Targeted Gene Silencing BRAF Synergized Photothermal Effect Inhibits Hepatoma Cell Growth Using New GAL-GNR-siBRAF Nanosystem
Bibliographic record
Abstract
Liver cancer is one of the most common malignancies worldwide. The RAF kinase inhibitors are effective in the treatment of hepatocellular carcinoma (HCC); therefore, inhibition of the BRAF/MEK/ERK pathway has become a new therapeutic strategy for novel HCC therapy. However, targeted specific delivery systems for tumors are still significant obstacle to clinical applications. Galactose (GAL) can target the asialoglycoprotein receptor (ASGPR) that is highly expressed on liver cancer cells. In this study, we designed a novel multifunctional nanomaterial GAL-GNR-siBRAF which consists of three parts, GAL as the liver cancer-targeting moiety, golden nanorods (GNR) offering photothermal capability under near infrared light, and siRNA specifically silencing BRAF (siBRAF). The nanocarrier GAL-GNR-siBRAF showed high siRNA loading capacity and inhibited the degradation of siRNA in serum. Compared with naked gold nanorods, GAL-GNR-siBRAF possessed lower biotoxicity and higher efficacy of gene silencing. Treatment with GAL-GNR-siBRAF significantly downregulated the expression of BRAF and impaired proliferation, migration, and invasion of liver cancer cells. Moreover, combinatorial photothermal effects and BRAF knockdown by GAL-GNR-siBRAF effectively given rise to tumor cell death. Therefore, our study developed a new type of targeted multi-functional nanomaterial GAL-GNR-siBRAF for the treatment of liver cancer, which provides ideas for the development of new clinical treatment methods.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".