Novel Frog Skin-Derived Peptide Dermaseptin-PP for Lung Cancer Treatment: In vitro/vivo Evaluation and Anti-tumor Mechanisms Study
Bibliographic record
Abstract
Lung cancer is the major cause of cancer deaths worldwide, which has the highest incidence and mortality among men and women in China. The first-line therapy for lung cancer treatment is the platinum-based chemotherapy drugs such as cisplatin. However, the application of present chemotherapies is limited by severe side effects, which stimulates the discovery of new drugs with new anti-tumor mechanisms and fewer side effects. Beneficially, many antimicrobial peptides (AMPs) from frog skin were reported to exhibit potent anti-cancer activities low toxicity, high selectivity and a low propensity to induce resistance. In this study, we first reported an AMP named Dermaseptin-PP, from a rarely studied frog species, Phyllomedusa palliata. Dermaseptin-PP exhibited selective cytotoxicity on H157, MCF-7, PC-3 and U251 MG cancer cells instead of normal HMEC-1 cells with low hemolytic effect. Furthermore, on H157 subcutaneous tumor model of nude mice, Dermaseptin-PP was found to perform potent in vivo anti-tumor activity in a dose-related manner without obvious hepatopulmonary side effects. Further mechanisms investigation by laser confocal observation, flow cytometry assay and immunohistochemical analysis unraveled that Dermaseptin-PP could disrupt H157 cell membranes, and induce H157 cell apoptosis via both endogenous mitochondrial and exogenous death receptor apoptosis pathways. Herein, we emphasize that the membrane disrupting and the apoptosis activation effects of Dermaseptin-PP both depend on its concentration. Overall, a novel frog skin-derived AMP, Dermaseptin-PP with strong antimicrobial and effective anti-tumor activity by distinct mechanisms has been identified for the first time. Moreover, this study revealed the possibility of Dermaseptin-PP for lung cancer treatment and provided a new perspective for designing novel AMP-based anti-tumor candidates with low risk of cytotoxicity.
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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) | 0.000 | 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".