Silencing linc00662 inhibits cell proliferation and colony formation of lung cancer cells via regulating the miR-145-5p–PAFAH1B2 axis
Bibliographic record
Abstract
Lung cancer is the most common cause of cancer-related death in the world. Long non-coding RNAs (lncRNAs) are longer than 200 nucleotide transcripts, and are not translated into protein. The lncRNA linc00662 is overexpressed in lung cancer; however, its role in lung cancer is still unknown. In our study, by analyzing the TCGA data, we found that linc00662 was overexpressed in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). We knocked-down the expression of linc00662 using siRNA, and found that silencing linc00662 significantly inhibited the proliferation and colony formation of the lung cancer cell lines A549 and H460. We also found that knockdown of linc00662 increased the expression of the microRNA miR-145-5p and decreased the expression of the platelet-activating factor acetylhydrolase IB subunit beta (PAFAH1B2) gene. We further show that linc00662 binds with miR-145-5p, and that miR-145-5p binds to the 3′UTR of PAFAH1B2. miR-145-5p negatively regulates PAFAH1B2 both at the mRNA and the protein level. Loss of miR-145-5p abolished the inhibitory effects of silencing linc00662 on the proliferation and colony formation of A549 and H460 cells. These findings indicate that linc00662 functions as an oncogene by acting as a competing endogenous RNA (ceRNA) and sponges and regulates miR-145-5p in lung cancer, and thus may provide a potential target for treating lung cancer.
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.
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".