Searching the Resource Information Network
Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
Recent studies have shown that microorganisms may be associated with the onset and development of bladder cancer. The purpose of this study is to identify the common core bacteria associated with bladder cancer. We characterized the urinary microbial profile of the individuals with bladder cancer by 16S rRNA gene sequencing, and the results of 24 bladder cancer samples collected in our laboratory reveal 31 common core bacteria at genera level. In addition, the abundance of four common core bacteria is significantly higher in bladder cancer samples than in samples from nondiseased people analyzed by LEfSe, based on two previous datasets. In particular, the abundance of Acinetobacter is much higher in bladder cancer samples. It has been reported that Acinetobacter is involved not only in biofilm formation but also in the adhesion and invasion of epithelial cells, the spread of bacteria caused by the degradation of phospholipids in the mucosal barrier, and the escape of the host immune response. Thus, Acinetobacter may be related to bladder cancer and is a potential microbial marker of bladder cancer. However, due to the limited number of participants, further studies are needed to better understand the role of microorganisms in bladder cancer to provide novel biomarkers for diagnosis, prognosis, and therapy.
Pubmed ID: 31321235
Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 23,2023.Software package for comparison and analysis of microbial communities, primarily based on high-throughput amplicon sequencing data, but also supporting analysis of other types of data. QIMME analyzes and transforms raw sequencing data generated on Illumina or other platforms to publication quality graphics and statistics.
View all literature mentionsCommercial vendor and service provider of laboratory reagents and antibodies. Supplier of scientific instrumentation, reagents and consumables, and software services.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Algorithm for high-dimensional biomarker discovery and explanation that identifies genes, pathways, or taxa characterizing the differences between two or more biological conditions. The algorithm identifies features that are statistically different among biological classes, then performs additional tests to assess whether these differences are consistent with respect to expected biological behavior. Statistical significance and biological relevance are emphasized.
View all literature mentions