Browsing by Author "Owzar, Kouros"

Now showing 1 - 11 of 11
  • Thumbnail Image
    ItemOpen Access
    A Novel Genetic Variant in Long Non-coding RNA Gene NEXN-AS1 is Associated with Risk of Lung Cancer.
    (Scientific reports, 2016-10-07) Yuan, Hua; Liu, Hongliang; Liu, Zhensheng; Owzar, Kouros; Han, Younghun; Su, Li; Wei, Yongyue; Hung, Rayjean J; McLaughlin, John; Brhane, Yonathan; Brennan, Paul; Bickeboeller, Heike; Rosenberger, Albert; Houlston, Richard S; Caporaso, Neil; Landi, Maria Teresa; Heinrich, Joachim; Risch, Angela; Christiani, David C; Gümüş, Zeynep H; Klein, Robert J; Amos, Christopher I; Wei, Qingyi
    Lung cancer etiology is multifactorial, and growing evidence has indicated that long non-coding RNAs (lncRNAs) are important players in lung carcinogenesis. We performed a large-scale meta-analysis of 690,564 SNPs in 15,531 autosomal lncRNAs by using datasets from six previously published genome-wide association studies (GWASs) from the Transdisciplinary Research in Cancer of the Lung (TRICL) consortium in populations of European ancestry. Previously unreported significant SNPs (P value < 1 × 10-7) were further validated in two additional independent lung cancer GWAS datasets from Harvard University and deCODE. In the final meta-analysis of all eight GWAS datasets with 17,153 cases and 239,337 controls, a novel risk SNP rs114020893 in the lncRNA NEXN-AS1 region at 1p31.1 remained statistically significant (odds ratio = 1.17; 95% confidence interval = 1.11-1.24; P = 8.31 × 10-9). In further in silico analysis, rs114020893 was predicted to change the secondary structure of the lncRNA. Our finding indicates that SNP rs114020893 of NEXN-AS1 at 1p31.1 may contribute to lung cancer susceptibility.
  • Thumbnail Image
    ItemOpen Access
    Associations between genetic variants in mRNA splicing-related genes and risk of lung cancer: a pathway-based analysis from published GWASs.
    (Scientific reports, 2017-03-17) Pan, Yongchu; Liu, Hongliang; Wang, Yanru; Kang, Xiaozheng; Liu, Zhensheng; Owzar, Kouros; Han, Younghun; Su, Li; Wei, Yongyue; Hung, Rayjean J; Brhane, Yonathan; McLaughlin, John; Brennan, Paul; Bickeböller, Heike; Rosenberger, Albert; Houlston, Richard S; Caporaso, Neil; Teresa Landi, Maria; Heinrich, Joachim; Risch, Angela; Wu, Xifeng; Ye, Yuanqing; Christiani, David C; Amos, Christopher I; Wei, Qingyi
    mRNA splicing is an important mechanism to regulate mRNA expression. Abnormal regulation of this process may lead to lung cancer. Here, we investigated the associations of 11,966 single-nucleotide polymorphisms (SNPs) in 206 mRNA splicing-related genes with lung cancer risk by using the summary data from six published genome-wide association studies (GWASs) of Transdisciplinary Research in Cancer of the Lung (TRICL) (12,160 cases and 16,838 controls) and another two lung cancer GWASs of Harvard University (984 cases and 970 controls) and deCODE (1,319 cases and 26,380 controls). We found that a total of 12 significant SNPs with false discovery rate (FDR) ≤0.05 were mapped to one novel gene PRPF6 and two previously reported genes (DHX16 and LSM2) that were also confirmed in this study. The six novel SNPs in PRPF6 were in high linkage disequilibrium and associated with PRPF6 mRNA expression in lymphoblastoid cells from 373 Europeans in the 1000 Genomes Project. Taken together, our studies shed new light on the role of mRNA splicing genes in the development of lung cancer.
  • Thumbnail Image
    ItemOpen Access
    Characterization of a castrate-resistant prostate cancer xenograft derived from a patient of West African ancestry.
    (Prostate cancer and prostatic diseases, 2021-10-13) Patierno, Brendon M; Foo, Wen-Chi; Allen, Tyler; Somarelli, Jason A; Ware, Kathryn E; Gupta, Santosh; Wise, Sandra; Wise, John P; Qin, Xiaodi; Zhang, Dadong; Xu, Lingfan; Li, Yanjing; Chen, Xufeng; Inman, Brant A; McCall, Shannon J; Huang, Jiaoti; Kittles, Rick A; Owzar, Kouros; Gregory, Simon; Armstrong, Andrew J; George, Daniel J; Patierno, Steven R; Hsu, David S; Freedman, Jennifer A

    Background

    Prostate cancer is a clinically and molecularly heterogeneous disease, with highest incidence and mortality among men of African ancestry. To date, prostate cancer patient-derived xenograft (PCPDX) models to study this disease have been difficult to establish because of limited specimen availability and poor uptake rates in immunodeficient mice. Ancestrally diverse PCPDXs are even more rare, and only six PCPDXs from self-identified African American patients from one institution were recently made available.

    Methods

    In the present study, we established a PCPDX from prostate cancer tissue from a patient of estimated 90% West African ancestry with metastatic castration resistant disease, and characterized this model's pathology, karyotype, hotspot mutations, copy number, gene fusions, gene expression, growth rate in normal and castrated mice, therapeutic response, and experimental metastasis.

    Results

    This PCPDX has a mutation in TP53 and loss of PTEN and RB1. We have documented a 100% take rate in mice after thawing the PCPDX tumor from frozen stock. The PCPDX is castrate- and docetaxel-resistant and cisplatin-sensitive, and has gene expression patterns associated with such drug responses. After tail vein injection, the PCPDX tumor cells can colonize the lungs of mice.

    Conclusion

    This PCPDX, along with others that are established and characterized, will be useful pre-clinically for studying the heterogeneity of prostate cancer biology and testing new therapeutics in models expected to be reflective of the clinical setting.
  • Thumbnail Image
    ItemOpen Access
    Genetic variants in the platelet-derived growth factor subunit B gene associated with pancreatic cancer risk.
    (International journal of cancer, 2018-04) Duan, Bensong; Hu, Jiangfeng; Liu, Hongliang; Wang, Yanru; Li, Hongyu; Liu, Shun; Xie, Jichun; Owzar, Kouros; Abbruzzese, James; Hurwitz, Herbert; Gao, Hengjun; Wei, Qingyi
    The platelet-derived growth factor (PDGF) signaling pathway plays important roles in development and progression of human cancers. In our study, we aimed to identify genetic variants of the PDGF pathway genes associated with pancreatic cancer (PC) risk in European populations using three published genome-wide association study datasets, which consisted of 9,381 cases and 7,719 controls. The expression quantitative trait loci (eQTL) analysis was also performed using data from the 1000 Genomes, TCGA and GTEx projects. As a result, we identified two potential susceptibility loci (rs5757573 and rs6001516) of PDGFB associated with PC risk [odds ratio (OR) = 1.10, 95% confidence interval (CI) = 1.05-1.16, and p = 4.70 × 10-5 for the rs5757573 C allele and 1.21, 1.11-1.32, and 2.01 × 10-5 for the rs6001516 T allele]. Haplotype analysis revealed that the C-T haplotype carriers had a significantly increased risk of PC than those carrying the T-C haplotype (OR = 1.23, 95% CI = 1.12-1.34, p =5.00 × 10-6 ). The multivariate regression model incorporating the number of unfavorable genotypes (NUGs) with age and sex showed that carriers with 1-2 NUGs, particularly among 60-70 age group or males, had an increased risk of PC, compared to those without NUG. Furthermore, the eQTL analysis revealed that both loci were correlated with a decreased mRNA expression level of PDGFB in lymphoblastoid cell lines and pancreatic tumor tissues (p = 0.015 and 0.071, respectively). Our results suggest that genetic variants in PDGFB may play a role in susceptibility to PC. Further population and functional validations of our findings are warranted.
  • Thumbnail Image
    ItemOpen Access
    Growth hormone mitigates against lethal irradiation and enhances hematologic and immune recovery in mice and nonhuman primates.
    (PLoS One, 2010-06-16) Chen, Benny J; Deoliveira, Divino; Spasojevic, Ivan; Sempowski, Gregory D; Jiang, Chen; Owzar, Kouros; Wang, Xiaojuan; Gesty-Palmer, Diane; Cline, J Mark; Bourland, J Daniel; Dugan, Greg; Meadows, Sarah K; Daher, Pamela; Muramoto, Garrett; Chute, John P; Chao, Nelson J
    Medications that can mitigate against radiation injury are limited. In this study, we investigated the ability of recombinant human growth hormone (rhGH) to mitigate against radiation injury in mice and nonhuman primates. BALB/c mice were irradiated with 7.5 Gy and treated post-irradiation with rhGH intravenously at a once daily dose of 20 microg/dose for 35 days. rhGH protected 17 out of 28 mice (60.7%) from lethal irradiation while only 3 out of 28 mice (10.7%) survived in the saline control group. A shorter course of 5 days of rhGH post-irradiation produced similar results. Compared with the saline control group, treatment with rhGH on irradiated BALB/c mice significantly accelerated overall hematopoietic recovery. Specifically, the recovery of total white cells, CD4 and CD8 T cell subsets, B cells, NK cells and especially platelets post radiation exposure were significantly accelerated in the rhGH-treated mice. Moreover, treatment with rhGH increased the frequency of hematopoietic stem/progenitor cells as measured by flow cytometry and colony forming unit assays in bone marrow harvested at day 14 after irradiation, suggesting the effects of rhGH are at the hematopoietic stem/progenitor level. rhGH mediated the hematopoietic effects primarily through their niches. Similar data with rhGH were also observed following 2 Gy sublethal irradiation of nonhuman primates. Our data demonstrate that rhGH promotes hematopoietic engraftment and immune recovery post the exposure of ionizing radiation and mitigates against the mortality from lethal irradiation even when administered after exposure.
  • Thumbnail Image
    ItemOpen Access
    Novel genetic variants in the P38MAPK pathway gene ZAK and susceptibility to lung cancer.
    (Molecular carcinogenesis, 2018-02) Feng, Yun; Wang, Yanru; Liu, Hongliang; Liu, Zhensheng; Mills, Coleman; Owzar, Kouros; Xie, Jichun; Han, Younghun; Qian, David C; Hung Rj, Rayjean J; Brhane, Yonathan; McLaughlin, John; Brennan, Paul; Bickeböller, Heike; Rosenberger, Albert; Houlston, Richard S; Caporaso, Neil; Landi, Maria Teresa; Brüske, Irene; Risch, Angela; Ye, Yuanqing; Wu, Xifeng; Christiani, David C; Amos, Christopher I; Wei, Qingyi
    The P38MAPK pathway participates in regulating cell cycle, inflammation, development, cell death, cell differentiation, and tumorigenesis. Genetic variants of some genes in the P38MAPK pathway are reportedly associated with lung cancer risk. To substantiate this finding, we used six genome-wide association studies (GWASs) to comprehensively investigate the associations of 14 904 single nucleotide polymorphisms (SNPs) in 108 genes of this pathway with lung cancer risk. We identified six significant lung cancer risk-associated SNPs in two genes (CSNK2B and ZAK) after correction for multiple comparisons by a false discovery rate (FDR) <0.20. After removal of three CSNK2B SNPs that are located in the same locus previously reported by GWAS, we performed the LD analysis and found that rs3769201 and rs7604288 were in high LD. We then chose two independent representative SNPs of rs3769201 and rs722864 in ZAK for further analysis. We also expanded the analysis by including these two SNPs from additional GWAS datasets of Harvard University (984 cases and 970 controls) and deCODE (1319 cases and 26 380 controls). The overall effects of these two SNPs were assessed using all eight GWAS datasets (OR = 0.92, 95%CI = 0.89-0.95, and P = 1.03 × 10-5 for rs3769201; OR = 0.91, 95%CI = 0.88-0.95, and P = 2.03 × 10-6 for rs722864). Finally, we performed an expression quantitative trait loci (eQTL) analysis and found that these two SNPs were significantly associated with ZAK mRNA expression levels in lymphoblastoid cell lines. In conclusion, the ZAK rs3769201 and rs722864 may be functional susceptibility loci for lung cancer risk.
  • Thumbnail Image
    ItemOpen Access
    permGPU: Using graphics processing units in RNA microarray association studies.
    (BMC Bioinformatics, 2010-06-16) Shterev, Ivo D; Jung, Sin-Ho; George, Stephen L; Owzar, Kouros
    BACKGROUND: Many analyses of microarray association studies involve permutation, bootstrap resampling and cross-validation, that are ideally formulated as embarrassingly parallel computing problems. Given that these analyses are computationally intensive, scalable approaches that can take advantage of multi-core processor systems need to be developed. RESULTS: We have developed a CUDA based implementation, permGPU, that employs graphics processing units in microarray association studies. We illustrate the performance and applicability of permGPU within the context of permutation resampling for a number of test statistics. An extensive simulation study demonstrates a dramatic increase in performance when using permGPU on an NVIDIA GTX 280 card compared to an optimized C/C++ solution running on a conventional Linux server. CONCLUSIONS: permGPU is available as an open-source stand-alone application and as an extension package for the R statistical environment. It provides a dramatic increase in performance for permutation resampling analysis in the context of microarray association studies. The current version offers six test statistics for carrying out permutation resampling analyses for binary, quantitative and censored time-to-event traits.
  • Thumbnail Image
    ItemOpen Access
    Robust test method for time-course microarray experiments.
    (BMC Bioinformatics, 2010-07-22) Sohn, Insuk; Owzar, Kouros; George, Stephen L; Kim, Sujong; Jung, Sin-Ho
    BACKGROUND: In a time-course microarray experiment, the expression level for each gene is observed across a number of time-points in order to characterize the temporal trajectories of the gene-expression profiles. For many of these experiments, the scientific aim is the identification of genes for which the trajectories depend on an experimental or phenotypic factor. There is an extensive recent body of literature on statistical methodology for addressing this analytical problem. Most of the existing methods are based on estimating the time-course trajectories using parametric or non-parametric mean regression methods. The sensitivity of these regression methods to outliers, an issue that is well documented in the statistical literature, should be of concern when analyzing microarray data. RESULTS: In this paper, we propose a robust testing method for identifying genes whose expression time profiles depend on a factor. Furthermore, we propose a multiple testing procedure to adjust for multiplicity. CONCLUSIONS: Through an extensive simulation study, we will illustrate the performance of our method. Finally, we will report the results from applying our method to a case study and discussing potential extensions.
  • Thumbnail Image
    ItemOpen Access
    Sample size calculation for studies with grouped survival data.
    (Statistics in medicine, 2018-06-10) Li, Zhiguo; Wang, Xiaofei; Wu, Yuan; Owzar, Kouros
    Grouped survival data arise often in studies where the disease status is assessed at regular visits to clinic. The time to the event of interest can only be determined to be between two adjacent visits or is right censored at one visit. In data analysis, replacing the survival time with the endpoint or midpoint of the grouping interval leads to biased estimators of the effect size in group comparisons. Prentice and Gloeckler developed a maximum likelihood estimator for the proportional hazards model with grouped survival data and the method has been widely applied. Previous work on sample size calculation for designing studies with grouped data is based on either the exponential distribution assumption or the approximation of variance under the alternative with variance under the null. Motivated by studies in HIV trials, cancer trials and in vitro experiments to study drug toxicity, we develop a sample size formula for studies with grouped survival endpoints that use the method of Prentice and Gloeckler for comparing two arms under the proportional hazards assumption. We do not impose any distributional assumptions, nor do we use any approximation of variance of the test statistic. The sample size formula only requires estimates of the hazard ratio and survival probabilities of the event time of interest and the censoring time at the endpoints of the grouping intervals for one of the two arms. The formula is shown to perform well in a simulation study and its application is illustrated in the three motivating examples.
  • Thumbnail Image
    ItemOpen Access
    Single-cell landscape analysis unravels molecular programming of the human B cell compartment in chronic GVHD.
    (JCI insight, 2023-06) Poe, Jonathan C; Fang, Jiyuan; Zhang, Dadong; Lee, Marissa R; DiCioccio, Rachel A; Su, Hsuan; Qin, Xiaodi; Zhang, Jennifer Y; Visentin, Jonathan; Bracken, Sonali J; Ho, Vincent T; Wang, Kathy S; Rose, Jeremy J; Pavletic, Steven Z; Hakim, Frances T; Jia, Wei; Suthers, Amy N; Curry-Chisolm, Itaevia M; Horwitz, Mitchell E; Rizzieri, David A; McManigle, William C; Chao, Nelson J; Cardones, Adela R; Xie, Jichun; Owzar, Kouros; Sarantopoulos, Stefanie
    Alloreactivity can drive autoimmune syndromes. After allogeneic hematopoietic stem cell transplantation (allo-HCT), chronic graft-versus-host disease (cGVHD), a B cell-associated autoimmune-like syndrome, commonly occurs. Because donor-derived B cells continually develop under selective pressure from host alloantigens, aberrant B cell receptor (BCR) activation and IgG production can emerge and contribute to cGVHD pathobiology. To better understand molecular programing of B cells in allo-HCT, we performed scRNA-Seq analysis on high numbers of purified B cells from patients. An unsupervised analysis revealed 10 clusters, distinguishable by signature genes for maturation, activation, and memory. Within the memory B cell compartment, we found striking transcriptional differences in allo-HCT patients compared with healthy or infected individuals, including potentially pathogenic atypical B cells (ABCs) that were expanded in active cGVHD. To identify intrinsic alterations in potentially pathological B cells, we interrogated all clusters for differentially expressed genes (DEGs) in active cGVHD versus patients who never had signs of immune tolerance loss (no cGVHD). Active cGVHD DEGs occurred in both naive and BCR-activated B cell clusters. Remarkably, some DEGs occurred across most clusters, suggesting common molecular programs that may promote B cell plasticity. Our study of human allo-HCT and cGVHD provides understanding of altered B cell memory during chronic alloantigen stimulation.
  • Thumbnail Image
    ItemOpen Access
    SNPpy--database management for SNP data from genome wide association studies.
    (PLoS One, 2011) Mitha, Faheem; Herodotou, Herodotos; Borisov, Nedyalko; Jiang, Chen; Yoder, Josh; Owzar, Kouros
    BACKGROUND: We describe SNPpy, a hybrid script database system using the Python SQLAlchemy library coupled with the PostgreSQL database to manage genotype data from Genome-Wide Association Studies (GWAS). This system makes it possible to merge study data with HapMap data and merge across studies for meta-analyses, including data filtering based on the values of phenotype and Single-Nucleotide Polymorphism (SNP) data. SNPpy and its dependencies are open source software. RESULTS: The current version of SNPpy offers utility functions to import genotype and annotation data from two commercial platforms. We use these to import data from two GWAS studies and the HapMap Project. We then export these individual datasets to standard data format files that can be imported into statistical software for downstream analyses. CONCLUSIONS: By leveraging the power of relational databases, SNPpy offers integrated management and manipulation of genotype and phenotype data from GWAS studies. The analysis of these studies requires merging across GWAS datasets as well as patient and marker selection. To this end, SNPpy enables the user to filter the data and output the results as standardized GWAS file formats. It does low level and flexible data validation, including validation of patient data. SNPpy is a practical and extensible solution for investigators who seek to deploy central management of their GWAS data.