EGFR expression variance in paired colorectal cancer primary and metastatic tumors
Bibliographic record
Abstract
BACKGROUND: Previous studies indicate that drugs targeting the Epidermal Growth Factor Receptor (EGFR) signaling pathways can induce objective responses, prolong time to progression and improve survival of patients with metastatic colorectal cancer (mCRC). EGFR expression in the primary tumour may not predict response to these agents and data is conflicting regarding the correlation of EGFR expression in the primary tumour with the metastatic site. In other tumour sites, the presence of EGFR mutations was associated with efficacy in a subset of patients. OBJECTIVES: The goal of this study is to correlate tumour EGFR expression between primary and liver metastatic sites, and to assess the mutational status in the EGFR kinase domain. METHODS: This is a single center retrospective study of patients who underwent surgical resection of CRC, for whom paired paraffin-embedded tissue blocks of primary tumours and resected liver metastases were available. EGFR immunostaining and mutation analyses were preformed. RESULTS: Fifty six paired colorectal primaries and metastases were available for analysis. EGFR was detectable in 96.6% of the primary samples and in 89.7% of the metastatic samples. Perfect concordance in the intensity score between the primary and the metastases was found in 46.5% of the cases. While individual pairs were poorly concordant for intensity, the proportion of primaries with intense staining was similar to the proportion with intense staining in the metastatic samples. Overall survival did not correlate with either EGFR expression in the primary tumour, or with EGFR expression in the metastasis. There were 2 cases with mutations in the EGFR kinase domain. Both mutations were found in exon21 C>T. CONCLUSIONS: In this analysis, EGFR expression in the primary tumor site was not predictive of its level in the metastasis. EGFR expression levels in the primaries and in the metastases do not appear to be useful prognostic markers.
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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 | 0.000 |
| 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) | 0.000 | 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".