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Record W2985910591 · doi:10.1038/s41523-019-0138-2

Menstrual cycle associated changes in hormone-related gene expression in oestrogen receptor positive breast cancer

2019· article· en· W2985910591 on OpenAlexaff
Ben P. Haynes, Ophira Ginsburg, Qiong Gao, Elizabeth Folkerd, Maria Afentakis, Richard Buus, Le Hong Quang, Pham Thi Han, Pham Hong Khoa, Nguyễn Văn Định, Ta Van To, Mark Clemons, Chris Holcombe, Caroline Osborne, Abigail Evans, Anthony Skene, Mark Sibbering, Clare Rogers, Siobhan Laws, Lubna Noor, Ian E. Smith, Mitch Dowsett

Bibliographic record

Venuenpj Breast Cancer · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEstrogen and related hormone effects
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersNational Institute for Health and Care ResearchBreast Cancer Research Foundation
KeywordsMenstrual cycleBreast cancerEndocrinologyInternal medicineProgesterone receptorGene expressionEstrogenHormoneCancerHormone receptorMedicineBiologyEstrogen receptorGeneGenetics

Abstract

fetched live from OpenAlex

Abstract The major changes in hormone levels that occur through the menstrual cycle have been postulated to affect the expression of hormone-regulated and proliferation-associated genes (PAGs) in premenopausal ER+ breast cancer. Whilst previous studies have demonstrated differences in gene expression, here, we investigated if there are within patient changes in the expression of oestrogen- and progesterone-regulated genes (ERGs and PRGs) and PAGs in ER+ breast cancer during the menstrual cycle. Samples from 96 patients in two independent prospective studies of the effect of menstrual cycle on ER+ breast cancer were used. Plasma hormone measurements were used to assign tumours to one of three pre-defined menstrual cycle windows: W1 (days 27–35 and 1–6; low oestradiol and low progesterone), W2 (days 7–16; high oestradiol and low progesterone) and W3 (days 17–26; intermediate oestradiol and high progesterone). RNA expression of 50 genes, including 27 ERGs, 11 putative PRGs and seven PAGs was measured. The AvERG (geomean of PGR, GREB1, TFF1 and PDZK1) was used as a composite measure of ERG expression and showed significant changes between the three windows of the menstrual cycle increasing over 2.2-fold between W1 and W2 and decreasing between W2 and W3 and between W3 and W1. Proliferation gene expression also varied significantly, following the same pattern of changes as ERG expression, but the changes were of lower magnitude (1.4-fold increase between W1 and W2). Significant changes in the expression of eight individual ERGs, including GREB1, PGR and TFF1, and two PAGs were observed between W1 and either W2 or W3 with all genes showing higher levels in W2 or W3 (1.3–2.4-fold; FDR 0.016–0.05). The AvProg, a composite measure of PRG expression, increased significantly (1.5-fold) in W3 compared to W1 or W2 but no significant changes were observed for individual PRGs. In conclusion, we observed significant changes in ERG, PRG and PAG expression in ER+ breast tumours during the menstrual cycle that may affect the assessment and interpretation of prominent biomarkers (e.g. PgR) and commonly used multigene prognostic signatures in premenopausal ER+ breast cancer.

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)0.001
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.003
GPT teacher head0.226
Teacher spread0.223 · 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

Citations38
Published2019
Admission routes1
Has abstractyes

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