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Lymphocyte Telomere Length Is Long in <i>BRCA1</i> and <i>BRCA2</i> Mutation Carriers Regardless of Cancer-Affected Status

2014· article· en· W2098553570 on OpenAlexfundno aff
Karen A. Pooley, Lesley McGuffog, Daniel Barrowdale, Debra Frost, Steve D. Ellis, Elena Fineberg, Radka Platte, Louise Izatt, Julian Adlard, Julian Bardwell, Carole Brewer, Trevor Cole, Jackie Cook, Rosemarie Davidson, Alan Donaldson, Huw Dorkins, Fiona Douglas, Jacqueline Eason, Catherine Houghton, Michael J. Kennedy, Emma McCann, Zosia Miedzybrodzka, Alex Murray, Mary Porteous, Mark T. Rogers, Lucy Side, Marc Tischkowitz, Lisa Walker, Shirley Hodgson, Patrick J. Morrison, D. Gareth Evans, Rosalind A. Eeles, Antonis C. Antoniou, Douglas F. Easton, Alison M. Dunning

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2014
Typearticle
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchNational Cancer InstituteNational Institute for Health and Care ResearchCancer Research UK
KeywordsTelomereOvarian cancerMutationCancerGermline mutationGeneticsBRCA mutationBiologyBreast cancerCancer researchDNAGene

Abstract

fetched live from OpenAlex

BACKGROUND: Telomere length has been linked to risk of common diseases, including cancer, and has previously been proposed as a biomarker for cancer risk. Germline BRCA1 and BRCA2 mutations predispose to breast, ovarian, and other cancer types. METHODS: We investigated telomere length in BRCA mutation carriers and their non-carrier relatives and further examined whether telomere length is a modifier of cancer risk in mutation carriers. We measured mean telomere length in DNA extracted from whole blood using high-throughput quantitative PCR. Participants were from the EMBRACE study in United Kingdom and Eire (n = 4,822) and comprised BRCA1 (n = 1,628) and BRCA2 (n = 1,506) mutation carriers and their non-carrier relatives (n = 1,688). RESULTS: We find no significant evidence that mean telomere length is associated with breast or ovarian cancer risk in BRCA mutation carriers. However, we find mutation carriers to have longer mean telomere length than their non-carrier relatives (all carriers vs. non-carriers, Ptrend = 0.0018), particularly in families with BRCA2 mutations (BRCA2 mutation carriers vs. all non-carriers, Ptrend = 0.0016). CONCLUSIONS: Our findings lend little support to the hypothesis that short mean telomere length predisposes to cancer. Conversely, our main and unexpected finding is that BRCA mutation carriers (regardless of cancer status) have longer telomeres than their non-mutation carrier, non-cancer-affected relatives. The longer telomere length in BRCA2 mutation carriers is consistent with its role in DNA damage response. Overall, it seems that increased telomere length may be a consequence of these mutations, but is not itself directly related to the increased cancer risk in carriers. IMPACT: The finding that mutation carriers have longer mean telomere lengths than their non-carrier relatives is unexpected but biologically plausible and could open up new lines of research into the functions of the BRCA proteins. To our knowledge, this is the largest study of telomere length in BRCA mutation carriers and their relatives. The null cancer-risk association supports recent large prospective studies of breast and ovarian cancer and indicates that mean telomere length would not be a useful biomarker in these cancers. Cancer Epidemiol Biomarkers Prev; 23(6); 1018-24. ©2014 AACR.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.349
Teacher spread0.321 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations23
Published2014
Admission routes1
Has abstractyes

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