Stratification of aggressive prostate cancer from indolent disease-Prospective controlled trial utilizing expression of 11 genes in apparently benign tissue.

BACKGROUND The aim of the study was to evaluate the diagnostic power of molecular markers in men with a clinical suspicion of prostate cancer (PCa) using apparently benign areas as targeted by magnetic resonance imaging (MRI). METHODS In the study, 99 consecutive men with clinical suspicion of PCa in a prospective controlled trial (IMPROD, NCT01864135) were included. In addition to 12-core systematic and MRI-targeted biopsies, cores from normal-appearing prostate areas, based on clinical examination, ultrasound, and biparametric prostate MRI, were obtained. The RNA transcript levels of ACSM1, AMACR, CACNA1D, DLX1, KLK3, PCA3, PLA2G7, RHOU, SPINK1, SPON2, TMPRSS2-ERG, and TDRD1 were measured with quantitative reverse-transcription polymerase chain reaction. RESULTS Of the 99 men, 69 were diagnosed with PCa, 31 with primary Gleason pattern 3 and 38 with primary Gleason 4 or 5. TDRD1 messenger RNA (mRNA) levels were 1.3 times higher (P = 0.029) and the presence of TMPRSS2-ERG mRNAs more frequent in biopsies from men diagnosed with PCa (27/69, 39%) than in men without (5/30, 16%) (P = 0.035). The 2 markers identified aggressive PCa defined as Gleason sum≥7 at biopsy: median TDRD1 mRNA level was 1.4 higher (P = 0.005) and TMPRSS2-ERG expression more frequent (P<0.001) in high-grade cancer. A multivariate analysis of mRNA expression of 11 candidate genes combined with KLK3, serum prostate-specific antigen (PSA), percentage-free PSA, and prostate volume improved the discrimination between aggressive and nonaggressive PCa (area under the curve = 0.77) compared with the use of the candidate genes or clinical parameters alone. However, serum PSA, percentage-free PSA, and prostate volume resulted in the best discrimination between non-organ-confined PCa (T3) from organ-confined PCa (T2) and healthy prostate (area under the curve = 0.86). CONCLUSIONS Of the 11 studied genes, TDRD1 and TMPRSS2-ERG were able to statistically significantly differentiate men with PCa from men without it as single markers. However, a multivariate analysis using 15 features outperformed each individual marker in identifying aggressive PCa.

[1]  Gilles Louppe,et al.  Independent consultant , 2013 .

[2]  L. Marks,et al.  APTIMA PCA3 molecular urine test: development of a method to aid in the diagnosis of prostate cancer. , 2006, Clinical chemistry.

[3]  H. Merisaari,et al.  Prebiopsy multiparametric 3T prostate MRI in patients with elevated PSA, normal digital rectal examination, and no previous biopsy , 2015, Journal of magnetic resonance imaging : JMRI.

[4]  K. Pettersson,et al.  Quantitative real-time RT-PCR assay for PCA3. , 2008, Clinical biochemistry.

[5]  J. Schalken,et al.  Rational basis for the combination of PCA3 and TMPRSS2:ERG gene fusion for prostate cancer diagnosis , 2013, The Prostate.

[6]  A. Ylikoski,et al.  Time-resolved fluorometry in end-point and real-time PCR quantification of nucleic acids. , 2000, Luminescence : the journal of biological and chemical luminescence.

[7]  G. Jenster,et al.  Identification of TDRD1 as a direct target gene of ERG in primary prostate cancer , 2013, International journal of cancer.

[8]  Thomas Hambrock,et al.  Magnetic resonance imaging guided prostate biopsy in men with repeat negative biopsies and increased prostate specific antigen. , 2010, The Journal of urology.

[9]  M. Cooperberg,et al.  Validation of a cell-cycle progression gene panel to improve risk stratification in a contemporary prostatectomy cohort. , 2012, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[10]  S. Leys,et al.  Optimization of preservation and storage time of sponge tissues to obtain quality mRNA for next‐generation sequencing , 2012, Molecular ecology resources.

[11]  Matthias Nees,et al.  Validation of Novel Biomarkers for Prostate Cancer Progression by the Combination of Bioinformatics, Clinical and Functional Studies , 2016, PloS one.

[12]  B. Trock,et al.  Evaluation of GSTP1 and APC methylation as indicators for repeat biopsy in a high‐risk cohort of men with negative initial prostate biopsies , 2012, BJU international.

[13]  P. Febbo,et al.  A 17-gene assay to predict prostate cancer aggressiveness in the context of Gleason grade heterogeneity, tumor multifocality, and biopsy undersampling. , 2014, European urology.

[14]  Tapio Salakoski,et al.  An experimental comparison of cross-validation techniques for estimating the area under the ROC curve , 2011, Comput. Stat. Data Anal..

[15]  M. Karp,et al.  High-performance real-time quantitative RT-PCR using lanthanide probes and a dual-temperature hybridization assay. , 2002, Analytical chemistry.

[16]  L. Pusztai,et al.  Effects of tissue handling on RNA integrity and microarray measurements from resected breast cancers. , 2011, Journal of the National Cancer Institute.

[17]  H. Lilja,et al.  Association of transcript levels of 10 established or candidate-biomarker gene targets with cancerous versus non-cancerous prostate tissue from radical prostatectomy specimens. , 2013, Clinical biochemistry.

[18]  O. Kallioniemi,et al.  Defining the molecular action of HDAC inhibitors and synergism with androgen deprivation in ERG‐positive prostate cancer , 2008, International journal of cancer.

[19]  Andrew J Vickers,et al.  Cancer-associated changes in the expression of TMPRSS2-ERG, PCA3, and SPINK1 in histologically benign tissue from cancerous vs noncancerous prostatectomy specimens. , 2014, Urology.

[20]  Pekka Taimen,et al.  Global expression of AMACR transcripts predicts risk for prostate cancer – a systematic comparison of AMACR protein and mRNA expression in cancerous and noncancerous prostate , 2016, BMC Urology.

[21]  Zhaohui S. Qin,et al.  An integrated network of androgen receptor, polycomb, and TMPRSS2-ERG gene fusions in prostate cancer progression. , 2010, Cancer cell.

[22]  O. Kallioniemi,et al.  TMPRSS2 fusions with oncogenic ETS factors in prostate cancer involve unbalanced genomic rearrangements and are associated with HDAC1 and epigenetic reprogramming. , 2006, Cancer research.

[23]  C. Roehrborn,et al.  Using biopsy to detect prostate cancer. , 2008, Reviews in urology.

[24]  David L Rimm,et al.  Development and Clinical Validation of an In Situ Biopsy-Based Multimarker Assay for Risk Stratification in Prostate Cancer , 2015, Clinical Cancer Research.

[25]  J. Oxley,et al.  Suitability of PSA-detected localised prostate cancers for focal therapy: experience from the ProtecT study , 2011, British Journal of Cancer.

[26]  H. Lehrach,et al.  ERG Induces Epigenetic Activation of Tudor Domain-Containing Protein 1 (TDRD1) in ERG Rearrangement-Positive Prostate Cancer , 2013, PloS one.

[27]  Anonymous Author Robust Reductions from Ranking to Classification , 2006 .

[28]  Vijayalakshmi Ananthanarayanan,et al.  Evidence for field cancerization of the prostate , 2009, The Prostate.

[29]  Tania Nolan,et al.  Pitfalls of quantitative real-time reverse-transcription polymerase chain reaction. , 2004, Journal of biomolecular techniques : JBT.

[30]  William J Catalona,et al.  Serial biopsy results in prostate cancer screening study. , 2002, The Journal of urology.