TRPM2‐AS inhibits the growth, migration, and invasion of gliomas through JNK, c‐Jun, and RGS4
Bibliographic record
Abstract
Gliomas are a group of brain cancers with high mortality and morbidity. Understanding the molecular mechanisms is important for the prevention or treatment of gliomas. The present study was to investigate the effects and mechanisms of long noncoding RNA TRPM2-AS in gliomas proliferation, migration, and invasion. We first compared the levels of TRPM2-AS in 111 patients with glioma to that of the normal control group by a quantitative polymerase chain reaction. The results indicated a significant increase of TRPM2-AS in patients with glioma (2.43 folds of control, p = .0135). MTT methods, wound healing assays, transwell analysis, and clone formation analysis indicated the overexpression of TRPM2-AS promoted the proliferation, migration, and invasion of U251 and U87 cells, while downregulation of TRPM2-AS inhibited the cell proliferation, migration, and invasion significantly (p < .05). To further uncover the mechanisms, bioinformatics analysis was conducted on the expression profiles, GSE40687 and GSE4290, from the Gene Expression Omnibus database. One hundred fifty-six genes were differentially expressed in both datasets (FC > 2.0; p = .05). Among these differentially expressed genes, the level of RGS4 messenger RNA was drastically regulated by TRPM2-AS. Further western-blot analysis indicated the increase of RGS4 protein expression and decrease of p-JNK/JNK and p-c-Jun/c-Jun ratio after TRPM2-AS overexpression. On the other hand, inhibition of TRPM2-AS by small interfering RNA suppressed the expression of RGS4 and promoted the ratios of p-JNK/JNK and p-c-Jun/c-Jun. The present work indicated the mechanisms of the participation of TRPM2-AS in the progression of gliomas might, at least partly, be related to JNK, c-Jun, and RGS4. Our work provided new insights into the underlying mechanisms of glioma cellular functions.
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How this classification was reachedexpand
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) | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".