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5 results on '"Eccles, Diana M [0000-0002-9935-3169]"'

1. Cancer Variant Interpretation Group UK (CanVIG-UK): an exemplar national subspecialty multidisciplinary network

Author

Andrew J Wallace, Diana Eccles, Lucy Side, Diana Baralle, Gail Norbury, Marc Tischkowitz, Helen Hanson, Rachel Robinson, D. Gareth Evans, George J Burghel, Cankut Çubuk, Alice Garrett, Treena Cranston, Sabrina Talukdar, Sheila Palmer-Smith, Emma R. Woodward, Alison Callaway, Fiona Lalloo, James Drummond, Ian R. Berry, Sian Ellard, Louise Izatt, Miranda Durkie, Clare Turnbull, Mary Alikian, Garrett, Alice [0000-0001-8942-283X], Burghel, George J [0000-0001-9360-8194], Berry, Ian R [0000-0002-9710-4724], Eccles, Diana M [0000-0002-9935-3169], Evans, D Gareth [0000-0002-8482-5784], Turnbull, Clare [0000-0002-1734-5772], and Apollo - University of Cambridge Repository

Subjects
0301 basic medicine, Male, medicine.medical_specialty, Service (systems architecture), Subspecialty, 03 medical and health sciences, 0302 clinical medicine, Multidisciplinary approach, Neoplasms, medicine, Cancer Genetics, Humans, genetics, guidelines, Genetic Testing, Genetics (clinical), business.industry, Interpretation (philosophy), Genetic Variation, High-Throughput Nucleotide Sequencing, Geneticist, Genomics, United Kingdom, Data sharing, 030104 developmental biology, 030220 oncology & carcinogenesis, Family medicine, molecular genetics, oncology, Medical genetics, Female, Personalized medicine, business, Psychology, Ireland, clinical genetics
Abstract

Advances in technology have led to a massive expansion in the capacity for genomic analysis, with a commensurate fall in costs. The clinical indications for genomic testing have evolved markedly; the volume of clinical sequencing has increased dramatically; and the range of clinical professionals involved in the process has broadened. There is general acceptance that our early dichotomous paradigms of variants being pathogenic–high risk and benign–no risk are overly simplistic. There is increasing recognition that the clinical interpretation of genomic data requires significant expertise in disease–gene-variant associations specific to each disease area. Inaccurate interpretation can lead to clinical mismanagement, inconsistent information within families and misdirection of resources. It is for this reason that ‘national subspecialist multidisciplinary meetings’ (MDMs) for genomic interpretation have been articulated as key for the new NHS Genomic Medicine Service, of which Cancer Variant Interpretation Group UK (CanVIG-UK) is an early exemplar. CanVIG-UK was established in 2017 and now has >100 UK members, including at least one clinical diagnostic scientist and one clinical cancer geneticist from each of the 25 regional molecular genetics laboratories of the UK and Ireland. Through CanVIG-UK, we have established national consensus around variant interpretation for cancer susceptibility genes via monthly national teleconferenced MDMs and collaborative data sharing using a secure online portal. We describe here the activities of CanVIG-UK, including exemplar outputs and feedback from the membership.

Published
2020
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2. Polygenic Risk Modelling for Prediction of Epithelial Ovarian Cancer Risk

Author

V. Wendy Setiawan, Ana Osorio, Liv Cecilie Vestrheim Thomsen, Francesca Gensini, Harsha Pathak, Barbara Wappenschmidt, Ingo B. Runnebaum, Javier Benitez, Rita K. Schmutzler, Jeffrey N. Weitzel, Yin Ling Woo, Kenneth Offit, Anthony N. Karnezis, Eitan Friedman, Jacques Simard, James M. Flanagan, Pedro Pérez-Segura, Siranoush Manoukian, Melissa C. Southey, Ramunas Janavicius, Finn Cilius Nielsen, Graham G. Giles, Usha Menon, Ava Kwong, Anna H. Wu, Thomas Hansen, Cristina Rodríguez-Antona, Maria A. Caligo, Argyrios Ziogas, Allison DePersia, Anna P. Sokolenko, Clarice R. Weinberg, Hoda Anton-Culver, Digna R. Velez Edwards, Jennifer B. Permuth, Patricia A. Ganz, Ana Vega, Keitaro Matsuo, Heli Nevanlinna, Frances Wang, Natalia Antonenkova, Claudine Isaacs, Conxi Lázaro, Melissa C. Larson, Henriette Roed Nielsen, Byoung-Gie Kim, Andreas du Bois, Dale P. Sandler, Anna Jakubowska, Paul D.P. Pharoah, Jenny Lester, Paolo Radice, Natalia Bogdanova, Lambertus A. Kiemeney, Mary Anne Rossing, Thilo Dörk, Ruea-Yea Huang, Judy Garber, Taymaa May, Diana Eccles, Mary Beth Terry, Jenny Chang-Claude, Jeffrey R. Marks, Dominique Stoppa-Lyonnet, Heather Eliassen, Douglas A. Levine, Phuong L. Mai, Gerasimos Aravantinos, Hui Cai, Britton Trabert, Amanda Black, Noura Mebirouk, Robin de Putter, Rayna K. Matsuno, Ralf Bützow, Joanne Ngeow Yuen Yie, James D. Brenton, Nadine Tung, Drakoulis Yannoukakos, Jonathan Tyrer, L Yan, Yen Y. Tan, Ian Komenaka, Simona Agata, Honglin Song, Tanja Pejovic, Marjorie J. Riggan, Antonis C. Antoniou, Katja K.H. Aben, Goska Leslie, Eric A. Ross, Estrid Høgdall, Kang Shan, Holly R. Harris, Eleanor Davies, Liene Nikitina-Zake, Florian Heitz, Stephen J. Chanock, Matthew Jones, Beth Y. Karlan, Matthias W. Beckmann, Penelope M. Webb, John L. Hopper, Peter A. Fasching, Jacek Gronwald, kConFab Investigators, Ana Peixoto, Joellen M. Schildkraut, Renée T. Fortner, Susan L. Neuhausen, Daehee Kang, Anthony J. Swerdlow, Lesley McGuffog, Marco Montagna, Paolo Peterlongo, Daniel R. Barnes, Marina Bermisheva, Alicja Wolk, Yuan Chun Ding, Marc Tischkowitz, Gord Glendon, Elza Khusnutdinova, Julie M. Cunningham, Saundra S. Buys, Albina N. Minlikeeva, Jennifer A. Doherty, Annemieke H. van der Hout, Austin Miller, Fergus J. Couch, Fabienne Lesueur, Peter Devilee, Kristin K. Zorn, Daniel Barrowdale, Christian F. Singer, Line Bjørge, Åke Borg, Diether Lambrechts, Shelley S. Tworoger, Allan Jensen, Ute Hamann, Douglas F. Easton, Bernardo Bonanni, Alvaro N.A. Monteiro, Johanna Rantala, Marc T. Goodman, Ellen Valen, Wei Zheng, Thomas A. Sellers, Marcus Q. Bernardini, Alice S. Whittemore, Kunle Odunsi, Inge Søkilde Pedersen, Laura Papi, Mads Thomassen, Allison W. Kurian, Emily White, Penny Soucy, D. Gareth Evans, Lenka Foretova, Kathryn L. Terry, Ruth C. Travis, Claus Høgdall, Hebon Investigators, Darya Prokofyeva, Stacey J. Winham, Yoke-Eng Chiew, Eileen Dareng, Jan Lubinski, Elizabeth Munro, Oskar T. Johannsson, Linda E. Kelemen, Kexin Chen, Xin Yang, Manuel R. Teixeira, Anna M. Piskorz, Edith Olah, Helen Steed, Beth N. Peshkin, Georgia Chenevix-Trench, Andrew K. Godwin, Pamela J. Thompson, Chad D. Huff, Rosa B. Barkardottir, Muriel A. Adank, Mikael Hartman, Linda J. Titus, Weiva Sieh, Simon A. Gayther, Peter J. Hulick, Michael T. Parsons, Elisa V. Bandera, Amanda E. Toland, Miguel de la Hoya, Orland Diez, Alicia Beeghly-Fadiel, Rebecca Sutphen, Francesmary Modugno, Judith Balmaña, Christoph Engel, Harvey A. Risch, Elizabeth J. van Rensburg, Michael Jones, Rikki Cannioto, Michelle A.T. Hildebrandt, Soo Hwang Teo, Fanny Dao, Susan J. Ramus, Sarah Colanna, Kathleen Claes, David G. Huntsman, Siel Olbrecht, Esther M. John, Robert A. Vierkant, Wendy K. Chung, Ellen L. Goode, Olufunmilayo I. Olopade, Evgeny N. Imyanitov, Joe Dennis, Andrew Berchuck, Banu Arun, Darcy L. Thull, Lian Li, Celeste Leigh Pearce, Sue K. Park, Susan M. Domchek, Agnieszka Budzilowska, Håkan Olsson, Susanne K. Kjaer, Mark H. Greene, Katia M. Zavaglia, Jolanta Kupryjanczyk, Nicolas Wentzensen, Karen H. Lu, Hayley Cassingham, Christopher A. Haiman, Eric Hahnen, Els Van Nieuwenhuysen, Katherine L. Nathanson, Anna deFazio, Ian G. Campbell, Paul A. James, Sara H. Olson, Eva Machackova, Anne M. van Altena, Irene L. Andrulis, Linda S. Cook, Matthias Dürst, Mary B. Daly, John R. McLaughlin, Niclas Håkansson, Jingmei Li, Diana Torres, Iain A. McNeish, Jennifer T. Loud, Roger L. Milne, Marta Santamariña, Annelie Augustinsson, Nhu D. Le, Kate Lawrenson, Kirsten B. Moysich, Dareng, Eileen O [0000-0003-0802-419X], Tyrer, Jonathan [0000-0003-3724-4757], Barnes, Daniel [0000-0002-3781-7570], Jones, Michelle R [0000-0001-5466-3844], Agata, Simona [0000-0002-6329-0768], Anton-Culver, Hoda [0000-0002-9603-0110], Augustinsson, Annelie [0000-0003-3415-0536], Bandera, Elisa V [0000-0002-8789-2755], Barkardottir, Rosa B [0000-0003-0629-2772], Brenton, James [0000-0002-5738-6683], Campbell, Ian [0000-0002-7773-4155], Chen, Kexin [0000-0003-1010-8093], Chung, Wendy K [0000-0003-3438-5685], Claes, Kathleen BM [0000-0003-0841-7372], Devilee, Peter [0000-0002-8023-2009], Diez, Orland [0000-0001-7339-0570], Bois, Andreas du [0000-0002-8477-506X], Eccles, Diana M [0000-0002-9935-3169], Eliassen, Heather A [0000-0002-3961-6609], Ganz, Patricia A [0000-0002-1841-4143], Giles, Graham G [0000-0003-4946-9099], Glendon, Gord [0000-0001-8630-6673], Greene, Mark H [0000-0003-1852-9239], Hartman, Mikael [0000-0001-5726-9965], Heitz, Florian [0000-0002-2412-0352], Isaacs, Claudine [0000-0002-9646-1260], Janavicius, Ramunas [0000-0002-3773-8485], John, Esther M [0000-0003-3259-8003], Kang, Daehee [0000-0003-4031-5878], Karlan, Beth Y [0000-0002-9451-2933], Khusnutdinova, Elza [0000-0003-2987-3334], Kjaer, Susanne K [0000-0002-8347-1398], Manoukian, Siranoush [0000-0002-6034-7562], Matsuo, Keitaro [0000-0003-1761-6314], Menon, Usha [0000-0003-3708-1732], Miller, Austin [0000-0001-9739-8462], Nikitina-Zake, Liene [0000-0003-2491-5187], Olbrecht, Siel [0000-0001-9452-5905], Olopade, Olufunmilayo I [0000-0002-9936-1599], Olson, Sara H [0000-0003-0182-2754], Papi, Laura [0000-0003-4552-9517], Park, Sue K [0000-0001-5002-9707], Parsons, Michael T [0000-0003-3242-8477], Permuth, Jennifer B [0000-0002-4726-9264], Peterlongo, Paolo [0000-0001-6951-6855], Radice, Paolo [0000-0001-6298-4111], Swerdlow, Anthony J [0000-0001-5550-4159], Toland, Amanda E [0000-0002-0271-1792], Webb, Penelope M [0000-0003-0733-5930], Weinberg, Clarice R [0000-0002-7713-8556], Weitzel, Jeffrey N [0000-0001-6714-092X], Winham, Stacey J [0000-0002-8492-9102], Wolk, Alicja [0000-0001-7387-6845], Yannoukakos, Drakoulis [0000-0001-7509-3510], Easton, Douglas [0000-0003-2444-3247], Ramus, Susan J [0000-0003-0005-7798], Chenevix-Trench, Georgia [0000-0002-1878-2587], and Apollo - University of Cambridge Repository

Subjects
Oncology, medicine.medical_specialty, 45/61, 45/43, Single-nucleotide polymorphism, Logistic regression, 631/208/2489, 03 medical and health sciences, 0302 clinical medicine, Lasso (statistics), Internal medicine, Genotype, medicine, SNP, 030304 developmental biology, 0303 health sciences, business.industry, Hazard ratio, article, Odds ratio, 631/208/721, medicine.disease, 3. Good health, 030220 oncology & carcinogenesis, business, Ovarian cancer, 692/499
Abstract

Funder: Funding details are provided in the Supplementary Material, Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally-efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, ���select and shrink for summary statistics��� (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestry; 7,669 women of East Asian ancestry; 1,072 women of African ancestry, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestry. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38(95%CI:1.28���1.48,AUC:0.588) per unit standard deviation, in women of European ancestry; 1.14(95%CI:1.08���1.19,AUC:0.538) in women of East Asian ancestry; 1.38(95%CI:1.21-1.58,AUC:0.593) in women of African ancestry; hazard ratios of 1.37(95%CI:1.30���1.44,AUC:0.592) in BRCA1 pathogenic variant carriers and 1.51(95%CI:1.36-1.67,AUC:0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.

Published
2022
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3. Combining evidence for and against pathogenicity for variants in cancer susceptibility genes: CanVIG-UK consensus recommendations

Author

Alison Callaway, Rachel Robinson, Cankut Çubuk, Sian Ellard, Bethany Torr, Clare Turnbull, George J Burghel, Diana Eccles, Miranda Durkie, Helen Hanson, Marc Tischkowitz, James Drummond, Ian R. Berry, Alice Garrett, Andrew J Wallace, Garrett, Alice [0000-0001-8942-283X], Burghel, George J [0000-0001-9360-8194], Berry, Ian R [0000-0002-9710-4724], Eccles, Diana M [0000-0002-9935-3169], and Apollo - University of Cambridge Repository

Subjects
0301 basic medicine, medicine.medical_specialty, Genomics, Computational biology, 030105 genetics & heredity, Biology, medical, genetic testing, 03 medical and health sciences, Neoplasms, medicine, genomics, Humans, genetics, Genetic Predisposition to Disease, Gene, Genetics (clinical), Genetic testing, Evidence-Based Medicine, medicine.diagnostic_test, Cancer susceptibility, Cancer, Genetic Variation, Geneticist, medicine.disease, Pathogenicity, 030104 developmental biology, Medical genetics, Genes, Neoplasm
Abstract

Accurate classification of variants in cancer susceptibility genes (CSGs) is key for correct estimation of cancer risk and management of patients. Consistency in the weighting assigned to individual elements of evidence has been much improved by the American College of Medical Genetics (ACMG) 2015 framework for variant classification, UK Association for Clinical Genomic Science (UK-ACGS) Best Practice Guidelines and subsequent Cancer Variant Interpretation Group UK (CanVIG-UK) consensus specification for CSGs. However, considerable inconsistency persists regarding practice in the combination of evidence elements. CanVIG-UK is a national subspecialist multidisciplinary network for cancer susceptibility genomic variant interpretation, comprising clinical scientist and clinical geneticist representation from each of the 25 diagnostic laboratories/clinical genetic units across the UK and Republic of Ireland. Here, we summarise the aggregated evidence elements and combinations possible within different variant classification schemata currently employed for CSGs (ACMG, UK-ACGS, CanVIG-UK and ClinGen gene-specific guidance for PTEN, TP53 and CDH1). We present consensus recommendations from CanVIG-UK regarding (1) consistent scoring for combinations of evidence elements using a validated numerical ‘exponent score’ (2) new combinations of evidence elements constituting likely pathogenic’ and ‘pathogenic’ classification categories, (3) which evidence elements can and cannot be used in combination for specific variant types and (4) classification of variants for which there are evidence elements for both pathogenicity and benignity.

Published
2020
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4. Psychosocial effects of whole-body MRI screening in adult high-risk pathogenic TP53 mutation carriers: A case-controlled study (SIGNIFY)

Author

Lucy Side, Emma Brown, Alexander Dias, Lauren Limb, Helen Hanson, Anthony Chamberlain, Sarah Benafif, Jeanette Rothwell, D. Gareth Evans, S. Aslam Sohaib, Rosalind A. Eeles, Jennifer Pope, Sibel Saya, Lisa Walker, Natalie Taylor, Richard W. Whitehouse, Diana Eccles, Christos Mikropoulos, Julian Barwell, Elizabeth Page, Martin O. Leach, Elizabeth Bancroft, Sarah Thomas, Balashanmugam Rajashanker, Dow-Mu Koh, Alan Donaldson, Susan Shanley, Jackie Cook, David J. Gallagher, Fiona J. Gilbert, Louise Izatt, Leslie G. Walker, Vicki Wiles, Bancroft, Elizabeth K [0000-0002-5482-5660], Saya, Sibel [0000-0002-4796-6852], Eccles, Diana M [0000-0002-9935-3169], Evans, D Gareth [0000-0002-8482-5784], and Apollo - University of Cambridge Repository

Subjects
0301 basic medicine, psychosocial, Male, Li-Fraumeni Syndrome, TP53 gene pathogenic variant, 0302 clinical medicine, Risk Factors, Neoplasms, Whole Body Imaging, Young adult, Genetics (clinical), media_common, education.field_of_study, Middle Aged, Magnetic Resonance Imaging, 030220 oncology & carcinogenesis, Cohort, Screening, Female, Worry, Psychosocial, MRI, Adult, medicine.medical_specialty, Heterozygote, media_common.quotation_subject, Population, case controlled study, Case controlled study, Stress, 03 medical and health sciences, Young Adult, Breast cancer, Internal medicine, Genetics, medicine, Cancer Genetics, Humans, Genetic Predisposition to Disease, education, Germ-Line Mutation, business.industry, Case-control study, Cancer, medicine.disease, 030104 developmental biology, Tumor Suppressor Protein p53, business
Abstract

BackgroundGermline TP53 gene pathogenic variants (pv) cause a very high lifetime risk of developing cancer, almost 100% for women and 75% for men. In the UK, annual MRI breast screening is recommended for female TP53 pv carriers. The SIGNIFY study (Magnetic Resonance Imaging screening in Li Fraumeni syndrome: An exploratory whole body MRI) study reported outcomes of whole-body MRI (WB-MRI) in a cohort of 44 TP53 pv carriers and 44 matched population controls. The results supported the use of a baseline WB-MRI screen in all adult TP53 pv carriers. Here we report the acceptability of WB-MRI screening and effects on psychosocial functioning and health-related quality of life in the short and medium terms.MethodsPsychosocial and other assessments were carried out at study enrolment, immediately before MRI, before and after MRI results, and at 12, 26 and 52 weeks’ follow-up.ResultsWB-MRI was found to be acceptable with high levels of satisfaction and low levels of psychological morbidity throughout. Although their mean levels of cancer worry were not high, carriers had significantly more cancer worry at most time-points than controls. They also reported significantly more clinically significant intrusive and avoidant thoughts about cancer than controls at all time-points. There were no clinically significant adverse psychosocial outcomes in either carriers with a history of cancer or in those requiring further investigations.ConclusionWB-MRI screening can be implemented in TP53 pv carriers without adverse psychosocial outcomes in the short and medium terms. A previous cancer diagnosis may predict a better psychosocial outcome. Some carriers seriously underestimate their risk of cancer. Carriers of pv should have access to a clinician to help them develop adaptive strategies to cope with cancer-related concerns and respond to clinically significant depression and/or anxiety.

Published
2020
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5. Towards controlled terminology for reporting germline cancer susceptibility variants: an ENIGMA report

Author

Arjen R. Mensenkamp, Paolo Radice, Mark E. Robson, Emma Tudini, Amanda B. Spurdle, Susan M. Domchek, Melissa A. Brown, Logan C. Walker, Miguel de la Hoya, Sean V. Tavtigian, Diana Eccles, Leslie Burke, Thilo Dörk, Clare Turnbull, Antonis C. Antoniou, Michael T. Parsons, Stephanie Greville-Heygate, Maaike P.G. Vreeswijk, Marc Tischkowitz, Alvaro N.A. Monteiro, Helen V. Firth, Spurdle, Amanda B [0000-0003-1337-7897], de la Hoya, Miguel [0000-0002-8113-1410], Parsons, Michael T [0000-0003-3242-8477], Radice, Paolo [0000-0001-6298-4111], Eccles, Diana M [0000-0002-9935-3169], and Apollo - University of Cambridge Repository

Subjects
0301 basic medicine, genetic variant, Vocabulary, media_common.quotation_subject, Genes, BRCA2, Genes, BRCA1, Computational biology, Biology, 03 medical and health sciences, symbols.namesake, 0302 clinical medicine, All institutes and research themes of the Radboud University Medical Center, International Classification of Diseases, Terminology as Topic, Genetic variation, Controlled vocabulary, Genetics, medicine, Biomarkers, Tumor, Humans, Genetic Predisposition to Disease, Genetics (clinical), interpretation, Germ-Line Mutation, Genetic testing, media_common, vocabulary, reporting, Massive parallel sequencing, Women's cancers Radboud Institute for Molecular Life Sciences [Radboudumc 17], medicine.diagnostic_test, Gene Expression Profiling, Cancer, Computational Biology, Genetic Variation, High-Throughput Nucleotide Sequencing, Neoplasms, Germ Cell and Embryonal, medicine.disease, cancer susceptibility, Genetic architecture, 3. Good health, 030104 developmental biology, Vocabulary, Controlled, 030220 oncology & carcinogenesis, Mendelian inheritance, symbols
Abstract

The vocabulary currently used to describe genetic variants and their consequences reflects many years of studying and discovering monogenic disease with high penetrance. With the recent rapid expansion of genetic testing brought about by wide availability of high-throughput massively parallel sequencing platforms, accurate variant interpretation has become a major issue. The vocabulary used to describe single genetic variants in silico, in vitro, in vivo and as a contributor to human disease uses terms in common, but the meaning is not necessarily shared across all these contexts. In the setting of cancer genetic tests, the added dimension of using data from genetic sequencing of tumour DNA to direct treatment is an additional source of confusion to those who are not experienced in cancer genetics. The language used to describe variants identified in cancer susceptibility genetic testing typically still reflects an outdated paradigm of Mendelian inheritance with dichotomous outcomes. Cancer is a common disease with complex genetic architecture; an improved lexicon is required to better communicate among scientists, clinicians and patients, the risks and implications of genetic variants detected. This review arises from a recognition of, and discussion about, inconsistencies in vocabulary usage by members of the ENIGMA international multidisciplinary consortium focused on variant classification in breast-ovarian cancer susceptibility genes. It sets out the vocabulary commonly used in genetic variant interpretation and reporting, and suggests a framework for a common vocabulary that may facilitate understanding and clarity in clinical reporting of germline genetic tests for cancer susceptibility.

Published
2019

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