Newswise — New Brunswick, N.J. – August 22, 2016 - Research from investigators at Rutgers Cancer Institute of New Jersey; University of California, Los Angeles (UCLA); University of California, Santa Cruz and other institutions shows a computational approach examining abnormal “signaling” in clinical prostate cancer tissues that is responsible for their spread and resistance to treatment and can help identify patient subsets for targeted therapies. Rutgers Cancer Institute researcher Justin Drake, PhD, an assistant professor of medicine at Rutgers Robert Wood Johnson Medical School who started the work as part of postdoctoral research at UCLA, is a co-lead and co-corresponding author of the study published in the August 4 edition of Cell (DOI: http://dx.doi.org/10.1016/j.cell.2016.07.007). He shares more about the work:

Q: Why is this topic important to explore? A: Defining patient subsets that will best respond to appropriate cancer therapies remains a difficult clinical challenge – especially in prostate cancer for which patients are treated similarly and there are no subtypes to stratify for treatment purposes. Typically, cancers are characterized and treated by the genetic mutations that drive the particular disease. In prostate cancer, however, these driver mutations are less common. Our current and previous publications attempt to explore new approaches to find these drivers where mutations may not tell the whole story. Our approach helps to identify new therapeutic targets in prostate cancer that may not have been uncovered by simply looking at mutations alone.

Q: How did you approach this work? A: We evaluated genomic and proteomic features in clinical tissue from patients whose prostate cancer had spread and was no longer responsive to hormone therapy (metastatic castrate-resistant prostate cancer). Using advanced computational/systems biology approaches we were able to integrate these different features to generate more robust signaling networks. The key to this approach is that we developed the computational pipeline to integrate new phosphoproteomic information from these patients. This allowed us to evaluate which signaling proteins may be possible drivers in this disease in the absence of driver mutations. We were able to identify several signaling proteins, known as kinases, which have high potential to be targeted for cancer therapy. From our studies, we now have the opportunity to pinpoint these kinases in individual patients paving the way for a future precision medicine-based approach clinically which is very exciting.

Q: What is the implication of this finding?A: These results provide the momentum for further investigation in in vivo model systems to determine if the kinases we identified are truly the drivers of metastatic prostate cancer. Overall, our approach has given us a different perspective on how we evaluate tumors for clinical decision making. It is becoming more apparent that proteomics (or phosphoproteomics) will be used to complement already established clinical tools such as genomic profiling to find altered signaling pathways. As the technology progresses to more sensitively detect proteins in tumor tissues, I anticipate that in the near future it will become standard for a patient to have both a proteomics and a genomics portrait conducted and the results of which will be used to better guide treatment decisions.

Grants from the Department of Defense Prostate Cancer Research Program (W81XWH-14-1-0148) and Prostate Cancer Foundation Young Investigator Award to Dr. Drake helped support this work. The research also was supported by grants from the National Institutes of Health, American Cancer Society, and Stand Up to Cancer. (The Stand Up to Cancer Prostate Cancer Foundation Prostate Dream Team Translational Cancer Research Grant is made possible by the generous support of the Movember Foundation. Stand Up To Cancer is a program of the Entertainment Industry Foundation administered by the American Association for Cancer Research.)

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