Therapeutic delivery of siRNA with polymeric carriers to down-regulate STAT5A expression in high-risk B-cell acute lymphoblastic leukemia (B-ALL)
Bibliographic record
Abstract
Overexpression and persistent activation of STAT5 play an important role in the development and progression of acute lymphoblastic leukemia (ALL), the most common pediatric cancer. Small interfering RNA (siRNA)-mediated downregulation of STAT5 represents a promising therapeutic approach for ALL to overcome the limitations of current treatment modalities such as high relapse rates and poor prognosis. However, to effectively transport siRNA molecules to target cells, development of potent carriers is of utmost importance to surpass hurdles of delivery. In this study, we investigated the use of lipopolymers as non-viral delivery systems derived from low molecular weight polyethylenimines (PEI) substituted with lauric acid (Lau), linoleic acid (LA) and stearic acid (StA) to deliver siRNA molecules to ALL cell lines and primary samples. Among the lipid-substituted polymers explored, Lau- and LA-substituted PEI displayed excellent siRNA delivery to SUP-B15 and RS4;11 cells. STAT5A gene expression was downregulated (36-92%) in SUP-B15 and (32%) in RS4;11 cells using the polymeric delivery systems, which consequently reduced cell growth and inhibited the formation of colonies in ALL cells. With regard to ALL primary cells, siRNA-mediated STAT5A gene silencing was observed in four of eight patient cells using our leading polymeric delivery system, 1.2PEI-Lau8, accompanied by the significant reduction in colony formation in three of eight patients. In both BCR-ABL positive and negative groups, three of five patients demonstrated marked cell growth inhibition in both MTT and trypan blue exclusion assays using 1.2PEI-Lau8/siRNA complexes in comparison with their control siRNA groups. Three patient samples did not show any positive results with our delivery systems. Differential therapeutic responses to siRNA therapy observed in different patients could result from variable genetic profiles and patient-to-patient variability in delivery. This study supports the potential of siRNA therapy and the designed lipopolymers as a delivery system in ALL therapy.
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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) | 0.000 | 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 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".