Up-regulated LINC01234 promotes non-small-cell lung cancer cell metastasis by activating VAV3 and repressing BTG2 expression
Bibliographic record
Abstract
BACKGROUND: Long noncoding RNAs (lncRNAs) are known to regulate tumorigenesis and cancer progression, but their contributions to non-small-cell lung cancer (NSCLC) metastasis remain poorly understood. Our previous and other studies have revealed the involvement of upregulated LINC01234 in regulating gastric cancer and colon cancer cells proliferation, and we aimed to investigate whether LINC01234 overexpression also contribute to cancer cells metastasis in this study. METHODS: We collect the NSCLC tissues and adjacent non-tumor tissues and analyzed expression levels of LINC01234 by quantitative reverse-transcription PCR. LINC01234 were knocked down by using siRNAs or shRNAs, and overexpressed by transfection with overexpression vector; RNA levels of miRNA were downregulated or upregulated with inhibitors or mimics. Transwell assays were used to evaluate cell migration and invasive ability; in vivo metastasis experiments were performed to investigate the effect of LINC01234 on NSCLC cells metastasis. Luciferase reporter, RIP, and ChIP assays were used to determine the regulation of LINC01234 on its targets. RESULTS: LINC01234 expression is increased in NSCLC tissues, and its upregulation is associated with metastasis and shorter survival in NSCLC. Downregulation of LINC01234 impairs cell migration and invasion in vitro, and inhibits cells metastasis in vivo by acting as a competing endogenous RNA for the miR-340-5p and miR-27b-3p. LINC01234 also interacts with the RNA-binding proteins LSD1 and EZH2, leading to histone modification and transcriptional repression of the anti-proliferative genes BTG2. CONCLUSIONS: Taken together, our findings identify two oncogenic regulatory axes in NSCLC centering on LINC01234: one involving miR-340-5p/miR-27b-3p in the cytoplasm and the second involving EZH2, LSD1, and BTG2 in the nucleus. Our study indicates that these genes may be targeted to reduce or prevent NSCLC metastasis.
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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) | 0.003 | 0.001 |
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".