Prognostic Value of ADAMTS Proteases and Their Substrates in Epithelial Ovarian Cancer
Bibliographic record
Abstract
BACKGROUND: ADAMTS are metalloproteases with disintegrin and thrombospondin motifs. They are secreted proteases playing a role in biological processes such as inflammation, angiogenesis, and urogenital development. ADAMTS have specific substrates, such as the proteoglycans (PG) versican, aggrecan, and brevican. Despite data indicating a role of ADAMTS in tumor invasion and metastases, effects played by these molecules in cancer progression are still controversial. In ovarian cancer, the importance of ADAMTS gene mutations was recently described and related to chemotherapy outcome. OBJECTIVE: To analyze protein levels of ADAMTS-1, -4, and -5, and TIMP-3 in human ovarian cancer classified as benign, borderline, or malignant. We also assessed the expression of the ADAMTS substrates aggrecan, brevican, and versican in these neoplasms. Correlations between overall survival and protein expression were performed. METHODS: Tumors were classified according to the WHO Classification of Tumors of Female Reproductive Organs. Protein and PG expression was studied by immunohistochemistry. Differences in labeling were analyzed by percent measurements of stained areas. RESULTS: ADAMTS-1, ADAMTS-5, and its tissue inhibitor TIMP-3 are increased in borderline and malignant tumors compared to benign neoplasms. Aggrecan and versican levels were increased in malignant subtypes compared to benign ovarian cancer. Higher ADAMTS-1, TIMP-3, and versican expression was associated with a shorter overall survival. CONCLUSIONS: Comparison of protease, TIMP-3, and substrate expression showed that in malignant tumors all ADAMTS and TIMP-3 expression levels were significantly raised compared to the substrates studied.
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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 | 0.002 |
| 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".