A Serum‐Stable Antimicrobial Peptide‐Based Delivery Platform for Selective Treatment of Nontargetable and Chemoresistant Tumors
Bibliographic record
Abstract
Antibody-drug conjugates (ADCs) have transformed cancer therapy but remain limited by their dependence on internalizing antigens, poor applicability to untargetable tumors, and susceptibility to drug resistance. Therefore, a modular antimicrobial-peptide (AMP)-based therapeutic system centered on a rationally designed conjugate, 270, is presented, which integrates three optimized components: a selectivity-enhanced AMP core via a membrane affinity reconstruction strategy, a conformation-driven polyethylene glycolylated blocker to minimize off-target effects, and an N-terminal cap to improve stability in human serum. By targeting nonendocytic membrane surface receptors via small-molecule ligands, conjugate 270 exhibits potent and selective cytotoxicity against target tumor cells, effectively eliminating the majority of tumor cells within a few hours. Meanwhile, it exhibits high serum stability, minimal hemolysis, and negligible cytotoxicity toward normal cells at therapeutic concentrations. Mechanistic studies confirm ligand-dependent membrane localization, rapid depolarization, and disruption, along with mitochondrial dysfunction. Moreover, it demonstrates significant therapeutic efficacy against four cell lines resistant to conventional chemotherapeutic agents. While additional in vivo validation is warranted, this work lays the foundation for a flexible AMP-based approach to address untargetable and drug-resistant cancers.
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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 | 0.001 |
| 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".