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Shared heritability and functional enrichment across six solid cancers
Jiang, Xia; Finucane, Hilary K; Schumacher, Fredrick R; Schmit, Stephanie L; Tyrer, Jonathan P; Han, Younghun; Michailidou, Kyriaki; Lesseur, Corina; Kuchenbaecker, Karoline B; Dennis, Joe; Conti, David V; Casey, Graham; Gaudet, Mia M; Huyghe, Jeroen R; Albanes, Demetrius; Aldrich, Melinda C; Andrew, Angeline S; Andrulis, Irene L; Anton-Culver, Hoda; Antoniou, Antonis C; Antonenkova, Natalia N; Arnold, Susanne M; Aronson, Kristan J; Arun, Banu K; Bandera, Elisa V; Barkardottir, Rosa B; Barnes, Daniel R; Batra, Jyotsna; Beckmann, Matthias W; Benitez, Javier; Benlloch, Sara; Berchuck, Andrew; Berndt, Sonja I; Bickeböller, Heike; Bien, Stephanie A; Blomqvist, Carl; Boccia, Stefania; Bogdanova, Natalia V; Bojesen, Stig E; Bolla, Manjeet K; Brauch, Hiltrud; Brenner, Hermann; Brenton, James D; Brook, Mark N; Brunet, Joan; Brunnström, Hans; Buchanan, Daniel D; Burwinkel, Barbara; Butzow, Ralf; Cadoni, Gabriella; Caldés, Trinidad; Caligo, Maria A; Campbell, Ian; Campbell, Peter T; Cancel-Tassin, Géraldine; Cannon-Albright, Lisa; Campa, Daniele; Caporaso, Neil; Carvalho, André L; Chan, Andrew T; Chang-Claude, Jenny; Chanock, Stephen J; Chen, Chu; Christiani, David C; Claes, Kathleen B M; Claessens, Frank; Clements, Judith; Collée, J Margriet; Correa, Marcia Cruz; Couch, Fergus J; Cox, Angela; Cunningham, Julie M; Cybulski, Cezary; Czene, Kamila; Daly, Mary B; deFazio, Anna; Devilee, Peter; Diez, Orland; Gago-Dominguez, Manuela; Donovan, Jenny L; Dörk, Thilo; Duell, Eric J; Dunning, Alison M; Dwek, Miriam; Eccles, Diana M; Edlund, Christopher K; Edwards, Digna R Velez; Ellberg, Carolina; Evans, D Gareth; Fasching, Peter A; Ferris, Robert L; Liloglou, Triantafillos; Figueiredo, Jane C; Fletcher, Olivia; Fortner, Renée T; Fostira, Florentia; Franceschi, Silvia; Friedman, Eitan; Gallinger, Steven J; Ganz, Patricia A; Garber, Judy; García-Sáenz, José A; Gayther, Simon A; Giles, Graham G; Godwin, Andrew K; Goldberg, Mark S; Goldgar, David E; Goode, Ellen L; Goodman, Marc T; Goodman, Gary; Grankvist, Kjell; Greene, Mark H; Gronberg, Henrik; Gronwald, Jacek; Guénel, Pascal; HÃ¥kansson, Niclas; Hall, Per; Hamann, Ute; Hamdy, Freddie C; Hamilton, Robert J; Hampe, Jochen; Haugen, Aage; Heitz, Florian; Herrero, Rolando; Hillemanns, Peter; Hoffmeister, Michael; Høgdall, Estrid; Hong, Yun-Chul; Hopper, John L; Houlston, Richard; Hulick, Peter J; Hunter, David J; Huntsman, David G; Idos, Gregory; Imyanitov, Evgeny N; Ingles, Sue Ann; Isaacs, Claudine; Jakubowska, Anna; James, Paul; Jenkins, Mark A; Johansson, Mattias; Johansson, Mikael; John, Esther M; Joshi, Amit D; Kaneva, Radka; Karlan, Beth Y; Kelemen, Linda E; Kühl, Tabea; Khaw, Kay-Tee; Khusnutdinova, Elza; Kibel, Adam S; Kiemeney, Lambertus A; Kim, Jeri; Kjaer, Susanne K; Knight, Julia A; Kogevinas, Manolis; Kote-Jarai, Zsofia; Koutros, Stella; Kristensen, Vessela N; Kupryjanczyk, Jolanta; Lacko, Martin; Lam, Stephan; Lambrechts, Diether; Landi, Maria Teresa; Lazarus, Philip; Le, Nhu D; Lee, Eunjung; Lejbkowicz, Flavio; Lenz, Heinz-Josef; Leslie, Goska; Lessel, Davor; Lester, Jenny; Levine, Douglas A; Li, Li; Li, Christopher I; Lindblom, Annika; Lindor, Noralane M; Liu, Geoffrey; Loupakis, Fotios; LubiÅ„ski, Jan; Maehle, Lovise; Maier, Christiane; Mannermaa, Arto; Marchand, Loic Le; Margolin, Sara; May, Taymaa; McGuffog, Lesley; Meindl, Alfons; Middha, Pooja; Miller, Austin; Milne, Roger L; MacInnis, Robert J; Modugno, Francesmary; Montagna, Marco; Moreno, Victor; Moysich, Kirsten B; Mucci, Lorelei; Muir, Kenneth; Mulligan, Anna Marie; Nathanson, Katherine L; Neal, David E; Ness, Andrew R; Neuhausen, Susan L; Nevanlinna, Heli; Newcomb, Polly A; Newcomb, Lisa F; Nielsen, Finn Cilius; Nikitina-Zake, Liene; Nordestgaard, Børge G; Nussbaum, Robert L; Offit, Kenneth; Olah, Edith; Olama, Ali Amin Al; Olopade, Olufunmilayo I; Olshan, Andrew F; Olsson, HÃ¥kan; Osorio, Ana; Pandha, Hardev; Park, Jong Y; Pashayan, Nora; Parsons, Michael T; Pejovic, Tanja; Penney, Kathryn L; Peters, Wilbert H M; Phelan, Catherine M; Phipps, Amanda I; Plaseska-Karanfilska, Dijana; Pring, Miranda; Prokofyeva, Darya; Radice, Paolo; Stefansson, Kari; Ramus, Susan J; Raskin, Leon; Rennert, Gad; Rennert, Hedy S; van Rensburg, Elizabeth J; Riggan, Marjorie J; Risch, Harvey A; Risch, Angela; Roobol, Monique J; Rosenstein, Barry S; Rossing, Mary Anne; De Ruyck, Kim; Saloustros, Emmanouil; Sandler, Dale P; Sawyer, Elinor J; Schabath, Matthew B; Schleutker, Johanna; Schmidt, Marjanka K; Setiawan, V Wendy; Shen, Hongbing; Siegel, Erin M; Sieh, Weiva; Singer, Christian F; Slattery, Martha L; Sorensen, Karina Dalsgaard; Southey, Melissa C; Spurdle, Amanda B; Stanford, Janet L; Stevens, Victoria L; Stintzing, Sebastian; Stone, Jennifer; Sundfeldt, Karin; Sutphen, Rebecca; Swerdlow, Anthony J; Tajara, Eloiza H; Tangen, Catherine M; Tardon, Adonina; Taylor, Jack A; Teare, M Dawn; Teixeira, Manuel R; Terry, Mary Beth; Terry, Kathryn L; Thibodeau, Stephen N; Thomassen, Mads; Bjørge, Line; Tischkowitz, Marc; Toland, Amanda E; Torres, Diana; Townsend, Paul A; Travis, Ruth C; Tung, Nadine; Tworoger, Shelley S; Ulrich, Cornelia M; Usmani, Nawaid; Vachon, Celine M; Van Nieuwenhuysen, Els; Vega, Ana; Aguado-Barrera, Miguel ElÃas; Wang, Qin; Webb, Penelope M; Weinberg, Clarice R; Weinstein, Stephanie; Weissler, Mark C; Weitzel, Jeffrey N; West, Catharine M L; White, Emily; Whittemore, Alice S; Wichmann, H-Erich; Wiklund, Fredrik; Winqvist, Robert; Wolk, Alicja; Woll, Penella; Woods, Michael; Wu, Anna H; Wu, Xifeng; Yannoukakos, Drakoulis; Zheng, Wei; Zienolddiny, Shanbeh; Ziogas, Argyrios; Zorn, Kristin K; Lane, Jacqueline M; Saxena, Richa; Thomas, Duncan; Hung, Rayjean J; Diergaarde, Brenda; McKay, James; Peters, Ulrike; Hsu, Li; García-Closas, Montserrat; Eeles, Rosalind A; Chenevix-Trench, Georgia; Brennan, Paul J; Haiman, Christopher A; Simard, Jacques; Easton, Douglas F; Gruber, Stephen B; Pharoah, Paul D P; Price, Alkes L; Pasaniuc, Bogdan; Amos, Christopher I; Kraft, Peter; Lindström, Sara
Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (rg = 0.57, p = 4.6 × 10-8), breast and ovarian cancer (rg = 0.24, p = 7 × 10-5), breast and lung cancer (rg = 0.18, p =1.5 × 10-6) and breast and colorectal cancer (rg = 0.15, p = 1.1 × 10-4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.
PMID: 30683880
ISSN: 2041-1723
CID: 3610232
Author Correction: Germline variation at 8q24 and prostate cancer risk in men of European ancestry [Correction]
Matejcic, Marco; Saunders, Edward J; Dadaev, Tokhir; Brook, Mark N; Wang, Kan; Sheng, Xin; Olama, Ali Amin Al; Schumacher, Fredrick R; Ingles, Sue A; Govindasami, Koveela; Benlloch, Sara; Berndt, Sonja I; Albanes, Demetrius; Koutros, Stella; Muir, Kenneth; Stevens, Victoria L; Gapstur, Susan M; Tangen, Catherine M; Batra, Jyotsna; Clements, Judith; Gronberg, Henrik; Pashayan, Nora; Schleutker, Johanna; Wolk, Alicja; West, Catharine; Mucci, Lorelei; Kraft, Peter; Cancel-Tassin, Géraldine; Sorensen, Karina D; Maehle, Lovise; Grindedal, Eli M; Strom, Sara S; Neal, David E; Hamdy, Freddie C; Donovan, Jenny L; Travis, Ruth C; Hamilton, Robert J; Rosenstein, Barry; Lu, Yong-Jie; Giles, Graham G; Kibel, Adam S; Vega, Ana; Bensen, Jeanette T; Kogevinas, Manolis; Penney, Kathryn L; Park, Jong Y; Stanford, Janet L; Cybulski, Cezary; Nordestgaard, Børge G; Brenner, Hermann; Maier, Christiane; Kim, Jeri; Teixeira, Manuel R; Neuhausen, Susan L; De Ruyck, Kim; Razack, Azad; Newcomb, Lisa F; Lessel, Davor; Kaneva, Radka; Usmani, Nawaid; Claessens, Frank; Townsend, Paul A; Gago-Dominguez, Manuela; Roobol, Monique J; Menegaux, Florence; Khaw, Kay-Tee; Cannon-Albright, Lisa A; Pandha, Hardev; Thibodeau, Stephen N; Schaid, Daniel J; Wiklund, Fredrik; Chanock, Stephen J; Easton, Douglas F; Eeles, Rosalind A; Kote-Jarai, Zsofia; Conti, David V; Haiman, Christopher A
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.
PMID: 30655571
ISSN: 2041-1723
CID: 3617932
Circulating Metabolic Biomarkers of Screen-Detected Prostate Cancer in the ProtecT Study
Adams, Charleen D; Richmond, Rebecca; Ferreira, Diana L Santos; Spiller, Wes; Tan, Vanessa; Zheng, Jie; Würtz, Peter; Donovan, Jenny; Hamdy, Freddie; Neal, David; Lane, J Athene; Smith, George Davey; Relton, Caroline; Eeles, Rosalind A; Haiman, Christopher A; Kote-Jarai, ZSofia; Schumacher, Fredrick R; Olama, Ali Amin Al; Benlloch, Sara; Muir, Kenneth; Berndt, Sonja I; Conti, David V; Wiklund, Fredrik; Chanock, Stephen J; Gapstur, Susan; Stevens, Victoria L; Tangen, Catherine M; Batra, Jyotsna; Clements, Judith A; Gronberg, Henrik; Pashayan, Nora; Schleutker, Johanna; Albanes, Demetrius; Wolk, Alicja; West, Catharine M L; Mucci, Lorelei A; Cancel-Tassin, Géraldine; Koutros, Stella; Sorensen, Karina Dalsgaard; Maehle, Lovise; Travis, Ruth C; Hamilton, Robert J; Ingles, Sue Ann; Rosenstein, Barry S; Lu, Yong-Jie; Giles, Graham G; Kibel, Adam S; Vega, Ana; Kogevinas, Manolis; Penney, Kathryn L; Park, Jong Y; Stanford, Janet L; Cybulski, Cezary; Nordestgaard, Børge G; Brenner, Hermann; Maier, Christiane; Kim, Jeri; John, Esther M; Teixeira, Manuel R; Neuhausen, Susan L; De Ruyck, Kim; Razack, Azad; Newcomb, Lisa F; Lessel, Davor; Kaneva, Radka P; Usmani, Nawaid; Claessens, Frank; Townsend, Paul A; Dominguez, Manuela Gago; Roobol, Monique J; Menegaux, Florence; Khaw, Kay-Tee; Cannon-Albright, Lisa A; Pandha, Hardev; Thibodeau, Stephen N; Martin, Richard M
BACKGROUND:Whether associations between circulating metabolites and prostate cancer are causal is unknown. We report on the largest study of metabolites and prostate cancer (2,291 cases and 2,661 controls) and appraise causality for a subset of the prostate cancer-metabolite associations using two-sample Mendelian randomization (MR). METHODS:The case-control portion of the study was conducted in nine UK centers with men ages 50-69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. RESULTS:< 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal. CONCLUSIONS:We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk. IMPACT/CONCLUSIONS:The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.
PMID: 30352818
ISSN: 1538-7755
CID: 3654162
Germline variation at 8q24 and prostate cancer risk in men of European ancestry
Matejcic, Marco; Saunders, Edward J; Dadaev, Tokhir; Brook, Mark N; Wang, Kan; Sheng, Xin; Olama, Ali Amin Al; Schumacher, Fredrick R; Ingles, Sue A; Govindasami, Koveela; Benlloch, Sara; Berndt, Sonja I; Albanes, Demetrius; Koutros, Stella; Muir, Kenneth; Stevens, Victoria L; Gapstur, Susan M; Tangen, Catherine M; Batra, Jyotsna; Clements, Judith; Gronberg, Henrik; Pashayan, Nora; Schleutker, Johanna; Wolk, Alicja; West, Catharine; Mucci, Lorelei; Kraft, Peter; Cancel-Tassin, Géraldine; Sorensen, Karina D; Maehle, Lovise; Grindedal, Eli M; Strom, Sara S; Neal, David E; Hamdy, Freddie C; Donovan, Jenny L; Travis, Ruth C; Hamilton, Robert J; Rosenstein, Barry; Lu, Yong-Jie; Giles, Graham G; Kibel, Adam S; Vega, Ana; Bensen, Jeanette T; Kogevinas, Manolis; Penney, Kathryn L; Park, Jong Y; Stanford, Janet L; Cybulski, Cezary; Nordestgaard, Børge G; Brenner, Hermann; Maier, Christiane; Kim, Jeri; Teixeira, Manuel R; Neuhausen, Susan L; De Ruyck, Kim; Razack, Azad; Newcomb, Lisa F; Lessel, Davor; Kaneva, Radka; Usmani, Nawaid; Claessens, Frank; Townsend, Paul A; Dominguez, Manuela G; Roobol, Monique J; Menegaux, Florence; Khaw, Kay-Tee; Cannon-Albright, Lisa A; Pandha, Hardev; Thibodeau, Stephen N; Schaid, Daniel J; Wiklund, Fredrik; Chanock, Stephen J; Easton, Douglas F; Eeles, Rosalind A; Kote-Jarai, Zsofia; Conti, David V; Haiman, Christopher A
Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10-15), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62-4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification.
PMID: 30397198
ISSN: 2041-1723
CID: 3490052
Radiation biology and oncology in the genomic era
Kerns, Sarah L; Chuang, Kuang-Hsiang; Hall, William; Werner, Zachary; Chen, Yuhchyau; Ostrer, Harry; West, Catharine; Rosenstein, Barry
Radiobiology research is building the foundation for applying genomics in precision radiation oncology. Advances in high-throughput approaches will underpin increased understanding of radiosensitivity and the development of future predictive assays for clinical application. There is an established contribution of genetics as a risk factor for radiotherapy side effects. An individual's radiosensitivity is an inherited polygenic trait with an architecture that includes rare mutations in a few genes that confer large effects and common variants in many genes with small effects. Current thinking is that some will be tissue specific, and future tests will be tailored to the normal tissues at risk. The relationship between normal and tumor cell radiosensitivity is poorly understood. Data are emerging suggesting interplay between germline genetic variation and epigenetic modification with growing evidence that changes in DNA methylation regulate the radiosensitivity of cancer cells and histone acetyltransferase inhibitors have radiosensitizing effects. Changes in histone methylation can also impair DNA damage response signaling and alter radiosensitivity. An important effort to advance radiobiology in the genomic era was establishment of the Radiogenomics Consortium to enable the creation of the large radiotherapy cohorts required to exploit advances in genomics. To address challenges in harmonizing data from multiple cohorts, the consortium established the REQUITE project to collect standardized data and genotyping for ~5,000 patients. The collection of detailed dosimetric data is important to produce validated multivariable models. Continued efforts will identify new genes that impact on radiosensitivity to generate new knowledge on toxicity pathogenesis and tests to incorporate into the clinical decision-making process.
PMID: 29888979
ISSN: 1748-880x
CID: 3166962
Performance/outcomes data and physician process challenges for practical big data efforts in radiation oncology
Matuszak, Martha M; Fuller, Clifton D; Yock, Torunn I; Hess, Clayton B; McNutt, Todd; Jolly, Shruti; Gabriel, Peter; Mayo, Charles S; Thor, Maria; Caissie, Amanda; Rao, Arvind; Owen, Dawn; Smith, Wade; Palta, Jatinder; Kapoor, Rishabh; Hayman, James; Waddle, Mark; Rosenstein, Barry; Miller, Robert; Choi, Seungtaek; Moreno, Amy; Herman, Joseph; Feng, Mary
It is an exciting time for big data efforts in radiation oncology. The use of big data to help aid both outcomes and decision-making research is becoming a reality. However, there are true challenges that exist in the space of gathering and utilizing performance and outcomes data. Here, we summarize the current state of big data in radiation oncology with respect to outcomes and discuss some of the efforts and challenges in radiation oncology big data.
PMID: 30229946
ISSN: 2473-4209
CID: 3372052
Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci
Schumacher, Fredrick R; Al Olama, Ali Amin; Berndt, Sonja I; Benlloch, Sara; Ahmed, Mahbubl; Saunders, Edward J; Dadaev, Tokhir; Leongamornlert, Daniel; Anokian, Ezequiel; Cieza-Borrella, Clara; Goh, Chee; Brook, Mark N; Sheng, Xin; Fachal, Laura; Dennis, Joe; Tyrer, Jonathan; Muir, Kenneth; Lophatananon, Artitaya; Stevens, Victoria L; Gapstur, Susan M; Carter, Brian D; Tangen, Catherine M; Goodman, Phyllis J; Thompson, Ian M; Batra, Jyotsna; Chambers, Suzanne; Moya, Leire; Clements, Judith; Horvath, Lisa; Tilley, Wayne; Risbridger, Gail P; Gronberg, Henrik; Aly, Markus; Nordström, Tobias; Pharoah, Paul; Pashayan, Nora; Schleutker, Johanna; Tammela, Teuvo L J; Sipeky, Csilla; Auvinen, Anssi; Albanes, Demetrius; Weinstein, Stephanie; Wolk, Alicja; HÃ¥kansson, Niclas; West, Catharine M L; Dunning, Alison M; Burnet, Neil; Mucci, Lorelei A; Giovannucci, Edward; Andriole, Gerald L; Cussenot, Olivier; Cancel-Tassin, Géraldine; Koutros, Stella; Beane Freeman, Laura E; Sorensen, Karina Dalsgaard; Orntoft, Torben Falck; Borre, Michael; Maehle, Lovise; Grindedal, Eli Marie; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Martin, Richard M; Travis, Ruth C; Key, Tim J; Hamilton, Robert J; Fleshner, Neil E; Finelli, Antonio; Ingles, Sue Ann; Stern, Mariana C; Rosenstein, Barry S; Kerns, Sarah L; Ostrer, Harry; Lu, Yong-Jie; Zhang, Hong-Wei; Feng, Ninghan; Mao, Xueying; Guo, Xin; Wang, Guomin; Sun, Zan; Giles, Graham G; Southey, Melissa C; MacInnis, Robert J; FitzGerald, Liesel M; Kibel, Adam S; Drake, Bettina F; Vega, Ana; Gómez-Caamaño, Antonio; Szulkin, Robert; Eklund, Martin; Kogevinas, Manolis; Llorca, Javier; Castaño-Vinyals, Gemma; Penney, Kathryn L; Stampfer, Meir; Park, Jong Y; Sellers, Thomas A; Lin, Hui-Yi; Stanford, Janet L; Cybulski, Cezary; Wokolorczyk, Dominika; Lubinski, Jan; Ostrander, Elaine A; Geybels, Milan S; Nordestgaard, Børge G; Nielsen, Sune F; Weischer, Maren; Bisbjerg, Rasmus; Røder, Martin Andreas; Iversen, Peter; Brenner, Hermann; Cuk, Katarina; Holleczek, Bernd; Maier, Christiane; Luedeke, Manuel; Schnoeller, Thomas; Kim, Jeri; Logothetis, Christopher J; John, Esther M; Teixeira, Manuel R; Paulo, Paula; Cardoso, Marta; Neuhausen, Susan L; Steele, Linda; Ding, Yuan Chun; De Ruyck, Kim; De Meerleer, Gert; Ost, Piet; Razack, Azad; Lim, Jasmine; Teo, Soo-Hwang; Lin, Daniel W; Newcomb, Lisa F; Lessel, Davor; Gamulin, Marija; Kulis, Tomislav; Kaneva, Radka; Usmani, Nawaid; Singhal, Sandeep; Slavov, Chavdar; Mitev, Vanio; Parliament, Matthew; Claessens, Frank; Joniau, Steven; Van den Broeck, Thomas; Larkin, Samantha; Townsend, Paul A; Aukim-Hastie, Claire; Dominguez, Manuela Gago; Castelao, Jose Esteban; Martinez, Maria Elena; Roobol, Monique J; Jenster, Guido; van Schaik, Ron H N; Menegaux, Florence; Truong, Thérèse; Koudou, Yves Akoli; Xu, Jianfeng; Khaw, Kay-Tee; Cannon-Albright, Lisa; Pandha, Hardev; Michael, Agnieszka; Thibodeau, Stephen N; McDonnell, Shannon K; Schaid, Daniel J; Lindstrom, Sara; Turman, Constance; Ma, Jing; Hunter, David J; Riboli, Elio; Siddiq, Afshan; Canzian, Federico; Kolonel, Laurence N; Le Marchand, Loic; Hoover, Robert N; Machiela, Mitchell J; Cui, Zuxi; Kraft, Peter; Amos, Christopher I; Conti, David V; Easton, Douglas F; Wiklund, Fredrik; Chanock, Stephen J; Henderson, Brian E; Kote-Jarai, Zsofia; Haiman, Christopher A; Eeles, Rosalind A
Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P < 5.0 × 10-8) with PrCa and one locus significantly associated with early-onset PrCa (≤55 years). Our findings include missense variants rs1800057 (odds ratio (OR) = 1.16; P = 8.2 × 10-9; G>C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa 1 .
PMID: 29892016
ISSN: 1546-1718
CID: 3167102
Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants
Dadaev, Tokhir; Saunders, Edward J; Newcombe, Paul J; Anokian, Ezequiel; Leongamornlert, Daniel A; Brook, Mark N; Cieza-Borrella, Clara; Mijuskovic, Martina; Wakerell, Sarah; Olama, Ali Amin Al; Schumacher, Fredrick R; Berndt, Sonja I; Benlloch, Sara; Ahmed, Mahbubl; Goh, Chee; Sheng, Xin; Zhang, Zhuo; Muir, Kenneth; Govindasami, Koveela; Lophatananon, Artitaya; Stevens, Victoria L; Gapstur, Susan M; Carter, Brian D; Tangen, Catherine M; Goodman, Phyllis; Thompson, Ian M; Batra, Jyotsna; Chambers, Suzanne; Moya, Leire; Clements, Judith; Horvath, Lisa; Tilley, Wayne; Risbridger, Gail; Gronberg, Henrik; Aly, Markus; Nordström, Tobias; Pharoah, Paul; Pashayan, Nora; Schleutker, Johanna; Tammela, Teuvo L J; Sipeky, Csilla; Auvinen, Anssi; Albanes, Demetrius; Weinstein, Stephanie; Wolk, Alicja; Hakansson, Niclas; West, Catharine; Dunning, Alison M; Burnet, Neil; Mucci, Lorelei; Giovannucci, Edward; Andriole, Gerald; Cussenot, Olivier; Cancel-Tassin, Géraldine; Koutros, Stella; Freeman, Laura E Beane; Sorensen, Karina Dalsgaard; Orntoft, Torben Falck; Borre, Michael; Maehle, Lovise; Grindedal, Eli Marie; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Martin, Richard M; Travis, Ruth C; Key, Tim J; Hamilton, Robert J; Fleshner, Neil E; Finelli, Antonio; Ingles, Sue Ann; Stern, Mariana C; Rosenstein, Barry; Kerns, Sarah; Ostrer, Harry; Lu, Yong-Jie; Zhang, Hong-Wei; Feng, Ninghan; Mao, Xueying; Guo, Xin; Wang, Guomin; Sun, Zan; Giles, Graham G; Southey, Melissa C; MacInnis, Robert J; FitzGerald, Liesel M; Kibel, Adam S; Drake, Bettina F; Vega, Ana; Gómez-Caamaño, Antonio; Fachal, Laura; Szulkin, Robert; Eklund, Martin; Kogevinas, Manolis; Llorca, Javier; Castaño-Vinyals, Gemma; Penney, Kathryn L; Stampfer, Meir; Park, Jong Y; Sellers, Thomas A; Lin, Hui-Yi; Stanford, Janet L; Cybulski, Cezary; Wokolorczyk, Dominika; Lubinski, Jan; Ostrander, Elaine A; Geybels, Milan S; Nordestgaard, Børge G; Nielsen, Sune F; Weisher, Maren; Bisbjerg, Rasmus; Røder, Martin Andreas; Iversen, Peter; Brenner, Hermann; Cuk, Katarina; Holleczek, Bernd; Maier, Christiane; Luedeke, Manuel; Schnoeller, Thomas; Kim, Jeri; Logothetis, Christopher J; John, Esther M; Teixeira, Manuel R; Paulo, Paula; Cardoso, Marta; Neuhausen, Susan L; Steele, Linda; Ding, Yuan Chun; De Ruyck, Kim; De Meerleer, Gert; Ost, Piet; Razack, Azad; Lim, Jasmine; Teo, Soo-Hwang; Lin, Daniel W; Newcomb, Lisa F; Lessel, Davor; Gamulin, Marija; Kulis, Tomislav; Kaneva, Radka; Usmani, Nawaid; Slavov, Chavdar; Mitev, Vanio; Parliament, Matthew; Singhal, Sandeep; Claessens, Frank; Joniau, Steven; Van den Broeck, Thomas; Larkin, Samantha; Townsend, Paul A; Aukim-Hastie, Claire; Gago-Dominguez, Manuela; Castelao, Jose Esteban; Martinez, Maria Elena; Roobol, Monique J; Jenster, Guido; van Schaik, Ron H N; Menegaux, Florence; Truong, Thérèse; Koudou, Yves Akoli; Xu, Jianfeng; Khaw, Kay-Tee; Cannon-Albright, Lisa; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Thibodeau, Stephen N; McDonnell, Shannon K; Schaid, Daniel J; Lindstrom, Sara; Turman, Constance; Ma, Jing; Hunter, David J; Riboli, Elio; Siddiq, Afshan; Canzian, Federico; Kolonel, Laurence N; Le Marchand, Loic; Hoover, Robert N; Machiela, Mitchell J; Kraft, Peter; Freedman, Matthew; Wiklund, Fredrik; Chanock, Stephen; Henderson, Brian E; Easton, Douglas F; Haiman, Christopher A; Eeles, Rosalind A; Conti, David V; Kote-Jarai, Zsofia
Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.
PMCID:5995836
PMID: 29892050
ISSN: 2041-1723
CID: 3157202
Machine Learning on a Genome-wide Association Study to Predict Late Genitourinary Toxicity After Prostate Radiation Therapy
Lee, Sangkyu; Kerns, Sarah; Ostrer, Harry; Rosenstein, Barry; Deasy, Joseph O; Oh, Jung Hun
PURPOSE/OBJECTIVE:Late genitourinary (GU) toxicity after radiation therapy limits the quality of life of prostate cancer survivors; however, efforts to explain GU toxicity using patient and dose information have remained unsuccessful. We identified patients with a greater congenital GU toxicity risk by identifying and integrating patterns in genome-wide single nucleotide polymorphisms (SNPs). METHODS AND MATERIALS/METHODS:We applied a preconditioned random forest regression method for predicting risk from the genome-wide data to combine the effects of multiple SNPs and overcome the statistical power limitations of single-SNP analysis. We studied a cohort of 324 prostate cancer patients who were self-assessed for 4 urinary symptoms at 2Â years after radiation therapy using the International Prostate Symptom Score. RESULTS:The predictive accuracy of the method varied across the symptoms. Only for the weak stream endpoint did it achieve a significant area under the curve of 0.70 (95% confidence interval 0.54-0.86; PÂ =Â .01) on hold-out validation data that outperformed competing methods. Gene ontology analysis highlighted key biological processes, such as neurogenesis and ion transport, from the genes known to be important for urinary tract functions. CONCLUSIONS:We applied machine learning methods and bioinformatics tools to genome-wide data to predict and explain GU toxicity. Our approach enabled the design of a more powerful predictive model and the determination of plausible biomarkers and biological processes associated with GU toxicity.
PMCID:5886789
PMID: 29502932
ISSN: 1879-355x
CID: 2991892
Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes
Oh, Jung Hun; Kerns, Sarah; Ostrer, Harry; Powell, Simon N; Rosenstein, Barry; Deasy, Joseph O
The biological cause of clinically observed variability of normal tissue damage following radiotherapy is poorly understood. We hypothesized that machine/statistical learning methods using single nucleotide polymorphism (SNP)-based genome-wide association studies (GWAS) would identify groups of patients of differing complication risk, and furthermore could be used to identify key biological sources of variability. We developed a novel learning algorithm, called pre-conditioned random forest regression (PRFR), to construct polygenic risk models using hundreds of SNPs, thereby capturing genomic features that confer small differential risk. Predictive models were trained and validated on a cohort of 368 prostate cancer patients for two post-radiotherapy clinical endpoints: late rectal bleeding and erectile dysfunction. The proposed method results in better predictive performance compared with existing computational methods. Gene ontology enrichment analysis and protein-protein interaction network analysis are used to identify key biological processes and proteins that were plausible based on other published studies. In conclusion, we confirm that novel machine learning methods can produce large predictive models (hundreds of SNPs), yielding clinically useful risk stratification models, as well as identifying important underlying biological processes in the radiation damage and tissue repair process. The methods are generally applicable to GWAS data and are not specific to radiotherapy endpoints.
PMCID:5324069
PMID: 28233873
ISSN: 2045-2322
CID: 3078932
