Repression of linc01555 up-regulates angiomotin-p130 via the microRNA-122-5p/clic1 axis to impact vasculogenic mimicry-mediated chemotherapy resistance in small cell lung cancer
Bibliographic record
Abstract
Long non-coding ribonucleic acid 01555 (linc01555) is a brand-new long non-coding RNA (lncRNA) that acts a carcinogenic function in various cancers. However, its role in small cell lung cancer (SCLC) is uncertain. This research was to figure out the role of linc01555 in cisplatin (DDP) resistance of SCLC cells and its possible latent mechanism. After establishment of the resistant sub-strain H446/DDP or DMS-53/DDP, detection of linc01555, microRNA (miR)-122-5p and CLICl was done in the H446/DDP or DMS-53/DDP cell line. After intervention, cell biological functions were determined, as well as tube formation ability. The detection of angiomotin (Amot)-p130 and the validation of the regulatory mechanism were performed. Furthermore, tumor xenografts were applied in nude mice to evaluate the effect of linc01555 on DDP resistance in SCLC in vivo. Linc01555 was elevated in SCLC tissues and cells, and in H446/DDP cells or DMS-53/DDP vs. its parental cells; Restraining linc01555 or elevating miR-122-5p repressed the proliferation and metastasis of H446/DDP or DMS-53/DDP cells and vasculogenic mimicry (VM) formation. CLIC1 mediated miR-122-5p to influence the occurrence and development of SCLC. Linc01555 competitively combined with miR-122-5p, which targeted CLIC1. Refrained linc01555 elevated Amot-p130 via the miR-122-5p/CLIC1 axis. Reduced linc01555 refrained tumor growth and DDP resistance in vivo.In short, linc01555 may cause changes in DDP resistance via miR-122-5p/CLIC1 in SCLC. The finding may offer drug targets for SCLC resistance.
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) | 0.002 | 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".