PYGB facilitates cell proliferation and invasiveness in non-small cell lung cancer by activating the Wnt–β-catenin signaling pathway
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
Brain-type glycogen phosphorylase (PYGB) has been correlated with the progression of various human malignancies; however, its effects and regulatory mechanisms in non-small cell lung cancer (NSCLC) are still unclear. We used Western blotting, immunohistochemistry, and qRT-PCR to verify that the protein and mRNA expression levels of PYGB are up-regulated in both NSCLC cell lines and tissues. The expression of PYGB was positively related to TNM stage, positive lymph node metastasis, and poor prognosis in patients with NSCLC. Moreover, overexpression of PYGB promoted cell proliferation, migration, and invasiveness, but inhibited apoptosis, in vitro. Immunofluorescence assays showed that overexpression of PYGB promoted the nuclear import and accumulation of β-catenin. By comparison, silencing PYGB produced the opposite effects. Further, overexpression of PYGB resulted in activation of the Wnt signaling pathway, and transfection with Sh-PYGB produced the opposite effect, and these effects were abrogated by XAV-939 (a β-catenin inhibitor) or overexpression of β-catenin, respectively. Finally, knockdown of PYGB inhibited tumor growth in a mouse model of xenograft tumors. These findings highlight the role of PYGB in the progression of NSCLC, and reveal a link between PYGB and the Wnt-β-catenin signaling pathway, thus providing a new potential target for treatment of NSCLC.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 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".