significantly dysregulated in BLCA patients, including Bifidobacterium, Lactobacillus, Streptococcus, Blautia, and Eubacterium. We also found 11Z-eicosenoic acid, 3-methoxytyrosine, abrine, aniline-2-sulfonate, arachidic acid, conjugated linoleic acids, elaidic acid, glycylleucine, glycylproline, leucyl-glycine, linoelaidic acid, linoleic acid, nicotinamide hypoxanthine dinucleotide, oleic acid, petroselinic acid, and ricinoleic acid to be significantly decreased, while cholesterol sulfate was significantly increased in BLCA patients. Integration of metagenomics and metabolomics revealed interactions between gut microbiota and metabolites and the host. We identified the alterations of gut microbiomes and metabolites in BLCA in a Chinese population. Moreover, we preliminarily revealed the associations between specific gut microbiomes and metabolites. These findings determined potential causative links among gut dysbiosis, dysregulated metabolites, and BLCA.

Background: Patients with urothelial bladder carcinoma (UBC) have a poor prognosis and a high risk of progression. Recently, tRNA-derived small RNAs (tsRNAs), a novel type of noncoding RNA, have been identified. In our previous study, we found tiRNA-Gly-GCC-1 was significantly upregulated in UBC tissue and might target the predicted target gene toll-like receptor 4 (TLR4) to play a regulatory role in UBC. Thus, the aim of this study was to identify the functional roles of tiRNA-Gly-GCC-1 and the relationship between tiRNA-Gly-GCC-1 and TLR4. Methods: After lentiviral transfection in 5637 and T24 cell lines, quantitative reverse transcription-PCR, Cell Counting Kit-8, IncuCyte ZOOM™ live cell imaging, flow cytometry, Transwell assays, scratch assay, and luciferase assay were performed. Results: The results showed down-regulation of tiRNA-Gly-GCC-1 inhibits cell proliferation, migration and invasion, promotes cell apoptosis, and affects the cell cycle. Besides, tiRNA-Gly-GCC-1 was found to inhibit TLR4 expression by directly targeting its 3′UTR. Conclusions: Our study demonstrated that tiRNA-Gly-GCC-1 promotes the progression of UBC and directly targets TLR4. This study provides novel insights for future investigations to explore the mechanisms and therapeutic targets for UBC.

Muscle-invasive bladder cancer (MIBC) leads to a large societal burden. Recently, tRNA-derived small RNAs (tsRNAs), a novel type of noncoding RNA (ncRNAs), have been identified. However, the expression patterns and functions of tsRNAs in MIBC have not yet been identified. Here, RNA sequencing, bioinformatics, and quantitative reverse transcription- polymerase chain reaction (qRT-PCR) were used to screen the expression profiles and predict the potential roles of tsRNAs in MIBC. Of 406 tsRNAs differentially expressed in MIBC tissues, 91 tsRNAs were significantly differentially expressed. Then, four candidate tsRNAs, tiRNA-1:34-Val-CAC-2, tiRNA-1:33-Gly-GCC-1, tRF-1:32-Gly-GCC-1, and tRF-+1:T20-Ser-TGA-1, were selected. Next, a bioinformatics analysis showed the potential target genes and tsRNA–mRNA network. The most significant and meaningful terms of gene ontology were the positive regulation of the phosphate metabolic process, lamellipodium, and protein-cysteine S-acyltransferase activity in the biological process, cellular component, and molecular function, respectively. In addition, the top four pathways were predicted by the Kyoto Encyclopedia of Genes and Genomes database (KEGG). Finally, qRT-PCR demonstrated a similar expression pattern compared to sequencing data for the candidate tsRNAs. In short, we find differential expression profiles and predict that tiRNA-1:33-Gly-GCC-1, tRF-1:32-Gly-GCC-1, and tRF-+1:T20-Ser-TGA-1 are very likely to engage in the pathophysiological process of MIBC via regulating the target genes in the key pathways.