The function and therapeutic targeting of anaplastic lymphoma kinase (ALK) in non-small cell lung cancer (NSCLC)
Bibliographic record
Abstract
Lung cancer is the leading cause of death by cancer in North America. A decade ago, genomic rearrangements in the anaplastic lymphoma kinase (ALK) receptor tyrosine kinase were identified in a subset of non-small cell lung carcinoma (NSCLC) patients. Soon after, crizotinib, a small molecule ATP-competitive ALK inhibitor was proven to be more effective than chemotherapy in ALK-positive NSCLC patients. Crizotinib and two other ATP-competitive ALK inhibitors, ceritinib and alectinib, are approved for use as a first-line therapy in these patients, where ALK rearrangement is currently diagnosed by immunohistochemistry and in situ hybridization. The clinical success of these three ALK inhibitors has led to the development of next-generation ALK inhibitors with even greater potency and selectivity. However, patients inevitably develop resistance to ALK inhibitors leading to tumor relapse that commonly manifests in the form of brain metastasis. Several new approaches aim to overcome the various mechanisms of resistance that develop in ALK-positive NSCLC including the knowledge-based alternate and successive use of different ALK inhibitors, as well as combined therapies targeting ALK plus alternative signaling pathways. Key issues to resolve for the optimal implementation of established and emerging treatment modalities for ALK-rearranged NSCLC therapy include the high cost of the targeted inhibitors and the potential of exacerbated toxicities with combination therapies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".