Evaluation of a Synthetic PEI-based Polymeric Vector for ING4 Gene Delivery to MCF-7 Breast Cancer Cells
Bibliographic record
Abstract
Objectives: Breast cancer is the most common type of cancer among women and the second most common cause of death after lung cancer.The inhibitor of growth (ING) transcript levels are often suppressed in cancer cells, making it a promising candidate for cancer therapy.In this study, we aimed to formulate a polyplex that effectively carries and delivers pING4 to breast cancer cells.Materials and Methods: Polyethyleneimine (PEI)-based non-viral vectors were synthesized and characterized for plasmid DNA delivery.Complexation was achieved via electrostatic interactions between the synthesized polymeric vectors and plasmid DNA.Characterization studies were conducted by testing Sodium dodecyl sulfate-induced complexation, Deoxyribonuclease I protection, and serum stability of the polyplexes.Subsequently, polyplexes were tested on MCF-7 cells for anticancer activity using the XTT cell viability assay.Western blot analysis was performed for the ING4 protein.Results: Polyplexes carrying the ING4 gene exhibited significantly lower cell viability than control polyplexes (p=0.0067).During the 5-day viability assay, the lowest cell viability was observed on day 4. Approximately 69.112.18%cell viability was observed with ING4 treatment and the control group showed no cell death on day 4 (101.535.06%).The prepared delivery systems did not show a toxic effect on MCF-7 cells treated alone.In addition, the MCF10A normal mammary cell line was used as a positive control.Western blotting was performed to confirm the overexpression of ING4 protein in the treatment groups.Unlike in the control groups, the overexpression of ING4 was clear in the wells of the treatment group.Conclusion: Our findings suggest that ING4 gene delivery using prepared PEI-based nonviral delivery systems is a promising approach for breast cancer treatment.
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 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 | 0.002 | 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".