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Li, Donghui

https://orcid.org/0000-0002-7542-0662

Mayo Clinic

The University of Texas MD Anderson Cancer Center

Citations 26

Genome-Wide Gene–Diabetes and Gene–Obesity Interaction Scan in 8,255 Cases and 11,900 Controls from PanScan and PanC4 Consortia
Tang, Hongwei, Jiang, Lai , Arslan, Alan A. , Bracci, Paige M. , Brennan, Paul , Canzian, Federico , Du, Mengmeng , Gallinger, Steven , Goodman, Phyllis J. , Visvanathan, Kala , Andreotti, Gabriella , Babić, Ana , Berndt, Sonja I. , Bueno‐de‐Mesquita, Bas , Buring, Julie E. , Campa, Daniele , Childs, Erica J., Fuchs, Charles S. , Gaziano, J. Michael , Hartge, Patricia, Hassam, Manal H., Holly, Elizabeth A. , Hoover, Robert N. , Hung, Rayjean J. , Kurtz, Robert C. , Lee, I-Min, Ng, Kimmie , Oberg, Ann L. , Peters, Ulrike , Porta, Miquel , Rabe, Kari G. , Rothman, Nathaniel , Scélo, Ghislaine , Sesso, Howard D. , Thompson, Ian M. , Tjønneland, Anne , Trichopoulou, Antonia , Wactawski‐Wende, Jean , Wentzensen, Nicolas , Zeleniuch‐Jacquotte, Anne , Jacobs, Eric J. , Petersen, Gloria M. , Wolpin, Brian M. , Chatterjee, Nilanjan , Li, Donghui , Arslan, Alan A , Brennan, Paul , Canzian, Federico , Bamlet, William R , Blackford, Amanda , Duell, Eric J , Hung, Rayjean J , Malats, Nuria , Milne, Roger L , Oberg, Ann L , Orlow, Irene , Sesso, Howard D , Tjønneland, Anne , Wactawski-Wende, Jean , Yu, Herbert , Amundadottir, Laufey , Klein, Alison P , Li, Donghui , Chaffee, Kari G. , Visvanathan, Kala , Porta, Miquel , Thompson, Ian M , Zeleniuch-Jacquotte, Anne , Stolzenberg‐Solomon, Rachael Z. , Freeman, Laura E. Beane , Giles, Graham G. , Kooperberg, Charles , Marchand, Loı̈c Le , Neale, Rachel Ε. , Shu, Xiao‐Ou , White, Emily , Zheng, Wei , Albanes, Demetrius , Bamlet, William R. , Chanock, Stephen Jacob , Duell, Eric J. , Goggins, Michael , Malats, Núria , Milne, Roger L. , Orlow, Irene , Rothman, Nathaniel , Silverman, Debra T. , Wilkens, Lynne R. , Yu, Kai , Ámundadóttir, Laufey T. , Risch, Harvey A. , Klein, Alison P. , Kraft, Peter , Wei, Peng

Cancer Epidemiology, Biomarkers & Prevention | June 16, 2020 | Volume: 29 | Issue: 9 | Pages: 1784-1791

10.1158/1055-9965.epi-20-0275 Get It

Abstract Background: Obesity and diabetes are major modifiable risk factors for pancreatic cancer. Interactions between genetic variants and diabetes/obesity have not previously been comprehensively investigated in pancreatic cancer at the genome-wide level. Methods: We conducted a gene–environment interaction (GxE) analysis including 8,255 cases and 11,900 controls from four pancreatic cancer genome-wide association study (GWAS) datasets (Pancreatic Cancer Cohort Consortium I–III and Pancreatic Cancer Case Control Consortium). Obesity (body mass index ≥30 kg/m2) and diabetes (duration ≥3 years) were the environmental variables of interest. Approximately 870,000 SNPs (minor allele frequency ≥0.005, genotyped in at least one dataset) were analyzed. Case–control (CC), case-only (CO), and joint-effect test methods were used for SNP-level GxE analysis. As a complementary approach, gene-based GxE analysis was also performed. Age, sex, study site, and principal components accounting for population substructure were included as covariates. Meta-analysis was applied to combine individual GWAS summary statistics. Results: No genome-wide significant interactions (departures from a log-additive odds model) with diabetes or obesity were detected at the SNP level by the CC or CO approaches. The joint-effect test detected numerous genome-wide significant GxE signals in the GWAS main effects top hit regions, but the significance diminished after adjusting for the GWAS top hits. In the gene-based analysis, a significant interaction of diabetes with variants in the FAM63A (family with sequence similarity 63 member A) gene (significance threshold P < 1.25 × 10−6) was observed in the meta-analysis (PGxE = 1.2 ×10−6, PJoint = 4.2 ×10−7). Conclusions: This analysis did not find significant GxE interactions at the SNP level but found one significant interaction with diabetes at the gene level. A larger sample size might unveil additional genetic factors via GxE scans. Impact: This study may contribute to discovering the mechanism of diabetes-associated pancreatic cancer.
Population-based targeted sequencing of 54 candidate genes identifies PALB2 as a susceptibility gene for high-grade serous ovarian cancer
Song, Honglin , Dicks, Ed , Intermaggio, Maria P., Chenevix‐Trench, Georgia , Bowtell, David D.L. , Traficante, Nadia , Group, AOCS, Hosking, Karen, Piskorz, Anna , Oudenhove, Elke Van , Doherty, J.A. , Rossing, Mary Anne, Duerst, Matthias, Dörk, Thilo , Bogdanova, Natalia , Moysich, Kirsten B. , Odunsi, Kunle , Ness, Roberta B., Lester, Jenny, Pujara, Miguel Angel, Cunningham, Julie M. , Hildebrandt, Michelle, Huff, Chad , Li, Donghui , Wu, Xifeng , Yu, Yao , Levine, Douglas A. , Schildkraut, Joellen M. , Riggan, Marjorie J. , Webb, Penelope M. , Group, OPAL Study, Jakubowska, Anna , Alsop, Jennifer , Harrington, Patricia, Chan, Isaac H Y , Menon, Usha , Pearce, Celeste Leigh, Wu, Anna H. , Fazio, Anna de , Kennedy, Catherine J. , Goode, Ellen L. , Ramus, Susan J. , Gayther, Simon A. , DeFazio, Anna , Cunningham, Julie, Vierkant, Robert, Huff, Chad , Cybulski, Cezary , Pharoah, Paul D P , Dörk, Thilo , Ramus, Susan J , Webb, Penelope M , Menon, Usha , Moysich, Kirsten , Kennedy, Catherine J , Jakubowska, Anna , Bogdanova, Natalia V , Chenevix-Trench, Georgia , Traficante, Nadia , Bowtell, David D , Tyrer, Jonathan P. , Group, AOCS, Brenton, James D. , Goranova, Teodora , Harris, Holly R. , Modugno, Francesmary , Karlan, Beth Y. , Jensen, Allan , Kjær, Susanne K. , Høgdall, Estrid , Campbell, Ian , Lázaro, Conxi , Vierkant, Robert A. , Winham, Stacey J. , Permuth, Jennifer B. , Berchuck, Andrew , Cybulski, Cezary , Gronwald, Jacek , Lubiński, Jan , Pharoah, Paul D.P.

Journal of Medical Genetics | June 16, 2020 | Volume: 58 | Issue: 5 | Pages: 305-313

10.1136/jmedgenet-2019-106739 Get It

Purpose The known epithelial ovarian cancer (EOC) susceptibility genes account for less than 50% of the heritable risk of ovarian cancer suggesting that other susceptibility genes exist. The aim of this study was to evaluate the contribution to ovarian cancer susceptibility of rare deleterious germline variants in a set of candidate genes. Methods We sequenced the coding region of 54 candidate genes in 6385 invasive EOC cases and 6115 controls of broad European ancestry. Genes with an increased frequency of putative deleterious variants in cases versus controls were further examined in an independent set of 14 135 EOC cases and 28 655 controls from the Ovarian Cancer Association Consortium and the UK Biobank. For each gene, we estimated the EOC risks and evaluated associations between germline variant status and clinical characteristics. Results The ORs associated for high-grade serous ovarian cancer were 3.01 for PALB2 (95% CI 1.59 to 5.68; p=0.00068), 1.99 for POLK (95% CI 1.15 to 3.43; p=0.014) and 4.07 for SLX4 (95% CI 1.34 to 12.4; p=0.013). Deleterious mutations in FBXO10 were associated with a reduced risk of disease (OR 0.27, 95% CI 0.07 to 1.00, p=0.049). However, based on the Bayes false discovery probability, only the association for PALB2 in high-grade serous ovarian cancer is likely to represent a true positive. Conclusions We have found strong evidence that carriers of PALB2 deleterious mutations are at increased risk of high-grade serous ovarian cancer. Whether the magnitude of risk is sufficiently high to warrant the inclusion of PALB2 in cancer gene panels for ovarian cancer risk testing is unclear; much larger sample sizes will be needed to provide sufficiently precise estimates for clinical counselling.
Associations between Genetically Predicted Blood Protein Biomarkers and Pancreatic Cancer Risk
Zhu, Jingjing , Shu, Xiao-Ou , Bao, Jiandong , Milne, Roger L. , Du, Mengmeng , Goodman, Phyllis J. , Li, Donghui , Bracci, Paige M. , Gallinger, Steven , Arslan, Alan A. , Scélo, Ghislaine , Visvanathan, Kala , Haiman, Christopher A. , Petersen, Gloria M. , Wu, Lang , Shu, Xiao-Ou , Bao, Jiandong , Milne, Roger L , Malats, Nuria , Duell, Eric J , Li, Donghui , Katzke, Verena , Van Den Eeden, Stephen K , Arslan, Alan A , Canzian, Federico , Yu, Herbert , Klein, Alison P , Visvanathan, Kala , Guo, Xingyi , Liu, Duo, Giles, Graham G. , Wu, Chong , White, Emily , Risch, Harvey A. , Malats, Núria , Duell, Eric J. , Neale, Rachel Ε. , Canzian, Federico , Kooperberg, Charles , Freeman, Laura E. Beane , Marchand, Loı̈c Le , Yu, Kai , Stolzenberg‐Solomon, Rachael Z. , Klein, Alison P. , Cai, Qiuyin , Long, Jirong , Zheng, Wei

Cancer Epidemiology, Biomarkers & Prevention | May 21, 2020 | Volume: 29 | Issue: 7 | Pages: 1501-1508

10.1158/1055-9965.epi-20-0091 Get It

Abstract Background: 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 < 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.
A Transcriptome-Wide Association Study Identifies Novel Candidate Susceptibility Genes for Pancreatic Cancer
Zhong, Jun, Jermusyk, Ashley , Wu, Lang , Hoskins, Jason W. , Collins, Irene , Mocci, Evelina , Song, Lei , Chung, Charles C., Xiao, Wenming , Andreotti, Gabriella , Arslan, Alan A. , Babić, Ana , Berndt, Sonja, Borgida, Ayelet , Bracci, Paige M. , Brennan, Paul , Bueno‐de‐Mesquita, Bas , Buring, Julie E. , Childs, Erica J., Du, Mengmeng , Fuchs, Charles S. , Gallinger, Steven , Gaziano, J. Michael, Giovannucci, Edward L. , Goodman, Gary E. , Goodman, Phyllis J. , Haiman, Christopher, Hartge, Patricia, Hasan, Manal , Helzlsouer, Kathy J., Holly, Elizabeth A., Klein, Eric A. , Kogevinas, Manolis, Kurtz, Robert J., Ng, Kimmie , Obazee, Ofure , Oberg, Ann L. , Patel, Alpa V. , Peters, Ulrike , Porta, Miquel , Rothman, Nathaniel , Scélo, Ghislaine , Sesso, Howard D. , Sieri, Sabina , Tjønneland, Anne , Thornquist, Mark, Trichopoulou, Antonia , Visvanathan, Kala , Wactawski‐Wende, Jean , Wentzensen, Nicolas , Yuan, Chen , Zeleniuch‐Jacquotte, Anne , Hoover, Robert N. , Brown, Kevin M. , Jacobs, Eric J. , Li, Donghui , Yu, Kai , Wolpin, Brian M. , Chatterjee, Nilanjan , Shi, Jianxin , Petersen, Gloria M. , Zhong, Jun , Arslan, Alan A , Tjønneland, Anne , Wactawski-Wende, Jean , Visvanathan, Kala , Klein, Eric A , Porta, Miquel , Zeleniuch-Jacquotte, Anne , Zhong, Jun , Yuan, Chen , Hoskins, Jason W , Zhang, Mingfeng , Zhang, Tongwu , Albanes, Demetrius , Bamlet, William R. , Freeman, Laura E. Beane , Brais, Lauren K , Canzian, Federico , Cotterchio, Michelle , Duell, Eric J. , Giles, Graham G. , Goggins, Michael , Marchand, Loı̈c Le , Malats, Núria , Männistö, Satu , Milne, Roger L. , Neale, Rachel Ε. , Orlow, Irene , Rothman, Nathaniel , Severi, Gianluca , Silverman, Debra T. , Sund, Malin , Tobias, Geoffrey S. , Van Den Eeden, Stephen K , White, Emily , Yu, Kai , Kooperberg, Charles , Risch, Harvey A. , Shu, Xiao‐Ou , Chanock, Stephen Jacob , Stolzenberg‐Solomon, Rachael Z. , Klein, Alison P. , Smith, Jill Palmer , Kraft, Peter , Zheng, Wei , Ámundadóttir, Laufey T.

JNCI: Journal of the National Cancer Institute | December 31, 2019 | Volume: 112 | Issue: 10 | Pages: 1003-1012

10.1093/jnci/djz246 Get It

Abstract Background Although 20 pancreatic cancer susceptibility loci have been identified through genome-wide association studies in individuals of European ancestry, much of its heritability remains unexplained and the genes responsible largely unknown. Methods To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74–421 samples). Results We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate < .05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction. Conclusions By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.
Analysis of Heritability and Genetic Architecture of Pancreatic Cancer: A PanC4 Study
Chen, Fei , Childs, Erica J., Mocci, Evelina , Bracci, Paige M. , Gallinger, Steven , Li, Donghui , Scélo, Ghislaine , Borges, Michael , Brennan, Paul , Chaffee, Kari G. , Duggal, Priya , Hassan, Manal J., Holly, Elizabeth A. , Hung, Rayjean J., Kurtz, Robert C. , Oberg, Ann L. , Petersen, Gloria M. , Rabe, Kari G. , Hung, Rayjean J. , Oberg, Ann L , Orlow, Irene , Klein, Alison P , Li, Donghui , Hung, Rayjean J , Chen, Fei , Neale, Rachel Ε. , Olson, Sara H. , Bamlet, William R. , Blackford, Amanda , Goggins, Michael , Orlow, Irene , Yu, Kai , Risch, Harvey A. , Klein, Alison P. , Duggal, Priya

Cancer Epidemiology, Biomarkers & Prevention | April 23, 2019 | Volume: 28 | Issue: 7 | Pages: 1238-1245

10.1158/1055-9965.epi-18-1235 Get It

Abstract Background: Pancreatic cancer is the fourth-leading cause of cancer death in both men and women in the United States. The currently identified common susceptibility loci account for a small fraction of estimated heritability. We sought to estimate overall heritability of pancreatic cancer and partition the heritability by variant frequencies and functional annotations. Methods: Analysis using the genome-based restricted maximum likelihood method (GREML) was conducted on Pancreatic Cancer Case-Control Consortium (PanC4) genome-wide association study (GWAS) data from 3,568 pancreatic cancer cases and 3,363 controls of European Ancestry. Results: Applying linkage disequilibrium- and minor allele frequency-stratified GREML (GREML-LDMS) method to imputed GWAS data, we estimated the overall heritability of pancreatic cancer to be 21.2% (SE = 4.8%). Across the functional groups (intronic, intergenic, coding, and regulatory variants), intronic variants account for most of the estimated heritability (12.4%). Previously identified GWAS loci explained 4.1% of the total phenotypic variation of pancreatic cancer. Mutations in hereditary pancreatic cancer susceptibility genes are present in 4% to 10% of patients with pancreatic cancer, yet our GREML-LDMS results suggested these regions explain only 0.4% of total phenotypic variance for pancreatic cancer. Conclusions: Although higher than previous studies, our estimated 21.2% overall heritability may still be downwardly biased due to the inherent limitation that the contribution of rare variants in genes with a substantive overall impact on disease are not captured when applying these commonly used methods to imputed GWAS data. Impact: Our work demonstrated the importance of rare and common variants in pancreatic cancer risk.
Abstract 242: Large pathway and gene set analysis of GWAS data identifies novel associations for pancreatic cancer
Zhang, Han , Hyland, Paula L. , Yang, Qi , Childs, Erica J., Hartge, Patricia, Hoover, Robert N. , Li, Donghui , Jacobs, Eric J. , Petersen, Gloria M. , Wolpin, Brian M. , Walsh, Naomi , Mocci, Evelina , Zhang, Mingfeng , Wang, Zhaoming , Chanock, Stephen Jacob , Kraft, Peter , Risch, Harvey A. , Ámundadóttir, Laufey T. , Yu, Herbert , Klein, Alison P. , Stolzenberg‐Solomon, Rachael Z.

Cancer Research | August 17, 2018 | Volume: 78 | Issue: 13_Supplement | Pages: 242-242

10.1158/1538-7445.am2018-242 Get It

Abstract Objective Genome-wide association studies (GWAS) identify associations of individual SNPs with cancer risk but usually only explain a fraction of the inherited variability. Pathway analysis of genetic variants has been shown for many disorders to be a powerful tool in discovering novel networks of susceptibility genes. Design We have conducted a large agnostic pathway-based meta-analysis of GWAS data using the summary-based adaptive rank truncated product (sARTP) method to identify novel gene sets and pathways associated with pancreatic ductal adenocarcinoma (PDA) in 9,040 cases and 12,495 controls. We performed expression quantitative trait loci (eQTL) analysis and functional annotation of the top SNPs in genes identified in PDA-associated gene sets and pathways. Results We identified 14 gene sets and pathways associated with PDA at FDR < 0.05. Five of the strongest signals (P-value ≤ 1.3x10-5 Bonferroni corrected) were in genes from KEGG maturity onset diabetes of the young, Reactome regulation of beta cell development, Biocarta role of epidermal growth factor (EGF) receptor transactivation by G-protein-coupled receptors in cardiac hypertrophy pathway, Nikolsky breast cancer chr17q11-q21 amplicon gene set, and Pujana ATM Pearson correlation coefficient (PCC) network gene set. We identified and validated rs876493 and three correlated SNPs (PGAP3) and rs3124737 (CASP7) as eQTLs in two normal derived pancreas tissue datasets. Conclusion Our agnostic gene set and pathway analysis integrated with functional annotation and eQTL analysis provides novel insight into genes and pathways that may be biologically relevant for risk of PDA. Citation Format: Naomi Walsh, Han Zhang, Paula L. Hyland, Qi Yang, Evelina Mocci, Mingfeng Zhang, Erica J. Childs, Zhaoming Wang, Stephen Chanock, Patricia Hartge, Robert Hoover, Peter Kraft, Donghui Li, Eric J. Jacobs, Gloria M. Petersen, Brian M. Wolpin, Harvey A. Risch, Laufey T. Amundadottir, Kai Yu, Alison P. Klein, Rachael Z. Stolzenberg-Solomon. Large pathway and gene set analysis of GWAS data identifies novel associations for pancreatic cancer [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 242.
Agnostic Pathway/Gene Set Analysis of Genome-Wide Association Data Identifies Associations for Pancreatic Cancer
Walsh, Naomi , Hyland, Paula L. , Yang, Qi , Childs, Erica J., Collins, Irene , Wang, Zhaoming , Arslan, Alan A. , Bracci, Paige M. , Brennan, Paul , Canzian, Federico , Gallinger, Steven , Goodman, Gary E. , Goodman, Phyllis J. , Hung, Rayjean J, Kurtz, Robert C. , Scélo, Ghislaine , Shu, Xiao Ou , Visvanathan, Kala , consortia, PanScan and PanC4, Andreotti, Gabriella , Babić, Ana , Berndt, Sonja I. , Borgida, Ayelet , Bueno‐de‐Mesquita, Bas , Buring, Julie E. , Chaffee, Kari G. , Foretová, Lenka , Fuchs, Charles S. , Gaziano, J. Michael , Giovannucci, Edward, Hackert, Thilo , Haiman, Christopher A. , Hartge, Patricia, Hasan, Manal , Helzlsouer, Kathy J., Herman, Joseph M. , Holly, Elizabeth A., Hoover, Robert N. , Hung, Rayjean J, Janout, Vladimí­r , Klein, Eric A. , Laheru, Daniel A. , Lee, I‐Min , Oberg, Ann L. , Patel, Alpa V. , Peters, Ulrike , Porta, Miquel , Real, Francisco X. , Rothman, Nathaniel , Sesso, Howard D. , Strobel, Oliver , Thornquist, Mark, Wactawski‐Wende, Jean , Wareham, Nick, Weiderpass, Elisabete , Wentzensen, Nicolas , Wheeler, William, Zeleniuch‐Jacquotte, Anne , Kraft, Peter , Li, Donghui , Jacobs, Eric J. , Petersen, Gloria M. , Wolpin, Brian M. , Rabe, Kari G. , Hung, Rayjean J. , Cleary, Sean, Weiderpass, Elisabete , Arslan, Alan A , Canzian, Federico , Hung, Rayjean J , Wactawski-Wende, Jean , Wang, Zhaoming , Visvanathan, Kala , Klein, Eric A , Strobel, Oliver , Kraft, Peter , Porta, Miquel , Real, Francisco X , Zeleniuch-Jacquotte, Anne , Zhang, Han , Mocci, Evelina , Zhang, Mingfeng , Freeman, Laura E. Beane , Duell, Eric J. , Giles, Graham G. , Goggins, Michael , Hung, Rayjean J, Kooperberg, Charles , Malats, Núria , Marchand, Loı̈c Le , Neale, Rachel Ε. , Olson, Sara H. , Van Den Eeden, Stephen K , White, Emily , Zheng, Wei , consortia, PanScan and PanC4, Albanes, Demetrius , Bamlet, William R. , Boutron‐Ruault, Marie‐Christine , Brais, Lauren K , Chanock, Stephen Jacob , Cleary, Sean P. , Cotterchio, Michelle , Holcátová, Ivana , Hung, Rayjean J, Lu, Lingeng , Männistö, Satu , Milne, Roger L. , Orlow, Irene , Rothman, Nathaniel , Severi, Gianluca , Silverman, Debra T. , Sund, Malin , Tobias, Geoffrey S. , Wareham, Nick, Yu, Kai , Risch, Harvey A. , Ámundadóttir, Laufey T. , Yu, Kai , Klein, Alison P. , Stolzenberg‐Solomon, Rachael Z.

JNCI: Journal of the National Cancer Institute | August 15, 2018 | Volume: 111 | Issue: 6 | Pages: 557-567

10.1093/jnci/djy155 Get It

CDKN2AGermline Rare Coding Variants and Risk of Pancreatic Cancer in Minority Populations
Wieben, Eric D. , Chaffee, Kari G. , Antwi, Samuel O. , Olopade, Olufunmilayo I. , Li, Donghui , Highsmith, W. Edward, Colón‐Otero, Gerardo , Khanna, Lauren , Frucht, Harold, Blot, William J. , Wu, Lang , Almada, Luciana L. , Fernández-Zapico, Martín E. , Sicotte, Hugues , Pedersen, Katrina S. , Petersen, Gloria M. , Rabe, Kari G. , McWilliams, Robert R. , Raskin, Leon , Li, Donghui , Permuth, Jennifer B , Sicotte, Hugues , Antwi, Samuel O , Olopade, Olufunmilayo I , Pedersen, Katrina , Permuth, Jennifer B. , Olson, Janet E. , Genkinger, Jeanine M. , Zheng, Wei

Cancer Epidemiology, Biomarkers & Prevention | July 23, 2018 | Volume: 27 | Issue: 11 | Pages: 1364-1370

10.1158/1055-9965.epi-17-1065 Get It

AbstractBackground: Pathogenic germline mutations in the CDKN2A tumor suppressor gene are rare and associated with highly penetrant familial melanoma and pancreatic cancer in non-Hispanic whites (NHW). To date, the prevalence and impact of CDKN2A rare coding variants (RCV) in racial minority groups remain poorly characterized. We examined the role of CDKN2A RCVs on the risk of pancreatic cancer among minority subjects.Methods: We sequenced CDKN2A in 220 African American (AA) pancreatic cancer cases, 900 noncancer AA controls, and 183 Nigerian controls. RCV frequencies were determined for each group and compared with that of 1,537 NHW patients with pancreatic cancer. Odds ratios (OR) and 95% confidence intervals (CI) were calculated for both a case–case comparison of RCV frequencies in AAs versus NHWs, and case–control comparison between AA cases versus noncancer AA controls plus Nigerian controls. Smaller sets of Hispanic and Native American cases and controls also were sequenced.Results: One novel missense RCV and one novel frameshift RCV were found among AA patients: 400G>A and 258_278del. RCV carrier status was associated with increased risk of pancreatic cancer among AA cases (11/220; OR, 3.3; 95% CI, 1.5–7.1; P = 0.004) compared with AA and Nigerian controls (17/1,083). Further, AA cases had higher frequency of RCVs: 5.0% (OR, 13.4; 95% CI, 4.9–36.7; P < 0.001) compared with NHW cases (0.4%).Conclusions: CDKN2A RCVs are more common in AA than in NHW patients with pancreatic cancer and associated with moderately increased pancreatic cancer risk among AAs.Impact: RCVs in CDKN2A are frequent in AAs and are associated with risk for pancreatic cancer. Cancer Epidemiol Biomarkers Prev; 27(11); 1364–70. ©2018 AACR.
Abstract LB-160: Genetic variations in the AGEs/AGER pathway and risk of pancreatic cancer
Royse, Kathryn E. , Tang, Hongwei, Li, Donghui , Tinker, Lesley F. , Petersen, Gloria M. , Richardson, Peter , Sangi-Haghapeykar, Haleh, El‐Serag, Hashem B. , Jia, Guochong , Liang, Chen , Klein, Alison P. , White, Donna L. , Jiao, Li

Cancer Research | July 31, 2017 | Volume: 77 | Issue: 13_Supplement | Pages: LB-160-LB-160

10.1158/1538-7445.am2017-lb-160 Get It

Abstract Background: Chronic inflammation is implicated in pancreatic cancer carcinogenesis. Advanced glycation end-products (AGEs), which are rich in cooked red meat and cigarette smoke, can perpetuate inflammation by binding to the receptor for advanced glycation end products (AGER, also known as RAGE). We hypothesized that genetic variation of the AGEs/AGER pathway affects pancreatic cancer risk by modulating chronic inflammation. Methods: We conducted a two-stage case-control study to examine the association between 96 single nucleotide polymorphisms (SNPs) in 21 genes (GLO1, MSR1, PINK1, KIF17, AGPAT1, AKR1B1, DDOST, CD36, SCARB1, AGER, APP, HMGB1, S100A8, S100B, S100P, S100A12, MMP9, ADAM10, PPARG, NOTCH4, and PDGF) of the AGEs/AGER pathway and risk of pancreatic cancer. The discovery study was conducted in 672 pancreatic cancer cases and 1361 controls ascertained from the Women’s Health Initiative (WHI) Study matched on age, race/ethnicity and study arm. The validation study was conducted in a PANC4 pooled hospital-based case-control study of 1,034 women cases and 989 women controls. A pooled analysis of 1706 cases and 2350 controls was also performed. SNP data were obtained or imputed from the previously performed GWASs. Pancreatic cancer risk was calculated as odds ratios (ORs) and 95% confidence intervals (Cis) using logistic regression models adjusting for age, race/ethnicity, body mass index (BMI), type 2 diabetes, and smoking using an additive genetic model. The potential interaction between individual SNP and red meat intake and cigarette smoking was examined. A false discovery rate (FDR) adjusted q value < 0.20 was considered statistically significant in the pooled analyses. We also conducted logistic-Kernel machine (LKM) test to examine the association between sets of SNP and risk of pancreatic cancer in the pooled dataset. Results: We identified 11 SNPs with raw P values < 0.10 in the discovery stage in the WHI study. However, none of the SNPs was validated in the validation and pooled dataset. The LKM test showed that sets of SNPs in CD36 (P = 9.3E-10), GLO1(P =2.0E-7), and DDOST (P = 2.5E-4) were significantly associated with pancreatic cancer risk. We found an interaction effect between the GLO1 SNP rs6932648 and smoking status (never versus ever) in the WHI study (P for interaction = 0.01) and the pooled dataset (P for interaction = 0.049). In the pooled dataset, the variant T allele of rs6932648 (MAF = 0.12) was associated with increased risk of pancreatic cancer among ever smokers (additive OR = 1.26, 95% CI: 1.02-1.55), but not among never smokers (additive OR = 0.94, 95% CI: 0.78-1.14), compared with the C allele. Summary and Conclusion: We did not observe significant association between any of 96 single SNP and pancreatic cancer risk. However, we found combined set of SNPs in the GLO1, DDOST, and CD36 genes were associated with risk of pancreatic cancer. GLO SNP rs6932648 may modify the association between smoking and risk of pancreatic cancer. GLO1, DDOST, and CD36 are involved in detoxification or clearance of AGEs compounds. Further investigation of AGEs and receptors systems in pancreatic cancer is warranted. Citation Format: Guochong Jia, Kathryn Royse, Hongwei Tang, Donghui Li, Liang Chen, Lesley Tinker, Gloria Petersen, Alison Klein, Peter Richardson, Donna White, Haleh Sangi-Haghapeykar, Hashem B. El-Serag, Li Jiao. Genetic variations in the AGEs/AGER pathway and risk of pancreatic cancer [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 LB-160. doi:10.1158/1538-7445.AM2017-LB-160