Colon cancer-derived oncogenic EGFR G724S mutant identified by whole genome sequence analysis is dependent on asymmetric dimerization and sensitive to cetuximab
Bibliographic record
Abstract
BACKGROUND: Inhibition of the activated epidermal growth factor receptor (EGFR) with either enzymatic kinase inhibitors or anti-EGFR antibodies such as cetuximab, is an effective modality of treatment for multiple human cancers. Enzymatic EGFR inhibitors are effective for lung adenocarcinomas with somatic kinase domain EGFR mutations while, paradoxically, anti-EGFR antibodies are more effective in colon and head and neck cancers where EGFR mutations occur less frequently. In colorectal cancer, anti-EGFR antibodies are routinely used as second-line therapy of KRAS wild-type tumors. However, detailed mechanisms and genomic predictors for pharmacological response to these antibodies in colon cancer remain unclear. FINDINGS: We describe a case of colorectal adenocarcinoma, which was found to harbor a kinase domain mutation, G724S, in EGFR through whole genome sequencing. We show that G724S mutant EGFR is oncogenic and that it differs from classic lung cancer derived EGFR mutants in that it is cetuximab responsive in vitro, yet relatively insensitive to small molecule kinase inhibitors. Through biochemical and cellular pharmacologic studies, we have determined that cells harboring the colon cancer-derived G719S and G724S mutants are responsive to cetuximab therapy in vitro and found that the requirement for asymmetric dimerization of these mutant EGFR to promote cellular transformation may explain their greater inhibition by cetuximab than small-molecule kinase inhibitors. CONCLUSION: The colon-cancer derived G719S and G724S mutants are oncogenic and sensitive in vitro to cetuximab. These data suggest that patients with these mutations may benefit from the use of anti-EGFR antibodies as part of the first-line therapy.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".