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Evaluation of lipopolymer as therapeutic siRNA delivery agents in non-malignant and malignant primary cells.

2024· article· en· W4399328153 on OpenAlexaff
Aysha Ansari, Cezary Kucharski, Mahsa Mohseni, Daniel NM Sundaram, Joseph Brandwein, Xiaoyan Jiang, Hasan Uludağ

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsBC Cancer AgencyUniversity of Alberta
Fundersnot available
KeywordsMedicineMalignant cellsCancer researchPrimary (astronomy)OncologyCancerPharmacologyInternal medicine

Abstract

fetched live from OpenAlex

e15189 Background: Targeting leukemia-driving oncogenes via short interfering RNA (siRNA) offers an alternative approach to leukemia treatment that can overcome the limitations of current therapies. Low molecular weight polyethyleneimine grafted with lipids (lipopolymers) have emerged as promising carriers for siRNA delivery to leukemia cells. Lipopolymers harboring select lipids were recently shown to downregulate target oncogene leading to significant anti-leukemic activity in both in vitro and in vivo cell line-based leukemia models. The goal of this study was to evaluate these lipopolymers in (i) PBMCs obtained from healthy donors to determine the potential impact on non-malignant cells, and (ii) primary leukemia patient cells to assess therapeutic efficacy. Methods: Target gene levels were determined by RT-qPCR and the effect of treatment on progenitor cells was assessed by measuring changes in colony forming ability. Results: At day 1 post-treatment, no changes in FLT3 mRNA levels were observed in all 6 PBMC samples with the 2 candidate lipopolymers (LeuFectB and LeuFectC) tested. Among 11 PBMC samples evaluated at day 2, only one sample showed a significant reduction in oncogene transcript levels on treatment with LeuFectB. The impact of lipopolymer/siRNA complex treatment on progenitor cells in the PBMC population was then assessed. Of the 7 PBMC samples tested, significant reduction in colony numbers was observed in one sample with LeuFectB and two samples with LeuFectC. On an average, the lipopolymer/siRNA complexes were well tolerated by normal healthy cells as changes observed in oncogene expression and colony forming ability were not consistent across the whole pool. Primary acute lymphoblastic leukemia (ALL) patient cells treated with complexes targeting STAT5A showed marked reduction in STAT5A transcript levels in 4 out of 7 samples with both the lipopolymers tested. The subsequent impact of STAT5A downregulation on the clonogenicity of leukemia stem cells was observed in the significant decrease in colony numbers seen in 3 samples (out of 8) with LeuFects. Additionally, combined downregulation of STAT5A and BCR-ABL genes in BCR-ABL+ ALL patient samples led to a notable decrease in cell proliferation and viability. Moreover,2 out of 3 acute myeloid leukemia (AML) patient samples harboring the FLT3-ITD mutation showed significant retardation in their colony forming ability on treatment with FLT3-targeting siRNA complexes. Collectively, the ALL and AML primary samples demonstrated promising preliminary results, suggesting a therapeutic effect on the stem cell population which is critical for mitigating relapse or prolonging remission. Conclusions: These findings provide further proof-of-concept for clinical translation of lipopolymer mediated siRNA therapy of leukemia, showing relative safety and selectivity of these lipopolymer/siRNA complexes.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.101
GPT teacher head0.432
Teacher spread0.331 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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