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Record W2189635544 · doi:10.1038/srep17369

Meta-analysis of genome-wide association studies identifies common susceptibility polymorphisms for colorectal and endometrial cancer near SH2B3 and TSHZ1

2015· review· en· W2189635544 on OpenAlexaff
Timothy Cheng, Deborah J. Thompson, Jodie N. Painter, Tracy A. O’Mara, Maggie Gorman, Lynn Martin, Claire Palles, Angela Jones, Daniel D. Buchanan, Aung Ko Win, John L. Hopper, Mark A. Jenkins, Noralane M. Lindor, Polly A. Newcomb, Steve Gallinger, David V. Conti, Fredrick R. Schumacher, Graham Casey, Graham G. Giles, Paul D.P. Pharoah, Julian Peto, Angela Cox, Anthony J. Swerdlow, Fergus J. Couch, Julie M. Cunningham, Ellen L. Goode, Stacey J. Winham, Diether Lambrechts, Peter A. Fasching, Barbara Burwinkel, Hermann Brenner, Hiltrud Brauch, Jenny Chang‐Claude, Helga B. Salvesen, Vessela N. Kristensen, Hatef Darabi, Jingmei Li, Tao Liu, Annika Lindblom, Per Hall, Magdalena Echeverry de Polanco, Mónica Sans, Ángel Carracedo, Sergi Castellvı́-Bel, Augusto Rojas‐Martínez, Manuel R. Teixeira, Alison M. Dunning, Joe Dennis, Geoffrey Otton, Tony Proietto, Elizabeth Holliday, John Attia, Katie A. Ashton, Rodney J. Scott, Mark McEvoy, Sean C. Dowdy, Brooke L. Fridley, Henrica M.J. Werner, Jone Trovik, Tormund S. Njølstad, Emma Tham, Miriam Mints, Ingo B. Runnebaum, Peter Hillemanns, Thilo Dörk, Frédéric Amant, Stefanie Schrauwen, Alexander Hein, Matthias W. Beckmann, Arif B. Ekici, Kamila Czene, Alfons Meindl, Manjeet K. Bolla, Kyriaki Michailidou, Jonathan P. Tyrer, Qin Wang, Shahana Ahmed, Catherine S. Healey, Mitul Shah, Daniela Annibali, Jeroen Depreeuw, Nada Al Tassan, Rebecca Harris, Brian F. Meyer, Nicola Whiffin, Fay J. Hosking, Ben Kinnersley, Susan M. Farrington, Maria Timofeeva, Albert Tenesa, Harry Campbell, Robert W. Haile, Shirley Hodgson, Luis G. Carvajal‐Carmona, Jeremy P. Cheadle, Douglas F. Easton, Malcolm G. Dunlop, Richard S. Houlston, Amanda B. Spurdle, Ian Tomlinson

Bibliographic record

VenueScientific Reports · 2015
Typereview
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
FundersMedical Research CouncilNational Institute for Health and Care ResearchWellcome TrustFrancis Crick InstituteNational Cancer InstituteCancer Research UK
KeywordsColorectal cancerEndometrial cancerOdds ratioGenome-wide association studyGeneticsAlleleBiologyOncologyInternal medicineSingle-nucleotide polymorphismMedicineGenotypeCancerGene

Abstract

fetched live from OpenAlex

High-risk mutations in several genes predispose to both colorectal cancer (CRC) and endometrial cancer (EC). We therefore hypothesised that some lower-risk genetic variants might also predispose to both CRC and EC. Using CRC and EC genome-wide association series, totalling 13,265 cancer cases and 40,245 controls, we found that the protective allele [G] at one previously-identified CRC polymorphism, rs2736100 near TERT, was associated with EC risk (odds ratio (OR) = 1.08, P = 0.000167); this polymorphism influences the risk of several other cancers. A further CRC polymorphism near TERC also showed evidence of association with EC (OR = 0.92; P = 0.03). Overall, however, there was no good evidence that the set of CRC polymorphisms was associated with EC risk, and neither of two previously-reported EC polymorphisms was associated with CRC risk. A combined analysis revealed one genome-wide significant polymorphism, rs3184504, on chromosome 12q24 (OR = 1.10, P = 7.23 × 10(-9)) with shared effects on CRC and EC risk. This polymorphism, a missense variant in the gene SH2B3, is also associated with haematological and autoimmune disorders, suggesting that it influences cancer risk through the immune response. Another polymorphism, rs12970291 near gene TSHZ1, was associated with both CRC and EC (OR = 1.26, P = 4.82 × 10(-8)), with the alleles showing opposite effects on the risks of the two cancers.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.997
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.011
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.195
GPT teacher head0.412
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designMeta-analysis
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

Citations41
Published2015
Admission routes1
Has abstractyes

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