Abstract 2652: Metabolomics biomarkers for endometrial cancer and its recurrence after surgery in postmenopausal women
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".