The role of miR-150-5p/E2F3/survivin axis in the pathogenesis of plasmablastic lymphoma and its therapeutic potential
Bibliographic record
Abstract
ABSTRACT: Plasmablastic lymphoma (PBL) is an uncommon and aggressive B-cell lymphoma with a poor prognosis. Some studies have described genetic alterations in PBL, but its transcriptome has been scarcely studied, and molecular mechanisms driving lymphomagenesis remain poorly understood. Our goal was to delineate transcriptomic profiles to identify potential biomarkers for novel targeted therapy in PBL. RNA sequencing uncovered an enrichment of cell cycle-related genes, including MYC and E2F targets, and genes involved in G2/M checkpoint in PBL. Microarray analyses discovered 2 microRNA expression signatures depending on the presence of MYC translocation. Interestingly, miR-150-5p was downregulated, whereas E2F3 and BIRC5 (survivin), a cell cycle activator and an antiapoptotic regulator, respectively, were upregulated. Increasing miR-150-5p in PBL-1 cells induced G1 cell cycle arrest, suppressed proliferation by transcriptionally repressing E2F3, and promoted apoptosis by the downregulation of BIRC5. Interestingly, the miR-150-5p tumor suppressor activity was diminished in E2F3-knockdown cells. The combined inhibition of E2F3 and survivin attenuated lymphomagenesis in PBL cells and suppressed tumor growth in a chorioallantoic membrane-derived xenograft model of PBL. Overall, our study highlights the pivotal role of the miR-150-5p/E2F3/survivin axis in boosting PBL lymphomagenesis and unveils new therapeutic targets for this lymphoma.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".