LncRNA EPB41L4A-AS1 regulates glycolysis and glutaminolysis by mediating nucleolar translocation of HDAC2
Bibliographic record
Abstract
BACKGROUND: LncRNAs have been found to be involved in various aspects of biological processes. In this study, we aimed to uncover the molecular mechanisms of lncRNA EPB41L4A-AS1 in regulating glycolysis and glutaminolysis in cancer cells. METHODS: The expression of EPB41L4A-AS1 in cancer patients was analyzed in TCGA and GEO datasets. The level of cellular metabolism was determined by extracellular flux analyzer. The relationship between p53 and EPB41L4A-AS1 was explored by qRT-PCR, luciferase assay and ChIP assay. The interactions between EPB41L4A-AS1 and HDAC2 or NPM1 were determined by RNA immunoprecipitation, RNA pull-down assay and RNA-FISH- immunofluorescence. FINDINGS: EPB41L4A-AS1 was a p53-regulated gene. Low expression and deletion of lncRNA EPB41L4A-AS1 were found in a variety of human cancers and associated with poor prognosis of cancer patients. Knock down EPB41L4A-AS1 expression triggered Warburg effect, demonstrated as increased aerobic glycolysis and glutaminolysis. EPB41L4A-AS1 interacted and colocalized with HDAC2 and NPM1 in nucleolus. Silencing EPB41L4A-AS1 reduced the interaction between HDAC2 and NPM1, released HDAC2 from nucleolus and increased its distribution in nucleoplasm, enhanced HDAC2 occupation on VHL and VDAC1 promoter regions, and finally accelerated glycolysis and glutaminolysis. Depletion of EPB41L4A-AS1 increased the sensitivity of tumor to glutaminase inhibitor in tumor therapy. INTERPRETATION: EPB41L4A-AS1 functions as a repressor of the Warburg effect and plays important roles in metabolic reprogramming of cancer.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".