Sevtap Savas

Publications (24)87.62 Total impact

• Article: Vascular endothelial growth factor pathway polymorphisms as prognostic and pharmacogenetic factors in cancer: a systematic review and meta-analysis.

  Lawson Eng, Abul Kalam Azad, Steven Habbous, Vincent Pang, Wei Xu, Anke H Maitland-van der Zee, Sevtap Savas, Helen J Mackay, Eitan Amir, Geoffrey Liu
  [show abstract] [hide abstract]
  ABSTRACT: Angiogenesis is an important host process that interacts with cancer cells to promote growth, invasion, and metastasis. Numerous therapeutic agents targeting the VEGF pathway have been developed. Host variability in VEGF pathway can influence angiogenesis-dependent signaling, altering sensitivity to antiangiogenic drugs and prognosis. A systematic review and meta-analysis was conducted (May 1990-July 2011). Eligible studies involved cancer patients and compared polymorphisms in the VEGF pathway [VEGF and molecules directly interacting with VEGF: KDR, FLT1, FGF, FGF2, FGFR, NRP1, endostatin (encoded by COL18A1)], and reported one of the following outcomes: overall survival, progression-free survival, time to recurrence, disease-free survival, response rate, or drug toxicity. We identified 48 cancer studies assessing prognosis and 12 cancer studies exploring pharmacogenetics of anti-VEGF therapy across various VEGF pathway polymorphisms. There was marked inter- and intradisease site heterogeneity in the effect of polymorphisms on both outcome and response to therapy. Meta-analyses of 5 VEGF polymorphisms (+936C>T, -460T>C, +405G>C, -1154G>A, and -2578C>A) identified a significant prognostic relationship: VEGF +405G>C variants showed a highly statistically significant improvement in overall survival [HR, 0.74; 95% confidence interval, 0.60-0.91; P = 0.004]. Variants (heterozygotes and/or homozygotes) of VEGF +405G>C were significantly associated with improved survival in a meta-analysis of multiple cancer sites.
  Clinical Cancer Research 06/2012; 18(17):4526-37. · 7.74 Impact Factor
• Article: Genetic sequence variants and the development of secondary primary cancers in patients with head and neck cancers.

  Abul Kalam Azad, Isabelle Bairati, Elodie Samson, Dangxiao Cheng, Lu Cheng, Maryam Mirshams, Sevtap Savas, John Waldron, Changshu Wang, David Goldstein, Wei Xu, Francois Meyer, Geoffrey Liu
  [show abstract] [hide abstract]
  ABSTRACT: Secondary primary cancers (SPCs), a major cause of morbidity and mortality in head and neck cancers (HNCs), are commonly associated with field cancerization. We comprehensively evaluated 23 germline sequence variants (from published literature) in 17 genes from 7 biological pathways associated with the HNC survival. Because cancer prognosis correlates with disease aggressiveness, the factors that determine aggressive disease may influence field cancerization process to favor SPC development. We thus hypothesized that the same sequence variants associated with HNC survival can also be associated with SPC. Germline DNA from 531 stage I-II radiation-treated HNC patients (originally recruited for an alpha-tocopherol/beta-carotene placebo-controlled secondary prevention clinical trial) were genotyped, and analyzed using Cox proportional hazards models, stratified by treatment arm, adjusting for clinical prognostic factors. The majority of SPCs were of lung and HNCs. Median follow-up time was 5 years. SPCs were diagnosed in 21% of patients. The 5-year SPC-free survival was 79%. All but 1 evaluated sequence variant were not associated with SPC. There was a strong association of the DNA (cytosine-5-)-methyltransferase 3 beta (DNMT3B) sequence variant, DNMT3B:C149T (rs2424913) with SPC: the adjusted hazard ratio (aHR) for TT versus CC was 2.23 (1.32-3.78; P = .003), whereas each variant T allele was associated with an aHR of 1.49 (1.15-1.95; P = .003). A functional sequence variant in DNMT3B is associated with the development of SPCs in HNC early stage patients treated with radiation. Aberrant DNA methylation may be an important modulator of SPC development in at-risk individuals with HNCs.
  Cancer 03/2012; 118(6):1554-65. · 4.77 Impact Factor
• Article: A curated database of genetic markers from the angiogenesis/VEGF pathway and their relation to clinical outcome in human cancers.

  Sevtap Savas
  [show abstract] [hide abstract]
  ABSTRACT: Angiogenesis causes local growth, aggressiveness and metastasis in solid tumors, and thus, is almost always associated with poor prognosis and survival in cancer patients. Because of this clinical importance, several chemotherapeutic agents targeting angiogenesis have also been developed. Genes and genetic variations in angiogenesis/VEGF pathway thus may be correlated with clinical outcome in cancer patients. Here, we describe a manually curated public database, dbANGIO, which posts the results of studies testing the possible correlation of genetic variations (polymorphisms and mutations) from the angiogenesis/VEGF pathway with demographic features, clinicopathological features, treatment response and toxicity, and prognosis and survival-related endpoints in human cancers. The scientific findings are retrieved from PUBMED and posted in the dbANGIO website in a summarized form. As of September 2011, dbANGIO includes 362 entries from 83 research articles encompassing 154 unique genetic variations from 39 genes investigated in several solid and hematological cancers. By curating the literature findings and making them freely available to researchers, dbANGIO will expedite the research on genetic factors from the angiogenesis pathway and will assist in their utility in clinical management of cancer patients. dbANGIO is freely available for non-profit institutions at http://www.med.mun.ca/angio.
  Acta oncologica (Stockholm, Sweden) 12/2011; 51(2):243-6. · 2.27 Impact Factor
• Article: Validation of genetic sequence variants as prognostic factors in early-stage head and neck squamous cell cancer survival.

  Abul Kalam Azad, Isabelle Bairati, Elodie Samson, Dangxiao Cheng, Maryam Mirshams, Xin Qiu, Sevtap Savas, John Waldron, Changshu Wang, David Goldstein, Wei Xu, Francois Meyer, Geoffrey Liu
  [show abstract] [hide abstract]
  ABSTRACT: From the published literature, we identified 23 germ line sequence variants in 17 genes from hypothesis-generating studies that were associated with prognosis of head and neck cancer, including sequence variants of DNA repair (ERCC1, ERCC4, ERCC5, MSH2, XPA, ERCC2, XRCC1, XRCC3), DNA methylation (DNMT3B), cell cycle and proliferation (CCND1, TP53), xenobiotic metabolism (GSTM1, GSTT1, CYP2D6), metastatic -potential (MMP3), immunologic (CTLA4), and growth factor pathways (FGFR4). The purpose of this study was to validate the role of these 23 sequence variants for overall (OS) and disease-free survival (DFS) in a large, comprehensive, well-annotated data set of patients with head and neck cancer. We genotyped these sequence variants in 531 patients with stage I and II radiation-treated head and neck cancer (originally recruited for an alpha-tocopherol/beta-carotene placebo-controlled secondary prevention study), and analyzed using Cox proportional hazards models, stratified by treatment arm, adjusting for clinical prognostic factors. Two OS associations were statistically significant for each variant allele when compared with the wild-type: CTLA4: A49G [rs231775; adjusted HR (aHR), 1.32 (1.1-1.6); P = 0.01] and XRCC1: Arg339Gln [rs25487; aHR, 1.28 (1.05-1.57); P = 0.02]. Both of these sequence variants had significant results in the opposite direction as prior published literature. Two DFS associations were of borderline significance in the same direction as prior literature: ERCC2: Lys751Gln [rs13181; aHR, 0.80 (0.6-1.0); P = 0.05] and TP53: Arg72Pro [rs1042522; aHR, 1.28 (1.0-1.6); P = 0.03], comparing number of variant alleles with reference of zero variants. None of the prognostic sequence variants previously published was validated for OS in our patients with early-stage radiation-treated head and neck cancer, though rs1381and rs1042522 had borderline significant association with DFS.
  Clinical Cancer Research 11/2011; 18(1):196-206. · 7.74 Impact Factor
• Source

  Available from: Hilmi Ozcelik

  Article: Bioinformatic analyses identifies novel protein-coding pharmacogenomic markers associated with paclitaxel sensitivity in NCI60 cancer cell lines.

  Lawson Eng, Irada Ibrahim-zada, Hamdi Jarjanazi, Sevtap Savas, Mehran Meschian, Kathleen I Pritchard, Hilmi Ozcelik
  [show abstract] [hide abstract]
  ABSTRACT: Paclitaxel is a microtubule-stabilizing drug that has been commonly used in treating cancer. Due to genetic heterogeneity within patient populations, therapeutic response rates often vary. Here we used the NCI60 panel to identify SNPs associated with paclitaxel sensitivity. Using the panel's GI50 response data available from Developmental Therapeutics Program, cell lines were categorized as either sensitive or resistant. PLINK software was used to perform a genome-wide association analysis of the cellular response to paclitaxel with the panel's SNP-genotype data on the Affymetrix 125 k SNP array. FastSNP software helped predict each SNP's potential impact on their gene product. mRNA expression differences between sensitive and resistant cell lines was examined using data from BioGPS. Using Haploview software, we investigated for haplotypes that were more strongly associated with the cellular response to paclitaxel. Ingenuity Pathway Analysis software helped us understand how our identified genes may alter the cellular response to paclitaxel. 43 SNPs were found significantly associated (FDR<0.005) with paclitaxel response, with 10 belonging to protein-coding genes (CFTR, ROBO1, PTPRD, BTBD12, DCT, SNTG1, SGCD, LPHN2, GRIK1, ZNF607). SNPs in GRIK1, DCT, SGCD and CFTR were predicted to be intronic enhancers, altering gene expression, while SNPs in ZNF607 and BTBD12 cause conservative missense mutations. mRNA expression analysis supported these findings as GRIK1, DCT, SNTG1, SGCD and CFTR showed significantly (p<0.05) increased expression among sensitive cell lines. Haplotypes found in GRIK1, SGCD, ROBO1, LPHN2, and PTPRD were more strongly associated with response than their individual SNPs. Our study has taken advantage of available genotypic data and its integration with drug response data obtained from the NCI60 panel. We identified 10 SNPs located within protein-coding genes that were not previously shown to be associated with paclitaxel response. As only five genes showed differential mRNA expression, the remainder would not have been detected solely based on expression data. The identified haplotypes highlight the role of utilizing SNP combinations within genomic loci of interest to improve the risk determination associated with drug response. These genetic variants represent promising biomarkers for predicting paclitaxel response and may play a significant role in the cellular response to paclitaxel.
  BMC Medical Genomics 02/2011; 4:18. · 3.69 Impact Factor
• Source

  Available from: Hilmi Ozcelik

  Article: NCI60 cancer cell line panel data and RNAi analysis help identify EAF2 as a modulator of simvastatin and lovastatin response in HCT-116 cells.

  Sevtap Savas, David O Azorsa, Hamdi Jarjanazi, Irada Ibrahim-Zada, Irma M Gonzales, Shilpi Arora, Meredith C Henderson, Yun Hee Choi, Laurent Briollais, Hilmi Ozcelik, Sukru Tuzmen
  [show abstract] [hide abstract]
  ABSTRACT: Simvastatin and lovastatin are statins traditionally used for lowering serum cholesterol levels. However, there exists evidence indicating their potential chemotherapeutic characteristics in cancer. In this study, we used bioinformatic analysis of publicly available data in order to systematically identify the genes involved in resistance to cytotoxic effects of these two drugs in the NCI60 cell line panel. We used the pharmacological data available for all the NCI60 cell lines to classify simvastatin or lovastatin resistant and sensitive cell lines, respectively. Next, we performed whole-genome single marker case-control association tests for the lovastatin and simvastatin resistant and sensitive cells using their publicly available Affymetrix 125K SNP genomic data. The results were then evaluated using RNAi methodology. After correction of the p-values for multiple testing using False Discovery Rate, our results identified three genes (NRP1, COL13A1, MRPS31) and six genes (EAF2, ANK2, AKAP7, STEAP2, LPIN2, PARVB) associated with resistance to simvastatin and lovastatin, respectively. Functional validation using RNAi confirmed that silencing of EAF2 expression modulated the response of HCT-116 colon cancer cells to both statins. In summary, we have successfully utilized the publicly available data on the NCI60 cell lines to perform whole-genome association studies for simvastatin and lovastatin. Our results indicated genes involved in the cellular response to these statins and siRNA studies confirmed the role of the EAF2 in response to these drugs in HCT-116 colon cancer cells.
  PLoS ONE 01/2011; 6(4):e18306. · 4.09 Impact Factor
• Source

  Available from: harvard.edu

  Article: Useful genetic variation databases for oncologists investigating the genetic basis of variable treatment response and survival in cancer.

  Sevtap Savas
  [show abstract] [hide abstract]
  ABSTRACT: Identification of the genetic basis of variable treatment response, prognosis and survival in cancer patients (i.e. personalized medicine) is an important aim in current medicine. Millions of genetic variations exist in the human genome, some of which are already found to be directly involved in variable treatment response and survival among cancer patients. GENETIC VARIATION DATABASES: Special databases curate, compile, organize and post information related to these genetic variations for the scientific community in a user friendly and free-to-access manner via the World Wide Web. FUTURE DIRECTIONS AND CONCLUSION: Clinicians have a critical role in genetic predictive and prognostic studies. In this review, main public-domain databases on genetic variations, including the two comprehensive genetic variation databases (dbSNP and HapMap), a pharmacogenomics database (PharmGKB), two resequencing-based genetic variation databases (SeattleSNPs and EGP), a population-based genetic variation database (JSNPs), and a copy-number variant database (DGV), and their utility in cancer research are discussed. Utilization of these databases can assist clinicians in their studies related to treatment response and prognosis in cancer patients.
  Acta oncologica (Stockholm, Sweden) 11/2010; 49(8):1217-26. · 2.27 Impact Factor
• Article: dbCPCO: a database of genetic markers tested for their predictive and prognostic value in colorectal cancer.

  Sevtap Savas, H Banfield Younghusband
  [show abstract] [hide abstract]
  ABSTRACT: Colorectal cancer is the third most common cancer with a 5-year survival rate of 30-65%. A portion of the interpatient variability in its clinical outcome is attributed to inherited and somatic genetic factors. Although numerous research articles have investigated these factors in colorectal cancer, there has not been a central resource, such as a public database, that compiles these findings. Here we describe the dbCPCO, a database of genetic variations tested for association with colorectal cancer prognosis and clinical outcome. dbCPCO curates the results of research articles on colorectal cancer that investigate the possible correlation of genetic factors with various patient and tumor characteristics. Literature reports are retrieved from PubMed. The data that meet the inclusion criteria are compiled in a relational database and posted in a dedicated Website. The genetic factors include inherited genetic polymorphisms, and somatic and germline mutations in both nuclear and mitochondrial DNA. As of March 2010, the dbCPCO Website posts 778 scientific findings on 456 polymorphisms, somatic and germline mutations from 189 genes, and genetic loci tested for correlation with clinicopathological features and/or clinical outcome in colorectal cancer. The dbCPCO is periodically updated and freely available for the scientific and medical community at http://www.med.mun.ca/cpco.
  Human Mutation 08/2010; 31(8):901-7. · 5.69 Impact Factor
• Source

  Available from: Hilmi Ozcelik

  Article: A whole-genome SNP association study of NCI60 cell line panel indicates a role of Ca2+ signaling in selenium resistance.

  Sevtap Savas, Laurent Briollais, Irada Ibrahim-zada, Hamdi Jarjanazi, Yun Hee Choi, Mireia Musquera, Neil Fleshner, Vasundara Venkateswaran, Hilmi Ozcelik
  [show abstract] [hide abstract]
  ABSTRACT: Epidemiological studies have suggested an association between selenium intake and protection from a variety of cancer. Considering this clinical importance of selenium, we aimed to identify the genes associated with resistance to selenium treatment. We have applied a previous methodology developed by our group, which is based on the genetic and pharmacological data publicly available for the NCI60 cancer cell line panel. In short, we have categorized the NCI60 cell lines as selenium resistant and sensitive based on their growth inhibition (GI50) data. Then, we have utilized the Affymetrix 125K SNP chip data available and carried out a genome-wide case-control association study for the selenium sensitive and resistant NCI60 cell lines. Our results showed statistically significant association of four SNPs in 5q33-34, 10q11.2, 10q22.3 and 14q13.1 with selenium resistance. These SNPs were located in introns of the genes encoding for a kinase-scaffolding protein (AKAP6), a membrane protein (SGCD), a channel protein (KCNMA1), and a protein kinase (PRKG1). The knock-down of KCNMA1 by siRNA showed increased sensitivity to selenium in both LNCaP and PC3 cell lines. Furthermore, SNP-SNP interaction (epistasis) analysis indicated the interactions of the SNPs in AKAP6 with SGCD as well as SNPs in AKAP6 with KCNMA1 with each other, assuming additive genetic model. These genes were also all involved in the Ca(2+) signaling, which has a direct role in induction of apoptosis and induction of apoptosis in tumor cells is consistent with the chemopreventive action of selenium. Once our findings are further validated, this knowledge can be translated into clinics where individuals who can benefit from the chemopreventive characteristics of the selenium supplementation will be easily identified using a simple DNA analysis.
  PLoS ONE 01/2010; 5(9):e12601. · 4.09 Impact Factor
• Article: Studying genetic variations in cancer prognosis (and risk): a primer for clinicians.

  Sevtap Savas, Geoffrey Liu
  [show abstract] [hide abstract]
  ABSTRACT: Rare, high-penetrance genetic variations account for a small portion of genetic cancer syndromes. In contrast, most cancers develop from a combination of minor genetic influences and environmental factors. There are numerous publications on cancer susceptibility. In contrast, genetic studies in treatment response and outcome analyses are a rapidly emerging field. Approaches used in disease susceptibility can be adapted for genetic outcome studies. In this review, we summarize the current knowledge on how candidate genes and genetic variations are selected to evaluate gene-outcome, gene-prognosis, and gene-treatment response relationships as applicable to the practicing oncologist.
  The Oncologist 08/2009; 14(7):657-66. · 3.91 Impact Factor
• Article: Genetic variations as cancer prognostic markers: review and update.

  Sevtap Savas, Geoffrey Liu
  [show abstract] [hide abstract]
  ABSTRACT: Cancer molecular epidemiology traditionally studies the relationship between genetic variations and cancer risk. However, recent studies have also focused on disease outcomes. The application and design of disease outcome studies have been an extension of disease risk assessment. Yet there are a number of unique considerations important in outcome assessments. We review how genetic approaches used for disease susceptibility, such as candidate gene and genome-wide association study (GWAS) approaches, can be adapted carefully to systematically identify cancer prognostic and predictive alleles. We discuss the interrelatedness among the disease susceptibility, treatment response, and prognosis at the genetic level and focus on how the emerging technologies and approaches can uniquely benefit the genetic prognosis studies.
  Human Mutation 07/2009; 30(10):1369-77. · 5.69 Impact Factor
• Article: A comprehensive catalogue of functional genetic variations in the EGFR pathway: protein-protein interaction analysis reveals novel genes and polymorphisms important for cancer research.

  Sevtap Savas, Joseph Geraci, Igor Jurisica, Geoffrey Liu
  [show abstract] [hide abstract]
  ABSTRACT: The EGFR pathway is a critical signaling pathway deregulated in many solid tumors. In addition to the initiation and progression of cancer, the EGFR pathway is also implicated in variable treatment responses and prognoses. Genetic variation in the form of Single Nucleotide Polymorphisms (SNPs) can affect the function/expression of the EGFR pathway genes. Here, we applied a systematic and comprehensive approach utilizing diverse public databases and in silico analysis tools to select putative functional genetic variations from 244 genes involved in the EGFR pathway. Our data comprises 649 SNPs. Three hundred sixty SNPs are predicted to have biological consequences (functional SNPs). These SNPs can be directly used in further studies to test their association with risk, treatment response and prognosis in cancer. To systematically cover the EGFR pathway, we also performed a network-based analysis to further select putative functional SNPs from the genes whose protein products physically interact with the EGFR pathway proteins. We utilized protein-protein interaction information and focused on 14 proteins that have a high degree of connectivity (interacting with > or = 10 proteins) with the EGFR pathway genes identified to have functional SNPs (f-EGFR genes). Two of these proteins (FYN and LCK) had interactions with 17 of the f-EGFR genes, yet both lacked any putative functional SNP. However, our analysis indicated the presence of potentially functional SNPs in 9 other highly interactive proteins. The genes and their SNPs identified in the network-based analysis represent potential candidates for gene-gene and SNP-SNP interaction studies in cancer research.
  International Journal of Cancer 04/2009; 125(6):1257-65. · 5.44 Impact Factor
• Article: Discovery of genetic profiles impacting response to chemotherapy: application to gemcitabine.

  Hamdi Jarjanazi, Jeffrey Kiefer, Sevtap Savas, Laurent Briollais, Sukru Tuzmen, Noel Pabalan, Irada Ibrahim-Zada, Spyro Mousses, Hilmi Ozcelik
  [show abstract] [hide abstract]
  ABSTRACT: Chemotherapy is a major treatment modality for individuals affected by cancer. Currently, a number of genome-based technologies are being adopted to identify genes associated with drug response; however, large-scale genetic association applications are still limited. Here we describe a novel strategy based on the genetic and drug response data of the NCI60 cell lines to discover potential candidate genetic variants associated with variable response to chemotherapy. As an example we have applied this strategy to discover single genetic markers and haplotypes from candidate genes previously implicated in the pharmacobiology of gemcitabine. Single-marker association analyses have implicated the association of four SNPs within the gene loci of CDC5L, EPC2, POLS, and PARP1. We have also investigated the combined effect of SNPs using haplotype-based analysis. Accordingly, we have shown modest association of haplotypes in six genes, whereas the most significant associations included a haplotype of the POLS gene. The hypothesis-generating tool presented in this study can be applied to drugs profiled in the NCI60 cell line screen and provides an effective means for the identification of genes associated with drug response. The results obtained using this novel methodology can be used to better design the clinical trials for effective study of the chemotherapeutic agents and thus provide a basis for individualized chemotherapy.
  Human Mutation 05/2008; 29(4):461-7. · 5.69 Impact Factor
• Article: Biological implications of SNPs in signal peptide domains of human proteins.

  Hamdi Jarjanazi, Sevtap Savas, Noel Pabalan, James W Dennis, Hilmi Ozcelik
  [show abstract] [hide abstract]
  ABSTRACT: Proteins destined for secretion or membrane compartments possess signal peptides for insertion into the membrane. The signal peptide is therefore critical for localization and function of cell surface receptors and ligands that mediate cell-cell communication. About 4% of all human proteins listed in UniProt database have signal peptide domains in their N terminals. A comprehensive literature survey was performed to retrieve functional and disease associated genetic variants in the signal peptide domains of human proteins. In 21 human proteins we have identified 26 disease associated mutations within their signal peptide domains, 14 mutations of which have been experimentally shown to impair the signal peptide function and thus influence protein transportation. We took advantage of SignalP 3.0 predictions to characterize the signal peptide prediction score differences between the mutant and the wild-type alleles of each mutation, as well as 189 previously uncharacterized single nucleotide polymorphisms (SNPs) found to be located in the signal peptide domains of 165 human proteins. Comparisons of signal peptide prediction outcomes of mutations and SNPs, have implicated SNPs potentially impacting the signal peptide function, and thus the cellular localization of the human proteins. The majority of the top candidate proteins represented membrane and secreted proteins that are associated with molecular transport, cell signaling and cell to cell interaction processes of the cell. This is the first study that systematically characterizes genetic variation occurring in the signal peptides of all human proteins. This study represents a useful strategy for prioritization of SNPs occurring within the signal peptide domains of human proteins. Functional evaluation of candidates identified herein may reveal effects on major cellular processes including immune cell function, cell recognition and adhesion, and signal transduction.
  Proteins Structure Function and Bioinformatics 03/2008; 70(2):394-403. · 3.39 Impact Factor
• Source

  Available from: Ian Taylor

  Article: Functional nonsynonymous single nucleotide polymorphisms from the TGF-beta protein interaction network.

  Sevtap Savas, Ian W Taylor, Jeff L Wrana, Hilmi Ozcelik
  [show abstract] [hide abstract]
  ABSTRACT: Protein complexes mediated by protein-protein interactions are essential for many cellular functions. Transforming growth factor (TGF)-beta signaling involves a cascade of protein-protein interactions and malfunctioning of this pathway has been implicated in human diseases. Using an in silico approach, we analyzed the naturally occurring human genetic variations from the proteins involved in the TGF-beta signaling (10 TGF-beta proteins and 242 other proteins interacting with them) to identify the ones that have potential biological consequences. All proteins were searched in the dbSNP database for the presence of nonsynonymous single nucleotide polymorphisms (nsSNPs). A total of 118 validated nsSNPs from 63 proteins were retrieved and analyzed in terms of 1) evolutionary conservation status, 2) being located in a functional protein domain or motif, and 3) altering putative protein motif or phosphorylation sites. Our results indicated the presence of 31 nsSNPs that occurred at evolutionarily conserved residues, 37 nsSNPs were located in protein domains, motifs, or repeats, and 46 nsSNPs were predicted to either create or abolish putative protein motifs or phosphorylation sites. We undertook this study to analyze the human genetic variations that can affect the protein function and the TGF-beta signaling. The nsSNPs reported in here can be characterized by experimental approaches to elucidate their exact biological roles and whether they are related to human disease.
  Physiological Genomics 05/2007; 29(2):109-17. · 2.73 Impact Factor
• Source

  Available from: PubMed Central

  Article: Polymorphisms cMyc-N11S and p27-V109G and breast cancer risk and prognosis.

  Jane C Figueiredo, Julia A Knight, Stewart Cho, Sevtap Savas, U Venus Onay, Laurent Briollais, Pamela J Goodwin, John R McLaughlin, Irene L Andrulis, Hilmi Ozcelik
  [show abstract] [hide abstract]
  ABSTRACT: cMyc and p27 are key genes implicated in carcinogenesis. Whether polymorphisms in these genes affect breast cancer risk or prognosis is still unclear. In this study, we focus on a rare non-synonymous polymorphism in cMyc (N11S) and a common polymorphism in p27 (V109G) and determine their role in risk and prognosis using data collected from the Ontario Breast Cancer Family Registry. Risk factor data was collected at baseline on a large group of women (cases = 1,115 and population-based controls = 710) and clinical data (including treatment and follow-up) were collected prospectively by periodic review of medical records for a subset of cases (N = 967) for nearly a decade. A centralized pathology review was conducted. Unconditional logistic regression was used to determine the association of polymorphisms with breast cancer risk and the Cox proportional hazards model was used to determine their association with survival. Our results suggest that while cMyc-N11S can be considered a putatively functional polymorphism located in the N-terminal domain, it is not associated with risk, tumor characteristics or survival. The p27-G109 allele was associated with a modest protective effect in adjusted analyses and higher T stage. We found no evidence to suggest that p27-V109G alone or in combination with cMyc-N11S was associated with survival. Age at onset and first-degree family history of breast or ovarian cancer did not significantly modify the association of these polymorphisms with breast cancer risk. Further work is recommended to understand the potential functional role of these specific non-synonymous amino acid changes and a larger, more comprehensive investigation of genetic variation in these genes (e.g., using a tagSNP approach) in combination with other relevant genes is needed as well as consideration for treatment effects when assessing their potential role in prognosis.
  BMC Cancer 02/2007; 7:99. · 3.01 Impact Factor
• Article: Human non-synonymous single nucleotide polymorphisms can influence ubiquitin-mediated protein degradation.

  Sevtap Savas, Mehjabeen Shariff, Ian W Taylor, Hilmi Ozcelik
  [show abstract] [hide abstract]
  ABSTRACT: Ubiquitin-mediated proteolysis plays a critical role in the degradation of proteins important in the cellular processes, such as cell cycle/division, differentiation and development, DNA repair, transcriptional regulation, and signaling. It is carried out by a complex cascade of enzymes that contain a high degree of specificity to motifs found in many proteins with rapid turnover. For example, the PEST motifs are hydrophilic stretches of amino acids that serve as signals for proteolytic degradation. In this study, we propose that amino acid altering non-synonymous single nucleotide polymorphisms (nsSNP) result in the abolishment or creation of putative PEST motifs, and thus lead to abnormal stabilization or degradation of the proteins. Using a web-based algorithm, PESTFind, we analyzed a total of 253 nsSNPs from proteins involved in cell cycle (n = 24), DNA repair (n = 128), and TGFbeta signaling pathway (n = 101). Fifteen nsSNPs were located within putative PEST sequences, and 9/15 (60%) either created or abolished these PEST motifs. PEST motifs were abolished in the presence of nsSNPs in CCND3, PMS2, POLE4, SITPEC, and PPARG and putative PEST motifs were created in NEIL2, BIRC4, MLL2, and PPP1R15A. Although experimental analyses are required to confirm these results, they suggest that nsSNPs can induce changes in ubiquitin-mediated protein degradation.
  Omics A Journal of Integrative Biology 02/2007; 11(2):200-8. · 2.44 Impact Factor
• Article: Polymorphisms cMyc-N11S and p27-V109G and breast cancer risk and prognosis

  Jane Figueiredo, Julia Knight, Stewart Cho, Sevtap Savas, Onay U Venus, Laurent Briollais, Pamela Goodwin, John McLaughlin, Irene Andrulis, Hilmi Ozcelik
  [show abstract] [hide abstract]
  ABSTRACT: Abstract Background cMyc and p27 are key genes implicated in carcinogenesis. Whether polymorphisms in these genes affect breast cancer risk or prognosis is still unclear. In this study, we focus on a rare non-synonymous polymorphism in cMyc (N11S) and a common polymorphism in p27 (V109G) and determine their role in risk and prognosis using data collected from the Ontario Breast Cancer Family Registry. Methods Risk factor data was collected at baseline on a large group of women (cases = 1,115 and population-based controls = 710) and clinical data (including treatment and follow-up) were collected prospectively by periodic review of medical records for a subset of cases (N = 967) for nearly a decade. A centralized pathology review was conducted. Unconditional logistic regression was used to determine the association of polymorphisms with breast cancer risk and the Cox proportional hazards model was used to determine their association with survival. Results Our results suggest that while cMyc-N11S can be considered a putatively functional polymorphism located in the N-terminal domain, it is not associated with risk, tumor characteristics or survival. The p27-G109 allele was associated with a modest protective effect in adjusted analyses and higher T stage. We found no evidence to suggest that p27-V109G alone or in combination with cMyc-N11S was associated with survival. Age at onset and first-degree family history of breast or ovarian cancer did not significantly modify the association of these polymorphisms with breast cancer risk. Conclusion Further work is recommended to understand the potential functional role of these specific non-synonymous amino acid changes and a larger, more comprehensive investigation of genetic variation in these genes (e.g., using a tagSNP approach) in combination with other relevant genes is needed as well as consideration for treatment effects when assessing their potential role in prognosis.
  BMC Cancer. 01/2007;
• Source

  Available from: Hamdi Jarjanazi

  Article: Functional nsSNPs from carcinogenesis-related genes expressed in breast tissue: potential breast cancer risk alleles and their distribution across human populations.

  Sevtap Savas, Steffen Schmidt, Hamdi Jarjanazi, Hilmi Ozcelik
  [show abstract] [hide abstract]
  ABSTRACT: Although highly penetrant alleles of BRCA1 and BRCA2 have been shown to predispose to breast cancer, the majority of breast cancer cases are assumed to result from the presence of low-moderate penetrant alleles and environmental carcinogens. Non-synonymous single nucleotide polymorphisms (nsSNPs) are hypothesised to contribute to disease susceptibility and approximately 30 per cent of them are predicted to have a biological significance. In this study, we have applied a bioinformatics-based strategy to identify breast cancer-related nsSNPs from 981 carcinogenesis-related genes expressed in breast tissue. Our results revealed a total of 367 validated nsSNPs, 109 (29.7 per cent) of which are predicted to affect the protein function (functional nsSNPs), suggesting that these nsSNPs are likely to influence the development and homeostasis of breast tissue and hence contribute to breast cancer susceptibility. Sixty-seven of the functional nsSNPs presented as commonly occurring nsSNPs (minor allele frequencies > or =5 per cent), representing excellent candidates for breast cancer susceptibility. Additionally, a non-uniform distribution of the common functional nsSNPs among different human populations was observed: 15 nsSNPs were reported to be present in all populations analysed, whereas another set of 15 nsSNPs was specific to particular population(s). We propose that the nsSNPs analysed in this study constitute a unique resource of potential genetic factors for breast cancer susceptibility. Furthermore, the variations in functional nsSNP allele frequencies across major population backgrounds may point to the potential variability of the molecular basis of breast cancer predisposition and treatment response among different human populations.
  Human genomics 03/2006; 2(5):287-96.
• Source

  Available from: Sukru Tuzmen

  Article: Human SNPs resulting in premature stop codons and protein truncation.

  Sevtap Savas, Sukru Tuzmen, Hilmi Ozcelik
  [show abstract] [hide abstract]
  ABSTRACT: Single nucleotide polymorphisms (SNPs) constitute the most common type of genetic variation in humans. SNPs introducing premature termination codons (PTCs), herein called X-SNPs, can alter the stability and function of transcripts and proteins and thus are considered to be biologically important. Initial studies suggested a strong selection against such variations/mutations. In this study, we undertook a genome-wide systematic screening to identify human X-SNPs using the dbSNP database. Our results demonstrated the presence of 28 X-SNPs from 28 genes with known minor allele frequencies. Eight X-SNPs (28.6 per cent) were predicted to cause transcript degradation by nonsense-mediated mRNA decay. Seventeen X-SNPs (60.7 per cent) resulted in moderate to severe truncation at the C-terminus of the proteins (deletion of >50 per cent of the amino acids). The majority of the X-SNPs (78.6 per cent) represent commonly occurring SNPs, by contrast with the rarely occurring disease-causing PTC mutations. Interestingly, X-SNPs displayed a non-uniform distribution across human populations: eight X-SNPs were reported to be prevalent across three different human populations, whereas six X-SNPs were found exclusively in one or two population(s). In conclusion, we have systematically investigated human SNPs introducing PTCs with respect to their possible biological consequences, distributions across different human populations and evolutionary aspects. We believe that the SNPs reported here are likely to affect gene/protein function, although their biological and evolutionary roles need to be further investigated.
  Human genomics 03/2006; 2(5):274-86.