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1. Mendelian randomisation study of smoking exposure in relation to breast cancer risk

Author

Park, HA, Neumeyer, S, Michailidou, K, Bolla, MK, Wang, Q, Dennis, J, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Arndt, V, Aronson, KJ, Augustinsson, A, Baten, A, Beane Freeman, LE, Becher, H, Beckmann, MW, Behrens, S, Benitez, J, Bermisheva, M, Bogdanova, NV, Bojesen, SE, Brauch, H, Brenner, H, Brucker, SY, Burwinkel, B, Campa, D, Canzian, F, Castelao, JE, Chanock, SJ, Chenevix-Trench, G, Clarke, CL, Børresen-Dale, A-L, Grenaker Alnæs, GI, Sahlberg, KK, Ottestad, L, Kåresen, R, Schlichting, E, Holmen, MM, Sauer, T, Haakensen, V, Engebråten, O, Naume, B, Fosså, A, Kiserud, CE, Reinertsen, KV, Helland, Å, Riis, M, Geisler, J, Conroy, DM, Couch, FJ, Cox, A, Cross, SS, Czene, K, Daly, MB, Devilee, P, Dörk, T, dos-Santos-Silva, I, Dwek, M, Eccles, DM, Eliassen, AH, Engel, C, Eriksson, M, Evans, DG, Fasching, PA, Flyger, H, Fritschi, L, García-Closas, M, García-Sáenz, JA, Gaudet, MM, Giles, GG, Glendon, G, Goldberg, MS, Goldgar, DE, González-Neira, A, Grip, M, Guénel, P, Hahnen, E, Haiman, CA, Håkansson, N, Hall, P, Hamann, U, Han, S, Harkness, EF, Hart, SN, He, W, Heemskerk-Gerritsen, BAM, Hopper, JL, Hunter, DJ, Clarke, C, Marsh, D, Scott, R, Baxter, R, Yip, D, Carpenter, J, Davis, A, Pathmanathan, N, Simpson, P, Graham, D, Sachchithananthan, M, Amor, D, Andrews, L, Antill, Y, Balleine, R, Beesley, J, Bennett, I, Bogwitz, M, Botes, L, Brennan, M, Brown, M, Buckley, M, Burke, J, Butow, P, Caldon, L, Campbell, I, Chauhan, D, Chauhan, M, Christian, A, Cohen, P, Colley, A, Crook, A, Cui, J, Cummings, M, Dawson, S-J, DeFazio, A, Delatycki, M, Dickson, R, Dixon, J, Edkins, T, Edwards, S, Farshid, G, Fellows, A, Fenton, G, Field, M, Flanagan, J, Fong, P, Forrest, L, Fox, S, French, J, Friedlander, M, Gaff, C, Gattas, M, George, P, Greening, S, Harris, M, Hart, S, Hayward, N, Hopper, J, Hoskins, C, Hunt, C, James, P, Jenkins, M, Kidd, A, Kirk, J, Koehler, J, Kollias, J, Lakhani, S, Lawrence, M, Lindeman, G, Lipton, L, Lobb, L, Mann, G, McLachlan, SA, Meiser, B, Milne, R, Nightingale, S, O’Connell, S, O’Sullivan, S, Ortega, DG, Pachter, N, Patterson, B, Pearn, A, Phillips, K, Pieper, E, Rickard, E, Robinson, B, Saleh, M, Salisbury, E, Saunders, C, Saunus, J, Scott, C, Sexton, A, Shelling, A, Southey, M, Spurdle, A, Taylor, J, Taylor, R, Thorne, H, Trainer, A, Tucker, K, Visvader, J, Walker, L, Williams, R, Winship, I, Young, MA, Jager, A, Jakubowska, A, John, EM, Jung, A, Kaaks, R, Kapoor, PM, Keeman, R, Khusnutdinova, E, Kitahara, CM, Koppert, LB, Koutros, S, Kristensen, VN, Kurian, AW, Lacey, J, Lambrechts, D, Le Marchand, L, Lo, W-Y, Lubiński, J, Mannermaa, A, Manoochehri, M, Margolin, S, Martinez, ME, Mavroudis, D, Meindl, A, Menon, U, Milne, RL, Muranen, TA, Nevanlinna, H, Newman, WG, Nordestgaard, BG, Offit, K, Olshan, AF, Olsson, H, Park-Simon, T-W, Peterlongo, P, Peto, J, Plaseska-Karanfilska, D, Presneau, N, Radice, P, Rennert, G, Rennert, HS, Romero, A, Saloustros, E, Sawyer, EJ, Schmidt, MK, Schmutzler, RK, Schoemaker, MJ, Schwentner, L, Shah, M, Shu, X-O, Simard, J, Smeets, A, Southey, MC, Spinelli, JJ, Stevens, V, Swerdlow, AJ, Tamimi, RM, Tapper, WJ, Taylor, JA, Terry, MB, Tomlinson, I, Troester, MA, Truong, T, Vachon, CM, van Veen, EM, Vijai, J, Wang, S, Wendt, C, Winqvist, R, Wolk, A, Ziogas, A, Dunning, AM, Pharoah, PDP, Easton, DF, Zheng, W, Kraft, P, Chang-Claude, J, HUS Gynecology and Obstetrics, Department of Obstetrics and Gynecology, Park, Hanla A. [0000-0001-8055-3729], Dennis, Joe [0000-0003-4591-1214], Augustinsson, Annelie [0000-0003-3415-0536], Brenner, Hermann [0000-0002-6129-1572], Canzian, Federico [0000-0002-4261-4583], Cox, Angela [0000-0002-5138-1099], Devilee, Peter [0000-0002-8023-2009], Fasching, Peter A. [0000-0003-4885-8471], Harkness, Elaine F. [0000-0001-6625-7739], Hart, Steven N. [0000-0001-7714-2734], Heemskerk-Gerritsen, Bernadette A. M. [0000-0002-9724-6693], Jakubowska, Anna [0000-0002-5650-0501], Kapoor, Pooja Middha [0000-0001-5503-8215], Kurian, Allison W. [0000-0002-6175-9470], Newman, William G. [0000-0002-6382-4678], Peterlongo, Paolo [0000-0001-6951-6855], Peto, Julian [0000-0002-1685-8912], Sawyer, Elinor J. [0000-0001-8285-4111], Scott, Christopher [0000-0003-1340-0647], Smeets, Ann [0000-0002-5091-6602], Tomlinson, Ian [0000-0003-3037-1470], Truong, Thérèse [0000-0002-2943-6786], Pharoah, Paul D. P. [0000-0001-8494-732X], and Apollo - University of Cambridge Repository

Subjects
0301 basic medicine, Oncology, Medicin och hälsovetenskap, Cancer Research, Genotyping Techniques, Breast Neoplasms, Case-Control Studies, Cigarette Smoking, Female, Genetic Pleiotropy, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide, ALCOHOL, Medical and Health Sciences, 0302 clinical medicine, Breast cancer, Pleiotropy, Epidemiology, Medicine, TOBACCO, Breast Neoplasms/epidemiology, Cigarette Smoking/adverse effects, WOMEN, ASSOCIATION, Single Nucleotide, 3. Good health, Substance abuse, 692/699/67/1347, 030220 oncology & carcinogenesis, Life Sciences & Biomedicine, 692/499, medicine.medical_specialty, 3122 Cancers, Single-nucleotide polymorphism, Article, 03 medical and health sciences, Internal medicine, ddc:610, Polymorphism, Genetic association, Science & Technology, business.industry, Cancer, medicine.disease, 030104 developmental biology, Clinical research, Risk factors, TISSUE, INFERENCE, CIGARETTE-SMOKING, business
Abstract

Background Despite a modest association between tobacco smoking and breast cancer risk reported by recent epidemiological studies, it is still equivocal whether smoking is causally related to breast cancer risk. Methods We applied Mendelian randomisation (MR) to evaluate a potential causal effect of cigarette smoking on breast cancer risk. Both individual-level data as well as summary statistics for 164 single-nucleotide polymorphisms (SNPs) reported in genome-wide association studies of lifetime smoking index (LSI) or cigarette per day (CPD) were used to obtain MR effect estimates. Data from 108,420 invasive breast cancer cases and 87,681 controls were used for the LSI analysis and for the CPD analysis conducted among ever-smokers from 26,147 cancer cases and 26,072 controls. Sensitivity analyses were conducted to address pleiotropy. Results Genetically predicted LSI was associated with increased breast cancer risk (OR 1.18 per SD, 95% CI: 1.07–1.30, P = 0.11 × 10–2), but there was no evidence of association for genetically predicted CPD (OR 1.02, 95% CI: 0.78–1.19, P = 0.85). The sensitivity analyses yielded similar results and showed no strong evidence of pleiotropic effect. Conclusion Our MR study provides supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers.

Published
2021
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4. Association analysis identifies 65 new breast cancer risk loci

Author

Michailidou, K, Lindström, S, Dennis, J, Beesley, J, Hui, S, Kar, S, Lemaçon, A, Soucy, P, Glubb, D, Rostamianfar, A, Bolla, MK, Wang, Q, Tyrer, J, Dicks, E, Lee, A, Wang, Z, Allen, J, Keeman, R, Eilber, U, French, JD, Qing Chen, X, Fachal, L, McCue, K, McCart Reed, AE, Ghoussaini, M, Carroll, JS, Jiang, X, Finucane, H, Adams, M, Adank, MA, Ahsan, H, Aittomäki, K, Anton-Culver, H, Antonenkova, NN, Arndt, V, Aronson, KJ, Arun, B, Auer, PL, Bacot, F, Barrdahl, M, Baynes, C, Beckmann, MW, Behrens, S, Benitez, J, Bermisheva, M, Bernstein, L, Blomqvist, C, Bogdanova, NV, Bojesen, SE, Bonanni, B, Børresen-Dale, A-L, Brand, JS, Brauch, H, Brennan, P, Brenner, H, Brinton, L, Broberg, P, Brock, IW, Broeks, A, Brooks-Wilson, A, Brucker, SY, Brüning, T, Burwinkel, B, Butterbach, K, Cai, Q, Cai, H, Caldés, T, Canzian, F, Carracedo, A, Carter, BD, Castelao, JE, Chan, TL, David Cheng, T-Y, Seng Chia, K, Choi, J-Y, Christiansen, H, Clarke, CL, NBCS Collaborators, Collée, M, Conroy, DM, Cordina-Duverger, E, Cornelissen, S, Cox, DG, Cox, A, Cross, SS, Cunningham, JM, Czene, K, Daly, MB, Devilee, P, Doheny, KF, Dörk, T, Dos-Santos-Silva, I, Dumont, M, Durcan, L, Dwek, M, Eccles, DM, Ekici, AB, Eliassen, AH, Ellberg, C, Elvira, M, Engel, C, Eriksson, M, Fasching, PA, Figueroa, J, Flesch-Janys, D, Fletcher, O, Flyger, H, Fritschi, L, Gaborieau, V, Gabrielson, M, Gago-Dominguez, M, Gao, Y-T, Gapstur, SM, García-Sáenz, JA, Gaudet, MM, Georgoulias, V, Giles, GG, Glendon, G, Goldberg, MS, Goldgar, DE, González-Neira, A, Grenaker Alnæs, GI, Grip, M, Gronwald, J, Grundy, A, Guénel, P, Haeberle, L, Hahnen, E, Haiman, CA, Håkansson, N, Hamann, U, Hamel, N, Hankinson, S, Harrington, P, Hart, SN, Hartikainen, JM, Hartman, M, Hein, A, Heyworth, J, Hicks, B, Hillemanns, P, Ho, DN, Hollestelle, A, Hooning, MJ, Hoover, RN, Hopper, JL, Hou, M-F, Hsiung, C-N, Huang, G, Humphreys, K, Ishiguro, J, Ito, H, Iwasaki, M, Iwata, H, Jakubowska, A, Janni, W, John, EM, Johnson, N, Jones, K, Jones, M, Jukkola-Vuorinen, A, Kaaks, R, Kabisch, M, Kaczmarek, K, Kang, D, Kasuga, Y, Kerin, MJ, Khan, S, Khusnutdinova, E, Kiiski, JI, Kim, S-W, Knight, JA, Kosma, V-M, Kristensen, VN, Krüger, U, Kwong, A, Lambrechts, D, Le Marchand, L, Lee, E, Lee, MH, Lee, JW, Neng Lee, C, Lejbkowicz, F, Li, J, Lilyquist, J, Lindblom, A, Lissowska, J, Lo, W-Y, Loibl, S, Long, J, Lophatananon, A, Lubinski, J, Luccarini, C, Lux, MP, Ma, ESK, MacInnis, RJ, Maishman, T, Makalic, E, Malone, KE, Kostovska, IM, Mannermaa, A, Manoukian, S, Manson, JE, Margolin, S, Mariapun, S, Martinez, ME, Matsuo, K, Mavroudis, D, McKay, J, McLean, C, Meijers-Heijboer, H, Meindl, A, Menéndez, P, Menon, U, Meyer, J, Miao, H, Miller, N, Taib, NAM, Muir, K, Mulligan, AM, Mulot, C, Neuhausen, SL, Nevanlinna, H, Neven, P, Nielsen, SF, Noh, D-Y, Nordestgaard, BG, Norman, A, Olopade, OI, Olson, JE, Olsson, H, Olswold, C, Orr, N, Pankratz, VS, Park, SK, Park-Simon, T-W, Lloyd, R, Perez, JIA, Peterlongo, P, Peto, J, Phillips, K-A, Pinchev, M, Plaseska-Karanfilska, D, Prentice, R, Presneau, N, Prokofyeva, D, Pugh, E, Pylkäs, K, Rack, B, Radice, P, Rahman, N, Rennert, G, Rennert, HS, Rhenius, V, Romero, A, Romm, J, Ruddy, KJ, Rüdiger, T, Rudolph, A, Ruebner, M, Rutgers, EJT, Saloustros, E, Sandler, DP, Sangrajrang, S, Sawyer, EJ, Schmidt, DF, Schmutzler, RK, Schneeweiss, A, Schoemaker, MJ, Schumacher, F, Schürmann, P, Scott, RJ, Scott, C, Seal, S, Seynaeve, C, Shah, M, Sharma, P, Shen, C-Y, Sheng, G, Sherman, ME, Shrubsole, MJ, Shu, X-O, Smeets, A, Sohn, C, Southey, MC, Spinelli, JJ, Stegmaier, C, Stewart-Brown, S, Stone, J, Stram, DO, Surowy, H, Swerdlow, A, Tamimi, R, Taylor, JA, Tengström, M, Teo, SH, Beth Terry, M, Tessier, DC, Thanasitthichai, S, Thöne, K, Tollenaar, RAEM, Tomlinson, I, Tong, L, Torres, D, Truong, T, Tseng, C-C, Tsugane, S, Ulmer, H-U, Ursin, G, Untch, M, Vachon, C, Van Asperen, CJ, Van Den Berg, D, Van Den Ouweland, AMW, Van Der Kolk, L, Van Der Luijt, RB, Vincent, D, Vollenweider, J, Waisfisz, Q, Wang-Gohrke, S, Weinberg, CR, Wendt, C, Whittemore, AS, Wildiers, H, Willett, W, Winqvist, R, Wolk, A, Wu, AH, Xia, L, Yamaji, T, Yang, XR, Har Yip, C, Yoo, K-Y, Yu, J-C, Zheng, W, Zheng, Y, Zhu, B, Ziogas, A, Ziv, E, ABCTB Investigators, ConFab/AOCS Investigators, Lakhani, Antoniou, AC, Droit, A, Andrulis, IL, Amos, CI, Couch, FJ, Pharoah, PDP, Chang-Claude, J, Hall, P, Hunter, DJ, Milne, RL, García-Closas, M, Schmidt, MK, Chanock, SJ, Dunning, AM, Edwards, SL, Bader, GD, Chenevix-Trench, G, Simard, J, Kraft, P, and Easton, DF

Subjects
ConFab/AOCS Investigators, ABCTB Investigators, skin and connective tissue diseases, 3. Good health, NBCS Collaborators
Abstract

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

5. Germline polygenic risk scores are associated with immune gene expression signature and immune cell infiltration in breast cancer.

Author

Liu Y, Peng C, Brorson IS, O'Mahony DG, Kelly RL, Heng YJ, Baker GM, Grenaker Alnæs GI, Bodelon C, Stover DG, Van Allen EM, Eliassen AH, Kristensen VN, Tamimi RM, and Kraft P

Subjects
Humans, Female, Tumor Microenvironment genetics, Tumor Microenvironment immunology, Risk Factors, Middle Aged, Transcriptome, Adult, Genetic Risk Score, Breast Neoplasms genetics, Breast Neoplasms pathology, Breast Neoplasms immunology, Multifactorial Inheritance genetics, Genetic Predisposition to Disease
Abstract

The tumor immune microenvironment (TIME) plays key roles in tumor progression and response to immunotherapy. Previous studies have identified individual germline variants associated with differences in TIME. Here, we hypothesize that common variants associated with breast cancer risk or cancer-related traits, represented by polygenic risk scores (PRSs), may jointly influence immune features in TIME. We derived 154 immune traits from bulk gene expression profiles of 764 breast tumors and 598 adjacent normal tissue samples from 825 individuals with breast cancer in the Nurses' Health Study (NHS) and NHSII. Immunohistochemical staining of four immune cell markers were available for a subset of 205 individuals. Germline PRSs were calculated for 16 different traits including breast cancer, autoimmune diseases, type 2 diabetes, ages at menarche and menopause, body mass index (BMI), BMI-adjusted waist-to-hip ratio, alcohol intake, and tobacco smoking. Overall, we identified 44 associations between germline PRSs and immune traits at false discovery rate q < 0.25, including 3 associations with q < 0.05. We observed consistent inverse associations of inflammatory bowel disease (IBD) and Crohn disease (CD) PRSs with interferon signaling and STAT1 scores in breast tumor and adjacent normal tissue; these associations were replicated in a Norwegian cohort. Inverse associations were also consistently observed for IBD PRS and B cell abundance in normal tissue. We also observed positive associations between CD PRS and endothelial cell abundance in tumor. Our findings suggest that the genetic mechanisms that influence immune-related diseases are also associated with TIME in breast cancer., Competing Interests: Declaration of interests The authors declare no competing interests., (Published by Elsevier Inc.)

Published
2024
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6. Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.

Author

Mavaddat N, Michailidou K, Dennis J, Lush M, Fachal L, Lee A, Tyrer JP, Chen TH, Wang Q, Bolla MK, Yang X, Adank MA, Ahearn T, Aittomäki K, Allen J, Andrulis IL, Anton-Culver H, Antonenkova NN, Arndt V, Aronson KJ, Auer PL, Auvinen P, Barrdahl M, Beane Freeman LE, Beckmann MW, Behrens S, Benitez J, Bermisheva M, Bernstein L, Blomqvist C, Bogdanova NV, Bojesen SE, Bonanni B, Børresen-Dale AL, Brauch H, Bremer M, Brenner H, Brentnall A, Brock IW, Brooks-Wilson A, Brucker SY, Brüning T, Burwinkel B, Campa D, Carter BD, Castelao JE, Chanock SJ, Chlebowski R, Christiansen H, Clarke CL, Collée JM, Cordina-Duverger E, Cornelissen S, Couch FJ, Cox A, Cross SS, Czene K, Daly MB, Devilee P, Dörk T, Dos-Santos-Silva I, Dumont M, Durcan L, Dwek M, Eccles DM, Ekici AB, Eliassen AH, Ellberg C, Engel C, Eriksson M, Evans DG, Fasching PA, Figueroa J, Fletcher O, Flyger H, Försti A, Fritschi L, Gabrielson M, Gago-Dominguez M, Gapstur SM, García-Sáenz JA, Gaudet MM, Georgoulias V, Giles GG, Gilyazova IR, Glendon G, Goldberg MS, Goldgar DE, González-Neira A, Grenaker Alnæs GI, Grip M, Gronwald J, Grundy A, Guénel P, Haeberle L, Hahnen E, Haiman CA, Håkansson N, Hamann U, Hankinson SE, Harkness EF, Hart SN, He W, Hein A, Heyworth J, Hillemanns P, Hollestelle A, Hooning MJ, Hoover RN, Hopper JL, Howell A, Huang G, Humphreys K, Hunter DJ, Jakimovska M, Jakubowska A, Janni W, John EM, Johnson N, Jones ME, Jukkola-Vuorinen A, Jung A, Kaaks R, Kaczmarek K, Kataja V, Keeman R, Kerin MJ, Khusnutdinova E, Kiiski JI, Knight JA, Ko YD, Kosma VM, Koutros S, Kristensen VN, Krüger U, Kühl T, Lambrechts D, Le Marchand L, Lee E, Lejbkowicz F, Lilyquist J, Lindblom A, Lindström S, Lissowska J, Lo WY, Loibl S, Long J, Lubiński J, Lux MP, MacInnis RJ, Maishman T, Makalic E, Maleva Kostovska I, Mannermaa A, Manoukian S, Margolin S, Martens JWM, Martinez ME, Mavroudis D, McLean C, Meindl A, Menon U, Middha P, Miller N, Moreno F, Mulligan AM, Mulot C, Muñoz-Garzon VM, Neuhausen SL, Nevanlinna H, Neven P, Newman WG, Nielsen SF, Nordestgaard BG, Norman A, Offit K, Olson JE, Olsson H, Orr N, Pankratz VS, Park-Simon TW, Perez JIA, Pérez-Barrios C, Peterlongo P, Peto J, Pinchev M, Plaseska-Karanfilska D, Polley EC, Prentice R, Presneau N, Prokofyeva D, Purrington K, Pylkäs K, Rack B, Radice P, Rau-Murthy R, Rennert G, Rennert HS, Rhenius V, Robson M, Romero A, Ruddy KJ, Ruebner M, Saloustros E, Sandler DP, Sawyer EJ, Schmidt DF, Schmutzler RK, Schneeweiss A, Schoemaker MJ, Schumacher F, Schürmann P, Schwentner L, Scott C, Scott RJ, Seynaeve C, Shah M, Sherman ME, Shrubsole MJ, Shu XO, Slager S, Smeets A, Sohn C, Soucy P, Southey MC, Spinelli JJ, Stegmaier C, Stone J, Swerdlow AJ, Tamimi RM, Tapper WJ, Taylor JA, Terry MB, Thöne K, Tollenaar RAEM, Tomlinson I, Truong T, Tzardi M, Ulmer HU, Untch M, Vachon CM, van Veen EM, Vijai J, Weinberg CR, Wendt C, Whittemore AS, Wildiers H, Willett W, Winqvist R, Wolk A, Yang XR, Yannoukakos D, Zhang Y, Zheng W, Ziogas A, Dunning AM, Thompson DJ, Chenevix-Trench G, Chang-Claude J, Schmidt MK, Hall P, Milne RL, Pharoah PDP, Antoniou AC, Chatterjee N, Kraft P, García-Closas M, Simard J, and Easton DF

Subjects
Adult, Age Factors, Aged, Aged, 80 and over, Breast Neoplasms diagnosis, Breast Neoplasms prevention & control, Female, Humans, Medical History Taking, Middle Aged, Polymorphism, Single Nucleotide genetics, Receptors, Estrogen metabolism, Reproducibility of Results, Risk Assessment, Breast Neoplasms classification, Breast Neoplasms genetics, Genetic Predisposition to Disease, Multifactorial Inheritance genetics
Abstract

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

Published
2019
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7. Association analysis identifies 65 new breast cancer risk loci.

Author

Michailidou K, Lindström S, Dennis J, Beesley J, Hui S, Kar S, Lemaçon A, Soucy P, Glubb D, Rostamianfar A, Bolla MK, Wang Q, Tyrer J, Dicks E, Lee A, Wang Z, Allen J, Keeman R, Eilber U, French JD, Qing Chen X, Fachal L, McCue K, McCart Reed AE, Ghoussaini M, Carroll JS, Jiang X, Finucane H, Adams M, Adank MA, Ahsan H, Aittomäki K, Anton-Culver H, Antonenkova NN, Arndt V, Aronson KJ, Arun B, Auer PL, Bacot F, Barrdahl M, Baynes C, Beckmann MW, Behrens S, Benitez J, Bermisheva M, Bernstein L, Blomqvist C, Bogdanova NV, Bojesen SE, Bonanni B, Børresen-Dale AL, Brand JS, Brauch H, Brennan P, Brenner H, Brinton L, Broberg P, Brock IW, Broeks A, Brooks-Wilson A, Brucker SY, Brüning T, Burwinkel B, Butterbach K, Cai Q, Cai H, Caldés T, Canzian F, Carracedo A, Carter BD, Castelao JE, Chan TL, David Cheng TY, Seng Chia K, Choi JY, Christiansen H, Clarke CL, Collée M, Conroy DM, Cordina-Duverger E, Cornelissen S, Cox DG, Cox A, Cross SS, Cunningham JM, Czene K, Daly MB, Devilee P, Doheny KF, Dörk T, Dos-Santos-Silva I, Dumont M, Durcan L, Dwek M, Eccles DM, Ekici AB, Eliassen AH, Ellberg C, Elvira M, Engel C, Eriksson M, Fasching PA, Figueroa J, Flesch-Janys D, Fletcher O, Flyger H, Fritschi L, Gaborieau V, Gabrielson M, Gago-Dominguez M, Gao YT, Gapstur SM, García-Sáenz JA, Gaudet MM, Georgoulias V, Giles GG, Glendon G, Goldberg MS, Goldgar DE, González-Neira A, Grenaker Alnæs GI, Grip M, Gronwald J, Grundy A, Guénel P, Haeberle L, Hahnen E, Haiman CA, Håkansson N, Hamann U, Hamel N, Hankinson S, Harrington P, Hart SN, Hartikainen JM, Hartman M, Hein A, Heyworth J, Hicks B, Hillemanns P, Ho DN, Hollestelle A, Hooning MJ, Hoover RN, Hopper JL, Hou MF, Hsiung CN, Huang G, Humphreys K, Ishiguro J, Ito H, Iwasaki M, Iwata H, Jakubowska A, Janni W, John EM, Johnson N, Jones K, Jones M, Jukkola-Vuorinen A, Kaaks R, Kabisch M, Kaczmarek K, Kang D, Kasuga Y, Kerin MJ, Khan S, Khusnutdinova E, Kiiski JI, Kim SW, Knight JA, Kosma VM, Kristensen VN, Krüger U, Kwong A, Lambrechts D, Le Marchand L, Lee E, Lee MH, Lee JW, Neng Lee C, Lejbkowicz F, Li J, Lilyquist J, Lindblom A, Lissowska J, Lo WY, Loibl S, Long J, Lophatananon A, Lubinski J, Luccarini C, Lux MP, Ma ESK, MacInnis RJ, Maishman T, Makalic E, Malone KE, Kostovska IM, Mannermaa A, Manoukian S, Manson JE, Margolin S, Mariapun S, Martinez ME, Matsuo K, Mavroudis D, McKay J, McLean C, Meijers-Heijboer H, Meindl A, Menéndez P, Menon U, Meyer J, Miao H, Miller N, Taib NAM, Muir K, Mulligan AM, Mulot C, Neuhausen SL, Nevanlinna H, Neven P, Nielsen SF, Noh DY, Nordestgaard BG, Norman A, Olopade OI, Olson JE, Olsson H, Olswold C, Orr N, Pankratz VS, Park SK, Park-Simon TW, Lloyd R, Perez JIA, Peterlongo P, Peto J, Phillips KA, Pinchev M, Plaseska-Karanfilska D, Prentice R, Presneau N, Prokofyeva D, Pugh E, Pylkäs K, Rack B, Radice P, Rahman N, Rennert G, Rennert HS, Rhenius V, Romero A, Romm J, Ruddy KJ, Rüdiger T, Rudolph A, Ruebner M, Rutgers EJT, Saloustros E, Sandler DP, Sangrajrang S, Sawyer EJ, Schmidt DF, Schmutzler RK, Schneeweiss A, Schoemaker MJ, Schumacher F, Schürmann P, Scott RJ, Scott C, Seal S, Seynaeve C, Shah M, Sharma P, Shen CY, Sheng G, Sherman ME, Shrubsole MJ, Shu XO, Smeets A, Sohn C, Southey MC, Spinelli JJ, Stegmaier C, Stewart-Brown S, Stone J, Stram DO, Surowy H, Swerdlow A, Tamimi R, Taylor JA, Tengström M, Teo SH, Beth Terry M, Tessier DC, Thanasitthichai S, Thöne K, Tollenaar RAEM, Tomlinson I, Tong L, Torres D, Truong T, Tseng CC, Tsugane S, Ulmer HU, Ursin G, Untch M, Vachon C, van Asperen CJ, Van Den Berg D, van den Ouweland AMW, van der Kolk L, van der Luijt RB, Vincent D, Vollenweider J, Waisfisz Q, Wang-Gohrke S, Weinberg CR, Wendt C, Whittemore AS, Wildiers H, Willett W, Winqvist R, Wolk A, Wu AH, Xia L, Yamaji T, Yang XR, Har Yip C, Yoo KY, Yu JC, Zheng W, Zheng Y, Zhu B, Ziogas A, Ziv E, Lakhani SR, Antoniou AC, Droit A, Andrulis IL, Amos CI, Couch FJ, Pharoah PDP, Chang-Claude J, Hall P, Hunter DJ, Milne RL, García-Closas M, Schmidt MK, Chanock SJ, Dunning AM, Edwards SL, Bader GD, Chenevix-Trench G, Simard J, Kraft P, and Easton DF

Subjects
Asia ethnology, Asian People genetics, Binding Sites genetics, Breast Neoplasms diagnosis, Computer Simulation, Europe ethnology, Female, Humans, Multifactorial Inheritance genetics, Polymorphism, Single Nucleotide genetics, Regulatory Sequences, Nucleic Acid, Risk Assessment, Transcription Factors metabolism, White People genetics, Breast Neoplasms genetics, Genetic Loci, Genetic Predisposition to Disease genetics, Genome-Wide Association Study
Abstract

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10 -8 . The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

Published
2017
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8. DNA methylation signature (SAM40) identifies subgroups of the Luminal A breast cancer samples with distinct survival.

Author

Fleischer T, Klajic J, Aure MR, Louhimo R, Pladsen AV, Ottestad L, Touleimat N, Laakso M, Halvorsen AR, Grenaker Alnæs GI, Riis ML, Helland Å, Hautaniemi S, Lønning PE, Naume B, Børresen-Dale AL, Tost J, and Kristensen VN

Subjects
Breast Neoplasms pathology, Cluster Analysis, Epigenesis, Genetic, Epigenomics methods, Female, Gene Dosage, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Humans, Kaplan-Meier Estimate, Prognosis, Biomarkers, Tumor, Breast Neoplasms genetics, Breast Neoplasms mortality, DNA Methylation, Transcriptome
Abstract

Breast cancer patients with Luminal A disease generally have a good prognosis, but among this patient group are patients with good prognosis that are currently overtreated with adjuvant chemotherapy, and also patients that have a bad prognosis and should be given more aggressive treatment. There is no available method for subclassification of this patient group. Here we present a DNA methylation signature (SAM40) that segregates Luminal A patients based on prognosis, and identify one good prognosis group and one bad prognosis group. The prognostic impact of SAM40 was validated in four independent patient cohorts. Being able to subdivide the Luminal A patients may give the two-sided benefit of identifying one subgroup that may benefit from a more aggressive treatment than what is given today, and importantly, identifying a subgroup that may benefit from less treatment.

Published
2017
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9. Height and Breast Cancer Risk: Evidence From Prospective Studies and Mendelian Randomization.

Author

Zhang B, Shu XO, Delahanty RJ, Zeng C, Michailidou K, Bolla MK, Wang Q, Dennis J, Wen W, Long J, Li C, Dunning AM, Chang-Claude J, Shah M, Perkins BJ, Czene K, Darabi H, Eriksson M, Bojesen SE, Nordestgaard BG, Nielsen SF, Flyger H, Lambrechts D, Neven P, Wildiers H, Floris G, Schmidt MK, Rookus MA, van den Hurk K, de Kort WL, Couch FJ, Olson JE, Hallberg E, Vachon C, Rudolph A, Seibold P, Flesch-Janys D, Peto J, Dos-Santos-Silva I, Fletcher O, Johnson N, Nevanlinna H, Muranen TA, Aittomäki K, Blomqvist C, Li J, Humphreys K, Brand J, Guénel P, Truong T, Cordina-Duverger E, Menegaux F, Burwinkel B, Marme F, Yang R, Surowy H, Benitez J, Zamora MP, Perez JI, Cox A, Cross SS, Reed MW, Andrulis IL, Knight JA, Glendon G, Tchatchou S, Sawyer EJ, Tomlinson I, Kerin MJ, Miller N, Chenevix-Trench G, Haiman CA, Henderson BE, Schumacher F, Marchand LL, Lindblom A, Margolin S, Hooning MJ, Martens JW, Tilanus-Linthorst MM, Collée JM, Hopper JL, Southey MC, Tsimiklis H, Apicella C, Slager S, Toland AE, Ambrosone CB, Yannoukakos D, Giles GG, Milne RL, McLean C, Fasching PA, Haeberle L, Ekici AB, Beckmann MW, Brenner H, Dieffenbach AK, Arndt V, Stegmaier C, Swerdlow AJ, Ashworth A, Orr N, Jones M, Figueroa J, Garcia-Closas M, Brinton L, Lissowska J, Dumont M, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Grip M, Brauch H, Brüning T, Ko YD, Peterlongo P, Manoukian S, Bonanni B, Radice P, Bogdanova N, Antonenkova N, Dörk T, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Devilee P, Seynaeve C, Van Asperen CJ, Jakubowska A, Lubiński J, Jaworska-Bieniek K, Durda K, Hamann U, Torres D, Schmutzler RK, Neuhausen SL, Anton-Culver H, Kristensen VN, Grenaker Alnæs GI, Pierce BL, Kraft P, Peters U, Lindstrom S, Seminara D, Burgess S, Ahsan H, Whittemore AS, John EM, Gammon MD, Malone KE, Tessier DC, Vincent D, Bacot F, Luccarini C, Baynes C, Ahmed S, Maranian M, Healey CS, González-Neira A, Pita G, Alonso MR, Álvarez N, Herrero D, Pharoah PD, Simard J, Hall P, Hunter DJ, Easton DF, and Zheng W

Subjects
Evidence-Based Medicine, Female, Humans, Mendelian Randomization Analysis, Odds Ratio, Prospective Studies, Risk Factors, Body Height, Breast Neoplasms epidemiology
Abstract

Background: Epidemiological studies have linked adult height with breast cancer risk in women. However, the magnitude of the association, particularly by subtypes of breast cancer, has not been established. Furthermore, the mechanisms of the association remain unclear., Methods: We performed a meta-analysis to investigate associations between height and breast cancer risk using data from 159 prospective cohorts totaling 5216302 women, including 113178 events. In a consortium with individual-level data from 46325 case patients and 42482 control patients, we conducted a Mendelian randomization analysis using a genetic score that comprised 168 height-associated variants as an instrument. This association was further evaluated in a second consortium using summary statistics data from 16003 case patients and 41335 control patients., Results: The pooled relative risk of breast cancer was 1.17 (95% confidence interval [CI] = 1.15 to 1.19) per 10cm increase in height in the meta-analysis of prospective studies. In Mendelian randomization analysis, the odds ratio of breast cancer per 10cm increase in genetically predicted height was 1.22 (95% CI = 1.13 to 1.32) in the first consortium and 1.21 (95% CI = 1.05 to 1.39) in the second consortium. The association was found in both premenopausal and postmenopausal women but restricted to hormone receptor-positive breast cancer. Analyses of height-associated variants identified eight new loci associated with breast cancer risk after adjusting for multiple comparisons, including three loci at 1q21.2, DNAJC27, and CCDC91 at genome-wide significance level P < 5×10(-8)., Conclusions: Our study provides strong evidence that adult height is a risk factor for breast cancer in women and certain genetic factors and biological pathways affecting adult height have an important role in the etiology of breast cancer., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Published
2015
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10. Differential DNA methylation analysis of breast cancer reveals the impact of immune signaling in radiation therapy.

Author

Halvorsen AR, Helland A, Fleischer T, Haug KM, Grenaker Alnaes GI, Nebdal D, Syljuåsen RG, Touleimat N, Busato F, Tost J, Saetersdal AB, Børresen-Dale AL, Kristensen V, and Edvardsen H

Subjects
Breast Neoplasms immunology, Female, Gene Expression Profiling, Humans, Oligonucleotide Array Sequence Analysis, Real-Time Polymerase Chain Reaction, Signal Transduction, Tumor Cells, Cultured, Biomarkers, Tumor genetics, Breast metabolism, Breast Neoplasms genetics, Breast Neoplasms radiotherapy, DNA Methylation, Epigenomics
Abstract

Radiotherapy (RT) is a central treatment modality for breast cancer patients. The purpose of our study was to investigate the DNA methylation changes in tumors following RT, and to identify epigenetic markers predicting treatment outcome. Paired biopsies from patients with inoperable breast cancer were collected both before irradiation (n = 20) and after receiving 10-24 Gray (Gy) (n = 19). DNA methylation analysis was performed by using Illumina Infinium 27K arrays. Fourteen genes were selected for technical validation by pyrosequencing. Eighty-two differentially methylated genes were identified in irradiated (n = 11) versus nonirradiated (n = 19) samples (false discovery rate, FDR = 1.1%). Methylation levels in pathways belonging to the immune system were most altered after RT. Based on methylation levels before irradiation, a panel of five genes (H2AFY, CTSA, LTC4S, IL5RA and RB1) were significantly associated with clinical response (p = 0.041). Furthermore, the degree of methylation changes for 2,516 probes correlated with the given radiation dose. Within the 2,516 probes, an enrichment for pathways involved in cellular immune response, proliferation and apoptosis was identified (FDR < 5%). Here, we observed clear differences in methylation levels induced by radiation, some associated with response to treatment. Our study adds knowledge on the molecular mechanisms behind radiation response., (© 2014 The Authors. Published by Wiley Periodicals, Inc. on behalf of UICC.)

Published
2014
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11. SNP in TXNRD2 associated with radiation-induced fibrosis: a study of genetic variation in reactive oxygen species metabolism and signaling.

Author

Edvardsen H, Landmark-Høyvik H, Reinertsen KV, Zhao X, Grenaker-Alnæs GI, Nebdal D, Syvänen AC, Rødningen O, Alsner J, Overgaard J, Borresen-Dale AL, Fosså SD, and Kristensen VN

Subjects
Breast Neoplasms genetics, Dose Fractionation, Radiation, Female, Fibrosis, Humans, Pleura radiation effects, RNA, Messenger metabolism, Radiation Injuries metabolism, Radiation Pneumonitis genetics, Radiation Pneumonitis metabolism, Skin radiation effects, Survivors, Telangiectasis genetics, Breast Neoplasms radiotherapy, Genetic Variation genetics, Polymorphism, Single Nucleotide genetics, Radiation Injuries genetics, Reactive Oxygen Species metabolism, Thioredoxin Reductase 2 genetics
Abstract

Purpose: The aim of the study was to identify noninvasive markers of treatment-induced side effects. Reactive oxygen species (ROS) are generated after irradiation, and genetic variation in genes related to ROS metabolism might influence the level of radiation-induced adverse effects (AEs)., Methods and Materials: 92 breast cancer (BC) survivors previously treated with hypofractionated radiation therapy were assessed for the AEs subcutaneous atrophy and fibrosis, costal fractures, lung fibrosis, pleural thickening, and telangiectasias (median follow-up time 17.1 years). Single-nucleotide polymorphisms (SNPs) in 203 genes were analyzed for association to AE grade. SNPs associated with subcutaneous fibrosis were validated in an independent BC survivor material (n=283). The influence of the studied genetic variation on messenger ribonucleic acid (mRNA) expression level of 18 genes previously associated with fibrosis was assessed in fibroblast cell lines from BC patients., Results: Subcutaneous fibrosis and atrophy had the highest correlation (r=0.76) of all assessed AEs. The nonsynonymous SNP rs1139793 in TXNRD2 was associated with grade of subcutaneous fibrosis, the reference T-allele being more prevalent in the group experiencing severe levels of fibrosis. This was confirmed in another sample cohort of 283 BC survivors, and rs1139793 was found significantly associated with mRNA expression level of TXNRD2 in blood. Genetic variation in 24 ROS-related genes, including EGFR, CENPE, APEX1, and GSTP1, was associated with mRNA expression of 14 genes previously linked to fibrosis (P≤.005)., Conclusion: Development of subcutaneous fibrosis can be associated with genetic variation in the mitochondrial enzyme TXNRD2, critically involved in removal of ROS, and maintenance of the intracellular redox balance., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Published
2013
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12. Fatigued breast cancer survivors and gene polymorphisms in the inflammatory pathway.

Author

Reinertsen KV, Grenaker Alnæs GI, Landmark-Høyvik H, Loge JH, Wist E, Kristensen VN, Fosså SD, and Edvardsen H

Subjects
Adult, Aged, Breast Neoplasms blood, Breast Neoplasms complications, C-Reactive Protein genetics, C-Reactive Protein metabolism, Depression blood, Depression complications, Depression genetics, Fatigue blood, Fatigue complications, Female, Follow-Up Studies, Genetic Predisposition to Disease, Genotype, Humans, Inflammation blood, Inflammation complications, Interleukin-1beta blood, Interleukin-1beta genetics, Interleukin-6 blood, Interleukin-6 genetics, Middle Aged, RNA, Messenger genetics, Receptors, Interleukin-6 blood, Receptors, Interleukin-6 genetics, Surveys and Questionnaires, Survivors, Breast Neoplasms genetics, Fatigue genetics, Inflammation genetics, Polymorphism, Single Nucleotide
Abstract

Chronic fatigue (CF) in breast cancer survivors (BCSs) has been associated with increased serum C-reactive protein-levels (CRP), pro-inflammatory cytokines and cytokine gene single nucleotide polymorphisms (SNPs). Still, there are few studies on these topics, and due to small study-cohorts the possibility to adjust for other conditions related to inflammatory processes, e.g. depression, has been limited. In 302 BCSs, examined approximately four years after treatment for breast cancer stage II/III, data on high sensitivity (hs)CRP, leukocytes and mRNA interleukin (IL)1β and IL6R expression, depression and chronic fatigue were available. Three years thereafter, 236 BCSs were re-examined. The associations between fatigue and SNPs in inflammation-related genes; IL1β (rs16944), IL6 (rs1800795), IL6receptor (rs4129267, rs4845617, rs2228145), CRP (rs2794521, rs3091244) were investigated, together with the relations between SNPs in IL6R,IL1β and CRP genes and mRNA blood expression levels of IL6R and IL1β and serum hsCRP-levels, respectively. All analyses were repeated after exclusion of depressed individuals and separating BCSs with persistent fatigue from never-fatigued individuals. Even after exclusion of depressed individuals neither the SNPs nor the mRNA IL1β and IL6R expression levels were associated with chronic or persistent fatigue. In the subset of persistent fatigued and never-fatigued individuals the CRP SNP (rs3091244) was associated with hsCRP level (p=0.02). IL1β and IL6R mRNA expression levels were not related to the IL1β and IL6R genotypes. In a large cohort of BCSs the investigated SNPs in inflammation-related genes were not associated with fatigue, though subset analyses indicated an association between the CRP SNP (rs3091244) and serum hsCRP., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Published
2011
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13. Germline glutathione S-transferase variants in breast cancer: relation to diagnosis and cutaneous long-term adverse effects after two fractionation patterns of radiotherapy.

Author

Edvardsen H, Kristensen VN, Grenaker Alnaes GI, Bøhn M, Erikstein B, Helland A, Børresen-Dale AL, and Fosså SD

Subjects
Adult, Aged, Breast Neoplasms genetics, Breast Neoplasms radiotherapy, Breast Neoplasms surgery, Case-Control Studies, Dose Fractionation, Radiation, Humans, Middle Aged, Neoplastic Stem Cells enzymology, Neoplastic Stem Cells radiation effects, Polymerase Chain Reaction methods, Radiotherapy, Adjuvant adverse effects, Breast Neoplasms enzymology, Glutathione S-Transferase pi genetics, Glutathione Transferase genetics, Polymorphism, Genetic
Abstract

Purpose: To explore whether certain glutathione S-transferase (GST) polymorphisms are associated with an increased risk of breast cancer or the level of radiation-induced adverse effects after two fractionation patterns of adjuvant radiotherapy., Methods and Materials: The prevalence of germline polymorphic variants in GSTM1, GSTP1, and GSTT1 was determined in 272 breast cancer patients and compared with that in a control group of 270 women from the general population with no known history of breast cancer. The genetic variants were determined using multiplex polymerase chain reaction followed by restriction enzyme fragment analysis. In 253 of the patients surveyed for radiotherapy-induced side effects after a median observation time of 13.7 years (range, 7-22.8 years), the genotypes were related to the long-term effects observed after two fractionation patterns (treatment A, 4.3 Gy in 10 fractions for 156 patients; and treatment B, 2.5 Gy in 20 fractions for 97; both administered within a 5-week period)., Results: None of the GST polymorphisms conferred an increased risk of breast cancer, either alone or in combination. Compared with treatment B, treatment A was followed by an increased level of moderate to severe radiation-induced side effects for all the endpoints studied (i.e., degree of telangiectasia, subcutaneous fibrosis and atrophy, lung fibrosis, costal fractures, and pleural thickening; p <0.001 for all endpoints). A significant association was found between the level of pleural thickening and the GSTP1 Ile105Val variant., Conclusion: The results of this study have illustrated the impact of hypofractionation on the level of adverse effects and indicated that the specific alleles of GSTP1, M1, and T1 studied here may be significant in determining the level of adverse effects after radiotherapy.

Published
2007
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