The function and therapeutic targeting of anaplastic lymphoma kinase (ALK) in non-small cell lung cancer (NSCLC)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 it