An apoptotic molecular network identified by microarray: On the TRAIL to new insights in epithelial ovarian cancer
Bibliographic record
Abstract
BACKGROUND: In a previous microarray expression analysis, the authors identified candidate genes that were expressed differentially between ovarian tumors with low malignant potential and invasive serous epithelial ovarian tumors. Among them, the apoptosis-related candidate genes tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), caspase 8 (CASP8), FLICE-inhibitory protein (FLIP), and cytochrome C (CYC) were identified. METHODS: For the current study, the authors conducted immunohistochemical analyses of a tissue array comprised of 235 serous tumors of different grades and stages to evaluate whether there was differential protein expression for these candidates and for the 4 death cell receptors of Trail: Dr4, Dr5, DcR1, and DcR2. RESULTS: All proteins except DcR1 and DcR2 had significantly differential expression levels between grade 0 tumors (low malignant potential) and grade 2 and 3 tumors. Trail also showed differential expression between grade 0 tumors and grade 1 tumors. When all tumors were compared, the expression levels of Trail, Dr4, Dr5, DcR1, and Flip differed significantly between early-stage and advanced-stage disease. High Dr5 expression was associated with a poor prognosis in patients who had invasive tumors and in the subgroup of patients who had grade 3 tumors. Furthermore, the combinations of 2 proteins (Trail and Dr5, DcR2 and Cyc, Flip and Dr5, Flip and DcR2, DcR1 and Dr5 or Dr4 and Flip) revealed an association with patient prognosis. CONCLUSIONS: The identification of new proteins in the initial diagnosis and prognosis of patients with epithelial ovarian cancer may lead to a better understanding of the disease, highlighting new potential therapeutic targets, and may be useful in patient management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".