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  • American Association for Cancer Research (AACR)  (11)
  • 1
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 72, No. 8_Supplement ( 2012-04-15), p. LB-423-LB-423
    Abstract: Background: Estrogen receptors are over-expressed in around 70% of breast cancer cases. The genetic changes that occur during aromatase inhibitor (AI) treatment are not well understood and may differ depending upon the patient's response phenotype. Methods: We performed whole genome sequencing (WGS) of matched blood, pre-treatment, and post-treatment biopsy samples from 22 estrogen receptor positive breast cancer patients treated with neoadjuvant aromatase inhibitors. For 5 cases, we performed the whole genome sequencing (WGS) on patients’ matched normal, two pre AI-treatment, and two post AI-treatment DNA isolates from biopsy samples. We validated all putative coding and non-coding somatic mutations using deep sequencing. By comparing the validated somatic mutations from pre- and post- AI treatment biopsy samples, we were able to determine the alterations in the tumor genomes. In every case we defined the clonal architecture of each pair of pre-treatment and post-treatment biopsy samples by comparing the variant allele frequencies from thousands of validated somatic mutations. Results: Comparisons of the two pre AI-treatment biopsy samples from the same patient indicates that the variant allele frequencies of mutations showed high concordances in all 5 cases, 0.74 to 0.95 range of correlation coefficient. Only a small percentage of somatic mutations were detected in one pre-treatment sample and not the other (4.65% overall). In comparing the somatic variations between pre-treatment and matched post-treatment biopsy samples in 22 cases, we found that patients with good clinical response to AI treatment retained known driver mutations only in their pre-treatment tumors. Conversely, those patients with poor clinical response presented new driver mutations in their post-treatment samples. Furthermore, the variant allele frequency for most mutated genes decreased in post AI treatment samples for patients with good AI treatment response; on the contrary, the variant allele frequency increased for patients with poor clinical response. Conclusions: From WGS of matched normal, pre-treatment, and post-treatment biopsy samples, we identified new driver genes mutated in patients with poor clinical response, while patients with good clinical response had lost mutated driver genes in their post-treatment biopsy samples. The genetic landscape revealed by WGS of pre-treatment and post-treatment biopsy samples reveals mutational repertoires are remodeled by AI therapy. This finding suggests deep sequencing of AI treated samples will be necessary to reveal the complete complement of mutations present in a patient's tumor. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr LB-423. doi:1538-7445.AM2012-LB-423
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2012
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  • 2
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 13_Supplement ( 2018-07-01), p. 233-233
    Abstract: Glioma incidence is highest in non-Hispanic Whites, where it occurs ~2x as frequently compared with other race/ethnicity groups. Glioma GWAS to date have included European ancestry populations only, and it is unknown whether variants identified by these analyses are associated with glioma in non- European ancestry populations. African Americans and Hispanics are admixed populations with varying proportions of European ancestry. While global ancestry may be similar within admixed groups, the proportion of European ancestry at each allele can vary across the genome. As glioma is more common in European ancestry populations, the presence of increased local European ancestry in these admixed populations could be used to identify glioma risk loci. Here we assessed whether excess European ancestry at established risk loci (Melin et al, Nature Genetics, 2017) was associated with glioma risk in non-European ancestry populations. Global ancestry was estimated using fastStructure, and local ancestry was estimated using RFMix. Both methods used 1,000 genomes project reference populations (African: YRI; European: CEU; East Asian: CHB/JPT; and Native American: CLM/PEL/MXL). We evaluated differences in local European ancestry between cases and controls using logistic regression conditioned on global European ancestry within 500kb of 25 previously identified risk variants among individuals with ≥50% African ancestry, and ≥30% Native American ancestry for all gliomas, and for grade IV glioblastoma (GBM) and grade II-III non-GBM. There were 347 individuals (184 cases and 163 controls) with ≥50% global African ancestry, and 277 individuals (153 cases and 124 controls) with ≥30% global American ancestry. There was no significant difference in proportion of global European ancestry between cases and controls with ≥50% global African ancestry (cases: 18.2%, controls: 17.7%, p=0.6834), and no significant difference in proportion of global European ancestry between cases and controls with ≥30% global American ancestry (cases: 51.1%, controls: 49.0%, p=0.2123). Among individuals with & gt;50% African ancestry, we observed a nominally significant association between all glioma and increased local European ancestry at 7p11.2 (EGFR, pmin=0.0070) and between GBM and increased local European ancestry at 22q13.1 (CSNK1E, pmin=0.0098), both near SNPs previously associated with glioblastoma in majority European-ancestry populations. The dataset used for this analysis represents the largest collection of genotyped non-European glioma cases. These results suggest that glioma risk in African Americans may be associated with an increased local European ancestry variants at glioma risk loci previously identified in majority European ancestry populations (7p11.2 and 22q13.1). Citation Format: Quinn T. Ostrom, Kathleen M. Egan, L. Burt Nabors, Travis Gerke, Reid C. Thompson, Jeffrey J. Olson, Renato LaRocca, Sajeel Chowdhary, Jeanette E. Eckel-Passow, Georgina Armstrong, John K. Wiencke, Christopher I. Amos, Jonine L. Bernstein, Elizabeth B. Claus, Dora Il'yasova, Christoffer Johansen, Daniel H. Lachance, Rose Lai, Ryan T. Merrell, Sara H. Olson, Siegal Sadetzki, Joellen Schildkraut, Sanjay Shete, Richard S. Houlston, Robert B. Jenkins, Beatrice Melin, Melissa L. Bondy, Jill S. Barnholtz-Sloan. Evaluating glioma risk associated with extent of European admixture in African-Americans and Latinos [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 233.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2018
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  • 3
    In: Cancer Discovery, American Association for Cancer Research (AACR), Vol. 6, No. 2 ( 2016-02-01), p. 166-175
    Abstract: Pancreatic cancer is projected to become the second leading cause of cancer-related death in the United States by 2020. A familial aggregation of pancreatic cancer has been established, but the cause of this aggregation in most families is unknown. To determine the genetic basis of susceptibility in these families, we sequenced the germline genomes of 638 patients with familial pancreatic cancer and the tumor exomes of 39 familial pancreatic adenocarcinomas. Our analyses support the role of previously identified familial pancreatic cancer susceptibility genes such as BRCA2, CDKN2A, and ATM, and identify novel candidate genes harboring rare, deleterious germline variants for further characterization. We also show how somatic point mutations that occur during hematopoiesis can affect the interpretation of genome-wide studies of hereditary traits. Our observations have important implications for the etiology of pancreatic cancer and for the identification of susceptibility genes in other common cancer types. Significance: The genetic basis of disease susceptibility in the majority of patients with familial pancreatic cancer is unknown. We whole genome sequenced 638 patients with familial pancreatic cancer and demonstrate that the genetic underpinning of inherited pancreatic cancer is highly heterogeneous. This has significant implications for the management of patients with familial pancreatic cancer. Cancer Discov; 6(2); 166–75. ©2015 AACR. This article is highlighted in the In This Issue feature, p. 109
    Type of Medium: Online Resource
    ISSN: 2159-8274 , 2159-8290
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2016
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  • 4
    In: Cancer Prevention Research, American Association for Cancer Research (AACR), Vol. 7, No. 1 ( 2014-01-01), p. 105-113
    Abstract: Colorectal cancer often arises from adenomatous colonic polyps. Polyps can grow and progress to cancer, but may also remain static in size, regress, or resolve. Predicting which polyps progress and which remain benign is difficult. We developed a novel long-lived murine model of colorectal cancer with tumors that can be followed by colonoscopy. Our aim was to assess whether these tumors have similar growth patterns and histologic fates to human colorectal polyps to identify features to aid in risk stratification of colonic tumors. Long-lived ApcMin/+ mice were treated with dextran sodium sulfate to promote colonic tumorigenesis. Tumor growth patterns were characterized by serial colonoscopy with biopsies obtained for immunohistochemistry and gene expression profiling. Tumors grew, remained static, regressed, or resolved over time with different relative frequencies. Newly developed tumors demonstrated higher rates of growth and resolution than more established tumors that tended to remain static in size. Colonic tumors were hyperplastic lesions (3%), adenomas (73%), intramucosal carcinomas (20%), or adenocarcinomas (3%). Interestingly, the level of β-catenin was higher in adenomas that became intratumoral carcinomas than those that failed to progress. In addition, differentially expressed genes between adenomas and intramucosal carcinomas were identified. This novel murine model of intestinal tumorigenesis develops colonic tumors that can be monitored by serial colonoscopy, mirror growth patterns seen in human colorectal polyps, and progress to colorectal cancer. Further characterization of cellular and molecular features is needed to determine which features can be used to risk-stratify polyps for progression to colorectal cancer and potentially guide prevention strategies. Cancer Prev Res; 7(1); 105–13. ©2013 AACR.
    Type of Medium: Online Resource
    ISSN: 1940-6207 , 1940-6215
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2014
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  • 5
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 77, No. 11 ( 2017-06-01), p. 2869-2880
    Abstract: The vision of a precision medicine–guided approach to novel cancer drug development is challenged by high intratumor heterogeneity and interpatient diversity. This complexity is rarely modeled accurately during preclinical drug development, hampering predictions of clinical drug efficacy. To address this issue, we developed Comparative In Vivo Oncology (CIVO) arrayed microinjection technology to test tumor responsiveness to simultaneous microdoses of multiple drugs directly in a patient's tumor. Here, in a study of 18 canine patients with soft tissue sarcoma (STS), CIVO captured complex, patient-specific tumor responses encompassing both cancer cells and multiple immune infiltrates following localized exposure to different chemotherapy agents. CIVO also classified patient-specific tumor resistance to the most effective agent, doxorubicin, and further enabled assessment of a preclinical autophagy inhibitor, PS-1001, to reverse doxorubicin resistance. In a CIVO-identified subset of doxorubicin-resistant tumors, PS-1001 resulted in enhanced antitumor activity, increased infiltration of macrophages, and skewed this infiltrate toward M1 polarization. The ability to evaluate and cross-compare multiple drugs and drug combinations simultaneously in living tumors and across a diverse immunocompetent patient population may provide a foundation from which to make informed drug development decisions. This method also represents a viable functional approach to complement current precision oncology strategies. Cancer Res; 77(11); 2869–80. ©2017 AACR.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2017
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  • 6
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 76, No. 14_Supplement ( 2016-07-15), p. 3446-3446
    Abstract: Background: Numerous epidemiologic studies have examined the association between aspirin (ASA), non-steroid anti-inflammatory drugs (NSAIDs) and the development of glioma, but the results have been inconsistent. The goal of this study was to evaluate the relationship between the intake of these drugs and glioma risk in a large, international case-control study. Methods: Between 2010 and 2015, the Glioma International Case-Control Study (GICC) recruited newly diagnosed glioma cases and matched controls in 14 different sites across five countries. Each subject was interviewed using a standardized questionnaire to obtain NSAIDs and ASA use. We examined the associations between ever use (at least & gt; 6 months), duration of drug use and glioma histology. Ever use data on 4533 glioma cases and 4171 controls was combined using maximum likelihood estimation/restricted maximum likelihood meta-analysis methods. Furthermore, based on a priori hypotheses, we performed subgroup analyses based on gender and glioma histological grades. Results: Use of ASA for & gt; 6 months was associated with a 33% lower glioma risk compared to those who never took it (adjusted Meta-OR 0.67, 95% CI 0.54-0.83). Duration of intake showed a significant trend test (p & lt; 0.0001), with ORs became lower for increasing number of years of ASA use. In subgroup analyses, intake of ASA was significantly associated with glioma risk in both men and women (adjusted Meta-OR = 0.65, 95% CI 0.51-0.84 for men; adjusted Meta-OR = 0.74, 95% CI 0.58-0.93 for women). ASA intake was protective for grade IV glioma (glioblastoma) and grade II/III glioma (adjusted meta-OR 0.63, 95% CI 0.5-0.8 for glioblastoma; adjusted meta-OR 0.67, 95% CI 0.50 - 0.89 for grade II/III glioma). For NSAIDs intake, ever use & gt; 6 months was not associated with glioma risk (adjusted meta-OR 0.87, 95% CI 0.71-1.07). However, NSAIDs use was protective for women (adjusted meta-OR 0.72, 95% CI 0.55-0.93) in subgroup analyses but not for men (adjusted meta-OR 1.03; 95% CI 0.86-1.23). The interaction between gender, NSAIDs and glioma risk was significant (p-value 0.0076).. Sensitivity analyses excluding those who took ASA or NSAIDs within the past 12 months for headache, and the removal of proxy respondents did not change our results. Conclusion: ASA was associated with a significant protective effect for glioma, but NSAIDs were only associated with reduced glioma risk in women. Given the possibility of recall bias in case-control studies of brain tumors, we may verify dosage and duration of drug intake in those countries with electronic pharmacy records within the GICC. Citation Format: Rose K. Lai, Renke Zhou, E. Susan Amirian, Christoffer Johansen, Michael E. Scheurer, Georgina N. Armstrong, Ching C. Lau, Elizabeth B. Claus, Jill S. Barnholtz-Sloan, Dora Il’yasova, Joellen Schildkraut, Francis Ali-Osman, Siegal Sadetzki, Richard Houlston, Robert B. Jenkins, Daniel Lachance, Sara H. Olson, Jonine L. Bernstein, Ryan T. Merrell, Margaret R. Wrensch, Faith G. Davis, Sanjay Shete, Christopher I. Amos, Beatrice S. Melin, Melissa Bondy. Aspirin, non-steroidal anti-inflammatory drugs (NSAIDs) and the risk of glioma: Results from the Glioma International Case Control Study. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3446.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2016
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  • 7
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 8 ( 2019-04-15), p. 2065-2071
    Abstract: Genome-wide association studies (GWAS) have so far identified 25 loci associated with glioma risk, with most showing specificity for either glioblastoma (GBM) or non-GBM tumors. The majority of these GWAS susceptibility variants reside in noncoding regions and the causal genes underlying the associations are largely unknown. Here we performed a transcriptome-wide association study to search for novel risk loci and candidate causal genes at known GWAS loci using Genotype-Tissue Expression Project (GTEx) data to predict cis-predicted gene expression in relation to GBM and non-GBM risk in conjunction with GWAS summary statistics on 12,488 glioma cases (6,183 GBM and 5,820 non-GBM) and 18,169 controls. Imposing a Bonferroni-corrected significance level of P & lt; 5.69 × 10−6, we identified 31 genes, including GALNT6 at 12q13.33, as a candidate novel risk locus for GBM (mean Z = 4.43; P = 5.68 × 10−6). GALNT6 resides at least 55 Mb away from any previously identified glioma risk variant, while all other 30 significantly associated genes were located within 1 Mb of known GWAS-identified loci and were not significant after conditioning on the known GWAS-identified variants. These data identify a novel locus (GALNT6 at 12q13.33) and 30 genes at 12 known glioma risk loci associated with glioma risk, providing further insights into glioma tumorigenesis. Significance: This study identifies new genes associated with glioma risk, increasing understanding of how these tumors develop.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
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  • 8
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 4173-4173
    Abstract: BACKGROUND: Approximately 5% of gliomas occur in individuals with a family history of glioma, and first-degree relatives of brain tumor cases have a two-fold increase in risk of brain tumor. Recent somatic characterization has shown that tumors from familial cases are indistinguishable from sporadic cases, suggesting that familial cases may arise through similar mechanisms of gliomagenesis, and therefore may be associated with common variants as well as rare mutations. In this analysis, we assessed whether previously identified common risk variants are associated with familial glioma. METHODS: Data were obtained from the Glioma International Case Control (GICC) and Gliogene studies for 448 cases with reported family history, 4,405 cases without reported family history, and 3,288 controls. We assessed 25 risk loci previously identified by glioma GWAS, and odds ratios (OR) and 95% confidence intervals (95%CI) were calculated using an additive genetic logistic regression model adjusted for age, sex, and the first two principal components for familial cases versus unaffected controls, and non-familial cases versus controls. Results were considered significant at p & lt;0.002 (Bonferroni correction for 25 tests). RESULTS: Significant associations were detected at 5/25 loci, including TERT, EGFR, CCDC26, CDKN2B, and RTEL1. The strongest association was at rs55705857 (CCDC26, OR=2.7, p=7.49x10-17). For GBM (222 familial cases), significant associations were detected at 6/26 loci (TERT, EGFR, CDKN2B, TP53 and RTEL1), while in non-GBM (205 familial cases) significant associations were detected at 3/25 loci (LRIG1, CCDC26, PHLDB1). These SNPs were further examined using a case-only approach comparing familial to non-familial cases, and there was no significant difference in allele frequencies by family history status. There was a strong correlation between log(OR) for familial cases only versus non-familial cases (adjusted R2=0.88). CONCLUSIONS: In this analysis we identified a significant association between familial glioma and five common risk loci previously identified by glioma GWAS. This provides further evidence of shared pathways of genetic risk and gliomagenesis between familial and non-familial glioma. Further exploration is necessary to determine the overall contribution of common genetic variation to risk of familial glioma. Citation Format: Quinn T. Ostrom, Georgina Armstrong, Christopher I. Amos, Jonine L. Bernstein, Elizabeth B. Claus, Jeanette E. Eckel-Passow, Dora Il'yasova, Christoffer Johansen, Daniel H. Lachance, Rose K. Lai, Ryan T. Merrell, Sara H. Olson, Joellen H. Schildkraut, Sanjay S. Shete, Richard S. Houlston, Robert B. Jenkins, Margaret R. Wrensch, Beatrice Melin, Jill S. Barnholtz-Sloan, Melissa L. Bondy. Previously identified common glioma risk SNPs are associated with familial glioma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4173.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
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  • 9
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 77, No. 13_Supplement ( 2017-07-01), p. 1302-1302
    Abstract: BACKGROUND: Glioma accounts for ~27% of all primary brain tumors and is responsible for ~13,000 cancer-related deaths in the US each year. Glioma tumors can be broadly classified into glioblastoma (GBM) and lower-grade non-GBM. Typically gliomas have a poor prognosis irrespective of medical care, with the most common form, GBM, having a five-year survival rate of only 5%. While genome-wide association studies (GWAS) have transformed our understanding of glioma susceptibility, individual studies have had limited power to identify risk loci. METHODS: We performed the largest glioma GWAS to date, comprising a meta-analysis of six existing GWAS (6,405 cases, 14,100 controls) as well as new GWAS from the Glioma International Case Control Consortium (GICC; 4,572 cases and 3,286 controls) and University of California, San Francisco (UCSF)-Mayo (1,519 cases, 804 controls), totaling 12,496 cases (6,191 classified as GBM, 5,819 as non-GBM) and 18,190 controls. RESULTS: We identified five new risk loci for GBM at 1p31.3 (rs12752552; near JAK1, P=2.04×10-9, odds ratio (OR)=1.22), 11q14.1 (rs11233250; P=9.95×10-10, OR=1.24), 16p13.3 (rs2562152; near MPG, P=1.93x10-8, OR=1.21), 16q12.1 (rs10852606; HEATR3, P=1.29×10-11, OR=1.18), 22q13.1 (rs2235573; P=1.76×10-10, OR=1.15) and eight for non-GBM at 1q32.1 (rs4252707; MDM4, P=3.34×10-9, OR=1.19), 1q44 (rs12076373; AKT3, P=2.63×10-10, OR=1.23), 2q33.3 (rs7572263; near IDH1, P=2.18×10-10, OR=1.20), 3p14.1 (rs11706832; LRIG1, P=7.66×10-9, OR=1.15), 10q24.33 (rs11598018; OBFC1, P=3.39×10-8, OR=1.14), 11q21 (rs7107785; P=3.87×10-10, OR=1.16), 14q12 (rs10131032; P=5.07x10-11, OR=1.33) and 16p13.3 (rs3751667; P=2.61×10-9, OR=1.18). Case-only analyses confirmed the specificity of 11q14.1, 16p13.3 and 22q13.1 associations for GBM and 1q44, 2q33.3, 3p14.1, 11q21 and 14q12 for non-GBM tumors. In the combined meta-analysis, among previously published glioma risk SNPs, those for all glioma at 17p13.1 (TP53), GBM at 5p15.33 (TERT), 7p11.2 (EGFR), 9p21.3 (CDKN2B-AS1) and 20q13.33 (RTEL1) and for non-GBM at 8q24.21 (CCDC26), 11q23.2, 11q23.3 (PHLDB1) and 15q24.2 (ETFA) showed even greater evidence for association. SNPs at 10q25.2 and 12q12.1 for non-GBM tumors retained genome-wide significance (i.e. P & lt;5.0x10-8). Associations at the previously reported loci for GBM at 3q26.2 (near TERC) and 12q23.33 (POLR3B) did not retain statistical significance. CONCLUSIONS: Our findings substantiate genetic susceptibility to GBM and non-GBM glioma being highly distinct, consistent with their distinctive molecular profiles presumably resulting from different etiological pathways. Functional analyses should lead to further insights into the biological basis of the different glioma histologies. Such information can inform gene discovery initiatives and therefore have a measurable impact on the successful development of new therapeutic agents. Citation Format: Ben Kinnersley, Beatrice S. Melin, Jill S. Barnholtz-Sloan, Margaret R. Wrensch, Christoffer Johansen, Dora Il’yasova, Quinn Ostrom, and members of GICC, Karim Labreche, Jeanette E. Eckel-Passow, Paul A. Decker, Marianne Labussière, Ahmed Idbaih, Khe Hoang-Xuan, Anna-Luisa Di Stefano, Karima Mokhtari, Jean-Yves Delattre, Pilar Galan, Konstantinos Gousias, Johannes Schramm, Minouk J. Schoemaker, Sarah J. Fleming, Stefan Herms, Stefanie Heilmann, Marcus M. Nöthen, Heinz-Erich Wichmann, Stefan Schreiber, Anthony Swerdlow, Mark Lathrop, Matthias Simon, Marc Sanson, Preetha Rajaraman, Stephen Chanock, Martha Linet, Zhaoming Wang, Meredith Yeager, Rose K. Lai, Elizabeth B. Claus, Sara H. Olson, Robert B. Jenkins, Richard S. Houlston, Melissa L. Bondy. Genome-wide association study of glioma reveals specific differences in genetic susceptibility to glioblastoma and non-glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1302. doi:10.1158/1538-7445.AM2017-1302
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2017
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  • 10
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 28, No. 3 ( 2019-03-01), p. 555-562
    Abstract: There have been few studies of sufficient size to address the relationship between glioma risk and the use of aspirin or NSAIDs, and results have been conflicting. The purpose of this study was to examine the associations between glioma and aspirin/NSAID use, and to aggregate these findings with prior published studies using meta-analysis. Methods: The Glioma International Case-Control Study (GICC) consists of 4,533 glioma cases and 4,171 controls recruited from 2010 to 2013. Interviews were conducted using a standardized questionnaire to obtain information on aspirin/NSAID use. We examined history of regular use for ≥6 months and duration-response. Restricted maximum likelihood meta-regression models were used to aggregate site-specific estimates, and to combine GICC estimates with previously published studies. Results: A history of daily aspirin use for ≥6 months was associated with a 38% lower glioma risk, compared with not having a history of daily use [adjusted meta-OR = 0.62; 95% confidence interval (CI), 0.54–0.70]. There was a significant duration-response trend (P = 1.67 × 10−17), with lower ORs for increasing duration of aspirin use. Duration-response trends were not observed for NSAID use. In the meta-analysis aggregating GICC data with five previous studies, there was a marginally significant association between use of aspirin and glioma (mOR = 0.84; 95% CI, 0.70–1.02), but no association for NSAID use. Conclusions: Our study suggests that aspirin may be associated with a reduced risk of glioma. Impact: These results imply that aspirin use may be associated with decreased glioma risk. Further research examining the association between aspirin use and glioma risk is warranted.
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
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