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Research in Review

Microbiome Signature Helps Predict Prostate Cancer

Transcriptome sequencing that identifies pathogens in prostate cancer biopsies can be used as a signature for disease detection, according to research presented at the 2017 ASCO Annual Meeting (June 2-6, 2017; Chicago, IL).

Tumor biopsies are closely related to microbial species due to proximity with microbial communities or contamination during tissue processing. However, tumor biopsies have not been evaluated for tumor-associated microbiome in prostate cancer.

Researchers from the Weill Cornell Medical College (New York, NY) examined sequencing data from tumor biopsies of 32 patients with prostate cancer (n = 23 from primary tumor, n = 9 metastatic prostate cancer) from 2013 to 2015. Among the 9 metastatic samples, 5 were metastatic prostate cancer to bone and 4 were other metastases.

Total RNA was recorded from patient tumor biopsies for RNA sequencing. Approximately 268 million paired-end RNA-sequencing reads were generated, leading to 27 billion bases. Kraken and FusionCatcher software were used to identify the metagenome that maps to microbial species. Researchers analyzed microbial pathogens and created a heatmap of microbial abundance in prostate cancer. A giant cell tumor in bone was used as a control.

Researchers found 43 unique pathogens included in the microbiome associated with prostate cancer. Among those pathogens, the most abundant in prostate cancer bone metastases were also found to be the most abundant in primary prostate tumors.

Additionally, researchers found that prostate cancer bone metastases clustered separately from the primary prostate cancer samples, other metastases, and primary bone cancer.

The study’s findings indicate a putative microbiome signature associated with prostate cancer, which can be used as a predictive measure for such disease. Prostate cancer bone metastases cluster independently from prostate cancer, which suggests a non-random association with microbial communities.

Further research is needed to validate microbial association through orthogonal analyses and to more accurately identify the origin of the signature.—Zachary Bessette

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