<i>PIK3CA, BRAF</i>, and PTEN Status and Benefit from Cetuximab in the Treatment of Advanced Colorectal Cancer—Results from NCIC CTG/AGITG CO.17
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Bibliographic record
Abstract
PURPOSE: Cetuximab improves survival in patients with K-ras wild-type advanced colorectal cancer. We examined the predictive and prognostic significance of additional biomarkers in this setting, in particular BRAF, PIK3CA, and PTEN. EXPERIMENTAL DESIGN: Available colorectal tumor samples were analyzed from the CO.17 study. BRAF mutations were identified in tumor-derived DNA by direct sequencing and PIK3CA mutations were identified using a high-resolution melting screen with confirmation by sequencing. PTEN expression by immunohistochemistry (IHC) was performed on tissue microarrays. For each biomarker, prognostic and predictive effects were examined using a Cox model with tests for treatment-biomarker interaction. RESULTS: A total of 572 patients with pretreated colorectal cancer were randomly assigned to receive cetuximab or best supportive care (BSC). Of 401 patients assessed for BRAF status, 13 (3.2%) had mutations. Of 407 patients assessed for PIK3CA status, 61 (15%) had mutations. Of 205 patients assessed for PTEN, 148 (72%) were negative for IHC expression. None of BRAF, PIK3CA, or PTEN was prognostic for overall or progression-free survival in the BSC arm. None was predictive of benefit from cetuximab, either in the whole study population or the K-ras wild-type subset. In the K-ras wild-type subgroup, the overall survival adjusted HR according to BRAF mutation status was 1.39 (interaction P = 0.69), PIK3CA mutation status HR = 0.79 (interaction P = 0.63), and PTEN expression HR = 0.75 (interaction P = 0.61). CONCLUSIONS: In chemotherapy-refractory colorectal cancer, neither PIK3CA mutation status nor PTEN expression were prognostic, nor were they predictive of benefit from cetuximab. Evaluation of predictive significance of BRAF mutations requires a larger sample size.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it