Klein, Eric A

Objectives To determine the prognostic potential of a 24‐gene signature, Sig24, for identifying patients with prostate cancer who are at risk of developing metastases or of prostate cancer‐specific mortality (PCSM) after radical prostatectomy (RP). Patients and Methods Sig24 scores were calculated from previously collected gene expression microarray data from the Cleveland Clinic and Mayo Clinic (I and II). The performance of Sig24 was determined using time‐dependent c‐index analysis, Cox proportional hazards regression and Kaplan–Meier survival analysis. Results Higher Sig24 scores were significantly associated with higher pathological Gleason scores in all three cohorts. Analysis of the Mayo Clinic II cohort, which included time‐to‐event information, indicated that patients with high Sig24 scores also had a higher risk of developing metastasis (hazard ratio [HR] 3.78, 95% confidence interval [CI]: 1.96–7.29; P < 0.001) or of PCSM (HR 6.54, 95% CI: 2.16–19.83; P < 0.001). Conclusions The findings of the present study show the applicability of Sig24 for the prognosis of metastasis or PCSM after RP. Future studies investigating the combination of Sig24 with available prognostic tests may provide new approaches to improve risk stratification for patients with prostate cancer.

Abstract Serum levels of miR-194 have been reported to predict prostate cancer recurrence after surgery, but its functional contributions to this disease have not been studied. Herein, it is demonstrated that miR-194 is a driver of prostate cancer metastasis. Prostate tissue levels of miR-194 were associated with disease aggressiveness and poor outcome. Ectopic delivery of miR-194 stimulated migration, invasion, and epithelial–mesenchymal transition in human prostate cancer cell lines, and stable overexpression of miR-194 enhanced metastasis of intravenous and intraprostatic tumor xenografts. Conversely, inhibition of miR-194 activity suppressed the invasive capacity of prostate cancer cell lines in vitro and in vivo. Mechanistic investigations identified the ubiquitin ligase suppressor of cytokine signaling 2 (SOCS2) as a direct, biologically relevant target of miR-194 in prostate cancer. Low levels of SOCS2 correlated strongly with disease recurrence and metastasis in clinical specimens. SOCS2 downregulation recapitulated miR-194–driven metastatic phenotypes, whereas overexpression of a nontargetable SOCS2 reduced miR-194–stimulated invasion. Targeting of SOCS2 by miR-194 resulted in derepression of the oncogenic kinases FLT3 and JAK2, leading to enhanced ERK and STAT3 signaling. Pharmacologic inhibition of ERK and JAK/STAT pathways reversed miR-194–driven phenotypes. The GATA2 transcription factor was identified as an upstream regulator of miR-194, consistent with a strong concordance between GATA2 and miR-194 levels in clinical specimens. Overall, these results offer new insights into the molecular mechanisms of metastatic progression in prostate cancer. Cancer Res; 77(4); 1021–34. ©2016 AACR.

Abstract Background: Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma. Methods: We performed association testing of common variation in eight regions in 1,318 patients with multiple myeloma and 1,480 controls of European ancestry and 1,305 patients with multiple myeloma and 7,078 controls of African ancestry and conducted a meta-analysis to localize the signals, with epigenetic annotation used to predict functionality. Results: We found that variants in 7p15.3, 17p11.2, 22q13.1 were statistically significantly (P &lt; 0.05) associated with multiple myeloma risk in persons of African ancestry and persons of European ancestry, and the variant in 3p22.1 was associated in European ancestry only. In a combined African ancestry–European ancestry meta-analysis, variation in five regions (2p23.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) was statistically significantly associated with multiple myeloma risk. In 3p22.1, the correlated variants clustered within the gene body of ULK4. Correlated variants in 7p15.3 clustered around an enhancer at the 3′ end of the CDCA7L transcription termination site. A missense variant at 17p11.2 (rs34562254, Pro251Leu, OR, 1.32; P = 2.93 × 10−7) in TNFRSF13B encodes a lymphocyte-specific protein in the TNF receptor family that interacts with the NF-κB pathway. SNPs correlated with the index signal in 22q13.1 cluster around the promoter and enhancer regions of CBX7. Conclusions: We found that reported multiple myeloma susceptibility regions contain risk variants important across populations, supporting the use of multiple racial/ethnic groups with different underlying genetic architecture to enhance the localization and identification of putatively functional alleles. Impact: A subset of reported risk loci for multiple myeloma has consistent effects across populations and is likely to be functional. Cancer Epidemiol Biomarkers Prev; 25(12); 1609–18. ©2016 AACR.

Abstract Prostate cancer is a biologically heterogeneous disease with variable molecular alterations underlying cancer initiation and progression. Despite recent advances in understanding prostate cancer heterogeneity, better methods for classification of prostate cancer are still needed to improve prognostic accuracy and therapeutic outcomes. In this study, we computationally assembled a large virtual cohort (n = 1,321) of human prostate cancer transcriptome profiles from 38 distinct cohorts and, using pathway activation signatures of known relevance to prostate cancer, developed a novel classification system consisting of three distinct subtypes (named PCS1–3). We validated this subtyping scheme in 10 independent patient cohorts and 19 laboratory models of prostate cancer, including cell lines and genetically engineered mouse models. Analysis of subtype-specific gene expression patterns in independent datasets derived from luminal and basal cell models provides evidence that PCS1 and PCS2 tumors reflect luminal subtypes, while PCS3 represents a basal subtype. We show that PCS1 tumors progress more rapidly to metastatic disease in comparison with PCS2 or PCS3, including PSC1 tumors of low Gleason grade. To apply this finding clinically, we developed a 37-gene panel that accurately assigns individual tumors to one of the three PCS subtypes. This panel was also applied to circulating tumor cells (CTC) and provided evidence that PCS1 CTCs may reflect enzalutamide resistance. In summary, PCS subtyping may improve accuracy in predicting the likelihood of clinical progression and permit treatment stratification at early and late disease stages. Cancer Res; 76(17); 4948–58. ©2016 AACR.

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.