Dan Mercola, M.D., Ph.D.
University of California, Irvine
Dr. Mercola's program will refine and validate profiles that predict relapse in prostate cancer patients. These profiles will help distinguish indolent disease from disease that will progress. Dr. Mercola has developed anovel algorithm, during work carried out during the Director's Challenge program, that enables the assignment of molecular signatures to different cell types present in the prostate tumor. This algorithm captures important information about tumor-stromal interactions taking place in the diseased gland. Based on this algorithm, ~1,100 genes have been associated with relapse. The profile has been refined to 200 high priority relapse-associated genes. The profile will be refined further, confirmed using independent analytical strategies and validated in an observational clinical validation trial.
Koziol JA et al (2009) The wisdom of the commons: ensemble tree classifiers for prostate cancer prognosis. Bioinformatics 25: 54-60. PMID: 18628288
Development by the Mercola SPECS project of a classifier to distinguish indolent from aggressive prostate cancer.