Coexpression of the type 1 growth factor receptor family members HER‐1, HER‐2, and HER‐3 has a synergistic negative prognostic effect on breast carcinoma survival
Bibliographic record
Abstract
BACKGROUND: The clinical significance of coexpression of type 1 growth factor receptor (T1GFR) family members remains largely unknown. The objective of the current study was to determine the frequency and the possible prognostic effect of coexpression of HER-1, HER-2, HER-3, and HER-4 by breast carcinoma. METHODS: Tissue microarrays were constructed using clinically annotated formalin-fixed, paraffin-embedded tumor samples from 242 patients with invasive breast carcinomas with a median 15-year follow-up. The levels of TIGFR family members (HER-1-HER-4) were measured by immunohistochemistry. K-means clustering algorithm, as well as univariate (Kaplan-Meier, log-rank test) and multivariate (Cox regression) survival analyses were applied to the data set. RESULTS: Using univariate analysis, expression of HER-1, HER-2, and HER-3, but not HER-4, was significantly associated with decreased patient disease-specific survival (P < 0.05). Kaplan-Meier survival analysis showed that coexpression of >/= 2 of HER-1, HER-2, and HER-3 in any combination was associated with reduced patient disease-specific survival compared with single marker expression or no expression (35% vs. 65% vs. 78% 10-year survival rates, P = 0.001). Using multivariate analysis, expression of >/= 2 of HER-1, HER-2, and HER-3 was independent of lymph node status and tumor size. CONCLUSIONS: In a cohort of patients with breast carcinoma, the authors observed T1GFR family member coexpression (HER-1, HER-2, and HER-3) to have a negative synergistic effect on patient outcome, independent of tumor size or lymph node status. Thus, coexpression of T1GFR family members identified a subset of patients with a poor disease prognosis who may potentially benefit from therapy simultaneously targeting several T1GFR family members.
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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 | 0.001 |
| 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 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".