| Literature DB >> 35682787 |
Giulia E Valenti1, Silvana Alfei2, Debora Caviglia3, Cinzia Domenicotti1,4, Barbara Marengo1,4.
Abstract
In the last few years, antibiotic resistance and, analogously, anticancer drug resistance have increased considerably, becoming one of the main public health problems. For this reason, it is crucial to find therapeutic strategies able to counteract the onset of multi-drug resistance (MDR). In this review, a critical overview of the innovative tools available today to fight MDR is reported. In this direction, the use of membrane-disruptive peptides/peptidomimetics (MDPs), such as antimicrobial peptides (AMPs), has received particular attention, due to their high selectivity and to their limited side effects. Moreover, similarities between bacteria and cancer cells are herein reported and the hypothesis of the possible use of AMPs also in anticancer therapies is discussed. However, it is important to take into account the limitations that could negatively impact clinical application and, in particular, the need for an efficient delivery system. In this regard, the use of nanoparticles (NPs) is proposed as a potential strategy to improve therapy; moreover, among polymeric NPs, cationic ones are emerging as promising tools able to fight the onset of MDR both in bacteria and in cancer cells.Entities:
Keywords: antibiotics; anticancer drugs; antimicrobial peptides; cationic nanoparticles; multi-drug resistance
Mesh:
Substances:
Year: 2022 PMID: 35682787 PMCID: PMC9181033 DOI: 10.3390/ijms23116108
Source DB: PubMed Journal: Int J Mol Sci ISSN: 1422-0067 Impact factor: 6.208
Figure 1Comparison among membrane lipid composition of healthy mammalian cells, Gram-positive and Gram-negative bacteria.
Figure 2Comparison among membrane lipid composition of healthy mammalian cells and cancer cells.
ACPs showing antitumor and/or antiviral effects, classified according to their structural characteristics into four categories: α-helical, β-pleated sheets, random coil and cyclic [116,117].
| Category | Feature | ACP | Model |
|---|---|---|---|
| α-Helical | Peptides short in length | Magainin II | Lung cancer cells |
| Aurein | Glioblastoma cells | ||
| L-K6 | Breast cancer cells | ||
| LL37 | Colorectal cancer cells (HCT116) | ||
| FK-16 | |||
| β-Pleated sheet | Two or more disulfide bonds Good stability | Bovine lactoferrin (LfcinB) | Gastric cancer cells |
| MPLfcinB6 | Human T leukemia cells | ||
| MPLfcin-P13 | Hepatocellular carcinoma cells (HepG2) | ||
| Human neutrophil peptide | Prostate cancer cells | ||
| Random coil ACPs | Rich in proline and glycine | Alloferon | Herpes simplex virus |
| KW-WK | N.R. | ||
| PR39 | N.R. | ||
| PR35 | N.R. | ||
| Cyclic ACPs | Closed peptides composed of a head-to-tail cyclization backbone or disulfide bonds that form cystine knots | Hedyotis diffusa Cytide 1–3 | Prostate cancer cells |
| H-10 | Malignant melanoma cells (B16) | ||
| RA-XII | Colorectal tumor cells (HCT116) |
N.R. = not reported.
ACPs in clinical trials ongoing or already approved and marketed.
| ACPs in Development | Phase of Development | Target Tumor | Advantages |
|---|---|---|---|
| Bryostatin 1 | Phase 1 | Melanoma | |
| Aplidine (plitidepsin) | Phase 1 (completed) | Well tolerated | |
| Phase 2 (in progress) | Advanced medullary thyroid carcinoma | ||
| Kyprolis [ | Approved by FDA and EMA (marketed) | N.R. | N.S. |
| SomaKit TOC [ | |||
| Lutathera [ | |||
| Gallium Dotatoc Ga68 [ |
N.R. = not reported; N.S. = not specified.
Figure 3Models of ACPs’ action. In the carpet model (left), ACPs bind to the cell membrane via electrostatic interactions and, subsequently, ACPs may enter the cell membrane, inducing membrane disruption. In the barrel-stave model (right), peptides self-aggregate and form a transmembrane pore, leading to membrane depolarization.
Figure 4NPs’ interaction with cell membrane and their killing ability on cancer cells and bacteria.