Klein, Eric A.

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 < 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 In the era of precision medicine, genomic classifications of prostate cancer (PC) have not broadly impacted patient care. Here we present an integrative transcriptome analysis of 14 disease-related pathways in over 4,600 clinical specimens and 25 PC preclinical models. This approach provides a novel classification scheme, inclusive of 3 PC subtypes (PCS1-3), which predict disease progression and drug resistance. The PCS1 and PCS2 categories possess characteristics of luminal cells, while PCS3 exhibits basal features. Castration-resistant and metastatic cancers are over-represented in PCS1 and PCS3 tumors. All 3 subtypes are represented in commonly used PC cell lines; however, none of the mouse models we analyzed resembles PCS3. PCS classification using RNA expression data appears to be stable across primary and metastatic human tumors, cell lines, xenografts and mouse models. This new subtyping method provides novel opportunities for patient stratification that reflect specific features of tumor biology and may influence therapeutic decisions. Citation Format: Sungyong You, Beatrice Knudsen, Nicholas Erho, Mohammed Alshalalfa, Mandeep Takhar, Hussam Al-deen Ashab, Elai Davicioni, Robert Jeffrey Karnes, Eric A. Klein, Robert B. Den, Ashley E. Ross, Edward M. Schaeffer, Isla P. Garraway, Jayoung Kim, Michael R. Freeman. Three intrinsic subtypes of prostate cancer with distinct pathway activation profiles differ in prognosis and treatment response. [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 1502.

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.

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 Genome-wide association studies (GWAS) of multiple myeloma (MM) in Northern Europeans have identified seven novel risk loci (2p23.3, 3p22.1, 3q26.2, 6p21.33, 7p15.3, 17p11.2, 22q13.1). We performed a multiethnic meta-analysis of these regions in 1,274 MM patients and 1,486 controls of European ancestry (EA) and 1,049 MM patients and 7,080 controls of African ancestry (AA), leveraging the differential linkage-disequilibrium of these populations in order to better localize the putative functional variants. We observed directionally consistent effects for all seven index SNPs in both populations, with four significantly associated (p<0.05) with risk in EAs (3p22.1, 7p15.3, 17p11.2, 22q13.1), and two significantly associated with risk in AAs (7p15.3 and 22q13.1). In a fixed effects meta-analysis of six regions (excluding the HLA region on chromosome 6), variation in five of the regions (2p33.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) had statistically significant associations with risk (Table 1). In one region, the index variant had the strongest association [rs4487645 at 7p15.3, (OR = 1.30, p = 8.7×10−8)]. Five of the six most significantly associated variants identified in the multiethnic analyses overlapped with biologically relevant features indicating regulatory activity based on CD20+ (B lymphocyte) cells, showing evidence of potential function; those included a missense variant in (17p11.2, rs34562254, Pro251Leu) in TNFRSF13B, which encodes a lymphocyte-specific protein in the tumor necrosis factor receptor family that interacts with the NF-kb pathway. Our study shows that these regions are important in MM risk across ethnicities and further supports the use of multiple ethnic groups in genetic studies to enhance identification of risk variants. Table 1.Most significant associations for each region in the multiethnic meta-analysis.Individuals of European AncestryIndividuals of African AncestryMulitethnic Metar2 with IndexcCHRSNPRAaFreqbORP-valueFreqbORP-valueORP-valueP-het2rs732075G0.591.222.0×10−30.621.122.0×10−21.162.6×10−40.280.09/0.283rs73069394A0.191.243.0×10−30.621.181.5×10−21.201.3×10−50.550.77/0.963rs12637184G0.761.136.0×10−20.921.192.7×10−11.151.0×10−20.640.94/1.007rs4487645C0.671.237.0×10−40.891.485.5×10−51.308.7×10−80.07-d17rs34562254A0.121.452.4×10−50.131.212.2×10−31.312.5×10−60.120.33/0.9022rs139400T0.491.224.0×10−40.531.172.1×10−31.191.2×10−60.630.63/0.96aRisk allelebFrequency of the risk allele in European and African ancestry studiescr2 metrics based on 1000 Genomes Project AFR/EUR populationsdIndex SNP Citation Format: Kristin A. Rand, Chi Song, Eric Dean, Daniel Serie, Karen Curtin, Dennis Hazelett, Amie E. Hwang, Xin Sheng, Alex Stram, David J. Van Den Berg, Carol Ann Huff, Leon Bernal-Mizrachi, Michael H. Tomasson, Sikander Ailawadhi, Anneclaire De Roos, Seema Singhal, Karen Pawlish, Edward Peters, Catherine Bock, David V. Conti, Graham Colditz, Todd Zimmerman, Scott Huntsman, John Graff, African Ancestry Prostate Cancer GWAS Consortium,African Ancestry Breast Cancer GWAS Consortium, Stephen J. Chanock, Michael Lieber, Jayesh Mehta, Eric A. Klein, Nalini Janakiraman, Richard K. Severson, Angela R. Brooks-Wilson, Vincent Rajkumar, Elizabeth E. Brown, Laurence Kolonel, Susan Slager, Brian E. Henderson, Graham G. Giles, John J. Spinelli, Brian Chiu, Kenneth C. Anderson, Jeffrey Zonder, Robert Z. Orlowski, Sagar Lonial, Nicola Camp, Celine Vachon, Elad Ziv, Dan O. Stram, Christopher A. Haiman, Wendy Cozen. Multiple myeloma susceptibility loci examined in African and European ancestry populations. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4629. doi:10.1158/1538-7445.AM2015-4629