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Record W4318316381 · doi:10.1038/s41431-022-01257-w

FANCM missense variants and breast cancer risk: a case-control association study of 75,156 European women

2023· review· en· W4318316381 on OpenAlexafffund
Gisella Figlioli, Amandine Billaud, Thomas U. Ahearn, Natalia Antonenkova, Heiko Becher, Matthias W. Beckmann, Sabine Behrens, Javier Benı́tez, Marina Bermisheva, Marinus J. Blok, Natalia Bogdanova, Bernardo Bonanni, Barbara Burwinkel, Nicola J. Camp, Archie Campbell, Jose E. Castelao, Melissa H. Cessna, Stephen J. Chanock, Kristine Kleivi Sahlberg, Anne‐Lise Børresen‐Dale, Inger Torhild Gram, Karina Standahl Olsen, Olav Engebråten, Bjørn Naume, Jürgen Geisler, Tone F. Bathen, Elin Borgen, Britt Fritzman, Øystein Garred, Gry Aarum Geitvik, Solveig Hofvind, Anita Langerød, Ole Christian Lingjærde, Gunhild M. Mælandsmo, Hege G. Russnes, Helle Kristine Skjerven, Thérese Sørlie, Grethe I.G. Alnæs, Kamila Czene, Peter Devilee, Thilo Dörk, Christoph Engel, Mikael Eriksson, Peter A. Fasching, Jonine D. Figueroa, Marike Gabrielson, Manuela Gago-Domínguez, Montserrat García‐Closas, Anna González‐Neira, Felix Graßmann, Pascal Guénel, Melanie Gündert, Andreas Hadjisavvas, Eric Hahnen, Per Hall, Ute Hamann, Patricia Harrington, Wei He, Peter Hillemanns, Antoinette Hollestelle, Maartje J. Hooning, Reiner Hoppe, Anthony Howell, Keith Humphreys, David J. Amor, Lesley Andrews, Yoland Antill, Rosemary L. Balleine, Jonathan Beesley, Ian Bennett, Michael Bogwitz, Leon Botes, Meagan Brennan, Melissa A. Brown, Michael F. Buckley, Jo Burke, Phyllis Butow, Liz Caldon, Ian Campbell, Michelle Cao, Anannya Chakrabarti, Deepa Chauhan, Manisha Chauhan, Alice Christian, Paul A. Cohen, Alison Colley, Ashley Crook, James Cui, Eliza Courtney, Margaret C. Cummings, Sarah‐Jane Dawson, Anna DeFazio, Martin Delatycki, Rebecca Dickson, Joanne Dixon, Ted Edkins, Stacey L. Edwards, Gelareh Farshid, Andrew Fellows, Georgina Fenton, Michael Field, James M. Flanagan, Peter C.C. Fong, Laura Forrest, Stephen B. Fox, Juliet D. French, Michael Friedländer, Clara Gaff, Mike Gattas, Peter George, Sian Greening, Marion Harris, Stewart Hart, John L. Hopper, Cass Hoskins, Clare Hunt, Paul A. James, Mark A. Jenkins, Alexa Kidd, Judy Kirk, Jessica Koehler, James Kollias, Sunil R. Lakhani, Mitchell Lawrence, Jason Lee, Shuai Li, Geoffrey J. Lindeman, Lara Lipton, Liz Lobb, Sherene Loi, Graham J. Mann, Deborah J. Marsh, Sue Anne McLachlan, Bettina Meiser, Roger L. Milne, Sophie Nightingale, Shona O’Connell, Sarah O’Sullivan, David Gallego‐Ortega, Nick Pachter, Jia‐Min Pang, Gargi Pathak, Briony Patterson, Amy Pearn, Ellen Pieper, Susan J. Ramus, Edwina Rickard, Bridget A. Robinson, Mona Saleh, Anita Skandarajah, Elizabeth Salisbury, Christobel Saunders, Jodi M. Saunus, Rodney J. Scott, Clare L. Scott, Adrienne Sexton, Andrew N. Shelling, Peter T. Simpson, Melissa C. Southey, Amanda B. Spurdle, Jessica Taylor, Renea A. Taylor, Heather Thorne, Alison H. Trainer, Kathy Tucker, Jane E. Visvader, Logan C. Walker, Rachael Williams, Ingrid Winship, Mary Ann Young, Milita Zaheed, Agnes Jager, Anna Jakubowska, Э. К. Хуснутдинова, Yon‐Dschun Ko, Vessela N. Kristensen, Annika Lindblom, Jolanta Lissowska, Jan Lubiński, Siranoush Manoukian, Sara Margolin, Dimitrios Mavroudis, William G. Newman, Nadia Obi, Mihalis I. Panayiotidis, Muhammad Usman Rashid, Valerie Rhenius, Matti A. Rookus, Emmanouil Saloustros, Elinor J. Sawyer, Rita K. Schmutzler, Mitul Shah, Reijo Sironen, Maija Suvanto, Rob A.�E.�M. Tollenaar, Ian Tomlinson, Thérèse Truong, Lizet E. van der Kolk, Elke M. van Veen, Barbara Wappenschmidt, Xiaohong R. Yang, Manjeet K. Bolla, Joe Dennis, Alison M. Dunning, Douglas F. Easton, Michael Lush, Kyriaki Michailidou, Paul D.P. Pharoah, Qin Wang, Muriel A. Adank, Marjanka K. Schmidt, Irene L. Andrulis, Jenny Chang‐Claude, Heli Nevanlinna, Georgia Chenevix‐Trench, D. Gareth Evans, Paolo Radice, Paolo Peterlongo

Bibliographic record

VenueEuropean Journal of Human Genetics · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of Toronto
FundersMedical Research and Materiel CommandServicio Gallego de SaludInstituto de Salud Carlos IIICancer Council TasmaniaCancer Council South AustraliaNational Health and Medical Research CouncilMedical Research CouncilCanadian Institutes of Health ResearchProgramme Grants for Applied ResearchManchester Biomedical Research CentreU.S. ArmyNational Institutes of HealthCancer Council VictoriaMinistry of Science and Higher Education of the Russian FederationXunta de GaliciaRheinische Friedrich-Wilhelms-Universität BonnInstitut National Du CancerUniversity of UtahNIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer ResearchFondation de FranceDeutsche KrebshilfeMedizinischen Hochschule HannoverUniversity of CreteSyöpäsäätiöVetenskapsrådetStockholms Läns LandstingKuopion Yliopistollinen SairaalaKarolinska InstitutetDeutsche Gesetzliche UnfallversicherungNederlandse Organisatie voor Wetenschappelijk OnderzoekUniversitätsklinikum Hamburg-EppendorfRussian Foundation for Basic ResearchAgence Nationale de la RechercheHuntsman Cancer FoundationRobert Bosch StiftungAgency for Science, Technology and ResearchCancerfondenNational Cancer InstituteCancer Institute NSWChief Scientist Office, Scottish Government Health and Social Care DirectorateBundesministerium für Bildung und ForschungAgence Nationale de Sécurité Sanitaire de l’Alimentation, de l’Environnement et du TravailSwedish Cancer FoundationNational Breast Cancer FoundationEuropean CommissionMinisterio de Sanidad, Servicios Sociales e IgualdadUniversity of CambridgeGovernment of CanadaEberhard Karls Universität TübingenUniversität LeipzigWellcome TrustFondation du cancer du sein du QuébecFondazione Umberto VeronesiScottish Funding CouncilKWF KankerbestrijdingCancer Research UKKreftforeningenDivision of Cancer Prevention, National Cancer InstituteScottish GovernmentNorges ForskningsrådDeutsches KrebsforschungszentrumAssociazione Italiana per la Ricerca sul CancroItä-Suomen YliopistoGenome CanadaNational Institute for Health and Care ResearchResearch Promotion FoundationEuropean Regional Development FundKing's College LondonCancer Council NSWSusan G. Komen for the CureDivision of Cancer Epidemiology and Genetics, National Cancer InstituteFreistaat SachsenHuntsman Cancer InstituteU.S. Department of Health and Human Services
KeywordsBreast cancerMissense mutationCase-control studyOncologyFamily historyMedicineCancerDiseaseInternal medicineMeta-analysisGeneticsBiologyGeneMutation

Abstract

fetched live from OpenAlex

Evidence from literature, including the BRIDGES study, indicates that germline protein truncating variants (PTVs) in FANCM confer moderately increased risk of ER-negative and triple-negative breast cancer (TNBC), especially for women with a family history of the disease. Association between FANCM missense variants (MVs) and breast cancer risk has been postulated. In this study, we further used the BRIDGES study to test 689 FANCM MVs for association with breast cancer risk, overall and in ER-negative and TNBC subtypes, in 39,885 cases (7566 selected for family history) and 35,271 controls of European ancestry. Sixteen common MVs were tested individually; the remaining rare 673 MVs were tested by burden analyses considering their position and pathogenicity score. We also conducted a meta-analysis of our results and those from published studies. We did not find evidence for association for any of the 16 variants individually tested. The rare MVs were significantly associated with increased risk of ER-negative breast cancer by burden analysis comparing familial cases to controls (OR = 1.48; 95% CI 1.07-2.04; P = 0.017). Higher ORs were found for the subgroup of MVs located in functional domains or predicted to be pathogenic. The meta-analysis indicated that FANCM MVs overall are associated with breast cancer risk (OR = 1.22; 95% CI 1.08-1.38; P = 0.002). Our results support the definition from previous analyses of FANCM as a moderate-risk breast cancer gene and provide evidence that FANCM MVs could be low/moderate risk factors for ER-negative and TNBC subtypes. Further genetic and functional analyses are necessary to clarify better the increased risks due to FANCM MVs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.320
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2023
Admission routes2
Has abstractyes

Explore more

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