Search

Your search keyword '"Pharoah PD"' showing total 514 results
Start Over Author "Pharoah PD"

Refine your results

514 results on '"Pharoah PD"'

1. Assessing interactions between the associations of common genetic susceptibility variants, reproductive history and body mass index with breast cancer risk in the breast cancer association consortium: A combined case-control study

Author

Milne, RL, Gaudet, MM, Spurdle, AB, Fasching, PA, Couch, FJ, Benítez, J, Arias Pérez, JI, Zamora, MP, Malats, N, dos Santos Silva, I, Gibson, LJ, Fletcher, O, Johnson, N, Anton-Culver, H, Ziogas, A, Figueroa, J, Brinton, L, Sherman, ME, Lissowska, J, Hopper, JL, Dite, GS, Apicella, C, Southey, MC, Sigurdson, AJ, Linet, MS, Schonfeld, SJ, Freedman, DM, Mannermaa, A, Kosma, VM, Kataja, V, Auvinen, P, Andrulis, IL, Glendon, G, Knight, JA, Weerasooriya, N, Cox, A, Reed, MWR, Cross, SS, Dunning, AM, Ahmed, S, Shah, M, Brauch, H, Ko, YD, Brüning, T, Lambrechts, D, Reumers, J, Smeets, A, Wang-Gohrke, S, Hall, P, Czene, K, Liu, J, Irwanto, AK, Chenevix-Trench, G, Holland, H, Fab, KC, Giles, GG, Baglietto, L, Severi, G, Bojensen, SE, Nordestgaard, BG, Flyger, H, John, EM, West, DW, Whittemore, AS, Vachon, C, Olson, JE, Fredericksen, Z, Kosel, M, Hein, R, Vrieling, A, Flesch-Janys, D, Heinz, J, Beckmann, MW, Heusinger, K, Ekici, AB, Haeberle, L, Humphreys, MK, Morrison, J, Easton, DF, and Pharoah, PD

Abstract

Introduction: Several common breast cancer genetic susceptibility variants have recently been identified. We aimed to determine how these variants combine with a subset of other known risk factors to influence breast cancer risk in white women of European ancestry using case-control studies participating in the Breast Cancer Association Consortium.Methods: We evaluated two-way interactions between each of age at menarche, ever having had a live birth, number of live births, age at first birth and body mass index (BMI) and each of 12 single nucleotide polymorphisms (SNPs) (10q26-rs2981582 (FGFR2), 8q24-rs13281615, 11p15-rs3817198 (LSP1), 5q11-rs889312 (MAP3K1), 16q12-rs3803662 (TOX3), 2q35-rs13387042, 5p12-rs10941679 (MRPS30), 17q23-rs6504950 (COX11), 3p24-rs4973768 (SLC4A7), CASP8-rs17468277, TGFB1-rs1982073 and ESR1-rs3020314). Interactions were tested for by fitting logistic regression models including per-allele and linear trend main effects for SNPs and risk factors, respectively, and single-parameter interaction terms for linear departure from independent multiplicative effects.Results: These analyses were applied to data for up to 26,349 invasive breast cancer cases and up to 32,208 controls from 21 case-control studies. No statistical evidence of interaction was observed beyond that expected by chance. Analyses were repeated using data from 11 population-based studies, and results were very similar.Conclusions: The relative risks for breast cancer associated with the common susceptibility variants identified to date do not appear to vary across women with different reproductive histories or body mass index (BMI). The assumption of multiplicative combined effects for these established genetic and other risk factors in risk prediction models appears justified. © 2010 Milne et al.; licensee BioMed Central Ltd.

Published
2010

2. Evaluation of candidate stromal epithelial cross-talk genes identifies association between risk of serous ovarian cancer and TERT, a cancer susceptibility "hot-spot".

Author

Johnatty, SE, Beesley, J, Chen, X, Macgregor, S, Duffy, DL, Spurdle, AB, deFazio, A, Gava, N, Webb, PM, Rossing, MA, Doherty, JA, Goodman, MT, Lurie, G, Thompson, PJ, Wilkens, LR, Ness, RB, Moysich, KB, Chang-Claude, J, Wang-Gohrke, S, Cramer, DW, Terry, KL, Hankinson, SE, Tworoger, SS, Garcia-Closas, M, Yang, H, Lissowska, J, Chanock, SJ, Pharoah, PD, Song, H, Whitemore, AS, Pearce, CL, Stram, DO, Wu, AH, Pike, MC, Gayther, SA, Ramus, SJ, Menon, U, Gentry-Maharaj, A, Anton-Culver, H, Ziogas, A, Hogdall, E, Kjaer, SK, Hogdall, C, Berchuck, A, Schildkraut, JM, Iversen, ES, Moorman, PG, Phelan, CM, Sellers, TA, Cunningham, JM, Vierkant, RA, Rider, DN, Goode, EL, Haviv, I, Chenevix-Trench, G, Ovarian, CAC, Australian, OCSG, and Australian, CSOC

Abstract

We hypothesized that variants in genes expressed as a consequence of interactions between ovarian cancer cells and the host micro-environment could contribute to cancer susceptibility. We therefore used a two-stage approach to evaluate common single nucleotide polymorphisms (SNPs) in 173 genes involved in stromal epithelial interactions in the Ovarian Cancer Association Consortium (OCAC). In the discovery stage, cases with epithelial ovarian cancer (n=675) and controls (n=1,162) were genotyped at 1,536 SNPs using an Illumina GoldenGate assay. Based on Positive Predictive Value estimates, three SNPs-PODXL rs1013368, ITGA6 rs13027811, and MMP3 rs522616-were selected for replication using TaqMan genotyping in up to 3,059 serous invasive cases and 8,905 controls from 16 OCAC case-control studies. An additional 18 SNPs with Pper-alleleor=0.5). However genotypes at TERT rs7726159 were associated with ovarian cancer risk in the smaller, five-study replication study (Pper-allele=0.03). Combined analysis of the discovery and replication sets for this TERT SNP showed an increased risk of serous ovarian cancer among non-Hispanic whites [adj. ORper-allele 1.14 (1.04-1.24) p=0.003]. Our study adds to the growing evidence that, like the 8q24 locus, the telomerase reverse transcriptase locus at 5p15.33, is a general cancer susceptibility locus.

Published
2010

3. COGENT (COlorectal cancer GENeTics): an international consortium to study the role of polymorphic variation on the risk of colorectal cancer

Author

Tomlinson, IPM, Dunlop, M, Campbell, H, Zanke, B, Gallinger, S, Hudson, T, Koessler, T, Pharoah, PD, Niittymäkix, I, Tuupanenx, S, Aaltonen, LA, Hemminki, K, Lindblom, A, Försti, A, Sieber, O, Lipton, L, van Wezel, T, Morreau, H, Wijnen, JT, Devilee, P, Matsuda, K, Nakamura, Y, Castellví-Bel, S, Ruiz-Ponte, C, Castells, A, Carracedo, A, Ho, JWC, Sham, P, Hofstra, RMW, Vodicka, P, Brenner, H, Hampe, J, Schafmayer, C, Tepel, J, Schreiber, S, Völzke, H, Lerch, MM, Schmidt, CA, Buch, S, Moreno, V, Villanueva, CM, Peterlongo, P, Radice, P, Echeverry, MM, Velez, A, Carvajal-Carmona, L, Scott, R, Penegar, S, Broderick, P, Tenesa, A, and Houlston, RS

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Digestive Diseases, Genetics, Colo-Rectal Cancer, Cancer, Prevention, Aetiology, 2.1 Biological and endogenous factors, Colorectal Neoplasms, Genetic Predisposition to Disease, Humans, Penetrance, Polymorphism, Genetic, Prognosis, Risk, Risk Factors, colorectal cancer, association, polymorphism, Public Health and Health Services, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

It is now recognised that a part of the inherited risk of colorectal cancer (CRC) can be explained by the co-inheritance of low-penetrance genetic variants. The accumulated experience to date in identifying these variants has served to highlight difficulties in conducting statistically and methodologically rigorous studies and follow-up analyses. The COGENT (COlorectal cancer GENeTics) consortium includes 20 research groups in Europe, Australia, the Americas, China and Japan. The overarching goal of COGENT is to identify and characterise low-penetrance susceptibility variants for CRC through association-based analyses. In this study, we review the rationale for identifying low-penetrance variants for CRC and our proposed strategy for establishing COGENT.

Published
2010

4. Meta-analysis of the association between emphysematous change on thoracic computerized tomography scan and recurrent pneumothorax

Author

Girish, M, Pharoah, PD, Marciniak, SJ, Marciniak, SJ [0000-0001-8472-7183], and Apollo - University of Cambridge Repository

Subjects
Lung Diseases, Recurrence, Thoracic Surgery, Video-Assisted, Humans, Pneumothorax, Tomography, X-Ray Computed, Retrospective Studies
Abstract

OBJECTIVES: At least a third of patients go on to suffer a recurrence following a first spontaneous pneumothorax. Surgical intervention reduces the risk of recurrence and has been advocated as a primary treatment for pneumothorax. But surgery exposes patients to the risks of anaesthesia and in some cases can cause chronic pain. Risk stratification of patients to identify those most at risk of recurrence would help direct the most appropriate patients to early intervention. Many studies have addressed the role of thoracic computerized tomography (CT) in identifying those individuals at increased risk of recurrence, but a consensus is lacking. AIM: Our objective was to clarify whether CT provides valuable prognostic information for recurrent pneumothorax. DESIGN: Meta-analysis. METHODS: We conducted an exhaustive search of the literature for thoracic CT imaging and pneumothorax, and then performed a meta-analysis using a random effects model to estimate the common odds ratio and standard error. RESULTS: Here, we show by meta-analysis of data from 2475 individuals that emphysematous change on CT scan is associated with a significant increased odds ratio for recurrent pneumothorax ipsilateral to the radiological abnormality (odds ratio 2.49, 95% confidence interval 1.51-4.13). CONCLUSIONS: The association holds true for primary spontaneous pneumothorax when considering emphysematous changes including blebs and bullae. Features, such as bullae at the azygoesophageal recess or increased Goddard score similarly predicted recurrent secondary pneumothorax, as shown by subgroup analysis. Our meta-analysis suggests that CT scanning has value in risk stratifying patients considering surgery for pneumothorax.

Published
2022

5. Rare Copy Number Variants (CNVs) and Breast Cancer Risk

Author

Vessela N. Kristensen, Abctb Investigators, Elinor J. Sawyer, Jose Esteban Castelao, Christine L. Clarke, Argyrios Ziogas, Natalia Bogdanova, Pascal Guénel, Lin Fritschi, Marina Bermisheva, Alicja Wolk, Anthony J. Swerdlow, Graham G. Giles, Antoinette Hollestelle, Camilla Wendt, Stig E. Bojesen, Reiner Hoppe, Laure Dossus, Marike Gabrielson, Doug Easton, Dimitrios Mavroudis, Rulla M. Tamimi, Manuela Gago-Dominguez, Roger L. Milne, Kristan J. Aronson, Kyriaki Michailidou, Logan C. Walker, Siranoush Manoukian, Taru A. Muranen, Melissa A. Troester, Celine M. Vachon, Javier Benítez, Alicja Lukomska, Martha S. Linet, Heli Nevanlinna, Marjanka K. Schmidt, Thilo Dörk, Kubelka-Sabit K, Rita K. Schmutzler, Antonenkova Nn, Pharoah Pd, Anna González-Neira, H Brenner, Dijana Plaseska-Karanfilska, Fergus J. Couch, Ian Tomlinson, Thérèse Truong, Sabine Behrens, A. H. Eliassen, Peter A. Fasching, Cox A, P. Kraft, Wei Zheng, Rudolph Kaaks, Tyrer Jp, Renske Keeman, Rachel A. Murphy, Georgia Chenevix-Trench, Dale P. Sandler, Olivia Fletcher, Leila Dorling, Sara Margolin, Thomas U. Ahearn, Agnes Jager, Christopher A. Haiman, Lauren R. Teras, Tjoung-Won Park-Simon, James V. Lacey, Per Hall, Matthias W. Beckmann, Jacques Simard, Michael Jones, Collee Jm, D G Evans, Shibli R, Investigators k, Katri Pylkäs, Xiaohong R. Yang, Esther M. John, Eric Hahnen, D Lambrechts, Peter Devilee, Kamila Czene, Jonine D. Figueroa, Alison M. Dunning, Hoda Anton-Culver, Stella Koutros, Melissa C. Southey, Kosma, Joe Dennis, Yon-Dschun Ko, Mary Beth Terry, Jenny Chang-Claude, Anthony Howell, Beane Freeman Le, Charles M. Perou, Qinghua Wang, Henrik Flyger, Nichola Johnson, John L. Hopper, Paolo Peterlongo, Simon S. Cross, Jack A. Taylor, Audrey Y. Jung, Robert Winqvist, Håkan Olsson, Arndt, Irene L. Andrulis, Nicole L. Larson, Penny Soucy, Anna Jakubowska, Cari M. Kitahara, Janet E. Olson, Emmanouil Saloustros, Elza Khusnutdinova, Manjeet K. Bolla, M Garcia-Closas, Ann Smeets, Mikael Eriksson, Allison W. Kurian, Gadi Rennert, and Arto Mannermaa

Subjects
Genetics, 0303 health sciences, Cancer, Disease, Biology, medicine.disease, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, Breast cancer, 030220 oncology & carcinogenesis, Gene duplication, medicine, Human genome, Copy-number variation, Gene, CHEK2, 030304 developmental biology
Abstract

BackgroundCopy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data.ResultsGene burden tests detected the strongest association for deletions in BRCA1 (P= 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P= 0.0008), ATM (P= 0.002) and BRCA2 (P= 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci.ConclusionsThis is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance.

Published
2021

6. Multi-omic machine learning predictor of breast cancer therapy response

Author

Sammut, S-J, Crispin-Ortuzar, M, Chin, S-F, Provenzano, E, Bardwell, HA, Ma, W, Cope, W, Dariush, A, Dawson, S-J, Abraham, JE, Dunn, J, Hiller, L, Thomas, J, Cameron, DA, Bartlett, JMS, Hayward, L, Pharoah, PD, Markowetz, F, Rueda, OM, Earl, HM, Caldas, C, Sammut, S-J, Crispin-Ortuzar, M, Chin, S-F, Provenzano, E, Bardwell, HA, Ma, W, Cope, W, Dariush, A, Dawson, S-J, Abraham, JE, Dunn, J, Hiller, L, Thomas, J, Cameron, DA, Bartlett, JMS, Hayward, L, Pharoah, PD, Markowetz, F, Rueda, OM, Earl, HM, and Caldas, C

Abstract

Breast cancers are complex ecosystems of malignant cells and the tumour microenvironment1. The composition of these tumour ecosystems and interactions within them contribute to responses to cytotoxic therapy2. Efforts to build response predictors have not incorporated this knowledge. We collected clinical, digital pathology, genomic and transcriptomic profiles of pre-treatment biopsies of breast tumours from 168 patients treated with chemotherapy with or without HER2 (encoded by ERBB2)-targeted therapy before surgery. Pathology end points (complete response or residual disease) at surgery3 were then correlated with multi-omic features in these diagnostic biopsies. Here we show that response to treatment is modulated by the pre-treated tumour ecosystem, and its multi-omics landscape can be integrated in predictive models using machine learning. The degree of residual disease following therapy is monotonically associated with pre-therapy features, including tumour mutational and copy number landscapes, tumour proliferation, immune infiltration and T cell dysfunction and exclusion. Combining these features into a multi-omic machine learning model predicted a pathological complete response in an external validation cohort (75 patients) with an area under the curve of 0.87. In conclusion, response to therapy is determined by the baseline characteristics of the totality of the tumour ecosystem captured through data integration and machine learning. This approach could be used to develop predictors for other cancers.

Published
2021

7. CYP3A7*1C allele: linking premenopausal oestrone and progesterone levels with risk of hormone receptor-positive breast cancers

Author

Johnson, N, Maguire, S, Morra, A, Kapoor, PM, Tomczyk, K, Jones, ME, Schoemaker, MJ, Gilham, C, Bolla, MK, Wang, Q, Dennis, J, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Arndt, V, Aronson, KJ, Augustinsson, A, Baynes, C, Freeman, LEB, Beckmann, MW, Benitez, J, Bermisheva, M, Blomqvist, C, Boeckx, B, Bogdanova, NV, Bojesen, SE, Brauch, H, Brenner, H, Burwinkel, B, Campa, D, Canzian, F, Castelao, JE, Chanock, SJ, Chenevix-Trench, G, Clarke, CL, Conroy, D M, Couch, FJ, Cox, A, Cross, SS, Czene, K, Dork, T, Eliassen, A H, Engel, C, Evans, DGR, Fasching, PA, Figueroa, J, Floris, G, Flyger, H, Gago-Dominguez, M, Gapstur, SM, Garcia-Closas, M, Gaudet, MM, Giles, GG, Goldberg, MS, Gonzalez-Neira, A, Guenel, P, Hahnen, E, Haiman, CA, Hakansson, N, Hall, P, Hamann, U, Harrington, PA, Hart, S N, Hooning, Maartje, Hopper, JL, Howell, A, Hunter, DJ, Jager, Agnes, Jakubowska, A, John, EM, Kaaks, R, Keeman, R, Khusnutdinova, E, Kitahara, CM, Kosma, VM, Koutros, S, Kraft, P, Kristensen, VN, Kurian, AW, Lambrechts, D, Le Marchand, L, Linet, M, Lubinski, J, Mannermaa, A, Manoukian, S, Margolin, S, Martens, John, Mavroudis, D, Mayes, R, Meindl, A, Milne, RL, Neuhausen, SL, Nevanlinna, H, Newman, WG, Nielsen, SF, Nordestgaard, BG, Obi, N, Olshan, AF, Olson, JE, Olsson, H, Orban, E, Park-Simon, TW, Peterlongo, P, Plaseska-Karanfilska, D, Pylkas, K, Rennert, G, Rennert, HS, Ruddy, KJ, Saloustros, E, Sandler, DP, Sawyer, EJ, Schmutzler, RK, Scott, C, Shu, XO, Simard, J, Smichkoska, S, Sohn, C, Southey, MC, Spinelli, JJ, Stone, J, Tamimi, RM, Taylor, JA, Tollenaar, R, Tomlinson, I, Troester, MA, Truong, T, Vachon, CM, van Veen, EM, Wang, SSH, Weinberg, CR, Wendt, C, Wildiers, H, Winqvist, R, Wolk, A, Zheng, W, Ziogas, A, Dunning, AM, Pharoah, PD, Easton, DF, Howie, AF, Peto, J, dos-Santos-Silva, I, Swerdlow, AJ, Chang-Claude, J, Schmidt, MK (Marjanka), Orr, N, Fletcher, O, Johnson, N, Maguire, S, Morra, A, Kapoor, PM, Tomczyk, K, Jones, ME, Schoemaker, MJ, Gilham, C, Bolla, MK, Wang, Q, Dennis, J, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Arndt, V, Aronson, KJ, Augustinsson, A, Baynes, C, Freeman, LEB, Beckmann, MW, Benitez, J, Bermisheva, M, Blomqvist, C, Boeckx, B, Bogdanova, NV, Bojesen, SE, Brauch, H, Brenner, H, Burwinkel, B, Campa, D, Canzian, F, Castelao, JE, Chanock, SJ, Chenevix-Trench, G, Clarke, CL, Conroy, D M, Couch, FJ, Cox, A, Cross, SS, Czene, K, Dork, T, Eliassen, A H, Engel, C, Evans, DGR, Fasching, PA, Figueroa, J, Floris, G, Flyger, H, Gago-Dominguez, M, Gapstur, SM, Garcia-Closas, M, Gaudet, MM, Giles, GG, Goldberg, MS, Gonzalez-Neira, A, Guenel, P, Hahnen, E, Haiman, CA, Hakansson, N, Hall, P, Hamann, U, Harrington, PA, Hart, S N, Hooning, Maartje, Hopper, JL, Howell, A, Hunter, DJ, Jager, Agnes, Jakubowska, A, John, EM, Kaaks, R, Keeman, R, Khusnutdinova, E, Kitahara, CM, Kosma, VM, Koutros, S, Kraft, P, Kristensen, VN, Kurian, AW, Lambrechts, D, Le Marchand, L, Linet, M, Lubinski, J, Mannermaa, A, Manoukian, S, Margolin, S, Martens, John, Mavroudis, D, Mayes, R, Meindl, A, Milne, RL, Neuhausen, SL, Nevanlinna, H, Newman, WG, Nielsen, SF, Nordestgaard, BG, Obi, N, Olshan, AF, Olson, JE, Olsson, H, Orban, E, Park-Simon, TW, Peterlongo, P, Plaseska-Karanfilska, D, Pylkas, K, Rennert, G, Rennert, HS, Ruddy, KJ, Saloustros, E, Sandler, DP, Sawyer, EJ, Schmutzler, RK, Scott, C, Shu, XO, Simard, J, Smichkoska, S, Sohn, C, Southey, MC, Spinelli, JJ, Stone, J, Tamimi, RM, Taylor, JA, Tollenaar, R, Tomlinson, I, Troester, MA, Truong, T, Vachon, CM, van Veen, EM, Wang, SSH, Weinberg, CR, Wendt, C, Wildiers, H, Winqvist, R, Wolk, A, Zheng, W, Ziogas, A, Dunning, AM, Pharoah, PD, Easton, DF, Howie, AF, Peto, J, dos-Santos-Silva, I, Swerdlow, AJ, Chang-Claude, J, Schmidt, MK (Marjanka), Orr, N, and Fletcher, O

Abstract

Background: Epidemiological studies provide strong evidence for a role of endogenous sex hormones in the aetiology of breast cancer. The aim of this analysis was to identify genetic variants that are associated with urinary sex-hormone levels and breast cancer risk. Methods: We carried out a genome-wide association study of urinary oestrone-3-glucuronide and pregnanediol-3-glucuronide levels in 560 premenopausal women, with additional analysis of progesterone levels in 298 premenopausal women. To test for the association with breast cancer risk, we carried out follow-up genotyping in 90,916 cases and 89,893 controls from the Breast Cancer Association Consortium. All women were of European ancestry. Results: For pregnanediol-3-glucuronide, there were no genome-wide significant associations; for oestrone-3-glucuronide, we identified a single peak mapping to the CYP3A locus, annotated by rs45446698. The minor rs45446698-C allele was associated with lower oestrone-3-glucuronide (−49.2%, 95% CI −56.1% to −41.1%, P = 3.1 × 10–18); in follow-up analyses, rs45446698-C was also associated with lower progesterone (−26.7%, 95% CI −39.4% to −11.6%, P = 0.001) and reduced risk of oestrogen and progesterone receptor-positive breast cancer (OR = 0.86, 95% CI 0.82–0.91, P = 6.9 × 10–8). Conclusions: The CYP3A7*1C allele is associated with reduced risk of hormone receptor-positive breast cancer possibly mediated via an effect on the metabolism of endogenous sex hormones in premenopausal women.

Published
2021

8. Collateral damage: the impact on outcomes from cancer surgery of the COVID-19 pandemic

Author

Alice Garrett, Chey Loveday, Amit Sud, John Broggio, Y-E. Suh, James Larkin, Bethany Torr, Matthew Williams, Stephen Scott, Christopher Abbosh, Michael Jones, David Nicol, Georgios Lyratzopoulos, Stephen A. Boyce, J.M. Handy, F. Gronthoud, Nadia Yousaf, P. Ward, Clare Turnbull, Charles Swanton, Richard S. Houlston, Pharoah Pd, Shaman Jhanji, Pharoah, Paul [0000-0001-8494-732X], and Apollo - University of Cambridge Repository

Subjects
0301 basic medicine, Male, CYSTECTOMY, medicine.medical_treatment, MUSCLE INVASION, 0302 clinical medicine, Neoplasms, Pandemic, Health care, diagnostics, Aged, 80 and over, Hazard ratio, Hematology, Middle Aged, TIME, Hospitalization, Treatment Outcome, 030220 oncology & carcinogenesis, oncology, Female, Coronavirus Infections, Life Sciences & Biomedicine, Adult, medicine.medical_specialty, delay, Pneumonia, Viral, DIAGNOSIS, survival, Article, Time-to-Treatment, Cystectomy, 03 medical and health sciences, Betacoronavirus, Breast cancer, medicine, BREAST-CANCER, Humans, 1112 Oncology and Carcinogenesis, Oncology & Carcinogenesis, Pandemics, Aged, Science & Technology, business.industry, SARS-CoV-2, Public health, Cancer, COVID-19, medicine.disease, 030104 developmental biology, Emergency medicine, Observational study, business
Abstract

Background Cancer diagnostics and surgery have been disrupted by the response of healthcare services to the COVID-19 pandemic. Progression of cancers during delay will impact on patient long-term survival. Methods We generated per-day hazard ratios of cancer progression from observational studies and applied these to age-specific, stage-specific cancer survival for England 2013-2017. We modelled per-patient delay of three months and six months and periods of disruption of one year and two years. Using healthcare resource costing, we contextualise attributable lives saved and life-years gained from cancer surgery to equivalent volumes of COVID-19 hospitalisations. Findings Per year, 94,912 resections for major cancers result in 80,406 long-term survivors and 1,717,051 life years gained. Per-patient delay of three/six months would cause attributable death of 4,755/10,760 of these individuals with loss of 92,214/208,275 life-years. For cancer surgery, average life-years gained (LYGs) per patient are 18.1 under standard conditions and 17.1/15.9 with a delay of three/six months (an average loss of 0.97/2.19 LYG per patient). Taking into account units of healthcare resource (HCRU), surgery results on average per patient in 2.25 resource-adjusted life-years gained (RALYGs) under standard conditions and 2.12/1.97 RALYGs following delay of three/six months. For 94,912 hospital COVID-19 admissions, there are 482,022 LYGs requiring of 1,052,949 HCRUs. Hospitalisation of community-acquired COVID-19 patients yields on average per patient 5.08 LYG and 0.46 RALYGs. Interpretation Modest delays in surgery for cancer incur significant impact on survival. Delay of three/six months in surgery for incident cancers would mitigate 19%/43% of life-years gained by hospitalisation of an equivalent volume of admissions for community-acquired COVID-19. This rises to 26%/59% when considering resource-adjusted life-years gained. To avoid a downstream public health crisis of avoidable cancer deaths, cancer diagnostic and surgical pathways must be maintained at normal throughput, with rapid attention to any backlog already accrued., Highlights • Lockdown and re-deployment due to the COVID-19 pandemic is causing significant disruption to cancer diagnosis and management. • 3-month delay to surgery across all Stage 1-3 cancers is estimated to cause >4,700 attributable deaths per year in England. • The impact on life years lost of 3-6 month to surgery for Stage 1-3 disease varies widely between tumour types. • Strategic prioritisation of patients for diagnostics and surgery has potential to mitigate deaths attributable to delays. • The resource-adjusted benefit in avoiding delay in cancer management compares favourably to admission for COVID-19 infection.

Published
2020
Full Text
View/download PDF

9. Association Between Levels of Hormones and Risk of Esophageal Adenocarcinoma and Barrett's Esophagus

Author

Xie, S-H, Fang, R, Huang, M, Dai, J, Thrift, AP, Anderson, LA, Chow, W-H, Bernstein, L, Gammon, MD, Risch, HA, Shaheen, NJ, Reid, BJ, Wu, AH, Iyer, PG, Liu, G, Corley, DA, Whiteman, DC, Caldas, C, Pharoah, PD, Hardie, LJ, Fitzgerald, RC, Shen, H, Vaughan, TL, and Lagergren, J

Abstract

Background & Aims Esophageal adenocarcinoma (EAC) occurs most frequently in men. We performed a Mendelian randomization analysis to investigate whether genetic factors that regulate levels of sex hormones associated with risk of EAC or Barrett’s esophagus (BE). Methods We conducted a Mendelian randomization analysis using data from patients with EAC (n=2488) or BE (n=3247) and control participants (n=2127), included in international consortia of genome-wide association studies in Australia, Europe, and North America. Genetic risk scores or single nucleotide variants were used as instrumental variables for 9 specific sex hormones. Logistic regression provided odds ratios (ORs) with 95% CIs. Results Higher genetically predicted levels of follicle stimulating hormones were associated with increased risks of EAC and/or BE in men (OR, 1.14 per allele increase; 95% CI, 1.01-1.27) and in women (OR, 1.28; 95% CI, 1.03-1.59). Higher predicted levels of luteinizing hormone were associated with a decreased risk of EAC in men (OR, 0.92 per standard deviation increase; 95% CI, 0.87-0.99) and in women (OR, 0.93; 95% CI, 0.79-1.09), and decreased risks of BE (OR, 0.88; 95% CI, 0.77-0.99) and EAC and/or BE (OR, 0.89; 95% CI, 0.79-1.00) in women. We found no clear associations for other hormones studied, including sex hormone-binding globulin, dehydroepiandrosterone sulphate, testosterone, dihydrotestosterone, estradiol, progesterone, or free androgen index. Conclusions In a Mendelian randomization analysis of data from patients with EAC or BE, we found an association between genetically predicted levels of follicle stimulating and luteinizing hormones and risk of BE and EAC.

Published
2020

10. Cumulative Burden of Colorectal Cancer Associated Genetic Variants Is More Strongly Associated With Early-Onset vs Late-Onset Cancer

Author

Archambault, AN, Su, Y-R, Jeon, J, Thomas, M, Lin, Y, Conti, DV, Win, AK, Sakoda, LC, Lansdorp-Vogelaar, I, Peterse, EFP, Zauber, AG, Duggan, D, Holowatyj, AN, Huyghe, JR, Brenner, H, Cotterchio, M, Bezieau, S, Schmit, SL, Edlund, CK, Southey, MC, MacInnis, RJ, Campbell, PT, Chang-Claude, J, Slattery, ML, Chan, AT, Joshi, AD, Song, M, Cao, Y, Woods, MO, White, E, Weinstein, SJ, Ulrich, CM, Hoffmeister, M, Bien, SA, Harrison, TA, Hampe, J, Li, CI, Schafmayer, C, Offit, K, Pharoah, PD, Moreno, V, Lindblom, A, Wolk, A, Wu, AH, Li, L, Gunter, MJ, Gsur, A, Keku, TO, Pearlman, R, Bishop, DT, Castellvi-Bel, S, Moreira, L, Vodicka, P, Kampman, E, Giles, GG, Albanes, D, Baron, JA, Berndt, SI, Brezina, S, Buch, S, Buchanan, DD, Trichopoulou, A, Severi, G, Chirlaque, M-D, Sanchez, M-J, Palli, D, Kuhn, T, Murphy, N, Cross, AJ, Burnett-Hartman, AN, Chanock, SJ, de la Chapelle, A, Easton, DF, Elliott, F, English, DR, Feskens, EJM, FitzGerald, LM, Goodman, PJ, Hopper, JL, Hudson, TJ, Hunter, DJ, Jacobs, EJ, Joshu, CE, Kury, S, Markowitz, SD, Milne, RL, Platz, EA, Rennert, G, Rennert, HS, Schumacher, FR, Sandler, RS, Seminara, D, Tangen, CM, Thibodeau, SN, Toland, AE, van Duijnhoven, FJB, Visvanathan, K, Vodickova, L, Potter, JD, Mannisto, S, Weigl, K, Figueiredo, J, Martin, V, Larsson, SC, Parfrey, PS, Huang, W-Y, Lenz, H-J, Castelao, JE, Gago-Dominguez, M, Munoz-Garzon, V, Mancao, C, Haiman, CA, Wilkens, LR, Siegel, E, Barry, E, Younghusband, B, Van Guelpen, B, Harlid, S, Zeleniuch-Jacquotte, A, Liang, PS, Du, M, Casey, G, Lindor, NM, Le Marchand, L, Gallinger, SJ, Jenkins, MA, Newcomb, PA, Gruber, SB, Schoen, RE, Hampel, H, Corley, DA, Hsu, L, Peters, U, Hayes, RB, Archambault, AN, Su, Y-R, Jeon, J, Thomas, M, Lin, Y, Conti, DV, Win, AK, Sakoda, LC, Lansdorp-Vogelaar, I, Peterse, EFP, Zauber, AG, Duggan, D, Holowatyj, AN, Huyghe, JR, Brenner, H, Cotterchio, M, Bezieau, S, Schmit, SL, Edlund, CK, Southey, MC, MacInnis, RJ, Campbell, PT, Chang-Claude, J, Slattery, ML, Chan, AT, Joshi, AD, Song, M, Cao, Y, Woods, MO, White, E, Weinstein, SJ, Ulrich, CM, Hoffmeister, M, Bien, SA, Harrison, TA, Hampe, J, Li, CI, Schafmayer, C, Offit, K, Pharoah, PD, Moreno, V, Lindblom, A, Wolk, A, Wu, AH, Li, L, Gunter, MJ, Gsur, A, Keku, TO, Pearlman, R, Bishop, DT, Castellvi-Bel, S, Moreira, L, Vodicka, P, Kampman, E, Giles, GG, Albanes, D, Baron, JA, Berndt, SI, Brezina, S, Buch, S, Buchanan, DD, Trichopoulou, A, Severi, G, Chirlaque, M-D, Sanchez, M-J, Palli, D, Kuhn, T, Murphy, N, Cross, AJ, Burnett-Hartman, AN, Chanock, SJ, de la Chapelle, A, Easton, DF, Elliott, F, English, DR, Feskens, EJM, FitzGerald, LM, Goodman, PJ, Hopper, JL, Hudson, TJ, Hunter, DJ, Jacobs, EJ, Joshu, CE, Kury, S, Markowitz, SD, Milne, RL, Platz, EA, Rennert, G, Rennert, HS, Schumacher, FR, Sandler, RS, Seminara, D, Tangen, CM, Thibodeau, SN, Toland, AE, van Duijnhoven, FJB, Visvanathan, K, Vodickova, L, Potter, JD, Mannisto, S, Weigl, K, Figueiredo, J, Martin, V, Larsson, SC, Parfrey, PS, Huang, W-Y, Lenz, H-J, Castelao, JE, Gago-Dominguez, M, Munoz-Garzon, V, Mancao, C, Haiman, CA, Wilkens, LR, Siegel, E, Barry, E, Younghusband, B, Van Guelpen, B, Harlid, S, Zeleniuch-Jacquotte, A, Liang, PS, Du, M, Casey, G, Lindor, NM, Le Marchand, L, Gallinger, SJ, Jenkins, MA, Newcomb, PA, Gruber, SB, Schoen, RE, Hampel, H, Corley, DA, Hsu, L, Peters, U, and Hayes, RB

Abstract

BACKGROUND & AIMS: Early-onset colorectal cancer (CRC, in persons younger than 50 years old) is increasing in incidence; yet, in the absence of a family history of CRC, this population lacks harmonized recommendations for prevention. We aimed to determine whether a polygenic risk score (PRS) developed from 95 CRC-associated common genetic risk variants was associated with risk for early-onset CRC. METHODS: We studied risk for CRC associated with a weighted PRS in 12,197 participants younger than 50 years old vs 95,865 participants 50 years or older. PRS was calculated based on single nucleotide polymorphisms associated with CRC in a large-scale genome-wide association study as of January 2019. Participants were pooled from 3 large consortia that provided clinical and genotyping data: the Colon Cancer Family Registry, the Colorectal Transdisciplinary Study, and the Genetics and Epidemiology of Colorectal Cancer Consortium and were all of genetically defined European descent. Findings were replicated in an independent cohort of 72,573 participants. RESULTS: Overall associations with CRC per standard deviation of PRS were significant for early-onset cancer, and were stronger compared with late-onset cancer (P for interaction = .01); when we compared the highest PRS quartile with the lowest, risk increased 3.7-fold for early-onset CRC (95% CI 3.28-4.24) vs 2.9-fold for late-onset CRC (95% CI 2.80-3.04). This association was strongest for participants without a first-degree family history of CRC (P for interaction = 5.61 × 10-5). When we compared the highest with the lowest quartiles in this group, risk increased 4.3-fold for early-onset CRC (95% CI 3.61-5.01) vs 2.9-fold for late-onset CRC (95% CI 2.70-3.00). Sensitivity analyses were consistent with these findings. CONCLUSIONS: In an analysis of associations with CRC per standard deviation of PRS, we found the cumulative burden of CRC-associated common genetic variants to associate with early-onset cancer, and to be mo

Published
2020

13. BRCA2 Hypomorphic Missense Variants Confer Moderate Risks of Breast Cancer

Author

Ian Tomlinson, Thérèse Truong, Henrik Flyger, Martha J. Shrubsole, Manjeet K. Bolla, Paolo Radice, Janet E. Olson, Xiao-Ou Shu, Ching-Yu Cheng, Kyriaki Michailidou, John L. Hopper, Annika Lindblom, Lizet E. van der Kolk, Paolo Peterlongo, Cora M. Aalfs, Susan L. Neuhausen, Hermela Shimelis, Jonine D. Figueroa, Florentia Fostira, Ji Yeob Choi, Fabienne Calléja, Setareh Moghadasi, Barbara Brouwers, Hui Miao, Pascal Guénel, Graham G. Giles, Roger L. Milne, Gord Glendon, Hidemi Ito, Per Hall, Jingmei Li, Elinor J. Sawyer, Javier Benitez, Isabel dos-Santos-Silva, Melissa C. Southey, Jyh-Cherng Yu, Curtis Olswold, Julian Peto, Valerie Rhenius, Katri Pylkäs, Anne Lise Børresen-Dale, Robert Winqvist, J. Margriet Collée, Mitul Shah, Minouk J. Schoemaker, Barbara Burwinkel, Pharoah Pd, Hermann Brenner, Keitaro Matsuo, Eva Machackova, Caroline M. Seynaeve, David E. Goldgar, Anna Jakubowska, Paul Brennan, Kathleen Claes, Montserrat Garcia-Closas, Vessela N. Kristensen, Douglas F. Easton, Hoda Anton-Culver, Åsa Ehlén, Stig E. Bojesen, Maaike P.G. Vreeswijk, Irene L. Andrulis, Annegien Broeks, Joe Dennis, Daniel O. Stram, Simon S. Cross, Christopher A. Haiman, Hatef Darabi, Veli-Matti Kosma, Daehee Kang, Frans B. L. Hogervorst, Alison M. Dunning, Aura Carreira, Antoinette Hollestelle, Kenneth Muir, Susan L. Slager, Thilo Dörk, Jennifer A. Leary, Sara Margolin, Jenna Lilyquist, Jenny Chang-Claude, Liliana Varesco, Amanda B. Spurdle, Georgia Chenevix-Trench, Diana Torres, Emily Hallberg, Marjanka K. Schmidt, Kristiina Aittomäki, Harry Vrieling, Loic Le Marchand, Catharina von Nicolai, Angela Cox, Matthias W. Beckmann, Natalia Bogdanova, Volker Arndt, Anja Rudolph, Arto Mannermaa, Heli Nevanlinna, Jamie Hinton, Lenka Foretova, Logan C. Walker, Muhammad Usman Rashid, Wei Zheng, Ying Zheng, Peter Devilee, Lucia Guidugli, Frederik Marme, Jan C. Oosterwijk, Alvaro N.A. Monteiro, Anna H. Wu, Anthony J. Swerdlow, Mikael Hartman, Soo H. Teo, Hiltrud Brauch, Thomas Brüning, Artitaya Lophatananon, Peter A. Fasching, Diether Lambrechts, Christi J. van Asperen, Chen-Yang Shen, Suleeporn Sangrajrang, Huong Meeks, Jan Lubinski, Kah-Nyin Lai, Ana Osorio, Chunling Hu, Qin Wang, Kamila Czene, Romy L. S. Mesman, Fergus J. Couch, Ute Hamann, Charlotte Martin, Dennis, Joe [0000-0003-4591-1214], Dunning, Alison [0000-0001-6651-7166], Pharoah, Paul [0000-0001-8494-732X], Rhenius, Valerie [0000-0003-4215-3235], Easton, Douglas [0000-0003-2444-3247], Apollo - University of Cambridge Repository, Damage and Repair in Cancer Development and Cancer Treatment (DARE), Targeted Gynaecologic Oncology (TARGON), Clinical Genetics, Medical Oncology, Human Genetics, Human genetics, and CCA - Cancer biology and immunology

Subjects
0301 basic medicine, Risk, Cancer Research, GENES, endocrine system diseases, Genotype, DNA-BINDING, Mutation, Missense, Breast Neoplasms, Biology, Bioinformatics, OVARIAN-CANCER, CLASSIFICATION, Article, 03 medical and health sciences, Mice, Breast cancer, Germline mutation, SDG 3 - Good Health and Well-being, medicine, UNCLASSIFIED VARIANTS, SEQUENCE VARIANTS, Missense mutation, Animals, Humans, skin and connective tissue diseases, Germ-Line Mutation, Aged, BRCA2 Protein, UNKNOWN CLINICAL-SIGNIFICANCE, Case-control study, Cancer, FUNCTIONAL-EVALUATION, medicine.disease, 3. Good health, 030104 developmental biology, Oncology, CELL-BASED ASSAY, Amino Acid Substitution, UNCERTAIN SIGNIFICANCE, Case-Control Studies, Female, Ovarian cancer
Abstract

Breast cancer risks conferred by many germline missense variants in the BRCA1 and BRCA2 genes, often referred to as variants of uncertain significance (VUS), have not been established. In this study, associations between 19 BRCA1 and 33 BRCA2 missense substitution variants and breast cancer risk were investigated through a breast cancer case–control study using genotyping data from 38 studies of predominantly European ancestry (41,890 cases and 41,607 controls) and nine studies of Asian ancestry (6,269 cases and 6,624 controls). The BRCA2 c.9104A>C, p.Tyr3035Ser (OR = 2.52; P = 0.04), and BRCA1 c.5096G>A, p.Arg1699Gln (OR = 4.29; P = 0.009) variant were associated with moderately increased risks of breast cancer among Europeans, whereas BRCA2 c.7522G>A, p.Gly2508Ser (OR = 2.68; P = 0.004), and c.8187G>T, p.Lys2729Asn (OR = 1.4; P = 0.004) were associated with moderate and low risks of breast cancer among Asians. Functional characterization of the BRCA2 variants using four quantitative assays showed reduced BRCA2 activity for p.Tyr3035Ser compared with wild-type. Overall, our results show how BRCA2 missense variants that influence protein function can confer clinically relevant, moderately increased risks of breast cancer, with potential implications for risk management guidelines in women with these specific variants. Cancer Res; 77(11); 2789–99. ©2017 AACR.

Published
2017

14. Novel Common Genetic Susceptibility Loci for Colorectal Cancer

Author

Schmit, SL, Edlund, CK, Schumacher, FR, Gong, J, Harrison, TA, Huyghe, JR, Qu, C, Melas, M, Van den Berg, DJ, Wang, H, Tring, S, Plummer, SJ, Albanes, D, Alonso, MH, Amos, CI, Anton, K, Aragaki, AK, Arndt, V, Barry, EL, Berndt, SI, Bezieau, S, Bien, S, Bloomer, A, Boehm, J, Boutron-Ruault, M-C, Brenner, H, Brezina, S, Buchanan, DD, Butterbach, K, Caan, BJ, Campbell, PT, Carlson, CS, Castelao, JE, Chan, AT, Chang-Claude, J, Chanock, SJ, Cheng, I, Cheng, Y-W, Chin, LS, Church, JM, Church, T, Coetzee, GA, Cotterchio, M, Correa, MC, Curtis, KR, Duggan, D, Easton, DF, English, D, Feskens, EJM, Fischer, R, FitzGerald, LM, Fortini, BK, Fritsche, LG, Fuchs, CS, Gago-Dominguez, M, Gala, M, Gallinger, SJ, Gauderman, WJ, Giles, GG, Giovannucci, EL, Gogarten, SM, Gonzalez-Villalpando, C, Gonzalez-Villalpando, EM, Grady, WM, Greenson, JK, Gsur, A, Gunter, M, Haiman, CA, Hampe, J, Harlid, S, Harju, JF, Hayes, RB, Hofer, P, Hoffmeister, M, Hopper, JL, Huang, S-C, Huerta, JM, Hudson, TJ, Hunter, DJ, Idos, GE, Iwasaki, M, Jackson, RD, Jacobs, EJ, Jee, SH, Jenkins, MA, Jia, W-H, Jiao, S, Joshi, AD, Kolonel, LN, Kono, S, Kooperberg, C, Krogh, V, Kuehn, T, Kury, S, LaCroix, A, Laurie, CA, Lejbkowicz, F, Lemire, M, Lenz, H-J, Levine, D, Li, CI, Li, L, Lieb, W, Lin, Y, Lindor, NM, Liu, Y-R, Loupakis, F, Lu, Y, Luh, F, Ma, J, Mancao, C, Manion, FJ, Markowitz, SD, Martin, V, Matsuda, K, Matsuo, K, McDonnell, KJ, McNeil, CE, Milne, R, Molina, AJ, Mukherjee, B, Murphy, N, Newcomb, PA, Offit, K, Omichessan, H, Palli, D, Cotore, JPP, Perez-Mayoral, J, Pharoah, PD, Potter, JD, Raskin, L, Rennert, G, Rennert, HS, Riggs, BM, Schafmayer, C, Schoen, RE, Sellers, TA, Seminara, D, Severi, G, Shi, W, Shibata, D, Shu, X-O, Siegel, EM, Slattery, ML, Southey, M, Stadler, ZK, Stern, MC, Stintzing, S, Taverna, D, Thibodeau, SN, Thomas, DC, Trichopoulou, A, Tsugane, S, Ulrich, CM, van Duijnhoven, FJB, van Guelpan, B, Vijai, J, Virtamo, J, Weinstein, SJ, White, E, Win, AK, Wolk, A, Woods, M, Wu, AH, Wu, K, Xiang, Y-B, Yen, Y, Zanke, BW, Zeng, Y-X, Zhang, B, Zubair, N, Kweon, S-S, Figueiredo, JC, Zheng, W, Le Marchand, L, Lindblom, A, Moreno, V, Peters, U, Casey, G, Hsu, L, Conti, DV, Gruber, SB, Schmit, SL, Edlund, CK, Schumacher, FR, Gong, J, Harrison, TA, Huyghe, JR, Qu, C, Melas, M, Van den Berg, DJ, Wang, H, Tring, S, Plummer, SJ, Albanes, D, Alonso, MH, Amos, CI, Anton, K, Aragaki, AK, Arndt, V, Barry, EL, Berndt, SI, Bezieau, S, Bien, S, Bloomer, A, Boehm, J, Boutron-Ruault, M-C, Brenner, H, Brezina, S, Buchanan, DD, Butterbach, K, Caan, BJ, Campbell, PT, Carlson, CS, Castelao, JE, Chan, AT, Chang-Claude, J, Chanock, SJ, Cheng, I, Cheng, Y-W, Chin, LS, Church, JM, Church, T, Coetzee, GA, Cotterchio, M, Correa, MC, Curtis, KR, Duggan, D, Easton, DF, English, D, Feskens, EJM, Fischer, R, FitzGerald, LM, Fortini, BK, Fritsche, LG, Fuchs, CS, Gago-Dominguez, M, Gala, M, Gallinger, SJ, Gauderman, WJ, Giles, GG, Giovannucci, EL, Gogarten, SM, Gonzalez-Villalpando, C, Gonzalez-Villalpando, EM, Grady, WM, Greenson, JK, Gsur, A, Gunter, M, Haiman, CA, Hampe, J, Harlid, S, Harju, JF, Hayes, RB, Hofer, P, Hoffmeister, M, Hopper, JL, Huang, S-C, Huerta, JM, Hudson, TJ, Hunter, DJ, Idos, GE, Iwasaki, M, Jackson, RD, Jacobs, EJ, Jee, SH, Jenkins, MA, Jia, W-H, Jiao, S, Joshi, AD, Kolonel, LN, Kono, S, Kooperberg, C, Krogh, V, Kuehn, T, Kury, S, LaCroix, A, Laurie, CA, Lejbkowicz, F, Lemire, M, Lenz, H-J, Levine, D, Li, CI, Li, L, Lieb, W, Lin, Y, Lindor, NM, Liu, Y-R, Loupakis, F, Lu, Y, Luh, F, Ma, J, Mancao, C, Manion, FJ, Markowitz, SD, Martin, V, Matsuda, K, Matsuo, K, McDonnell, KJ, McNeil, CE, Milne, R, Molina, AJ, Mukherjee, B, Murphy, N, Newcomb, PA, Offit, K, Omichessan, H, Palli, D, Cotore, JPP, Perez-Mayoral, J, Pharoah, PD, Potter, JD, Raskin, L, Rennert, G, Rennert, HS, Riggs, BM, Schafmayer, C, Schoen, RE, Sellers, TA, Seminara, D, Severi, G, Shi, W, Shibata, D, Shu, X-O, Siegel, EM, Slattery, ML, Southey, M, Stadler, ZK, Stern, MC, Stintzing, S, Taverna, D, Thibodeau, SN, Thomas, DC, Trichopoulou, A, Tsugane, S, Ulrich, CM, van Duijnhoven, FJB, van Guelpan, B, Vijai, J, Virtamo, J, Weinstein, SJ, White, E, Win, AK, Wolk, A, Woods, M, Wu, AH, Wu, K, Xiang, Y-B, Yen, Y, Zanke, BW, Zeng, Y-X, Zhang, B, Zubair, N, Kweon, S-S, Figueiredo, JC, Zheng, W, Le Marchand, L, Lindblom, A, Moreno, V, Peters, U, Casey, G, Hsu, L, Conti, DV, and Gruber, SB

Abstract

BACKGROUND: Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10-8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk. METHODS: We conducted a GWAS in European descent CRC cases and control subjects using a discovery-replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10-8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided. RESULTS: The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10-8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0. CONCLUSIONS: T

Published
2019

15. Going to extremes: determinants of extraordinary response and survival in patients with cancer

Author

Saner, FAM, Herschtal, A, Nelson, BH, deFazio, A, Goode, EL, Ramus, SJ, Pandey, A, Beach, JA, Fereday, S, Berchuck, A, Lheureux, S, Pearce, CL, Pharoah, PD, Pike, MC, Garsed, DW, Bowtell, DDL, Saner, FAM, Herschtal, A, Nelson, BH, deFazio, A, Goode, EL, Ramus, SJ, Pandey, A, Beach, JA, Fereday, S, Berchuck, A, Lheureux, S, Pearce, CL, Pharoah, PD, Pike, MC, Garsed, DW, and Bowtell, DDL

Abstract

Research into factors affecting treatment response or survival in patients with cancer frequently involves cohorts that span the most common range of clinical outcomes, as such patients are most readily available for study. However, attention has turned to highly unusual patients who have exceptionally favourable or atypically poor responses to treatment and/or overall survival, with the expectation that patients at the extremes may provide insights that could ultimately improve the outcome of individuals with more typical disease trajectories. While clinicians can often recount surprising patients whose clinical journey was very unusual, given known clinical characteristics and prognostic indicators, there is a lack of consensus among researchers on how best to define exceptional patients, and little has been proposed for the optimal design of studies to identify factors that dictate unusual outcome. In this Opinion article, we review different approaches to identifying exceptional patients with cancer and possible study designs to investigate extraordinary clinical outcomes. We discuss pitfalls with finding these rare patients, including challenges associated with accrual of patients across different treatment centres and time periods. We describe recent molecular and immunological factors that have been identified as contributing to unusual patient outcome and make recommendations for future studies on these intriguing patients.

Published
2019

16. Interactions Between Genetic Variants and Environmental Factors Affect Risk of Esophageal Adenocarcinoma and Barrett's Esophagus

Author

Dong, J, Levine, DM, Buas, MF, Zhang, R, Onstad, L, Fitzgerald, RC, Stomach and Oesophageal Cancer Study (SOCS) Consortium, Corley, DA, Shaheen, NJ, Lagergren, J, Hardie, LJ, Reid, BJ, Iyer, PG, Risch, HA, Caldas, C, Caldas, I, Pharoah, PD, Liu, G, Gammon, MD, Chow, W-H, Bernstein, L, Bird, NC, Ye, W, Wu, AH, Anderson, LA, MacGregor, S, Whiteman, DC, Vaughan, TL, Thrift, AP, Fitzgerald, Rebecca [0000-0002-3434-3568], Caldas, Carlos [0000-0003-3547-1489], Pharoah, Paul [0000-0001-8494-732X], and Apollo - University of Cambridge Repository

Subjects
Male, Esophageal Neoplasms, Genetic Variants, Environmental Exposure, Adenocarcinoma, Middle Aged, Polymorphism, Single Nucleotide, Risk Assessment, United Kingdom, Barrett Esophagus, Esophagus, SDG 3 - Good Health and Well-being, Risk Factors, Humans, Female, Genetic Predisposition to Disease, Esophageal Neoplasm, Aged, Genome-Wide Association Study
Abstract

Background & Aims: Genome-wide association studies (GWAS) have identified more than 20 susceptibility loci for esophageal adenocarcinoma (EA) and Barrett’s esophagus (BE). However, variants in these loci account for a small fraction of cases of EA and BE. Genetic factors might interact with environmental factors to affect risk of EA and BE. We aimed to identify single nucleotide polymorphisms (SNPs) that may modify the associations of body mass index (BMI), smoking, and gastroesophageal reflux disease (GERD), with risks of EA and BE. Methods: We collected data on single BMI measurements, smoking status, and symptoms of GERD from 2284 patients with EA, 3104 patients with BE, and 2182 healthy individuals (controls) participating in the Barrett’s and Esophageal Adenocarcinoma Consortium GWAS, the UK Barrett’s Esophagus Gene Study, and the UK Stomach and Oesophageal Cancer Study. We analyzed 993,501 SNPs in DNA samples of all study subjects. We used standard case–control logistic regression to test for gene-environment interactions. Results: For EA, rs13429103 at chromosome 2p25.1, near the RNF144A-LOC339788 gene, showed a borderline significant interaction with smoking status (P=2.18×10-7). Ever smoking was associated with an almost 12-fold increase in risk of EA among individuals with rs13429103-AA genotype (odds ratio=11.82; 95% CI, 4.03–34.67). Three SNPs (rs12465911, rs2341926, rs13396805) at chromosome 2q23.3, near the RND3-RBM43 gene, interacted with GERD symptoms (P=1.70×10-7, P=1.83×10-7, and P=3.58×10-7, respectively) to affect risk of EA. For BE, rs491603 at chromosome 1p34.3, near the EIF2C3 gene, and rs11631094 at chromosome 15q14, at the SLC12A6 gene, interacted with BMI (P=4.44×10-7) and pack-years of smoking history (P=2.82×10-7), respectively. Conclusion: The associations of BMI, smoking, and GERD symptoms with risks of EA and BE appear to vary with SNPs at chromosomes 1, 2, and 15. Validation of these suggestive interactions is warranted.

Published
2018

18. Association of p16 expression with prognosis varies across ovarian carcinoma histotypes: an Ovarian Tumor Tissue Analysis consortium study

Author

Rambau, PF, Vierkant, RA, Intermaggio, MP, Kelemen, LE, Goodman, MT, Herpel, E, Pharoah, PD, Kommoss, S, Jimenez-Linan, M, Karlan, BY, Gentry-Maharaj, A, Menon, U, Polo, SH, Candido Dos Reis, FJ, Doherty, JA, Gayther, SA, Sharma, R, Larson, MC, Harnett, PR, Hatfield, E, de Andrade, JM, Nelson, GS, Steed, H, Schildkraut, JM, Carney, ME, Høgdall, E, Whittemore, AS, Widschwendter, M, Kennedy, CJ, Wang, F, Wang, Q, Wang, C, Armasu, SM, Daley, F, Coulson, P, Jones, ME, Anglesio, MS, Chow, C, de Fazio, A, García-Closas, M, Brucker, SY, Cybulski, C, Harris, HR, Hartkopf, AD, Huzarski, T, Jensen, A, Lubiński, J, Oszurek, O, Benitez, J, Mina, F, Staebler, A, Taran, FA, Pasternak, J, Talhouk, A, Rossing, MA, Hendley, J, Edwards, RP, Fereday, S, Modugno, F, Ness, RB, Sieh, W, El-Bahrawy, MA, Winham, SJ, Lester, J, Kjaer, SK, Gronwald, J, Sinn, P, Fasching, PA, Chang-Claude, J, Moysich, KB, Bowtell, DD, Hernandez, BY, Luk, H, Behrens, S, Shah, M, Jung, A, Ghatage, P, Alsop, J, Alsop, K, García-Donas, J, Thompson, PJ, Swerdlow, AJ, Karpinskyj, C, Cazorla-Jiménez, A, García, MJ, Deen, S, Wilkens, LR, Palacios, J, Berchuck, A, Koziak, JM, Brenton, JD, Cook, LS, Goode, EL, Huntsman, DG, Ramus, SJ, Köbel, M, Rambau, PF, Vierkant, RA, Intermaggio, MP, Kelemen, LE, Goodman, MT, Herpel, E, Pharoah, PD, Kommoss, S, Jimenez-Linan, M, Karlan, BY, Gentry-Maharaj, A, Menon, U, Polo, SH, Candido Dos Reis, FJ, Doherty, JA, Gayther, SA, Sharma, R, Larson, MC, Harnett, PR, Hatfield, E, de Andrade, JM, Nelson, GS, Steed, H, Schildkraut, JM, Carney, ME, Høgdall, E, Whittemore, AS, Widschwendter, M, Kennedy, CJ, Wang, F, Wang, Q, Wang, C, Armasu, SM, Daley, F, Coulson, P, Jones, ME, Anglesio, MS, Chow, C, de Fazio, A, García-Closas, M, Brucker, SY, Cybulski, C, Harris, HR, Hartkopf, AD, Huzarski, T, Jensen, A, Lubiński, J, Oszurek, O, Benitez, J, Mina, F, Staebler, A, Taran, FA, Pasternak, J, Talhouk, A, Rossing, MA, Hendley, J, Edwards, RP, Fereday, S, Modugno, F, Ness, RB, Sieh, W, El-Bahrawy, MA, Winham, SJ, Lester, J, Kjaer, SK, Gronwald, J, Sinn, P, Fasching, PA, Chang-Claude, J, Moysich, KB, Bowtell, DD, Hernandez, BY, Luk, H, Behrens, S, Shah, M, Jung, A, Ghatage, P, Alsop, J, Alsop, K, García-Donas, J, Thompson, PJ, Swerdlow, AJ, Karpinskyj, C, Cazorla-Jiménez, A, García, MJ, Deen, S, Wilkens, LR, Palacios, J, Berchuck, A, Koziak, JM, Brenton, JD, Cook, LS, Goode, EL, Huntsman, DG, Ramus, SJ, and Köbel, M

Abstract

We aimed to validate the prognostic association of p16 expression in ovarian high-grade serous carcinomas (HGSC) and to explore it in other ovarian carcinoma histotypes. p16 protein expression was assessed by clinical-grade immunohistochemistry in 6525 ovarian carcinomas including 4334 HGSC using tissue microarrays from 24 studies participating in the Ovarian Tumor Tissue Analysis consortium. p16 expression patterns were interpreted as abnormal (either overexpression referred to as block expression or absence) or normal (heterogeneous). CDKN2A (which encodes p16) mRNA expression was also analyzed in a subset (n = 2280) mostly representing HGSC (n = 2010). Association of p16 expression with overall survival (OS) was determined within histotypes as was CDKN2A expression for HGSC only. p16 block expression was most frequent in HGSC (56%) but neither protein nor mRNA expression was associated with OS. However, relative to heterogeneous expression, block expression was associated with shorter OS in endometriosis-associated carcinomas, clear cell [hazard ratio (HR): 2.02, 95% confidence (CI) 1.47-2.77, p < 0.001] and endometrioid (HR: 1.88, 95% CI 1.30-2.75, p = 0.004), while absence was associated with shorter OS in low-grade serous carcinomas (HR: 2.95, 95% CI 1.61-5.38, p = 0.001). Absence was most frequent in mucinous carcinoma (50%), and was not associated with OS in this histotype. The prognostic value of p16 expression is histotype-specific and pattern dependent. We provide definitive evidence against an association of p16 expression with survival in ovarian HGSC as previously suggested. Block expression of p16 in clear cell and endometrioid carcinoma should be further validated as a prognostic marker, and absence in low-grade serous carcinoma justifies CDK4 inhibition.

Published
2018

19. Etiology of hormone receptor positive breast cancer differs by levels of histologic grade and proliferation

Author

Abubakar, M, Chang-Claude, J, Ali, HR, Chatterjee, N, Coulson, P, Daley, F, Blows, F, Benitez, J, Milne, RL, Brenner, H, Stegmaier, C, Mannermaa, A, Rudolph, A, Sinn, P, Couch, FJ, Devilee, P, Tollenaar, RAEM, Seynaeve, C, Figueroa, J, Lissowska, J, Hewitt, S, Hooning, MJ, Hollestelle, A, Foekens, R, Koppert, LB, Bolla, MK, Wang, Q, Jones, ME, Schoemaker, MJ, Keeman, R, Easton, DF, Swerdlow, AJ, Sherman, ME, Schmidt, MK, Pharoah, PD, Garcia-Closas, M, Abubakar, M, Chang-Claude, J, Ali, HR, Chatterjee, N, Coulson, P, Daley, F, Blows, F, Benitez, J, Milne, RL, Brenner, H, Stegmaier, C, Mannermaa, A, Rudolph, A, Sinn, P, Couch, FJ, Devilee, P, Tollenaar, RAEM, Seynaeve, C, Figueroa, J, Lissowska, J, Hewitt, S, Hooning, MJ, Hollestelle, A, Foekens, R, Koppert, LB, Bolla, MK, Wang, Q, Jones, ME, Schoemaker, MJ, Keeman, R, Easton, DF, Swerdlow, AJ, Sherman, ME, Schmidt, MK, Pharoah, PD, and Garcia-Closas, M

Abstract

Limited epidemiological evidence suggests that the etiology of hormone receptor positive (HR+) breast cancer may differ by levels of histologic grade and proliferation. We pooled risk factor and pathology data on 5,905 HR+ breast cancer cases and 26,281 controls from 11 epidemiological studies. Proliferation was determined by centralized automated measures of KI67 in tissue microarrays. Odds ratios (OR), 95% confidence intervals (CI) and p-values for case-case and case-control comparisons for risk factors in relation to levels of grade and quartiles (Q1-Q4) of KI67 were estimated using polytomous logistic regression models. Case-case comparisons showed associations between nulliparity and high KI67 [OR (95% CI) for Q4 vs. Q1 = 1.54 (1.22, 1.95)]; obesity and high grade [grade 3 vs. 1 = 1.68 (1.31, 2.16)] and current use of combined hormone therapy (HT) and low grade [grade 3 vs. 1 = 0.27 (0.16, 0.44)] tumors. In case-control comparisons, nulliparity was associated with elevated risk of tumors with high but not low levels of proliferation [1.43 (1.14, 1.81) for KI67 Q4 vs. 0.83 (0.60, 1.14) for KI67 Q1]; obesity among women ≥50 years with high but not low grade tumors [1.55 (1.17, 2.06) for grade 3 vs. 0.88 (0.66, 1.16) for grade 1] and HT with low but not high grade tumors [3.07 (2.22, 4.23) for grade 1 vs. 0.85 (0.55, 1.30) for grade 3]. Menarcheal age and family history were similarly associated with HR+ tumors of different grade or KI67 levels. These findings provide insights into the etiologic heterogeneity of HR+ tumors.

Published
2018

20. P-values and confidence intervals: not fit for purpose?

Author

Pharoah Pd, Siddhartha Kar, and Matthew Jones

Subjects
Scientific inference, Statistics, Range (statistics), Data mining, Interval (mathematics), Biostatistics, Null hypothesis, computer.software_genre, Value (mathematics), Measure (mathematics), computer, Confidence interval, Mathematics
Abstract

After collecting data to address an hypotheis the primary question the scientist wishes to answer is what is the probability that the null hypothesis is true? The P-value is not the probability that the null hypothesis is true, nor is it an approximation of that probability. After collecting data to measure the magnitude of a parameter of interest (effect size) the scientist wishes to know a range of values within which the true value of that parameter likely to lie (with specified probability). The 95 per cent confidence interval is not an interval within which the true value of the parameter is likely to lie with 95 per cent probability. Continues reliance on the P-value and the 95 per cent confidence interval as the primary statistics of interest in the reporting of biomendical science is the result of a failure to acknowledge that they do not provide the answers to the key questions of interest. A radical rethink of the requirements for the reporting of biostatistics is needed in order to promote sound scientific inference.

Published
2017
Full Text
View/download PDF

21. Rare, protein-truncating variants in $\textit{ATM}$, $\textit{CHEK2}$ and $\textit{PALB2}$, but not $\textit{XRCC2}$, are associated with increased breast cancer risks

Author

Decker, B, Allen, J, Luccarini, C, Pooley, KA, Shah, M, Bolla, MK, Wang, Q, Ahmed, S, Baynes, C, Conroy, DM, Brown, J, Luben, R, Ostrander, EA, Pharoah, PD, Dunning, AM, Easton, DF, Allen, Jamie [0000-0002-8677-2225], Pooley, Karen [0000-0002-1274-9460], Wang, Jean [0000-0002-9139-0627], Luben, Robert [0000-0002-5088-6343], Pharoah, Paul [0000-0001-8494-732X], Dunning, Alison [0000-0001-6651-7166], Easton, Douglas [0000-0003-2444-3247], and Apollo - University of Cambridge Repository

Subjects
Cancer: breast, Genetic Variation, Breast Neoplasms, Ataxia Telangiectasia Mutated Proteins, DNA-Binding Proteins, Checkpoint Kinase 2, Evidence Based Practice, Sequence Analysis, Protein, Genetic Epidemiology, Humans, Female, Genetic Predisposition to Disease, Fanconi Anemia Complementation Group N Protein, Geneticscreening/counselling
Abstract

BACKGROUND: Breast cancer (BC) is the most common malignancy in women and has a major heritable component. The risks associated with most rare susceptibility variants are not well estimated. To better characterise the contribution of variants in ATM, CHEK2, PALB2 and XRCC2, we sequenced their coding regions in 13 087 BC cases and 5488 controls from East Anglia, UK. METHODS: Gene coding regions were enriched via PCR, sequenced, variant called and filtered for quality. ORs for BC risk were estimated separately for carriers of truncating variants and of rare missense variants, which were further subdivided by functional domain and pathogenicity as predicted by four in silico algorithms. RESULTS: Truncating variants in PALB2 (OR=4.69, 95% CI 2.27 to 9.68), ATM (OR=3.26; 95% CI 1.82 to 6.46) and CHEK2 (OR=3.11; 95% CI 2.15 to 4.69), but not XRCC2 (OR=0.94; 95% CI 0.26 to 4.19) were associated with increased BC risk. Truncating variants in ATM and CHEK2 were more strongly associated with risk of oestrogen receptor (ER)-positive than ER-negative disease, while those in PALB2 were associated with similar risks for both subtypes. There was also some evidence that missense variants in ATM, CHEK2 and PALB2 may contribute to BC risk, but larger studies are necessary to quantify the magnitude of this effect. CONCLUSIONS: Truncating variants in PALB2 are associated with a higher risk of BC than those in ATM or CHEK2. A substantial risk of BC due to truncating XRCC2 variants can be excluded.

Published
2017
Full Text
View/download PDF

22. Meta-Analysis of Genome-Wide Association Studies (GWAS) of Late Toxicity in 3,874 Men Treated with Radiation for Prostate Cancer

Author

Gillian C. Barnett, Harry Ostrer, Alison M. Dunning, Leila Dorling, AG CaamaNo, Ana Vega, Emma Hall, D. Dearnaley, Neil G. Burnet, Matthew Parliament, Nawaid Usmani, K. De Ruyck, Pmp Higuero, Pharoah Pd, Matthew R. Sydes, Laura Fachal, Barry S. Rosenstein, Sarah L. Kerns, Ana Carballo, and Catharine M L West

Subjects
Oncology, Cancer Research, medicine.medical_specialty, Radiation, business.industry, Genome-wide association study, medicine.disease, Late toxicity, Prostate cancer, Meta-analysis, Internal medicine, medicine, Radiology, Nuclear Medicine and imaging, business
Published
2018

23. Fine-Scale mapping of the 11q13 breast cancer susceptibility locus

Author

Ghoussaini, M, Ahmed, S, Michailidou, K, Gregory, K, Dicks, E, Driver, K, Pharoah, PD, Easton, DF, and Dunning, AM

Subjects
Genotype, Quantitative Trait Loci, 4202 Epidemiology, 32 Biomedical and Clinical Sciences, Breast Neoplasms, Polymorphism, Single Nucleotide, Risk Assessment, 3105 Genetics, Linkage Disequilibrium, Gene Frequency, Breast Cancer, Genetics, 2.1 Biological and endogenous factors, Humans, Genetic Predisposition to Disease, Alleles, Genetic Association Studies, Cancer, 2 Aetiology, Prevention, Human Genome, 42 Health Sciences, Chromosome Mapping, Computational Biology, 4203 Health Services and Systems, 3211 Oncology and Carcinogenesis, Chromosomes, Human, Pair 1, FOS: Biological sciences, Case-Control Studies, Population Surveillance, Female, Neoplasm Grading, 31 Biological Sciences
Abstract

The Cancer Genetic Markers of Susceptibility genome-wide association study (GWAS) originally identified a single nucleotide polymorphism (SNP) rs11249433 at 1p11.2 associated with breast cancer risk. To fine-map this locus, we genotyped 92 SNPs in a 900kb region (120,505,799–121,481,132) flanking rs11249433 in 45,276 breast cancer cases and 48,998 controls of European, Asian and African ancestry from 50 studies in the Breast Cancer Association Consortium. Genotyping was done using iCOGS, a custom-built array. Due to the complicated nature of the region on chr1p11.2: 120,300,000–120,505,798, that lies near the centromere and contains seven duplicated genomic segments, we restricted analyses to 429 SNPs excluding the duplicated regions (42 genotyped and 387 imputed). Perallelic associations with breast cancer risk were estimated using logistic regression models adjusting for study and ancestry-specific principal components. The strongest association observed was with the original identified index SNP rs11249433 (minor allele frequency (MAF) 0.402; per-allele odds ratio (OR) = 1.10, 95% confidence interval (CI) 1.08–1.13, $\small \textit{P}$ = 1.49 x 10$^{-21}$). The association for rs11249433 was limited to ER-positive breast cancers (test for heterogeneity $\small \textit{P}$ $\leq$ 8.41 x 10$^{-5}$). Additional analyses by other tumor characteristics showed stronger associations with moderately/well differentiated tumors and tumors of lobular histology. Although no significant eQTL associations were observed, in silico analyses showed that rs11249433 was located in a region that is likely a weak enhancer/promoter. Fine-mapping analysis of the 1p11.2 breast cancer susceptibility locus confirms this region to be limited to risk to cancers that are ER-positive.

Published
2016
Full Text
View/download PDF

24. Genomic analyses for age at menarche identify 389 independent signals and indicate BMI-independent effects of puberty timing on cancer susceptibility

Author

Nora Franceschini, Rico Rueedi, Gerardo Heiss, Behrooz Z. Alizadeh, Marike Gabrielson, Henry Völzke, Daniela Ruggiero, Judith S. Brand, Stig E. Bojesen, Iffat Rahman, Fergus J. Couch, Patrick Sulem, Harold Snieder, Jenny Chang-Claude, Caterina Barbieri, Ute Hamann, Hinds D, Pascal Guénel, Amanda B. Spurdle, Paul M. Ridker, Ulla Sovio, Roger L. Milne, Hamdi Mbarek, H Brenner, Hilary K. Finucane, Maristella Steri, Lude Franke, Emmi Tikkanen, Ivana Kolcic, Vitart, Ken K. Ong, Alison M. Dunning, Aarno Palotie, Caroline Hayward, Jouke J. Hottenga, Abhishek Sarkar, Stefania Lenarduzzi, Nicholas G. Martin, Katharina E. Schraut, Eva Albrecht, Hiltrud Brauch, Lisette Stolk, Joop S.E. Laven, Penelope A. Lind, Ilaria Gandin, Patrik K. E. Magnusson, Ellen A. Nohr, Tanguy Corre, Jing Hua Zhao, N J Timpson, Jenny A. Visser, Harald Grallert, P. A. Fasching, Susan M. Ring, Stöckl D, Grant W. Montgomery, Marzyeh Amini, Velez Edwards Dr, Thomas Meitinger, Qinghua Wang, David Karasik, Daniel I. Chasman, Nicholas J. Wareham, Alexander Teumer, Mellissa C. Southey, Kathryn L. Lunetta, S. E. Medland, Dieter Flesch-Janys, Maartje J. Hooning, Lili Milani, D Lambrechts, Ozren Polasek, Po-Ru Loh, James F. Wilson, Campbell A, Julian Peto, Ellen W. Demerath, Christian Gieger, de Geus Ej, Cox A, Javier Benítez, Mitul Shah, Eric Boerwinkle, Matthias W. Beckmann, Thorsteindottir U, Julie E. Buring, De Vivo I, Hannes Helgason, Paolo Radice, Tracy A. O'Mara, L. J. Launer, D. F. Gudbjartsson, Frits R. Rosendaal, C.A. Hartman, Stefania Bandinelli, Felix R. Day, Lynda M. Rose, van Dijk Kw, Natalia Perjakova, Anneli Pouta, Igor Rudan, Sven Bergmann, Kamila Czene, Georgia Chenevix-Trench, Pau Navarro, Sean Whalen, Heli Nevanlinna, Teresa Nutile, Diana L. Cousminer, Albert V. Smith, Massimo Mangino, Uwe Völker, Michela Traglia, Lindsay Fernández-Rhodes, Ayush Giri, Linda Broer, Albertine J. Oldehinkel, Isabel dos-Santos-Silva, Peter Vollenweider, Jian'an Luan, Nancy L. Pedersen, Irene L. Andrulis, Reedik Mägi, Robert Winqvist, Gonneke Willemsen, John L. Hopper, Gudnason, Marjanka K. Schmidt, David G. Hunter, Robert A. Scott, T.B. Harris, Joanne M. Murabito, David J. Porteous, Harry Campbell, Eleonora Porcu, D.I. Boomsma, Thibaud Boutin, M. A. Ikram, Doug Easton, Magdalena Zoledziewska, Meir J. Stampfer, Katherine S. Pollard, Eulalia Catamo, Tõnu Esko, M-R Jarvelin, Laura Crisponi, Claudia Langenberg, Marek Zygmunt, Antonietta Robino, Emily Hallberg, Manjeet K. Bolla, Ruth Ks, Bruce H W Wolffenbuttel, Lavinia Paternoster, Tyrer Jp, P. Kraft, George Davey-Smith, Robert Karlsson, Graham G. Giles, Jingmei Li, Pharoah Pd, Segrè Av, Marina Ciullo, Perry, Brumat Marco, Peter K. Joshi, Chunyan He, Sara Lindström, Joe Dennis, Thérèse Truong, Yongmei Liu, Anna Marie Mulligan, Mike A. Nalls, Cinzia Sala, K. Stefansson, Murray A, Debbie A Lawlor, Tung Jy, Deborah J. Thompson, Dennis O. Mook-Kanamori, Daniela Toniolo, Luigi Ferrucci, Peter Devilee, S. Chanock, Cristina Menni, George McMahon, Murielle Bochud, A. Metspalu, Tomohiro Tanaka, E. Widen, Hae Kyung Im, Dale R. Nyholt, Ilja M. Nolte, Thomas Brüning, Christina Meisinger, Annette Peters, Kyriaki Michailidou, Per Hall, Rossella Sorice, Genevieve Lachance, Johan G. Eriksson, Francesco Cucca, A.G. Uitterlinden, Z. Kutalik, Mark I. McCarthy, Frank B. Hu, Konstantin Strauch, Tim D. Spector, Elisabeth Altmaier, S. Ulivi, Alkes L. Price, Arto Mannermaa, Raymond Noordam, and de Mutsert R

Subjects
Genetics, 0303 health sciences, 03 medical and health sciences, 0302 clinical medicine, 030220 oncology & carcinogenesis, Genotype, Menarche, Trait, Cancer susceptibility, Genomics, Biology, 030304 developmental biology
Abstract

The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Here, we analyse 1000-Genome reference panel imputed genotype data on up to ~370,000 women and identify 389 independent signals (all P−8) for age at menarche, a notable milestone in female pubertal development. In Icelandic data from deCODE, these signals explain ~7.4% of the population variance in age at menarche, corresponding to one quarter of the estimated heritability. We implicate over 250 genes via coding variation or associated gene expression, and demonstrate enrichment across genes active in neural tissues. We identify multiple rare variants near the imprinted genes MKRN3 and DLK1 that exhibit large effects on menarche only when paternally inherited. Disproportionate effects of variants on early or late puberty timing are observed: single variant and heritability estimates are larger for early than late puberty timing in females. The opposite pattern is seen in males, with larger estimates for late than early puberty timing. Mendelian randomization analyses indicate causal inverse associations, independent of BMI, between puberty timing and risks for breast and endometrial cancers in women, and prostate cancer in men. In aggregate, our findings reveal new complexity in the genetic regulation of puberty timing and support new causal links with adult cancer risks.

Published
2016
Full Text
View/download PDF

25. High-throughput automated scoring of Ki67 in breast cancer tissue microarrays from the Breast Cancer Association Consortium

Author

Abubakar, M, Howat, WJ, Daley, F, Zabaglo, L, McDuffus, L A, Blows, F, Coulson, P, Raza Ali, H, Benitez, J, Milne, R, Brenner, H, Stegmaier, C, Mannermaa, A, Chang-Claude, J, Rudolph, A, Sinn, P, Couch, FJ, Tollenaar, RA, Devilee, P, Figueroa, J, Sherman, ME, Lissowska, J, Hewitt, S, Eccles, D, Hooning, Maartje, Hollestelle, Antoinette, Martens, John, van Deurzen, Carolien, Bolla, MK, Wang, Q, Jones, M, Schoemaker, M, Broeks, A, van Leeuwen, FE, van't Veer, L, Swerdlow, AJ, Orr, N, Dowsett, M, Easton, D, Schmidt, MK (Marjanka), Pharoah, PD, Garcia-Closas, M, Medical Oncology, and Pathology

Subjects
SDG 3 - Good Health and Well-being
Published
2016

26. Predicting the likelihood of carrying a BRCA1 or BRCA2 mutation: validation of BOADICEA, BRCAPRO, IBIS, Myriad and the Manchester scoring system using data from UK genetics clinics

Author

Douglas F. Easton, Patrick J. Morrison, J. Scott, Diana Eccles, Louise Izatt, D G R Evans, Antonis C. Antoniou, Fiona Douglas, A Shenton, Pharoah Pd, Leslie G. Walker, Rosalind A. Eeles, R.L. Zimmern, Rachel Hardy, Susan Shanley, Gabriella Pichert, and S. Rose

Subjects
Concordance, Genetic counseling, Genes, BRCA2, Genes, BRCA1, Breast Neoplasms, Genetic Counseling, Disease, Sensitivity and Specificity, Breast cancer, Predictive Value of Tests, Genetics, medicine, Humans, Genetic Predisposition to Disease, Genetic Testing, Family history, Genetics (clinical), Genetic testing, Ovarian Neoplasms, Ibis, Models, Statistical, medicine.diagnostic_test, biology, business.industry, medicine.disease, biology.organism_classification, ROC Curve, Mutation (genetic algorithm), Female, business, Algorithms
Abstract

Genetic testing for the breast and ovarian cancer susceptibility genes BRCA1 and BRCA2 has important implications for the clinical management of people found to carry a mutation. However, genetic testing is expensive and may be associated with adverse psychosocial effects. To provide a cost-efficient and clinically appropriate genetic counselling service, genetic testing should be targeted at those individuals most likely to carry pathogenic mutations. Several algorithms that predict the likelihood of carrying a BRCA1 or a BRCA2 mutation are currently used in clinical practice to identify such individuals.We evaluated the performance of the carrier prediction algorithms BOADICEA, BRCAPRO, IBIS, the Manchester scoring system and Myriad tables, using 1934 families seen in cancer genetics clinics in the UK in whom an index patient had been screened for BRCA1 and/or BRCA2 mutations. The models were evaluated for calibration, discrimination and accuracy of the predictions.Of the five algorithms, only BOADICEA predicted the overall observed number of mutations detected accurately (ie, was well calibrated). BOADICEA also provided the best discrimination, being significantly better (p0.05) than all models except BRCAPRO (area under the receiver operating characteristic curve statistics: BOADICEA = 0.77, BRCAPRO = 0.76, IBIS = 0.74, Manchester = 0.75, Myriad = 0.72). All models underpredicted the number of BRCA1 and BRCA2 mutations in the low estimated risk category.Carrier prediction algorithms provide a rational basis for counselling individuals likely to carry BRCA1 or BRCA2 mutations. Their widespread use would improve equity of access and the cost-effectiveness of genetic testing.

Published
2008

28. Prognostic value of automated KI67 scoring in breast cancer: a centralised evaluation of 8088 patients from 10 study groups

Author

Abubakar, M, Orr, N, Daley, F, Coulson, P, Ali, HR, Blows, F, Benitez, J, Milne, R, Brenner, H, Stegmaier, C, Mannermaa, A, Chang-Claude, J, Rudolph, A, Sinn, P, Couch, FJ, Devilee, P, Tollenaar, RAEM, Seynaeve, C, Figueroa, J, Sherman, ME, Lissowska, J, Hewitt, S, Eccles, D, Hooning, MJ, Hollestelle, A, Martens, JWM, van Deurzen, CHM, Bolla, MK, Wang, Q, Jones, M, Schoemaker, M, Wesseling, J, van Leeuwen, FE, Van 't Veer, L, Easton, D, Swerdlow, AJ, Dowsett, M, Pharoah, PD, Schmidt, MK, Garcia-Closas, M, Abubakar, M, Orr, N, Daley, F, Coulson, P, Ali, HR, Blows, F, Benitez, J, Milne, R, Brenner, H, Stegmaier, C, Mannermaa, A, Chang-Claude, J, Rudolph, A, Sinn, P, Couch, FJ, Devilee, P, Tollenaar, RAEM, Seynaeve, C, Figueroa, J, Sherman, ME, Lissowska, J, Hewitt, S, Eccles, D, Hooning, MJ, Hollestelle, A, Martens, JWM, van Deurzen, CHM, Bolla, MK, Wang, Q, Jones, M, Schoemaker, M, Wesseling, J, van Leeuwen, FE, Van 't Veer, L, Easton, D, Swerdlow, AJ, Dowsett, M, Pharoah, PD, Schmidt, MK, and Garcia-Closas, M

Abstract

BACKGROUND: The value of KI67 in breast cancer prognostication has been questioned due to concerns on the analytical validity of visual KI67 assessment and methodological limitations of published studies. Here, we investigate the prognostic value of automated KI67 scoring in a large, multicentre study, and compare this with pathologists' visual scores available in a subset of patients. METHODS: We utilised 143 tissue microarrays containing 15,313 tumour tissue cores from 8088 breast cancer patients in 10 collaborating studies. A total of 1401 deaths occurred during a median follow-up of 7.5 years. Centralised KI67 assessment was performed using an automated scoring protocol. The relationship of KI67 levels with 10-year breast cancer specific survival (BCSS) was investigated using Kaplan-Meier survival curves and Cox proportional hazard regression models adjusted for known prognostic factors. RESULTS: Patients in the highest quartile of KI67 (>12 % positive KI67 cells) had a worse 10-year BCSS than patients in the lower three quartiles. This association was statistically significant for ER-positive patients (hazard ratio (HR) (95 % CI) at baseline = 1.96 (1.31-2.93); P = 0.001) but not for ER-negative patients (1.23 (0.86-1.77); P = 0.248) (P-heterogeneity = 0.064). In spite of differences in characteristics of the study populations, the estimates of HR were consistent across all studies (P-heterogeneity = 0.941 for ER-positive and P-heterogeneity = 0.866 for ER-negative). Among ER-positive cancers, KI67 was associated with worse prognosis in both node-negative (2.47 (1.16-5.27)) and node-positive (1.74 (1.05-2.86)) tumours (P-heterogeneity = 0.671). Further classification according to ER, PR and HER2 showed statistically significant associations with prognosis among hormone receptor-positive patients regardless of HER2 status (P-heterogeneity = 0.270) and among triple-negative patients (1.70 (1.02-2.84)). Model fit parameters were similar for visual and automated me

Published
2016

29. A splicing variant of TERT identified by GWAS interacts with menopausal estrogen therapy in risk of ovarian cancer

Author

Lee, AW, Bomkamp, A, Bandera, EV, Jensen, A, Ramus, SJ, Goodman, MT, Rossing, MA, Modugno, F, Moysich, KB, Chang-Claude, J, Rudolph, A, Gentry-Maharaj, A, Terry, KL, Gayther, SA, Cramer, DW, Doherty, JA, Schildkraut, JM, Kjaer, SK, Ness, RB, Menon, U, Berchuck, A, Mukherjee, B, Roman, L, Pharoah, PD, Chenevix-Trench, G, Olson, S, Hogdall, E, Wu, AH, Pike, MC, Stram, DO, Pearce, CL, Lee, AW, Bomkamp, A, Bandera, EV, Jensen, A, Ramus, SJ, Goodman, MT, Rossing, MA, Modugno, F, Moysich, KB, Chang-Claude, J, Rudolph, A, Gentry-Maharaj, A, Terry, KL, Gayther, SA, Cramer, DW, Doherty, JA, Schildkraut, JM, Kjaer, SK, Ness, RB, Menon, U, Berchuck, A, Mukherjee, B, Roman, L, Pharoah, PD, Chenevix-Trench, G, Olson, S, Hogdall, E, Wu, AH, Pike, MC, Stram, DO, and Pearce, CL

Abstract

Menopausal estrogen-alone therapy (ET) is a well-established risk factor for serous and endometrioid ovarian cancer. Genetics also plays a role in ovarian cancer, which is partly attributable to 18 confirmed ovarian cancer susceptibility loci identified by genome-wide association studies. The interplay among these loci, ET use and ovarian cancer risk has yet to be evaluated. We analyzed data from 1,414 serous cases, 337 endometrioid cases and 4,051 controls across 10 case-control studies participating in the Ovarian Cancer Association Consortium (OCAC). Conditional logistic regression was used to determine the association between the confirmed susceptibility variants and risk of serous and endometrioid ovarian cancer among ET users and non-users separately and to test for statistical interaction. A splicing variant in TERT, rs10069690, showed a statistically significant interaction with ET use for risk of serous ovarian cancer (pint = 0.013). ET users carrying the T allele had a 51% increased risk of disease (OR = 1.51, 95% CI 1.19-1.91), which was stronger for long-term ET users of 10+ years (OR = 1.85, 95% CI 1.28-2.66, pint = 0.034). Non-users showed essentially no association (OR = 1.08, 95% CI 0.96-1.21). Two additional genomic regions harboring rs7207826 (C allele) and rs56318008 (T allele) also had significant interactions with ET use for the endometrioid histotype (pint = 0.021 and pint = 0.037, respectively). Hence, three confirmed susceptibility variants were identified whose associations with ovarian cancer risk are modified by ET exposure; follow-up is warranted given that these interactions are not adjusted for multiple comparisons. These findings, if validated, may elucidate the mechanism of action of these loci.

Published
2016

30. 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

31. The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes

Author

Pereira, B, Chin, S-F, Rueda, OM, Vollan, H-KM, Provenzano, E, Bardwell, HA, Pugh, M, Jones, L, Russell, R, Sammut, S-J, Tsui, DWY, Liu, B, Dawson, S-J, Abraham, J, Northen, H, Peden, JF, Mukherjee, A, Turashvili, G, Green, AR, McKinney, S, Oloumi, A, Shah, S, Rosenfeld, N, Murphy, L, Bentley, DR, Ellis, IO, Purushotham, A, Pinder, SE, Borresen-Dale, A-L, Earl, HM, Pharoah, PD, Ross, MT, Aparicio, S, Caldas, C, Pereira, B, Chin, S-F, Rueda, OM, Vollan, H-KM, Provenzano, E, Bardwell, HA, Pugh, M, Jones, L, Russell, R, Sammut, S-J, Tsui, DWY, Liu, B, Dawson, S-J, Abraham, J, Northen, H, Peden, JF, Mukherjee, A, Turashvili, G, Green, AR, McKinney, S, Oloumi, A, Shah, S, Rosenfeld, N, Murphy, L, Bentley, DR, Ellis, IO, Purushotham, A, Pinder, SE, Borresen-Dale, A-L, Earl, HM, Pharoah, PD, Ross, MT, Aparicio, S, and Caldas, C

Abstract

The genomic landscape of breast cancer is complex, and inter- and intra-tumour heterogeneity are important challenges in treating the disease. In this study, we sequence 173 genes in 2,433 primary breast tumours that have copy number aberration (CNA), gene expression and long-term clinical follow-up data. We identify 40 mutation-driver (Mut-driver) genes, and determine associations between mutations, driver CNA profiles, clinical-pathological parameters and survival. We assess the clonal states of Mut-driver mutations, and estimate levels of intra-tumour heterogeneity using mutant-allele fractions. Associations between PIK3CA mutations and reduced survival are identified in three subgroups of ER-positive cancer (defined by amplification of 17q23, 11q13-14 or 8q24). High levels of intra-tumour heterogeneity are in general associated with a worse outcome, but highly aggressive tumours with 11q13-14 amplification have low levels of intra-tumour heterogeneity. These results emphasize the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies.

Published
2016

32. Genome-wide association study of renal cell carcinoma identifiestwo susceptibility loci on 2p21 and 11q13.3

Author

Purdue MP, Johansson M, Zelenika D, Toro JR, Scelo G, Moore LE, Prokhortchouk E, Wu X, Kiemeney LA, Gaborieau V, Jacobs KB, Chow WH, Zaridze D, Matveev V, Lubinski J, Trubicka J, Szeszenia Dabrowska N, Lissowska J, Rudnai P, Fabianova E, Bucur A, Bencko V, Foretova L, Janout V, Boffetta P, Colt JS, Davis FG, Schwartz KL, Banks RE, Selby PJ, Harnden P, Berg CD, Hsing AW, Grubb RL 3rd, Boeing H, Vineis P, Clavel Chapelon F, Palli D, Tumino R, Krogh V, Duell EJ, Quirós JR, Sanchez MJ, Navarro C, Ardanaz E, Dorronsoro M, Khaw KT, Allen NE, Bueno de Mesquita HB, Peeters PH, Trichopoulos D, Linseisen J, Ljungberg B, Overvad K, Tjønneland A, Romieu I, Riboli E, Mukeria A, Shangina O, Stevens VL, Thun MJ, Diver WR, Gapstur SM, Pharoah PD, Easton DF, Albanes D, Weinstein SJ, Virtamo J, Vatten L, Hveem K, Njølstad I, Tell GS, Stoltenberg C, Kumar R, Koppova K, Cussenot O, Benhamou S, Oosterwijk E, Vermeulen SH, Aben KK, van der Marel SL, Ye Y, Wood CG, Pu X, Mazur AM, Boulygina ES, Chekanov NN, Foglio M, Lechner D, Gut I, Heath S, Blanche H, Hutchinson A, Thomas G, Wang Z, Yeager M, Fraumeni JF Jr, Skryabin KG, McKay JD, Rothman N, Chanock SJ, Lathrop M, Brennan P., PANICO, SALVATORE, Purdue, Mp, Johansson, M, Zelenika, D, Toro, Jr, Scelo, G, Moore, Le, Prokhortchouk, E, Wu, X, Kiemeney, La, Gaborieau, V, Jacobs, Kb, Chow, Wh, Zaridze, D, Matveev, V, Lubinski, J, Trubicka, J, Szeszenia Dabrowska, N, Lissowska, J, Rudnai, P, Fabianova, E, Bucur, A, Bencko, V, Foretova, L, Janout, V, Boffetta, P, Colt, J, Davis, Fg, Schwartz, Kl, Banks, Re, Selby, Pj, Harnden, P, Berg, Cd, Hsing, Aw, Grubb RL, 3rd, Boeing, H, Vineis, P, Clavel Chapelon, F, Palli, D, Tumino, R, Krogh, V, Panico, Salvatore, Duell, Ej, Quirós, Jr, Sanchez, Mj, Navarro, C, Ardanaz, E, Dorronsoro, M, Khaw, Kt, Allen, Ne, Bueno de Mesquita, Hb, Peeters, Ph, Trichopoulos, D, Linseisen, J, Ljungberg, B, Overvad, K, Tjønneland, A, Romieu, I, Riboli, E, Mukeria, A, Shangina, O, Stevens, Vl, Thun, Mj, Diver, Wr, Gapstur, Sm, Pharoah, Pd, Easton, Df, Albanes, D, Weinstein, Sj, Virtamo, J, Vatten, L, Hveem, K, Njølstad, I, Tell, G, Stoltenberg, C, Kumar, R, Koppova, K, Cussenot, O, Benhamou, S, Oosterwijk, E, Vermeulen, Sh, Aben, Kk, van der Marel, Sl, Ye, Y, Wood, Cg, Pu, X, Mazur, Am, Boulygina, E, Chekanov, Nn, Foglio, M, Lechner, D, Gut, I, Heath, S, Blanche, H, Hutchinson, A, Thomas, G, Wang, Z, Yeager, M, Fraumeni JF, Jr, Skryabin, Kg, Mckay, Jd, Rothman, N, Chanock, Sj, Lathrop, M, and Brennan, P.

Published
2011

33. Personalized testing based on polygenic risk score is promising for more efficient population-based screening programs for common oncological diseases

Author

Paolo Peterlongo, Paolo Radice, and Pharoah Pd

Subjects
Risk, 0301 basic medicine, medicine.medical_specialty, business.industry, Hematology, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Oncology, 030220 oncology & carcinogenesis, Humans, Medicine, Polygenic risk score, Genetic Testing, Population screening, business, Intensive care medicine
Published
2016

35. 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

36. Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium

Author

Howat, WJ, Blows, FM, Provenzano, E, Brook, MN, Morris, L, Gazinska, P, Johnson, N, McDuffus, L-A, Miller, J, Sawyer, EJ, Pinder, S, van Deurzen, CHM, Jones, L, Sironen, R, Visscher, D, Caldas, C, Daley, F, Coulson, P, Broeks, A, Sanders, J, Wesseling, J, Nevanlinna, H, Fagerholm, R, Blomqvist, C, Heikkila, P, Ali, HR, Dawson, S-J, Figueroa, J, Lissowska, J, Brinton, L, Mannermaa, A, Kataja, V, Kosma, V-M, Cox, A, Brock, IW, Cross, SS, Reed, MW, Couch, FJ, Olson, JE, Devillee, P, Mesker, WE, Seyaneve, CM, Hollestelle, A, Benitez, J, Perez, JIA, Menendez, P, Bolla, MK, Easton, DF, Schmidt, MK, Pharoah, PD, Sherman, ME, Garcia-Closas, M, Howat, WJ, Blows, FM, Provenzano, E, Brook, MN, Morris, L, Gazinska, P, Johnson, N, McDuffus, L-A, Miller, J, Sawyer, EJ, Pinder, S, van Deurzen, CHM, Jones, L, Sironen, R, Visscher, D, Caldas, C, Daley, F, Coulson, P, Broeks, A, Sanders, J, Wesseling, J, Nevanlinna, H, Fagerholm, R, Blomqvist, C, Heikkila, P, Ali, HR, Dawson, S-J, Figueroa, J, Lissowska, J, Brinton, L, Mannermaa, A, Kataja, V, Kosma, V-M, Cox, A, Brock, IW, Cross, SS, Reed, MW, Couch, FJ, Olson, JE, Devillee, P, Mesker, WE, Seyaneve, CM, Hollestelle, A, Benitez, J, Perez, JIA, Menendez, P, Bolla, MK, Easton, DF, Schmidt, MK, Pharoah, PD, Sherman, ME, and Garcia-Closas, M

Abstract

Breast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large-scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65-70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa = 0.76), followed by human epidermal growth factor receptor 2 (Kappa = 0.69) and progesterone receptor (Kappa = 0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose-response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96-98%), but yielded many false positives (positive predictive value = 30-32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large-scale, quantitative scoring of immunohistochemically stained tissue microarrays available in consortia. Howeve

Published
2015

37. Ovarian cancer susceptibility alleles and risk of ovarian cancer in BRCA1 and BRCA2 mutation carriers

Author

Ramus, Susan J., Antoniou, Antonis C., Kuchenbaecker, Karoline B., Penny, Soucy, Jonathan, Beesley, Xiaoqing, Chen, Lesley, Mcguffog, Sinilnikova, Olga M., Sue, Healey, Daniel, Barrowdale, Andrew, Lee, Mads, Thomassen, Anne Marie Gerdes, Kruse, Torben A., Uffe Birk Jensen, Anne Bine Skytte, Caligo, Maria A., Annelie, Liljegren, Annika, Lindblom, Hakan, Olsson, Ulf, Kristoffersson, Marie Stenmark Askmalm, Swe Brca Melin, B., Swe, Brca, Domchek, Susan M., Domchek, Sm, Nathanson, Katherine L., Rebbeck, Timothy R., Anna, Jakubowska, Jan, Lubinski, Katarzyna, Jaworska, Katarzyna, Durda, Elzbieta, Złowocka, Jacek, Gronwald, Tomasz, Huzarski, Tomasz, Byrski, Cezary, Cybulski, Aleksandra Toloczko Grabarek, Ana, Osorio, Javier, Benitez, Mercedes, Duran, Maria Isabel Tejada, Ute, Hamann, Matti, Rookus, Van Leeuwen, Flora E., Aalfs, Cora M., Meijers Heijboer, Hanne E. J., Van Asperen, Christi J., Van Roozendaal, K. E. P., Nicoline, Hoogerbrugge, Collee, Margriet J., Margriet Collee, J., Mieke, Kriege, Hebon Van Der Luijt, R. B., Embrace, Embrace, Hebon, Susan, Peock, Debra, Frost, Ellis, Steve D., Radka, Platte, Elena, Fineberg, Gareth Evans, D., Fiona, Lalloo, Chris, Jacobs, Ros, Eeles, Julian, Adlard, Rosemarie, Davidson, Diana, Eccles, Trevor, Cole, Jackie, Cook, Joan, Paterson, Fiona, Douglas, Carole, Brewer, Shirley, Hodgson, Morrison, Patrick J., Lisa, Walker, Porteous, Mary E., John Kennedy, M., Harsh, Pathak, Godwin, Andrew K., Dominique Stoppa Lyonnet, Virginie Caux Moncoutier, Antoine Pauw, D. E., De Pauw, A., Marion Gauthier Villars, Sylvie, Mazoyer, Melanie, Leone, Alain, Calender, Christine, Lasset, Valerie, Bonadona, Agnes, Hardouin, Pascaline, Berthet, Yves Jean Bignon, Nancy, Uhrhammer, Laurence, Faivre, Catherine, Loustalot, Gemo, Saundra, Buys, Mary, Daly, Buys, Daly, S., Alex, Miron, Beth, Terry M., Mary Beth Terry, Terry, M. B., Chung, Wendy K., Esther, John M., John, Em, Melissa, Southey, David, Goldgar, Singer, Christian F., Muy Kheng Tea, Georg, Pfeiler, Anneliese Fink Retter, Hansen, Thomas V. O., Hansen, Tv, Bent, Ejlertsen, Oskar Th Johannsson, Kenneth, Offit, Tomas, Kirchhoff, Gaudet, Mia M., Joseph, Vijai, Mark, Robson, Marion, Piedmonte, Kelly Anne Phillips, Linda Van Le, Hoffman, James S., Amanda Ewart Toland, Ewart Toland, A., Marco, Montagna, Silvia, Tognazzo, Evgeny, Imyanitov, Claudine, Isaacs, Issacs, C., Ramunas, Janavicius, Conxi, Lazaro, Ignacio, Blanco, Eva, Tornero, Matilde, Navarro, Moysich, Kirsten B., Karlan, Beth Y., Jenny, Gross, Edith, Olah, Tibor, Vaszko, Soo Hwang Teo, Ganz, Patricia A., Beattie, Mary S., Dorfling, Cecelia M., Van Rensburg, Elizabeth J., Orland, Diez, Ava, Kwong, Schmutzler, Rita K., Barbara, Wappenschmidt, Christoph, Engel, Alfons, Meindl, Nina, Ditsch, Norbert, Arnold, Simone, Heidemann, Dieter, Niederacher, Sabine Preisler Adams, Dorotehea, Gadzicki, Raymonda Varon Mateeva, Helmut, Deissler, Andrea, Gehrig, Christian, Sutter, Karin, Kast, Britta, Fiebig, Dieter, Schafer, Trinidad, Caldes, Miguel De La Hoya, Heli, Nevanlinna, Kristiina, Aittomaki, Marie, Plante, Kconfab Spurdle, A. B., Kconfab, Neuhausen, Susan L., Neuhausen, Sl, Yuan Chun Ding, Xianshu, Wang, Noralane, Lindor, Zachary, Fredericksen, Shane Pankratz, V., Paolo, Peterlongo, Siranoush, Manoukian, Bernard, Peissel, Daniela, Zaffaroni, Bernardo, Bonanni, Loris, Bernard, Riccardo, Dolcetti, Laura, Papi, Ottini, Laura, Paolo, Radice, Greene, Mark H., Mai, Phuong L., Andrulis, Irene L., Gord, Glendon, Ocgn Ozcelik, H., Ocgn, Pharoah, Paul D. P., Pharoah, Pd, Gayther, Simon A., Jacques, Simard, Easton, Douglas F., Couch, Fergus J., Georgia Chenevix Trench, Behalf Of The Consortium Of Investigators Of Modifiers Of Brca1/2, O. N., Biostatistiques santé, Département biostatistiques et modélisation pour la santé et l'environnement [LBBE], Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Human Genetics, CCA -Cancer Center Amsterdam, ARD - Amsterdam Reproduction and Development, Universitat de Barcelona, Genetica & Celbiologie, MUMC+: DA KG Lab Centraal Lab (9), RS: CARIM School for Cardiovascular Diseases, RS: GROW - School for Oncology and Reproduction, and Clinical Genetics

Subjects
Oncology, endocrine system diseases, [SDV]Life Sciences [q-bio], Càncer d'ovari, DCN PAC - Perception action and control, Cohort Studies, Breast cancer, 0302 clinical medicine, brca1, brca2, Odds Ratio, Genetics (clinical), ComputingMilieux_MISCELLANEOUS, Ovarian Neoplasms, Genetics, 0303 health sciences, education.field_of_study, BRCA1 Protein, Hazard ratio, Middle Aged, 3. Good health, ovarian cancer, 030220 oncology & carcinogenesis, Female, Adult, Heterozygote, medicine.medical_specialty, Hereditary cancer and cancer-related syndromes Genetics and epigenetic pathways of disease [ONCOL 1], Population, Single-nucleotide polymorphism, Biology, Ovarian Neoplasms - genetics, Polymorphism, Single Nucleotide, Article, Càncer de mama, 03 medical and health sciences, Germline mutation, SDG 3 - Good Health and Well-being, Translational research [ONCOL 3], Ovarian cancer, Internal medicine, medicine, Humans, Genetic Predisposition to Disease, ddc:610, Genetics and epigenetic pathways of disease Translational research [NCMLS 6], education, Retrospective Studies, 030304 developmental biology, BRCA2 Protein, Hereditary cancer and cancer-related syndromes [ONCOL 1], association, Retrospective cohort study, snp, Odds ratio, BRCA1 Protein - genetics, medicine.disease, BRCA2 Protein - genetics, Mutation
Abstract

Germline mutations in BRCA1 and BRCA2 are associated with increased risks of breast and ovarian cancer. A genome-wide association study (GWAS) identified six alleles associated with risk of ovarian cancer for women in the general population. We evaluated four of these loci as potential modifiers of ovarian cancer risk for BRCA1 and BRCA2 mutation carriers. Four single-nucleotide polymorphisms (SNPs), rs10088218 (at 8q24), rs2665390 (at 3q25), rs717852 (at 2q31), and rs9303542 (at 17q21), were genotyped in 12,599 BRCA1 and 7,132 BRCA2 carriers, including 2,678 ovarian cancer cases. Associations were evaluated within a retrospective cohort approach. All four loci were associated with ovarian cancer risk in BRCA2 carriers; rs10088218 per-allele hazard ratio (HR) = 0.81 (95% CI: 0.67-0.98) P-trend = 0.033, rs2665390 HR = 1.48 (95% CI: 1.21-1.83) P-trend = 1.8 x 10(-4), rs717852 HR = 1.25 (95% CI: 1.10-1.42) P-trend = 6.6 x 10(-4), rs9303542 HR = 1.16 (95% CI: 1.02-1.33) P-trend = 0.026. Two loci were associated with ovarian cancer risk in BRCA1 carriers; rs10088218 per-allele HR = 0.89 (95% CI: 0.81-0.99) P-trend = 0.029, rs2665390 HR = 1.25 (95% CI: 1.10-1.42) P-trend = 6.1 x 10(-4). The HR estimates for the remaining loci were consistent with odds ratio estimates for the general population. The identification of multiple loci modifying ovarian cancer risk may be useful for counseling women with BRCA1 and BRCA2 mutations regarding their risk of ovarian cancer., link_to_OA_fulltext

Published
2012

38. Astronomical algorithms for automated analysis of tissue protein expression in breast cancer

Author

Ali, HR, Irwin, M, Morris, L, Dawson, S-J, Blows, FM, Provenzano, E, Mahler-Araujo, B, Pharoah, PD, Walton, NA, Brenton, JD, Caldas, C, Ali, HR, Irwin, M, Morris, L, Dawson, S-J, Blows, FM, Provenzano, E, Mahler-Araujo, B, Pharoah, PD, Walton, NA, Brenton, JD, and Caldas, C

Abstract

BACKGROUND: High-throughput evaluation of tissue biomarkers in oncology has been greatly accelerated by the widespread use of tissue microarrays (TMAs) and immunohistochemistry. Although TMAs have the potential to facilitate protein expression profiling on a scale to rival experiments of tumour transcriptomes, the bottleneck and imprecision of manually scoring TMAs has impeded progress. METHODS: We report image analysis algorithms adapted from astronomy for the precise automated analysis of IHC in all subcellular compartments. The power of this technique is demonstrated using over 2000 breast tumours and comparing quantitative automated scores against manual assessment by pathologists. RESULTS: All continuous automated scores showed good correlation with their corresponding ordinal manual scores. For oestrogen receptor (ER), the correlation was 0.82, P<0.0001, for BCL2 0.72, P<0.0001 and for HER2 0.62, P<0.0001. Automated scores showed excellent concordance with manual scores for the unsupervised assignment of cases to 'positive' or 'negative' categories with agreement rates of up to 96%. CONCLUSION: The adaptation of astronomical algorithms coupled with their application to large annotated study cohorts, constitutes a powerful tool for the realisation of the enormous potential of digital pathology.

Published
2013

39. Aurora kinase A outperforms Ki67 as a prognostic marker in ER-positive breast cancer

Author

Ali, HR, Dawson, S-J, Blows, FM, Provenzano, E, Pharoah, PD, Caldas, C, Ali, HR, Dawson, S-J, Blows, FM, Provenzano, E, Pharoah, PD, and Caldas, C

Abstract

BACKGROUND: Proliferation has emerged as a major prognostic factor in luminal breast cancer. The immunohistochemical (IHC) proliferation marker Ki67 has been most extensively investigated but has not gained widespread clinical acceptance. METHODS: We have conducted a head-to-head comparison of a panel of proliferation markers, including Ki67. Our aim was to establish the marker of the greatest prognostic utility. Tumour samples from 3093 women with breast cancer were constructed as tissue microarrays. We used IHC to detect expression of mini-chromosome maintenance protein 2, Ki67, aurora kinase A (AURKA), polo-like kinase 1, geminin and phospho-histone H3. We used a Cox proportional-hazards model to investigate the association with 10-year breast cancer-specific survival (BCSS). Missing values were resolved using multiple imputation. RESULTS: The prognostic significance of proliferation was limited to oestrogen receptor (ER)-positive breast cancer. Aurora kinase A emerged as the marker of the greatest prognostic significance in a multivariate model adjusted for the standard clinical and molecular covariates (hazard ratio 1.3; 95% confidence interval 1.1-1.5; P=0.005), outperforming all other markers including Ki67. CONCLUSION: Aurora kinase A outperforms other proliferation markers as an independent predictor of BCSS in ER-positive breast cancer. It has the potential for use in routine clinical practice.

Published
2012

40. Cancer stem cell markers in breast cancer: pathological, clinical and prognostic significance

Author

Ali, HR, Dawson, S-J, Blows, FM, Provenzano, E, Pharoah, PD, Caldas, C, Ali, HR, Dawson, S-J, Blows, FM, Provenzano, E, Pharoah, PD, and Caldas, C

Abstract

INTRODUCTION: The cancer stem cell (CSC) hypothesis states that tumours consist of a cellular hierarchy with CSCs at the apex driving tumour recurrence and metastasis. Hence, CSCs are potentially of profound clinical importance. We set out to establish the clinical relevance of breast CSC markers by profiling a large cohort of breast tumours in tissue microarrays (TMAs) using immunohistochemistry (IHC). METHODS: We included 4, 125 patients enrolled in the SEARCH population-based study with tumours represented in TMAs and classified into molecular subtype according to a validated IHC-based five-marker scheme. IHC was used to detect CD44/CD24, ALDH1A1, aldehyde dehydrogenase family 1 member A3 (ALDH1A3) and integrin alpha-6 (ITGA6). A 'Total CSC' score representing expression of all four CSC markers was also investigated. Association with breast cancer specific survival (BCSS) at 10 years was assessed using a Cox proportional-hazards model. This study was complied with REMARK criteria. RESULTS: In ER negative cases, multivariate analysis showed that ITGA6 was an independent prognostic factor with a time-dependent effect restricted to the first two years of follow-up (hazard ratio (HR) for 0 to 2 years follow-up, 2.4; 95% confidence interval (95% CI), 1.2 to 4.8; P = 0.009). The composite 'Total CSC' score carried independent prognostic significance in ER negative cases for the first four years of follow-up (HR for 0 to 4 years follow-up, 1.3; 95% CI, 1.1 to 1.6; P = 0.006). CONCLUSIONS: Breast CSC markers do not identify identical subpopulations in primary tumours. Both ITGA6 and a composite Total CSC score show independent prognostic significance in ER negative disease. The use of multiple markers to identify tumours enriched for CSCs has the greatest prognostic value. In the absence of more specific markers, we propose that the effective translation of the CSC hypothesis into patient benefit will necessitate the use of a panel of markers to robustly identify tumours

Published
2011

41. Comparison of methods for handling missing data on immunohistochemical markers in survival analysis of breast cancer

Author

Ali, AMG, Dawson, S-J, Blows, FM, Provenzano, E, Ellis, IO, Baglietto, L, Huntsman, D, Caldas, C, Pharoah, PD, Ali, AMG, Dawson, S-J, Blows, FM, Provenzano, E, Ellis, IO, Baglietto, L, Huntsman, D, Caldas, C, and Pharoah, PD

Abstract

BACKGROUND: Tissue micro-arrays (TMAs) are increasingly used to generate data of the molecular phenotype of tumours in clinical epidemiology studies, such as studies of disease prognosis. However, TMA data are particularly prone to missingness. A variety of methods to deal with missing data are available. However, the validity of the various approaches is dependent on the structure of the missing data and there are few empirical studies dealing with missing data from molecular pathology. The purpose of this study was to investigate the results of four commonly used approaches to handling missing data from a large, multi-centre study of the molecular pathological determinants of prognosis in breast cancer. PATIENTS AND METHODS: We pooled data from over 11,000 cases of invasive breast cancer from five studies that collected information on seven prognostic indicators together with survival time data. We compared the results of a multi-variate Cox regression using four approaches to handling missing data - complete case analysis (CCA), mean substitution (MS) and multiple imputation without inclusion of the outcome (MI-) and multiple imputation with inclusion of the outcome (MI+). We also performed an analysis in which missing data were simulated under different assumptions and the results of the four methods were compared. RESULTS: Over half the cases had missing data on at least one of the seven variables and 11 percent had missing data on 4 or more. The multi-variate hazard ratio estimates based on multiple imputation models were very similar to those derived after using MS, with similar standard errors. Hazard ratio estimates based on the CCA were only slightly different, but the estimates were less precise as the standard errors were large. However, in data simulated to be missing completely at random (MCAR) or missing at random (MAR), estimates for MI+ were least biased and most accurate, whereas estimates for CCA were most biased and least accurate. CONCLUSION: In

Published
2011

42. Functional Polymorphisms in the TERT Promoter Are Associated with Risk of Serous Epithelial Ovarian and Breast Cancers

Author

Zhang, L, Beesley, J, Pickett, HA, Johnatty, SE, Dunning, AM, Chen, X, Li, J, Michailidou, K, Lu, Y, Rider, DN, Palmieri, RT, Stutz, MD, Lambrechts, D, Despierre, E, Lambrechts, S, Vergote, I, Chang-Claude, J, Nickels, S, Vrieling, A, Flesch-Janys, D, Wang-Gohrke, S, Eilber, U, Bogdanova, N, Antonenkova, N, Runnebaum, IB, Doerk, T, Goodman, MT, Lurie, G, Wilkens, LR, Matsuno, RK, Kiemeney, LA, Aben, KKH, Marees, T, Massuger, LFAG, Fridley, BL, Vierkant, RA, Bandera, EV, Olson, SH, Orlow, I, Rodriguez-Rodriguez, L, Cook, LS, Le, ND, Brooks-Wilson, A, Kelemen, LE, Campbell, I, Gayther, SA, Ramus, SJ, Gentry-Maharaj, A, Menon, U, Ahmed, S, Baynes, C, Pharoah, PD, Muir, K, Lophatananon, A, Chaiwerawattana, A, Wiangnon, S, Macgregor, S, Easton, DF, Reddel, RR, Goode, EL, Chenevix-Trench, G, Zhang, L, Beesley, J, Pickett, HA, Johnatty, SE, Dunning, AM, Chen, X, Li, J, Michailidou, K, Lu, Y, Rider, DN, Palmieri, RT, Stutz, MD, Lambrechts, D, Despierre, E, Lambrechts, S, Vergote, I, Chang-Claude, J, Nickels, S, Vrieling, A, Flesch-Janys, D, Wang-Gohrke, S, Eilber, U, Bogdanova, N, Antonenkova, N, Runnebaum, IB, Doerk, T, Goodman, MT, Lurie, G, Wilkens, LR, Matsuno, RK, Kiemeney, LA, Aben, KKH, Marees, T, Massuger, LFAG, Fridley, BL, Vierkant, RA, Bandera, EV, Olson, SH, Orlow, I, Rodriguez-Rodriguez, L, Cook, LS, Le, ND, Brooks-Wilson, A, Kelemen, LE, Campbell, I, Gayther, SA, Ramus, SJ, Gentry-Maharaj, A, Menon, U, Ahmed, S, Baynes, C, Pharoah, PD, Muir, K, Lophatananon, A, Chaiwerawattana, A, Wiangnon, S, Macgregor, S, Easton, DF, Reddel, RR, Goode, EL, and Chenevix-Trench, G

Abstract

Genetic variation at the TERT-CLPTM1L locus at 5p15.33 is associated with susceptibility to several cancers, including epithelial ovarian cancer (EOC). We have carried out fine-mapping of this region in EOC which implicates an association with a single nucleotide polymorphism (SNP) within the TERT promoter. We demonstrate that the minor alleles at rs2736109, and at an additional TERT promoter SNP, rs2736108, are associated with decreased breast cancer risk, and that the combination of both SNPs substantially reduces TERT promoter activity.

Published
2011

43. A novel recurrent mutation in MITF predisposes to familial and sporadic melanoma

Author

Yokoyama, S, Woods, SL, Boyle, GM, Aoude, LG, MacGregor, S, Zismann, V, Gartside, M, Cust, AE, Haq, R, Harland, M, Taylor, JC, Duffy, DL, Holohan, K, Dutton-Regester, K, Palmer, JM, Bonazzi, V, Stark, MS, Symmons, J, Law, MH, Schmidt, C, Lanagan, C, O'Connor, L, Holland, EA, Schmid, H, Maskiell, JA, Jetann, J, Ferguson, M, Jenkins, MA, Kefford, RF, Giles, G, Armstrong, BK, Aitken, JF, Hopper, JL, Whiteman, DC, Pharoah, PD, Easton, DF, Dunning, AM, Newton-Bishop, JA, Montgomery, GW, Martin, NG, Mann, GJ, Bishop, DT, Tsao, H, Trent, JM, Fisher, DE, Hayward, NK, Brown, KM, Yokoyama, S, Woods, SL, Boyle, GM, Aoude, LG, MacGregor, S, Zismann, V, Gartside, M, Cust, AE, Haq, R, Harland, M, Taylor, JC, Duffy, DL, Holohan, K, Dutton-Regester, K, Palmer, JM, Bonazzi, V, Stark, MS, Symmons, J, Law, MH, Schmidt, C, Lanagan, C, O'Connor, L, Holland, EA, Schmid, H, Maskiell, JA, Jetann, J, Ferguson, M, Jenkins, MA, Kefford, RF, Giles, G, Armstrong, BK, Aitken, JF, Hopper, JL, Whiteman, DC, Pharoah, PD, Easton, DF, Dunning, AM, Newton-Bishop, JA, Montgomery, GW, Martin, NG, Mann, GJ, Bishop, DT, Tsao, H, Trent, JM, Fisher, DE, Hayward, NK, and Brown, KM

Abstract

So far, two genes associated with familial melanoma have been identified, accounting for a minority of genetic risk in families. Mutations in CDKN2A account for approximately 40% of familial cases, and predisposing mutations in CDK4 have been reported in a very small number of melanoma kindreds. Here we report the whole-genome sequencing of probands from several melanoma families, which we performed in order to identify other genes associated with familial melanoma. We identify one individual carrying a novel germline variant (coding DNA sequence c.G1075A; protein sequence p.E318K; rs149617956) in the melanoma-lineage-specific oncogene microphthalmia-associated transcription factor (MITF). Although the variant co-segregated with melanoma in some but not all cases in the family, linkage analysis of 31 families subsequently identified to carry the variant generated a log of odds (lod) score of 2.7 under a dominant model, indicating E318K as a possible intermediate risk variant. Consistent with this, the E318K variant was significantly associated with melanoma in a large Australian case-control sample. Likewise, it was similarly associated in an independent case-control sample from the United Kingdom. In the Australian sample, the variant allele was significantly over-represented in cases with a family history of melanoma, multiple primary melanomas, or both. The variant allele was also associated with increased naevus count and non-blue eye colour. Functional analysis of E318K showed that MITF encoded by the variant allele had impaired sumoylation and differentially regulated several MITF targets. These data indicate that MITF is a melanoma-predisposition gene and highlight the utility of whole-genome sequencing to identify novel rare variants associated with disease susceptibility.

Published
2011

44. Subtyping of Breast Cancer by Immunohistochemistry to Investigate a Relationship between Subtype and Short and Long Term Survival: A Collaborative Analysis of Data for 10,159 Cases from 12 Studies

Author

Marincola, FM, Blows, FM, Driver, KE, Schmidt, MK, Broeks, A, van Leeuwen, FE, Wesseling, J, Cheang, MC, Gelmon, K, Nielsen, TO, Blomqvist, C, Heikkila, P, Heikkinen, T, Nevanlinna, H, Akslen, LA, Begin, LR, Foulkes, WD, Couch, FJ, Wang, X, Cafourek, V, Olson, JE, Baglietto, L, Giles, GG, Severi, G, McLean, CA, Southey, MC, Rakha, E, Green, AR, Ellis, IO, Sherman, ME, Lissowska, J, Anderson, WF, Cox, A, Cross, SS, Reed, MWR, Provenzano, E, Dawson, S-J, Dunning, AM, Humphreys, M, Easton, DF, Garcia-Closas, M, Caldas, C, Pharoah, PD, Huntsman, D, Marincola, FM, Blows, FM, Driver, KE, Schmidt, MK, Broeks, A, van Leeuwen, FE, Wesseling, J, Cheang, MC, Gelmon, K, Nielsen, TO, Blomqvist, C, Heikkila, P, Heikkinen, T, Nevanlinna, H, Akslen, LA, Begin, LR, Foulkes, WD, Couch, FJ, Wang, X, Cafourek, V, Olson, JE, Baglietto, L, Giles, GG, Severi, G, McLean, CA, Southey, MC, Rakha, E, Green, AR, Ellis, IO, Sherman, ME, Lissowska, J, Anderson, WF, Cox, A, Cross, SS, Reed, MWR, Provenzano, E, Dawson, S-J, Dunning, AM, Humphreys, M, Easton, DF, Garcia-Closas, M, Caldas, C, Pharoah, PD, and Huntsman, D

Abstract

BACKGROUND: Immunohistochemical markers are often used to classify breast cancer into subtypes that are biologically distinct and behave differently. The aim of this study was to estimate mortality for patients with the major subtypes of breast cancer as classified using five immunohistochemical markers, to investigate patterns of mortality over time, and to test for heterogeneity by subtype. METHODS AND FINDINGS: We pooled data from more than 10,000 cases of invasive breast cancer from 12 studies that had collected information on hormone receptor status, human epidermal growth factor receptor-2 (HER2) status, and at least one basal marker (cytokeratin [CK]5/6 or epidermal growth factor receptor [EGFR]) together with survival time data. Tumours were classified as luminal and nonluminal tumours according to hormone receptor expression. These two groups were further subdivided according to expression of HER2, and finally, the luminal and nonluminal HER2-negative tumours were categorised according to expression of basal markers. Changes in mortality rates over time differed by subtype. In women with luminal HER2-negative subtypes, mortality rates were constant over time, whereas mortality rates associated with the luminal HER2-positive and nonluminal subtypes tended to peak within 5 y of diagnosis and then decline over time. In the first 5 y after diagnosis the nonluminal tumours were associated with a poorer prognosis, but over longer follow-up times the prognosis was poorer in the luminal subtypes, with the worst prognosis at 15 y being in the luminal HER2-positive tumours. Basal marker expression distinguished the HER2-negative luminal and nonluminal tumours into different subtypes. These patterns were independent of any systemic adjuvant therapy. CONCLUSIONS: The six subtypes of breast cancer defined by expression of five markers show distinct behaviours with important differences in short term and long term prognosis. Application of these markers in the clinical s

Published
2010

45. Familial relative risks for breast cancer by pathological subtype: a population-based cohort study

Author

Mavaddat, N, Pharoah, PD, Blows, F, Driver, KE, Provenzano, E, Thompson, D, MacInnis, RJ, Shah, M, Easton, DF, Antoniou, AC, Mavaddat, N, Pharoah, PD, Blows, F, Driver, KE, Provenzano, E, Thompson, D, MacInnis, RJ, Shah, M, Easton, DF, and Antoniou, AC

Abstract

INTRODUCTION: The risk of breast cancer to first degree relatives of breast cancer patients is approximately twice that of the general population. Breast cancer, however, is a heterogeneous disease and it is plausible that the familial relative risk (FRR) for breast cancer may differ by the pathological subtype of the tumour. The contribution of genetic variants associated with breast cancer susceptibility to the subtype-specific FRR is still unclear. METHODS: We computed breast cancer FRR for subtypes of breast cancer by comparing breast cancer incidence in relatives of breast cancer cases from a population-based series with known estrogen receptor (ER), progesterone receptor (PR) or human epidermal growth factor receptor 2 (HER2) status with that expected from the general population. We estimated the contribution to the FRR of genetic variants associated with breast cancer susceptibility using subtype-specific genotypic relative risks and allele frequencies for each variant. RESULTS: At least one marker was measured for 4,590 breast cancer cases, who reported 9,014 affected and unaffected first-degree female relatives. There was no difference between the breast cancer FRR for relatives of patients with ER-negative (FRR = 1.78, 95% confidence intervals (CI): 1.44 to 2.11) and ER-positive disease (1.82, 95% CI: 1.67 to 1.98), P = 0.99. There was some suggestion that the breast cancer FRR for relatives of patients with ER-negative disease was higher than that for ER-positive disease for ages of the relative less than 50 years old (FRR = 2.96, 95% CI: 2.04 to 3.87; and 2.05, 95% CI: 1.70 to 2.40 respectively; P = 0.07), and that the breast cancer FRR for relatives of patients with ER-positive disease was higher than for ER-negative disease when the age of the relative was greater than 50 years (FRR = 1.76, 95% CI: 1.59 to 1.93; and 1.41, 95% CI: 1.08 to 1.74 respectively, P = 0.06). We estimated that mutations in BRCA1 and BRCA2 explain 32% of breast cancer FRR for re

Published
2010

46. Evaluation of Candidate Stromal Epithelial Cross-Talk Genes Identifies Association between Risk of Serous Ovarian Cancer and TERT, a Cancer Susceptibility 'Hot-Spot'

Author

Dermitzakis, ET, Johnatty, SE, Beesley, J, Chen, X, Macgregor, S, Duffy, DL, Spurdle, AB, deFazio, A, Gava, N, Webb, PM, Rossing, MA, Doherty, JA, Goodman, MT, Lurie, G, Thompson, PJ, Wilkens, LR, Ness, RB, Moysich, KB, Chang-Claude, J, Wang-Gohrke, S, Cramer, DW, Terry, KL, Hankinson, SE, Tworoger, SS, Garcia-Closas, M, Yang, H, Lissowska, J, Chanock, SJ, Pharoah, PD, Song, H, Whitemore, AS, Pearce, CL, Stram, DO, Wu, AH, Pike, MC, Gayther, SA, Ramus, SJ, Menon, U, Gentry-Maharaj, A, Anton-Culver, H, Ziogas, A, Hogdall, E, Kjaer, SK, Hogdall, C, Berchuck, A, Schildkraut, JM, Iversen, ES, Moorman, PG, Phelan, CM, Sellers, TA, Cunningham, JM, Vierkant, RA, Rider, DN, Goode, EL, Haviv, I, Chenevix-Trench, G, Dermitzakis, ET, Johnatty, SE, Beesley, J, Chen, X, Macgregor, S, Duffy, DL, Spurdle, AB, deFazio, A, Gava, N, Webb, PM, Rossing, MA, Doherty, JA, Goodman, MT, Lurie, G, Thompson, PJ, Wilkens, LR, Ness, RB, Moysich, KB, Chang-Claude, J, Wang-Gohrke, S, Cramer, DW, Terry, KL, Hankinson, SE, Tworoger, SS, Garcia-Closas, M, Yang, H, Lissowska, J, Chanock, SJ, Pharoah, PD, Song, H, Whitemore, AS, Pearce, CL, Stram, DO, Wu, AH, Pike, MC, Gayther, SA, Ramus, SJ, Menon, U, Gentry-Maharaj, A, Anton-Culver, H, Ziogas, A, Hogdall, E, Kjaer, SK, Hogdall, C, Berchuck, A, Schildkraut, JM, Iversen, ES, Moorman, PG, Phelan, CM, Sellers, TA, Cunningham, JM, Vierkant, RA, Rider, DN, Goode, EL, Haviv, I, and Chenevix-Trench, G

Abstract

We hypothesized that variants in genes expressed as a consequence of interactions between ovarian cancer cells and the host micro-environment could contribute to cancer susceptibility. We therefore used a two-stage approach to evaluate common single nucleotide polymorphisms (SNPs) in 173 genes involved in stromal epithelial interactions in the Ovarian Cancer Association Consortium (OCAC). In the discovery stage, cases with epithelial ovarian cancer (n=675) and controls (n=1,162) were genotyped at 1,536 SNPs using an Illumina GoldenGate assay. Based on Positive Predictive Value estimates, three SNPs-PODXL rs1013368, ITGA6 rs13027811, and MMP3 rs522616-were selected for replication using TaqMan genotyping in up to 3,059 serous invasive cases and 8,905 controls from 16 OCAC case-control studies. An additional 18 SNPs with Pper-allele<0.05 in the discovery stage were selected for replication in a subset of five OCAC studies (n=1,233 serous invasive cases; n=3,364 controls). The discovery stage associations in PODXL, ITGA6, and MMP3 were attenuated in the larger replication set (adj. Pper-allele>or=0.5). However genotypes at TERT rs7726159 were associated with ovarian cancer risk in the smaller, five-study replication study (Pper-allele=0.03). Combined analysis of the discovery and replication sets for this TERT SNP showed an increased risk of serous ovarian cancer among non-Hispanic whites [adj. ORper-allele 1.14 (1.04-1.24) p=0.003]. Our study adds to the growing evidence that, like the 8q24 locus, the telomerase reverse transcriptase locus at 5p15.33, is a general cancer susceptibility locus.

Published
2010

47. A large-scale meta-analysis to refine colorectal cancer risk estimates associated with MUTYH variants

Author

Theodoratou, E, Campbell, H, Tenesa, A, Houlston, R, Webb, E, Lubbe, S, Broderick, P, Gallinger, S, Croitoru, EM, Jenkins, MA, Win, AK, Cleary, SP, Koessler, T, Pharoah, PD, Kuery, S, Bezieau, S, Buecher, B, Ellis, NA, Peterlongo, P, Offit, K, Aaltonen, LA, Enholm, S, Lindblom, A, Zhou, X-L, Tomlinson, IP, Moreno, V, Blanco, I, Capella, G, Barnetson, R, Porteous, ME, Dunlop, MG, Farrington, SM, Theodoratou, E, Campbell, H, Tenesa, A, Houlston, R, Webb, E, Lubbe, S, Broderick, P, Gallinger, S, Croitoru, EM, Jenkins, MA, Win, AK, Cleary, SP, Koessler, T, Pharoah, PD, Kuery, S, Bezieau, S, Buecher, B, Ellis, NA, Peterlongo, P, Offit, K, Aaltonen, LA, Enholm, S, Lindblom, A, Zhou, X-L, Tomlinson, IP, Moreno, V, Blanco, I, Capella, G, Barnetson, R, Porteous, ME, Dunlop, MG, and Farrington, SM

Abstract

BACKGROUND: defective DNA repair has a causal role in hereditary colorectal cancer (CRC). Defects in the base excision repair gene MUTYH are responsible for MUTYH-associated polyposis and CRC predisposition as an autosomal recessive trait. Numerous reports have suggested MUTYH mono-allelic variants to be low penetrance risk alleles. We report a large collaborative meta-analysis to assess and refine CRC risk estimates associated with bi-allelic and mono-allelic MUTYH variants and investigate age and sex influence on risk. METHODS: MUTYH genotype data were included from 20 565 cases and 15 524 controls. Three logistic regression models were tested: a crude model; adjusted for age and sex; adjusted for age, sex and study. RESULTS: all three models produced very similar results. MUTYH bi-allelic carriers demonstrated a 28-fold increase in risk (95% confidence interval (CI): 6.95-115). Significant bi-allelic effects were also observed for G396D and Y179C/G396D compound heterozygotes and a marginal mono-allelic effect for variant Y179C (odds ratio (OR)=1.34; 95% CI: 1.00-1.80). A pooled meta-analysis of all published and unpublished datasets submitted showed bi-allelic effects for MUTYH, G396D and Y179C (OR=10.8, 95% CI: 5.02-23.2; OR=6.47, 95% CI: 2.33-18.0; OR=3.35, 95% CI: 1.14-9.89) and marginal mono-allelic effect for variants MUTYH (OR=1.16, 95% CI: 1.00-1.34) and Y179C alone (OR=1.34, 95% CI: 1.01-1.77). CONCLUSIONS: overall, this large study refines estimates of disease risk associated with mono-allelic and bi-allelic MUTYH carriers.

Published
2010

48. Heterogeneity of breast cancer associations with five susceptibility loci by clinical and pathological characteristics

Author

Leal, SM, Garcia-Closas, M, Hall, P, Nevanlinna, H, Pooley, K, Morrison, J, Richesson, DA, Bojesen, SE, Nordestgaard, BG, Axelsson, CK, Arias, JI, Milne, RL, Ribas, G, Gonzalez-Neira, A, Benitez, J, Zamora, P, Brauch, H, Justenhoven, C, Hamann, U, Ko, Y-D, Bruening, T, Haas, S, Doerk, T, Schuermann, P, Hillemanns, P, Bogdanova, N, Bremer, M, Karstens, JH, Fagerholm, R, Aaltonen, K, Aittomaki, K, Von Smitten, K, Blomqvist, C, Mannermaa, A, Uusitupa, M, Eskelinen, M, Tengstrom, M, Kosma, V-M, Kataja, V, Chenevix-Trench, G, Spurdle, AB, Beesley, J, Chen, X, Devilee, P, Van Asperen, CJ, Jacobi, CE, Tollenaar, RAEM, Huijts, PEA, Klijn, JGM, Chang-Claude, J, Kropp, S, Slanger, T, Flesch-Janys, D, Mutschelknauss, E, Salazar, R, Wang-Gohrke, S, Couch, F, Goode, EL, Olson, JE, Vachon, C, Fredericksen, ZS, Giles, GG, Baglietto, L, Severi, G, Hopper, JL, English, DR, Southey, MC, Haiman, CA, Henderson, BE, Kolonel, LN, Le Marchand, L, Stram, DO, Hunter, DJ, Hankinson, SE, Cox, DG, Tamimi, R, Kraft, P, Sherman, ME, Chanock, SJ, Lissowska, J, Brinton, LA, Peplonska, B, Hooning, MJ, Meijers-Heijboer, H, Collee, JM, Van den Ouweland, A, Uitterlinden, AG, Liu, J, Lin, LY, Yuqing, L, Humphreys, K, Czene, K, Cox, A, Balasubramanian, SP, Cross, SS, Reed, MWR, Blows, F, Driver, K, Dunning, A, Tyrer, J, Ponder, BAJ, Sangrajrang, S, Brennan, P, Mckay, J, Odefrey, F, Gabrieau, V, Sigurdson, A, Doody, M, Struewing, JP, Alexander, B, Easton, DF, Pharoah, PD, Leal, SM, Garcia-Closas, M, Hall, P, Nevanlinna, H, Pooley, K, Morrison, J, Richesson, DA, Bojesen, SE, Nordestgaard, BG, Axelsson, CK, Arias, JI, Milne, RL, Ribas, G, Gonzalez-Neira, A, Benitez, J, Zamora, P, Brauch, H, Justenhoven, C, Hamann, U, Ko, Y-D, Bruening, T, Haas, S, Doerk, T, Schuermann, P, Hillemanns, P, Bogdanova, N, Bremer, M, Karstens, JH, Fagerholm, R, Aaltonen, K, Aittomaki, K, Von Smitten, K, Blomqvist, C, Mannermaa, A, Uusitupa, M, Eskelinen, M, Tengstrom, M, Kosma, V-M, Kataja, V, Chenevix-Trench, G, Spurdle, AB, Beesley, J, Chen, X, Devilee, P, Van Asperen, CJ, Jacobi, CE, Tollenaar, RAEM, Huijts, PEA, Klijn, JGM, Chang-Claude, J, Kropp, S, Slanger, T, Flesch-Janys, D, Mutschelknauss, E, Salazar, R, Wang-Gohrke, S, Couch, F, Goode, EL, Olson, JE, Vachon, C, Fredericksen, ZS, Giles, GG, Baglietto, L, Severi, G, Hopper, JL, English, DR, Southey, MC, Haiman, CA, Henderson, BE, Kolonel, LN, Le Marchand, L, Stram, DO, Hunter, DJ, Hankinson, SE, Cox, DG, Tamimi, R, Kraft, P, Sherman, ME, Chanock, SJ, Lissowska, J, Brinton, LA, Peplonska, B, Hooning, MJ, Meijers-Heijboer, H, Collee, JM, Van den Ouweland, A, Uitterlinden, AG, Liu, J, Lin, LY, Yuqing, L, Humphreys, K, Czene, K, Cox, A, Balasubramanian, SP, Cross, SS, Reed, MWR, Blows, F, Driver, K, Dunning, A, Tyrer, J, Ponder, BAJ, Sangrajrang, S, Brennan, P, Mckay, J, Odefrey, F, Gabrieau, V, Sigurdson, A, Doody, M, Struewing, JP, Alexander, B, Easton, DF, and Pharoah, PD

Abstract

A three-stage genome-wide association study recently identified single nucleotide polymorphisms (SNPs) in five loci (fibroblast growth receptor 2 (FGFR2), trinucleotide repeat containing 9 (TNRC9), mitogen-activated protein kinase 3 K1 (MAP3K1), 8q24, and lymphocyte-specific protein 1 (LSP1)) associated with breast cancer risk. We investigated whether the associations between these SNPs and breast cancer risk varied by clinically important tumor characteristics in up to 23,039 invasive breast cancer cases and 26,273 controls from 20 studies. We also evaluated their influence on overall survival in 13,527 cases from 13 studies. All participants were of European or Asian origin. rs2981582 in FGFR2 was more strongly related to ER-positive (per-allele OR (95%CI) = 1.31 (1.27-1.36)) than ER-negative (1.08 (1.03-1.14)) disease (P for heterogeneity = 10(-13)). This SNP was also more strongly related to PR-positive, low grade and node positive tumors (P = 10(-5), 10(-8), 0.013, respectively). The association for rs13281615 in 8q24 was stronger for ER-positive, PR-positive, and low grade tumors (P = 0.001, 0.011 and 10(-4), respectively). The differences in the associations between SNPs in FGFR2 and 8q24 and risk by ER and grade remained significant after permutation adjustment for multiple comparisons and after adjustment for other tumor characteristics. Three SNPs (rs2981582, rs3803662, and rs889312) showed weak but significant associations with ER-negative disease, the strongest association being for rs3803662 in TNRC9 (1.14 (1.09-1.21)). rs13281615 in 8q24 was associated with an improvement in survival after diagnosis (per-allele HR = 0.90 (0.83-0.97). The association was attenuated and non-significant after adjusting for known prognostic factors. Our findings show that common genetic variants influence the pathological subtype of breast cancer and provide further support for the hypothesis that ER-positive and ER-negative disease are biologically distinct. Understanding

Published
2008

Catalog

Books, media, physical & digital resources
See catalog results