Known and putative mechanisms of resistance to EGFR targeted therapies in NSCLC patients with EGFR mutations-a review.
Bibliographic record
Abstract
Lung cancer is the leading cause of cancer related deaths in Canada with non-small cell lung cancer (NSCLC) being the predominant form of the disease. Tumor characterization can identify cancer-driving mutations as treatment targets. One of the most successful examples of cancer targeted therapy is inhibition of mutated epidermal growth factor receptor (EGFR), which occurs in ~10-30% of NSCLC patients. While this treatment has benefited many patients with activating EGFR mutations, almost all who initially benefited will eventually acquire resistance. Approximately 50% of cases of acquired resistance (AR) are due to a secondary T790M mutation in exon 20 of the EGFR gene; however, many of the remaining mechanisms of resistance are still unknown. Much work has been done to elucidate the remaining mechanisms of resistance. This review aims to highlight both the mechanisms of resistance that have already been identified in patients and potential novel mechanisms identified in preclinical models which have yet to be validated in the patient settings.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".