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  • American Association for Cancer Research (AACR)  (13)
  • 1
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 24, No. 11 ( 2015-11-01), p. 1680-1691
    Abstract: Background: A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. Methods: We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium. Results: Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10−4; OR, 1.04; 95% confidence interval (CI), 1.02–1.07] and rs77928427 (P = 1.86 × 10−4; OR, 1.04; 95% CI, 1.02–1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r2 ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor–binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue. Conclusion: Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2. Impact: Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk. Cancer Epidemiol Biomarkers Prev; 24(11); 1680–91. ©2015 AACR.
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2015
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  • 2
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    American Association for Cancer Research (AACR) ; 2020
    In:  Cancer Epidemiology, Biomarkers & Prevention Vol. 29, No. 7 ( 2020-07-01), p. 1501-1508
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 29, No. 7 ( 2020-07-01), p. 1501-1508
    Abstract: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies, with few known risk factors and biomarkers. Several blood protein biomarkers have been linked to PDAC in previous studies, but these studies have assessed only a limited number of biomarkers, usually in small samples. In this study, we evaluated associations of circulating protein levels and PDAC risk using genetic instruments. Methods: To identify novel circulating protein biomarkers of PDAC, we studied 8,280 cases and 6,728 controls of European descent from the Pancreatic Cancer Cohort Consortium and the Pancreatic Cancer Case-Control Consortium, using genetic instruments of protein quantitative trait loci. Results: We observed associations between predicted concentrations of 38 proteins and PDAC risk at an FDR of & lt; 0.05, including 23 of those proteins that showed an association even after Bonferroni correction. These include the protein encoded by ABO, which has been implicated as a potential target gene of PDAC risk variant. Eight of the identified proteins (LMA2L, TM11D, IP-10, ADH1B, STOM, TENC1, DOCK9, and CRBB2) were associated with PDAC risk after adjusting for previously reported PDAC risk variants (OR ranged from 0.79 to 1.52). Pathway enrichment analysis showed that the encoding genes for implicated proteins were significantly enriched in cancer-related pathways, such as STAT3 and IL15 production. Conclusions: We identified 38 candidates of protein biomarkers for PDAC risk. Impact: This study identifies novel protein biomarker candidates for PDAC, which if validated by additional studies, may contribute to the etiologic understanding of PDAC development.
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2020
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  • 3
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 30, No. 1 ( 2021-01-01), p. 217-228
    Abstract: Accumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers. Methods: Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data. Results: Genetic correlation analysis revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10−5). We found seven loci associated with risk for both cancers (PBonferroni & lt; 2.4 × 10−9). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified (P & lt; 5 × 10−7). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation. Conclusions: Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis. Impact: Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings.
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2021
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  • 4
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 80, No. 16_Supplement ( 2020-08-15), p. 1200-1200
    Abstract: Pancreatic ductal adenocarcinoma (PDAC) is one of most lethal malignancies with few known risk factors and biomarkers. Identification of disease biomarkers is critical for understanding the pathogenesis of this cancer and identifying high risk individuals for close surveillance. Several blood protein biomarkers have been linked to PDAC in previous studies, but these studies have assessed only a limited number of biomarkers usually in small samples. To identify novel circulating protein biomarkers of PDAC, we studied 8,280 cases and 6,728 controls of European descent from the Pancreatic Cancer Cohort Consortium and the Pancreatic Cancer Case-Control Consortium, by using genetic instruments. Protein quantitative trait loci (pQTLs) for 1,226 plasma proteins identified in a large INTERVAL study of 3,301 healthy European descendants were used as instruments to evaluate associations between genetically predicted protein levels and PDAC. For proteins showing a significant association, we further conducted conditional analysis with adjustments for previously identified risk variants to assess whether the observed associations between genetically predicted protein concentrations and PDAC risk were independent of the risk variants identified in genome-wide association studies (GWAS). Furthermore, for the proteins that were associated with PDAC risk, we performed an enrichment analysis of the genes encoding these proteins to examine whether they are enriched in specific pathways, functions or networks. We observed associations between predicted concentrations of 38 proteins and PDAC risk at a false discovery rate of & lt; 0.05, including those of 23 proteins that showed a significant association even after Bonferroni correction (4.08 × 10−5). These include Histo-blood group ABO system transferase encoded by ABO, which has been previously implicated as a potential target gene of PDAC risk variant identified in GWAS. Eight of the identified proteins (Beta-crystallin B2, Dedicator of cytokinesis protein 9, VIP36-like protein, Erythrocyte band 7 integral membrane protein, Tensin-2, Transmembrane protease serine 11D, Alcohol dehydrogenase 1B, and C-X-C motif chemokine 10) were associated with PDAC risk after conditioning on previously reported pancreatic cancer risk variants (odds ratios ranged from 0.79 to 1.52, P-values from 1.28 × 10−3 to 6.47 × 10−4). Pathway enrichment analysis showed that the encoding genes for the implicated proteins were significantly enriched in cancer-related pathways, such as STAT3 and IL-15 production. In conclusion, we identified 38 protein biomarker candidates for PDAC risk, which if validated by additional studies, may contribute to the etiological understanding of PDAC tumor development. Citation Format: Jingjing Zhu, Xiang Shu, Xingyi Guo, Duo Liu, Jiandong bao, Roger Milne, Graham G Giles, Chong Wu, Mengmeng Du, Emily White, Harvey A Risch, Nuria Malats, Eric J. Duell, Phyllis J. Goodman, Donghui Li, Paige Bracci, Verena Katzke, Rachel E Neale, Steven Gallinger, Stephen Van Den Eeden, Alan Arslan, Federico Canzian, Charles Kooperberg, Brian Wolpin, Laura Beane-Freeman, Ghislaine Scelo, Kala Visvanatha, Christopher A. Haiman, Loïc Le Marchand, Herbert Yu, Gloria M Petersen, Rachael Stolzenberg-Solomon, Alison P Klein, Laufey T Amundadottir, Qiuyin Cai, Jirong Long, Xiao-Ou Shu, Wei Zheng, Lang Wu. Associations between genetically predicted blood protein biomarkers and pancreatic ductal adenocarcinoma risk [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1200.
    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: 2020
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  • 5
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 3 ( 2019-02-01), p. 505-517
    Abstract: DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study (N = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of P & lt; 7.94 × 10−7. Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely MAPT, HOXB3, ABHD8, ARHGAP27, and SKAP1. We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression. Significance: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.
    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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  • 6
    In: Cancer Discovery, American Association for Cancer Research (AACR), Vol. 6, No. 9 ( 2016-09-01), p. 1052-1067
    Abstract: Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P & lt; 10−8 seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type–specific expression quantitative trait locus and enhancer–gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P & lt; 10−5 in the three-cancer meta-analysis. Significance: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052–67. ©2016 AACR. This article is highlighted in the In This Issue feature, p. 932
    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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  • 7
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 68, No. 4 ( 2008-02-15), p. 1119-1127
    Abstract: Phosphatase and tensin homologue deleted from chromosome 10 (Pten) is expressed aberrantly in non–small cell lung cancer cells, but the role of Pten in lung neoplasia has not been fully elucidated. In this study, we used a genetic approach to inactivate Pten in the bronchial epithelium of mice. Although, by itself, Pten inactivation had no discernible effect on bronchial epithelial histology, it accelerated lung tumorigenesis initiated by oncogenic K-ras, causing more rapid lethality than that induced by oncogenic K-ras alone (8 weeks versus 24 weeks of median duration of survival, respectively). Lung tumors arose in K-ras mutant, Pten-deficient mice that rapidly obstructed bronchial lumina and replaced alveolar spaces. Relative to K-ras mutant tumors, the K-ras mutant, Pten-deficient tumors exhibited more advanced histologic severity and more prominent inflammation and vascularity. Thus, Pten inactivation cooperated with oncogenic K-ras in promoting lung tumorigenesis. [Cancer Res 2008;68(4):1119–27]
    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: 2008
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  • 8
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 31, No. 6 ( 2022-06-01), p. 1216-1226
    Abstract: The etiology of colorectal cancer is not fully understood. Methods: Using genetic variants and metabolomics data including 217 metabolites from the Framingham Heart Study (n = 1,357), we built genetic prediction models for circulating metabolites. Models with prediction R2 & gt; 0.01 (Nmetabolite = 58) were applied to predict levels of metabolites in two large consortia with a combined sample size of approximately 46,300 cases and 59,200 controls of European and approximately 21,700 cases and 47,400 controls of East Asian (EA) descent. Genetically predicted levels of metabolites were evaluated for their associations with colorectal cancer risk in logistic regressions within each racial group, after which the results were combined by meta-analysis. Results: Of the 58 metabolites tested, 24 metabolites were significantly associated with colorectal cancer risk [Benjamini–Hochberg FDR (BH-FDR) & lt; 0.05] in the European population (ORs ranged from 0.91 to 1.06; P values ranged from 0.02 to 6.4 × 10−8). Twenty one of the 24 associations were replicated in the EA population (ORs ranged from 0.26 to 1.69, BH-FDR & lt; 0.05). In addition, the genetically predicted levels of C16:0 cholesteryl ester was significantly associated with colorectal cancer risk in the EA population only (OREA: 1.94, 95% CI, 1.60−2.36, P = 2.6 × 10−11; OREUR: 1.01, 95% CI, 0.99−1.04, P = 0.3). Nineteen of the 25 metabolites were glycerophospholipids and triacylglycerols (TAG). Eighteen associations exhibited significant heterogeneity between the two racial groups (PEUR-EA-Het & lt; 0.005), which were more strongly associated in the EA population. This integrative study suggested a potential role of lipids, especially certain glycerophospholipids and TAGs, in the etiology of colorectal cancer. Conclusions: This study identified potential novel risk biomarkers for colorectal cancer by integrating genetics and circulating metabolomics data. Impact: The identified metabolites could be developed into new tools for risk assessment of colorectal cancer in both European and EA populations.
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2022
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  • 9
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 71, No. 4 ( 2011-02-15), p. 1344-1355
    Abstract: We evaluated the generalizability of a single nucleotide polymorphism (SNP), rs2046210 (A/G allele), associated with breast cancer risk that was initially identified at 6q25.1 in a genome-wide association study conducted among Chinese women. In a pooled analysis of more than 31,000 women of East-Asian, European, and African ancestry, we found a positive association for rs2046210 and breast cancer risk in Chinese women [ORs (95% CI) = 1.30 (1.22–1.38) and 1.64 (1.50–1.80) for the AG and AA genotypes, respectively, P for trend = 1.54 × 10−30], Japanese women [ORs (95% CI) = 1.31 (1.13–1.52) and 1.37 (1.06–1.76), P for trend = 2.51 × 10−4] , and European-ancestry American women [ORs (95% CI) = 1.07 (0.99–1.16) and 1.18 (1.04–1.34), P for trend = 0.0069]. No association with this SNP, however, was observed in African American women [ORs (95% CI) = 0.81 (0.63–1.06) and 0.85 (0.65–1.11) for the AG and AA genotypes, respectively, P for trend = 0.4027] . In vitro functional genomic studies identified a putative functional variant, rs6913578. This SNP is 1,440 bp downstream of rs2046210 and is in high linkage disequilibrium with rs2046210 in Chinese (r2 = 0.91) and European-ancestry (r2 = 0.83) populations, but not in Africans (r2 = 0.57). SNP rs6913578 was found to be associated with breast cancer risk in Chinese and European-ancestry American women. After adjusting for rs2046210, the association of rs6913578 with breast cancer risk in African Americans approached borderline significance. Results from this large consortium study confirmed the association of rs2046210 with breast cancer risk among women of Chinese, Japanese, and European ancestry. This association may be explained in part by a putatively functional variant (rs6913578) identified in the region. Cancer Res; 71(4); 1344–55. ©2011 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: 2011
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  • 10
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 70, No. 8_Supplement ( 2010-04-15), p. 3267-3267
    Abstract: Human breast cancer development is a complex pathobiological process driven by genetic changes in normal epithelial cells which lead to uncontrollable growth in a permissive microenvironment. Therefore, it is not surprising that tumors from different patients exhibit variable responses to standard of care therapy with unfortunately only a small percentage of patients benefitting from therapy. It has therefore become a priority in oncology and personalized medicine to match patients to drugs that will result in a favorable treatment outcome. In this report, we describe a population based approach for response prediction featuring naturally occurring variation in tumors derived from genetically defined human-in-mouse models of cancer. De novo human breast tumors were generated by genetically engineering normal primary human breast epithelial cells with HER2 and SV40 early region (HER2/SV40er) or KRAS and SV40 early region (KRAS/SV40er) in an in vivo Human_In_Mouse (HIM) tissue transgenic model. The HER2/SV40er and the KRAS/SV40er HIM tumors develop as human breast adenocarcinoma that are histologically similar to those observed in patients. Also similar to that observed in human tumors, microarray profiling demonstrated significant inter-tumor variation among the established tumors. Moreover, the KRAS/SV40er tumors could be clustered with basal type breast cancers from patients, a poor prognosis human breast cancer subtype. Both HER2/SV40er and KRAS/SV40er tumors exhibited variable responses to treatments with the potent selective triple VEGFR inhibitor, tivozanib. Further characterization of those tumors, both pre- and post- treatment, identified potential biomarkers for tumor response to tivozanib. This population-based approach enables us to identify and validate biomarkers of therapeutic response in an in vivo human tumor model. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3267.
    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: 2010
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