Low CAIX expression and absence of VHL gene mutation are associated with tumor aggressiveness and poor survival of clear cell renal cell carcinoma
Bibliographic record
Abstract
We attempted to describe, in a series of clear cell renal cell carcinoma (RCC), the relationship between CAIX expression, VHL gene mutations, tumor characteristics and outcome. Radical nephrectomy was performed in 100 patients. Genomic DNA was extracted from frozen tumor samples. Four amplimers covering the whole coding sequence of the VHL gene were synthesized by PCR and sequenced. The monoclonal antibody M75 was used to evaluate CAIX protein expression immunohistochemically. VHL mutations were identified in 58 patients (58%) and high CAIX expression (>85%) was observed in 78 (78%). Tumors with VHL mutation showed higher CAIX expression than those without (p = 0.02). Low CAIX expression and absence of VHL mutation were associated with a more advanced tumors e.g., higher T stages and presence of metastases. VHL mutation and high CAIX expression predicted longer progression-free survival (p = 0.037) and disease-specific survival (p = 0.001), respectively. In combination, they defined three prognostic groups (p = 0.002): (i) good prognosis, defined as VHL mutation and high CAIX (2-year survival: 86%), (ii) intermediate prognosis with either VHL mutation or high CAIX (69%), and (iii) poor prognosis with no VHL mutation and low CAIX (45%, median survival 18 months). CAIX expression, but not VHL mutational status, was an independent prognostic factor in multivariate analysis. Taken together, CAIX expression and VHL mutational status are able to stratify patients with clear cell RCC into distinct groups with regards to clinicopathological variables and prognosis, with low CAIX expression and absence of VHL mutation being associated with a poor clinicopathological phenotype and diminished survival.
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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 | 0.000 |
| 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) | 0.001 | 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".