Liposomal delivery of DK14 chalcone analogue: A promising therapeutic strategy against triple-negative breast cancer
Bibliographic record
Abstract
Triple negative breast cancer (TNBC) is considered the most aggressive type of breast malignancy. TNBC management approaches remain limited, with a high risk of relapse and metastasis. Chalcone compounds are established for their anticancer activity. A recently patented novel chalcone compound (DK14) by our group has demonstrated a considerable activity against TNBC; however, its limited water-solubility is a challenge. In this study, we incorporated DK14 into a nano-liposomal formulation to enhance its solubility, safety and anticancer activity. The formulation was characterized in terms of particle size, zeta potential, drug entrapment, and release profile. Additionally, cytotoxicity, cell migration, colony formation and protein expression analysis were conducted. Furthermore, Angiogenesis study was performed using the chorioallantoic membrane (CAM) of the chicken embryo. DK14-liposomes demonstrated the ability to inhibit growth of TNBC cells and trigger apoptosis, accompanied by induction of BAX/BCL-2/Caspase-3 pathway. DK14-liposomes also exhibited an enhanced safety profile on non-tumorigenic mammary epithelial cells (MCF-10A) compared to free DK14 while suppressing cell migration and colony formation. Moreover, DK14-liposomes dysregulated PI3K/AKT/mTOR pathway, which is defective in TNBC; and significantly inhibited angiogenesis in ovo using a chiken embryo model. In conclusion, our results imply that DK14-liposomes have a substantial anticancer activity against TNBC with distinct anti-angiogenic properties.
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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".