SNS01-T Modulation of eIF5A Inhibits B-cell Cancer Progression and Synergizes With Bortezomib and Lenalidomide
Bibliographic record
Abstract
The high rates of recurrence and low median survival in many B-cell cancers highlight a need for new targeted therapeutic modalities. In dividing cells, eukaryotic translation initiation factor 5A (eIF5A) is hypusinated and involved in regulation of protein synthesis and proliferation, whereas the non-hypusinated form of eIF5A is a potent inducer of cell death in malignant cells. Here, we demonstrate the potential of modulating eIF5A expression as a novel approach to treating B-cell cancers. SNS01-T is a nonviral polyethylenimine-based nanoparticle, designed to induce apoptosis selectively in B-cell cancers by small interfering RNA-mediated suppression of hypusinated eIF5A and plasmid-based overexpression of a non-hypusinable eIF5A mutant. In this study, we show that SNS01-T is preferentially taken up by malignant B cells, inhibits tumor growth in multiple animal models of B-cell cancers without damaging normal tissues, and synergizes with the current therapies bortezomib and lenalidomide to inhibit tumor progression. The results collectively demonstrate the potential of SNS01-T as a novel therapeutic for treatment of a diverse range of B-cell malignancies.
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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".