Citations

Abstract Glioblastoma multiforme (GBM) is the most common and highly malignant primary brain tumor in adults with a median survival just over 1 year, and novel therapies are urgently needed. Deregulation of the p16 (INK4A)-CDK4/6-pRb pathway are commonly found in human GBM patients and selective inhibitors of CDK4/6 may be specifically useful to suppress proliferation associated with these alterations. PD0332991 is an orally active small molecule that specifically inhibits CDK4 and CDK6. Therefore, the efficacy of PD0332991 was evaluated in the Mayo panel of primary GBM xenograft lines using short-term explant cultures. We hypothesized that expression of p15 and/or p16, endogenous inhibitors of CDK4/6 activity, would suppress the response of GBM tumors to PD0332991 treatment. To test this hypothesis, 2 GBM xenograft cell lines with wild-type p16/p15 levels (GBM5 and 28) and 2 lines without detectable p16/p15 levels (GBM22 and 43) were selected for further analysis. Tumor cells were treated with graded concentrations (10 nanoM to1 microM) of PD0332991 for 5 days and subjected to CyQUANT cell proliferation assays. Consistent with our hypothesis, treatment with 1 microM PD0332991 effectively inhibited cell proliferation to 56.6±3.5% (P<0.001) and 44.3±3.4% (P<0.001) of control in GBM22 and GBM43 cells respectively, but did not affect cell proliferation in GBM5 and GBM28 cells (98.7±15.6% and 101.8±12.0% of control, respectively). In addition, 1 microM PD0332991 induced G1-phase cell cycle arrest in GBM22 (treated 79.7±0.8% vs. control 63.4±0.5% of cells in G1 phase, P<0.001) and GBM43 (treated 70.6±1.1% vs. control 48.9±4.6% of cells in G1 phase, P<0.001) but not in GBM5 and GBM28 (treated 52.3±2.7% vs. control 54.0±5.1%, treated 52.4±4.7% vs. control 54.6±2.6%, respectively). The status of p15 and p16 was confirmed by RT-PCR, which demonstrated readily detectable expression of p15 and p16 in GBM5 and GBM28, but not in GBM22 and GBM43 cells. Additional comparative genomic hybridization (CGH) data showed that CDKN2A and 2B (genes encode for p16 and p15 respectively) are homozygously deleted in GBM22 and 43, hemizygously deleted in GBM5 and normal in GBM28. We also examined the status of CDK4, CDK6, pRb and other molecules in the p16-CDK4/6-pRb pathway by Western, RT-PCR and CGH in these GBM lines and the data will be presented. We are now testing whether shRNA knockdown and/or re-expression of p15/p16 in the relevant cell lines alters their responsiveness to PD0332991. In conclusion, CDK4/6 inhibitor PD0332991 inhibits cell proliferation and induces G1 cell cycle arrest in p15/p16- null GBM tumors, but is less effective in p15/p16 expressing tumors. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):C191.

Abstract It is believed that multiple genetic variants with small individual effects contribute to the risk of alcohol dependence. Such polygenic effects are difficult to detect in genome-wide association studies that test for association of the phenotype with each single nucleotide polymorphism (SNP) individually. To overcome this challenge, gene-set analysis (GSA) methods that jointly test for the effects of pre-defined groups of genes have been proposed. Rather than testing for association between the phenotype and individual SNPs, these analyses evaluate the global evidence of association with a set of related genes enabling the identification of cellular or molecular pathways or biological processes that play a role in development of the disease. It is hoped that by aggregating the evidence of association for all available SNPs in a group of related genes, these approaches will have enhanced power to detect genetic associations with complex traits. We performed GSA using data from a genome-wide study of 1165 alcohol-dependent cases and 1379 controls from the Study of Addiction: Genetics and Environment (SAGE), for all 200 pathways listed in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results demonstrated a potential role of the ‘synthesis and degradation of ketone bodies’ pathway. Our results also support the potential involvement of the ‘neuroactive ligand–receptor interaction’ pathway, which has previously been implicated in addictive disorders. These findings demonstrate the utility of GSA in the study of complex disease, and suggest specific directions for further research into the genetic architecture of alcohol dependence.

Abstract Purpose: Glioblastoma is a devastating, incurable disease with few known prognostic factors. Here, we present the first genome-wide survival and validation study for glioblastoma. Experimental Design: Cox regressions for survival with 314,635 inherited autosomal single-nucleotide polymorphisms (SNP) among 315 San Francisco Adult Glioma Study patients for discovery and three independent validation data sets [87 Mayo Clinic, 232 glioma patients recruited from several medical centers in Southeastern United States (GliomaSE), and 115 The Cancer Genome Atlas patients] were used to identify SNPs associated with overall survival for Caucasian glioblastoma patients treated with the current standard of care, resection, radiation, and temozolomide (total n = 749). Tumor expression of the gene that contained the identified prognostic SNP was examined in three separate data sets (total n = 619). Genotype imputation was used to estimate hazard ratios (HR) for SNPs that had not been directly genotyped. Results: From the discovery and validation analyses, we identified a variant in single-stranded DNA-binding protein 2 (SSBP2) on 5q14.1 associated with overall survival in combined analyses (HR, 1.64; P = 1.3 × 10−6). Expression of SSBP2 in tumors from three independent data sets also was significantly related to patient survival (P = 5.3 × 10−4). Using genotype imputation, the SSBP2 SNP rs17296479 had the strongest statistically significant genome-wide association with poorer overall patient survival (HR, 1.79; 95% CI, 1.45-2.22; P = 1.0 × 10−7). Conclusion: The minor allele of SSBP2 SNP rs17296479 and the increased tumor expression of SSBP2 were statistically significantly associated with poorer overall survival among glioblastoma patients. With further confirmation, previously unrecognized inherited variations influencing survival may warrant inclusion in clinical trials to improve randomization. Unaccounted for genetic influence on survival could produce unwanted bias in such studies. Clin Cancer Res; 18(11); 3154–62. ©2012 AACR.

With new technologies, multiple types of genomic data are commonly collected on a single set of samples. However, standard analysis methods concentrate on a single data type at a time and ignore the relationships between genes, proteins, and biochemical reactions that give rise to complex phenotypes. In this paper, we propose a novel integrative model to incorporate multiple types of genomic data into an association analysis with a complex phenotype. The method combines path analysis and stochastic search variable selection into a Bayesian hierarchical model that simultaneously identifies both direct and indirect genomic effects on the phenotype. Results from a simulation study and application of the Bayesian model to a pharmacogenomic study of the drug gemcitabine demonstrate greater sensitivity to detect genomic effects in some simulation scenarios, when compared to the standard single data type analysis. Further research is required to extend and modify this integrative modeling framework to increase computational efficiency to best capitalize on the wealth of information available across multiple genomic data types. Genet. Epidemiol. 36:352–359, 2012. © 2012 Wiley Periodicals, Inc.

Abstract Background: Genome-wide association studies (GWAS) for epithelial ovarian cancer (EOC), the most lethal gynecologic malignancy, have identified novel susceptibility loci. GWAS for survival after EOC have had more limited success. The association of each single-nucleotide polymorphism (SNP) individually may not be well suited to detect small effects of multiple SNPs, such as those operating within the same biologic pathway. Gene set analysis (GSA) overcomes this limitation by assessing overall evidence for association of a phenotype with all measured variation in a set of genes. Methods: To determine gene sets associated with EOC overall survival, we conducted GSA using data from two large GWAS (N cases = 2,813, N deaths = 1,116), with a novel Principal Component-Gamma GSA method. Analysis was completed for all cases and then separately for high-grade serous histologic subtype. Results: Analysis of the high-grade serous subjects resulted in 43 gene sets with P < 0.005 (1.7%); of these, 21 gene sets had P < 0.10 in both GWAS, including intracellular signaling pathway (P = 7.3 × 10−5) and macrolide binding (P = 6.2 × 10−4) gene sets. The top gene sets in analysis of all cases were meiotic mismatch repair (P = 6.3 × 10−4) and macrolide binding (P = 1.0 × 10−3). Of 18 gene sets with P < 0.005 (0.7%), eight had P < 0.10 in both GWAS. Conclusion: This research detected novel gene sets associated with EOC survival. Impact: Novel gene sets associated with EOC survival might lead to new insights and avenues for development of novel therapies for EOC and pharmacogenomic studies. Cancer Epidemiol Biomarkers Prev; 21(3); 529–36. ©2012 AACR.

ObjectiveTo assess nonresponse bias in a mixed‐mode general population health survey.Data SourcesSecondary analysis of linked survey sample frame and administrative data, including demographic and health‐related information.Study DesignThe survey was administered by mail with telephone follow‐up to nonrespondents after two mailings. To determine whether an additional mail contact or mode switch reduced nonresponse bias, we compared all respondents (N = 3,437) to respondents from each mailing and telephone respondents to the sample frame (N = 6,716).Principal FindingsSwitching modes did not minimize the under‐representation of younger people, nonwhites, those with congestive heart failure, high users of office‐based services, and low‐utilizers of the emergency room but did reduce the over‐representation of older adults.ConclusionsMultiple contact and mixed‐mode surveys may increase response rates, but they do not necessarily reduce nonresponse bias.

Abstract Purpose: We examined the frequency, tumor characteristics, and prognostic impact of HER2 protein expression and gene amplification in patients with curatively resected esophageal adenocarcinoma (EAC). Experimental Design: HER2 expression was analyzed by immunohistochemistry (IHC) in surgical EAC specimens (n = 713). Gene amplification was examined by FISH in a large subset (n = 344). Most tumors were T3–4 (66%) or node positive (72%); 95% were located in the esophagus or gastroesophageal junction. No patient received neoadjuvant therapy. Cox models were used. Results: Overall, 17% of EACs were HER2 positive (i.e., IHC3+ or IHC2+ with amplification), with strong agreement between HER2 amplification (HER2/CEP17 ratio ≥2) and expression (κ = 0.83). HER2 positivity was significantly associated with lower tumor grade, less invasiveness, fewer malignant nodes, and the presence of adjacent Barrett's esophagus (BE). EACs with BE had higher odds of HER2 positivity than EACs without BE, independent of pathologic features [OR = 1.8 (95% CI: 1.1–2.8), P = 0.014]. Among all cases, HER2 positivity was significantly associated with disease-specific survival (DSS) in a manner that differed by the presence or absence of BE (Pinteraction = 0.0047). In EACs with BE, HER2 positivity was significantly associated with improved DSS [HR = 0.54 (95% CI: 0.35–0.84), P = 0.0065] and overall survival (P = 0.0022) independent of pathologic features, but was not prognostic among EACs without BE. Conclusions: HER2 positivity was shown in 17% of resected EACs and associated with reduced tumor aggressiveness. EACs with BE had nearly twice the odds of being HER2 positive and, within this subgroup, HER2 positivity was independently associated with improved survival. Clin Cancer Res; 18(2); 546–54. ©2012 AACR.

AbstractGene‐set analyses have been widely used in gene expression studies, and some of the developed methods have been extended to genome wide association studies (GWAS). Yet, complications due to linkage disequilibrium (LD) among single nucleotide polymorphisms (SNPs), and variable numbers of SNPs per gene and genes per gene‐set, have plagued current approaches, often leading to ad hoc “fixes.” To overcome some of the current limitations, we developed a general approach to scan GWAS SNP data for both gene‐level and gene‐set analyses, building on score statistics for generalized linear models, and taking advantage of the directed acyclic graph structure of the gene ontology when creating gene‐sets. However, other types of gene‐set structures can be used, such as the popular Kyoto Encyclopedia of Genes and Genomes (KEGG). Our approach combines SNPs into genes, and genes into gene‐sets, but assures that positive and negative effects of genes on a trait do not cancel. To control for multiple testing of many gene‐sets, we use an efficient computational strategy that accounts for LD and provides accurate step‐down adjustedP‐values for each gene‐set. Application of our methods to two different GWAS provide guidance on the potential strengths and weaknesses of our proposed gene‐set analyses.

Purpose NCCTG (North Central Cancer Treatment Group) N9831 is the only randomized phase III trial evaluating trastuzumab added sequentially or used concurrently with chemotherapy in resected stages I to III invasive human epidermal growth factor receptor 2–positive breast cancer. Patients and Methods Patients received doxorubicin and cyclophosphamide every 3 weeks for four cycles, followed by paclitaxel weekly for 12 weeks (arm A), paclitaxel plus sequential trastuzumab weekly for 52 weeks (arm B), or paclitaxel plus concurrent trastuzumab for 12 weeks followed by trastuzumab for 40 weeks (arm C). The primary end point was disease-free survival (DFS). Results Comparison of arm A (n = 1,087) and arm B (n = 1,097), with 6-year median follow-up and 390 events, revealed 5-year DFS rates of 71.8% and 80.1%, respectively. DFS was significantly increased with trastuzumab added sequentially to paclitaxel (log-rank P < .001; arm B/arm A hazard ratio [HR], 0.69; 95% CI, 0.57 to 0.85). Comparison of arm B (n = 954) and arm C (n = 949), with 6-year median follow-up and 313 events, revealed 5-year DFS rates of 80.1% and 84.4%, respectively. There was an increase in DFS with concurrent trastuzumab and paclitaxel relative to sequential administration (arm C/arm B HR, 0.77; 99.9% CI, 0.53 to 1.11), but the P value (.02) did not cross the prespecified O'Brien-Fleming boundary (.00116) for the interim analysis. Conclusion DFS was significantly improved with 52 weeks of trastuzumab added to adjuvant chemotherapy. On the basis of a positive risk-benefit ratio, we recommend that trastuzumab be incorporated into a concurrent regimen with taxane chemotherapy as an important standard-of-care treatment alternative to a sequential regimen.

Abstract Purpose: Inherited variability in the prognosis of lung cancer patients treated with platinum-based chemotherapy has been widely investigated. However, the overall contribution of genetic variation to platinum response is not well established. To identify novel candidate single nucleotide polymorphisms (SNP)/genes, we carried out a genome-wide association study (GWAS) for cisplatin cytotoxicity by using lymphoblastoid cell lines (LCL), followed by an association study of selected SNPs from the GWAS with overall survival (OS) in lung cancer patients. Experimental Design: A GWAS for cisplatin was conducted with 283 ethnically diverse LCLs. A total of 168 top SNPs were genotyped in 222 small cell lung cancer (SCLC) and 961 non-SCLC (NSCLC) patients treated with platinum-based therapy. Association of the SNPs with OS was determined by using the Cox regression model. Selected candidate genes were functionally validated by siRNA knockdown in human lung cancer cells. Results: Among 157 successfully genotyped SNPs, 9 and 10 SNPs were top SNPs associated with OS for patients with NSCLC and SCLC, respectively, although they were not significant after adjusting for multiple testing. Fifteen genes, including 7 located within 200 kb up or downstream of the 4 top SNPs and 8 genes for which expression was correlated with 3 SNPs in LCLs were selected for siRNA screening. Knockdown of DAPK3 and METTL6, for which expression levels were correlated with the rs11169748 and rs2440915 SNPs, significantly decreased cisplatin sensitivity in lung cancer cells. Conclusions: This series of clinical and complementary laboratory-based functional studies identified several candidate genes/SNPs that might help predict treatment outcomes for platinum-based therapy of lung cancer. Clin Cancer Res; 17(17); 5801–11. ©2011 AACR.