The lncRNA <i>ELDR</i> suppresses tumorigenicity of AML by interfering with DNA replication and chromatin accessibility
Bibliographic record
Abstract
ABSTRACT: Acute myeloid leukemia (AML) with rearrangement of the mixed lineage leukemia gene expresses MLL-AF9 fusion protein, a transcription factor that impairs differentiation and drives expansion of leukemic cells. In this work, the zinc finger protein "growth factor independent 1" together with the histone methyltransferase LSD1 is revealed to occupy the promoter and regulate the expression of the lncRNA ELDR (EGFR [epidermal growth factor receptor] long non-coding downstream RNA) in the rearranged Mixed Lineage Leukemia (MLL) (MLL-r) AML cell line THP-1. Forced ELDR overexpression enhanced the growth inhibition of an Lysine-Specific Demethylase 1 inhibitor (LSD1i)/all-trans retinoic acid (ATRA) combination treatment and reduced the capacity of these cells to generate leukemia in xenografts, leading to a longer leukemia-free survival. ELDR is found to bind the clamp protein Proliferating Cell Nuclear Antigen (PCNA) and the MCM5 helicases causing defects of DNA replication fork progression. Moreover, AML cells overexpressing ELDR had reduced chromatin accessibility and transcription at α-satellite repeats in centromeres. In addition, ELDR RNA was detected close to MLL-AF9 at centromeres suggesting that it impedes leukemic progression preferentially of MLL-r AML by interfering with both DNA replication and centromeric transcription. Our findings reveal novel functions of the lncRNA ELDR in DNA replication and centromere biology when expressed at high levels in AML cells with MLL rearrangements. These discoveries could provide rationale for future strategies to treat MLL-r AML, which has a poor prognosis in children and adults. Delivery of the ELDR RNA could potentially be used as an adjunct to LSD1i/ATRA treatment or other currently used chemotherapeutic drugs to develop novel therapies for these AML subtypes.
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".