Evaluation of the association of matrix metalloproteinase-1 (MMP-1) and matrix metalloproteinase-2 (MMP-2) expression with KRAS and BRAF mutational status or survival outcomes in colorectal cancer (CRC) patients.
Bibliographic record
Abstract
452 Background: MMP-1 and MMP-2 proteins are felt to be involved in tumor growth, invasion and metastasis and may be regulated by the KRAS pathway. Methods: A tissue microarray was constructed from archival formalin-fixed paraffin-embedded primary tumor tissue samples of 96 patients with metastatic CRC. MMP-1 and MMP-2 expression was measured semiquantitatively by immunohistochemistry and graded 0 to 2. Mutation analysis was done for KRAS in codons 12 and 13, and patients without KRAS mutations were tested for BRAF V600E mutation. Chi-squared test, Fisher's exact test and Cox-proportionate hazard ratios were used for statistical analysis. Results: 96 patients had samples available for analysis (median age at diagnosis 60, 57% male, 46% stage IV at diagnosis, 33/93 (35%) KRAS mutated, 7/51 (14%) BRAF mutated, 22% received anti-EGFR therapy). No significant association was identified between MMP-1 and KRAS (p=0.88) or BRAF (p=0.54), or between MMP-2 and KRAS (p=0.08) or BRAF (p=0.41). Neither overall survival nor survival from diagnosis of metastatic disease were affected by MMP-1 or MMP-2 expression. Conclusions: MMP-1 and MMP-2 expression is not associated with KRAS or BRAF mutational status and is not a prognostic factor in our cohort of CRC patients. No significant financial relationships to disclose.
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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 | 0.001 | 0.002 |
| 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) | 0.002 | 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".