Jenkins, Robert B.

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) have identified SNPs in six genes that are associated with childhood acute lymphoblastic leukemia (ALL). A lead SNP was found to occur on chromosome 9p21.3, a region that is deleted in 30% of childhood ALLs, suggesting the presence of causal polymorphisms linked to ALL risk. We used SNP genotyping and imputation-based fine-mapping of a multiethnic ALL case–control population (Ncases = 1,464, Ncontrols = 3,279) to identify variants of large effect within 9p21.3. We identified a CDKN2A missense variant (rs3731249) with 2% allele frequency in controls that confers three-fold increased risk of ALL in children of European ancestry (OR, 2.99; P = 1.51 × 10−9) and Hispanic children (OR, 2.77; P = 3.78 × 10−4). Moreover, of 17 patients whose tumors displayed allelic imbalance at CDKN2A, 14 preferentially retained the risk allele and lost the protective allele (PBinomial = 0.006), suggesting that the risk allele provides a selective advantage during tumor growth. Notably, the CDKN2A variant was not significantly associated with melanoma, glioblastoma, or pancreatic cancer risk, implying that this polymorphism specifically confers ALL risk but not general cancer risk. Taken together, our findings demonstrate that coding polymorphisms of large effect can underlie GWAS “hits” and that inherited polymorphisms may undergo directional selection during clonal expansion of tumors. Cancer Res; 75(22); 4884–94. ©2015 AACR.

Abstract BACKGROUND/PURPOSE The Mayo Clinic has developed a large panel of patient-derived xenografts (PDX) from patients with glioblastoma multiforme (GBM). Here we report initial molecular profiling of the Mayo PDX panel and a comparison of patient and PDX molecular profile and response to therapy. METHODS & MATERIALS Clinical data was retrieved by retrospective chart review. Animal data from all PDX investigations conducted between 2004-2014 were retrieved from experimental logs and subsequently consolidated into a database for analysis. RESULTS From 1999 to 2014, 182 patient tumor samples of varying histological grades were attempted for xenograft with 73 resulting viable PDX lines. Viable xenografts were only produced from WHO grade IV tumor specimens, yielding an overall success rate of 49% for these tumors. GBM patients that produced viable xenografts compared to those that did not exhibited a trend for decreased overall survival (P = 0.18). There was no significant association between successful xenografting and whether tissue was from newly diagnosed (45/93%) or recurrent (20/40; 50%) tumors. Patient age > 45 at diagnosis was correlated with increased PDX viability in GBMs (p = 0.05). Of the viable PDX models analyzed, EGFR mutation was identified in 17 lines, TERT mutation was found in 13 lines, IDH mutation in 1 line, and MGMT hypermethylation in 25 lines. RNAseq was performed on orthotopic tumor samples from 53 PDX models. After excluding contaminating murine sequence reads, expression analysis demonstrated 32 models with a mesenchymal phenotype. Array comparative genomic hybridization was performed on 9 patient samples and derivative early, mid and late passage PDX tumors. Using unbiased hierarchical clustering, there was a high concordance between patient and xenograft models. Within the PDX panel, fractionated radiation (RT) alone and RT combined with temozolomide (TMZ) was tested in orthotopic tumors in 38 lines. The overall median survival benefit (ratio of median survival for treated vs. placebo) in PDX lines treated with RT only was 1.6 (range: 0.9-2.5) and with RT/TMZ was 2.5 (range: 1.1 - 8.9). There was a positive association between observed patient survival and the corresponding survival benefit in the PDX for subjects treated with RT/TMZ (r = 0.2; n = 17). Response to adjuvant TMZ was evaluated in 42 tumor lines, and response to bevacizumab was tested in 33 tumor lines, and correlations with clinical treatment response are being evaluated. CONCLUSIONS: The Mayo GBM PDX panel is widely used in the neuro-oncology community. The initial molecular analysis suggests a good correlation between patient and PDX at the level of genotypic characteristics and therapeutic sensitivity. Citation Format: Dioval A. Remonde, Brett L. Carlson, Mark A. Schroeder, Brock Armstrong, Sen Peng, Lisa Evers, Paul A. Decker, Jeanette Eckel Passow, Michael E. Berens, Nhan L. Tran, Robert B. Jenkins, Jann N. Sarkaria. Characterization of patient-derived xenograft (PDX) models to evaluate clinical and therapeutic responses of glioblastoma multiforme. [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 1468. doi:10.1158/1538-7445.AM2015-1468

Abstract Background: Specific germline alterations within the TERT, EGFR, CCDC26, CDKN2A/B, PHLDB1, TP53 and RTEL1 regions are associated with development of glioma. While some of these germline variants are associated with all gliomas (e.g. rs2736100 in TERT), others are associated with a specific morphologic and/or molecular subtype. For example, the RTEL1 region variants are associated with primary glioblastoma and rs55705857 in CCDC26 is associated with 1p/19q co-deleted oligodendrogliomas and with IDH mutant astrocytic gliomas. We hypothesized that germline variants in these regions will be associated with other molecular subtypes. The Cancer Genome Atlas (TCGA) and other groups have described molecular subtypes of glioma based on acquired somatic mutation patterns. Herein, we grouped glioma patients into mutation-based molecular subgroups based on three molecular alterations and determined if germline polymorphisms are associated with these mutation-based molecular subtypes. Methods: Five molecular subtypes were defined based on combinations of the following molecular alterations: TERT promoter mutation (TERTmut vs. TERTwt), IDH1/2 mutation (IDH mut vs. IDH wt) and 1p/19q co-deletion (1p19qcodel vs. 1p19q noncodel). Germline single nucleotide polymorphisms (SNPs) were evaluated by custom Illumina array analysis of blood-derived DNA and 1K genome imputation. Results: One hundred ninety-nine gliomas (24 oligodendrogliomas, 59 mixed oligoastrocytomas, 41 grade 2-3 astrocytomas and 75 glioblastomas) had both SNP data and mutation data available in order to assign them into the five molecular subgroups. The prevalence of each of the molecular subtypes was as follows: TERTmut/IDHmut/1p19qcodel (20%), TERTmut/IDHmut/1p19qnoncodel (5%), TERTmut/IDHwt/1p19qnoncodel (32%), TERTwt/IDHmut/1p19qnondel (35%) and TERTwt/IDHwt/1p19qnoncodel (8%). The TERT SNP (rs2736100) was protective for TERTmut/IDHmut/1p19qnoncodel and TERTwt/IDHmut/1p19qnoncodel gliomas. The CCDC26 SNP (rs55705857) was strongly associated with the risk of developing TERTmut/IDHmut/1p19qcodel and TERTwt/IDHmut/1p19qnoncodel gliomas. The TP53 SNP (rs7837822) was strongly associated with risk of developing TERTmut/IDHmut/1p19qnoncodel and TERTwt/IDHmut/1p19qnoncodel gliomas. Interestingly, while one RTEL1 region SNP (rs6062297) was strongly associated with glioma risk, RTEL1 SNPs rs6010620 and rs2297440 were protective for the development of TERTmut/IDHwt/1p19qnoncodel gliomas. We are currently in the process of validating these results using the TCGA glioblastoma and low grade glioma data. Conclusions: Glioma patients can be meaningfully classified according to their acquired mutation subtype. Importantly, our results suggest that there are significant associations between germline polymorphisms and mutation-based glioma molecular subtypes. Citation Format: Jeanette E. Eckel-Passow, Thomas M. Kollmeyer, Gobinda Sarkar, Anisha Chada, Paul A. Decker, Matthew L. Kosel, Alissa A. Caron, Hugues Sicotte, Kannabiran Nandakumar, Naresh Prodduturi, Brian P. O'Neill, Daniel H. Lachance, Robert B. Jenkins. The association of glioma germline risk SNPs with mutation-based molecular subgroups. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4714. doi:10.1158/1538-7445.AM2014-4714

Abstract Background ETS gene fusions and PTEN loss are the most common genomic alteration events in prostate cancer that stratify patients into molecularly distinct subtypes. Recently, a commercially available genomic classifier (GC, DecipherTM) has been validated to predict metastasis in patients with high-risk prostate cancer. In this study we evaluated the robustness of the GC model in the light of prostate cancer molecular heterogeneity. Methods: Analysis of PTEN expression loss, ERG overexpression and GC scores were performed on a previously reported genome-wide microarray dataset (Karnes et al., 2013). Microarray probesets mapping to exons of PTEN were benchmarked to identify a representative exon whose loss of expression was highly correlated to FISH analysis for PTEN deletion (PTEN-loss) performed on an independent dataset. ERG overexpression (ERG+) was determined similarly and the microarray probesets that best correlate with the FISH status (in independent dataset) were used to annotate the ERG status of the samples in this study. Receiver operating characteristic area under the curve (AUC), and multivariable regression analysis were used to assess GC performance for predicting metastasis in subsets of patient tumors with genomic alterations. Results Using the microarray method 42% of the tumors had ERG overexpression, 23% had PTEN-loss and 11% had both events. ERG+ and PTEN-loss were not on their own predictive of metastasis with AUCs of 0.52 (CI:0.44-0.6) and 0.47(CI 0.39-0.56), respectively. In ERG+ tumors GC had an AUC of 0.82 (p=4e-7) and high GC score ERG+ patients had a hazard ratio (HR) of 100 (p=6e-7) for metastasis. Similarly, in PTEN-loss tumors GC had an AUC of 0.83 (p=7.9e-5) and high GC score PTEN-loss patients had an HR of 62 (p=1.8e-4) for metastasis. When GC was evaluated in patient tumors with both ERG+ and PTEN-loss the AUC was 0.85 (p=2e-15) and high GC score patients had an HR of 95 (p=4e-4) for metastasis. In multivariable analysis, Decipher was the only significant risk factor with an HR of 55 (CI 12.2-249, p=1.8e-7) for metastasis after adjusting for ERG+, PTEN-loss, Gleason score, PSA, tumor stage, margins and adjuvant treatment. Conclusion The Decipher genomic classifier is a powerful prognostic marker that retains its significance for predicting metastasis in subsets of patients with tumors that harbor common genomic alterations. Patients with high GC scores and these alterations may represent an extremely high-risk subset of prostate cancer. Citation Format: Mohammed Alshalalfa, Ismael Vergara, Nicholas Erho, Elai Davicioni, Robert Jenkins, Kollmeyer Thomas. Evaluation of a genomic classifier (Decipher®) in subsets of primary tumors with common prostate cancer genomic alterations. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4720. doi:10.1158/1538-7445.AM2014-4720

Purpose To develop a genomic signature that predicts benefit from trastuzumab in human epidermal growth factor receptor 2–positive breast cancer. Patients and Methods DASL technology was used to quantify mRNA in samples from 1,282 patients enrolled onto the Combination Chemotherapy With or Without Trastuzumab in Treating Women With Breast Cancer (North Central Cancer Treatment Group N9831 [NCCTG-N9831]) adjuvant trastuzumab trial. Cox proportional hazard ratios (HRs), adjusted for significant clinicopathologic risk factors, were used to determine the association of each gene with relapse-free survival (RFS) for 433 patients who received chemotherapy alone (arm A) and 849 patients who received chemotherapy plus trastuzumab (arms B and C). Network and pathway analyses were used to identify key biologic processes linked to RFS. The signature was built by using a voting scheme. Results Network and functional ontology analyses suggested that increased RFS was linked to a subset of immune function genes. A voting scheme model was used to define immune gene enrichment based on the expression of any nine or more of 14 immune function genes at or above the 0.40 quantile for the population. This model was used to identify immune gene–enriched tumors in arm A and arms B and C. Immune gene enrichment was linked to increased RFS in arms B and C (HR, 0.35; 95% CI, 0.22 to 0.55; P < .001), whereas arm B and C patients who did not exhibit immune gene enrichment did not benefit from trastuzumab (HR, 0.89; 95% CI, 0.62 to 1.28; P = .53). Enriched immune function gene expression as defined by our predictive signature was not associated with increased RFS in arm A (HR, 0.90; 95% CI, 0.60 to 1.37; P = .64). Conclusion Increased expression of a subset of immune function genes may provide a means of predicting benefit from adjuvant trastuzumab.

Significant gaps exist in our understanding of the causes and clinical management of glioma. One of the biggest gaps is how best to manage low-grade (World Health Organization [WHO] Grade II) glioma. Low-grade glioma (LGG) is a uniformly fatal disease of young adults (mean age 41 years), with survival averaging approximately 7 years. Although LGG patients have better survival than patients with high-grade (WHO Grade III or IV) glioma, all LGGs eventually progress to high-grade glioma and death. Data from the Surveillance, Epidemiology and End Results (SEER) program of the National Cancer Institute suggest that for the majority of LGG patients, overall survival has not significantly improved over the past 3 decades, highlighting the need for intensified study of this tumor. Recently published research suggests that historically used clinical variables are not sufficient (and are likely inferior) prognostic and predictive indicators relative to information provided by recently discovered tumor markers (e.g., 1p/19q deletion and IDH1 or IDH2 mutation status), tumor expression profiles (e.g., the proneural profile) and/or constitutive genotype (e.g., rs55705857 on 8q24.21). Discovery of such tumor and constitutive variation may identify variables needed to improve randomization in clinical trials as well as identify patients more sensitive to current treatments and targets for improved treatment in the future. This article reports on survival trends for patients diagnosed with LGG within the United States from 1973 through 2011 and reviews the emerging role of tumor and constitutive genetics in refining risk stratification, defining targeted therapy, and improving survival for this group of relatively young patients.