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1. A multi-level investigation of the genetic relationship between endometriosis and ovarian cancer histotypes

Author

Mortlock, S, Corona, R, Kho, PF, Pharoah, P, Seo, J-H, Freedman, ML, Gayther, SA, Siedhoff, MT, Rogers, PAW, Leuchter, R, Walsh, CS, Cass, I, Karlan, BY, Rimel, BJ, Montgomery, GW, Lawrenson, K, Kar, SP, Mortlock, S, Corona, R, Kho, PF, Pharoah, P, Seo, J-H, Freedman, ML, Gayther, SA, Siedhoff, MT, Rogers, PAW, Leuchter, R, Walsh, CS, Cass, I, Karlan, BY, Rimel, BJ, Montgomery, GW, Lawrenson, K, and Kar, SP

Abstract

Endometriosis is associated with increased risk of epithelial ovarian cancers (EOCs). Using data from large endometriosis and EOC genome-wide association meta-analyses, we estimate the genetic correlation and evaluate the causal relationship between genetic liability to endometriosis and EOC histotypes, and identify shared susceptibility loci. We estimate a significant genetic correlation (rg) between endometriosis and clear cell (rg = 0.71), endometrioid (rg = 0.48), and high-grade serous (rg = 0.19) ovarian cancer, associations supported by Mendelian randomization analyses. Bivariate meta-analysis identified 28 loci associated with both endometriosis and EOC, including 19 with evidence for a shared underlying association signal. Differences in the shared risk suggest different underlying pathways may contribute to the relationship between endometriosis and the different histotypes. Functional annotation using transcriptomic and epigenomic profiles of relevant tissues/cells highlights several target genes. This comprehensive analysis reveals profound genetic overlap between endometriosis and EOC histotypes with valuable genomic targets for understanding the biological mechanisms linking the diseases.

Published
2022

2. Copy Number Variants Are Ovarian Cancer Risk Alleles at Known and Novel Risk Loci

Author

DeVries, AA, Dennis, J, Tyrer, JP, Peng, P-C, Coetzee, SG, Reyes, AL, Plummer, JT, Davis, BD, Chen, SS, Dezem, FS, Aben, KKH, Anton-Culver, H, Antonenkova, NN, Beckmann, MW, Beeghly-Fadiel, A, Berchuck, A, Bogdanova, N, Bogdanova-Markov, N, Brenton, JD, Butzow, R, Campbell, I, Chang-Claude, J, Chenevix-Trench, G, Cook, LS, DeFazio, A, Doherty, JA, Dork, T, Eccles, DM, Eliassen, AH, Fasching, PA, Fortner, RT, Giles, GG, Goode, EL, Goodman, MT, Gronwald, J, Hakansson, N, Hildebrandt, MAT, Huff, C, Huntsman, DG, Jensen, A, Kar, S, Karlan, BY, Khusnutdinova, EK, Kiemeney, LA, Kjaer, SK, Kupryjanczyk, J, Labrie, M, Lambrechts, D, Le, ND, Lubinski, J, May, T, Menon, U, Milne, RL, Modugno, F, Monteiro, AN, Moysich, KB, Odunsi, K, Olsson, H, Pearce, CL, Pejovic, T, Ramus, SJ, Riboli, E, Riggan, MJ, Romieu, I, Sandler, DP, Schildkraut, JM, Setiawan, VW, Sieh, W, Song, H, Sutphen, R, Terry, KL, Thompson, PJ, Titus, L, Tworoger, SS, Van Nieuwenhuysen, E, Edwards, DV, Webb, PM, Wentzensen, N, Whittemore, AS, Wolk, A, Wu, AH, Ziogas, A, Freedman, ML, Lawrenson, K, Pharoah, PDP, Easton, DF, Gayther, SA, Jones, MR, DeVries, AA, Dennis, J, Tyrer, JP, Peng, P-C, Coetzee, SG, Reyes, AL, Plummer, JT, Davis, BD, Chen, SS, Dezem, FS, Aben, KKH, Anton-Culver, H, Antonenkova, NN, Beckmann, MW, Beeghly-Fadiel, A, Berchuck, A, Bogdanova, N, Bogdanova-Markov, N, Brenton, JD, Butzow, R, Campbell, I, Chang-Claude, J, Chenevix-Trench, G, Cook, LS, DeFazio, A, Doherty, JA, Dork, T, Eccles, DM, Eliassen, AH, Fasching, PA, Fortner, RT, Giles, GG, Goode, EL, Goodman, MT, Gronwald, J, Hakansson, N, Hildebrandt, MAT, Huff, C, Huntsman, DG, Jensen, A, Kar, S, Karlan, BY, Khusnutdinova, EK, Kiemeney, LA, Kjaer, SK, Kupryjanczyk, J, Labrie, M, Lambrechts, D, Le, ND, Lubinski, J, May, T, Menon, U, Milne, RL, Modugno, F, Monteiro, AN, Moysich, KB, Odunsi, K, Olsson, H, Pearce, CL, Pejovic, T, Ramus, SJ, Riboli, E, Riggan, MJ, Romieu, I, Sandler, DP, Schildkraut, JM, Setiawan, VW, Sieh, W, Song, H, Sutphen, R, Terry, KL, Thompson, PJ, Titus, L, Tworoger, SS, Van Nieuwenhuysen, E, Edwards, DV, Webb, PM, Wentzensen, N, Whittemore, AS, Wolk, A, Wu, AH, Ziogas, A, Freedman, ML, Lawrenson, K, Pharoah, PDP, Easton, DF, Gayther, SA, and Jones, MR

Abstract

BACKGROUND: Known risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort. METHODS: Single nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer-related cell types. RESULTS: We identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P < .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P < .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types. CONCLUSIONS: CNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention.

Published
2022

3. Association of Genomic Domains in BRCA1 and BRCA2 with Prostate Cancer Risk and Aggressiveness

Author

Patel, VL, Busch, EL, Friebel, TM, Cronin, A, Leslie, G, McGuffog, L, Adlard, J, Agata, S, Agnarsson, BA, Ahmed, M, Aittomaki, K, Alducci, E, Andrulis, IL, Arason, A, Arnold, N, Artioli, G, Arver, B, Auber, B, Azzollini, J, Balmana, J, Barkardottir, RB, Barnes, DR, Barroso, A, Barrowdale, D, Belotti, M, Benitez, J, Bertelsen, B, Blok, MJ, Bodrogi, I, Bonadona, V, Bonanni, B, Bondavalli, D, Boonen, SE, Borde, J, Borg, A, Bradbury, AR, Brady, A, Brewer, C, Brunet, J, Buecher, B, Buys, SS, Cabezas-Camarero, S, Caldes, T, Caliebe, A, Caligo, MA, Calvello, M, Campbell, IG, Carnevali, I, Carrasco, E, Chan, TL, Chu, ATW, Chung, WK, Claes, KBM, Cook, J, Cortesi, L, Couch, FJ, Daly, MB, Damante, G, Darder, E, Davidson, R, de la Hoya, M, Della Puppa, L, Dennis, J, Diez, O, Ding, YC, Ditsch, N, Domchek, SM, Donaldson, A, Dworniczak, B, Easton, DF, Eccles, DM, Eeles, RA, Ehrencrona, H, Ejlertsen, B, Engel, C, Evans, DG, Faivre, L, Faust, U, Feliubadalo, L, Foretova, L, Fostira, F, Fountzilas, G, Frost, D, Garcia-Barberan, V, Garre, P, Gauthier-Villars, M, Geczi, L, Gehrig, A, Gerdes, A-M, Gesta, P, Giannini, G, Glendon, G, Godwin, AK, Goldgar, DE, Greene, MH, Gutierrez-Barrera, AM, Hahnen, E, Hamann, U, Hauke, J, Herold, N, Hogervorst, FBL, Honisch, E, Hopper, JL, Hulick, PJ, Izatt, L, Jager, A, James, P, Janavicius, R, Jensen, UB, Jensen, TD, Johannsson, OT, John, EM, Joseph, V, Kang, E, Kast, K, Kiiski, J, Kim, S-W, Kim, Z, Ko, K-P, Konstantopoulou, I, Kramer, G, Krogh, L, Kruse, TA, Kwong, A, Larsen, M, Lasset, C, Lautrup, C, Lazaro, C, Lee, J, Lee, JW, Lee, MH, Lemke, J, Lesueur, F, Liljegren, A, Lindblom, A, Llovet, P, Lopez-Fernandez, A, Lopez-Perolio, I, Lorca, V, Loud, JT, Ma, ESK, Mai, PL, Manoukian, S, Mari, V, Martin, L, Matricardi, L, Mebirouk, N, Medici, V, Meijers-Heijboer, HEJ, Meindl, A, Mensenkamp, AR, Miller, C, Gomes, DM, Montagna, M, Mooij, TM, Moserle, L, Mouret-Fourme, E, Mulligan, AM, Nathanson, KL, Navratilova, M, Nevanlinna, H, Niederacher, D, Nielsen, FCC, Nikitina-Zake, L, Offit, K, Olah, E, Olopade, O, Ong, K-R, Osorio, A, Ott, C-E, Palli, D, Park, SK, Parsons, MT, Pedersen, IS, Peissel, B, Peixoto, A, Perez-Segura, P, Peterlongo, P, Petersen, AH, Porteous, ME, Angel Pujana, M, Radice, P, Ramser, J, Rantala, J, Rashid, MU, Rhiem, K, Rizzolo, P, Robson, ME, Rookus, MA, Rossing, CM, Ruddy, KJ, Santos, C, Saule, C, Scarpitta, R, Schmutzler, RK, Schuster, H, Senter, L, Seynaeve, CM, Shah, PD, Sharma, P, Shin, VY, Silvestri, V, Simard, J, Singer, CF, Skytte, A-B, Snape, K, Solano, AR, Soucy, P, Southey, MC, Spurdle, AB, Steele, L, Steinemann, D, Stoppa-Lyonnet, D, Stradella, A, Sunde, L, Sutter, C, Tan, YY, Teixeira, MR, Teo, SH, Thomassen, M, Tibiletti, MG, Tischkowitz, M, Tognazzo, S, Toland, AE, Tommasi, S, Torres, D, Toss, A, Trainer, AH, Tung, N, van Asperen, CJ, van der Baan, FH, van der Kolk, LE, van der Luijt, RB, van Hest, LP, Varesco, L, Varon-Mateeva, R, Viel, A, Vierstraete, J, Villa, R, von Wachenfeldt, A, Wagner, P, Wang-Gohrke, S, Wappenschmidt, B, Weitzel, JN, Wieme, G, Yadav, S, Yannoukakos, D, Yoon, S-Y, Zanzottera, C, Zorn, KK, D'Amico, A, Freedman, ML, Pomerantz, MM, Chenevix-Trench, G, Antoniou, AC, Neuhausen, SL, Ottini, L, Nielsen, HR, Rebbeck, TR, Patel, VL, Busch, EL, Friebel, TM, Cronin, A, Leslie, G, McGuffog, L, Adlard, J, Agata, S, Agnarsson, BA, Ahmed, M, Aittomaki, K, Alducci, E, Andrulis, IL, Arason, A, Arnold, N, Artioli, G, Arver, B, Auber, B, Azzollini, J, Balmana, J, Barkardottir, RB, Barnes, DR, Barroso, A, Barrowdale, D, Belotti, M, Benitez, J, Bertelsen, B, Blok, MJ, Bodrogi, I, Bonadona, V, Bonanni, B, Bondavalli, D, Boonen, SE, Borde, J, Borg, A, Bradbury, AR, Brady, A, Brewer, C, Brunet, J, Buecher, B, Buys, SS, Cabezas-Camarero, S, Caldes, T, Caliebe, A, Caligo, MA, Calvello, M, Campbell, IG, Carnevali, I, Carrasco, E, Chan, TL, Chu, ATW, Chung, WK, Claes, KBM, Cook, J, Cortesi, L, Couch, FJ, Daly, MB, Damante, G, Darder, E, Davidson, R, de la Hoya, M, Della Puppa, L, Dennis, J, Diez, O, Ding, YC, Ditsch, N, Domchek, SM, Donaldson, A, Dworniczak, B, Easton, DF, Eccles, DM, Eeles, RA, Ehrencrona, H, Ejlertsen, B, Engel, C, Evans, DG, Faivre, L, Faust, U, Feliubadalo, L, Foretova, L, Fostira, F, Fountzilas, G, Frost, D, Garcia-Barberan, V, Garre, P, Gauthier-Villars, M, Geczi, L, Gehrig, A, Gerdes, A-M, Gesta, P, Giannini, G, Glendon, G, Godwin, AK, Goldgar, DE, Greene, MH, Gutierrez-Barrera, AM, Hahnen, E, Hamann, U, Hauke, J, Herold, N, Hogervorst, FBL, Honisch, E, Hopper, JL, Hulick, PJ, Izatt, L, Jager, A, James, P, Janavicius, R, Jensen, UB, Jensen, TD, Johannsson, OT, John, EM, Joseph, V, Kang, E, Kast, K, Kiiski, J, Kim, S-W, Kim, Z, Ko, K-P, Konstantopoulou, I, Kramer, G, Krogh, L, Kruse, TA, Kwong, A, Larsen, M, Lasset, C, Lautrup, C, Lazaro, C, Lee, J, Lee, JW, Lee, MH, Lemke, J, Lesueur, F, Liljegren, A, Lindblom, A, Llovet, P, Lopez-Fernandez, A, Lopez-Perolio, I, Lorca, V, Loud, JT, Ma, ESK, Mai, PL, Manoukian, S, Mari, V, Martin, L, Matricardi, L, Mebirouk, N, Medici, V, Meijers-Heijboer, HEJ, Meindl, A, Mensenkamp, AR, Miller, C, Gomes, DM, Montagna, M, Mooij, TM, Moserle, L, Mouret-Fourme, E, Mulligan, AM, Nathanson, KL, Navratilova, M, Nevanlinna, H, Niederacher, D, Nielsen, FCC, Nikitina-Zake, L, Offit, K, Olah, E, Olopade, O, Ong, K-R, Osorio, A, Ott, C-E, Palli, D, Park, SK, Parsons, MT, Pedersen, IS, Peissel, B, Peixoto, A, Perez-Segura, P, Peterlongo, P, Petersen, AH, Porteous, ME, Angel Pujana, M, Radice, P, Ramser, J, Rantala, J, Rashid, MU, Rhiem, K, Rizzolo, P, Robson, ME, Rookus, MA, Rossing, CM, Ruddy, KJ, Santos, C, Saule, C, Scarpitta, R, Schmutzler, RK, Schuster, H, Senter, L, Seynaeve, CM, Shah, PD, Sharma, P, Shin, VY, Silvestri, V, Simard, J, Singer, CF, Skytte, A-B, Snape, K, Solano, AR, Soucy, P, Southey, MC, Spurdle, AB, Steele, L, Steinemann, D, Stoppa-Lyonnet, D, Stradella, A, Sunde, L, Sutter, C, Tan, YY, Teixeira, MR, Teo, SH, Thomassen, M, Tibiletti, MG, Tischkowitz, M, Tognazzo, S, Toland, AE, Tommasi, S, Torres, D, Toss, A, Trainer, AH, Tung, N, van Asperen, CJ, van der Baan, FH, van der Kolk, LE, van der Luijt, RB, van Hest, LP, Varesco, L, Varon-Mateeva, R, Viel, A, Vierstraete, J, Villa, R, von Wachenfeldt, A, Wagner, P, Wang-Gohrke, S, Wappenschmidt, B, Weitzel, JN, Wieme, G, Yadav, S, Yannoukakos, D, Yoon, S-Y, Zanzottera, C, Zorn, KK, D'Amico, A, Freedman, ML, Pomerantz, MM, Chenevix-Trench, G, Antoniou, AC, Neuhausen, SL, Ottini, L, Nielsen, HR, and Rebbeck, TR

Abstract

Pathogenic sequence variants (PSV) in BRCA1 or BRCA2 (BRCA1/2) are associated with increased risk and severity of prostate cancer. We evaluated whether PSVs in BRCA1/2 were associated with risk of overall prostate cancer or high grade (Gleason 8+) prostate cancer using an international sample of 65 BRCA1 and 171 BRCA2 male PSV carriers with prostate cancer, and 3,388 BRCA1 and 2,880 BRCA2 male PSV carriers without prostate cancer. PSVs in the 3' region of BRCA2 (c.7914+) were significantly associated with elevated risk of prostate cancer compared with reference bin c.1001-c.7913 [HR = 1.78; 95% confidence interval (CI), 1.25-2.52; P = 0.001], as well as elevated risk of Gleason 8+ prostate cancer (HR = 3.11; 95% CI, 1.63-5.95; P = 0.001). c.756-c.1000 was also associated with elevated prostate cancer risk (HR = 2.83; 95% CI, 1.71-4.68; P = 0.00004) and elevated risk of Gleason 8+ prostate cancer (HR = 4.95; 95% CI, 2.12-11.54; P = 0.0002). No genotype-phenotype associations were detected for PSVs in BRCA1. These results demonstrate that specific BRCA2 PSVs may be associated with elevated risk of developing aggressive prostate cancer. SIGNIFICANCE: Aggressive prostate cancer risk in BRCA2 mutation carriers may vary according to the specific BRCA2 mutation inherited by the at-risk individual.

Published
2020

5. Role of Genetic Testing for Inherited Prostate Cancer Risk: Philadelphia Prostate Cancer Consensus Conference 2017

Author

Giri, VN, Knudsen, KE, Kelly, WK, Abida, W, Andriole, GL, Bangma, C.H., Bekelman, JE, Benson, MC, Blanco, A, Burnett, A, Catalona, WJ, Cooney, KA, Cooperberg, M, Crawford, DE, Den, RB, Dicker, AP, Eggener, S, Fleshner, N, Freedman, ML, Hamdy, FC, Hoffman-Censits, J, Hurwitz, MD, Hyatt, C, Isaacs, WB, Kane, CJ, Kantoff, P, Karnes, RJ, Karsh, LI, Klein, EA, Lin, DW, Loughlin, KR, Lu-Yao, G, Malkowicz, SB, Mann, MJ, Mark, JR, McCue, PA, Miner, MM, Morgan, T, Moul, JW, Myers, RE, Nielsen, SM, Obeid, E, Pavlovich, CP, Peiper, SC, Penson, DF, Petrylak, D, Pettaway, CA, Pilarski, R, Pinto, PA, Poage, W, Raj, GV, Rebbeck, TR, Robson, ME, Rosenberg, MT, Sandler, H, Sartor, O, Schaeffer, E, Schwartz, GF, Shahin, MS, Shore, ND, Shuch, B, Soule, HR, Tomlins, SA, Trabulsi, EJ, Uzzo, R, Griend, DJV, Walsh, PC, Weil, CJ, Wender, R, Gomella, LG, Giri, VN, Knudsen, KE, Kelly, WK, Abida, W, Andriole, GL, Bangma, C.H., Bekelman, JE, Benson, MC, Blanco, A, Burnett, A, Catalona, WJ, Cooney, KA, Cooperberg, M, Crawford, DE, Den, RB, Dicker, AP, Eggener, S, Fleshner, N, Freedman, ML, Hamdy, FC, Hoffman-Censits, J, Hurwitz, MD, Hyatt, C, Isaacs, WB, Kane, CJ, Kantoff, P, Karnes, RJ, Karsh, LI, Klein, EA, Lin, DW, Loughlin, KR, Lu-Yao, G, Malkowicz, SB, Mann, MJ, Mark, JR, McCue, PA, Miner, MM, Morgan, T, Moul, JW, Myers, RE, Nielsen, SM, Obeid, E, Pavlovich, CP, Peiper, SC, Penson, DF, Petrylak, D, Pettaway, CA, Pilarski, R, Pinto, PA, Poage, W, Raj, GV, Rebbeck, TR, Robson, ME, Rosenberg, MT, Sandler, H, Sartor, O, Schaeffer, E, Schwartz, GF, Shahin, MS, Shore, ND, Shuch, B, Soule, HR, Tomlins, SA, Trabulsi, EJ, Uzzo, R, Griend, DJV, Walsh, PC, Weil, CJ, Wender, R, and Gomella, LG

Published
2018

6. Genome-wide association study identifies multiple risk loci for renal cell carcinoma

Author

Scelo, G, Purdue, MP, Brown, KM, Johansson, M, Wang, Z, Eckel-Passow, JE, Ye, Y, Hoffman, JN, Choi, J, Foll, M, Gaborieau, V, Machiela, MJ, Colli, LM, Li, P, Sampson, JN, Abedi-Ardekani, B, Besse, C, Blanche, H, Boland, A, Burdette, L, Charbrier, A, Durand, G, Le Calvez-Kelm, F, Prokhortchouk, E, Robinot, N, Skyrabin, KG, Wozniak, MB, Yeager, M, Basta-Jovanovich, G, Dzamic, Z, Foretova, L, Holcatova, I, Janout, V, Mates, D, Mukeriya, A, Rascu, S, Zaridze, D, Bencko, V, Cybulski, C, Fabianova, E, Jinga, V, Lissowska, J, Lubinski, J, Navratilova, M, Rudnai, P, Szeszenia-Dabrowska, N, Benhamou, S, Cancel-Tassin, G, Cussenot, O, Baglietto, L, Boeing, H, Khaw, K-T, Weiderpass, E, Ljungberg, B, Sitaram, RT, Bruinsma, F, Jordan, SJ, Severi, G, Winship, I, Hveem, K, Vatten, LJ, Fletcher, T, Koppova, K, Larsson, SC, Wolk, A, Banks, RE, Selby, PJ, Easton, DF, Pharoah, P, Andreotti, G, Beane Freeman, LE, Koutros, S, Albanes, D, Mannisto, S, Weinstein, S, Clark, PE, Edwards, TL, Lipworth, L, Gapstur, SM, Stevens, VL, Carol, H, Freedman, ML, Pomerantz, MM, Cho, E, Kraft, P, Preston, MA, Wilson, KM, Gaziano, JM, Sesso, HD, Black, A, Freedman, ND, Huang, WY, Anema, JG, Kahnoski, RJ, Lane, BR, Noyes, SL, Petillo, D, Teh, BT, Peters, U, White, E, Anderson, GL, Johnson, L, Luo, J, Buring, J, Lee, I-M, Chow, W-H, Moore, LE, Wood, C, Eisen, T, Henrion, M, Larkin, J, Barman, P, Leibovich, BC, Choueiri, TK, Lathrop, GM, Rothman, N, Deleuze, J-F, McKay, JD, Parker, AS, Wu, X, Houlston, RS, Brennan, P, and Chanock, SJ

Abstract

Previous genome-wide association studies (GWAS) have identified six risk loci for renal cell carcinoma (RCC). We conducted a meta-analysis of two new scans of 5,198 cases and 7,331 controls together with four existing scans, totalling 10,784 cases and 20,406 controls of European ancestry. Twenty-four loci were tested in an additional 3,182 cases and 6,301 controls. We confirm the six known RCC risk loci and identify seven new loci at 1p32.3 (rs4381241, P=3.1 × 10−10), 3p22.1 (rs67311347, P=2.5 × 10−8), 3q26.2 (rs10936602, P=8.8 × 10−9), 8p21.3 (rs2241261, P=5.8 × 10−9), 10q24.33-q25.1 (rs11813268, P=3.9 × 10−8), 11q22.3 (rs74911261, P=2.1 × 10−10) and 14q24.2 (rs4903064, P=2.2 × 10−24). Expression quantitative trait analyses suggest plausible candidate genes at these regions that may contribute to RCC susceptibility.

Published
2017

7. Enrichment of putative PAX8 target genes at serous epithelial ovarian cancer susceptibility loci

Author

Kar, SP, Adler, E, Tyrer, J, Hazelett, D, Anton-Culver, H, Bandera, EV, Beckmann, MW, Berchuck, A, Bogdanova, N, Brinton, L, Butzow, R, Campbell, I, Carty, K, Chang-Claude, J, Cook, LS, Cramer, DW, Cunningham, JM, Dansonka-Mieszkowska, A, Doherty, JA, Doerk, T, Duerst, M, Eccles, D, Fasching, PA, Flanagan, J, Gentry-Maharaj, A, Glasspool, R, Goode, EL, Goodman, MT, Gronwald, J, Heitz, F, Hildebrandt, MAT, Hogdall, E, Hogdall, CK, Huntsman, DG, Jensen, A, Karlan, BY, Kelemen, LE, Kiemeney, LA, Kjaer, SK, Kupryjanczyk, J, Lambrechts, D, Levine, DA, Li, Q, Lissowska, J, Lu, KH, Lubinski, J, Massuger, LFAG, McGuire, V, McNeish, I, Menon, U, Modugno, F, Monteiro, AN, Moysich, KB, Ness, RB, Nevanlinna, H, Paul, J, Pearce, CL, Pejovic, T, Permuth, JB, Phelan, C, Pike, MC, Poole, EM, Ramus, SJ, Risch, HA, Rossing, MA, Salvesen, HB, Schildkraut, JM, Sellers, TA, Sherman, M, Siddiqui, N, Sieh, W, Song, H, Southey, M, Terry, KL, Tworoger, SS, Walsh, C, Wentzensen, N, Whittemore, AS, Wu, AH, Yang, H, Zheng, W, Ziogas, A, Freedman, ML, Gayther, SA, Pharoah, PDP, Lawrenson, K, Kar, SP, Adler, E, Tyrer, J, Hazelett, D, Anton-Culver, H, Bandera, EV, Beckmann, MW, Berchuck, A, Bogdanova, N, Brinton, L, Butzow, R, Campbell, I, Carty, K, Chang-Claude, J, Cook, LS, Cramer, DW, Cunningham, JM, Dansonka-Mieszkowska, A, Doherty, JA, Doerk, T, Duerst, M, Eccles, D, Fasching, PA, Flanagan, J, Gentry-Maharaj, A, Glasspool, R, Goode, EL, Goodman, MT, Gronwald, J, Heitz, F, Hildebrandt, MAT, Hogdall, E, Hogdall, CK, Huntsman, DG, Jensen, A, Karlan, BY, Kelemen, LE, Kiemeney, LA, Kjaer, SK, Kupryjanczyk, J, Lambrechts, D, Levine, DA, Li, Q, Lissowska, J, Lu, KH, Lubinski, J, Massuger, LFAG, McGuire, V, McNeish, I, Menon, U, Modugno, F, Monteiro, AN, Moysich, KB, Ness, RB, Nevanlinna, H, Paul, J, Pearce, CL, Pejovic, T, Permuth, JB, Phelan, C, Pike, MC, Poole, EM, Ramus, SJ, Risch, HA, Rossing, MA, Salvesen, HB, Schildkraut, JM, Sellers, TA, Sherman, M, Siddiqui, N, Sieh, W, Song, H, Southey, M, Terry, KL, Tworoger, SS, Walsh, C, Wentzensen, N, Whittemore, AS, Wu, AH, Yang, H, Zheng, W, Ziogas, A, Freedman, ML, Gayther, SA, Pharoah, PDP, and Lawrenson, K

Abstract

BACKGROUND: Genome-wide association studies (GWAS) have identified 18 loci associated with serous ovarian cancer (SOC) susceptibility but the biological mechanisms driving these findings remain poorly characterised. Germline cancer risk loci may be enriched for target genes of transcription factors (TFs) critical to somatic tumorigenesis. METHODS: All 615 TF-target sets from the Molecular Signatures Database were evaluated using gene set enrichment analysis (GSEA) and three GWAS for SOC risk: discovery (2196 cases/4396 controls), replication (7035 cases/21 693 controls; independent from discovery), and combined (9627 cases/30 845 controls; including additional individuals). RESULTS: The PAX8-target gene set was ranked 1/615 in the discovery (PGSEA<0.001; FDR=0.21), 7/615 in the replication (PGSEA=0.004; FDR=0.37), and 1/615 in the combined (PGSEA<0.001; FDR=0.21) studies. Adding other genes reported to interact with PAX8 in the literature to the PAX8-target set and applying an alternative to GSEA, interval enrichment, further confirmed this association (P=0.006). Fifteen of the 157 genes from this expanded PAX8 pathway were near eight loci associated with SOC risk at P<10-5 (including six with P<5 × 10-8). The pathway was also associated with differential gene expression after shRNA-mediated silencing of PAX8 in HeyA8 (PGSEA=0.025) and IGROV1 (PGSEA=0.004) SOC cells and several PAX8 targets near SOC risk loci demonstrated in vitro transcriptomic perturbation. CONCLUSIONS: Putative PAX8 target genes are enriched for common SOC risk variants. This finding from our agnostic evaluation is of particular interest given that PAX8 is well-established as a specific marker for the cell of origin of SOC.

Published
2017

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

Author

Gusev, A, Shi, H, Kichaev, G, Pomerantz, M, Li, F, Long, HW, Ingles, SA, Kittles, RA, Strom, SS, Rybicki, BA, Nemesure, B, Isaacs, WB, Zheng, W, Pettaway, CA, Yeboah, ED, Tettey, Y, Biritwum, RB, Adjei, AA, Tay, E, Truelove, A, Niwa, S, Chokkalingam, AP, John, EM, Murphy, AB, Signorello, LB, Carpten, J, Leske, MC, Wu, S-Y, Hennis, AJM, Neslund-Dudas, C, Hsing, AW, Chu, L, Goodman, PJ, Klein, EA, Witte, JS, Casey, G, Kaggwa, S, Cook, MB, Stram, DO, Blot, WJ, Eeles, RA, Easton, D, Kote-Jarai, Z, Al Olama, AA, Benlloch, S, Muir, K, Giles, GG, Southey, MC, Fitzgerald, LM, Gronberg, H, Wiklund, F, Aly, M, Henderson, BE, Schleutker, J, Wahlfors, T, Tammela, TLJ, Nordestgaard, BG, Key, TJ, Travis, RC, Neal, DE, Donovan, JL, Hamdy, FC, Pharoah, P, Pashayan, N, Khaw, K-T, Stanford, JL, Thibodeau, SN, McDonnell, SK, Schaid, DJ, Maier, C, Vogel, W, Luedeke, M, Herkommer, K, Kibel, AS, Cybulski, C, Wokolorczyk, D, Kluzniak, W, Cannon-Albright, L, Teerlink, C, Brenner, H, Dieffenbach, AK, Arndt, V, Park, JY, Sellers, TA, Lin, H-Y, Slavov, C, Kaneva, R, Mitev, V, Batra, J, Spurdle, A, Clements, JA, Teixeira, MR, Pandha, H, Michael, A, Paulo, P, Maia, S, Kierzek, A, Conti, DV, Albanes, D, Berg, C, Berndt, SI, Campa, D, Crawford, ED, Diver, WR, Gapstur, SM, Gaziano, JM, Giovannucci, E, Hoover, R, Hunter, DJ, Johansson, M, Kraft, P, Le Marchand, L, Lindstrom, S, Navarro, C, Overvad, K, Riboli, E, Siddiq, A, Stevens, VL, Trichopoulos, D, Vineis, P, Yeager, M, Trynka, G, Raychaudhuri, S, Schumacher, FR, Price, AL, Freedman, ML, Haiman, CA, Pasaniuc, B, Cook, M, Guy, M, Govindasami, K, Leongamornlert, D, Sawyer, EJ, Wilkinson, R, Saunders, EJ, Tymrakiewicz, M, Dadaev, T, Morgan, A, Fisher, C, Hazel, S, Livni, N, Lophatananon, A, Pedersen, J, Hopper, JL, Adolfson, J, Stattin, P, Johansson, J-E, Cavalli-Bjoerkman, C, Karlsson, A, Broms, M, Auvinen, A, Kujala, P, Maeaettaenen, L, Murtola, T, Taari, K, Weischer, M, Nielsen, SF, Klarskov, P, Roder, A, Iversen, P, Wallinder, H, Gustafsson, S, Cox, A, Brown, P, George, A, Marsden, G, Lane, A, Davis, M, Tillmans, L, Riska, S, Wang, L, Rinckleb, A, Lubiski, J, Stegmaier, C, Pow-Sang, J, Park, H, Radlein, S, Rincon, M, Haley, J, Zachariah, B, Kachakova, D, Popov, E, Mitkova, A, Vlahova, A, Dikov, T, Christova, S, Heathcote, P, Wood, G, Malone, G, Saunders, P, Eckert, A, Yeadon, T, Kerr, K, Collins, A, Turner, M, Srinivasan, S, Kedda, M-A, Alexander, K, Omara, T, Wu, H, Henrique, R, Pinto, P, Santos, J, Barros-Silva, J, and Consortium, PRACTICAL

Subjects
urologic and male genital diseases
Abstract

Although genome-wide association studies have identified over 100 risk loci that explain ~33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa.

Published
2016

9. Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus

Author

Lawrenson, K, Kar, S, McCue, K, Kuchenbaeker, K, Michailidou, K, Tyrer, J, Beesley, J, Ramus, SJ, Li, Q, Delgado, MK, Lee, JM, Aittomaki, K, Andrulis, IL, Anton-Culver, H, Arndt, V, Arun, BK, Arver, B, Bandera, EV, Barile, M, Barkardottir, RB, Barrowdale, D, Beckmann, MW, Benitez, J, Berchuck, A, Bisogna, M, Bjorge, L, Blomqvist, C, Blot, W, Bogdanova, N, Bojesen, A, Bojesen, SE, Bolla, MK, Bonanni, B, Borresen-Dale, A-L, Brauch, H, Brennan, P, Brenner, H, Bruinsma, F, Brunet, J, Buhari, SA, Burwinkel, B, Butzow, R, Buys, SS, Cai, Q, Caldes, T, Campbell, I, Canniotto, R, Chang-Claude, J, Chiquette, J, Choi, J-Y, Claes, KBM, Cook, LS, Cox, A, Cramer, DW, Cross, SS, Cybulski, C, Czene, K, Daly, MB, Damiola, F, Dansonka-Mieszkowska, A, Darabi, H, Dennis, J, Devilee, P, Diez, O, Doherty, JA, Domchek, SM, Dorfling, CM, Doerk, T, Dumont, M, Ehrencrona, H, Ejlertsen, B, Ellis, S, Engel, C, Lee, E, Evans, DG, Fasching, PA, Feliubadalo, L, Figueroa, J, Flesch-Janys, D, Fletcher, O, Flyger, H, Foretova, L, Fostira, F, Foulkes, WD, Fridley, BL, Friedman, E, Frost, D, Gambino, G, Ganz, PA, Garber, J, Garcia-Closas, M, Gentry-Maharaj, A, Ghoussaini, M, Giles, GG, Glasspool, R, Godwin, AK, Goldberg, MS, Goldgar, DE, Gonzalez-Neira, A, Goode, EL, Goodman, MT, Greene, MH, Gronwald, J, Guenel, P, Haiman, CA, Hall, P, Hallberg, E, Hamann, U, Hansen, TVO, Harrington, PA, Hartman, M, Hassan, N, Healey, S, Heitz, F, Herzog, J, Hogdall, E, Hogdall, CK, Hogervorst, FBL, Hollestelle, A, Hopper, JL, Hulick, PJ, Huzarski, T, Imyanitov, EN, Isaacs, C, Ito, H, Jakubowska, A, Janavicius, R, Jensen, A, John, EM, Johnson, N, Kabisch, M, Kang, D, Kapuscinski, M, Karlan, BY, Khan, S, Kiemeney, LA, Kjaer, SK, Knight, JA, Konstantopoulou, I, Kosma, V-M, Kristensen, V, Kupryjanczyk, J, Kwong, A, de la Hoya, M, Laitman, Y, Lambrechts, D, Le, N, De Leeneer, K, Lester, J, Levine, DA, Li, J, Lindblom, A, Long, J, Lophatananon, A, Loud, JT, Lu, K, Lubinski, J, Mannermaa, A, Manoukian, S, Le Marchand, L, Margolin, S, Marme, F, Massuger, LFAG, Matsuo, K, Mazoyer, S, McGuffog, L, McLean, C, McNeish, I, Meindl, A, Menon, U, Mensenkamp, AR, Milne, RL, Montagna, M, Moysich, KB, Muir, K, Mulligan, AM, Nathanson, KL, Ness, RB, Neuhausen, SL, Nevanlinna, H, Nord, S, Nussbaum, RL, Odunsi, K, Offit, K, Olah, E, Olopade, OI, Olson, JE, Olswold, C, O'Malley, D, Orlow, I, Orr, N, Osorio, A, Park, SK, Pearce, CL, Pejovic, T, Peterlongo, P, Pfeiler, G, Phelan, CM, Poole, EM, Pylkas, K, Radice, P, Rantala, J, Rashid, MU, Rennert, G, Rhenius, V, Rhiem, K, Risch, HA, Rodriguez, G, Rossing, MA, Rudolph, A, Salvesen, HB, Sangrajrang, S, Sawyer, EJ, Schildkraut, JM, Schmidt, MK, Schmutzler, RK, Sellers, TA, Seynaeve, C, Shah, M, Shen, C-Y, Shu, X-O, Sieh, W, Singer, CF, Sinilnikova, OM, Slager, S, Song, H, Soucy, P, Southey, MC, Stenmark-Askmalm, M, Stoppa-Lyonnet, D, Sutter, C, Swerdlow, A, Tchatchou, S, Teixeira, MR, Teo, SH, Terry, KL, Terry, MB, Thomassen, M, Tibiletti, MG, Tihomirova, L, Tognazzo, S, Toland, AE, Tomlinson, I, Torres, D, Truong, T, Tseng, C-C, Tung, N, Tworoger, SS, Vachon, C, van den Ouweland, AMW, van Doorn, HC, van Rensburg, EJ, Van't Veer, LJ, Vanderstichele, A, Vergote, I, Vijai, J, Wang, Q, Wang-Gohrke, S, Weitzel, JN, Wentzensen, N, Whittemore, AS, Wildiers, H, Winqvist, R, Wu, AH, Yannoukakos, D, Yoon, S-Y, Yu, J-C, Zheng, W, Zheng, Y, Khanna, KK, Simard, J, Monteiro, AN, French, JD, Couch, FJ, Freedman, ML, Easton, DF, Dunning, AM, Pharoah, PD, Edwards, SL, Chenevix-Trench, G, Antoniou, AC, Gayther, SA, Lawrenson, K, Kar, S, McCue, K, Kuchenbaeker, K, Michailidou, K, Tyrer, J, Beesley, J, Ramus, SJ, Li, Q, Delgado, MK, Lee, JM, Aittomaki, K, Andrulis, IL, Anton-Culver, H, Arndt, V, Arun, BK, Arver, B, Bandera, EV, Barile, M, Barkardottir, RB, Barrowdale, D, Beckmann, MW, Benitez, J, Berchuck, A, Bisogna, M, Bjorge, L, Blomqvist, C, Blot, W, Bogdanova, N, Bojesen, A, Bojesen, SE, Bolla, MK, Bonanni, B, Borresen-Dale, A-L, Brauch, H, Brennan, P, Brenner, H, Bruinsma, F, Brunet, J, Buhari, SA, Burwinkel, B, Butzow, R, Buys, SS, Cai, Q, Caldes, T, Campbell, I, Canniotto, R, Chang-Claude, J, Chiquette, J, Choi, J-Y, Claes, KBM, Cook, LS, Cox, A, Cramer, DW, Cross, SS, Cybulski, C, Czene, K, Daly, MB, Damiola, F, Dansonka-Mieszkowska, A, Darabi, H, Dennis, J, Devilee, P, Diez, O, Doherty, JA, Domchek, SM, Dorfling, CM, Doerk, T, Dumont, M, Ehrencrona, H, Ejlertsen, B, Ellis, S, Engel, C, Lee, E, Evans, DG, Fasching, PA, Feliubadalo, L, Figueroa, J, Flesch-Janys, D, Fletcher, O, Flyger, H, Foretova, L, Fostira, F, Foulkes, WD, Fridley, BL, Friedman, E, Frost, D, Gambino, G, Ganz, PA, Garber, J, Garcia-Closas, M, Gentry-Maharaj, A, Ghoussaini, M, Giles, GG, Glasspool, R, Godwin, AK, Goldberg, MS, Goldgar, DE, Gonzalez-Neira, A, Goode, EL, Goodman, MT, Greene, MH, Gronwald, J, Guenel, P, Haiman, CA, Hall, P, Hallberg, E, Hamann, U, Hansen, TVO, Harrington, PA, Hartman, M, Hassan, N, Healey, S, Heitz, F, Herzog, J, Hogdall, E, Hogdall, CK, Hogervorst, FBL, Hollestelle, A, Hopper, JL, Hulick, PJ, Huzarski, T, Imyanitov, EN, Isaacs, C, Ito, H, Jakubowska, A, Janavicius, R, Jensen, A, John, EM, Johnson, N, Kabisch, M, Kang, D, Kapuscinski, M, Karlan, BY, Khan, S, Kiemeney, LA, Kjaer, SK, Knight, JA, Konstantopoulou, I, Kosma, V-M, Kristensen, V, Kupryjanczyk, J, Kwong, A, de la Hoya, M, Laitman, Y, Lambrechts, D, Le, N, De Leeneer, K, Lester, J, Levine, DA, Li, J, Lindblom, A, Long, J, Lophatananon, A, Loud, JT, Lu, K, Lubinski, J, Mannermaa, A, Manoukian, S, Le Marchand, L, Margolin, S, Marme, F, Massuger, LFAG, Matsuo, K, Mazoyer, S, McGuffog, L, McLean, C, McNeish, I, Meindl, A, Menon, U, Mensenkamp, AR, Milne, RL, Montagna, M, Moysich, KB, Muir, K, Mulligan, AM, Nathanson, KL, Ness, RB, Neuhausen, SL, Nevanlinna, H, Nord, S, Nussbaum, RL, Odunsi, K, Offit, K, Olah, E, Olopade, OI, Olson, JE, Olswold, C, O'Malley, D, Orlow, I, Orr, N, Osorio, A, Park, SK, Pearce, CL, Pejovic, T, Peterlongo, P, Pfeiler, G, Phelan, CM, Poole, EM, Pylkas, K, Radice, P, Rantala, J, Rashid, MU, Rennert, G, Rhenius, V, Rhiem, K, Risch, HA, Rodriguez, G, Rossing, MA, Rudolph, A, Salvesen, HB, Sangrajrang, S, Sawyer, EJ, Schildkraut, JM, Schmidt, MK, Schmutzler, RK, Sellers, TA, Seynaeve, C, Shah, M, Shen, C-Y, Shu, X-O, Sieh, W, Singer, CF, Sinilnikova, OM, Slager, S, Song, H, Soucy, P, Southey, MC, Stenmark-Askmalm, M, Stoppa-Lyonnet, D, Sutter, C, Swerdlow, A, Tchatchou, S, Teixeira, MR, Teo, SH, Terry, KL, Terry, MB, Thomassen, M, Tibiletti, MG, Tihomirova, L, Tognazzo, S, Toland, AE, Tomlinson, I, Torres, D, Truong, T, Tseng, C-C, Tung, N, Tworoger, SS, Vachon, C, van den Ouweland, AMW, van Doorn, HC, van Rensburg, EJ, Van't Veer, LJ, Vanderstichele, A, Vergote, I, Vijai, J, Wang, Q, Wang-Gohrke, S, Weitzel, JN, Wentzensen, N, Whittemore, AS, Wildiers, H, Winqvist, R, Wu, AH, Yannoukakos, D, Yoon, S-Y, Yu, J-C, Zheng, W, Zheng, Y, Khanna, KK, Simard, J, Monteiro, AN, French, JD, Couch, FJ, Freedman, ML, Easton, DF, Dunning, AM, Pharoah, PD, Edwards, SL, Chenevix-Trench, G, Antoniou, AC, and Gayther, SA

Abstract

A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10(-20)), ER-negative BC (P=1.1 × 10(-13)), BRCA1-associated BC (P=7.7 × 10(-16)) and triple negative BC (P-diff=2 × 10(-5)). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10(-3)) and ABHD8 (P<2 × 10(-3)). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3'-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk.

Published
2016

10. Genome-wide significant risk associations for mucinous ovarian carcinoma

Author

Kelemen, LE, Lawrenson, K, Tyrer, J, Li, Q, Lee, JM, Seo, J-H, Phelan, CM, Beesley, J, Chen, X, Spindler, TJ, Aben, KKH, Anton-Culver, H, Antonenkova, N, Baker, H, Bandera, EV, Bean, Y, Beckmann, MW, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bruinsma, F, Butzow, R, Campbell, IG, Carty, K, Chang-Claude, J, Chen, YA, Chen, Z, Cook, LS, Cramer, DW, Cunningham, JM, Cybulski, C, Dansonka-Mieszkowska, A, Dennis, J, Dicks, E, Doherty, JA, Doerk, T, du Bois, A, Duerst, M, Eccles, D, Easton, DT, Edwards, RP, Eilber, U, Ekici, AB, Engelholm, SA, Fasching, PA, Fridley, BL, Gao, Y-T, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Goode, EL, Goodman, MT, Grownwald, J, Harrington, P, Harter, P, Hasmad, HN, Hein, A, Heitz, F, Hildebrandt, MAT, Hillemanns, P, Hogdall, E, Hogdall, C, Hosono, S, Iversen, ES, Jakubowska, A, Jensen, A, Ji, B-T, Karlan, BY, Kellar, M, Kelley, JL, Kiemeney, LA, Krakstad, C, Kjaer, SK, Kupryjanczyk, J, Lambrechts, D, Lambrechts, S, Le, ND, Lee, AW, Lele, S, Leminen, A, Lester, J, Levine, DA, Liang, D, Lissowska, J, Lu, K, Lubinski, J, Lundvall, L, Massuger, LFAG, Matsuo, K, McGuire, V, McLaughlin, JR, McNeish, I, Menon, U, Modugno, F, Moes-Sosnowska, J, Moysich, KB, Narod, SA, Nedergaard, L, Ness, RB, Nevanlinna, H, Adenan, NAM, Odunsi, K, Olson, SH, Orlow, I, Orsulic, S, Weber, RP, Paul, J, Pearce, CL, Pejovic, T, Pelttari, LM, Permuth-Wey, J, Pike, MC, Poole, EM, Ramus, SJ, Risch, HA, Rosen, B, Rossing, MA, Rothstein, JH, Rudolph, A, Runnebaum, IB, Rzepecka, IK, Salvesen, HB, Schildkraut, JM, Schwaab, I, Shu, X-O, Shvetsov, YB, Siddiqui, N, Sieh, W, Song, H, Southey, MC, Sucheston, L, Tangen, IL, Teo, S-H, Terry, KL, Thompson, PJ, Tworoger, SS, van Altena, AM, Van Nieuwenhuysen, E, Vergote, I, Vierkant, RA, Wang-Gohrke, S, Walsh, C, Wentzensen, N, Whittemore, AS, Wicklund, KG, Wilkens, LR, Sawicki, W, Woo, Y-L, Wu, X, Wu, AH, Yang, H, Zheng, W, Ziogas, A, Sellers, TA, Freedman, ML, Chenevix-Trench, G, Pharoah, PDP, Gayther, SA, Berchuck, A, Kelemen, LE, Lawrenson, K, Tyrer, J, Li, Q, Lee, JM, Seo, J-H, Phelan, CM, Beesley, J, Chen, X, Spindler, TJ, Aben, KKH, Anton-Culver, H, Antonenkova, N, Baker, H, Bandera, EV, Bean, Y, Beckmann, MW, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bruinsma, F, Butzow, R, Campbell, IG, Carty, K, Chang-Claude, J, Chen, YA, Chen, Z, Cook, LS, Cramer, DW, Cunningham, JM, Cybulski, C, Dansonka-Mieszkowska, A, Dennis, J, Dicks, E, Doherty, JA, Doerk, T, du Bois, A, Duerst, M, Eccles, D, Easton, DT, Edwards, RP, Eilber, U, Ekici, AB, Engelholm, SA, Fasching, PA, Fridley, BL, Gao, Y-T, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Goode, EL, Goodman, MT, Grownwald, J, Harrington, P, Harter, P, Hasmad, HN, Hein, A, Heitz, F, Hildebrandt, MAT, Hillemanns, P, Hogdall, E, Hogdall, C, Hosono, S, Iversen, ES, Jakubowska, A, Jensen, A, Ji, B-T, Karlan, BY, Kellar, M, Kelley, JL, Kiemeney, LA, Krakstad, C, Kjaer, SK, Kupryjanczyk, J, Lambrechts, D, Lambrechts, S, Le, ND, Lee, AW, Lele, S, Leminen, A, Lester, J, Levine, DA, Liang, D, Lissowska, J, Lu, K, Lubinski, J, Lundvall, L, Massuger, LFAG, Matsuo, K, McGuire, V, McLaughlin, JR, McNeish, I, Menon, U, Modugno, F, Moes-Sosnowska, J, Moysich, KB, Narod, SA, Nedergaard, L, Ness, RB, Nevanlinna, H, Adenan, NAM, Odunsi, K, Olson, SH, Orlow, I, Orsulic, S, Weber, RP, Paul, J, Pearce, CL, Pejovic, T, Pelttari, LM, Permuth-Wey, J, Pike, MC, Poole, EM, Ramus, SJ, Risch, HA, Rosen, B, Rossing, MA, Rothstein, JH, Rudolph, A, Runnebaum, IB, Rzepecka, IK, Salvesen, HB, Schildkraut, JM, Schwaab, I, Shu, X-O, Shvetsov, YB, Siddiqui, N, Sieh, W, Song, H, Southey, MC, Sucheston, L, Tangen, IL, Teo, S-H, Terry, KL, Thompson, PJ, Tworoger, SS, van Altena, AM, Van Nieuwenhuysen, E, Vergote, I, Vierkant, RA, Wang-Gohrke, S, Walsh, C, Wentzensen, N, Whittemore, AS, Wicklund, KG, Wilkens, LR, Sawicki, W, Woo, Y-L, Wu, X, Wu, AH, Yang, H, Zheng, W, Ziogas, A, Sellers, TA, Freedman, ML, Chenevix-Trench, G, Pharoah, PDP, Gayther, SA, and Berchuck, A

Abstract

Genome-wide association studies have identified several risk associations for ovarian carcinomas but not for mucinous ovarian carcinomas (MOCs). Our analysis of 1,644 MOC cases and 21,693 controls with imputation identified 3 new risk associations: rs752590 at 2q13 (P = 3.3 × 10(-8)), rs711830 at 2q31.1 (P = 7.5 × 10(-12)) and rs688187 at 19q13.2 (P = 6.8 × 10(-13)). We identified significant expression quantitative trait locus (eQTL) associations for HOXD9 at 2q31.1 in ovarian (P = 4.95 × 10(-4), false discovery rate (FDR) = 0.003) and colorectal (P = 0.01, FDR = 0.09) tumors and for PAX8 at 2q13 in colorectal tumors (P = 0.03, FDR = 0.09). Chromosome conformation capture analysis identified interactions between the HOXD9 promoter and risk-associated SNPs at 2q31.1. Overexpressing HOXD9 in MOC cells augmented the neoplastic phenotype. These findings provide the first evidence for MOC susceptibility variants and insights into the underlying biology of the disease.

Published
2015

11. Cis-eQTL analysis and functional validation of candidate susceptibility genes for high-grade serous ovarian cancer

Author

Lawrenson, K, Li, Q, Kar, S, Seo, J-H, Tyrer, J, Spindler, TJ, Lee, J, Chen, Y, Karst, A, Drapkin, R, Aben, KKH, Anton-Culver, H, Antonenkova, N, Baker, H, Bandera, EV, Bean, Y, Beckmann, MW, Berchuck, A, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bruinsma, F, Butzow, R, Campbell, IG, Carty, K, Chang-Claude, J, Chenevix-Trench, G, Chen, A, Chen, Z, Cook, LS, Cramer, DW, Cunningham, JM, Cybulski, C, Dansonka-Mieszkowska, A, Dennis, J, Dicks, E, Doherty, JA, Doerk, T, Du Bois, A, Duerst, M, Eccles, D, Easton, DT, Edwards, RP, Eilber, U, Ekici, AB, Fasching, PA, Fridley, BL, Gao, Y-T, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Goode, EL, Goodman, MT, Grownwald, J, Harrington, P, Harter, P, Hasmad, HN, Hein, A, Heitz, F, Hildebrandt, MAT, Hillemanns, P, Hogdall, E, Hogdall, C, Hosono, S, Iversen, ES, Jakubowska, A, James, P, Jensen, A, Ji, B-T, Karlan, BY, Kjaer, SK, Kelemen, LE, Kellar, M, Kelley, JL, Kiemeney, LA, Krakstad, C, Kupryjanczyk, J, Lambrechts, D, Lambrechts, S, Le, ND, Lee, AW, Lele, S, Leminen, A, Lester, J, Levine, DA, Liang, D, Lissowska, J, Lu, K, Lubinski, J, Lundvall, L, Massuger, LFAG, Matsuo, K, McGuire, V, McLaughlin, JR, Nevanlinna, H, McNeish, I, Menon, U, Modugno, F, Moysich, KB, Narod, SA, Nedergaard, L, Ness, RB, Azmi, MAN, Odunsi, K, Olson, SH, Orlow, I, Orsulic, S, Weber, RP, Pearce, CL, Pejovic, T, Pelttari, LM, Permuth-Wey, J, Phelan, CM, Pike, MC, Poole, EM, Ramus, SJ, Risch, HA, Rosen, B, Rossing, MA, Rothstein, JH, Rudolph, A, Runnebaum, IB, Rzepecka, IK, Salvesen, HB, Schildkraut, JM, Schwaab, I, Sellers, TA, Shu, X-O, Shvetsov, YB, Siddiqui, N, Sieh, W, Song, H, Southey, MC, Sucheston, L, Tangen, IL, Teo, S-H, Terry, KL, Thompson, PJ, Timorek, A, Tsai, Y-Y, Tworoger, SS, Van Altena, AM, Van Nieuwenhuysen, E, Vergote, I, Vierkant, RA, Wang-Gohrke, S, Walsh, C, Wentzensen, N, Whittemore, AS, Wicklund, KG, Wilkens, LR, Woo, Y-L, Wu, X, Wu, AH, Yang, H, Zheng, W, Ziogas, A, Monteiro, A, Pharoah, PD, Gayther, SA, Freedman, ML, Grp, AOCS, Bowtell, D, Webb, PM, Defazio, A, Lawrenson, K, Li, Q, Kar, S, Seo, J-H, Tyrer, J, Spindler, TJ, Lee, J, Chen, Y, Karst, A, Drapkin, R, Aben, KKH, Anton-Culver, H, Antonenkova, N, Baker, H, Bandera, EV, Bean, Y, Beckmann, MW, Berchuck, A, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bruinsma, F, Butzow, R, Campbell, IG, Carty, K, Chang-Claude, J, Chenevix-Trench, G, Chen, A, Chen, Z, Cook, LS, Cramer, DW, Cunningham, JM, Cybulski, C, Dansonka-Mieszkowska, A, Dennis, J, Dicks, E, Doherty, JA, Doerk, T, Du Bois, A, Duerst, M, Eccles, D, Easton, DT, Edwards, RP, Eilber, U, Ekici, AB, Fasching, PA, Fridley, BL, Gao, Y-T, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Goode, EL, Goodman, MT, Grownwald, J, Harrington, P, Harter, P, Hasmad, HN, Hein, A, Heitz, F, Hildebrandt, MAT, Hillemanns, P, Hogdall, E, Hogdall, C, Hosono, S, Iversen, ES, Jakubowska, A, James, P, Jensen, A, Ji, B-T, Karlan, BY, Kjaer, SK, Kelemen, LE, Kellar, M, Kelley, JL, Kiemeney, LA, Krakstad, C, Kupryjanczyk, J, Lambrechts, D, Lambrechts, S, Le, ND, Lee, AW, Lele, S, Leminen, A, Lester, J, Levine, DA, Liang, D, Lissowska, J, Lu, K, Lubinski, J, Lundvall, L, Massuger, LFAG, Matsuo, K, McGuire, V, McLaughlin, JR, Nevanlinna, H, McNeish, I, Menon, U, Modugno, F, Moysich, KB, Narod, SA, Nedergaard, L, Ness, RB, Azmi, MAN, Odunsi, K, Olson, SH, Orlow, I, Orsulic, S, Weber, RP, Pearce, CL, Pejovic, T, Pelttari, LM, Permuth-Wey, J, Phelan, CM, Pike, MC, Poole, EM, Ramus, SJ, Risch, HA, Rosen, B, Rossing, MA, Rothstein, JH, Rudolph, A, Runnebaum, IB, Rzepecka, IK, Salvesen, HB, Schildkraut, JM, Schwaab, I, Sellers, TA, Shu, X-O, Shvetsov, YB, Siddiqui, N, Sieh, W, Song, H, Southey, MC, Sucheston, L, Tangen, IL, Teo, S-H, Terry, KL, Thompson, PJ, Timorek, A, Tsai, Y-Y, Tworoger, SS, Van Altena, AM, Van Nieuwenhuysen, E, Vergote, I, Vierkant, RA, Wang-Gohrke, S, Walsh, C, Wentzensen, N, Whittemore, AS, Wicklund, KG, Wilkens, LR, Woo, Y-L, Wu, X, Wu, AH, Yang, H, Zheng, W, Ziogas, A, Monteiro, A, Pharoah, PD, Gayther, SA, Freedman, ML, Grp, AOCS, Bowtell, D, Webb, PM, and Defazio, A

Abstract

Genome-wide association studies have reported 11 regions conferring risk of high-grade serous epithelial ovarian cancer (HGSOC). Expression quantitative trait locus (eQTL) analyses can identify candidate susceptibility genes at risk loci. Here we evaluate cis-eQTL associations at 47 regions associated with HGSOC risk (P≤10(-5)). For three cis-eQTL associations (P<1.4 × 10(-3), FDR<0.05) at 1p36 (CDC42), 1p34 (CDCA8) and 2q31 (HOXD9), we evaluate the functional role of each candidate by perturbing expression of each gene in HGSOC precursor cells. Overexpression of HOXD9 increases anchorage-independent growth, shortens population-doubling time and reduces contact inhibition. Chromosome conformation capture identifies an interaction between rs2857532 and the HOXD9 promoter, suggesting this SNP is a leading causal variant. Transcriptomic profiling after HOXD9 overexpression reveals enrichment of HGSOC risk variants within HOXD9 target genes (P=6 × 10(-10) for risk variants (P<10(-4)) within 10 kb of a HOXD9 target gene in ovarian cells), suggesting a broader role for this network in genetic susceptibility to HGSOC.

Published
2015

12. A meta-analysis of 87,040 individuals identifies 23 new susceptibility loci for prostate cancer

Author

Al Olama, AA, Kote-Jarai, Z, Berndt, SI, Conti, DV, Schumacher, F, Han, Y, Benlloch, S, Hazelett, DJ, Wang, Z, Saunders, E, Leongamornlert, D, Lindstrom, S, Jugurnauth-Little, S, Dadaev, T, Tymrakiewicz, M, Stram, DO, Rand, K, Wan, P, Stram, A, Sheng, X, Pooler, LC, Park, K, Xia, L, Tyrer, J, Kolonel, LN, Le Marchand, L, Hoover, RN, Machiela, MJ, Yeager, M, Burdette, L, Chung, CC, Hutchinson, A, Yu, K, Goh, C, Ahmed, M, Govindasami, K, Guy, M, Tammela, TLJ, Auvinen, A, Wahlfors, T, Schleutker, J, Visakorpi, T, Leinonen, KA, Xu, J, Aly, M, Donovan, J, Travis, RC, Key, TJ, Siddiq, A, Canzian, F, Khaw, K-T, Takahashi, A, Kubo, M, Pharoah, P, Pashayan, N, Weischer, M, Nordestgaard, BG, Nielsen, SF, Klarskov, P, Roder, MA, Iversen, P, Thibodeau, SN, McDonnell, SK, Schaid, DJ, Stanford, JL, Kolb, S, Holt, S, Knudsen, B, Coll, AH, Gapstur, SM, Diver, WR, Stevens, VL, Maier, C, Luedeke, M, Herkommer, K, Rinckleb, AE, Strom, SS, Pettaway, C, Yeboah, ED, Tettey, Y, Biritwum, RB, Adjei, AA, Tay, E, Truelove, A, Niwa, S, Choklcalingam, AP, Cannon-Albright, L, Cybulski, C, Wokolorczyk, D, Kluzniak, W, Park, J, Sellers, T, Lin, H-Y, Isaacs, WB, Partin, AW, Brenner, H, Dieffenbach, AK, Stegmaier, C, Chen, C, Giovannucci, EL, Ma, J, Stampfer, M, Penney, KL, Mucci, L, John, EM, Ingles, SA, Kittles, RA, Murphy, AB, Pandha, H, Michael, A, Kierzek, AM, Blot, W, Signorello, LB, Zheng, W, Albanes, D, Virtamo, J, Weinstein, S, Nemesure, B, Carpten, J, Leske, C, Wu, S-Y, Hennis, A, Kibel, AS, Rybicki, BA, Neslund-Dudas, C, Hsing, AW, Chu, L, Goodman, PJ, Klein, EA, Zheng, SL, Batra, J, Clements, J, Spurdle, A, Teixeira, MR, Paulo, P, Maia, S, Slavov, C, Kaneva, R, Mitev, V, Witte, JS, Casey, G, Gillanders, EM, Seminara, D, Riboli, E, Hamdy, FC, Coetzee, GA, Li, Q, Freedman, ML, Hunter, DJ, Muir, K, Gronberg, H, Nea, DE, Southey, M, Giles, GG, Severi, G, Cook, MB, Nakagawa, H, Wiklund, F, Kraft, P, Chanock, SJ, Henderson, BE, Easton, DF, Eeles, RA, Haiman, CA, Al Olama, AA, Kote-Jarai, Z, Berndt, SI, Conti, DV, Schumacher, F, Han, Y, Benlloch, S, Hazelett, DJ, Wang, Z, Saunders, E, Leongamornlert, D, Lindstrom, S, Jugurnauth-Little, S, Dadaev, T, Tymrakiewicz, M, Stram, DO, Rand, K, Wan, P, Stram, A, Sheng, X, Pooler, LC, Park, K, Xia, L, Tyrer, J, Kolonel, LN, Le Marchand, L, Hoover, RN, Machiela, MJ, Yeager, M, Burdette, L, Chung, CC, Hutchinson, A, Yu, K, Goh, C, Ahmed, M, Govindasami, K, Guy, M, Tammela, TLJ, Auvinen, A, Wahlfors, T, Schleutker, J, Visakorpi, T, Leinonen, KA, Xu, J, Aly, M, Donovan, J, Travis, RC, Key, TJ, Siddiq, A, Canzian, F, Khaw, K-T, Takahashi, A, Kubo, M, Pharoah, P, Pashayan, N, Weischer, M, Nordestgaard, BG, Nielsen, SF, Klarskov, P, Roder, MA, Iversen, P, Thibodeau, SN, McDonnell, SK, Schaid, DJ, Stanford, JL, Kolb, S, Holt, S, Knudsen, B, Coll, AH, Gapstur, SM, Diver, WR, Stevens, VL, Maier, C, Luedeke, M, Herkommer, K, Rinckleb, AE, Strom, SS, Pettaway, C, Yeboah, ED, Tettey, Y, Biritwum, RB, Adjei, AA, Tay, E, Truelove, A, Niwa, S, Choklcalingam, AP, Cannon-Albright, L, Cybulski, C, Wokolorczyk, D, Kluzniak, W, Park, J, Sellers, T, Lin, H-Y, Isaacs, WB, Partin, AW, Brenner, H, Dieffenbach, AK, Stegmaier, C, Chen, C, Giovannucci, EL, Ma, J, Stampfer, M, Penney, KL, Mucci, L, John, EM, Ingles, SA, Kittles, RA, Murphy, AB, Pandha, H, Michael, A, Kierzek, AM, Blot, W, Signorello, LB, Zheng, W, Albanes, D, Virtamo, J, Weinstein, S, Nemesure, B, Carpten, J, Leske, C, Wu, S-Y, Hennis, A, Kibel, AS, Rybicki, BA, Neslund-Dudas, C, Hsing, AW, Chu, L, Goodman, PJ, Klein, EA, Zheng, SL, Batra, J, Clements, J, Spurdle, A, Teixeira, MR, Paulo, P, Maia, S, Slavov, C, Kaneva, R, Mitev, V, Witte, JS, Casey, G, Gillanders, EM, Seminara, D, Riboli, E, Hamdy, FC, Coetzee, GA, Li, Q, Freedman, ML, Hunter, DJ, Muir, K, Gronberg, H, Nea, DE, Southey, M, Giles, GG, Severi, G, Cook, MB, Nakagawa, H, Wiklund, F, Kraft, P, Chanock, SJ, Henderson, BE, Easton, DF, Eeles, RA, and Haiman, CA

Abstract

Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of > 10 million SNPs in 43,303 prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three new susceptibility loci were identified at association P < 5 × 10(-8); 15 variants were identified among men of European ancestry, 7 were identified in multi-ancestry analyses and 1 was associated with early-onset prostate cancer. These 23 variants, in combination with known prostate cancer risk variants, explain 33% of the familial risk for this disease in European-ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the usefulness of combining ancestrally diverse populations to discover risk loci for disease.

Published
2014

13. Haplotype analysis of the HSD17B1 gene and risk of breast cancer: A comprehensive approach to multicenter analyses of prospective cohort studies

Author

Feigelson, HS Cox, DG Cann, HM Wacholder, S Kaaks, R and Henderson, BE Albanes, D Altshuler, D Berglund, G and Berrino, F Bingham, S Buring, JE Burtt, NP Calle, EE and Chanock, SJ Clavel-Chapelon, F Colditz, G Diver, WR and Freedman, ML Haiman, CA Hankinson, SE Hayes, RB and Hirschhorn, JN Hunter, D Kolonel, LN Kraft, P and LeMarchand, L Linseisen, J Modi, W Navarro, C Peeters, PH Pike, MC Riboli, E Setiawan, VW Stram, DO Thomas, G Thun, MJ Tjonneland, A Trichopoulos, D

Abstract

The 17 beta-hydroxysteroid dehydrogenase 1 gene (HSD17B1) encodes 17HSD1, which catalyzes the final step of estradiol biosynthesis. Despite the important role of HSD17B1 in hormone metabolism, few epidemiologic studies of HSD17B1 and breast cancer have been conducted. This study includes 5,370 breast cancer cases and 7,480 matched controls from five large cohorts in the Breast and Prostate Cancer Cohort Consortium. We characterized variation in HSD17B1 by resequencing and dense genotyping a multiethnic sample and identified haplotype-tagging single nucleotide polymorphisms (htSNP) that capture common variation within a 33.3-kb region around HSD17B1. Four htSNPs, including the previously studied SNP rs605059 (S312G), were genotyped to tag five common haplotypes in all cases and controls. Conditional logistic regression was used to estimate odds ratios (OR) for disease. We found no evidence of association between common HSD17B1 haplotypes or htSNPs and overall risk of breast cancer. The OR for each haplotype relative to the most common haplotype ranged from 0.98 to 1.07 (omnibus test for association: X-2 = 3.77, P = 0.58, 5 degrees of freedom). When cases were subdivided by estrogen receptor (ER) status, two common haplotypes were associated with ER-negative tumors (test for trend, Ps = 0.0009 and 0.0076; n = 353 cases). HSD17B1 variants that are common in Caucasians are not associated with overall risk of breast cancer; however, there was an association among the subset of ER-negative tumors. Although the probability that these ER-negative findings are false-positive results is high, these findings were consistent across each cohort examined and warrant further study.

Published
2006

14. Genetic variation in the HSD17B1 gene and risk of prostate cancer

Author

Kraft, P Pharoah, P Chanock, SJ Albanes, D Kolonel, LN and Hayes, RB Altshuler, D Andriole, G Berg, C Boeing, H and Burtt, NP Bueno-de-Mesquita, B Calle, EE Cann, H and Canzian, F Chen, YC Crawford, DE Dunning, AM Feigelson, HS Freedman, ML Gaziano, JM Giovannucci, E Gonzalez, CA and Haiman, CA Hallmans, G Henderson, BE Hirschhorn, JN and Hunter, DJ Kaaks, R Key, T Le Marchand, L Ma, J and Overvad, K Palli, D Pike, MC Riboli, E Rodriguez, C and Setiawan, WV Stampfer, MJ Stram, DO Thomas, G Thun, MJ and Travis, R Trichopoulou, A Virtamo, J Wacholder, S

Abstract

Steroid hormones are believed to play an important role in prostate carcinogenesis, but epidemiological evidence linking prostate cancer and steroid hormone genes has been inconclusive, in part due to small sample sizes or incomplete characterization of genetic variation at the locus of interest. Here we report on the results of a comprehensive study of the association between HSD17B1 and prostate cancer by the Breast and Prostate Cancer Cohort Consortium, a large collaborative study. HSD17B1 encodes 17p-hydroxysteroid clehydrogenase 1, an enzyme that converts clihydroepiandrosterone to the testosterone precursor Delta 5-androsterone-3 beta, 17 beta-diol and converts estrone to estradiol. The Breast and Prostate Cancer Cohort Consortium researchers systematically characterized variation in HSD17B1 by targeted resequencing and dense genotyping; selected haplotype-tagging single nucleotide polymorphisms (htSNPs) that efficiently predict common variants in U.S. and European whites, Latinos, Japanese Americans, and Native Hawaiians; and genotyped these htSNPs in 8,290 prostate cancer cases and 9,367 study-, age-, and ethnicity-matched controls. We found no evidence that HSD17B1 htSNPs (including the nonsynonymous coding SNP S312G) or htSNP haplotypes were associated with risk of prostate cancer or tumor stage in the pooled multiethnic sample or in U.S. and European whites. Analyses stratified by age, body mass index, and family history of disease found no subgroup-specific associations between these HSD17B1 htSNPs and prostate cancer. We found significant evidence of heterogeneity in associations between HSD17B1 haplotypes and prostate cancer across ethnicity: one haplotype had a significant (p < 0.002) inverse association with risk of prostate cancer in Latinos and Japanese Americans but showed no evidence of association in African Americans, Native Hawaiians, or whites. However, the smaller numbers of Latinos and Japanese Americans in this study makes these subgroup analyses less reliable. These results suggest that the germline variants in HSD17B1 characterized by these htSNPs do not substantially influence the risk of prostate cancer in U.S. and European whites.

Published
2005

15. Admixture mapping of 15,280 African Americans identifies obesity susceptibility loci on chromosomes 5 and X

Author

Cheng, CY, Kao, WHL, Patterson, N, Tandon, A, Haiman, CA, Harris, TB, Xing, C, John, EM, Ambrosone, CB, Brancati, FL, Coresh, J, Press, MF, Parekh, RS, Klag, MJ, Meoni, LA, Hsueh, WC, Fejerman, L, Pawlikowska, L, Freedman, ML, Jandorf, LH, Bandera, EV, Ciupak, GL, Nalls, MA, Akylbekova, EL, Orwoll, ES, Leak, TS, Miljkovic, I, Li, R, Ursin, G, Bernstein, L, Ardlie, K, Taylor, HA, Boerwinckle, E, Zmuda, JM, Henderson, BE, Wilson, JG, Reich, D, Cheng, CY, Kao, WHL, Patterson, N, Tandon, A, Haiman, CA, Harris, TB, Xing, C, John, EM, Ambrosone, CB, Brancati, FL, Coresh, J, Press, MF, Parekh, RS, Klag, MJ, Meoni, LA, Hsueh, WC, Fejerman, L, Pawlikowska, L, Freedman, ML, Jandorf, LH, Bandera, EV, Ciupak, GL, Nalls, MA, Akylbekova, EL, Orwoll, ES, Leak, TS, Miljkovic, I, Li, R, Ursin, G, Bernstein, L, Ardlie, K, Taylor, HA, Boerwinckle, E, Zmuda, JM, Henderson, BE, Wilson, JG, and Reich, D

Abstract

The prevalence of obesity (body mass index (BMI) $30 kg/m2) is higher in African Americans than in European Americans, even after adjustment for socioeconomic factors, suggesting that genetic factors may explain some of the difference. To identify genetic loci influencing BMI, we carried out a pooled analysis of genome-wide admixture mapping scans in 15,280 African Americans from 14 epidemiologic studies. Samples were genotyped at a median of 1,411 ancestry-informative markers. After adjusting for age, sex, and study, BMI was analyzed both as a dichotomized (top 20% versus bottom 20%) and a continuous trait. We found that a higher percentage of European ancestry was significantly correlated with lower BMI (ρ = -0.042, P = 1.6×10 -7). In the dichotomized analysis, we detected two loci on chromosome X as associated with increased African ancestry: the first at Xq25 (locus-specific LOD = 5.94; genome-wide score = 3.22; case-control Z =23.94); and the second at Xq13.1 (locus-specific LOD = 2.22; case-control Z =24.62). Quantitative analysis identified a third locus at 5q13.3 where higher BMI was highly significantly associated with greater European ancestry (locus-specific LOD = 6.27; genome-wide score = 3.46). Further mapping studies with dense sets of markers will be necessary to identify the alleles in these regions of chromosomes X and 5 that may be associated with variation in BMI.

Published
2009

18. Geriatric assessment: focus on function.

Author

Beck JC, Freedman ML, and Warshaw GA

Abstract

Functional assessment promotes continued independence and quality of life, even for the very old. These tips will help you evaluate older patients despite the obstacles of limited time and meager reimbursement. [ABSTRACT FROM AUTHOR]

Published
1994

20. IMMUNIZATION AGAINST MEASLES

Author

Freedman Ml

Subjects
Adolescent, business.industry, Immune Sera, Measles Vaccine, Age Factors, Australia, Infant, General Medicine, medicine.disease, Measles, Virology, United Kingdom, United States, Immunity, Active, Immunization, Measles virus, Child, Preschool, medicine, Humans, Child, business, Immunity, Maternally-Acquired, Immunization Schedule
Published
1968

21. Treatment of crises in sickle cell anemia

Author

Freedman Ml

Subjects
Pediatrics, medicine.medical_specialty, business.industry, medicine, General Medicine, medicine.disease, business, Sickle cell anemia
Published
1971

22. Elevated platelet count and megathrombocyte number in sickle cell anemia

Author

Freedman, ML and Karpatkin, S

Abstract

Eight adult patients with sickle cell anemia were followed over a 6-mo period. During this time all patients had elevated plateletcounts, 1.7- fold (mean, 438,398 +/- 86,223), and megathrombocyte numbers, 2.3-fold (mean, 79,535 +/- 38,907), during asymptomatic periods. These data are interpreted as suggesting that the elevated platelets and megathrombocytes in asymptomatic sickle cell patients result from lack of splenic sequestration. During three crises in two patients, both megathrombocyte number and platelet count fell significantly. It is speculated that platelets may be associated with the pathology in this disease. Platelet function studies performed during crises, therefore, must take into account the number of megathrombocytes.

Published
1975
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23. Hemin reversal of benzene-induced inhibition of reticulocyte protein synthesis

Author

Forte, FJ, Cohen, HS, Rosman, J, and Freedman, ML

Abstract

Benzene (0.056–0.113 M) rapidly and reversibly inhibited protein synthesis in anucleate human sickle cell and rabbit reticulocytes. Hemin (50 muM) both prevented and reversed this effect of benzene. The inhibition in rabbit reticulocytes was accompanied by a conversion of polyribosomal disaggregation required ribosomal movement along mRNA and was also prevented and reversed by 50 muM hemin. Benzene was also shown to inhibit heme synthesis in rabbit reticulocytes while neither ATP nor GSH levels were altered. A translational repressor (HCR) of reticulocyte cell-free protein synthesis was isolated from intact cells incubated with benzene, while no significant amount of HCR was found in cells incubated with both benzene and hemin. These results indicated that benzene inhibits translation at the heme-dependent site of initiation. The clinical implications of these experiments remain to be elucidated.

Published
1976
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24. A smallpox vaccination survey in New South Wales

Author

Freedman Ml

Subjects
medicine.medical_specialty, Geography, Family medicine, Smallpox vaccination, Vaccination, medicine, Australia, Humans, General Medicine, Virology, Health Surveys, Smallpox
Published
1968

25. DEFINING AN mRNA EXPRESSION SIGNATURE OF GLEASON GRADE

Author

Penney, Kl, Sinnott, Ja, Falla, K., Pawitan, Y., Hoshida, Y., Kraft, P., Fiorentino, M., Perner, S., Finn, S., Stefano Calza, Flavin, R., Freedman, Ml, Setlur, S., Andersson, So, Martin, N., Kantoff, Pw, Johansson, Je, Adami, Ho, Rubin, M., Loda, M., Golub, Tr, Andre, O., Stampfer, Mj, and Mucci, La

26. Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus

Author

Lawrenson, K, Kar, S, McCue, K, Kuchenbaeker, K, Michailidou, K, Tyrer, J, Beesley, J, Ramus, SJ, Li, Q, Delgado, MK, Lee, JM, Aittomäki, K, Andrulis, IL, Anton-Culver, H, Arndt, V, Arun, BK, Arver, B, Bandera, EV, Barile, M, Barkardottir, RB, Barrowdale, D, Beckmann, MW, Benitez, J, Berchuck, A, Bisogna, M, Bjorge, L, Blomqvist, C, Blot, W, Bogdanova, N, Bojesen, A, Bojesen, SE, Bolla, MK, Bonanni, B, Børresen-Dale, A-L, Brauch, H, Brennan, P, Brenner, H, Bruinsma, F, Brunet, J, Buhari, SA, Burwinkel, B, Butzow, R, Buys, SS, Cai, Q, Caldes, T, Campbell, I, Canniotto, R, Chang-Claude, J, Chiquette, J, Choi, J-Y, Claes, KBM, GEMO Study Collaborators, Cook, LS, Cox, A, Cramer, DW, Cross, SS, Cybulski, C, Czene, K, Daly, MB, Damiola, F, Dansonka-Mieszkowska, A, Darabi, H, Dennis, J, Devilee, P, Diez, O, Doherty, JA, Domchek, SM, Dorfling, CM, Dörk, T, Dumont, M, Ehrencrona, H, Ejlertsen, B, Ellis, S, EMBRACE, Engel, C, Lee, E, Evans, DG, Fasching, PA, Feliubadalo, L, Figueroa, J, Flesch-Janys, D, Fletcher, O, Flyger, H, Foretova, L, Fostira, F, Foulkes, WD, Fridley, BL, Friedman, E, Frost, D, Gambino, G, Ganz, PA, Garber, J, García-Closas, M, Gentry-Maharaj, A, Ghoussaini, M, Giles, GG, Glasspool, R, Godwin, AK, Goldberg, MS, Goldgar, DE, González-Neira, A, Goode, EL, Goodman, MT, Greene, MH, Gronwald, J, Guénel, P, Haiman, CA, Hall, P, Hallberg, E, Hamann, U, Hansen, TVO, Harrington, PA, Hartman, M, Hassan, N, Healey, S, Hereditary Breast And Ovarian Cancer Research Group Netherlands (HEBON), Heitz, F, Herzog, J, Høgdall, E, Høgdall, CK, Hogervorst, FBL, Hollestelle, A, Hopper, JL, Hulick, PJ, Huzarski, T, Imyanitov, EN, KConFab Investigators, Australian Ovarian Cancer Study Group, Isaacs, C, Ito, H, Jakubowska, A, Janavicius, R, Jensen, A, John, EM, Johnson, N, Kabisch, M, Kang, D, Kapuscinski, M, Karlan, BY, Khan, S, Kiemeney, LA, Kjaer, SK, Knight, JA, Konstantopoulou, I, Kosma, V-M, Kristensen, V, Kupryjanczyk, J, Kwong, A, De La Hoya, M, Laitman, Y, Lambrechts, D, Le, N, De Leeneer, K, Lester, J, Levine, DA, Li, J, Lindblom, A, Long, J, Lophatananon, A, Loud, JT, Lu, K, Lubinski, J, Mannermaa, A, Manoukian, S, Le Marchand, L, Margolin, S, Marme, F, Massuger, LFAG, Matsuo, K, Mazoyer, S, McGuffog, L, McLean, C, McNeish, I, Meindl, A, Menon, U, Mensenkamp, AR, Milne, RL, Montagna, M, Moysich, KB, Muir, K, Mulligan, AM, Nathanson, KL, Ness, RB, Neuhausen, SL, Nevanlinna, H, Nord, S, Nussbaum, RL, Odunsi, K, Offit, K, Olah, E, Olopade, OI, Olson, JE, Olswold, C, O'Malley, D, Orlow, I, Orr, N, Osorio, A, Park, SK, Pearce, CL, Pejovic, T, Peterlongo, P, Pfeiler, G, Phelan, CM, Poole, EM, Pylkäs, K, Radice, P, Rantala, J, Rashid, MU, Rennert, G, Rhenius, V, Rhiem, K, Risch, HA, Rodriguez, G, Rossing, MA, Rudolph, A, Salvesen, HB, Sangrajrang, S, Sawyer, EJ, Schildkraut, JM, Schmidt, MK, Schmutzler, RK, Sellers, TA, Seynaeve, C, Shah, M, Shen, C-Y, Shu, X-O, Sieh, W, Singer, CF, Sinilnikova, OM, Slager, S, Song, H, Soucy, P, Southey, MC, Stenmark-Askmalm, M, Stoppa-Lyonnet, D, Sutter, C, Swerdlow, A, Tchatchou, S, Teixeira, MR, Teo, SH, Terry, KL, Terry, MB, Thomassen, M, Tibiletti, MG, Tihomirova, L, Tognazzo, S, Toland, AE, Tomlinson, I, Torres, D, Truong, T, Tseng, C-C, Tung, N, Tworoger, SS, Vachon, C, Van Den Ouweland, AMW, Van Doorn, HC, Van Rensburg, EJ, Van't Veer, LJ, Vanderstichele, A, Vergote, I, Vijai, J, Wang, Q, Wang-Gohrke, S, Weitzel, JN, Wentzensen, N, Whittemore, AS, Wildiers, H, Winqvist, R, Wu, AH, Yannoukakos, D, Yoon, S-Y, Yu, J-C, Zheng, W, Zheng, Y, Khanna, KK, Simard, J, Monteiro, AN, French, JD, Couch, FJ, Freedman, ML, Easton, DF, Dunning, AM, Pharoah, PD, Edwards, SL, Chenevix-Trench, G, Antoniou, AC, and Gayther, SA

Subjects
Ovarian Neoplasms, Genotype, Black People, Breast Neoplasms, Polymorphism, Single Nucleotide, 3. Good health, Asian People, Humans, Female, Genetic Predisposition to Disease, RNA, Messenger, Chromosomes, Human, Pair 19, Alleles, Genome-Wide Association Study
Abstract

A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10(-20)), ER-negative BC (P=1.1 × 10(-13)), BRCA1-associated BC (P=7.7 × 10(-16)) and triple negative BC (P-diff=2 × 10(-5)). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10(-3)) and ABHD8 (P

27. Fatty Acid Synthase Polymorphisms, Tumor Expression, Body Mass Index, Prostate Cancer Risk, and Survival

Author

Stephen P. Finn, Meir J. Stampfer, Giuseppe Fedele, Fredrick R. Schumacher, Christopher Fiore, Anna Eisenstein, Weiliang Qiu, Edward Giovannucci, Jing Ma, Kathryn L. Penney, Michelangelo Fiorentino, Paul L. Nguyen, Lorelei A. Mucci, Rosina T. Lis, Matthew L. Freedman, Massimo Loda, Jorge E. Chavarro, Nguyen PL, Ma J, Chavarro JE, Freedman ML, Lis R, Fedele G, Fiore C, Qiu W, Fiorentino M, Finn S, Penney KL, Eisenstein A, Schumacher FR, Mucci LA, Stampfer MJ, Giovannucci E, and Loda M

Subjects
Adult, Male, Cancer Research, medicine.medical_specialty, Single-nucleotide polymorphism, Overweight, urologic and male genital diseases, Polymorphism, Single Nucleotide, Body Mass Index, Prostate cancer, Risk Factors, Internal medicine, Original Reports, medicine, Humans, SNP, Genetic Predisposition to Disease, Aged, biology, business.industry, Prostatic Neoplasms, Cancer, Middle Aged, medicine.disease, Fatty acid synthase, Endocrinology, Oncology, Relative risk, biology.protein, fatty acid synthase body mass index prostate cancer, Fatty Acid Synthases, medicine.symptom, business, Body mass index
Abstract

Purpose Fatty acid synthase (FASN) regulates de novo lipogenesis, body weight, and tumor growth. We examined whether common germline single nucleotide polymorphisms (SNPs) in the FASN gene affect prostate cancer (PCa) risk or PCa-specific mortality and whether these effects vary by body mass index (BMI). Methods In a prospective nested case-control study of 1,331 white patients with PCa and 1,267 age-matched controls, we examined associations of five common SNPs within FASN (and 5 kb upstream/downstream, R2 > 0.8) with PCa incidence and, among patients, PCa-specific death and tested for an interaction with BMI. Survival analyses were repeated for tumor FASN expression (n = 909). Results Four of the five SNPs were associated with lethal PCa. SNP rs1127678 was significantly related to higher BMI and interacted with BMI for both PCa risk (Pinteraction = .004) and PCa mortality (Pinteraction = .056). Among overweight men (BMI ≥ 25 kg/m2), but not leaner men, the homozygous variant allele carried a relative risk of advanced PCa of 2.49 (95% CI, 1.00 to 6.23) compared with lean men with the wild type. Overweight patients carrying the variant allele had a 2.04 (95% CI, 1.31 to 3.17) times higher risk of PCa mortality. Similarly, overweight patients with elevated tumor FASN expression had a 2.73 (95% CI, 1.05 to 7.08) times higher risk of lethal PCa (Pinteraction = .02). Conclusion FASN germline polymorphisms were significantly associated with risk of lethal PCa. Significant interactions of BMI with FASN polymorphisms and FASN tumor expression suggest FASN as a potential link between obesity and poor PCa outcome and raise the possibility that FASN inhibition could reduce PCa-specific mortality, particularly in overweight men.

Published
2010

28. mRNA Expression Signature of Gleason Grade Predicts Lethal Prostate Cancer

Author

Michelangelo Fiorentino, Massimo Loda, Katja Fall, Swen Olof Andersson, Stephen P. Finn, Lorelei A. Mucci, Richard Flavin, Mark A. Rubin, Neil E. Martin, Jan-Erik Johansson, Jennifer R. Stark, Todd R. Golub, Hans-Olov Adami, Meir J. Stampfer, Sunita R. Setlur, Kathryn L. Penney, Sven Perner, Peter Kraft, Ove Andrén, Howard D. Sesso, Jennifer A. Sinnott, Matthew L. Freedman, Stefano Calza, Yujin Hoshida, Yudi Pawitan, Philip W. Kantoff, Penney KL, Sinnott JA, Fall K, Pawitan Y, Hoshida Y, Kraft P, Stark JR, Fiorentino M, Perner S, Finn S, Calza S, Flavin R, Freedman ML, Setlur S, Sesso HD, Andersson SO, Martin N, Kantoff PW, Johansson JE, Adami HO, Rubin MA, Loda M, Golub TR, Andrén O, Stampfer MJ, and Mucci LA

Subjects
Male, Oncology, Cancer Research, Pathology, medicine.medical_specialty, medicine.medical_treatment, Disease, Gleason grade, urologic and male genital diseases, 03 medical and health sciences, Prostate cancer, 0302 clinical medicine, Prostate, Internal medicine, Original Reports, medicine, Humans, neoplasms, Aged, 030304 developmental biology, Aged, 80 and over, 0303 health sciences, prostate cancer, gene expression, lethality, business.industry, Gene Expression Profiling, Area under the curve, Prostatic Neoplasms, Cell Differentiation, Middle Aged, medicine.disease, 3. Good health, Gene expression profiling, medicine.anatomical_structure, surgical procedures, operative, 030220 oncology & carcinogenesis, Cohort, Disease Progression, business, Watchful waiting
Abstract

Purpose Prostate-specific antigen screening has led to enormous overtreatment of prostate cancer because of the inability to distinguish potentially lethal disease at diagnosis. We reasoned that by identifying an mRNA signature of Gleason grade, the best predictor of prognosis, we could improve prediction of lethal disease among men with moderate Gleason 7 tumors, the most common grade, and the most indeterminate in terms of prognosis. Patients and Methods Using the complementary DNA–mediated annealing, selection, extension, and ligation assay, we measured the mRNA expression of 6,100 genes in prostate tumor tissue in the Swedish Watchful Waiting cohort (n = 358) and Physicians' Health Study (PHS; n = 109). We developed an mRNA signature of Gleason grade comparing individuals with Gleason ≤ 6 to those with Gleason ≥ 8 tumors and applied the model among patients with Gleason 7 to discriminate lethal cases. Results We built a 157-gene signature using the Swedish data that predicted Gleason with low misclassification (area under the curve [AUC] = 0.91); when this signature was tested in the PHS, the discriminatory ability remained high (AUC = 0.94). In men with Gleason 7 tumors, who were excluded from the model building, the signature significantly improved the prediction of lethal disease beyond knowing whether the Gleason score was 4 + 3 or 3 + 4 (P = .006). Conclusion Our expression signature and the genes identified may improve our understanding of the de-differentiation process of prostate tumors. Additionally, the signature may have clinical applications among men with Gleason 7, by further estimating their risk of lethal prostate cancer and thereby guiding therapy decisions to improve outcomes and reduce overtreatment.

Published
2011

29. A Large Study of Androgen Receptor Germline Variants and Their Relation to Sex Hormone Levels and Prostate Cancer Risk. Results from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium

Author

Peter Kraft, Loic Le Marchand, H. Bas Bueno-de-Mesquita, Pär Stattin, Stephen J. Chanock, Daniel O. Stram, Stephanie J. Weinstein, Alison M. Dunning, Jarmo Virtamo, Heather Spencer Feigelson, Richard B. Hayes, Rosario Tumino, Matthew L. Freedman, Kim Overvad, David Altshuler, Demetrius Albanes, Jing Ma, Meredith Yeager, Heiner Boeing, Carmen Martinez, Meir J. Stampfer, Rudolf Kaaks, David J. Hunter, Brian E. Henderson, Elio Riboli, Michael J. Thun, Afshan Siddiq, Edward Giovannucci, Christopher A. Haiman, Laurence N. Kolonel, Naomi E. Allen, Sara Lindström, J. Michael Gaziano, Sonja I. Berndt, Dimitrios Trichopoulos, [Lindstroem,S, Hunter,DJ, Kraft,P] Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA. [Lindstroem,S, Stampfer,M, Trichopoulos,D, Kraft,P] Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA. [Giovannucci,E, Stampfer,M] Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, USA. [Kraft,P] Department of Biostatisctics, Harvard School of Public Health, Boston, Massachusetts, USA. [Ma,J, Stampfer,M] Department of Medicine, Channing Laboratory, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA. [Altshuler,D] Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts, Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, Department of Molecular Biology, Massachusetts General Hospital, Boston, Massachusetts, Department of Genetics, Harvard Medical School, Boston, Massachusetts, Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts. [Riboli,E, Siddiq,A] Department of Epidemiology and Public Health, Faculty of Medicine, Imperial College, London, United Kingdom. [Albanes,D, Berndt,SI, Chanock,SJ, Hayes,RB, Weinstein,SJ] Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland. [Allen,NE] Cancer Epidemiology Unit, University of Oxford, Oxford, United Kingdom. [Boeing,H] German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany. [Bueno-de-Mesquita,HB] National Institute for Public Health and the Environment, Bilthoven, The Netherlands. [Dunning,AM] Department of Oncology, University of Cambridge, Cambridge, United Kingdom. [Feigelson,HS, Thun,MJ] Department of Epidemiology, American Cancer Society, Atlanta, Georgia. [Feigelson, HS] Kaiser Permanente, Denver, Colorado. [Gaziano,JM] Massachusetts Veterans Epidemiology and Research Information Center and Geriatric Research, Education, Clinical Center, Boston Veterans Affairs Healthcare System, Boston, Massachusetts, Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts. [Haiman,CA, Henderson,BE, Stram, DO] Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California. [Hayes,RB] Division of Epidemiology, New York University Langone Medical Center, New York, New York. [Kaaks,R] Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany. [Kolonel,LN, Le Marchand,L]Cancer Research Center, University of Hawaii, Honolulu, Hawaii. [Martinez,C] Andalusian School of Public Health. Centro de Investigación Biomédica en Red Epidemiología y Salud Pública, Granada, Spain. [Overvad,K] Clinical Epidemiology and Cardiology, Aalborg Hospital, Aarhus University Hospital, Aalborg, Denmark. [Stattin,P] Surgical and Perioperative Sciences, Urology and Andrology, Umeå University, Umeå, Sweden. [Tumino,R] Cancer Registry Azienda Ospedaliera 'Civile M.P.Arezzo', Ragusa, Italy. [Virtamo,J] Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland. [Yeager,M] Core Genotyping Facility, Advanced Technology Program, SAIC Frederick, Inc., National Cancer Institute at Frederick, Frederick, Maryland. [Freedman,ML] Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts. The Broad Institute of Harvard and MIT, Cambridge, Massachusetts, and This work was supported by National Cancer Institute cooperative agreements UO1-CA98233, UO1-CA98710, UO1-CA98216, and UO1-CA98758, and by the Intramural Research Program of National Institutes of Health/National Cancer Institute, Division of Cancer Epidemiology and Genetics. S.L. is supported by the Swedish Research Council (Vetenskapsrådet).

Subjects
Male, Oncology, Neoplasias de la próstata, Endocrinology, Diabetes and Metabolism, Clinical Biochemistry, urologic and male genital diseases, Biochemistry, Germline, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Genetic Techniques::Genetic Association Studies [Medical Subject Headings], Cohort Studies, Androgen deprivation therapy, Prostate cancer, Endocrinology, Sex hormone-binding globulin, Trinucleotide Repeats, Receptores androgénicos, Gonadal Steroid Hormones, Prostate cancer risk, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Epidemiologic Study Characteristics as Topic::Epidemiologic Studies::Case-Control Studies [Medical Subject Headings], General Medicine, Middle Aged, Receptors, Androgen, Cohort, Original Article, Female, Health Care::Health Care Economics and Organizations::Organizations::Government::Federal Government::United States Government Agencies::United States Dept. of Health and Human Services::National Institutes of Health (U.S.)::National Cancer Institute (U.S.) [Medical Subject Headings], Risk, medicine.medical_specialty, Estudios de cohortes, Breast Neoplasms, Biology, Diseases::Neoplasms::Neoplasms by Site::Urogenital Neoplasms::Genital Neoplasms, Male::Prostatic Neoplasms [Medical Subject Headings], Germline mutation, Translational Highlights from Jcem, Health Care::Environment and Public Health::Public Health::Epidemiologic Methods::Epidemiologic Study Characteristics as Topic::Epidemiologic Studies::Cohort Studies [Medical Subject Headings], Internal medicine, Carcinoma, medicine, Humans, Genetic Predisposition to Disease, Molecular Biology, Diseases::Neoplasms::Neoplasms by Site::Breast Neoplasms [Medical Subject Headings], Genetic Association Studies, Germ-Line Mutation, Aged, Hormonas esteroides gonadales, Estudios de asociación genética, Biochemistry (medical), Case-control study, Prostatic Neoplasms, Cancer, medicine.disease, National Cancer Institute (U.S.), United States, Androgen receptor, Chemicals and Drugs::Hormones, Hormone Substitutes, and Hormone Antagonists::Hormones::Gonadal Hormones::Gonadal Steroid Hormones [Medical Subject Headings], Case-Control Studies, Chemicals and Drugs::Amino Acids, Peptides, and Proteins::Proteins::Receptors, Cytoplasmic and Nuclear::Receptors, Steroid::Receptors, Androgen [Medical Subject Headings], biology.protein
Abstract

Background: Androgens are key regulators of prostate gland maintenance and prostate cancer growth, and androgen deprivation therapy has been the mainstay of treatment for advanced prostate cancer for many years. A long-standing hypothesis has been that inherited variation in the androgen receptor (AR) gene plays a role in prostate cancer initiation. However, studies to date have been inconclusive and often suffered from small sample sizes. Objective and Methods: We investigated the association of AR sequence variants with circulating sex hormone levels and prostate cancer risk in 6058 prostate cancer cases and 6725 controls of Caucasian origin within the Breast and Prostate Cancer Cohort Consortium. We genotyped a highly polymorphic CAG microsatellite in exon 1 and six haplotype tagging single nucleotide polymorphisms and tested each genetic variant for association with prostate cancer risk and with sex steroid levels. Results: We observed no association between AR genetic variants and prostate cancer risk. However, there was a strong association between longer CAG repeats and higher levels of testosterone (P = 4.73 × 10−5) and estradiol (P = 0.0002), although the amount of variance explained was small (0.4 and 0.7%, respectively). Conclusions: This study is the largest to date investigating AR sequence variants, sex steroid levels, and prostate cancer risk. Although we observed no association between AR sequence variants and prostate cancer risk, our results support earlier findings of a relation between the number of CAG repeats and circulating levels of testosterone and estradiol.

Published
2010

30. Decoding the epigenetics and chromatin loop dynamics of androgen receptor-mediated transcription.

Author

Altıntaş UB, Seo JH, Giambartolomei C, Ozturan D, Fortunato BJ, Nelson GM, Goldman SR, Adelman K, Hach F, Freedman ML, and Lack NA

Subjects
Humans, Male, Cell Line, Tumor, Gene Expression Regulation, Neoplastic, Enhancer Elements, Genetic, Protein Binding, Receptors, Androgen metabolism, Receptors, Androgen genetics, Chromatin metabolism, Chromatin genetics, Epigenesis, Genetic, Promoter Regions, Genetic, Prostatic Neoplasms genetics, Prostatic Neoplasms metabolism, Transcription, Genetic
Abstract

Androgen receptor (AR)-mediated transcription plays a critical role in development and prostate cancer growth. AR drives gene expression by binding to thousands of cis-regulatory elements (CRE) that loop to hundreds of target promoters. With multiple CREs interacting with a single promoter, it remains unclear how individual AR bound CREs contribute to gene expression. To characterize the involvement of these CREs, we investigate the AR-driven epigenetic and chromosomal chromatin looping changes by generating a kinetic multi-omic dataset comprised of steady-state mRNA, chromatin accessibility, transcription factor binding, histone modifications, chromatin looping, and nascent RNA. Using an integrated regulatory network, we find that AR binding induces sequential changes in the epigenetic features at CREs, independent of gene expression. Further, we show that binding of AR does not result in a substantial rewiring of chromatin loops, but instead increases the contact frequency of pre-existing loops to target promoters. Our results show that gene expression strongly correlates to the changes in contact frequency. We then propose and experimentally validate an unbalanced multi-enhancer model where the impact on gene expression of AR-bound enhancers is heterogeneous, and is proportional to their contact frequency with target gene promoters. Overall, these findings provide insights into AR-mediated gene expression upon acute androgen simulation and develop a mechanistic framework to investigate nuclear receptor mediated perturbations., (© 2024. The Author(s).)

Published
2024
Full Text
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31. Frequent CHD1 deletions in prostate cancers of African American men is associated with rapid disease progression.

Author

Diossy M, Tisza V, Li H, Sahgal P, Zhou J, Sztupinszki Z, Young D, Nousome D, Kuo C, Jiang J, Chen Y, Ebner R, Sesterhenn IA, Moncur JT, Chesnut GT, Petrovics G, Klus GT, Valcz G, Nuzzo PV, Ribli D, Börcsök J, Prosz A, Krzystanek M, Ried T, Szuts D, Rizwan K, Kaochar S, Pathania S, D'Andrea AD, Csabai I, Srivastava S, Freedman ML, Dobi A, Spisak S, and Szallasi Z

Abstract

We analyzed genomic data from the prostate cancer of African- and European American men to identify differences contributing to racial disparity of outcome. We also performed FISH-based studies of Chromodomain helicase DNA-binding protein 1 (CHD1) loss on prostate cancer tissue microarrays. We created CHD1-deficient prostate cancer cell lines for genomic, drug sensitivity and functional homologous recombination (HR) activity analysis. Subclonal deletion of CHD1 was nearly three times as frequent in prostate tumors of African American than in European American men and it associates with rapid disease progression. CHD1 deletion was not associated with HR deficiency associated mutational signatures or HR deficiency as detected by RAD51 foci formation. This was consistent with the moderate increase of olaparib and talazoparib sensitivity with several CHD1 deficient cell lines showing talazoparib sensitivity in the clinically relevant concentration range. CHD1 loss may contribute to worse disease outcome in African American men., (© 2024. The Author(s).)

Published
2024
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32. Detecting Small Cell Transformation in Patients with Advanced EGFR Mutant Lung Adenocarcinoma through Epigenomic cfDNA Profiling.

Author

El Zarif T, Meador CB, Qiu X, Seo JH, Davidsohn MP, Savignano H, Lakshminarayanan G, McClure HM, Canniff J, Fortunato B, Li R, Banwait MK, Semaan K, Eid M, Long H, Hung YP, Mahadevan NR, Barbie DA, Oser MG, Piotrowska Z, Choueiri TK, Baca SC, Hata AN, Freedman ML, and Berchuck JE

Subjects
Humans, Mice, Animals, Biomarkers, Tumor genetics, Female, Small Cell Lung Carcinoma genetics, Small Cell Lung Carcinoma pathology, Small Cell Lung Carcinoma blood, Small Cell Lung Carcinoma diagnosis, DNA Methylation, Male, Cell Transformation, Neoplastic genetics, Epigenesis, Genetic, ErbB Receptors genetics, Adenocarcinoma of Lung genetics, Adenocarcinoma of Lung pathology, Adenocarcinoma of Lung blood, Adenocarcinoma of Lung diagnosis, Mutation, Lung Neoplasms genetics, Lung Neoplasms pathology, Lung Neoplasms blood, Lung Neoplasms diagnosis, Cell-Free Nucleic Acids genetics, Cell-Free Nucleic Acids blood, Epigenomics methods
Abstract

Purpose: Histologic transformation to small cell lung cancer (SCLC) is a mechanism of treatment resistance in patients with advanced oncogene-driven lung adenocarcinoma (LUAD) that currently requires histologic review for diagnosis. Herein, we sought to develop an epigenomic cell-free DNA (cfDNA)-based approach to noninvasively detect small cell transformation in patients with EGFR mutant (EGFRm) LUAD., Experimental Design: To characterize the epigenomic landscape of transformed (t)SCLC relative to LUAD and de novo SCLC, we performed chromatin immunoprecipitation sequencing (ChIP-seq) to profile the histone modifications H3K27ac, H3K4me3, and H3K27me3; methylated DNA immunoprecipitation sequencing (MeDIP-seq); assay for transposase-accessible chromatin sequencing; and RNA sequencing on 26 lung cancer patient-derived xenograft (PDX) tumors. We then generated and analyzed H3K27ac ChIP-seq, MeDIP-seq, and whole genome sequencing cfDNA data from 1 mL aliquots of plasma from patients with EGFRm LUAD with or without tSCLC., Results: Analysis of 126 epigenomic libraries from the lung cancer PDXs revealed widespread epigenomic reprogramming between LUAD and tSCLC, with a large number of differential H3K27ac (n = 24,424), DNA methylation (n = 3,298), and chromatin accessibility (n = 16,352) sites between the two histologies. Tumor-informed analysis of each of these three epigenomic features in cfDNA resulted in accurate noninvasive discrimination between patients with EGFRm LUAD versus tSCLC [area under the receiver operating characteristic curve (AUROC) = 0.82-0.87]. A multianalyte cfDNA-based classifier integrating these three epigenomic features discriminated between EGFRm LUAD versus tSCLC with an AUROC of 0.94., Conclusions: These data demonstrate the feasibility of detecting small cell transformation in patients with EGFRm LUAD through epigenomic cfDNA profiling of 1 mL of patient plasma., (©2024 The Authors; Published by the American Association for Cancer Research.)

Published
2024
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33. MYBL2 Drives Prostate Cancer Plasticity: Inhibiting Its Transcriptional Target CDK2 for RB1-Deficient Neuroendocrine Prostate Cancer.

Author

German B, Alaiwi SA, Ho KL, Nanda JS, Fonseca MA, Burkhart DL, Sheahan AV, Bergom HE, Morel KL, Beltran H, Hwang JH, Freedman ML, Lawrenson K, and Ellis L

Subjects
Animals, Humans, Male, Mice, Carcinoma, Neuroendocrine genetics, Carcinoma, Neuroendocrine pathology, Carcinoma, Neuroendocrine metabolism, Cell Cycle Proteins genetics, Cell Cycle Proteins metabolism, Cell Line, Tumor, Cell Plasticity, Cell Proliferation, Gene Expression Regulation, Neoplastic, Neuroendocrine Tumors genetics, Neuroendocrine Tumors pathology, Neuroendocrine Tumors metabolism, Proto-Oncogene Mas, Retinoblastoma Binding Proteins genetics, Retinoblastoma Binding Proteins metabolism, Trans-Activators genetics, Trans-Activators metabolism, Ubiquitin-Protein Ligases, Cyclin-Dependent Kinase 2 genetics, Cyclin-Dependent Kinase 2 metabolism, Prostatic Neoplasms genetics, Prostatic Neoplasms pathology, Prostatic Neoplasms metabolism
Abstract

Phenotypic plasticity is a recognized mechanism driving therapeutic resistance in patients with prostate cancer. Although underlying molecular causations driving phenotypic plasticity have been identified, therapeutic success is yet to be achieved. To identify putative master regulator transcription factors (MR-TF) driving phenotypic plasticity in prostate cancer, this work utilized a multiomic approach using genetically engineered mouse models of prostate cancer combined with patient data to identify MYB proto-oncogene like 2 (MYBL2) as a significantly enriched transcription factor in prostate cancer exhibiting phenotypic plasticity. Genetic inhibition of Mybl2 using independent murine prostate cancer cell lines representing phenotypic plasticity demonstrated Mybl2 loss significantly decreased in vivo growth as well as cell fitness and repressed gene expression signatures involved in pluripotency and stemness. Because MYBL2 is currently not druggable, a MYBL2 gene signature was employed to identify cyclin-dependent kinase-2 (CDK2) as a potential therapeutic target. CDK2 inhibition phenocopied genetic loss of Mybl2 and significantly decreased in vivo tumor growth associated with enrichment of DNA damage. Together, this work demonstrates MYBL2 as an important MR-TF driving phenotypic plasticity in prostate cancer. Furthermore, high MYBL2 activity identifies prostate cancer that would be responsive to CDK2 inhibition., Significance: Prostate cancers that escape therapy targeting the androgen receptor signaling pathways via phenotypic plasticity are currently untreatable. Our study identifies MYBL2 as a MR-TF in phenotypic plastic prostate cancer and implicates CDK2 inhibition as a novel therapeutic target for this most lethal subtype of prostate cancer., (©2024 The Authors; Published by the American Association for Cancer Research.)

Published
2024
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34. Plasma Kidney Injury Molecule-1 for Preoperative Prediction of Renal Cell Carcinoma Versus Benign Renal Masses, and Association With Clinical Outcomes.

Author

Xu W, Gaborieau V, Niman SM, Mukeria A, Liu X, Maremanda KP, Takakura A, Zaridze D, Freedman ML, Xie W, McDermott DF, Choueiri TK, Catalano PJ, Sabbisetti V, Bonventre JV, Pierorazio PM, Singla N, Brennan P, and Bhatt RS

Subjects
Humans, Male, Female, Middle Aged, Aged, Biomarkers, Tumor blood, Prospective Studies, ROC Curve, Nephrectomy, Adult, Prognosis, Predictive Value of Tests, Carcinoma, Renal Cell surgery, Carcinoma, Renal Cell blood, Carcinoma, Renal Cell pathology, Carcinoma, Renal Cell mortality, Kidney Neoplasms surgery, Kidney Neoplasms blood, Kidney Neoplasms pathology, Kidney Neoplasms mortality, Hepatitis A Virus Cellular Receptor 1 blood
Abstract

Purpose: Both clear cell and papillary renal cell carcinomas (RCCs) overexpress kidney injury molecule-1 (KIM-1). We investigated whether plasma KIM-1 (pKIM-1) may be a useful risk stratification tool among patients with suspicious renal masses., Methods: Prenephrectomy pKIM-1 was measured in two independent cohorts of patients with renal masses. Cohort 1, from the prospective K2 trial, included 162 patients found to have clear cell RCC (cases) and 162 patients with benign renal masses (controls). Cohort 2 included 247 patients with small (cT1a) renal masses from an academic biorepository, of whom 184 had RCC. We assessed the relationship between pKIM-1, surgical pathology, and clinical outcomes., Results: In Cohort 1, pKIM-1 distinguished RCC versus benign masses with area under the receiver operating curve (AUC-ROC, 0.81 [95% CI, 0.76 to 0.86]). In Cohort 2 (cT1a only), pKIM-1 distinguished RCC versus benign masses (AUC-ROC, 0.74 [95% CI, 0.67 to 0.80]) and the addition of pKIM-1 to an established nomogram for predicting malignancy improved the model AUC-ROC (0.65 [95% CI, 0.57 to 0.74] v 0.78 [95% CI, 0.72 to 0.85]). A pKIM-1 cutpoint identified using Cohort 2 demonstrated sensitivity of 92.5% and specificity of 60% for identifying RCC in Cohort 1. In long-term follow-up of RCC cases (Cohort 1), higher prenephrectomy pKIM-1 was associated with worse metastasis-free survival (multivariable MFS hazard ratio [HR] 1.29 per unit increase in log pKIM-1, 95% CI, 1.10 to 1.53) and overall survival (multivariable OS HR 1.31 per unit increase in log pKIM-1, 95% CI, 1.10 to 1.54). In long-term follow-up of Cohort 2, no metastatic events occurred, consistent with the favorable prognosis of resected cT1a RCC., Conclusion: Among patients with renal masses, pKIM-1 is associated with malignant pathology, worse MFS, and risk of death. pKIM-1 may be useful for selecting patients with renal masses for intervention versus surveillance.

Published
2024
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35. Epigenomic signatures of sarcomatoid differentiation to guide the treatment of renal cell carcinoma.

Author

El Zarif T, Semaan K, Eid M, Seo JH, Garinet S, Davidsohn MP, Sahgal P, Fortunato B, Canniff J, Nassar AH, Abou Alaiwi S, Bakouny Z, Lakshminarayanan G, Savignano H, Lyons K, Matar S, Ali A, Saad E, Saliby RM, Cordeiro P, Zhang Z, El Ahmar N, Laimon YN, Labaki C, Shah V, Freeman D, O'Toole J, Lee GM, Hwang J, Pomerantz M, Signoretti S, Van Allen EM, Xie W, Berchuck JE, Viswanathan SR, Braun DA, Choueiri TK, Freedman ML, and Baca SC

Subjects
Humans, DNA Methylation genetics, Cell Differentiation, Gene Expression Regulation, Neoplastic, Male, Female, Epigenesis, Genetic, Middle Aged, Proto-Oncogene Proteins c-fos, Carcinoma, Renal Cell genetics, Carcinoma, Renal Cell pathology, Carcinoma, Renal Cell metabolism, Kidney Neoplasms genetics, Kidney Neoplasms pathology, Kidney Neoplasms metabolism, Epigenomics methods
Abstract

Renal cell carcinoma with sarcomatoid differentiation (sRCC) is associated with poor survival and a heightened response to immune checkpoint inhibitors (ICIs). Two major barriers to improving outcomes for sRCC are the limited understanding of its gene regulatory programs and the low diagnostic yield of tumor biopsies due to spatial heterogeneity. Herein, we characterized the epigenomic landscape of sRCC by profiling 107 epigenomic libraries from tissue and plasma samples from 50 patients with RCC and healthy volunteers. By profiling histone modifications and DNA methylation, we identified highly recurrent epigenomic reprogramming enriched in sRCC. Furthermore, CRISPRa experiments implicated the transcription factor FOSL1 in activating sRCC-associated gene regulatory programs, and FOSL1 expression was associated with the response to ICIs in RCC in two randomized clinical trials. Finally, we established a blood-based diagnostic approach using detectable sRCC epigenomic signatures in patient plasma, providing a framework for discovering epigenomic correlates of tumor histology via liquid biopsy., Competing Interests: Declaration of interests S.R.V. reports consulting (current or past 3 years) for Jnana Therapeutics, research support from Bayer, and that their spouse is an employee of and holds equity in Kojin Therapeutics. D.A.B. reports honoraria from LM Education/Exchange Services; advisory board fees from Exelixis and AVEO; consulting fees from Merck, Pfizer, and Elephas; equity in Elephas, Fortress Biotech (subsidiary), and CurIOS Therapeutics; personal fees from Schlesinger Associates, Cancer Expert Now, Adnovate Strategies, MDedge, CancerNetwork, Catenion, OncLive, Cello Health BioConsulting, PWW Consulting, Haymarket Medical Network, Aptitude Health, ASCO Post/Harborside, Targeted Oncology, Accolade 2nd.MD, DLA Piper, AbbVie, Compugen, Link Cell Therapies, and Scholar Rock; and research support from Exelixis and AstraZeneca, outside of the submitted work. S.C.B., T.K.C., and M.L.F. are co-founders and shareholders of Precede Biosciences., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Published
2024
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36. Increased chromatin accessibility mediated by nuclear factor I drives transition to androgen receptor splice variant dependence in castration-resistant prostate cancer.

Author

Poluben L, Nouri M, Liang J, Varkaris A, Ersoy-Fazlioglu B, Voznesensky O, Lee II, Qiu X, Cato L, Seo JH, Freedman ML, Sowalsky AG, Lack NA, Corey E, Nelson PS, Brown M, Long HW, Russo JW, and Balk SP

Abstract

Androgen receptor (AR) splice variants, of which ARv7 is the most common, are increased in prostate cancer (PC) that develops resistance to androgen signaling inhibitor drugs, but the extent to which these variants drive AR activity, and whether they have novel functions or dependencies, remain to be determined. We generated a subline of VCaP PC cells (VCaP16) that is resistant to the AR inhibitor enzalutamide (ENZ) and found that AR activity was independent of the full-length AR (ARfl), despite its continued high-level expression, and was instead driven by ARv7. The ARv7 cistrome and transcriptome in VCaP16 cells mirrored that of the ARfl in VCaP cells, although ARv7 chromatin binding was weaker, and strong ARv7 binding sites correlated with higher affinity ARfl binding sites across multiple models and clinical samples. Notably, although ARv7 expression in VCaP cells increased rapidly in response to ENZ, there was a long lag before it gained chromatin binding and transcriptional activity. This lag was associated with an increase in chromatin accessibility, with the AR and nuclear factor I (NFI) motifs being most enriched at these more accessible sites. Moreover, the transcriptional effects of combined NFIB and NFIX knockdown versus ARv7 knockdown were highly correlated. These findings indicate that ARv7 can drive the AR program, but that its activity is dependent on adaptations that increase chromatin accessibility to enhance its intrinsically weak chromatin binding.

Published
2024
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37. Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions.

Author

Dareng EO, Coetzee SG, Tyrer JP, Peng PC, Rosenow W, Chen S, Davis BD, Dezem FS, Seo JH, Nameki R, Reyes AL, Aben KKH, Anton-Culver H, Antonenkova NN, Aravantinos G, Bandera EV, Beane Freeman LE, Beckmann MW, Beeghly-Fadiel A, Benitez J, Bernardini MQ, Bjorge L, Black A, Bogdanova NV, Bolton KL, Brenton JD, Budzilowska A, Butzow R, Cai H, Campbell I, Cannioto R, Chang-Claude J, Chanock SJ, Chen K, Chenevix-Trench G, Chiew YE, Cook LS, DeFazio A, Dennis J, Doherty JA, Dörk T, du Bois A, Dürst M, Eccles DM, Ene G, Fasching PA, Flanagan JM, Fortner RT, Fostira F, Gentry-Maharaj A, Giles GG, Goodman MT, Gronwald J, Haiman CA, Håkansson N, Heitz F, Hildebrandt MAT, Høgdall E, Høgdall CK, Huang RY, Jensen A, Jones ME, Kang D, Karlan BY, Karnezis AN, Kelemen LE, Kennedy CJ, Khusnutdinova EK, Kiemeney LA, Kjaer SK, Kupryjanczyk J, Labrie M, Lambrechts D, Larson MC, Le ND, Lester J, Li L, Lubiński J, Lush M, Marks JR, Matsuo K, May T, McLaughlin JR, McNeish IA, Menon U, Missmer S, Modugno F, Moffitt M, Monteiro AN, Moysich KB, Narod SA, Nguyen-Dumont T, Odunsi K, Olsson H, Onland-Moret NC, Park SK, Pejovic T, Permuth JB, Piskorz A, Prokofyeva D, Riggan MJ, Risch HA, Rodríguez-Antona C, Rossing MA, Sandler DP, Setiawan VW, Shan K, Song H, Southey MC, Steed H, Sutphen R, Swerdlow AJ, Teo SH, Terry KL, Thompson PJ, Vestrheim Thomsen LC, Titus L, Trabert B, Travis R, Tworoger SS, Valen E, Van Nieuwenhuysen E, Edwards DV, Vierkant RA, Webb PM, Weinberg CR, Weise RM, Wentzensen N, White E, Winham SJ, Wolk A, Woo YL, Wu AH, Yan L, Yannoukakos D, Zeinomar N, Zheng W, Ziogas A, Berchuck A, Goode EL, Huntsman DG, Pearce CL, Ramus SJ, Sellers TA, Freedman ML, Lawrenson K, Schildkraut JM, Hazelett D, Plummer JT, Kar S, Jones MR, Pharoah PDP, and Gayther SA

Subjects
Humans, Female, Carcinoma, Ovarian Epithelial genetics, Transcriptome, Risk Factors, Genomics methods, Case-Control Studies, Multiomics, Genome-Wide Association Study, Polymorphism, Single Nucleotide, Ovarian Neoplasms genetics, Ovarian Neoplasms pathology, Genetic Predisposition to Disease
Abstract

To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five histotype-specific EOC risk regions (p value <5 × 10 -8 ) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (p value <10 -5 ). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue datasets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (false discovery rate <0.05). Finally, by integrating genome-wide HiChIP interactome analysis with transcriptome-wide association study (TWAS), variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8, and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by a genome-wide association study., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Published
2024
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38. Multi-ancestry genome-wide association study of kidney cancer identifies 63 susceptibility regions.

Author

Purdue MP, Dutta D, Machiela MJ, Gorman BR, Winter T, Okuhara D, Cleland S, Ferreiro-Iglesias A, Scheet P, Liu A, Wu C, Antwi SO, Larkin J, Zequi SC, Sun M, Hikino K, Hajiran A, Lawson KA, Cárcano F, Blanchet O, Shuch B, Nepple KG, Margue G, Sundi D, Diver WR, Folgueira MAAK, van Bokhoven A, Neffa F, Brown KM, Hofmann JN, Rhee J, Yeager M, Cole NR, Hicks BD, Manning MR, Hutchinson AA, Rothman N, Huang WY, Linehan WM, Lori A, Ferragu M, Zidane-Marinnes M, Serrano SV, Magnabosco WJ, Vilas A, Decia R, Carusso F, Graham LS, Anderson K, Bilen MA, Arciero C, Pellegrin I, Ricard S, Scelo G, Banks RE, Vasudev NS, Soomro N, Stewart GD, Adeyoju A, Bromage S, Hrouda D, Gibbons N, Patel P, Sullivan M, Protheroe A, Nugent FI, Fournier MJ, Zhang X, Martin LJ, Komisarenko M, Eisen T, Cunningham SA, Connolly DC, Uzzo RG, Zaridze D, Mukeria A, Holcatova I, Hornakova A, Foretova L, Janout V, Mates D, Jinga V, Rascu S, Mijuskovic M, Savic S, Milosavljevic S, Gaborieau V, Abedi-Ardekani B, McKay J, Johansson M, Phouthavongsy L, Hayman L, Li J, Lungu I, Bezerra SM, Souza AG, Sares CTG, Reis RB, Gallucci FP, Cordeiro MD, Pomerantz M, Lee GM, Freedman ML, Jeong A, Greenberg SE, Sanchez A, Thompson RH, Sharma V, Thiel DD, Ball CT, Abreu D, Lam ET, Nahas WC, Master VA, Patel AV, Bernhard JC, Freedman ND, Bigot P, Reis RM, Colli LM, Finelli A, Manley BJ, Terao C, Choueiri TK, Carraro DM, Houlston R, Eckel-Passow JE, Abbosh PH, Ganna A, Brennan P, Gu J, and Chanock SJ

Subjects
Humans, Case-Control Studies, Von Hippel-Lindau Tumor Suppressor Protein genetics, White People genetics, Black People, Carcinoma, Renal Cell genetics, Genetic Predisposition to Disease, Genome-Wide Association Study, Kidney Neoplasms genetics, Polymorphism, Single Nucleotide, Quantitative Trait Loci
Abstract

Here, in a multi-ancestry genome-wide association study meta-analysis of kidney cancer (29,020 cases and 835,670 controls), we identified 63 susceptibility regions (50 novel) containing 108 independent risk loci. In analyses stratified by subtype, 52 regions (78 loci) were associated with clear cell renal cell carcinoma (RCC) and 6 regions (7 loci) with papillary RCC. Notably, we report a variant common in African ancestry individuals ( rs7629500 ) in the 3' untranslated region of VHL, nearly tripling clear cell RCC risk (odds ratio 2.72, 95% confidence interval 2.23-3.30). In cis-expression quantitative trait locus analyses, 48 variants from 34 regions point toward 83 candidate genes. Enrichment of hypoxia-inducible factor-binding sites underscores the importance of hypoxia-related mechanisms in kidney cancer. Our results advance understanding of the genetic architecture of kidney cancer, provide clues for functional investigation and enable generation of a validated polygenic risk score with an estimated area under the curve of 0.65 (0.74 including risk factors) among European ancestry individuals., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Published
2024
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39. Author Correction: Liquid biopsy epigenomic profiling for cancer subtyping.

Author

Baca SC, Seo JH, Davidsohn MP, Fortunato B, Semaan K, Sotudian S, Lakshminarayanan G, Diossy M, Qiu X, El Zarif T, Savignano H, Canniff J, Madueke I, Saliby RM, Zhang Z, Li R, Jiang Y, Taing L, Awad M, Chau CH, DeCaprio JA, Figg WD, Greten TF, Hata AN, Hodi FS, Hughes ME, Ligon KL, Lin N, Ng K, Oser MG, Meador C, Parsons HA, Pomerantz MM, Rajan A, Ritz J, Thakuria M, Tolaney SM, Wen PY, Long H, Berchuck JE, Szallasi Z, Choueiri TK, and Freedman ML

Published
2024
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40. The PENGUIN approach to reconstruct protein interactions at enhancer-promoter regions and its application to prostate cancer.

Author

Armaos A, Serra F, Núñez-Carpintero I, Seo JH, Baca SC, Gustincich S, Valencia A, Freedman ML, Cirillo D, Giambartolomei C, and Tartaglia GG

Subjects
Male, Animals, Humans, Enhancer Elements, Genetic genetics, Promoter Regions, Genetic genetics, Proteins genetics, Spheniscidae genetics, Prostatic Neoplasms genetics
Abstract

We introduce Promoter-Enhancer-Guided Interaction Networks (PENGUIN), a method for studying protein-protein interaction (PPI) networks within enhancer-promoter interactions. PENGUIN integrates H3K27ac-HiChIP data with tissue-specific PPIs to define enhancer-promoter PPI networks (EPINs). We validated PENGUIN using cancer (LNCaP) and benign (LHSAR) prostate cell lines. Our analysis detected EPIN clusters enriched with the architectural protein CTCF, a regulator of enhancer-promoter interactions. CTCF presence was coupled with the prevalence of prostate cancer (PrCa) single nucleotide polymorphisms (SNPs) within the same EPIN clusters, suggesting functional implications in PrCa. Within the EPINs displaying enrichments in both CTCF and PrCa SNPs, we also show enrichment in oncogenes. We substantiated our identified SNPs through CRISPR/Cas9 knockout and RNAi screens experiments. Here we show that PENGUIN provides insights into the intricate interplay between enhancer-promoter interactions and PPI networks, which are crucial for identifying key genes and potential intervention targets. A dedicated server is available at https://penguin.life.bsc.es/ ., (© 2023. The Author(s).)

Published
2023
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41. Grade Group 1 Prostate Cancers Exhibit Tumor-defining Androgen Receptor-driven Programs.

Author

Linder S, Severson TM, van der Mijn KJC, Nevedomskaya E, Siefert JC, Stelloo S, Pomerantz MM, Freedman ML, van der Poel H, Jerónimo C, Henrique R, Bergman AM, and Zwart W

Subjects
Male, Humans, Neoplasm Grading, Prostate pathology, Receptors, Androgen genetics, Receptors, Androgen metabolism, Prostatic Neoplasms pathology
Abstract

Grade group 1 (GG1) primary prostate cancers with a pathologic Gleason score of 6 are considered indolent and generally not associated with fatal outcomes, so treatment is not indicated for most cases. These low-grade cancers have an overall negligible risk of locoregional progression and metastasis to distant organs, which is why there is an ongoing debate about whether these lesions should be reclassified as "noncancerous". However, the underlying molecular activity of key disease drivers, such as the androgen receptor (AR), have thus far not been thoroughly characterized in low-grade tumors. Therefore, we set out to delineate the AR chromatin-binding landscape in low-grade GG1 prostate cancers to gain insights into whether these AR-driven programs are actually tumor-specific or are normal prostate epithelium-like. These analyses showed that GG1 tumors do not harbor a distinct AR cistrome and, similar to higher-grade cancers, AR preferentially binds to tumor-defining cis-regulatory elements. Furthermore, the enhancer activity of these regions and the expression of their respective target genes were not significantly different in GG1 tumors. From an epigenetic perspective, this finding supports the cancer designation currently given to these low-grade tumors and clearly distinguishes them from noncancerous benign tissue. PATIENT SUMMARY: We characterized the molecular activity of the androgen receptor protein, which drives prostate cancer disease, in low-grade tumors. Our results show that these tumors are true cancers and are clearly separate from benign prostate tissue despite their low clinical aggressiveness., (Copyright © 2023 European Association of Urology. Published by Elsevier B.V. All rights reserved.)

Published
2023
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42. Liquid biopsy epigenomic profiling for cancer subtyping.

Author

Baca SC, Seo JH, Davidsohn MP, Fortunato B, Semaan K, Sotudian S, Lakshminarayanan G, Diossy M, Qiu X, El Zarif T, Savignano H, Canniff J, Madueke I, Saliby RM, Zhang Z, Li R, Jiang Y, Taing L, Awad M, Chau CH, DeCaprio JA, Figg WD, Greten TF, Hata AN, Hodi FS, Hughes ME, Ligon KL, Lin N, Ng K, Oser MG, Meador C, Parsons HA, Pomerantz MM, Rajan A, Ritz J, Thakuria M, Tolaney SM, Wen PY, Long H, Berchuck JE, Szallasi Z, Choueiri TK, and Freedman ML

Subjects
Humans, Epigenomics, Biomarkers, Tumor genetics, Liquid Biopsy methods, Mutation, Neoplasms genetics, Circulating Tumor DNA genetics
Abstract

Although circulating tumor DNA (ctDNA) assays are increasingly used to inform clinical decisions in cancer care, they have limited ability to identify the transcriptional programs that govern cancer phenotypes and their dynamic changes during the course of disease. To address these limitations, we developed a method for comprehensive epigenomic profiling of cancer from 1 ml of patient plasma. Using an immunoprecipitation-based approach targeting histone modifications and DNA methylation, we measured 1,268 epigenomic profiles in plasma from 433 individuals with one of 15 cancers. Our assay provided a robust proxy for transcriptional activity, allowing us to infer the expression levels of diagnostic markers and drug targets, measure the activity of therapeutically targetable transcription factors and detect epigenetic mechanisms of resistance. This proof-of-concept study in advanced cancers shows how plasma epigenomic profiling has the potential to unlock clinically actionable information that is currently accessible only via direct tissue sampling., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Published
2023
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44. A biallelic multiple nucleotide length polymorphism explains functional causality at 5p15.33 prostate cancer risk locus.

Author

Spisak S, Tisza V, Nuzzo PV, Seo JH, Pataki B, Ribli D, Sztupinszki Z, Bell C, Rohanizadegan M, Stillman DR, Alaiwi SA, Bartels AH, Papp M, Shetty A, Abbasi F, Lin X, Lawrenson K, Gayther SA, Pomerantz M, Baca S, Solymosi N, Csabai I, Szallasi Z, Gusev A, and Freedman ML

Subjects
Humans, Male, Chromatin genetics, Acetylation, Alleles, Nucleotides, Polymorphism, Single Nucleotide, Neoplasms
Abstract

To date, single-nucleotide polymorphisms (SNPs) have been the most intensively investigated class of polymorphisms in genome wide associations studies (GWAS), however, other classes such as insertion-deletion or multiple nucleotide length polymorphism (MNLPs) may also confer disease risk. Multiple reports have shown that the 5p15.33 prostate cancer risk region is a particularly strong expression quantitative trait locus (eQTL) for Iroquois Homeobox 4 (IRX4) transcripts. Here, we demonstrate using epigenome and genome editing that a biallelic (21 and 47 base pairs (bp)) MNLP is the causal variant regulating IRX4 transcript levels. In LNCaP prostate cancer cells (homozygous for the 21 bp short allele), a single copy knock-in of the 47 bp long allele potently alters the chromatin state, enabling de novo functional binding of the androgen receptor (AR) associated with increased chromatin accessibility, Histone 3 lysine 27 acetylation (H3K27ac), and ~3-fold upregulation of IRX4 expression. We further show that an MNLP is amongst the strongest candidate susceptibility variants at two additional prostate cancer risk loci. We estimated that at least 5% of prostate cancer risk loci could be explained by functional non-SNP causal variants, which may have broader implications for other cancers GWAS. More generally, our results underscore the importance of investigating other classes of inherited variation as causal mediators of human traits., (© 2023. Springer Nature Limited.)

Published
2023
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45. Rewiring of master transcription factor cistromes during high-grade serous ovarian cancer development.

Author

Nameki RA, Chang H, Yu P, Abbasi F, Lin X, Reddy J, Haro M, Fonseca MA, Freedman ML, Drapkin R, Corona RI, and Lawrenson K

Abstract

The transcription factors MECOM, PAX8, SOX17 and WT1 are candidate master regulators of high-grade serous 'ovarian' cancer (HGSC), yet their cooperative role in the hypothesized tissue of origin, the fallopian tube secretory epithelium (FTSEC) is unknown. We generated 26 epigenome (CUT&TAG, CUT&RUN, ATAC-seq and HiC) data sets and 24 profiles of RNA-seq transcription factor knock-down followed by RNA sequencing in FTSEC and HGSC models to define binding sites and gene sets regulated by these factors in cis and trans . This revealed that MECOM, PAX8, SOX17 and WT1 are lineage-enriched, super-enhancer associated master regulators whose cooperative DNA-binding patterns and target genes are re-wired during tumor development. All four TFs were indispensable for HGSC clonogenicity and survival but only depletion of PAX8 and WT1 impaired FTSEC cell survival. These four TFs were pharmacologically inhibited by transcriptional inhibitors only in HGSCs but not in FTSECs. Collectively, our data highlights that tumor-specific epigenetic remodeling is tightly related to MECOM, PAX8, SOX17 and WT1 activity and these transcription factors are targetable in a tumor-specific manner through transcriptional inhibitors.

Published
2023
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46. Analysis of evolutionary dynamics and clonal architecture in prostate cancer.

Author

Conway JR, Tewari AK, Camp SY, Han S, Crowdis J, He MX, Nyame YA, AlDubayan SH, Schultz N, Szallasi Z, Pomerantz MM, Freedman ML, Fong L, Nelson PS, Brown M, Salari K, and Allen EV

Abstract

The extent to which clinical and genomic characteristics associate with prostate cancer clonal architecture, tumor evolution, and therapeutic response remains unclear. Here, we reconstructed the clonal architecture and evolutionary trajectories of 845 prostate cancer tumors with harmonized clinical and molecular data. We observed that tumors from patients who self-reported as Black had more linear and monoclonal architectures, despite these men having higher rates of biochemical recurrence. This finding contrasts with prior observations relating polyclonal architecture to adverse clinical outcomes. Additionally, we utilized a novel approach to mutational signature analysis that leverages clonal architecture to uncover additional cases of homologous recombination and mismatch repair deficiency in primary and metastatic tumors and link the origin of mutational signatures to specific subclones. Broadly, prostate cancer clonal architecture analysis reveals novel biological insights that may be immediately clinically actionable and provide multiple opportunities for subsequent investigation., Statement of Significance: Tumors from patients who self-reported as Black demonstrate linear and monoclonal evolutionary trajectories yet experience higher rates of biochemical recurrence. In addition, analysis of clonal and subclonal mutational signatures identifies additional tumors with potentially actionable alterations such as deficiencies in mismatch repair and homologous recombination.

Published
2023
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47. Nucleosome Patterns in Circulating Tumor DNA Reveal Transcriptional Regulation of Advanced Prostate Cancer Phenotypes.

Author

De Sarkar N, Patton RD, Doebley AL, Hanratty B, Adil M, Kreitzman AJ, Sarthy JF, Ko M, Brahma S, Meers MP, Janssens DH, Ang LS, Coleman IM, Bose A, Dumpit RF, Lucas JM, Nunez TA, Nguyen HM, McClure HM, Pritchard CC, Schweizer MT, Morrissey C, Choudhury AD, Baca SC, Berchuck JE, Freedman ML, Ahmad K, Haffner MC, Montgomery RB, Corey E, Henikoff S, Nelson PS, and Ha G

Subjects
Male, Humans, Nucleosomes genetics, Precision Medicine, Gene Expression Regulation, Neoplastic, Phenotype, Circulating Tumor DNA genetics, Prostatic Neoplasms pathology
Abstract

Advanced prostate cancers comprise distinct phenotypes, but tumor classification remains clinically challenging. Here, we harnessed circulating tumor DNA (ctDNA) to study tumor phenotypes by ascertaining nucleosome positioning patterns associated with transcription regulation. We sequenced plasma ctDNA whole genomes from patient-derived xenografts representing a spectrum of androgen receptor active (ARPC) and neuroendocrine (NEPC) prostate cancers. Nucleosome patterns associated with transcriptional activity were reflected in ctDNA at regions of genes, promoters, histone modifications, transcription factor binding, and accessible chromatin. We identified the activity of key phenotype-defining transcriptional regulators from ctDNA, including AR, ASCL1, HOXB13, HNF4G, and GATA2. To distinguish NEPC and ARPC in patient plasma samples, we developed prediction models that achieved accuracies of 97% for dominant phenotypes and 87% for mixed clinical phenotypes. Although phenotype classification is typically assessed by IHC or transcriptome profiling from tumor biopsies, we demonstrate that ctDNA provides comparable results with diagnostic advantages for precision oncology., Significance: This study provides insights into the dynamics of nucleosome positioning and gene regulation associated with cancer phenotypes that can be ascertained from ctDNA. New methods for classification in phenotype mixtures extend the utility of ctDNA beyond assessments of somatic DNA alterations with important implications for molecular classification and precision oncology. This article is highlighted in the In This Issue feature, p. 517., (©2022 The Authors; Published by the American Association for Cancer Research.)

Published
2023
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48. Enhancer profiling identifies epigenetic markers of endocrine resistance and reveals therapeutic options for metastatic castration-resistant prostate cancer patients.

Author

Severson TM, Zhu Y, Prekovic S, Schuurman K, Nguyen HM, Brown LG, Hakkola S, Kim Y, Kneppers J, Linder S, Stelloo S, Lieftink C, van der Heijden M, Nykter M, van der Noort V, Sanders J, Morris B, Jenster G, van Leenders GJ, Pomerantz M, Freedman ML, Beijersbergen RL, Urbanucci A, Wessels L, Corey E, Zwart W, and Bergman AM

Abstract

Androgen Receptor (AR) signaling inhibitors, including enzalutamide, are treatment options for patients with metastatic castration-resistant prostate cancer (mCRPC), but resistance inevitably develops. Using metastatic samples from a prospective phase II clinical trial, we epigenetically profiled enhancer/promoter activities with H3K27ac chromatin immunoprecipitation followed by sequencing, before and after AR-targeted therapy. We identified a distinct subset of H3K27ac-differentially marked regions that associated with treatment responsiveness. These data were successfully validated in mCRPC patient-derived xenograft models (PDX). In silico analyses revealed HDAC3 as a critical factor that can drive resistance to hormonal interventions, which we validated in vitro . Using cell lines and mCRPC PDX tumors in vitro , we identified drug-drug synergy between enzalutamide and the pan-HDAC inhibitor vorinostat, providing therapeutic proof-of-concept. These findings demonstrate rationale for new therapeutic strategies using a combination of AR and HDAC inhibitors to improve patient outcome in advanced stages of mCRPC.

Published
2023
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49. Optimized high-throughput screening of non-coding variants identified from genome-wide association studies.

Author

Morova T, Ding Y, Huang CF, Sar F, Schwarz T, Giambartolomei C, Baca SC, Grishin D, Hach F, Gusev A, Freedman ML, Pasaniuc B, and Lack NA

Subjects
Humans, Male, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Transcription Factors genetics, Genome-Wide Association Study, Regulatory Sequences, Nucleic Acid
Abstract

The vast majority of disease-associated single nucleotide polymorphisms (SNP) identified from genome-wide association studies (GWAS) are localized in non-coding regions. A significant fraction of these variants impact transcription factors binding to enhancer elements and alter gene expression. To functionally interrogate the activity of such variants we developed snpSTARRseq, a high-throughput experimental method that can interrogate the functional impact of hundreds to thousands of non-coding variants on enhancer activity. snpSTARRseq dramatically improves signal-to-noise by utilizing a novel sequencing and bioinformatic approach that increases both insert size and the number of variants tested per loci. Using this strategy, we interrogated known prostate cancer (PCa) risk-associated loci and demonstrated that 35% of them harbor SNPs that significantly altered enhancer activity. Combining these results with chromosomal looping data we could identify interacting genes and provide a mechanism of action for 20 PCa GWAS risk regions. When benchmarked to orthogonal methods, snpSTARRseq showed a strong correlation with in vivo experimental allelic-imbalance studies whereas there was no correlation with predictive in silico approaches. Overall, snpSTARRseq provides an integrated experimental and computational framework to functionally test non-coding genetic variants., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Published
2023
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50. Epigenomic charting and functional annotation of risk loci in renal cell carcinoma.

Author

Nassar AH, Abou Alaiwi S, Baca SC, Adib E, Corona RI, Seo JH, Fonseca MAS, Spisak S, El Zarif T, Tisza V, Braun DA, Du H, He M, Flaifel A, Alchoueiry M, Denize T, Matar SG, Acosta A, Shukla S, Hou Y, Steinharter J, Bouchard G, Berchuck JE, O'Connor E, Bell C, Nuzzo PV, Mary Lee GS, Signoretti S, Hirsch MS, Pomerantz M, Henske E, Gusev A, Lawrenson K, Choueiri TK, Kwiatkowski DJ, and Freedman ML

Subjects
Humans, Epigenomics, Transcription Factors genetics, Oncogenes, Forkhead Transcription Factors genetics, Carcinoma, Renal Cell pathology, Kidney Neoplasms pathology
Abstract

While the mutational and transcriptional landscapes of renal cell carcinoma (RCC) are well-known, the epigenome is poorly understood. We characterize the epigenome of clear cell (ccRCC), papillary (pRCC), and chromophobe RCC (chRCC) by using ChIP-seq, ATAC-Seq, RNA-seq, and SNP arrays. We integrate 153 individual data sets from 42 patients and nominate 50 histology-specific master transcription factors (MTF) to define RCC histologic subtypes, including EPAS1 and ETS-1 in ccRCC, HNF1B in pRCC, and FOXI1 in chRCC. We confirm histology-specific MTFs via immunohistochemistry including a ccRCC-specific TF, BHLHE41. FOXI1 overexpression with knock-down of EPAS1 in the 786-O ccRCC cell line induces transcriptional upregulation of chRCC-specific genes, TFCP2L1, ATP6V0D2, KIT, and INSRR, implicating FOXI1 as a MTF for chRCC. Integrating RCC GWAS risk SNPs with H3K27ac ChIP-seq and ATAC-seq data reveals that risk-variants are significantly enriched in allelically-imbalanced peaks. This epigenomic atlas in primary human samples provides a resource for future investigation., (© 2023. The Author(s).)

Published
2023
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