p66 Shc Tumor Levels Show a Strong Prognostic Correlation with Disease Outcome in Stage IIA Colon Cancer
Bibliographic record
Abstract
PURPOSE: Most stage IIA colon cancer patients receive no adjuvant therapy despite an estimated 15% risk of disease-related death within 5 years of resection. Prognostication of disease outcome would benefit the clinician by categorizing patients with stage IIA disease by risk. The abundance of the signal transduction proteins p66 Shc and tyrosine-phosphorylated (PY)-Shc in tumor cells is a prognostic indicator of disease outcome in breast cancer, suggesting that Shc analysis may provide prognostic information in stage IIA colon cancer. EXPERIMENTAL DESIGN: Immunohistochemical staining of p66 Shc and PY-Shc was examined in resection specimens from 240 chemotherapy-naïve patients with stage IIA (T(3)N(0)M(0)) colon cancer from two independent (130 and 110 cases, respectively) retrospective cohorts. Staining was scored on a 0 to 5 scale and correlated with relapse-free survival and disease-specific survival in a multivariate analysis to obtain hazard ratios (HR) for both outcomes. RESULTS: In a pooled analysis of both cohorts, p66 Shc score was a significant prognostic indicator of relapse-free survival (full-range HR, 13.0; P = 0.012) and disease-specific survival (full-range HR, 36.6; P = 0.004) when analyzed as a continuous variable in a multivariate Cox proportional hazards model stratified by study site and adjusted for age, sex, grade, and lymphovascular involvement. PY-Shc in this multivariate Cox model, however, did not achieve statistical significance for either outcome. CONCLUSIONS: Measuring p66 Shc tumor levels provides a unique and simple tool for stratifying stage IIA colon cancer patients by risk of recurrence and disease-specific death and may assist in determining treatment strategies for these patients.
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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 | 0.001 |
| 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) | 0.001 | 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".