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Record W2047184953 · doi:10.1038/aja.2008.18

Identification of new genetic risk factors for prostate cancer

2008· review· en· W2047184953 on OpenAlexaff
Michelle Guy, Zsofia Kote‐Jarai, Graham G. Giles, Ali Amin Al Olama, Sarah Jugurnauth, S. Grant Mulholland, Daniel Leongamornlert, Stephen M. Edwards, Jonathan J. Morrison, Helen I. Field, Melissa C. Southey, Gianluca Severi, Jenny Donovan, Freddie C. Hamdy, David P. Dearnaley, Kenneth Muir, Charmaine Smith, Melisa Bagnato, Audrey Ardern‐Jones, Amanda L. Hall, Lynne T. O'Brien, Beatrice N. Gehr-Swain, Rosemary Wilkinson, Angela Cox, Sarah J. Lewis, Paul Brown, Sameer Jhavar, Malgorzata Tymrakiewicz, Artitaya Lophatananon, Sarah L. Bryant, A. Horwich, Robert Huddart, Vincent Khoo, Christopher Parker, Christopher Woodhouse, Alan Thompson, Tim Christmas, Chris Ogden, Cyril Fisher, Charles Jameson, Colin S. Cooper, Dallas R. English, John L. Hopper, David E. Neal, Douglas F. Easton, Rosalind A. Eeles

Bibliographic record

VenueAsian Journal of Andrology · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities
Canadian institutionsInstitute of Cancer Research
FundersCancer Council VictoriaHealth Technology Assessment ProgrammeCancer Research UKCongressionally Directed Medical Research ProgramsNational Health and Medical Research CouncilRoyal Marsden NHS Foundation TrustNational Institute for Health and Care ResearchNational Cancer Research InstituteMedical Research CouncilCancer Research Institute
KeywordsProstate cancerGenome-wide association studyPenetranceGeneticsGenetic testingGenetic associationBiologyCandidate geneIdentification (biology)Genetic predispositionGeneCancerBioinformaticsMedicineComputational biologyGenotypeSingle-nucleotide polymorphismPhenotype

Abstract

fetched live from OpenAlex

There is evidence that a substantial part of genetic predisposition to prostate cancer (PCa) may be due to lower penetrance genes which are found by genome-wide association studies. We have recently conducted such a study and seven new regions of the genome linked to PCa risk have been identified. Three of these loci contain candidate susceptibility genes: MSMB, LMTK2 and KLK2/3. The MSMB and KLK2/3 genes may be useful for PCa screening, and the LMTK2 gene might provide a potential therapeutic target. Together with results from other groups, there are now 23 germline genetic variants which have been reported. These results have the potential to be developed into a genetic test. However, we consider that marketing of tests to the public is premature, as PCa risk can not be evaluated fully at this stage and the appropriate screening protocols need to be developed. Follow-up validation studies, as well as studies to explore the psychological implications of genetic profile testing, will be vital prior to roll out into healthcare.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.023
GPT teacher head0.322
Teacher spread0.299 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations25
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueAsian Journal of AndrologySame topicGenetic and Clinical Aspects of Sex Determination and Chromosomal AbnormalitiesFrench-language works237,207