Modulation of eIF5A Expression Using SNS01 Nanoparticles Inhibits NF-κB Activity and Tumor Growth in Murine Models of Multiple Myeloma
Bibliographic record
Abstract
Despite recent advances in the first-line treatment of multiple myeloma, almost all patients eventually experience relapse with drug-resistant disease. New therapeutic modalities are needed, and to this end, SNS01, a therapeutic nanoparticle, is being investigated for treatment of multiple myeloma. The antitumoral activity of SNS01 is based upon modulation of eukaryotic translation initiation factor 5A (eIF5A), a highly conserved protein that is involved in many cellular processes including proliferation, apoptosis, differentiation and inflammation. eIF5A is regulated by post-translational hypusine modification, and overexpression of hypusination-resistant mutants of eIF5A induces apoptosis in many types of cancer cells. SNS01 is a polyethylenimine (PEI)-based nanoparticle that contains both a B-cell-specific expression plasmid expressing a non-hypusinable mutant of eIF5A and a small interfering RNA (siRNA) which depletes endogenous hypusinated eIF5A. Reducing hypusine-modified eIF5A levels was found to inhibit phosphorylation and activity of ERK MAPK and nuclear factor-κB (NF-κB), and thus sensitize myeloma cells to apoptosis resulting from transfection of a plasmid expressing eIF5A(K50R). SNS01 exhibited significant antitumoral activity in both KAS-6/1 (95% inhibition; P < 0.05) and RPMI 8226 (59% inhibition; P < 0.05) multiple myeloma xenograft models following systemic administration. These results highlight the potential of using this approach as a new therapeutic strategy for multiple myeloma.
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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".