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    Prostate Ca phenotypic assay predicts adverse clinical pathology

    Prostate cancer makes up over 28% of total cancer cases in the United States, but current screening measures are unable to objectively assess the aggressiveness of tumors. In this interview, David Albala, MD, describes his group’s research on a diagnostic platform that is based on the measurement of a panel of phenotypic and molecular biomarkers in live biopsy-derived cells. The award-winning poster was presented at the 2016 AUA annual meeting in San Diego. Dr. Albala was interviewed by J. Brantley Thrasher, MD, a Urology Times editorial consultant.

    Dr. Thrasher: Please give us a brief overview of the poster you presented at the AUA annual meeting in San Diego.

    Dr. Albala: Essentially, our work looked at a novel phenotypic marker system for prostate cancer cells. What we’ve been able to do is take prostate cancer cells, grow them out in an extracellular matrix, then process them in a microfluidic device. Then using machine algorithms, we are able to essentially assess prostate cancer aggressiveness or adverse pathology using machine algorithms. So we can look at the cells and how the cells interact with one another, then predict adverse pathology versus non-adverse pathology. What’s unique about this process is that it can be done within 72 hours.

    Dr. Thrasher: If you look at some of the genomic profiling being done, how does this compare?

    Dr. Albala: I think the easiest analogy is the genomic profiling essentially is looking at a set of genes and how they interact with a particular cancer. What we’re doing is looking at a video, if you will, of how the cells interact with one another and then from that interaction, assessing malignant potential or adverse pathology. What we found is that the accuracy of the phenotypic markers is a little better than what we’ve seen with the genotypic markers and in the Gleason score.

    Dr. Thrasher: Do you have plans to do a comparison between your phenotypic marker and the genotypic profiling that’s out there now with tests such as Decipher?

    Dr. Albala: We’ve done that preliminarily. First was a validation study looking at 300 prostate cancer patients. One thing that we found that was interesting is now we’re seeing a field effect. So we can biopsy tissue, not necessarily tumor itself but near the tumor, and essentially be predictive. The areas under the curve are close to 90%. So the sensitivity and specificity are much, much better.

    Dr. Thrasher: Thank you very much, and congratulations.

    Dr. Albala: Thank you.

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