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Record W1626602876 · doi:10.1080/2162402x.2015.1074375

Autoantibodies specific to estrogen receptor alpha act as estrogen agonists and their levels correlate with breast cancer cell proliferation

2015· article· en· W1626602876 on OpenAlexfundno aff
Angela Maselli, Sara Capoccia, Patrizia Pugliese, Carla Raggi, Francesca Cirulli, Alessandra Fabi, Walter Malorni, Marina Pierdominici, Elena Ortona

Bibliographic record

VenueOncoImmunology · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEstrogen and related hormone effects
Canadian institutionsnot available
FundersUniversity of Lethbridge
KeywordsBreast cancerEstrogen receptorCancerAutoantibodyMedicineCancer researchEstrogenReceptorCell growthEstrogen receptor alphaInternal medicineEndocrinologyCancer cellImmunologyAntibodyBiology

Abstract

fetched live from OpenAlex

Estrogen receptors have recently been demonstrated at the cell surface. Unlike nuclear receptors, they are able to trigger rapid responses inside the cells. In this study, we evaluated the presence and the possible role of autoantibodies specific to estrogen receptor (anti-ER Abs) in the peripheral blood of breast cancer patients. Anti-ERα Abs were detectable in 22/48 (46%) patients' sera and their levels positively correlated with the percentage of Ki-67-positive breast cancer cells. Anti-ERα Abs purified from breast cancer patients' sera were able: (i) to recognize ERα epitopes expressed at the cell surface of ER-positive breast cancer cells, (ii) to trigger rapid extracellular signal-regulated kinase (ERK) phosphorylation, and (iii) to induce cell proliferation. Our results suggest that anti-ERα Abs can act as estrogen agonists playing a pathogenetic role as breast cancer-promoting factors. These autoantibodies could also be considered as possible peripheral blood biomarkers indicative of the breast cancer growth potential.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.010
GPT teacher head0.243
Teacher spread0.233 · 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 designBench or experimental
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

Citations25
Published2015
Admission routes1
Has abstractyes

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