Analytical Validation of a Cell Cycle Progression Signature Used as a Prognostic Marker in Prostate Cancer

  • Julia E M
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Abstract

Background: Prostate cancer is the most common cancer in men in the developed world. Appropriate clinical care requires accurate prognostic information to determine whether definitive treatment or conservative management is most appropriate for a given patient. We previously demonstrated that a gene expression signature, which measures the RNA expression of 31 cell cycle progression (CCP) genes and generates a CCP score, is a robust predictor of patient outcome in cohorts of conservatively managed patients diagnosed by needle biopsy or transurethral resection of the prostate. Methods: These current studies represent the analytical validation of this gene signature, for the testing of either formalin-fixed paraffin-embedded (FFPE) prostate resection tissue (radical prostatectomy, RP) or FFPE prostate needle biopsy samples. Results: Results: The measured standard deviation (SD) of the signature was determined to be 0.1 score units, representing 1.6% of the range of scores observed within previous clinical validation studies. Individual amplicons for all genes within the signature had a SD <1 CT , with a median SD of 0.52 CT ’s. We observed the median amplification efficiency for all genes was 92.6%. The linear range of the signature was over a ~260-fold range of RNA concentrations. We observed that 100% of RP samples and 99.8% of needle biopsy samples produced sufficient RNA for testing, when RNA was extracted from 7,525 recent prostate samples. Finally, RNA samples were able to reproduce similar CCP scores when stored for up to 8 weeks. Conclusion: These studies indicate that this prognostic gene signature is robust and reproducible, and is analytically validated for use on FFPE prostate biopsy radical prostatectomy samples.\r

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APA

Julia E, M. B. W. (2015). Analytical Validation of a Cell Cycle Progression Signature Used as a Prognostic Marker in Prostate Cancer. Journal of Molecular Biomarkers & Diagnosis, 06(04). https://doi.org/10.4172/2155-9929.1000239

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