Ross, Ashley E.

Abstract Purpose: There is a clear need to improve risk stratification and to identify novel therapeutic targets in aggressive prostate cancer. The goal of this study was to investigate genes with outlier expression with prognostic association in high-risk prostate cancer patients as potential biomarkers and drug targets. Experimental Design: We interrogated microarray gene expression data from prostatectomy samples from 545 high-risk prostate cancer patients with long-term follow-up (mean 13.4 years). Three independent clinical datasets totaling an additional 545 patients were used for validation. Novel prognostic outlier genes were interrogated for impact on oncogenic phenotypes in vitro using siRNA-based knockdown. Association with clinical outcomes and comparison with existing prognostic instruments was assessed with multivariable models using a prognostic outlier score. Results: Analysis of the discovery cohort identified 20 prognostic outlier genes. Three top prognostic outlier genes were novel prostate cancer genes; NVL, SMC4, or SQLE knockdown reduced migration and/or invasion and outlier expression was significantly associated with poor prognosis. Increased prognostic outlier score was significantly associated with poor prognosis independent of standard clinicopathologic variables. Finally, the prognostic outlier score prognostic association is independent of, and adds to existing genomic and clinical tools for prognostication in prostate cancer (Decipher, the cell-cycle progression signature, and CAPRA-S). Conclusions: To our knowledge, this study represents the first unbiased high-throughput investigation of prognostic outlier genes in prostate cancer and demonstrates the potential biomarker and therapeutic importance of this previously unstudied class of cancer genes. Clin Cancer Res; 22(7); 1777–86. ©2015 AACR.

Abstract Background: Prostate cancer molecular subtypes based on ETS gene fusions and SPINK1 were originally identified through distinct gene expression profiles. Such molecular subtypes may have utility in disease stratification and clonality assessment, complementing available purely prognostic tests. Hence, we determined the analytical validity of molecular subtyping and explored clinical associations using global gene expression profiles in a large cohort of PCa. Methods: We analyzed 1,577 patient Affymetrix Human Exon 1.0ST GeneChip expression profiles from 8 radical prostatectomy (RP) cohorts; 5 of them generated as part of the Decipher® platform for the Decipher® discovery or validation. Multi-feature random forest classifiers and outlier analysis were used to define microarray-based molecular subtypes and characterize clinical associations. Results: A random forest (RF) classifier (m-ERG) was trained and validated to predict ERG fusion status using separate subsets of a single-institution RP cohort (total n=407) with known ERG rearrangement status defined by FISH, achieving >95% sensitivity and specificity in the validation subset. The model was then applied to 7 independent RP cohorts to predict ERG rearrangement status. Less frequent rearrangements involving other ETS genes (ETV1, ETV4, ETV5, FLI1) or SPINK1 over-expression were predicted based on gene expression outlier analysis. Across cohorts, 45%, 9% 8% and 38% of PCa were classified as ERG+, ERG—ETS+, ERG—SPINK+, and Triple Negative (ERG—/ETS—/SPINK1—), respectively. Global gene expression analysis shows that the four subtypes could be collapsed into three entities (ERG+, ERG—ETS+ and SPINK+/Triple Negative) based on expression patterns and clinical characteristics similarity. Based on multivariable analysis, ERG+ is significantly associated with lower pre-PSA (p<0.001), lower Gleason score (p<0.001), the presence of extraprostatic extension (p<0.001) and European Americans (p<0.001), but not associated with outcome. ERG—ETS+ is significantly associated with SVI (p=0.01) and ERG—SPINK+ is enriched in African Americans (p<0.001). Conclusions: The Decipher® platform can accurately determine ERG rearrangement status and PCa molecular subtypes. Inclusion of molecular subtyping, such as m-ERG status, may enable additional precision medicine opportunities in prognostic tests and provides insights into the development of novel therapeutic approaches. Citation Format: Mohammed Alshalalfa, Scott A. Tomlins, Nicholas Erho, Kasra Yousefi, Shuang Zhao, Robert B. Den, Adam P. Dicker, Bruce Trock, Angelo DeMarzo, Edward M. Schaeffer, Ashley Ross, Eric A. Klein, Cristina Magi-Galluzzi, Jeffery R. Karnes, Robert B Jenkins, Elai Davicioni, Felix Feng. Molecular and clinical characterization of 1,577 primary prostate cancer tumors reveals novel clinical and biological insights into its subtypes. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A1-64.

Abstract Purpose: Prostate cancers incite tremendous morbidity upon metastatic growth. We previously identified Asporin (ASPN) as a potential mediator of metastatic progression found within the tumor microenvironment. ASPN contains an aspartic acid (D)-repeat domain and germline polymorphisms in D-repeat-length have been associated with degenerative diseases. Associations of germline ASPN D polymorphisms with risk of prostate cancer progression to metastatic disease have not been assessed. Experimental Design: Germline ASPN D-repeat-length was retrospectively analyzed in 1,600 men who underwent radical prostatectomy for clinically localized prostate cancer and in 548 noncancer controls. Multivariable Cox proportional hazards models were used to test the associations of ASPN variations with risk of subsequent oncologic outcomes, including metastasis. Orthotopic xenografts were used to establish allele- and stroma-specific roles for ASPN D variants in metastatic prostate cancer. Results: Variation at the ASPN D locus was differentially associated with poorer oncologic outcomes. ASPN D14 [HR, 1.72; 95% confidence interval (CI), 1.05–2.81, P = 0.032] and heterozygosity for ASPN D13/14 (HR, 1.86; 95% CI, 1.03–3.35, P = 0.040) were significantly associated with metastatic recurrence, while homozygosity for the ASPN D13 variant was significantly associated with a reduced risk of metastatic recurrence (HR, 0.44; 95% CI, 0.21–0.94, P = 0.035) in multivariable analyses. Orthotopic xenografts established biologic roles for ASPN D14 and ASPN D13 variants in metastatic prostate cancer progression that were consistent with patient-based data. Conclusions: We observed associations between ASPN D variants and oncologic outcomes, including metastasis. Our data suggest that ASPN expressed in the tumor microenvironment is a heritable modulator of metastatic progression. Clin Cancer Res; 22(2); 448–58. ©2015 AACR.

Prostate cancer is the second leading cause of cancer death among United States men. However, disease aggressiveness is varied, with low-grade disease often being indolent and high-grade cancer accounting for the greatest density of deaths. Outcomes are also disparate among men with high-grade prostate cancer, with upwards of 65% having disease recurrence even after primary treatment. Identification of men at risk for recurrence and elucidation of the molecular processes that drive their disease is paramount, as these men are the most likely to benefit from multimodal therapy. We previously showed that androgen-induced expression profiles in prostate development are reactivated in aggressive prostate cancers. Herein, we report the down-regulation of one such gene, Sparcl1 , a secreted protein, acidic and rich in cysteine (SPARC) family matricellular protein, during invasive phases of prostate development and regeneration. We further demonstrate a parallel process in prostate cancer, with decreased expression of SPARCL1 in high-grade/metastatic prostate cancer. Mechanistically, we demonstrate that SPARCL1 loss increases the migratory and invasive properties of prostate cancer cells through Ras homolog gene family, member C (RHOC), a known mediator of metastatic progression. By using models incorporating clinicopathologic parameters to predict prostate cancer recurrence after treatment, we show that SPARCL1 loss is a significant, independent prognostic marker of disease progression. Thus, SPARCL1 is a potent regulator of cell migration/invasion and its loss is independently associated with prostate cancer recurrence.