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1. Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population

Author

Jianxin Shi, Kouya Shiraishi, Jiyeon Choi, Keitaro Matsuo, Tzu-Yu Chen, Juncheng Dai, Rayjean J. Hung, Kexin Chen, Xiao-Ou Shu, Young Tae Kim, Maria Teresa Landi, Dongxin Lin, Wei Zheng, Zhihua Yin, Baosen Zhou, Bao Song, Jiucun Wang, Wei Jie Seow, Lei Song, I-Shou Chang, Wei Hu, Li-Hsin Chien, Qiuyin Cai, Yun-Chul Hong, Hee Nam Kim, Yi-Long Wu, Maria Pik Wong, Brian Douglas Richardson, Karen M. Funderburk, Shilan Li, Tongwu Zhang, Charles Breeze, Zhaoming Wang, Batel Blechter, Bryan A. Bassig, Jin Hee Kim, Demetrius Albanes, Jason Y. Y. Wong, Min-Ho Shin, Lap Ping Chung, Yang Yang, She-Juan An, Hong Zheng, Yasushi Yatabe, Xu-Chao Zhang, Young-Chul Kim, Neil E. Caporaso, Jiang Chang, James Chung Man Ho, Michiaki Kubo, Yataro Daigo, Minsun Song, Yukihide Momozawa, Yoichiro Kamatani, Masashi Kobayashi, Kenichi Okubo, Takayuki Honda, Dean H. Hosgood, Hideo Kunitoh, Harsh Patel, Shun-ichi Watanabe, Yohei Miyagi, Haruhiko Nakayama, Shingo Matsumoto, Hidehito Horinouchi, Masahiro Tsuboi, Ryuji Hamamoto, Koichi Goto, Yuichiro Ohe, Atsushi Takahashi, Akiteru Goto, Yoshihiro Minamiya, Megumi Hara, Yuichiro Nishida, Kenji Takeuchi, Kenji Wakai, Koichi Matsuda, Yoshinori Murakami, Kimihiro Shimizu, Hiroyuki Suzuki, Motonobu Saito, Yoichi Ohtaki, Kazumi Tanaka, Tangchun Wu, Fusheng Wei, Hongji Dai, Mitchell J. Machiela, Jian Su, Yeul Hong Kim, In-Jae Oh, Victor Ho Fun Lee, Gee-Chen Chang, Ying-Huang Tsai, Kuan-Yu Chen, Ming-Shyan Huang, Wu-Chou Su, Yuh-Min Chen, Adeline Seow, Jae Yong Park, Sun-Seog Kweon, Kun-Chieh Chen, Yu-Tang Gao, Biyun Qian, Chen Wu, Daru Lu, Jianjun Liu, Ann G. Schwartz, Richard Houlston, Margaret R. Spitz, Ivan P. Gorlov, Xifeng Wu, Ping Yang, Stephen Lam, Adonina Tardon, Chu Chen, Stig E. Bojesen, Mattias Johansson, Angela Risch, Heike Bickeböller, Bu-Tian Ji, H-Erich Wichmann, David C. Christiani, Gadi Rennert, Susanne Arnold, Paul Brennan, James McKay, John K. Field, Sanjay S. Shete, Loic Le Marchand, Geoffrey Liu, Angeline Andrew, Lambertus A. Kiemeney, Shan Zienolddiny-Narui, Kjell Grankvist, Mikael Johansson, Angela Cox, Fiona Taylor, Jian-Min Yuan, Philip Lazarus, Matthew B. Schabath, Melinda C. Aldrich, Hyo-Sung Jeon, Shih Sheng Jiang, Jae Sook Sung, Chung-Hsing Chen, Chin-Fu Hsiao, Yoo Jin Jung, Huan Guo, Zhibin Hu, Laurie Burdett, Meredith Yeager, Amy Hutchinson, Belynda Hicks, Jia Liu, Bin Zhu, Sonja I. Berndt, Wei Wu, Junwen Wang, Yuqing Li, Jin Eun Choi, Kyong Hwa Park, Sook Whan Sung, Li Liu, Chang Hyun Kang, Wen-Chang Wang, Jun Xu, Peng Guan, Wen Tan, Chong-Jen Yu, Gong Yang, Alan Dart Loon Sihoe, Ying Chen, Yi Young Choi, Jun Suk Kim, Ho-Il Yoon, In Kyu Park, Ping Xu, Qincheng He, Chih-Liang Wang, Hsiao-Han Hung, Roel C. H. Vermeulen, Iona Cheng, Junjie Wu, Wei-Yen Lim, Fang-Yu Tsai, John K. C. Chan, Jihua Li, Hongyan Chen, Hsien-Chih Lin, Li Jin, Jie Liu, Norie Sawada, Taiki Yamaji, Kathleen Wyatt, Shengchao A. Li, Hongxia Ma, Meng Zhu, Zhehai Wang, Sensen Cheng, Xuelian Li, Yangwu Ren, Ann Chao, Motoki Iwasaki, Junjie Zhu, Gening Jiang, Ke Fei, Guoping Wu, Chih-Yi Chen, Chien-Jen Chen, Pan-Chyr Yang, Jinming Yu, Victoria L. Stevens, Joseph F. Fraumeni, Nilanjan Chatterjee, Olga Y. Gorlova, Chao Agnes Hsiung, Christopher I. Amos, Hongbing Shen, Stephen J. Chanock, Nathaniel Rothman, Takashi Kohno, and Qing Lan

Subjects
Science
Abstract

Abstract Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (Pinteraction = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications.

Published
2023
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2. A cross-sectional study of inflammatory markers as determinants of circulating kynurenines in the Lung Cancer Cohort Consortium

Author

Øivind Midttun, Arve Ulvik, Klaus Meyer, Hana Zahed, Graham G. Giles, Jonas Manjer, Malte Sandsveden, Arnulf Langhammer, Elin Pettersen Sørgjerd, Annelie F. Behndig, Mikael Johansson, Neal D. Freedman, Wen-Yi Huang, Chu Chen, Ross Prentice, Victoria L. Stevens, Ying Wang, Loïc Le Marchand, Stephanie J. Weinstein, Qiuyin Cai, Alan A. Arslan, Yu Chen, Xiao-Ou Shu, Wei Zheng, Jian-Min Yuan, Woon-Puay Koh, Kala Visvanathan, Howard D. Sesso, Xuehong Zhang, J. Michael Gaziano, Anouar Fanidi, Hilary A. Robbins, Paul Brennan, Mattias Johansson, and Per M. Ueland

Subjects
Medicine, Science
Abstract

Abstract Circulating concentrations of metabolites (collectively called kynurenines) in the kynurenine pathway of tryptophan metabolism increase during inflammation, particularly in response to interferon-gamma (IFN-γ). Neopterin and the kynurenine/tryptophan ratio (KTR) are IFN-γ induced inflammatory markers, and together with C-reactive protein (CRP) and kynurenines they are associated with various diseases, but comprehensive data on the strength of associations of inflammatory markers with circulating concentrations of kynurenines are lacking. We measured circulating concentrations of neopterin, CRP, tryptophan and seven kynurenines in 5314 controls from 20 cohorts in the Lung Cancer Cohort Consortium (LC3). The associations of neopterin, KTR and CRP with kynurenines were investigated using regression models. In mixed models, one standard deviation (SD) higher KTR was associated with a 0.46 SD higher quinolinic acid (QA), and 0.31 SD higher 3-hydroxykynurenine (HK). One SD higher neopterin was associated with 0.48, 0.44, 0.36 and 0.28 SD higher KTR, QA, kynurenine and HK, respectively. KTR and neopterin respectively explained 24.1% and 16.7% of the variation in QA, and 11.4% and 7.5% of HK. CRP was only weakly associated with kynurenines in regression models. In summary, QA was the metabolite that was most strongly associated with the inflammatory markers. In general, the inflammatory markers were most strongly related to metabolites located along the tryptophan–NAD axis, which may support suggestions of increased production of NAD from tryptophan during inflammation.

Published
2023
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3. A prospective case–cohort analysis of plasma metabolites and breast cancer risk

Author

Victoria L. Stevens, Brian D. Carter, Eric J. Jacobs, Marjorie L. McCullough, Lauren R. Teras, and Ying Wang

Subjects
Breast cancer, Metabolomics, Prospective study, Metabolites, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Breast cancer incidence rates have not declined despite an improvement in risk prediction and the identification of modifiable risk factors, suggesting the need to identify novel risk factors and etiological pathways involved in this cancer. Metabolomics has emerged as a promising tool to find circulating metabolites associated with breast cancer risk. Methods Untargeted metabolomic analysis was done on prediagnostic plasma samples from a case–cohort study of 1695 incident breast cancer cases and a 1983 women subcohort drawn from Cancer Prevention Study 3. The associations of 868 named metabolites (per one standard deviation increase) with breast cancer were determined using Prentice-weighted Cox proportional hazards regression modeling. Results A total of 11 metabolites were associated with breast cancer at false discovery rate (FDR)

Published
2023
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4. Evaluation of pre-diagnostic blood protein measurements for predicting survival after lung cancer diagnosisResearch in context

Author

Xiaoshuang Feng, David C. Muller, Hana Zahed, Karine Alcala, Florence Guida, Karl Smith-Byrne, Jian-Min Yuan, Woon-Puay Koh, Renwei Wang, Roger L. Milne, Julie K. Bassett, Arnulf Langhammer, Kristian Hveem, Victoria L. Stevens, Ying Wang, Mikael Johansson, Anne Tjønneland, Rosario Tumino, Mahdi Sheikh, Mattias Johansson, and Hilary A. Robbins

Subjects
Lung cancer, Lung cancer survival, Protein biomarkers, Lung cancer prognosis, Medicine, Medicine (General), R5-920
Abstract

Summary: Background: To evaluate whether circulating proteins are associated with survival after lung cancer diagnosis, and whether they can improve prediction of prognosis. Methods: We measured up to 1159 proteins in blood samples from 708 participants in 6 cohorts. Samples were collected within 3 years prior to lung cancer diagnosis. We used Cox proportional hazards models to identify proteins associated with overall mortality after lung cancer diagnosis. To evaluate model performance, we used a round-robin approach in which models were fit in 5 cohorts and evaluated in the 6th cohort. Specifically, we fit a model including 5 proteins and clinical parameters and compared its performance with clinical parameters only. Findings: There were 86 proteins nominally associated with mortality (p

Published
2023
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5. Epidemiology of 40 blood biomarkers of one-carbon metabolism, vitamin status, inflammation, and renal and endothelial function among cancer-free older adults

Author

Hana Zahed, Mattias Johansson, Per M. Ueland, Øivind Midttun, Roger L. Milne, Graham G. Giles, Jonas Manjer, Malte Sandsveden, Arnulf Langhammer, Elin Pettersen Sørgjerd, Kjell Grankvist, Mikael Johansson, Neal D. Freedman, Wen-Yi Huang, Chu Chen, Ross Prentice, Victoria L. Stevens, Ying Wang, Loic Le Marchand, Lynne R. Wilkens, Stephanie J. Weinstein, Demetrius Albanes, Qiuyin Cai, William J. Blot, Alan A. Arslan, Anne Zeleniuch-Jacquotte, Xiao-Ou Shu, Wei Zheng, Jian-Min Yuan, Woon-Puay Koh, Kala Visvanathan, Howard D. Sesso, Xuehong Zhang, J. Michael Gaziano, Anouar Fanidi, David Muller, Paul Brennan, Florence Guida, and Hilary A. Robbins

Subjects
Medicine, Science
Abstract

Abstract Imbalances of blood biomarkers are associated with disease, and biomarkers may also vary non-pathologically across population groups. We described variation in concentrations of biomarkers of one-carbon metabolism, vitamin status, inflammation including tryptophan metabolism, and endothelial and renal function among cancer-free older adults. We analyzed 5167 cancer-free controls aged 40–80 years from 20 cohorts in the Lung Cancer Cohort Consortium (LC3). Centralized biochemical analyses of 40 biomarkers in plasma or serum were performed. We fit multivariable linear mixed effects models to quantify variation in standardized biomarker log-concentrations across four factors: age, sex, smoking status, and body mass index (BMI). Differences in most biomarkers across most factors were small, with 93% (186/200) of analyses showing an estimated difference lower than 0.25 standard-deviations, although most were statistically significant due to large sample size. The largest difference was for creatinine by sex, which was − 0.91 standard-deviations lower in women than men (95%CI − 0.98; − 0.84). The largest difference by age was for total cysteine (0.40 standard-deviation increase per 10-year increase, 95%CI 0.36; 0.43), and by BMI was for C-reactive protein (0.38 standard-deviation increase per 5-kg/m2 increase, 95%CI 0.34; 0.41). For 31 of 40 markers, the mean difference between current and never smokers was larger than between former and never smokers. A statistically significant (p

Published
2021
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6. A meta-analysis of genome-wide association studies of multiple myeloma among men and women of African ancestry

Author

Zhaohui Du, Niels Weinhold, Gregory Chi Song, Kristin A. Rand, David J. Van Den Berg, Amie E. Hwang, Xin Sheng, Victor Hom, Sikander Ailawadhi, Ajay K. Nooka, Seema Singhal, Karen Pawlish, Edward S. Peters, Cathryn Bock, Ann Mohrbacher, Alexander Stram, Sonja I. Berndt, William J. Blot, Graham Casey, Victoria L. Stevens, Rick Kittles, Phyllis J. Goodman, W. Ryan Diver, Anselm Hennis, Barbara Nemesure, Eric A. Klein, Benjamin A. Rybicki, Janet L. Stanford, John S. Witte, Lisa Signorello, Esther M. John, Leslie Bernstein, Antoinette M. Stroup, Owen W. Stephens, Maurizio Zangari, Frits Van Rhee, Andrew Olshan, Wei Zheng, Jennifer J. Hu, Regina Ziegler, Sarah J. Nyante, Sue Ann Ingles, Michael F. Press, John David Carpten, Stephen J. Chanock, Jayesh Mehta, Graham A. Colditz, Jeffrey Wolf, Thomas G. Martin, Michael Tomasson, Mark A. Fiala, Howard Terebelo, Nalini Janakiraman, Laurence Kolonel, Kenneth C. Anderson, Loic Le Marchand, Daniel Auclair, Brian C.-H. Chiu, Elad Ziv, Daniel Stram, Ravi Vij, Leon Bernal-Mizrachi, Gareth J. Morgan, Jeffrey A. Zonder, Carol Ann Huff, Sagar Lonial, Robert Z. Orlowski, David V. Conti, Christopher A. Haiman, and Wendy Cozen

Subjects
Specialties of internal medicine, RC581-951
Abstract

Abstract: Persons of African ancestry (AA) have a twofold higher risk for multiple myeloma (MM) compared with persons of European ancestry (EA). Genome-wide association studies (GWASs) support a genetic contribution to MM etiology in individuals of EA. Little is known about genetic risk factors for MM in individuals of AA. We performed a meta-analysis of 2 GWASs of MM in 1813 cases and 8871 controls and conducted an admixture mapping scan to identify risk alleles. We fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. In GWAS meta-analysis, we identified 2 suggestive novel loci located at 9p24.3 and 9p13.1 at P < 1 × 10−6; however, no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. Of the 23 known EA risk variants, 20 showed directional consistency, and 9 replicated at P < .05 in AA individuals. In 8 regions, we identified markers that better capture MM risk in persons with AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95% confidence interval, 1.56-2.11) increased MM risk compared with those with average risk (25%-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P = 5.1 × 10−12). Our study shows that common genetic variation contributes to MM risk in individuals with AA.

Published
2020
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8. Publisher Correction: Shared heritability and functional enrichment across six solid cancers

Author

Xia Jiang, Hilary K. Finucane, Fredrick R. Schumacher, Stephanie L. Schmit, Jonathan P. Tyrer, Younghun Han, Kyriaki Michailidou, Corina Lesseur, Karoline B. Kuchenbaecker, Joe Dennis, David V. Conti, Graham Casey, Mia M. Gaudet, Jeroen R. Huyghe, Demetrius Albanes, Melinda C. Aldrich, Angeline S. Andrew, Irene L. Andrulis, Hoda Anton-Culver, Antonis C. Antoniou, Natalia N. Antonenkova, Susanne M. Arnold, Kristan J. Aronson, Banu K. Arun, Elisa V. Bandera, Rosa B. Barkardottir, Daniel R. Barnes, Jyotsna Batra, Matthias W. Beckmann, Javier Benitez, Sara Benlloch, Andrew Berchuck, Sonja I. Berndt, Heike Bickeböller, Stephanie A. Bien, Carl Blomqvist, Stefania Boccia, Natalia V. Bogdanova, Stig E. Bojesen, Manjeet K. Bolla, Hiltrud Brauch, Hermann Brenner, James D. Brenton, Mark N. Brook, Joan Brunet, Hans Brunnström, Daniel D. Buchanan, Barbara Burwinkel, Ralf Butzow, Gabriella Cadoni, Trinidad Caldés, Maria A. Caligo, Ian Campbell, Peter T. Campbell, Géraldine Cancel-Tassin, Lisa Cannon-Albright, Daniele Campa, Neil Caporaso, André L. Carvalho, Andrew T. Chan, Jenny Chang-Claude, Stephen J. Chanock, Chu Chen, David C. Christiani, Kathleen B. M. Claes, Frank Claessens, Judith Clements, J. Margriet Collée, Marcia Cruz Correa, Fergus J. Couch, Angela Cox, Julie M. Cunningham, Cezary Cybulski, Kamila Czene, Mary B. Daly, Anna deFazio, Peter Devilee, Orland Diez, Manuela Gago-Dominguez, Jenny L. Donovan, Thilo Dörk, Eric J. Duell, Alison M. Dunning, Miriam Dwek, Diana M. Eccles, Christopher K. Edlund, Digna R. Velez Edwards, Carolina Ellberg, D. Gareth Evans, Peter A. Fasching, Robert L. Ferris, Triantafillos Liloglou, Jane C. Figueiredo, Olivia Fletcher, Renée T. Fortner, Florentia Fostira, Silvia Franceschi, Eitan Friedman, Steven J. Gallinger, Patricia A. Ganz, Judy Garber, José A. García-Sáenz, Simon A. Gayther, Graham G. Giles, Andrew K. Godwin, Mark S. Goldberg, David E. Goldgar, Ellen L. Goode, Marc T. Goodman, Gary Goodman, Kjell Grankvist, Mark H. Greene, Henrik Gronberg, Jacek Gronwald, Pascal Guénel, Niclas Håkansson, Per Hall, Ute Hamann, Freddie C. Hamdy, Robert J. Hamilton, Jochen Hampe, Aage Haugen, Florian Heitz, Rolando Herrero, Peter Hillemanns, Michael Hoffmeister, Estrid Høgdall, Yun-Chul Hong, John L. Hopper, Richard Houlston, Peter J. Hulick, David J. Hunter, David G. Huntsman, Gregory Idos, Evgeny N. Imyanitov, Sue Ann Ingles, Claudine Isaacs, Anna Jakubowska, Paul James, Mark A. Jenkins, Mattias Johansson, Mikael Johansson, Esther M. John, Amit D. Joshi, Radka Kaneva, Beth Y. Karlan, Linda E. Kelemen, Tabea Kühl, Kay-Tee Khaw, Elza Khusnutdinova, Adam S. Kibel, Lambertus A. Kiemeney, Jeri Kim, Susanne K. Kjaer, Julia A. Knight, Manolis Kogevinas, Zsofia Kote-Jarai, Stella Koutros, Vessela N. Kristensen, Jolanta Kupryjanczyk, Martin Lacko, Stephan Lam, Diether Lambrechts, Maria Teresa Landi, Philip Lazarus, Nhu D. Le, Eunjung Lee, Flavio Lejbkowicz, Heinz-Josef Lenz, Goska Leslie, Davor Lessel, Jenny Lester, Douglas A. Levine, Li Li, Christopher I. Li, Annika Lindblom, Noralane M. Lindor, Geoffrey Liu, Fotios Loupakis, Jan Lubiński, Lovise Maehle, Christiane Maier, Arto Mannermaa, Loic Le Marchand, Sara Margolin, Taymaa May, Lesley McGuffog, Alfons Meindl, Pooja Middha, Austin Miller, Roger L. Milne, Robert J. MacInnis, Francesmary Modugno, Marco Montagna, Victor Moreno, Kirsten B. Moysich, Lorelei Mucci, Kenneth Muir, Anna Marie Mulligan, Katherine L. Nathanson, David E. Neal, Andrew R. Ness, Susan L. Neuhausen, Heli Nevanlinna, Polly A. Newcomb, Lisa F. Newcomb, Finn Cilius Nielsen, Liene Nikitina-Zake, Børge G. Nordestgaard, Robert L. Nussbaum, Kenneth Offit, Edith Olah, Ali Amin Al Olama, Olufunmilayo I. Olopade, Andrew F. Olshan, Håkan Olsson, Ana Osorio, Hardev Pandha, Jong Y. Park, Nora Pashayan, Michael T. Parsons, Tanja Pejovic, Kathryn L. Penney, Wilbert H. M. Peters, Catherine M. Phelan, Amanda I. Phipps, Dijana Plaseska-Karanfilska, Miranda Pring, Darya Prokofyeva, Paolo Radice, Kari Stefansson, Susan J. Ramus, Leon Raskin, Gad Rennert, Hedy S. Rennert, Elizabeth J. van Rensburg, Marjorie J. Riggan, Harvey A. Risch, Angela Risch, Monique J. Roobol, Barry S. Rosenstein, Mary Anne Rossing, Kim De Ruyck, Emmanouil Saloustros, Dale P. Sandler, Elinor J. Sawyer, Matthew B. Schabath, Johanna Schleutker, Marjanka K. Schmidt, V. Wendy Setiawan, Hongbing Shen, Erin M. Siegel, Weiva Sieh, Christian F. Singer, Martha L. Slattery, Karina Dalsgaard Sorensen, Melissa C. Southey, Amanda B. Spurdle, Janet L. Stanford, Victoria L. Stevens, Sebastian Stintzing, Jennifer Stone, Karin Sundfeldt, Rebecca Sutphen, Anthony J. Swerdlow, Eloiza H. Tajara, Catherine M. Tangen, Adonina Tardon, Jack A. Taylor, M. Dawn Teare, Manuel R. Teixeira, Mary Beth Terry, Kathryn L. Terry, Stephen N. Thibodeau, Mads Thomassen, Line Bjørge, Marc Tischkowitz, Amanda E. Toland, Diana Torres, Paul A. Townsend, Ruth C. Travis, Nadine Tung, Shelley S. Tworoger, Cornelia M. Ulrich, Nawaid Usmani, Celine M. Vachon, Els Van Nieuwenhuysen, Ana Vega, Miguel Elías Aguado-Barrera, Qin Wang, Penelope M. Webb, Clarice R. Weinberg, Stephanie Weinstein, Mark C. Weissler, Jeffrey N. Weitzel, Catharine M. L. West, Emily White, Alice S. Whittemore, H-Erich Wichmann, Fredrik Wiklund, Robert Winqvist, Alicja Wolk, Penella Woll, Michael Woods, Anna H. Wu, Xifeng Wu, Drakoulis Yannoukakos, Wei Zheng, Shanbeh Zienolddiny, Argyrios Ziogas, Kristin K. Zorn, Jacqueline M. Lane, Richa Saxena, Duncan Thomas, Rayjean J. Hung, Brenda Diergaarde, James McKay, Ulrike Peters, Li Hsu, Montserrat García-Closas, Rosalind A. Eeles, Georgia Chenevix-Trench, Paul J. Brennan, Christopher A. Haiman, Jacques Simard, Douglas F. Easton, Stephen B. Gruber, Paul D. P. Pharoah, Alkes L. Price, Bogdan Pasaniuc, Christopher I. Amos, Peter Kraft, and Sara Lindström

Subjects
Science
Abstract

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Published
2019
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9. Shared heritability and functional enrichment across six solid cancers

Author

Xia Jiang, Hilary K. Finucane, Fredrick R. Schumacher, Stephanie L. Schmit, Jonathan P. Tyrer, Younghun Han, Kyriaki Michailidou, Corina Lesseur, Karoline B. Kuchenbaecker, Joe Dennis, David V. Conti, Graham Casey, Mia M. Gaudet, Jeroen R. Huyghe, Demetrius Albanes, Melinda C. Aldrich, Angeline S. Andrew, Irene L. Andrulis, Hoda Anton-Culver, Antonis C. Antoniou, Natalia N. Antonenkova, Susanne M. Arnold, Kristan J. Aronson, Banu K. Arun, Elisa V. Bandera, Rosa B. Barkardottir, Daniel R. Barnes, Jyotsna Batra, Matthias W. Beckmann, Javier Benitez, Sara Benlloch, Andrew Berchuck, Sonja I. Berndt, Heike Bickeböller, Stephanie A. Bien, Carl Blomqvist, Stefania Boccia, Natalia V. Bogdanova, Stig E. Bojesen, Manjeet K. Bolla, Hiltrud Brauch, Hermann Brenner, James D. Brenton, Mark N. Brook, Joan Brunet, Hans Brunnström, Daniel D. Buchanan, Barbara Burwinkel, Ralf Butzow, Gabriella Cadoni, Trinidad Caldés, Maria A. Caligo, Ian Campbell, Peter T. Campbell, Géraldine Cancel-Tassin, Lisa Cannon-Albright, Daniele Campa, Neil Caporaso, André L. Carvalho, Andrew T. Chan, Jenny Chang-Claude, Stephen J. Chanock, Chu Chen, David C. Christiani, Kathleen B. M. Claes, Frank Claessens, Judith Clements, J. Margriet Collée, Marcia Cruz Correa, Fergus J. Couch, Angela Cox, Julie M. Cunningham, Cezary Cybulski, Kamila Czene, Mary B. Daly, Anna deFazio, Peter Devilee, Orland Diez, Manuela Gago-Dominguez, Jenny L. Donovan, Thilo Dörk, Eric J. Duell, Alison M. Dunning, Miriam Dwek, Diana M. Eccles, Christopher K. Edlund, Digna R Velez Edwards, Carolina Ellberg, D. Gareth Evans, Peter A. Fasching, Robert L. Ferris, Triantafillos Liloglou, Jane C. Figueiredo, Olivia Fletcher, Renée T. Fortner, Florentia Fostira, Silvia Franceschi, Eitan Friedman, Steven J. Gallinger, Patricia A. Ganz, Judy Garber, José A. García-Sáenz, Simon A. Gayther, Graham G. Giles, Andrew K. Godwin, Mark S. Goldberg, David E. Goldgar, Ellen L. Goode, Marc T. Goodman, Gary Goodman, Kjell Grankvist, Mark H. Greene, Henrik Gronberg, Jacek Gronwald, Pascal Guénel, Niclas Håkansson, Per Hall, Ute Hamann, Freddie C. Hamdy, Robert J. Hamilton, Jochen Hampe, Aage Haugen, Florian Heitz, Rolando Herrero, Peter Hillemanns, Michael Hoffmeister, Estrid Høgdall, Yun-Chul Hong, John L. Hopper, Richard Houlston, Peter J. Hulick, David J. Hunter, David G. Huntsman, Gregory Idos, Evgeny N. Imyanitov, Sue Ann Ingles, Claudine Isaacs, Anna Jakubowska, Paul James, Mark A. Jenkins, Mattias Johansson, Mikael Johansson, Esther M. John, Amit D. Joshi, Radka Kaneva, Beth Y. Karlan, Linda E. Kelemen, Tabea Kühl, Kay-Tee Khaw, Elza Khusnutdinova, Adam S. Kibel, Lambertus A. Kiemeney, Jeri Kim, Susanne K. Kjaer, Julia A. Knight, Manolis Kogevinas, Zsofia Kote-Jarai, Stella Koutros, Vessela N. Kristensen, Jolanta Kupryjanczyk, Martin Lacko, Stephan Lam, Diether Lambrechts, Maria Teresa Landi, Philip Lazarus, Nhu D. Le, Eunjung Lee, Flavio Lejbkowicz, Heinz-Josef Lenz, Goska Leslie, Davor Lessel, Jenny Lester, Douglas A. Levine, Li Li, Christopher I. Li, Annika Lindblom, Noralane M. Lindor, Geoffrey Liu, Fotios Loupakis, Jan Lubiński, Lovise Maehle, Christiane Maier, Arto Mannermaa, Loic Le Marchand, Sara Margolin, Taymaa May, Lesley McGuffog, Alfons Meindl, Pooja Middha, Austin Miller, Roger L. Milne, Robert J. MacInnis, Francesmary Modugno, Marco Montagna, Victor Moreno, Kirsten B. Moysich, Lorelei Mucci, Kenneth Muir, Anna Marie Mulligan, Katherine L. Nathanson, David E. Neal, Andrew R. Ness, Susan L. Neuhausen, Heli Nevanlinna, Polly A. Newcomb, Lisa F. Newcomb, Finn Cilius Nielsen, Liene Nikitina-Zake, Børge G. Nordestgaard, Robert L. Nussbaum, Kenneth Offit, Edith Olah, Ali Amin Al Olama, Olufunmilayo I. Olopade, Andrew F. Olshan, Håkan Olsson, Ana Osorio, Hardev Pandha, Jong Y. Park, Nora Pashayan, Michael T. Parsons, Tanja Pejovic, Kathryn L. Penney, Wilbert H M. Peters, Catherine M. Phelan, Amanda I. Phipps, Dijana Plaseska-Karanfilska, Miranda Pring, Darya Prokofyeva, Paolo Radice, Kari Stefansson, Susan J. Ramus, Leon Raskin, Gad Rennert, Hedy S. Rennert, Elizabeth J. van Rensburg, Marjorie J. Riggan, Harvey A. Risch, Angela Risch, Monique J. Roobol, Barry S. Rosenstein, Mary Anne Rossing, Kim De Ruyck, Emmanouil Saloustros, Dale P. Sandler, Elinor J. Sawyer, Matthew B. Schabath, Johanna Schleutker, Marjanka K. Schmidt, V. Wendy Setiawan, Hongbing Shen, Erin M. Siegel, Weiva Sieh, Christian F. Singer, Martha L. Slattery, Karina Dalsgaard Sorensen, Melissa C. Southey, Amanda B. Spurdle, Janet L. Stanford, Victoria L. Stevens, Sebastian Stintzing, Jennifer Stone, Karin Sundfeldt, Rebecca Sutphen, Anthony J. Swerdlow, Eloiza H. Tajara, Catherine M. Tangen, Adonina Tardon, Jack A. Taylor, M. Dawn Teare, Manuel R. Teixeira, Mary Beth Terry, Kathryn L. Terry, Stephen N. Thibodeau, Mads Thomassen, Line Bjørge, Marc Tischkowitz, Amanda E. Toland, Diana Torres, Paul A. Townsend, Ruth C. Travis, Nadine Tung, Shelley S. Tworoger, Cornelia M. Ulrich, Nawaid Usmani, Celine M. Vachon, Els Van Nieuwenhuysen, Ana Vega, Miguel Elías Aguado-Barrera, Qin Wang, Penelope M. Webb, Clarice R. Weinberg, Stephanie Weinstein, Mark C. Weissler, Jeffrey N. Weitzel, Catharine M. L. West, Emily White, Alice S. Whittemore, H-Erich Wichmann, Fredrik Wiklund, Robert Winqvist, Alicja Wolk, Penella Woll, Michael Woods, Anna H. Wu, Xifeng Wu, Drakoulis Yannoukakos, Wei Zheng, Shanbeh Zienolddiny, Argyrios Ziogas, Kristin K. Zorn, Jacqueline M. Lane, Richa Saxena, Duncan Thomas, Rayjean J. Hung, Brenda Diergaarde, James McKay, Ulrike Peters, Li Hsu, Montserrat García-Closas, Rosalind A. Eeles, Georgia Chenevix-Trench, Paul J. Brennan, Christopher A. Haiman, Jacques Simard, Douglas F. Easton, Stephen B. Gruber, Paul D. P. Pharoah, Alkes L. Price, Bogdan Pasaniuc, Christopher I. Amos, Peter Kraft, and Sara Lindström

Subjects
Science
Abstract

Similarities in cancers can be studied to interrogate their etiology. Here, the authors use genome-wide association study summary statistics from six cancer types based on 296,215 cases and 301,319 controls of European ancestry, showing that solid tumours arising from different tissues share a degree of common germline genetic basis.

Published
2019
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10. Author Correction: Germline variation at 8q24 and prostate cancer risk in men of European ancestry

Author

Marco Matejcic, Edward J. Saunders, Tokhir Dadaev, Mark N. Brook, Kan Wang, Xin Sheng, Ali Amin Al Olama, Fredrick R. Schumacher, Sue A. Ingles, Koveela Govindasami, Sara Benlloch, Sonja I. Berndt, Demetrius Albanes, Stella Koutros, Kenneth Muir, Victoria L. Stevens, Susan M. Gapstur, Catherine M. Tangen, Jyotsna Batra, Judith Clements, Henrik Gronberg, Nora Pashayan, Johanna Schleutker, Alicja Wolk, Catharine West, Lorelei Mucci, Peter Kraft, Géraldine Cancel-Tassin, Karina D. Sorensen, Lovise Maehle, Eli M. Grindedal, Sara S. Strom, David E. Neal, Freddie C. Hamdy, Jenny L. Donovan, Ruth C. Travis, Robert J. Hamilton, Barry Rosenstein, Yong-Jie Lu, Graham G. Giles, Adam S. Kibel, Ana Vega, Jeanette T. Bensen, Manolis Kogevinas, Kathryn L. Penney, Jong Y. Park, Janet L. Stanford, Cezary Cybulski, Børge G. Nordestgaard, Hermann Brenner, Christiane Maier, Jeri Kim, Manuel R. Teixeira, Susan L. Neuhausen, Kim De Ruyck, Azad Razack, Lisa F. Newcomb, Davor Lessel, Radka Kaneva, Nawaid Usmani, Frank Claessens, Paul A. Townsend, Manuela Gago-Dominguez, Monique J. Roobol, Florence Menegaux, Kay-Tee Khaw, Lisa A. Cannon-Albright, Hardev Pandha, Stephen N. Thibodeau, Daniel J. Schaid, The PRACTICAL Consortium, Fredrik Wiklund, Stephen J. Chanock, Douglas F. Easton, Rosalind A. Eeles, Zsofia Kote-Jarai, David V. Conti, and Christopher A. Haiman

Subjects
Science
Abstract

The original version of this Article contained an error in the spelling of the author Manuela Gago-Dominguez, which was incorrectly given as Manuela G. Dominguez. This has now been corrected in both the PDF and HTML versions of the Article.

Published
2019
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11. Germline variation at 8q24 and prostate cancer risk in men of European ancestry

Author

Marco Matejcic, Edward J. Saunders, Tokhir Dadaev, Mark N. Brook, Kan Wang, Xin Sheng, Ali Amin Al Olama, Fredrick R. Schumacher, Sue A. Ingles, Koveela Govindasami, Sara Benlloch, Sonja I. Berndt, Demetrius Albanes, Stella Koutros, Kenneth Muir, Victoria L. Stevens, Susan M. Gapstur, Catherine M. Tangen, Jyotsna Batra, Judith Clements, Henrik Gronberg, Nora Pashayan, Johanna Schleutker, Alicja Wolk, Catharine West, Lorelei Mucci, Peter Kraft, Géraldine Cancel-Tassin, Karina D. Sorensen, Lovise Maehle, Eli M. Grindedal, Sara S. Strom, David E. Neal, Freddie C. Hamdy, Jenny L. Donovan, Ruth C. Travis, Robert J. Hamilton, Barry Rosenstein, Yong-Jie Lu, Graham G. Giles, Adam S. Kibel, Ana Vega, Jeanette T. Bensen, Manolis Kogevinas, Kathryn L. Penney, Jong Y. Park, Janet L. Stanford, Cezary Cybulski, Børge G. Nordestgaard, Hermann Brenner, Christiane Maier, Jeri Kim, Manuel R. Teixeira, Susan L. Neuhausen, Kim De Ruyck, Azad Razack, Lisa F. Newcomb, Davor Lessel, Radka Kaneva, Nawaid Usmani, Frank Claessens, Paul A. Townsend, Manuela Gago-Dominguez, Monique J. Roobol, Florence Menegaux, Kay-Tee Khaw, Lisa A. Cannon-Albright, Hardev Pandha, Stephen N. Thibodeau, Daniel J. Schaid, The PRACTICAL (Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome) Consortium, Fredrik Wiklund, Stephen J. Chanock, Douglas F. Easton, Rosalind A. Eeles, Zsofia Kote-Jarai, David V. Conti, and Christopher A. Haiman

Subjects
Science
Abstract

Chromosome 8q24 is known to be a major susceptibility region for prostate cancer risk. Here the authors analyze genetic data across the 8q24 region from 71,535 prostate cancer patients identifying 12 risk loci, three previously unreported, highlighting the contribution of germline variation at this locus.

Published
2018
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12. Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Author

Tokhir Dadaev, Edward J. Saunders, Paul J. Newcombe, Ezequiel Anokian, Daniel A. Leongamornlert, Mark N. Brook, Clara Cieza-Borrella, Martina Mijuskovic, Sarah Wakerell, Ali Amin Al Olama, Fredrick R. Schumacher, Sonja I. Berndt, Sara Benlloch, Mahbubl Ahmed, Chee Goh, Xin Sheng, Zhuo Zhang, Kenneth Muir, Koveela Govindasami, Artitaya Lophatananon, Victoria L. Stevens, Susan M. Gapstur, Brian D. Carter, Catherine M. Tangen, Phyllis Goodman, Ian M. Thompson, Jyotsna Batra, Suzanne Chambers, Leire Moya, Judith Clements, Lisa Horvath, Wayne Tilley, Gail Risbridger, Henrik Gronberg, Markus Aly, Tobias Nordström, Paul Pharoah, Nora Pashayan, Johanna Schleutker, Teuvo L. J. Tammela, Csilla Sipeky, Anssi Auvinen, Demetrius Albanes, Stephanie Weinstein, Alicja Wolk, Niclas Hakansson, Catharine West, Alison M. Dunning, Neil Burnet, Lorelei Mucci, Edward Giovannucci, Gerald Andriole, Olivier Cussenot, Géraldine Cancel-Tassin, Stella Koutros, Laura E. Beane Freeman, Karina Dalsgaard Sorensen, Torben Falck Orntoft, Michael Borre, Lovise Maehle, Eli Marie Grindedal, David E. Neal, Jenny L. Donovan, Freddie C. Hamdy, Richard M. Martin, Ruth C. Travis, Tim J. Key, Robert J. Hamilton, Neil E. Fleshner, Antonio Finelli, Sue Ann Ingles, Mariana C. Stern, Barry Rosenstein, Sarah Kerns, Harry Ostrer, Yong-Jie Lu, Hong-Wei Zhang, Ninghan Feng, Xueying Mao, Xin Guo, Guomin Wang, Zan Sun, Graham G. Giles, Melissa C. Southey, Robert J. MacInnis, Liesel M. FitzGerald, Adam S. Kibel, Bettina F. Drake, Ana Vega, Antonio Gómez-Caamaño, Laura Fachal, Robert Szulkin, Martin Eklund, Manolis Kogevinas, Javier Llorca, Gemma Castaño-Vinyals, Kathryn L. Penney, Meir Stampfer, Jong Y. Park, Thomas A. Sellers, Hui-Yi Lin, Janet L. Stanford, Cezary Cybulski, Dominika Wokolorczyk, Jan Lubinski, Elaine A. Ostrander, Milan S. Geybels, Børge G. Nordestgaard, Sune F. Nielsen, Maren Weisher, Rasmus Bisbjerg, Martin Andreas Røder, Peter Iversen, Hermann Brenner, Katarina Cuk, Bernd Holleczek, Christiane Maier, Manuel Luedeke, Thomas Schnoeller, Jeri Kim, Christopher J. Logothetis, Esther M. John, Manuel R. Teixeira, Paula Paulo, Marta Cardoso, Susan L. Neuhausen, Linda Steele, Yuan Chun Ding, Kim De Ruyck, Gert De Meerleer, Piet Ost, Azad Razack, Jasmine Lim, Soo-Hwang Teo, Daniel W. Lin, Lisa F. Newcomb, Davor Lessel, Marija Gamulin, Tomislav Kulis, Radka Kaneva, Nawaid Usmani, Chavdar Slavov, Vanio Mitev, Matthew Parliament, Sandeep Singhal, Frank Claessens, Steven Joniau, Thomas Van den Broeck, Samantha Larkin, Paul A. Townsend, Claire Aukim-Hastie, Manuela Gago-Dominguez, Jose Esteban Castelao, Maria Elena Martinez, Monique J. Roobol, Guido Jenster, Ron H. N. van Schaik, Florence Menegaux, Thérèse Truong, Yves Akoli Koudou, Jianfeng Xu, Kay-Tee Khaw, Lisa Cannon-Albright, Hardev Pandha, Agnieszka Michael, Andrzej Kierzek, Stephen N. Thibodeau, Shannon K. McDonnell, Daniel J. Schaid, Sara Lindstrom, Constance Turman, Jing Ma, David J. Hunter, Elio Riboli, Afshan Siddiq, Federico Canzian, Laurence N. Kolonel, Loic Le Marchand, Robert N. Hoover, Mitchell J. Machiela, Peter Kraft, The PRACTICAL (Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome) Consortium, Matthew Freedman, Fredrik Wiklund, Stephen Chanock, Brian E. Henderson, Douglas F. Easton, Christopher A. Haiman, Rosalind A. Eeles, David V. Conti, and Zsofia Kote-Jarai

Subjects
Science
Abstract

Prostate cancer (PrCa) involves a large heritable genetic component. Here, the authors perform multivariate fine-mapping of known PrCa GWAS loci, identifying variants enriched for biological function, explaining more familial relative risk, and with potential application in clinical risk profiling.

Published
2018
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13. Genome-wide association study identifies multiple risk loci for renal cell carcinoma

Author

Ghislaine Scelo, Mark P. Purdue, Kevin M. Brown, Mattias Johansson, Zhaoming Wang, Jeanette E. Eckel-Passow, Yuanqing Ye, Jonathan N. Hofmann, Jiyeon Choi, Matthieu Foll, Valerie Gaborieau, Mitchell J. Machiela, Leandro M. Colli, Peng Li, Joshua N. Sampson, Behnoush Abedi-Ardekani, Celine Besse, Helene Blanche, Anne Boland, Laurie Burdette, Amelie Chabrier, Geoffroy Durand, Florence Le Calvez-Kelm, Egor Prokhortchouk, Nivonirina Robinot, Konstantin G. Skryabin, Magdalena B. Wozniak, Meredith Yeager, Gordana Basta-Jovanovic, Zoran Dzamic, Lenka Foretova, Ivana Holcatova, Vladimir Janout, Dana Mates, Anush Mukeriya, Stefan Rascu, David Zaridze, Vladimir Bencko, Cezary Cybulski, Eleonora Fabianova, Viorel Jinga, Jolanta Lissowska, Jan Lubinski, Marie Navratilova, Peter Rudnai, Neonila Szeszenia-Dabrowska, Simone Benhamou, Geraldine Cancel-Tassin, Olivier Cussenot, Laura Baglietto, Heiner Boeing, Kay-Tee Khaw, Elisabete Weiderpass, Borje Ljungberg, Raviprakash T. Sitaram, Fiona Bruinsma, Susan J. Jordan, Gianluca Severi, Ingrid Winship, Kristian Hveem, Lars J. Vatten, Tony Fletcher, Kvetoslava Koppova, Susanna C. Larsson, Alicja Wolk, Rosamonde E. Banks, Peter J. Selby, Douglas F. Easton, Paul Pharoah, Gabriella Andreotti, Laura E. Beane Freeman, Stella Koutros, Demetrius Albanes, Satu Männistö, Stephanie Weinstein, Peter E. Clark, Todd L. Edwards, Loren Lipworth, Susan M. Gapstur, Victoria L. Stevens, Hallie Carol, Matthew L. Freedman, Mark M. Pomerantz, Eunyoung Cho, Peter Kraft, Mark A. Preston, Kathryn M. Wilson, J. Michael Gaziano, Howard D. Sesso, Amanda Black, Neal D. Freedman, Wen-Yi Huang, John G. Anema, Richard J. Kahnoski, Brian R. Lane, Sabrina L. Noyes, David Petillo, Bin Tean Teh, Ulrike Peters, Emily White, Garnet L. Anderson, Lisa Johnson, Juhua Luo, Julie Buring, I-Min Lee, Wong-Ho Chow, Lee E. Moore, Christopher Wood, Timothy Eisen, Marc Henrion, James Larkin, Poulami Barman, Bradley C. Leibovich, Toni K. Choueiri, G. Mark Lathrop, Nathaniel Rothman, Jean-Francois Deleuze, James D. McKay, Alexander S. Parker, Xifeng Wu, Richard S. Houlston, Paul Brennan, and Stephen J. Chanock

Subjects
Science
Abstract

Risk for renal cell carcinoma (RCC) is higher when there are first-degree family members with the disease. Here, Scelo and colleagues perform a genome-wide association meta-analysis and new genome-wide scan to identify seven new loci with significant RCC association.

Published
2017
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14. Mosaic chromosome 20q deletions are more frequent in the aging population

Author

Mitchell J. Machiela, Weiyin Zhou, Neil Caporaso, Michael Dean, Susan M. Gapstur, Lynn Goldin, Nathaniel Rothman, Victoria L. Stevens, Meredith Yeager, and Stephen J. Chanock

Subjects
Specialties of internal medicine, RC581-951
Abstract

Abstract: Deletions on the long-arm of chromosome 20, del(20q), are common karyotypic abnormalities in myeloid disorders. Bioinformatic analyses of the B-allele frequency and log R ratio values from genome-wide association data have identified individuals who are mosaic for large structural abnormalities (>2 Mb). We investigated the most common autosomal event, namely mosaic del(20q), in 46 254 nonhematologic cancer cases and 36 229 cancer-free controls. We detected 91 mosaic del(20q) in leukocytes (80%) and buccal material (20%). The mosaic del(20q) mapped to a well-characterized minimally deleted region (MDR) reported in myeloid disorders. Common breakpoint clusters map to the coordinates of 29.9 to 31.5 Mb on the centromeric side of mosaic del(20q), and 42.0 to 45.4 Mb and 48.1 to 50.7 Mb on the telomeric end (GRCh36). Multivariate analyses suggest del(20q) increases with age, and is more common in males but less common in individuals of African ancestry. No conclusive associations were noted between the presence of mosaic del(20q) and subsequent solid tumor risk. Our observations demonstrate that the MDR of del(20q) is the most common large scale mosaic autosomal abnormality in whole blood and has a frequency of ∼1 in every 1000 adults over the age of 50, which exceeds the expected incidence of myeloid leukemia in the population. Our results indicate that subclonal mosaic events of a region implicated in myeloid disorders on 20q are more frequent than the predicted population-estimated incidence of myeloid diseases, and thus suggest that these events can be tolerated until additional events accumulate that drive myeloid disorders.

Published
2017
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15. Identification and Reproducibility of Urinary Metabolomic Biomarkers of Habitual Food Intake in a Cross-Sectional Analysis of the Cancer Prevention Study-3 Diet Assessment Sub-Study

Author

Ying Wang, Rebecca A. Hodge, Victoria L. Stevens, Terryl J. Hartman, and Marjorie L. McCullough

Subjects
untargeted metabolomics, food biomarker, FFQ, 24 h diet recalls, urine, Microbiology, QR1-502
Abstract

Previous cross-sectional metabolomics studies have identified many potential dietary biomarkers, mostly in blood. Few studies examined urine samples although urine is preferred for dietary biomarker discovery. Furthermore, little is known regarding the reproducibility of urinary metabolomic biomarkers over time. We aimed to identify urinary metabolomic biomarkers of diet and assess their reproducibility over time. We conducted a metabolomics analysis among 648 racially/ethnically diverse men and women in the Diet Assessment Sub-study of the Cancer Prevention Study-3 cohort to examine the correlation between >100 food groups/items [101 by a food frequency questionnaire (FFQ), and 105 by repeated 24 h diet recalls (24HRs)] and 1391 metabolites measured in 24 h urine sample replicates, six months apart. Diet–metabolite associations were examined by Pearson’s partial correlation analysis. Biomarkers were evaluated for prediction accuracy assessed using area under the curve (AUC) calculated from the receiver operating characteristic curve and for reproducibility assessed using intraclass correlation coefficients (ICCs). A total of 1708 diet–metabolite associations were identified after Bonferroni correction for multiple comparisons and restricting correlation coefficients to >0.2 or

Published
2021
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16. Pre-Diagnostic Circulating Metabolites and Colorectal Cancer Risk in the Cancer Prevention Study-II Nutrition Cohort

Author

Marjorie L. McCullough, Rebecca A. Hodge, Peter T. Campbell, Victoria L. Stevens, and Ying Wang

Subjects
metabolomics, colorectal cancer, epidemiology, biomarkers, nested case–control, Microbiology, QR1-502
Abstract

Untargeted metabolomic studies have identified potential biomarkers of colorectal cancer risk, but evidence is still limited and broadly inconsistent. Among 39,239 Cancer Prevention Study II Nutrition cohort participants who provided a blood sample between 1998–2001, 517 newly diagnosed colorectal cancers were identified through 30 June 2015. In this nested case–control study, controls were matched 1:1 to cases on age, sex, race and date of blood draw. Mass spectroscopy-based metabolomic analyses of pre-diagnostic plasma identified 886 named metabolites, after quality control exclusions. Conditional logistic regression models estimated multivariable-adjusted odds ratios (OR) and 95% confidence intervals (CI) for 1 standard deviation (SD) increase in each metabolite with risk of colorectal cancer. Six metabolites were associated with colorectal cancer risk at a false discovery rate < 0.20. These metabolites were of several classes, including cofactors and vitamins, nucleotides, xenobiotics, lipids and amino acids. Five metabolites (guanidinoacetate, 2’-O-methylcytidine, vanillylmandelate, bilirubin (E,E) and N-palmitoylglycine) were positively associated (OR per 1 SD = 1.29 to 1.32), and one (3-methylxanthine) was inversely associated with CRC risk (OR = 0.79, 95% CI, 0.69–0.89). We did not replicate findings from two earlier prospective studies of 250 cases each after adjusting for multiple comparisons. Large pooled prospective analyses are warranted to confirm or refute these findings and to discover and replicate metabolites associated with colorectal cancer risk.

Published
2021
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17. A Metabolomics Analysis of Postmenopausal Breast Cancer Risk in the Cancer Prevention Study II

Author

Steven C. Moore, Kaitlyn M. Mazzilli, Joshua N. Sampson, Charles E. Matthews, Brian D. Carter, Mary C. Playdon, Ying Wang, and Victoria L. Stevens

Subjects
breast cancer, epidemiology, carnitines, glycerolipids, sex steroid hormones, alcohol, Microbiology, QR1-502
Abstract

Breast cancer is the most common cancer in women, but its incidence can only be partially explained through established risk factors. Our aim was to use metabolomics to identify novel risk factors for breast cancer and to validate recently reported metabolite-breast cancer findings. We measured levels of 1275 metabolites in prediagnostic serum in a nested case-control study of 782 postmenopausal breast cancer cases and 782 matched controls. Metabolomics analysis was performed by Metabolon Inc using ultra-performance liquid chromatography and a Q-Exactive high resolution/accurate mass spectrometer. Controls were matched by birth date, date of blood draw, and race/ethnicity. Odds ratios (ORs) and 95% confidence intervals (CIs) of breast cancer at the 90th versus 10th percentile (modeled on a continuous basis) of metabolite levels were estimated using conditional logistic regression, with adjustment for age. Twenty-four metabolites were significantly associated with breast cancer risk at a false discovery rate

Published
2021
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18. Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome

Author

Mitchell J. Machiela, Weiyin Zhou, Eric Karlins, Joshua N. Sampson, Neal D. Freedman, Qi Yang, Belynda Hicks, Casey Dagnall, Christopher Hautman, Kevin B. Jacobs, Christian C. Abnet, Melinda C. Aldrich, Christopher Amos, Laufey T. Amundadottir, Alan A. Arslan, Laura E. Beane-Freeman, Sonja I. Berndt, Amanda Black, William J. Blot, Cathryn H. Bock, Paige M. Bracci, Louise A. Brinton, H Bas Bueno-de-Mesquita, Laurie Burdett, Julie E. Buring, Mary A. Butler, Federico Canzian, Tania Carreón, Kari G. Chaffee, I-Shou Chang, Nilanjan Chatterjee, Chu Chen, Constance Chen, Kexin Chen, Charles C. Chung, Linda S. Cook, Marta Crous Bou, Michael Cullen, Faith G. Davis, Immaculata De Vivo, Ti Ding, Jennifer Doherty, Eric J. Duell, Caroline G. Epstein, Jin-Hu Fan, Jonine D. Figueroa, Joseph F. Fraumeni, Christine M. Friedenreich, Charles S. Fuchs, Steven Gallinger, Yu-Tang Gao, Susan M. Gapstur, Montserrat Garcia-Closas, Mia M. Gaudet, J. Michael Gaziano, Graham G. Giles, Elizabeth M. Gillanders, Edward L. Giovannucci, Lynn Goldin, Alisa M. Goldstein, Christopher A. Haiman, Goran Hallmans, Susan E. Hankinson, Curtis C. Harris, Roger Henriksson, Elizabeth A. Holly, Yun-Chul Hong, Robert N. Hoover, Chao A. Hsiung, Nan Hu, Wei Hu, David J. Hunter, Amy Hutchinson, Mazda Jenab, Christoffer Johansen, Kay-Tee Khaw, Hee Nam Kim, Yeul Hong Kim, Young Tae Kim, Alison P. Klein, Robert Klein, Woon-Puay Koh, Laurence N. Kolonel, Charles Kooperberg, Peter Kraft, Vittorio Krogh, Robert C. Kurtz, Andrea LaCroix, Qing Lan, Maria Teresa Landi, Loic Le Marchand, Donghui Li, Xiaolin Liang, Linda M. Liao, Dongxin Lin, Jianjun Liu, Jolanta Lissowska, Lingeng Lu, Anthony M. Magliocco, Nuria Malats, Keitaro Matsuo, Lorna H. McNeill, Robert R. McWilliams, Beatrice S. Melin, Lisa Mirabello, Lee Moore, Sara H. Olson, Irene Orlow, Jae Yong Park, Ana Patiño-Garcia, Beata Peplonska, Ulrike Peters, Gloria M. Petersen, Loreall Pooler, Jennifer Prescott, Ludmila Prokunina-Olsson, Mark P. Purdue, You-Lin Qiao, Preetha Rajaraman, Francisco X. Real, Elio Riboli, Harvey A. Risch, Benjamin Rodriguez-Santiago, Avima M. Ruder, Sharon A. Savage, Fredrick Schumacher, Ann G. Schwartz, Kendra L. Schwartz, Adeline Seow, Veronica Wendy Setiawan, Gianluca Severi, Hongbing Shen, Xin Sheng, Min-Ho Shin, Xiao-Ou Shu, Debra T. Silverman, Margaret R. Spitz, Victoria L. Stevens, Rachael Stolzenberg-Solomon, Daniel Stram, Ze-Zhong Tang, Philip R. Taylor, Lauren R. Teras, Geoffrey S. Tobias, David Van Den Berg, Kala Visvanathan, Sholom Wacholder, Jiu-Cun Wang, Zhaoming Wang, Nicolas Wentzensen, William Wheeler, Emily White, John K. Wiencke, Brian M. Wolpin, Maria Pik Wong, Chen Wu, Tangchun Wu, Xifeng Wu, Yi-Long Wu, Jay S. Wunder, Lucy Xia, Hannah P. Yang, Pan-Chyr Yang, Kai Yu, Krista A. Zanetti, Anne Zeleniuch-Jacquotte, Wei Zheng, Baosen Zhou, Regina G. Ziegler, Luis A. Perez-Jurado, Neil E. Caporaso, Nathaniel Rothman, Margaret Tucker, Michael C. Dean, Meredith Yeager, and Stephen J. Chanock

Subjects
Science
Abstract

It is unclear how often genetic mosaicism of chromosome X arises. Here, the authors examine women with cancer and cancer-free controls and show that X chromosome mosaicism occurs more frequently than on autosomes, especially on the inactive X chromosome, but is not linked to non-haematologic cancer risk

Published
2016
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19. Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation

Author

Alexander Gusev, Huwenbo Shi, Gleb Kichaev, Mark Pomerantz, Fugen Li, Henry W. Long, Sue A. Ingles, Rick A. Kittles, Sara S. Strom, Benjamin A. Rybicki, Barbara Nemesure, William B. Isaacs, Wei Zheng, Curtis A. Pettaway, Edward D. Yeboah, Yao Tettey, Richard B. Biritwum, Andrew A. Adjei, Evelyn Tay, Ann Truelove, Shelley Niwa, Anand P. Chokkalingam, Esther M. John, Adam B. Murphy, Lisa B. Signorello, John Carpten, M. Cristina Leske, Suh-Yuh Wu, Anslem J. M. Hennis, Christine Neslund-Dudas, Ann W. Hsing, Lisa Chu, Phyllis J. Goodman, Eric A. Klein, John S. Witte, Graham Casey, Sam Kaggwa, Michael B. Cook, Daniel O. Stram, William J. Blot, Rosalind A. Eeles, Douglas Easton, ZSofia Kote-Jarai, Ali Amin Al Olama, Sara Benlloch, Kenneth Muir, Graham G. Giles, Melissa C. Southey, Liesel M. Fitzgerald, Henrik Gronberg, Fredrik Wiklund, Markus Aly, Brian E. Henderson, Johanna Schleutker, Tiina Wahlfors, Teuvo L. J. Tammela, Børge G. Nordestgaard, Tim J. Key, Ruth C. Travis, David E. Neal, Jenny L. Donovan, Freddie C. Hamdy, Paul Pharoah, Nora Pashayan, Kay-Tee Khaw, Janet L. Stanford, Stephen N. Thibodeau, Shannon K. McDonnell, Daniel J. Schaid, Christiane Maier, Walther Vogel, Manuel Luedeke, Kathleen Herkommer, Adam S. Kibel, Cezary Cybulski, Dominika Wokolorczyk, Wojciech Kluzniak, Lisa Cannon-Albright, Craig Teerlink, Hermann Brenner, Aida K. Dieffenbach, Volker Arndt, Jong Y. Park, Thomas A. Sellers, Hui-Yi Lin, Chavdar Slavov, Radka Kaneva, Vanio Mitev, Jyotsna Batra, Amanda Spurdle, Judith A. Clements, Manuel R. Teixeira, Hardev Pandha, Agnieszka Michael, Paula Paulo, Sofia Maia, Andrzej Kierzek, The PRACTICAL consortium, David V. Conti, Demetrius Albanes, Christine Berg, Sonja I. Berndt, Daniele Campa, E. David Crawford, W. Ryan Diver, Susan M. Gapstur, J. Michael Gaziano, Edward Giovannucci, Robert Hoover, David J. Hunter, Mattias Johansson, Peter Kraft, Loic Le Marchand, Sara Lindström, Carmen Navarro, Kim Overvad, Elio Riboli, Afshan Siddiq, Victoria L. Stevens, Dimitrios Trichopoulos, Paolo Vineis, Meredith Yeager, Gosia Trynka, Soumya Raychaudhuri, Frederick R. Schumacher, Alkes L. Price, Matthew L. Freedman, Christopher A. Haiman, and Bogdan Pasaniuc

Subjects
Science
Abstract

Over one hundred loci have been identified to be associated with the familial risk of prostate cancer but the functional effects are poorly understood. Here the authors use single-nucleotide variant and epigentic data to show an underlying genetic architecture marked by histone modification.

Published
2016
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20. Identification and Reproducibility of Plasma Metabolomic Biomarkers of Habitual Food Intake in a US Diet Validation Study

Author

Ying Wang, Rebecca A. Hodge, Victoria L. Stevens, Terryl J. Hartman, and Marjorie L. McCullough

Subjects
untargeted metabolomics, food biomarker, FFQ, 24-h diet recalls, plasma, Microbiology, QR1-502
Abstract

Previous metabolomic studies have identified putative blood biomarkers of dietary intake. These biomarkers need to be replicated in other populations and tested for reproducibility over time for the potential use in future epidemiological studies. We conducted a metabolomics analysis among 671 racially/ethnically diverse men and women included in a diet validation study to examine the correlation between >100 food groups/items (101 by a food frequency questionnaire (FFQ), 105 by 24-h diet recalls (24HRs)) with 1141 metabolites measured in fasting plasma sample replicates, six months apart. Diet–metabolite associations were examined by Pearson’s partial correlation analysis. Biomarker reproducibility was assessed using intraclass correlation coefficients (ICCs). A total of 677 diet–metabolite associations were identified after Bonferroni adjustment for multiple comparisons and restricting absolute correlation coefficients to greater than 0.2 (601 associations using the FFQ and 395 using 24HRs). The median ICCs of the 238 putative biomarkers was 0.56 (interquartile range 0.46–0.68). In this study, with repeated FFQs, 24HRs and plasma metabolic profiles, we identified several potentially novel food biomarkers and replicated others found in our previous study. Our findings contribute to the growing literature on food-based biomarkers and provide important information on biomarker reproducibility which could facilitate their utilization in future nutritional epidemiological studies.

Published
2020
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21. Pre-Analytical Factors that Affect Metabolite Stability in Human Urine, Plasma, and Serum: A Review

Author

Victoria L. Stevens, Elise Hoover, Ying Wang, and Krista A. Zanetti

Subjects
metabolomics, metabolite, pre-analytical factors, Microbiology, QR1-502
Abstract

Metabolomics provides a comprehensive assessment of numerous small molecules in biological samples. As it integrates the effects of exogenous exposures, endogenous metabolism, and genetic variation, metabolomics is well-suited for studies examining metabolic profiles associated with a variety of chronic diseases. In this review, we summarize the studies that have characterized the effects of various pre-analytical factors on both targeted and untargeted metabolomic studies involving human plasma, serum, and urine and were published through 14 January 2019. A standardized protocol was used for extracting data from full-text articles identified by searching PubMed and EMBASE. For plasma and serum samples, metabolomic profiles were affected by fasting status, hemolysis, collection time, processing delays, particularly at room temperature, and repeated freeze/thaw cycles. For urine samples, collection time and fasting, centrifugation conditions, filtration and the use of additives, normalization procedures and multiple freeze/thaw cycles were found to alter metabolomic findings. Consideration of the effects of pre-analytical factors is a particularly important issue for epidemiological studies where samples are often collected in nonclinical settings and various locations and are subjected to time and temperature delays prior being to processed and frozen for storage.

Published
2019
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22. Metabolomics Approach for Validation of Self-Reported Ibuprofen and Acetaminophen Use

Author

Kristine K. Dennis, Brian D. Carter, Susan M. Gapstur, and Victoria L. Stevens

Subjects
metabolomics, acetaminophen, ibuprofen, analgesics, molecular epidemiology, Microbiology, QR1-502
Abstract

Over-the-counter analgesic use is common and is typically assessed through self-report; therefore, it is subject to misclassification. Detection of drug metabolites in biofluids offers a viable tool for validating self-reported analgesic use. Thus, the aim of this study was to determine the utility of a metabolomics approach for the validation of acetaminophen and ibuprofen use in blood samples. Untargeted mass spectrometry-based metabolomics analysis was conducted in serum samples from 1547 women and plasma samples from 556 men. The presence of two metabolites each for acetaminophen and ibuprofen at levels at or above a defined cutoff value was used to determine concordance with self-reported use. For acetaminophen use based on the presence of both acetaminophen and acetamidophenylglucuronide, concordance was 98.5–100% among individuals reporting use today, and 79.8–91.4% for those reporting never or rare use. Ibuprofen use based on the presence of both carboxyibuprofen and hydroxyibuprofen resulted in concordance of 51.3–52.5% for individuals reporting use today and 99.4–100% for those reporting never or rare use. Our findings suggest that an untargeted metabolomics approach in blood samples may be useful for validating self-reported acetaminophen use. However, this approach appears unlikely to be suitable for validating ibuprofen use.

Published
2018
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23. Supplementary Data from Smoking Modifies Pancreatic Cancer Risk Loci on 2q21.3

Author

Rachael Stolzenberg-Solomon, Alison P. Klein, Nilanjan Chatterjee, Peter Kraft, Harvey A. Risch, Brian M. Wolpin, Gloria M. Petersen, Eric J. Jacobs, Donghui Li, Laufey T. Amundadottir, Anne Zeleniuch-Jacquotte, Fangcheng Yuan, Herbert Yu, Lynne R. Wilkens, Nicolas Wentzensen, Jean Wactawski-Wende, Stephen K. Van Den Eeden, Antonia Trichopoulou, Anne Tjonneland, Ian M. Thompson, Oliver Strobel, Victoria L. Stevens, Debra T. Silverman, Howard D. Sesso, Ghislaine Scelo, Nathaniel Rothman, Elio Riboli, Kari G. Rabe, Miquel Porta, Ulrike Peters, Salvatore Panico, Ann L. Oberg, Kimmie Ng, Roger L. Milne, Núria Malats, I-Min Lee, Robert C. Kurtz, Rayjean J. Hung, Robert N. Hoover, Elizabeth A. Holly, Manal M. Hassan, Patricia Hartge, Michael G. Goggins, Edward L. Giovannucci, J. Michael Gaziano, Charles S. Fuchs, Eric J. Duell, Erica J. Childs, Stephen J. Chanock, Daniele Campa, Julie E. Buring, Bas Bueno-de-Mesquita, Amanda L. Blackford, Sonja I. Berndt, William R. Bamlet, Ana Babic, Gabriella Andreotti, Demetrius Albanes, Wei Zheng, Emily White, Kala Visvanathan, Xiao-Ou Shu, Rachel E. Neale, Loic Le Marchand, Charles Kooperberg, Phyllis J. Goodman, Graham G. Giles, Steven Gallinger, Mengmeng Du, Federico Canzian, Paul Brennan, Paige M. Bracci, Laura E. Beane-Freeman, Alan A. Arslan, William Wheeler, Prosenjit Kundu, and Evelina Mocci

Abstract

Supplemental figures 1 and 2. Supplemental tables 1-7.

Published
2023

24. Data from Potential Susceptibility Loci Identified for Renal Cell Carcinoma by Targeting Obesity-Related Genes

Author

Xifeng Wu, Stephen J. Chanock, Nathaniel Rothman, Victoria L. Stevens, Susan M. Gapstur, Demetrius Albanes, Zhaoming Wang, Nizar M. Tannir, Christopher G. Wood, Huakang Tu, Yuanqing Ye, Mark P. Purdue, and Xiang Shu

Abstract

Background: Obesity is an established risk factor for renal cell carcinoma (RCC). Although genome-wide association studies (GWAS) of RCC have identified several susceptibility loci, additional variants might be missed due to the highly conservative selection.Methods: We conducted a multiphase study utilizing three independent genome-wide scans at MD Anderson Cancer Center (MDA RCC GWAS and MDA RCC OncoArray) and National Cancer Institute (NCI RCC GWAS), which consisted of a total of 3,530 cases and 5,714 controls, to investigate genetic variations in obesity-related genes and RCC risk.Results: In the discovery phase, 32,946 SNPs located at ±10 kb of 2,001 obesity-related genes were extracted from MDA RCC GWAS and analyzed using multivariable logistic regression. Proxies (R2 > 0.8) were searched or imputation was performed if SNPs were not directly genotyped in the validation sets. Twenty-one SNPs with P < 0.05 in both MDA RCC GWAS and NCI RCC GWAS were subsequently evaluated in MDA RCC OncoArray. In the overall meta-analysis, significant (P < 0.05) associations with RCC risk were observed for SNP mapping to IL1RAPL2 [rs10521506-G: ORmeta = 0.87 (0.81–0.93), Pmeta = 2.33 × 10−5], PLIN2 [rs2229536-A: ORmeta = 0.87 (0.81–0.93), Pmeta = 2.33 × 10−5], SMAD3 [rs4601989-A: ORmeta = 0.86 (0.80–0.93), Pmeta = 2.71 × 10−4], MED13L [rs10850596-A: ORmeta = 1.14 (1.07–1.23), Pmeta = 1.50 × 10−4], and TSC1 [rs3761840-G: ORmeta = 0.90 (0.85–0.97), Pmeta = 2.47 × 10−3]. We did not observe any significant cis-expression quantitative trait loci effect for these SNPs in the TCGA KIRC data.Conclusions: Taken together, we found that genetic variation of obesity-related genes could influence RCC susceptibility.Impact: The five identified loci may provide new insights into disease etiology that reveal importance of obesity-related genes in RCC development. Cancer Epidemiol Biomarkers Prev; 26(9); 1436–42. ©2017 AACR.

Published
2023

25. Supplementary notes from Genome-Wide Association Study of Prostate Cancer–Specific Survival

Author

Fredrik Wiklund, Sara Lindström, Johanna Schleutker, Lovise Maehle, David G. Cox, Anne Tjønneland, Bas H. Bueno-de-Mesquita, Antonia Trichopoulou, Stephanie J. Weinstein, Victoria L. Stevens, Meir J. Stampfer, Kathryn L. Penney, Alison M. Mondul, Jing Ma, Loic Le Marchand, Peter Kraft, David J. Hunter, Edward L. Giovannucci, Susan M. Gapstur, Stephen Chanock, Sonja I. Berndt, Gerald L. Andriole, Demetrius Albanes, Judith A. Clements, Jyotsna Batra, Andrzej Kierzek, Agnieszka Michael, Hardev Pandha, Sofia Maia, Paula Paulo, Manuel R. Teixeira, Amanda Spurdle, Vanio I. Mitev, Radka P. Kaneva, Chavdar Slavov, Hui-Yi Lim, Thomas A. Sellers, Jong Y. Park, Bernd Holleczek, Volker Herrmann, Hermann Brenner, Lisa Cannon-Albright, Wojciech Kluźniak, Jan Lubiński, Cezary Cybulski, Adam S. Kibel, Kathleen Herkommer, Manuel Luedeke, Walther Vogel, Christiane Maier, Daniel J. Schaid, Shannon K. McDonnell, Stephen N. Thibodeau, Janet L. Stanford, Kay-Tee Khaw, Nora Pashayan, Paul D.P. Pharoah, Freddie C. Hamdy, Jenny L. Donovan, David E. Neal, Ruth C. Travis, Timothy J. Key, Børge G. Nordestgaard, Teuvo L.J. Tammela, Csilla Sipeky, Christopher A. Haiman, Fredrick R. Schumacher, Brian E. Henderson, Liesel M. FitzGerald, Melissa C. Southey, Graham G. Giles, Kenneth Muir, Sara Benlloch, Ali Amin Al Olama, Zsofia Kote-Jarai, Douglas F. Easton, Rosalind A. Eeles, Henrik Gronberg, Markus Aly, Thomas Whitington, Robert Karlsson, and Robert Szulkin

Abstract

Supplementary acknowledgments.

Published
2023

26. Supplementary Tables from Potential Susceptibility Loci Identified for Renal Cell Carcinoma by Targeting Obesity-Related Genes

Author

Xifeng Wu, Stephen J. Chanock, Nathaniel Rothman, Victoria L. Stevens, Susan M. Gapstur, Demetrius Albanes, Zhaoming Wang, Nizar M. Tannir, Christopher G. Wood, Huakang Tu, Yuanqing Ye, Mark P. Purdue, and Xiang Shu

Abstract

Table S1. Obesity relevant pathways selected from Biocarta, KEGG and Reactome pathway databases Table S2. Meta-analysis of 21 SNPs in phase I MDA-GWAS and phase II NCI-GWAS Table S3. Validation of 19 SNPs in phase III MDA-Oncoarray Table S4. Enhancer and Dnase enrichment analysis for rs4601989 Table S5. Association of previous GWAS identified susceptibility loci in the current study

Published
2023

27. Supplementary Table 2 and Supplemental Figures from Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations

Author

Rayjean J. Hung, Brian E. Henderson, Christopher A. Haiman, David J. Hunter, Douglas F. Easton, Thomas A. Sellers, Christopher I. Amos, Stephen B. Gruber, Ulrike Peters, Jian Gong, Stephen J. Chanock, Daniela Seminara, Qiyuan Li, Matthew L. Freedman, Wim Timens, David Nickle, Ma'en Obeidat, Yohan Bossé, Atsushi Takahashi, Kouya Shiraishi, Xiao-Ou Shu, Zhibin Hu, Hongbing Shen, Yongyue Wei, David C. Christiani, Jonathan P. Tyrer, Y. Ann Chen, Patrick Sulem, Kari Stefansson, Simon N. Stacey, Julius Gudmundsson, Thorunn Rafnar, Michael O. Woods, Stephen N. Thibodeau, Stephanie L. Schmit, Noralene M. Lindor, Li Li, Loïc Le Marchand, Mark Jenkins, Robert W. Haile, Steven Gallinger, Christopher K. Edlund, David V. Conti, Graham Casey, Daniel D. Buchanan, Wei Zheng, Xiaohong R. Yang, Alice S. Whittemore, Zhaoming Wang, Andre G. Uitterlinden, Clare Turnbull, Ruth C. Travis, Rulla Tamimi, Melissa C. Southey, Rita K. Schmutzler, Daniel F. Schmidt, Maria Jose Sanchez, Nazneen Rahman, Ross L. Prentice, Julian Peto, Petra H. Peeters, Heli Nevanlinna, Taru A. Muranen, Bertram Müller-Myhsok, Alfons Meindl, Enes Makalic, Eiliv Lund, Jianjun Liu, Peter Lichtner, Muhammad G. Kibriya, Rudolf Kaaks, Mattias Johansson, Astrid Irwanto, John L. Hopper, Albert Hofman, Rebecca Hein, Aditi Hazra, Per Hall, Nichola Johnson, Mia M. Gaudet, Montserrat Garcia-Closas, Olivia Fletcher, Dieter Flesch-Janys, Jonine D. Figueroa, A. Heather Eliassen, Isabel dos-Santos-Silva, Kamila Czene, Federico Canzian, Carl Blomquist, Laura Baglietto, Kristiina Aittomäki, Habibul Ahsan, Muriel A. Adank, Emily White, Martha L. Slattery, Robert E. Schoen, Polly A. Newcomb, Jonathan K. Kocarnik, Thomas J. Hudson, Jenny Chang-Claude, Andrew T. Chan, Hermann Brenner, Stephane Bezieau, Brett M. Reid, Harvey A. Risch, Jennifer B. Permuth, Ellen L. Goode, Walter C. Willett, Fredrik Wiklund, Victoria L. Stevens, Meir J. Stampfer, Kenneth Muir, Jing Ma, Zsofia Kote-Jarai, Henrik Grönberg, Edward L. Giovannucci, Sonja I. Berndt, Ali Amin Al Olama, Angela Risch, Neil Caporaso, Maria Teresa Landi, Richard S. Houlston, Heike Bickeböller, Paul Brennan, Sara Lindström, Joellen M. Schildkraut, Fredrick R. Schumacher, Nilanjan Chatterjee, Rosalind A. Eeles, Paul D. Pharoah, Peter Kraft, and Gordon Fehringer

Abstract

Table S2: Odds ratio and 95% confidence limits for cancers associated with variants with pleiotropic associations. Figure S1: Flowchart showing analysis steps. Figure S2. Manhattan plots by chromosome for individual cancer sites. Figure S3. Results for rs11571833. Figure S4: Conditional QQ-plots.

Published
2023

28. Figure legends to Figs 1 2 and 3 from Body Mass Index, Waist Circumference, Diabetes, and Risk of Liver Cancer for U.S. Adults

Author

Katherine A. McGlynn, Andrew G. Renehan, Anne Zeleniuch-Jacquotte, Jean Wactawski-Wende, Victoria L. Stevens, Alice J. Sigurdson, Howard D. Sesso, Catherine Schairer, Vikrant V. Sahasrabuddhe, Lynn Rosenberg, Kim Robien, Mark P. Purdue, Jenny N. Poynter, Jessica L. Petrick, Julie R. Palmer, Martha S. Linet, I.-Min Lee, Lindsey King, Albert R. Hollenbeck, Barry I. Graubard, Edward L. Giovannucci, J. Michael Gaziano, Mia M. Gaudet, Mridul Datta, Dawn Q. Chong, Andrew T. Chan, Julie E. Buring, Laura E. Beane Freeman, Michael C. Alavanja, Jill Koshiol, Neal D. Freedman, Christina C. Newton, and Peter T. Campbell

Abstract

figure legends for supp. figures 1, 2, and 3

Published
2023

29. Supplementary Tables for BMI, WC and diabetes with risk of liver cancer from Body Mass Index, Waist Circumference, Diabetes, and Risk of Liver Cancer for U.S. Adults

Author

Katherine A. McGlynn, Andrew G. Renehan, Anne Zeleniuch-Jacquotte, Jean Wactawski-Wende, Victoria L. Stevens, Alice J. Sigurdson, Howard D. Sesso, Catherine Schairer, Vikrant V. Sahasrabuddhe, Lynn Rosenberg, Kim Robien, Mark P. Purdue, Jenny N. Poynter, Jessica L. Petrick, Julie R. Palmer, Martha S. Linet, I.-Min Lee, Lindsey King, Albert R. Hollenbeck, Barry I. Graubard, Edward L. Giovannucci, J. Michael Gaziano, Mia M. Gaudet, Mridul Datta, Dawn Q. Chong, Andrew T. Chan, Julie E. Buring, Laura E. Beane Freeman, Michael C. Alavanja, Jill Koshiol, Neal D. Freedman, Christina C. Newton, and Peter T. Campbell

Abstract

Descriptive table or cohorts and results from sensitivity analyses

Published
2023

30. Supplementary Figure 2. Individual participant meta-analysis of waist circumference (per 5 cm) and liver cancer risk in the Liver Cancer Pooling Project from Body Mass Index, Waist Circumference, Diabetes, and Risk of Liver Cancer for U.S. Adults

Author

Katherine A. McGlynn, Andrew G. Renehan, Anne Zeleniuch-Jacquotte, Jean Wactawski-Wende, Victoria L. Stevens, Alice J. Sigurdson, Howard D. Sesso, Catherine Schairer, Vikrant V. Sahasrabuddhe, Lynn Rosenberg, Kim Robien, Mark P. Purdue, Jenny N. Poynter, Jessica L. Petrick, Julie R. Palmer, Martha S. Linet, I.-Min Lee, Lindsey King, Albert R. Hollenbeck, Barry I. Graubard, Edward L. Giovannucci, J. Michael Gaziano, Mia M. Gaudet, Mridul Datta, Dawn Q. Chong, Andrew T. Chan, Julie E. Buring, Laura E. Beane Freeman, Michael C. Alavanja, Jill Koshiol, Neal D. Freedman, Christina C. Newton, and Peter T. Campbell

Abstract

Results from individual participant meta-analysis of WC. Footnote to Supplementary Figure 2. Multivariable models include age, sex, study, alcohol, smoking, race and body mass index.

Published
2023

31. Data from Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations

Author

Rayjean J. Hung, Brian E. Henderson, Christopher A. Haiman, David J. Hunter, Douglas F. Easton, Thomas A. Sellers, Christopher I. Amos, Stephen B. Gruber, Ulrike Peters, Jian Gong, Stephen J. Chanock, Daniela Seminara, Qiyuan Li, Matthew L. Freedman, Wim Timens, David Nickle, Ma'en Obeidat, Yohan Bossé, Atsushi Takahashi, Kouya Shiraishi, Xiao-Ou Shu, Zhibin Hu, Hongbing Shen, Yongyue Wei, David C. Christiani, Jonathan P. Tyrer, Y. Ann Chen, Patrick Sulem, Kari Stefansson, Simon N. Stacey, Julius Gudmundsson, Thorunn Rafnar, Michael O. Woods, Stephen N. Thibodeau, Stephanie L. Schmit, Noralene M. Lindor, Li Li, Loïc Le Marchand, Mark Jenkins, Robert W. Haile, Steven Gallinger, Christopher K. Edlund, David V. Conti, Graham Casey, Daniel D. Buchanan, Wei Zheng, Xiaohong R. Yang, Alice S. Whittemore, Zhaoming Wang, Andre G. Uitterlinden, Clare Turnbull, Ruth C. Travis, Rulla Tamimi, Melissa C. Southey, Rita K. Schmutzler, Daniel F. Schmidt, Maria Jose Sanchez, Nazneen Rahman, Ross L. Prentice, Julian Peto, Petra H. Peeters, Heli Nevanlinna, Taru A. Muranen, Bertram Müller-Myhsok, Alfons Meindl, Enes Makalic, Eiliv Lund, Jianjun Liu, Peter Lichtner, Muhammad G. Kibriya, Rudolf Kaaks, Mattias Johansson, Astrid Irwanto, John L. Hopper, Albert Hofman, Rebecca Hein, Aditi Hazra, Per Hall, Nichola Johnson, Mia M. Gaudet, Montserrat Garcia-Closas, Olivia Fletcher, Dieter Flesch-Janys, Jonine D. Figueroa, A. Heather Eliassen, Isabel dos-Santos-Silva, Kamila Czene, Federico Canzian, Carl Blomquist, Laura Baglietto, Kristiina Aittomäki, Habibul Ahsan, Muriel A. Adank, Emily White, Martha L. Slattery, Robert E. Schoen, Polly A. Newcomb, Jonathan K. Kocarnik, Thomas J. Hudson, Jenny Chang-Claude, Andrew T. Chan, Hermann Brenner, Stephane Bezieau, Brett M. Reid, Harvey A. Risch, Jennifer B. Permuth, Ellen L. Goode, Walter C. Willett, Fredrik Wiklund, Victoria L. Stevens, Meir J. Stampfer, Kenneth Muir, Jing Ma, Zsofia Kote-Jarai, Henrik Grönberg, Edward L. Giovannucci, Sonja I. Berndt, Ali Amin Al Olama, Angela Risch, Neil Caporaso, Maria Teresa Landi, Richard S. Houlston, Heike Bickeböller, Paul Brennan, Sara Lindström, Joellen M. Schildkraut, Fredrick R. Schumacher, Nilanjan Chatterjee, Rosalind A. Eeles, Paul D. Pharoah, Peter Kraft, and Gordon Fehringer

Abstract

Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer, and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. Cancer Res; 76(17); 5103–14. ©2016 AACR.

Published
2023

32. Supplementary Figure 3. Individual participant meta-analysis of diabetes (yes versus no) and liver cancer risk in the Liver Cancer Pooling Project from Body Mass Index, Waist Circumference, Diabetes, and Risk of Liver Cancer for U.S. Adults

Author

Katherine A. McGlynn, Andrew G. Renehan, Anne Zeleniuch-Jacquotte, Jean Wactawski-Wende, Victoria L. Stevens, Alice J. Sigurdson, Howard D. Sesso, Catherine Schairer, Vikrant V. Sahasrabuddhe, Lynn Rosenberg, Kim Robien, Mark P. Purdue, Jenny N. Poynter, Jessica L. Petrick, Julie R. Palmer, Martha S. Linet, I.-Min Lee, Lindsey King, Albert R. Hollenbeck, Barry I. Graubard, Edward L. Giovannucci, J. Michael Gaziano, Mia M. Gaudet, Mridul Datta, Dawn Q. Chong, Andrew T. Chan, Julie E. Buring, Laura E. Beane Freeman, Michael C. Alavanja, Jill Koshiol, Neal D. Freedman, Christina C. Newton, and Peter T. Campbell

Abstract

Results from individual participant meta-analysis of diabetes. Multivariable models include age, sex, study, alcohol, smoking, race and body mass index.

Published
2023

34. Data from Smoking Modifies Pancreatic Cancer Risk Loci on 2q21.3

Author

Rachael Stolzenberg-Solomon, Alison P. Klein, Nilanjan Chatterjee, Peter Kraft, Harvey A. Risch, Brian M. Wolpin, Gloria M. Petersen, Eric J. Jacobs, Donghui Li, Laufey T. Amundadottir, Anne Zeleniuch-Jacquotte, Fangcheng Yuan, Herbert Yu, Lynne R. Wilkens, Nicolas Wentzensen, Jean Wactawski-Wende, Stephen K. Van Den Eeden, Antonia Trichopoulou, Anne Tjonneland, Ian M. Thompson, Oliver Strobel, Victoria L. Stevens, Debra T. Silverman, Howard D. Sesso, Ghislaine Scelo, Nathaniel Rothman, Elio Riboli, Kari G. Rabe, Miquel Porta, Ulrike Peters, Salvatore Panico, Ann L. Oberg, Kimmie Ng, Roger L. Milne, Núria Malats, I-Min Lee, Robert C. Kurtz, Rayjean J. Hung, Robert N. Hoover, Elizabeth A. Holly, Manal M. Hassan, Patricia Hartge, Michael G. Goggins, Edward L. Giovannucci, J. Michael Gaziano, Charles S. Fuchs, Eric J. Duell, Erica J. Childs, Stephen J. Chanock, Daniele Campa, Julie E. Buring, Bas Bueno-de-Mesquita, Amanda L. Blackford, Sonja I. Berndt, William R. Bamlet, Ana Babic, Gabriella Andreotti, Demetrius Albanes, Wei Zheng, Emily White, Kala Visvanathan, Xiao-Ou Shu, Rachel E. Neale, Loic Le Marchand, Charles Kooperberg, Phyllis J. Goodman, Graham G. Giles, Steven Gallinger, Mengmeng Du, Federico Canzian, Paul Brennan, Paige M. Bracci, Laura E. Beane-Freeman, Alan A. Arslan, William Wheeler, Prosenjit Kundu, and Evelina Mocci

Abstract

Germline variation and smoking are independently associated with pancreatic ductal adenocarcinoma (PDAC). We conducted genome-wide smoking interaction analysis of PDAC using genotype data from four previous genome-wide association studies in individuals of European ancestry (7,937 cases and 11,774 controls). Examination of expression quantitative trait loci data from the Genotype-Tissue Expression Project followed by colocalization analysis was conducted to determine whether there was support for common SNP(s) underlying the observed associations. Statistical tests were two sided and P < 5 × 10–8 was considered statistically significant. Genome-wide significant evidence of qualitative interaction was identified on chr2q21.3 in intron 5 of the transmembrane protein 163 (TMEM163) and upstream of the cyclin T2 (CCNT2). The most significant SNP using the Empirical Bayes method, in this region that included 45 significantly associated SNPs, was rs1818613 [per allele OR in never smokers 0.87, 95% confidence interval (CI), 0.82–0.93; former smokers 1.00, 95% CI, 0.91–1.07; current smokers 1.25, 95% CI 1.12–1.40, Pinteraction = 3.08 × 10–9). Examination of the Genotype-Tissue Expression Project data demonstrated an expression quantitative trait locus in this region for TMEM163 and CCNT2 in several tissue types. Colocalization analysis supported a shared SNP, rs842357, in high linkage disequilibrium with rs1818613 (r2 = 0. 94) driving both the observed interaction and the expression quantitative trait loci signals. Future studies are needed to confirm and understand the differential biologic mechanisms by smoking status that contribute to our PDAC findings.Significance:This large genome-wide interaction study identifies a susceptibility locus on 2q21.3 that significantly modified PDAC risk by smoking status, providing insight into smoking-associated PDAC, with implications for prevention.

Published
2023

35. Supplementary table 8 from Smoking Modifies Pancreatic Cancer Risk Loci on 2q21.3

Author

Rachael Stolzenberg-Solomon, Alison P. Klein, Nilanjan Chatterjee, Peter Kraft, Harvey A. Risch, Brian M. Wolpin, Gloria M. Petersen, Eric J. Jacobs, Donghui Li, Laufey T. Amundadottir, Anne Zeleniuch-Jacquotte, Fangcheng Yuan, Herbert Yu, Lynne R. Wilkens, Nicolas Wentzensen, Jean Wactawski-Wende, Stephen K. Van Den Eeden, Antonia Trichopoulou, Anne Tjonneland, Ian M. Thompson, Oliver Strobel, Victoria L. Stevens, Debra T. Silverman, Howard D. Sesso, Ghislaine Scelo, Nathaniel Rothman, Elio Riboli, Kari G. Rabe, Miquel Porta, Ulrike Peters, Salvatore Panico, Ann L. Oberg, Kimmie Ng, Roger L. Milne, Núria Malats, I-Min Lee, Robert C. Kurtz, Rayjean J. Hung, Robert N. Hoover, Elizabeth A. Holly, Manal M. Hassan, Patricia Hartge, Michael G. Goggins, Edward L. Giovannucci, J. Michael Gaziano, Charles S. Fuchs, Eric J. Duell, Erica J. Childs, Stephen J. Chanock, Daniele Campa, Julie E. Buring, Bas Bueno-de-Mesquita, Amanda L. Blackford, Sonja I. Berndt, William R. Bamlet, Ana Babic, Gabriella Andreotti, Demetrius Albanes, Wei Zheng, Emily White, Kala Visvanathan, Xiao-Ou Shu, Rachel E. Neale, Loic Le Marchand, Charles Kooperberg, Phyllis J. Goodman, Graham G. Giles, Steven Gallinger, Mengmeng Du, Federico Canzian, Paul Brennan, Paige M. Bracci, Laura E. Beane-Freeman, Alan A. Arslan, William Wheeler, Prosenjit Kundu, and Evelina Mocci

Abstract

Supplemental Table 8. Enrichment in regulatory regions for rs842357 and related SNPs

Published
2023

36. Supplementary Figure 1. Individual participant meta-analysis of body mass index (per 5 kg/m2) and liver cancer risk in the Liver Cancer Pooling Project from Body Mass Index, Waist Circumference, Diabetes, and Risk of Liver Cancer for U.S. Adults

Author

Katherine A. McGlynn, Andrew G. Renehan, Anne Zeleniuch-Jacquotte, Jean Wactawski-Wende, Victoria L. Stevens, Alice J. Sigurdson, Howard D. Sesso, Catherine Schairer, Vikrant V. Sahasrabuddhe, Lynn Rosenberg, Kim Robien, Mark P. Purdue, Jenny N. Poynter, Jessica L. Petrick, Julie R. Palmer, Martha S. Linet, I.-Min Lee, Lindsey King, Albert R. Hollenbeck, Barry I. Graubard, Edward L. Giovannucci, J. Michael Gaziano, Mia M. Gaudet, Mridul Datta, Dawn Q. Chong, Andrew T. Chan, Julie E. Buring, Laura E. Beane Freeman, Michael C. Alavanja, Jill Koshiol, Neal D. Freedman, Christina C. Newton, and Peter T. Campbell

Abstract

Results from individual participant meta-analysis of BMI. Multivariable models include age, sex, study, alcohol, smoking, and race.

Published
2023

37. Data from Genome-Wide Association Study of Prostate Cancer–Specific Survival

Author

Fredrik Wiklund, Sara Lindström, Johanna Schleutker, Lovise Maehle, David G. Cox, Anne Tjønneland, Bas H. Bueno-de-Mesquita, Antonia Trichopoulou, Stephanie J. Weinstein, Victoria L. Stevens, Meir J. Stampfer, Kathryn L. Penney, Alison M. Mondul, Jing Ma, Loic Le Marchand, Peter Kraft, David J. Hunter, Edward L. Giovannucci, Susan M. Gapstur, Stephen Chanock, Sonja I. Berndt, Gerald L. Andriole, Demetrius Albanes, Judith A. Clements, Jyotsna Batra, Andrzej Kierzek, Agnieszka Michael, Hardev Pandha, Sofia Maia, Paula Paulo, Manuel R. Teixeira, Amanda Spurdle, Vanio I. Mitev, Radka P. Kaneva, Chavdar Slavov, Hui-Yi Lim, Thomas A. Sellers, Jong Y. Park, Bernd Holleczek, Volker Herrmann, Hermann Brenner, Lisa Cannon-Albright, Wojciech Kluźniak, Jan Lubiński, Cezary Cybulski, Adam S. Kibel, Kathleen Herkommer, Manuel Luedeke, Walther Vogel, Christiane Maier, Daniel J. Schaid, Shannon K. McDonnell, Stephen N. Thibodeau, Janet L. Stanford, Kay-Tee Khaw, Nora Pashayan, Paul D.P. Pharoah, Freddie C. Hamdy, Jenny L. Donovan, David E. Neal, Ruth C. Travis, Timothy J. Key, Børge G. Nordestgaard, Teuvo L.J. Tammela, Csilla Sipeky, Christopher A. Haiman, Fredrick R. Schumacher, Brian E. Henderson, Liesel M. FitzGerald, Melissa C. Southey, Graham G. Giles, Kenneth Muir, Sara Benlloch, Ali Amin Al Olama, Zsofia Kote-Jarai, Douglas F. Easton, Rosalind A. Eeles, Henrik Gronberg, Markus Aly, Thomas Whitington, Robert Karlsson, and Robert Szulkin

Abstract

Background: Unnecessary intervention and overtreatment of indolent disease are common challenges in clinical management of prostate cancer. Improved tools to distinguish lethal from indolent disease are critical.Methods: We performed a genome-wide survival analysis of cause-specific death in 24,023 prostate cancer patients (3,513 disease-specific deaths) from the PRACTICAL and BPC3 consortia. Top findings were assessed for replication in a Norwegian cohort (CONOR).Results: We observed no significant association between genetic variants and prostate cancer survival.Conclusions: Common genetic variants with large impact on prostate cancer survival were not observed in this study.Impact: Future studies should be designed for identification of rare variants with large effect sizes or common variants with small effect sizes. Cancer Epidemiol Biomarkers Prev; 24(11); 1796–800. ©2015 AACR.

Published
2023

38. Supplementary Table 1 from Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations

Author

Rayjean J. Hung, Brian E. Henderson, Christopher A. Haiman, David J. Hunter, Douglas F. Easton, Thomas A. Sellers, Christopher I. Amos, Stephen B. Gruber, Ulrike Peters, Jian Gong, Stephen J. Chanock, Daniela Seminara, Qiyuan Li, Matthew L. Freedman, Wim Timens, David Nickle, Ma'en Obeidat, Yohan Bossé, Atsushi Takahashi, Kouya Shiraishi, Xiao-Ou Shu, Zhibin Hu, Hongbing Shen, Yongyue Wei, David C. Christiani, Jonathan P. Tyrer, Y. Ann Chen, Patrick Sulem, Kari Stefansson, Simon N. Stacey, Julius Gudmundsson, Thorunn Rafnar, Michael O. Woods, Stephen N. Thibodeau, Stephanie L. Schmit, Noralene M. Lindor, Li Li, Loïc Le Marchand, Mark Jenkins, Robert W. Haile, Steven Gallinger, Christopher K. Edlund, David V. Conti, Graham Casey, Daniel D. Buchanan, Wei Zheng, Xiaohong R. Yang, Alice S. Whittemore, Zhaoming Wang, Andre G. Uitterlinden, Clare Turnbull, Ruth C. Travis, Rulla Tamimi, Melissa C. Southey, Rita K. Schmutzler, Daniel F. Schmidt, Maria Jose Sanchez, Nazneen Rahman, Ross L. Prentice, Julian Peto, Petra H. Peeters, Heli Nevanlinna, Taru A. Muranen, Bertram Müller-Myhsok, Alfons Meindl, Enes Makalic, Eiliv Lund, Jianjun Liu, Peter Lichtner, Muhammad G. Kibriya, Rudolf Kaaks, Mattias Johansson, Astrid Irwanto, John L. Hopper, Albert Hofman, Rebecca Hein, Aditi Hazra, Per Hall, Nichola Johnson, Mia M. Gaudet, Montserrat Garcia-Closas, Olivia Fletcher, Dieter Flesch-Janys, Jonine D. Figueroa, A. Heather Eliassen, Isabel dos-Santos-Silva, Kamila Czene, Federico Canzian, Carl Blomquist, Laura Baglietto, Kristiina Aittomäki, Habibul Ahsan, Muriel A. Adank, Emily White, Martha L. Slattery, Robert E. Schoen, Polly A. Newcomb, Jonathan K. Kocarnik, Thomas J. Hudson, Jenny Chang-Claude, Andrew T. Chan, Hermann Brenner, Stephane Bezieau, Brett M. Reid, Harvey A. Risch, Jennifer B. Permuth, Ellen L. Goode, Walter C. Willett, Fredrik Wiklund, Victoria L. Stevens, Meir J. Stampfer, Kenneth Muir, Jing Ma, Zsofia Kote-Jarai, Henrik Grönberg, Edward L. Giovannucci, Sonja I. Berndt, Ali Amin Al Olama, Angela Risch, Neil Caporaso, Maria Teresa Landi, Richard S. Houlston, Heike Bickeböller, Paul Brennan, Sara Lindström, Joellen M. Schildkraut, Fredrick R. Schumacher, Nilanjan Chatterjee, Rosalind A. Eeles, Paul D. Pharoah, Peter Kraft, and Gordon Fehringer

Abstract

Variants selected for replication

Published
2023

39. Supplementary Material: Funding, Acknowledgements, Consortia, and Bioinformatics Tools Funding sources from Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations

Author

Rayjean J. Hung, Brian E. Henderson, Christopher A. Haiman, David J. Hunter, Douglas F. Easton, Thomas A. Sellers, Christopher I. Amos, Stephen B. Gruber, Ulrike Peters, Jian Gong, Stephen J. Chanock, Daniela Seminara, Qiyuan Li, Matthew L. Freedman, Wim Timens, David Nickle, Ma'en Obeidat, Yohan Bossé, Atsushi Takahashi, Kouya Shiraishi, Xiao-Ou Shu, Zhibin Hu, Hongbing Shen, Yongyue Wei, David C. Christiani, Jonathan P. Tyrer, Y. Ann Chen, Patrick Sulem, Kari Stefansson, Simon N. Stacey, Julius Gudmundsson, Thorunn Rafnar, Michael O. Woods, Stephen N. Thibodeau, Stephanie L. Schmit, Noralene M. Lindor, Li Li, Loïc Le Marchand, Mark Jenkins, Robert W. Haile, Steven Gallinger, Christopher K. Edlund, David V. Conti, Graham Casey, Daniel D. Buchanan, Wei Zheng, Xiaohong R. Yang, Alice S. Whittemore, Zhaoming Wang, Andre G. Uitterlinden, Clare Turnbull, Ruth C. Travis, Rulla Tamimi, Melissa C. Southey, Rita K. Schmutzler, Daniel F. Schmidt, Maria Jose Sanchez, Nazneen Rahman, Ross L. Prentice, Julian Peto, Petra H. Peeters, Heli Nevanlinna, Taru A. Muranen, Bertram Müller-Myhsok, Alfons Meindl, Enes Makalic, Eiliv Lund, Jianjun Liu, Peter Lichtner, Muhammad G. Kibriya, Rudolf Kaaks, Mattias Johansson, Astrid Irwanto, John L. Hopper, Albert Hofman, Rebecca Hein, Aditi Hazra, Per Hall, Nichola Johnson, Mia M. Gaudet, Montserrat Garcia-Closas, Olivia Fletcher, Dieter Flesch-Janys, Jonine D. Figueroa, A. Heather Eliassen, Isabel dos-Santos-Silva, Kamila Czene, Federico Canzian, Carl Blomquist, Laura Baglietto, Kristiina Aittomäki, Habibul Ahsan, Muriel A. Adank, Emily White, Martha L. Slattery, Robert E. Schoen, Polly A. Newcomb, Jonathan K. Kocarnik, Thomas J. Hudson, Jenny Chang-Claude, Andrew T. Chan, Hermann Brenner, Stephane Bezieau, Brett M. Reid, Harvey A. Risch, Jennifer B. Permuth, Ellen L. Goode, Walter C. Willett, Fredrik Wiklund, Victoria L. Stevens, Meir J. Stampfer, Kenneth Muir, Jing Ma, Zsofia Kote-Jarai, Henrik Grönberg, Edward L. Giovannucci, Sonja I. Berndt, Ali Amin Al Olama, Angela Risch, Neil Caporaso, Maria Teresa Landi, Richard S. Houlston, Heike Bickeböller, Paul Brennan, Sara Lindström, Joellen M. Schildkraut, Fredrick R. Schumacher, Nilanjan Chatterjee, Rosalind A. Eeles, Paul D. Pharoah, Peter Kraft, and Gordon Fehringer

Abstract

Funding sources, acknowledgements, consortia involved in study and bioinformatics tools used

Published
2023

40. Evaluation of pre-diagnostic blood protein measurements for predicting survival after lung cancer diagnosis

Author

Xiaoshuang Feng, David C. Muller, Hana Zahed, Karine Alcala, Florence Guida, Karl Smith-Byrne, Jian-Min Yuan, Woon-Puay Koh, Renwei Wang, Roger L. Milne, Julie K. Bassett, Arnulf Langhammer, Kristian Hveem, Victoria L. Stevens, Ying Wang, Mikael Johansson, Anne Tjønneland, Rosario Tumino, Mahdi Sheikh, Mattias Johansson, and Hilary A. Robbins

Subjects
Cancer och onkologi, Protein biomarkers, Cancer and Oncology, General Medicine, Lung cancer, Lung cancer survival, General Biochemistry, Genetics and Molecular Biology, Lung cancer prognosis
Abstract

BackgroundTo evaluate whether circulating proteins are associated with survival after lung cancer diagnosis, and whether they can improve prediction of prognosis.MethodsWe measured up to 1159 proteins in blood samples from 708 participants in 6 cohorts. Samples were collected within 3 years prior to lung cancer diagnosis. We used Cox proportional hazards models to identify proteins associated with overall mortality after lung cancer diagnosis. To evaluate model performance, we used a round-robin approach in which models were fit in 5 cohorts and evaluated in the 6th cohort. Specifically, we fit a model including 5 proteins and clinical parameters and compared its performance with clinical parameters only.FindingsThere were 86 proteins nominally associated with mortality (p < 0.05), but only CDCP1 remained statistically significant after accounting for multiple testing (hazard ratio per standard deviation: 1.19, 95% CI: 1.10–1.30, unadjusted p = 0.00004). The external C-index for the protein-based model was 0.63 (95% CI: 0.61–0.66), compared with 0.62 (95% CI: 0.59–0.64) for the model with clinical parameters only. Inclusion of proteins did not provide a statistically significant improvement in discrimination (C-index difference: 0.015, 95% CI: −0.003 to 0.035).InterpretationBlood proteins measured within 3 years prior to lung cancer diagnosis were not strongly associated with lung cancer survival, nor did they importantly improve prediction of prognosis beyond clinical information.FundingNo explicit funding for this study. Authors and data collection supported by the US National Cancer Institute (U19CA203654), INCA (France, 2019-1-TABAC-01), Cancer Research Foundation of Northern Sweden (AMP19-962), and Swedish Department of Health Ministry. Background: To evaluate whether circulating proteins are associated with survival after lung cancer diagnosis, and whether they can improve prediction of prognosis. Methods: We measured up to 1159 proteins in blood samples from 708 participants in 6 cohorts. Samples were collected within 3 years prior to lung cancer diagnosis. We used Cox proportional hazards models to identify proteins associated with overall mortality after lung cancer diagnosis. To evaluate model performance, we used a round-robin approach in which models were fit in 5 cohorts and evaluated in the 6th cohort. Specifically, we fit a model including 5 proteins and clinical parameters and compared its performance with clinical parameters only. Findings: There were 86 proteins nominally associated with mortality (p < 0.05), but only CDCP1 remained statistically significant after accounting for multiple testing (hazard ratio per standard deviation: 1.19, 95% CI: 1.10–1.30, unadjusted p = 0.00004). The external C-index for the protein-based model was 0.63 (95% CI: 0.61–0.66), compared with 0.62 (95% CI: 0.59–0.64) for the model with clinical parameters only. Inclusion of proteins did not provide a statistically significant improvement in discrimination (C-index difference: 0.015, 95% CI: −0.003 to 0.035). Interpretation: Blood proteins measured within 3 years prior to lung cancer diagnosis were not strongly associated with lung cancer survival, nor did they importantly improve prediction of prognosis beyond clinical information. Funding: No explicit funding for this study. Authors and data collection supported by the US National Cancer Institute ( U19CA203654), INCA (France, 2019-1-TABAC-01), Cancer Research Foundation of Northern Sweden ( AMP19-962), and Swedish Department of Health Ministry.

Published
2023

41. Association between Smoking Cannabis and Quitting Cigarettes in a Large American Cancer Society Cohort

Author

Kassandra I. Alcaraz, Christina C. Newton, Eric J. Jacobs, Sara Strollo, Brian D. Carter, W. Dana Flanders, J. Lee Westmaas, Johannes Thrul, W. Ryan Diver, Alpa V. Patel, and Victoria L. Stevens

Subjects
Adult, Male, Longitudinal study, Epidemiology, medicine.medical_treatment, Population, Marijuana Smoking, Intention, Cigarette Smoking, medicine, Humans, Longitudinal Studies, education, education.field_of_study, Cannabis smoking, Cancer prevention, biology, business.industry, Middle Aged, biology.organism_classification, Confidence interval, Cross-Sectional Studies, Oncology, Cohort, Smoking cessation, Female, Smoking Cessation, Cannabis, business, Follow-Up Studies, Demography
Abstract

Background: Cannabis use is increasing, including among smokers, an at-risk population for cancer. Research is equivocal on whether using cannabis inhibits quitting cigarettes. The current longitudinal study investigated associations between smoking cannabis and subsequently quitting cigarettes. Methods: Participants were 4,535 adult cigarette smokers from a cohort enrolled in the American Cancer Society's Cancer Prevention Study-3 in 2009–2013. Cigarette quitting was assessed on a follow-up survey in 2015–2017, an average of 3.1 years later. Rates of quitting cigarettes at follow-up were examined by retrospectively assessed baseline cannabis smoking status (never, former, recent), and by frequency of cannabis smoking among recent cannabis smokers (low: ≤3 days/month; medium: 4–19 days/month; high: ≥20 days/month). Logistic regression models adjusted for sociodemographic factors, smoking- and health-related behaviors, and time between baseline and follow-up. Results: Adjusted cigarette quitting rates at follow-up did not differ significantly by baseline cannabis smoking status [never 36.2%, 95% confidence interval (CI), 34.5–37.8; former 34.1%, CI, 31.4–37.0; recent 33.6%, CI, 30.1–37.3], nor by frequency of cannabis smoking (low 31.4%, CI, 25.6–37.3; moderate 36.7%, CI, 30.7–42.3; high 34.4%, CI, 28.3–40.2) among recent baseline cannabis smokers. In cross-sectional analyses conducted at follow-up, the proportion of cigarette smokers intending to quit smoking cigarettes in the next 30 days did not differ by cannabis smoking status (P = 0.83). Conclusions: Results do not support the hypothesis that cannabis smoking inhibits quitting cigarette smoking among adults. Impact: Future longitudinal research should include follow-ups of >1 year, and assess effects of intensity/frequency of cannabis use and motivation to quit on smoking cessation.

Published
2021

42. The Cancer Prevention Study-3 FFQ Is a Reliable and Valid Measure of Nutrient Intakes among Racial/Ethnic Subgroups, Compared with 24-Hour Recalls and Biomarkers

Author

Alpa V. Patel, Laura Sampson, Victoria L. Stevens, Terryl J. Hartman, Diane C. Mitchell, Rebecca A Hodge, Marjorie L. McCullough, W. Dana Flanders, and Ying Wang

Subjects
Adult, Male, 0301 basic medicine, Vitamin, Nutritional Status, Medicine (miscellaneous), Spearman's rank correlation coefficient, Cohort Studies, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Nutrient, Neoplasms, Surveys and Questionnaires, Ethnicity, Humans, Medicine, Prospective Studies, 030212 general & internal medicine, Prospective cohort study, Reproducibility, 030109 nutrition & dietetics, Nutrition and Dietetics, Cancer prevention, business.industry, Data Collection, Racial Groups, Food frequency questionnaire, Middle Aged, Diet Records, Diet, chemistry, Mental Recall, Cohort, Female, business, Biomarkers, Demography
Abstract

Background Valid assessment of dietary intake in diverse populations is important for studies of chronic disease risk in the United States. Objectives We evaluated the reproducibility and validity of a food frequency questionnaire (FFQ) modified for the American Cancer Society's Cancer Prevention Study-3 (CPS-3) prospective cohort, among a racially/ethnically diverse subgroup. Methods The Diet Assessment Substudy included 677 CPS-3 participants (64% women; 61% non-Hispanic white, 24% non-Hispanic black, 15% Hispanic), aged 31-70 y, who completed 2 FFQs 1 y apart (FFQ1, FFQ2), 4-6 telephone-administered 24-h dietary recalls (24HRs), and 2 fasting blood samples and 24-h urine collections ∼6 mo apart in the interim. Spearman rank correlation coefficients (ρ) were used to evaluate FFQ reproducibility and validity compared with 24HRs for 67 nutrient exposures. For 18 of these nutrients, we used the method of triads to calculate validity coefficients (VCs, ρ) from pairwise correlations of FFQ2, 24HRs, and biomarkers. Analyses were stratified by sex, race/ethnicity, education, and BMI. Results Mean (range) FFQ reproducibility correlations were ρ = 0.65 (0.50-0.91) for men and ρ = 0.63 (0.37-0.89) for women; mean (range) energy-adjusted, deattenuated correlations of FFQ2 with 24HRs were ρ = 0.60 (0.33-0.84) for men and ρ = 0.55 (0.21-0.79) for women. FFQ2 VCs (ρ) among men ranged from 0.42 for β-cryptoxanthin to 0.91 for omega-3 (n-3) fatty acids and, among women, from 0.41 for sodium to 0.79 for total vitamin D. Mean FFQ reproducibility and validity were highest among whites (ρ = 0.68, ρ = 0.58, respectively) and slightly lower among blacks (ρ = 0.57, ρ = 0.49, respectively) and Hispanics (ρ = 0.59, 0.55, respectively). FFQ reproducibility and validity were slightly lower among those with less than a 4-y college degree, and those with a BMI ≥30 kg/m2. Conclusions Reproducibility and validity of the CPS-3 FFQ were comparable with similar studies for most nutrients, among all subgroups. These findings support future dietary analyses in the contemporary CPS-3 cohort and other similar cohorts.

Published
2021

43. Smoking Modifies Pancreatic Cancer Risk Loci on 2q21.3

Author

Mengmeng Du, Rachael Z. Stolzenberg-Solomon, Herbert Yu, Paige M. Bracci, Antonia Trichopoulou, Anne Tjønneland, Eric J. Duell, Bas Bueno-de-Mesquita, Alison P. Klein, Graham G. Giles, Fangcheng Yuan, Howard D. Sesso, Federico Canzian, Sonja I. Berndt, I-Min Lee, Ghislaine Scelo, Lynne R. Wilkens, Jean Wactawski-Wende, Nicolas Wentzensen, Kari G. Rabe, Laufey T. Amundadottir, Eric J. Jacobs, Victoria L. Stevens, Phyllis J. Goodman, Harvey A. Risch, Edward Giovannucci, Evelina Mocci, Stephen K. Van Den Eeden, Stephen J. Chanock, Ann L. Oberg, Gloria M. Petersen, Rayjean J. Hung, Robert C. Kurtz, Xiao-Ou Shu, Charles Kooperberg, Charles S. Fuchs, Nilanjan Chatterjee, Nathaniel Rothman, Ulrike Peters, Núria Malats, Kimmie Ng, Ian M. Thompson, Roger L. Milne, William Wheeler, Paul Brennan, Emily White, J. Michael Gaziano, Steven Gallinger, Prosenjit Kundu, Wei Zheng, Miquel Porta, Brian M. Wolpin, Kala Visvanathan, Loic Le Marchand, Elio Riboli, Oliver Strobel, Michael Goggins, Daniele Campa, Salvatore Panico, Rachel E. Neale, Laura E. Beane Freeman, Gabriella Andreotti, Debra T. Silverman, Ana Babic, Erica J. Childs, Donghui Li, Julie E. Buring, Patricia Hartge, Manal M. Hassan, Alan A. Arslan, Robert N. Hoover, Amanda L. Blackford, Anne Zeleniuch-Jacquotte, Demetrius Albanes, William R. Bamlet, Peter Kraft, and Elizabeth A. Holly

Subjects
0301 basic medicine, Oncology, Cancer Research, medicine.medical_specialty, Pancreatic ductal adenocarcinoma, Genotype, Quantitative Trait Loci, Polymorphism, Single Nucleotide, Article, Chromosomes, Germline, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Pancreatic cancer, Internal medicine, medicine, Humans, SNP, Genetic Predisposition to Disease, Polymorphism, Genetic association, business.industry, Cyclin T, Carcinoma, Smoking, Membrane Proteins, Colocalization, Single Nucleotide, medicine.disease, Pancreatic Neoplasms, 030104 developmental biology, Pancreatic Ductal, Chromosomes, Human, Pair 2, 030220 oncology & carcinogenesis, Pair 2, Expression quantitative trait loci, Carcinoma, Pancreatic Ductal, Genome-Wide Association Study, business, Human
Abstract

Germline variation and smoking are independently associated with pancreatic ductal adenocarcinoma (PDAC). We conducted genome-wide smoking interaction analysis of PDAC using genotype data from four previous genome-wide association studies in individuals of European ancestry (7,937 cases and 11,774 controls). Examination of expression quantitative trait loci data from the Genotype-Tissue Expression Project followed by colocalization analysis was conducted to determine whether there was support for common SNP(s) underlying the observed associations. Statistical tests were two sided and P < 5 × 10–8 was considered statistically significant. Genome-wide significant evidence of qualitative interaction was identified on chr2q21.3 in intron 5 of the transmembrane protein 163 (TMEM163) and upstream of the cyclin T2 (CCNT2). The most significant SNP using the Empirical Bayes method, in this region that included 45 significantly associated SNPs, was rs1818613 [per allele OR in never smokers 0.87, 95% confidence interval (CI), 0.82–0.93; former smokers 1.00, 95% CI, 0.91–1.07; current smokers 1.25, 95% CI 1.12–1.40, Pinteraction = 3.08 × 10–9). Examination of the Genotype-Tissue Expression Project data demonstrated an expression quantitative trait locus in this region for TMEM163 and CCNT2 in several tissue types. Colocalization analysis supported a shared SNP, rs842357, in high linkage disequilibrium with rs1818613 (r2 = 0. 94) driving both the observed interaction and the expression quantitative trait loci signals. Future studies are needed to confirm and understand the differential biologic mechanisms by smoking status that contribute to our PDAC findings. Significance: This large genome-wide interaction study identifies a susceptibility locus on 2q21.3 that significantly modified PDAC risk by smoking status, providing insight into smoking-associated PDAC, with implications for prevention.

Published
2021

44. Plasma Metabolomic Profiles and Risk of Advanced and Fatal Prostate Cancer

Author

Victoria L. Stevens, Brian D. Carter, Eric J. Jacobs, Susan M. Gapstur, and Ying Wang

Subjects
Male, Oncology, medicine.medical_specialty, Urology, 030232 urology & nephrology, Cohort Studies, 03 medical and health sciences, Prostate cancer, 0302 clinical medicine, Metabolomics, Internal medicine, Cox proportional hazards regression, medicine, Humans, Radiology, Nuclear Medicine and imaging, Prospective Studies, Patient summary, Cancer prevention, business.industry, Prostatic Neoplasms, medicine.disease, 030220 oncology & carcinogenesis, Cohort, Etiology, Surgery, business, Follow-Up Studies, Cohort study
Abstract

Little is known about the underlying molecular mechanisms of prostate cancer, especially advanced and fatal prostate cancer.To examine associations of prediagnostic plasma metabolomic profiles with advanced and fatal prostate cancer.In a case-cohort study of the Cancer Prevention Study-II Nutrition Cohort, of 14 210 cancer-free men with a blood sample in 1998-2001, 129 were diagnosed with advanced prostate cancer (T3-T4 or N1 or M1) through June 2013 and 112 died from prostate cancer through December 2014. Plasma samples from advanced and fatal cases, and a randomly selected subcohort of 347 men were metabolically profiled using untargeted mass spectroscopy-based platforms.Prentice-weighted Cox proportional hazards regression models were used to assess associations of 699 known metabolites with advanced and fatal prostate cancer.Two metabolites derived from fatty acid metabolism (ethylmalonate and butyrylcarnitine), aspartate, sphingomyelin (d18:1/18:0), and two γ-glutamyl amino acids (γ-glutamylmethionine and γ-glutamylglutamine) were statistically significantly associated (false discovery rate0.2) with fatal prostate cancer. One standard deviation (SD) increase in each γ-glutamyl amino acid was associated with 34-38% decreased risk, whereas one SD increase in each of the other metabolites was associated with 45-53% increased risk. A metabolic risk score based on four of these metabolites (excluding butyrylcarnitine and γ-glutamylglutamine, which were not independent predictors) was strongly associated with fatal prostate cancer (relative risk per SD: 2.72, 95% confidence interval: 2.05-3.60). No metabolites were statistically significantly associated with advanced prostate cancer. These results were observational and may not be causal.These findings identified metabolic pathways that are altered in the development of fatal prostate cancer. Further research into these pathways may provide insights into the etiology of fatal prostate cancer.In a large follow-up study of cancer-free men, those with a certain metabolomic profile had a higher risk of dying from prostate cancer.

Published
2021

45. Comprehensive functional annotation of susceptibility variants identifies genetic heterogeneity between lung adenocarcinoma and squamous cell carcinoma

Author

Tongtong Hong, Christopher I. Amos, Shan Zienolddiny, Hongxia Ma, Matthew B. Schabath, John K. Field, David C. Christiani, Hongbing Shen, Angela Risch, Lambertus A. Kiemeney, Sanjay Shete, Chu Chen, Maria Teresa Landi, Susanne M. Arnold, H-Erich Wichmann, Neil E. Caporaso, Adonina Tardón, Mikael Johansson, Philip Lazarus, Meng Zhu, Heike Bickeböller, Penella J. Woll, Kjell Grankvist, Mattias Johansson, Rayjean J. Hung, Stig E. Bojesen, Gary E. Goodman, Guangfu Jin, Hans Brunnström, Stephen Lam, Juncheng Dai, Victoria L. Stevens, Na Qin, Yuancheng Li, Zhibin Hu, Cheng Wang, Gadi Rennert, Demetrius Albanes, Geoffrey Liu, Loic Le Marchand, Angeline S. Andrew, Melinda C. Aldrich, Olle Melander, and Paul Brennan

Subjects
0301 basic medicine, Lung Neoplasms, Adenocarcinoma of Lung, Genome-wide association study, Computational biology, Biology, Polymorphism, Single Nucleotide, Article, Transcriptome, Genetic Heterogeneity, 03 medical and health sciences, 0302 clinical medicine, Carcinoma, Non-Small-Cell Lung, Genotype, medicine, Humans, Genetic Predisposition to Disease, Gene, Epigenomics, Genetic association, Genetic heterogeneity, General Medicine, medicine.disease, 030104 developmental biology, Urological cancers Radboud Institute for Health Sciences [Radboudumc 15], 030220 oncology & carcinogenesis, Carcinoma, Squamous Cell, Adenocarcinoma, Genome-Wide Association Study
Abstract

Although genome-wide association studies have identified more than eighty genetic variants associated with non-small cell lung cancer (NSCLC) risk, biological mechanisms of these variants remain largely unknown. By integrating a large-scale genotype data of 15 581 lung adenocarcinoma (AD) cases, 8350 squamous cell carcinoma (SqCC) cases, and 27 355 controls, as well as multiple transcriptome and epigenomic databases, we conducted histology-specific meta-analyses and functional annotations of both reported and novel susceptibility variants. We identified 3064 credible risk variants for NSCLC, which were overrepresented in enhancer-like and promoter-like histone modification peaks as well as DNase I hypersensitive sites. Transcription factor enrichment analysis revealed that USF1 was AD-specific while CREB1 was SqCC-specific. Functional annotation and gene-based analysis implicated 894 target genes, including 274 specifics for AD and 123 for SqCC, which were overrepresented in somatic driver genes (ER = 1.95, P = 0.005). Pathway enrichment analysis and Gene-Set Enrichment Analysis revealed that AD genes were primarily involved in immune-related pathways, while SqCC genes were homologous recombination deficiency related. Our results illustrate the molecular basis of both well-studied and new susceptibility loci of NSCLC, providing not only novel insights into the genetic heterogeneity between AD and SqCC but also a set of plausible gene targets for post-GWAS functional experiments.

Published
2021

46. Design and methodological considerations for biomarker discovery and validation in the Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) Program

Author

Hilary A Robbins, Karine Alcala, Elham Khodayari Moez, Florence Guida, Sera Thomas, Hana Zahed, Matthew Warkentin, Karl Smith-Byrne, Yonathan Brhane, David Muller, Demetrius Albanes, Melinda C Aldrich, Alan A Arslan, Julie Bassett, Christine D Berg, Qiuyin Cai, Chu Chen, Michael PA Davies, Brenda Diergaarde, John K Field, Neal D Freedman, Wen-Yi Huang, Mikael Johansson, Michael Jones, Woon-Puay Koh, Stephen Lam, Qing Lan, Arnulf Langhammer, Linda M Liao, Geoffrey Liu, Reza Malekzadeh, Roger L Milne, Luis M Montuenga, Thomas Rohan, Howard D Sesso, Gianluca Severi, Mahdi Sheikh, Rashmi Sinha, Xiao-Ou Shu, Victoria L Stevens, Martin C Tammemägi, Lesley F Tinker, Kala Visvanathan, Ying Wang, Renwei Wang, Stephanie J Weinstein, Emily White, David Wilson, Jian-Min Yuan, Xuehong Zhang, Wei Zheng, Christopher I Amos, Paul Brennan, Mattias Johansson, and Rayjean J Hung

Abstract

The Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) program is an NCI-funded initiative with an objective to develop tools to optimize lung cancer screening. Here, we describe the rationale and design for the Risk Biomarker and Nodule Malignancy projects within INTEGRAL. The overarching goal of these projects is to systematically investigate circulating protein markers to include on a panel for use (i) pre-LDCT, to identify people likely to benefit from screening, and (ii) post-LDCT, to differentiate benign versus malignant nodules. To identify informative proteins, the Risk Biomarker project measured 1,161 proteins in a nested-case control study within 2 prospective cohorts (n=252 lung cancer cases and 252 controls) and replicated associations for a subset of proteins in 4 cohorts (n=479 cases and 479 controls). Eligible participants had any history of smoking and cases were diagnosed within 3 years of blood draw. The Nodule Malignancy project measured 1,077 proteins among participants with a heavy smoking history within 4 LDCT screening studies (n=425 cases within 5 years of blood draw, 398 benign-nodule controls, and 430 nodule-free controls). The INTEGRAL panel will enable absolute quantification of 21 proteins. We will evaluate its lung cancer discriminative performance in the Risk Biomarker project using a case-cohort study including 14 cohorts (n=1,696 cases and 2,926 subcohort representatives), and in the Nodule Malignancy project within 5 LDCT screening studies (n=675 cases, 648 benign-nodule controls, and 680 nodule-free controls). Future progress to advance lung cancer early detection biomarkers will require carefully designed validation, translational, and comparative studies.

Published
2022

47. A Germline Variant at 8q24 Contributes to Familial Clustering of Prostate Cancer in Men of African Ancestry

Author

Luc Multigner, William J. Blot, Alexander Lubwama, Stephen Watya, Peter E. Clark, Lucy Xia, Sara S. Strom, Adam S. Kibel, Jong Y. Park, Adam B. Murphy, Jennifer Cullen, Christopher A. Haiman, Florence Menegaux, Shiv Srivastava, Loreall Pooler, Mariana C. Stern, Anand P. Chokkalingam, Eric A. Klein, Wei Zheng, Thomas A. Sellers, Anselm Hennis, Dana C. Crawford, James L. Mohler, Jack A. Taylor, Esther M. John, Robin J. Leach, Sonja I. Berndt, Laurent Brureau, John D. Carpten, Susan Gundell, David V. Conti, Barbara Nemesure, Rosalind A. Eeles, Graham Casey, Pascal Blanchet, Benjamin A. Rybicki, Chad D. Huff, Maureen Sanderson, Stephen J. Chanock, Melinda C. Aldrich, Jay H. Fowke, Jennifer J. Hu, Diptasri Mandal, Sue A. Ingles, Kosj Yamoah, Kathleen A. Cooney, K. Govindasami, Ian M. Thompson, Patrick C. Walsh, Xin Sheng, Zsofia Kote-Jarai, Janet L. Stanford, Marie-Élise Parent, Christine Neslund-Dudas, Jianfeng Xu, William S. Bush, Phyllis J. Goodman, Meredith Yeager, Burcu F. Darst, Gary J. Smith, Victoria L. Stevens, Rick A. Kittles, Elaine A. Ostrander, Olivier Cussenot, Gyorgy Petrovics, Elizabeth T. H. Fontham, William B. Isaacs, Peggy Wan, Geraldine Cancel-Tassin, Susan M. Gapstur, Bettina F. Drake, Jeannette T. Bensen, University of Southern California (USC), Centre de Recherche pour les Pathologies Prostatiques. (CeRePP / UA 3104), CEREPP, CHU Tenon [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Institut de recherche en santé, environnement et travail (Irset), Université d'Angers (UA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Centre de recherche en épidémiologie et santé des populations (CESP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris-Sud - Paris 11 (UP11)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), CHU Pointe-à-Pitre/Abymes [Guadeloupe], U19 CA148537, U19 CA214253, R01 CA165862, and K99 CA246063, National Cancer Institute at the National Institutes of Health, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Université d'Angers (UA)-Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Sud - Paris 11 (UP11)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Male, Oncology, medicine.medical_specialty, Urology, Family history, Population, 030232 urology & nephrology, Black People, Familial prostate cancer, [SDV.CAN]Life Sciences [q-bio]/Cancer, Familial clustering, Risk Assessment, Article, Germline, 03 medical and health sciences, Prostate cancer, 0302 clinical medicine, Internal medicine, Genetics, Humans, Medicine, education, Genetic variant, Aged, education.field_of_study, business.industry, Genetic Variation, Prostatic Neoplasms, 8q24, Middle Aged, medicine.disease, Health equity, 3. Good health, Disease Hotspot, Germ Cells, Prostate cancer screening, African ancestry, 030220 oncology & carcinogenesis, Health disparities, business
Abstract

International audience; Although men of African ancestry have a high risk of prostate cancer (PCa), no genes or mutations have been identified that contribute to familial clustering of PCa in this population. We investigated whether the African ancestry-specific PCa risk variant at 8q24, rs72725854, is enriched in men with a PCa family history in 9052 cases, 143 cases from high-risk families, and 8595 controls of African ancestry. We found the risk allele to be significantly associated with earlier age at diagnosis, more aggressive disease, and enriched in men with a PCa family history (32% of high-risk familial cases carried the variant vs 23% of cases without a family history and 12% of controls). For cases with two or more first-degree relatives with PCa who had at least one family member diagnosed at age

Published
2020

48. Association Analysis of Driver Gene–Related Genetic Variants Identified Novel Lung Cancer Susceptibility Loci with 20,871 Lung Cancer Cases and 15,971 Controls

Author

Neil E. Caporaso, Paul Brennan, Juncheng Dai, Hongxia Ma, Hongbing Shen, Gad Rennert, Ivan P. Gorlov, Adonina Tardón, Philip Lazarus, Yuzhuo Wang, Shanbeh Zienolddiny, Zhibin Hu, Meng Zhu, David C. Christiani, Gary E. Goodman, Stephen Lam, Rayjean J. Hung, Chu Chen, Heike Bickeböller, Matthew B. Schabath, Sanjay Shete, Maria Teresa Landi, Olga Y. Gorlova, Mikael Johansson, Susanne M. Arnold, Lambertus A. Kiemeney, Demetrius Albanes, H. E. Wichmann, Christopher I. Amos, Penella J. Woll, Angela Risch, Geoffrey Liu, Guangfu Jin, Stig E. Bojesen, Hans Brunnström, Kjell Grankvist, Victoria L. Stevens, Loic Le Marchand, Angeline S. Andrew, Mattias Johansson, Melinda C. Aldrich, Olle Melander, and John K. Field

Subjects
Male, 0301 basic medicine, Oncology, medicine.medical_specialty, Lung Neoplasms, Epidemiology, Genome-wide association study, Single-nucleotide polymorphism, Biology, Article, 03 medical and health sciences, All institutes and research themes of the Radboud University Medical Center, 0302 clinical medicine, Internal medicine, Genetic variation, medicine, Humans, Genetic Predisposition to Disease, Lung cancer, Genetic association, Case-control study, Genetic Variation, Middle Aged, respiratory system, medicine.disease, Lung cancer susceptibility, respiratory tract diseases, 3. Good health, 030104 developmental biology, Urological cancers Radboud Institute for Health Sciences [Radboudumc 15], Case-Control Studies, 030220 oncology & carcinogenesis, Medical genetics, Female, Genome-Wide Association Study
Abstract

Background: A substantial proportion of cancer driver genes (CDG) are also cancer predisposition genes. However, the associations between genetic variants in lung CDGs and the susceptibility to lung cancer have rarely been investigated. Methods: We selected expression-related single-nucleotide polymorphisms (eSNP) and nonsynonymous variants of lung CDGs, and tested their associations with lung cancer risk in two large-scale genome-wide association studies (20,871 cases and 15,971 controls of European descent). Conditional and joint association analysis was performed to identify independent risk variants. The associations of independent risk variants with somatic alterations in lung CDGs or recurrently altered pathways were investigated using data from The Cancer Genome Atlas (TCGA) project. Results: We identified seven independent SNPs in five lung CDGs that were consistently associated with lung cancer risk in discovery (P < 0.001) and validation (P < 0.05) stages. Among these loci, rs78062588 in TPM3 (1q21.3) was a new lung cancer susceptibility locus (OR = 0.86, P = 1.65 × 10−6). Subgroup analysis by histologic types further identified nine lung CDGs. Analysis of somatic alterations found that in lung adenocarcinomas, rs78062588[C] allele (TPM3 in 1q21.3) was associated with elevated somatic copy number of TPM3 (OR = 1.16, P = 0.02). In lung adenocarcinomas, rs1611182 (HLA-A in 6p22.1) was associated with truncation mutations of the transcriptional misregulation in cancer pathway (OR = 0.66, P = 1.76 × 10−3). Conclusions: Genetic variants can regulate functions of lung CDGs and influence lung cancer susceptibility. Impact: Our findings might help unravel biological mechanisms underlying lung cancer susceptibility.

Published
2020

49. Erythrocyte levels of cadmium and lead and risk of <scp>B</scp> ‐cell non‐Hodgkin lymphoma and multiple myeloma

Author

Victoria L. Stevens, Susan M. Gapstur, Emily L. Deubler, Laura G. Haines, Mia M. Gaudet, Marjorie L. McCullough, Lauren R. Teras, Keith E. Levine, James M. Hodge, and W. Ryan Diver

Subjects
Adult, Male, Oncology, Cancer Research, medicine.medical_specialty, Erythrocytes, Follicular lymphoma, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, hemic and lymphatic diseases, Internal medicine, medicine, Humans, Multiple myeloma, Aged, Aged, 80 and over, Cancer prevention, business.industry, Incidence, Lymphoma, Non-Hodgkin, Middle Aged, medicine.disease, Confidence interval, Lymphoma, Logistic Models, Lead, Case-Control Studies, 030220 oncology & carcinogenesis, Relative risk, Cohort, B-Cell Non-Hodgkin Lymphoma, Female, Multiple Myeloma, business, Cadmium
Abstract

Cadmium and lead are persistent environmental toxins that are known or probable carcinogens, based on evidence for causality for nonhematologic cancers. Associations of these metals with risk of non-Hodgkin lymphoma (NHL) and multiple myeloma (MM) are unknown but biologically plausible. To examine the associations of circulating levels of lead and cadmium exposure with risk of B-cell NHL (B-NHL) and multiple myeloma, we conducted a nested case-control study among 299 incident B-cell NHLs and 76 MM cases within the Cancer Prevention Study-II Nutrition Cohort (CPS-II NC). Each case was incidence-density matched to two eligible controls on age, race, sex and blood draw date. Conditional logistic regression was used to estimate relative risks (RR) and 95% confidence intervals (CI) for lymphoid malignancies overall and stratified by subtype. We observed a significant positive association between high erythrocyte lead concentration and risk of lymphoid malignancies overall (RR = 1.16, 95% CI: 1.02-1.33 per 17.6 μg/L (1 standard deviation [SD])) and follicular lymphoma in particular (RR = 1.80, 95% CI: 1.15-2.80 per SD). In contrast, there was no association between erythrocyte cadmium and risk of B-NHL (RR = 0.89, 95% CI: 0.75-1.06 per 0.37 μg/L [1 SD]), or any B-NHL subtypes; but a strong inverse association with MM risk (RR = 0.59, 95% CI: 0.38-0.89, per SD). Results from our study suggest a positive association between erythrocyte lead level and risk of lymphoid malignancies and a possible inverse association between cadmium and myeloma. Additional research is needed to confirm and further explore these findings.

Published
2020

50. Postdiagnosis Body Mass Index, Weight Change, and Mortality From Prostate Cancer, Cardiovascular Disease, and All Causes Among Survivors of Nonmetastatic Prostate Cancer

Author

W. Dana Flanders, Alyssa N. Troeschel, Ted Gansler, Lauren E. McCullough, Victoria L. Stevens, Terryl J. Hartman, Ying Wang, and Eric J. Jacobs

Subjects
Adult, Male, Oncology, Cancer Research, medicine.medical_specialty, MEDLINE, Disease, Body Mass Index, 03 medical and health sciences, Prostate cancer, 0302 clinical medicine, Cancer Survivors, Prostate, Internal medicine, Humans, Medicine, Survivors, 030212 general & internal medicine, Aged, Proportional Hazards Models, Aged, 80 and over, business.industry, Body Weight, Weight change, Editorials, Prostatic Neoplasms, ORIGINAL REPORTS, Middle Aged, medicine.disease, medicine.anatomical_structure, Cardiovascular Diseases, 030220 oncology & carcinogenesis, business, Body mass index
Abstract

PURPOSE To investigate the association of postdiagnosis body mass index (BMI) and weight change with prostate cancer–specific mortality (PCSM), cardiovascular disease–related mortality (CVDM), and all-cause mortality among survivors of nonmetastatic prostate cancer. METHODS Men in the Cancer Prevention Study II Nutrition Cohort diagnosed with nonmetastatic prostate cancer between 1992 and 2013 were followed for mortality through December 2016. Current weight was self-reported on follow-up questionnaires approximately every 2 years. Postdiagnosis BMI was obtained from the first survey completed 1 to < 6 years after diagnosis. Weight change was the difference in weight between the first and second postdiagnosis surveys. Deaths occurring within 4 years of the follow-up were excluded to reduce bias from reverse causation. Analyses of BMI and weight change included 8,330 and 6,942 participants, respectively. RESULTS Postdiagnosis BMI analyses included 3,855 deaths from all causes (PCSM, n = 500; CVDM, n = 1,155). Using Cox proportional hazards models, hazard ratios (HRs) associated with postdiagnosis obesity (BMI ≥ 30 kg/m2) compared with healthy weight (BMI 18.5 to < 25.0 kg/m2) were 1.28 for PCSM (95% CI, 0.96 to 1.67), 1.24 for CVDM (95% CI, 1.03 to 1.49), and 1.23 for all-cause mortality (95% CI, 1.11 to 1.35). Weight gain analyses included 2,973 deaths (PCSM, n = 375; CVDM, n = 881). Postdiagnosis weight gain (> 5% of body weight), compared with stable weight (± < 3%), was associated with a higher risk of PCSM (HR, 1.65; 95% CI, 1.21 to 2.25) and all-cause mortality (HR, 1.27; 95% CI, 1.12 to 1.45) but not CVDM. CONCLUSION Results suggest that among survivors of nonmetastatic prostate cancer with largely localized disease, postdiagnosis obesity is associated with higher CVDM and all-cause mortality, and possibly higher PCSM, and that postdiagnosis weight gain may be associated with a higher mortality as a result of all causes and prostate cancer.

Published
2020

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