Self-assembled nanomedicine combining a berberine derivative and doxorubicin for enhanced antitumor and antimetastatic efficacy<i>via</i>mitochondrial pathways
Bibliographic record
Abstract
Mitochondria play a central role in cancer progression and tumor metastasis, and nanomedicines targeting mitochondria have emerged as a promising strategy for tumor therapy. However, mitochondria targeting strategies have not been widely explored in the inhibition of tumor metastasis, and they have disadvantages of complicated preparation, low drug loading, systemic toxicity of the carriers and poor accumulation at tumor sites. Here we firstly developed self-assembled nanodrugs with a high drug loading (∼68%) comprised of a berberine derivative (Ber) and doxorubicin (Dox) by a simple nano-precipitation method, which successfully altered the target location of Dox from the nucleus to mitochondria and therefore inhibited the proliferation, invasion and migration of MDA-MB-231 cells by triggering cell apoptosis. The surface of nanodrugs was modified with DSPE-PEG-folic acid (DSPE-PEG-FA) and hyaluronic acid (HA) for precise tumor recognition and enhanced accumulation (HA-FA-BD NDs). Upon arrival at the tumor site with the help of the enhanced permeability and retention (EPR) effect, the partial degradation of HA by hyaluronidase (HAase) at the tumor site allowed the partial exposure of the positively charged FA-BD NDs to the cells, then nanodrugs would accumulate and enter tumor cells by dual binding to both folic acid (FA) and CD-44 receptors. Once internalized into lysosomes, both the HA outer shell and DSPE-PEG-FA of nanodrugs were degraded or decomposed completely to expose positively charged BD NDs. Driven by delocalized lipophilic cations, nanodrugs could escape from lysosomes and reach mitochondria to induce a cascade reaction and finally cell apoptosis, as well as suppressing matrix metalloprotease (MMP)-2 and -9 activities and finally cell migration and invasion. In a xenograft mice model of MDA-MB-231 breast cancer cells, the nanodrugs repaired the defects in Mfn 1/Drp 1 mitochondrial proteins, suppressed the activity of MMP-2 and -9, and significantly inhibited tumor cell proliferation and pulmonary metastasis. Our study showed a promising strategy for the treatment of metastatic breast cancer by targeting mitochondria followed by enhanced apoptosis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".