Integrative Transcriptome Analyses of the Human Fallopian Tube: Fimbria and Ampulla—Site of Origin of Serous Carcinoma of the Ovary
Bibliographic record
Abstract
Epithelial ovarian cancer represents a group of heterogeneous diseases with high grade serous cancer (HGSC) representing the most common histotype. Molecular profiles of precancerous lesions found in the fallopian tube have implicated this tissue as the presumptive site of origin of HGSC. Precancerous lesions are primarily found in the distal fallopian tube (fimbria), near the ovary relative to the proximal tissue (ampulla), nearer to the uterus. The proximity of the fimbria to the ovary and the link between ovulation, through follicular fluid release, and ovarian cancer risk led us to examine transcriptional responses of fallopian tube epithelia (FTE) at the different anatomical sites of the human fallopian tube. Gene expression profiles of matched FTE from the fimbria and from premenopausal women resulted in differentially expressed genes (DEGs): CYYR1, SALL1, FOXP2, TAAR1, AKR1C2/C3/C4, NMBR, ME1 and GSTA2. These genes are part of the antioxidant, stem and inflammation pathways. Comparisons between the luteal phase (post-ovulation) to the follicular phase (pre-ovulation) demonstrated greater differences in DEGs than a comparison between fimbria and fallopian tube anatomical differences alone. This data suggests that cyclical transcriptional changes experienced in pre-menopause are inherent physiological triggers that expose the FTE in the fimbria to cytotoxic stressors. These cyclical exposures induce transcriptional changes reflective of genotoxic and cytotoxic damage to the FTE in the fimbria which are closely related to transcriptional and genomic alterations observed in ovarian cancer.
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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 | 0.000 | 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".