Long Non-coding RNA Rhabdomyosarcoma 2-Associated Transcript Regulates Angiogenesis in Endothelial Cells
Bibliographic record
Abstract
Background: Long non-coding RNAs (lncRNAs) are non-coding RNAs that have more than 200 nucleotides. They have recently emerged as important regulators of angiogenesis. To identify novel lncRNAs that may be involved in the regulation of angiogenesis, we detected the mRNA of 84 lncRNAs in human umbilical vein endothelial cells (HUVECs) exposed to hypoxia for 24h. One of these, rhabdomyosarcoma 2-associated transcript (RMST), is significantly upregulated by hypoxia. Little is known about the presence and roles of RMST in EC function. Objective: The main objective of the study was to investigate the regulation of RMST in ECs and to determine its role in EC survival, proliferation, migration, and differentiation. Methods: Using qPCR, basal mRNA levels of 10 RMST isoforms in HUVECs were measured. Levels were then measured in response to 24h of hypoxia, 7days of differentiation in a co-culture assay, and exposure to four different angiogenesis factors. Functional roles of RMST in EC survival, migration, and differentiation were quantified by using a loss-of-function approach (transfection with single-stranded antisense LNA GapmeRs). EC survival was measured using cell counts and crystal violet assays. Cell migration and differentiation were measured using scratch wound healing and Matrigel® differentiation assays, respectively. Results: Five RMST isoforms (RMST-202, -203, -204, -206, and -207) were detected in HUVECs and human microvascular endothelial cells (HMEC-1s). Other types of vascular cells, including human aortic valve interstitial cells and human aortic smooth muscle cells, did not display this expression profile. RMST was significantly upregulated in response to 24h of hypoxia and in response to 7days of HUVEC co-culture with human lung fibroblasts. RMST was significantly downregulated by angiopoietin-2 (Ang-2), but not by VEGF, FGF-2, or angiopoietin-1 (Ang-1). Selective knockdown of RMST demonstrated that it promotes EC survival in response to serum deprivation. It is also required for VEGF- and Ang-1-induced EC survival and migration, but not for differentiation. Conclusion: We conclude that RMST is expressed in human ECs and that this expression is upregulated in response to hypoxia and during differentiation into capillary-like structures. We also conclude that RMST plays important roles in EC survival and migration.
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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".