Wnt Signaling Pathway in Non-Small Cell Lung Cancer
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
Wnt/β-catenin alterations are prominent in human malignancies. In non-small cell lung cancer (NSCLC), β-catenin and APC mutations are uncommon, but Wnt signaling is important in NSCLC cell lines, and Wnt inhibition reduces proliferation. Overexpression of Wnt-1, -2, -3, and -5a and of Wnt-pathway components Frizzled-8, Dishevelled, Porcupine, and TCF-4 is common in resected NSCLC and is associated with poor prognosis. Conversely, noncanonical Wnt-7a suppresses NSCLC development and is often downregulated. Although β-catenin is often expressed in NSCLCs, it was paradoxically associated with improved prognosis in some series, possibly because of E-cadherin interactions. Downregulation of Wnt inhibitors (eg, by hypermethylation) is common in NSCLC tumor cell lines and resected samples; may be associated with high stage, dedifferentiation, and poor prognosis; and has been reported for AXIN, sFRPs 1-5, WIF-1, Dkk-1, Dkk-3, HDPR1, RUNX3, APC, CDX2, DACT2, TMEM88, Chibby, NKD1, EMX2, ING4, and miR-487b. AXIN is also destabilized by tankyrases, and GSK3β may be inactivated through phosphorylation by EGFR. Preclinically, restoration of Wnt inhibitor function is associated with reduced Wnt signaling, decreased cell proliferation, and increased apoptosis. Wnt signaling may also augment resistance to cisplatin, docetaxel, and radiotherapy, and Wnt inhibitors may restore sensitivity. Overall, available data indicate that Wnt signaling substantially impacts NSCLC tumorigenesis, prognosis, and resistance to therapy, with loss of Wnt signaling inhibitors by promoter hypermethylation or other mechanisms appearing to be particularly important. Wnt pathway antagonists warrant exploration clinically in NSCLC. Agents blocking selected specific β-catenin interactions and approaches to increase expression of downregulated Wnt inhibitors may be of particular interest.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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