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Record W2886543388 · doi:10.1158/1538-7445.am2018-2652

Abstract 2652: Metabolomics biomarkers for endometrial cancer and its recurrence after surgery in postmenopausal women

2018· article· en· W2886543388 on OpenAlexaff
Yannick Audet-Delage, Jean‐Pierre Grégoire, Marie Plante, Chantal Guillemette

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsUniversité LavalCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsEndometrial cancerMetabolomicsMedicineBiomarkerSerous fluidInternal medicineCancerMetaboliteGastroenterologyOncologyPhysiologyBiologyBioinformaticsBiochemistry

Abstract

fetched live from OpenAlex

Abstract Endometrial cancer (EC) is the most frequent cancer of the female genital tract in developed countries. Most EC occurs after menopause and are diagnosed as endometrioid type I carcinomas that exhibit a favorable prognosis especially for grades 1 and 2. In contrast, type II non-endometrioid carcinomas such as serous tumors have a poor prognosis. The use of small molecule biomarkers may facilitate accurate diagnosis and prognostic predictions. Our goal was to identify novel blood-based markers associated with EC subtypes and recurrence after surgery in postmenopausal women. Using mass spectrometry (MS)-based metabolomics, we examined preoperative serum metabolites of healthy women (n=18), non-recurrent and recurrent cases with type I endometrioid (n=24) and type II serous (n=12) carcinomas, matched for pathological characteristics, body mass index and age. Biochemicals including complex lipids were analyzed by gas chromatography-MS and ultrahigh performance liquid chromatography-tandem MS. A total of 1592 compounds of known identity and 14 different lipid classes were assessed. When comparing EC cases to healthy women, 137 metabolites were significantly different, with spermine as the most altered biochemical, identifying this metabolite as a potential biomarker of EC. Furthermore, recurrent cases of both histological types had higher levels of the monoacylglycerol 1-oleoylglycerol than non-recurrent cases. Type I recurrent cases were also characterized by much lower levels of bile acids and elevated concentrations of phosphorylated fibrinogen cleavage peptide, whereas type II recurrent cases displayed higher levels of ceramides and their derivatives. Our findings provide a first detailed metabolomics study in EC and identify potential non-invasive biomarkers to define clinically relevant risk groups. Citation Format: Yannick Audet-Delage, Lyne Villeneuve, Jean Grégoire, Marie Plante, Chantal Guillemette. Metabolomics biomarkers for endometrial cancer and its recurrence after surgery in postmenopausal women [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2652.

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)0.000
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.058
GPT teacher head0.382
Teacher spread0.324 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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