lunes, 10 de abril de 2017

Characterisation of microbial communities within aggressive prostate cancer tissues. - PubMed - NCBI

Characterisation of microbial communities within aggressive prostate cancer tissues. - PubMed - NCBI

 2017 Jan 13;12:4. doi: 10.1186/s13027-016-0112-7. eCollection 2017.

Characterisation of microbial communities within aggressive prostate cancer tissues.



An infectious aetiology for prostate cancer has been conjectured for decades but the evidence gained from questionnaire-based and sero-epidemiological studies is weak and inconsistent, and a causal association with any infectious agent is not established. We describe and evaluate the application of new technology to detect bacterial and viral agents in high-grade prostate cancer tissues. The potential of targeted 16S rRNA gene sequencing and total RNA sequencing was evaluated in terms of its utility to characterise microbial communities within high-grade prostate tumours.


Two different Massively Parallel Sequencing (MPS) approaches were applied. First, to capture and enrich for possible bacterial species, targeted-MPS of the V2-V3 hypervariable regions of the 16S rRNA gene was performed on DNA extracted from 20 snap-frozen prostate tissue cores from ten "aggressive" prostate cancer cases. Second, total RNA extracted from the same prostate tissue samples was also sequenced to capture the sequence profile of both bacterial and viral transcripts present.


Overall, 16S rRNA sequencing identified Enterobacteriaceae species common to all samples and P. acnes in 95% of analyzed samples. Total RNA sequencing detected endogenous retroviruses providing proof of concept but there was no evidence of bacterial or viral transcripts suggesting active infection, although it does not rule out a previous 'hit and run' scenario.


As these new investigative methods and protocols become more refined, MPS approaches may be found to have significant utility in identifying potential pathogens involved in disease aetiology. Further studies, specifically designed to detect associations between the disease phenotype and aetiological agents, are required.


16S rRNA; Infection; Propionibacterium acnes; Prostate cancer; RNA; Sexually transmitted infection; cDNA


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