Search

Recent prostate-specific antigen–based screening trials indicate an urgent need for novel and noninvasive biomarker identification strategies to improve the prediction of prostate cancer behavior. Noncoding microRNAs (miRNA) in the serum and plasma have been shown to have potential as noninvasive markers for physiologic and pathologic conditions. To identify serum miRNAs that diagnose and correlate with the prognosis of prostate cancer, we developed a multiplex quantitative reverse transcription PCR method involving the purification of multiplex PCR products followed by uniplex analysis on a microfluidics chip to evaluate 384 human miRNAs. Using Dgcr8 and Dicer knockout (small RNA-deficient) mouse ES cells as the benchmark, we confirmed the validity of our technique and uncovered a considerable lack of accuracy in previously published methods. Profiling 48 sera from healthy men and untreated prostate cancer patients with differing CAPRA scores, we identified miRNA signatures that allow us to diagnose cancer patients and correlate with a prognosis. These serum signatures include oncogenic and tumor-suppressive miRNAs, suggesting functional roles in prostate cancer progression. Cancer Res; 71(2); 550–60. ©2010 AACR.

Advanced prostate cancer (PC) is treated primarily by means of chemotherapy with one of the clinically approved microtubule (MT)-targeting agents (MTAs): paclitaxel, docetaxel and cabazitaxel. The mechanism of action of the MTAs on the cellular level is to bind to MTs and inhibit MT-dependent intracellular pathways, ultimately leading to cell death. In PC, MTAs are the only chemotherapy class shown to improve survival, however, there is high variability of response to MTA chemotherapy among patients as well as emergence of resistance to drug action which hampers the clinical efficacy. Clinicians need additional information to match individual patient tumors to the most effective drugs or refrain from treating patients that will not respond. However, the precise mechanism of action or resistance development to MTAs is not understood, which represents a critical gap in our knowledge to select the best treatment. Our hypothesis is that there are inherent differences in tumor MT dynamics among individual patients which dictates their response to treatment with specific MTAs. To this end, we envision that a systematic characterization of PC MT dynamics and their response to MTAs will allow chemotherapy customization and prolong survival. Specifically, our approach consists of the analysis of metastatic castrate resistant PC (mCRPC) organoids (Gao D. et al, 2014) derived from bone (acetabulum, vertebrae), soft tissue (salvage prostatectomy, lymph nodes), pleural effusion and circulating tumor cells biopsy samples obtained from metastatic patients who have received hormonal therapy and the MTA docetaxel or hormonal therapy alone or no treatment. We apply a quantitative single-cell image analysis algorithm (ClusterTrack) to measure a panel of twelve distinct MT dynamics parameters (a MT dynamics signature). Preliminary analysis suggests differences between different mCRPC organoids. MT tracking results indicate a correlation of decreased MT growth rate with increased Op18/stathmin expression. In this context, we hypothesize that differential expression of MT regulating genes affects specific parameters of MT dynamics, thus determining the sensitivity to MTA treatment. Citation Format: Alexandre Matov, Johan de Rooij, Jay Gatlin, Julia Rohrberg, Nikta Ahmad, Rahul Aggarwal, Jeff Simko, Andrei Goga, Charles Ryan, Torsten Wittmann. Investigating microtubule growth dynamics in patient-derived metastatic prostate cancer cells. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 243.