Cancer is currently ineffectively treated using therapeutic drugs, and is also able to resist drug action, resulting in increased side effects following drug treatment. A novel therapeutic strategy ...against cancer cells is the use of anticancer peptides (ACPs). The physicochemical properties, amino acid composition and the addition of chemical groups on the ACP sequence influences their conformation, net charge and orientation of the secondary structure, leading to an effect on targeting specificity and ACP-cell interaction, as well as peptide penetrating capability, stability and efficacy. ACPs have been developed from both naturally occurring and modified peptides by substituting neutral or anionic amino acid residues with cationic amino acid residues, or by adding a chemical group. The modified peptides lead to an increase in the effectiveness of cancer therapy. Due to this effectiveness, ACPs have recently been improved to form drugs and vaccines, which have sequentially been evaluated in various phases of clinical trials. The development of the ACPs remains focused on generating newly modified ACPs for clinical application in order to decrease the incidence of new cancer cases and decrease the mortality rate. The present review could further facilitate the design of ACPs and increase efficacious ACP therapy in the near future. Key words: therapeutic peptide, anticancer peptide, modified peptide, targeting peptide, cancer, clinical application, clinical trial
As anticancer peptides (ACPs) have attracted great interest for cancer treatment, several approaches based on machine learning have been proposed for ACP identification. Although existing methods ...have afforded high prediction accuracies, however such models are using a large number of descriptors together with complex ensemble approaches that consequently leads to low interpretability and thus poses a challenge for biologists and biochemists. Therefore, it is desirable to develop a simple, interpretable and efficient predictor for accurate ACP identification as well as providing the means for the rational design of new anticancer peptides with promising potential for clinical application. Herein, we propose a novel flexible scoring card method (FSCM) making use of propensity scores of local and global sequential information for the development of a sequence-based ACP predictor (named iACP-FSCM) for improving the prediction accuracy and model interpretability. To the best of our knowledge, iACP-FSCM represents the first sequence-based ACP predictor for rationalizing an in-depth understanding into the molecular basis for the enhancement of anticancer activities of peptides via the use of FSCM-derived propensity scores. The independent testing results showed that the iACP-FSCM provided accuracies of 0.825 and 0.910 as evaluated on the main and alternative datasets, respectively. Results from comparative benchmarking demonstrated that iACP-FSCM could outperform seven other existing ACP predictors with marked improvements of 7% and 17% for accuracy and MCC, respectively, on the main dataset. Furthermore, the iACP-FSCM (0.910) achieved very comparable results to that of the state-of-the-art ensemble model AntiCP2.0 (0.920) as evaluated on the alternative dataset. Comparative results demonstrated that iACP-FSCM was the most suitable choice for ACP identification and characterization considering its simplicity, interpretability and generalizability. It is highly anticipated that the iACP-FSCM may be a robust tool for the rapid screening and identification of promising ACPs for clinical use.
Recently, red blood cell-derived extracellular vesicles (RBCEVs) have attracted attention for clinical applications because of their safety and biocompatibility. RBCEVs can escape macrophages through ...the binding of CD47 to inhibitory receptor signal regulatory protein α. Furthermore, genetic materials such as siRNA, miRNA, mRNA, or single-stranded RNA can be encapsulated within RBCEVs and then released into target cells for precise treatment. However, their side effects, half-lives, target cell specificity, and limited large-scale production under good manufacturing practice remain challenging. In this review, we summarized the biogenesis and composition of RBCEVs, discussed the advantages and disadvantages of RBCEVs for drug delivery compared with synthetic nanovesicles and non-red blood cell-derived EVs, and provided perspectives for overcoming current limitations to the use of RBCEVs for clinical applications.
•EVs are key components of reciprocal communication between tumor and non-tumor cells in TME.•Tumors are eradicated by inhibiting EV release from tumor cells and transferring anti-cancer drug ...containing EV into the TME.•EVs can be engineered to improve tumor targeting and to carry anti-cancer drugs for more effective cancer therapy.
Tumor development is influenced by cell interactions within the tumor microenvironment (TME). Extracellular vesicles (EVs) released from tumor cells mediate critical signals that communicate with their TME to modulate tumor progression. These EVs can result in resistance to chemotherapy or immunotherapy during cancer treatment. Studies related to tumor-derived EV biogenesis and components have led to new strategies to enhance tumor sensitivity to standard treatments by blocking or neutralizing EV formation. Furthermore, engineered EVs expressing specific ligands and receptors have been investigated for targeted tumor delivery of therapeutic agents, improving treatment efficacy, and mitigating adverse effects. In addition, EVs have been modified to function as tumor vaccines to promote cancer immunity.
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Ten-Eleven Translocation methylcytosine dioxygenase 1 (TET1) is known to play a broad tumor suppressor role through demethylating and activating tumor suppressor genes. TET1 missense mutations are ...previously reported in many types of leukemia. Here, the human induced pluripotent stem cell line MURAi001-A was generated from skin fibroblasts derived from a 56-year-old female patient carrying the TET1 gene mutation c.4404A > G (p.I1468M), who had a history of ovarian germ cell tumor. The MURAi001-A cell line demonstrated embryonic-like characteristics as it expressed specific stemness markers, differentiated into the three germ layers, and retained normal karyotyping.
Extracellular vesicles (EVs) are nano-scaled vesicles released from all cell types into extracellular fluids and specifically contain signature molecules of the original cells and tissues, including ...the placenta. Placenta-derived EVs can be detected in maternal circulation at as early as six weeks of gestation, and their release can be triggered by the oxygen level and glucose concentration. Placental-associated complications such as preeclampsia, fetal growth restriction, and gestational diabetes have alterations in placenta-derived EVs in maternal plasma, and this can be used as a liquid biopsy for the diagnosis, prediction, and monitoring of such pregnancy complications. Alpha-thalassemia major ("homozygous alpha-thalassemia-1") or hemoglobin Bart's disease is the most severe form of thalassemia disease, and this condition is lethal for the fetus. Women with Bart's hydrops fetalis demonstrate signs of placental hypoxia and placentomegaly, thereby placenta-derived EVs provide an opportunity for a non-invasive liquid biopsy of this lethal condition. In this article, we introduced clinical features and current diagnostic markers of Bart's hydrops fetalis, extensively summarize the characteristics and biology of placenta-derived EVs, and discuss the challenges and opportunities of placenta-derived EVs as part of diagnostic tests for placental complications focusing on Bart's hydrop fetalis.
Hodgkin's lymphoma and anaplastic large cell lymphoma, especially relapsed or refractory diseases, could recently be cured by CD30-targeted immunotherapy. However, the CD30 antigen releases the ...soluble ectodomain of CD30, which might obscure the targeted therapy. Therefore, the membrane epitope of CD30 (mCD30), left on the cancer cells, might be a prospective target for lymphoma treatment. The discovery of novel mCD30 monoclonal antibodies (mAbs) using phage technology yielded 59 potential human single-chain variable fragments (HuscFvs). Ten candidate HuscFv clones have been selected based on various methods, i.e., direct PCR, ELISA and western blot assays, and nucleotide sequencing techniques. Fortunately, only one potential HuscFv clone, clone #A4, was determined by the prediction of HuscFv-peptide molecular docking and the binding affinity test using isothermal titration calorimetry. Finally, we proved that the HuscFv #A4, which had a binding affinity (Kd) of 421e-9 ± 2.76e-6 M, might be the novel mCD30 mAb. We generated chimeric antigen receptor-modified T lymphocytes using HuscFv #A4 as an antigen detection part (anti-mCD30-H4CART). The cytotoxicity assay of anti-mCD30-H4CART cells showed significant eradication of the CD30-expressing cell line, K562 (p = 0.0378). We found a novel mCD30 HuscFv using human phage technology. We systematically examined and proved that our HuscFv #A4 could specifically eradicate CD30-expressing cancers.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Children with refractory epilepsy (RE) are associated with increased mortality rate, nonfatal injuries, disability, and diminished quality of life. Biomarkers for the early prediction of RE is still ...an unmet need.
Eighteen children with RE and six age-matched unrelated controls were included in this study. Plasma samples were prefractionated by the optimized thermal treatment before proteomic analysis using 2DE-LC-MS/MS. Bioinformatic analysis was carried out using STRING protein network. Immunoassay of unprocessed plasma was applied to confirm changes of proteins of interest. P-value < 0.05 was considered statistically significant.
Proteomic analysis (n = 6 each group) revealed nine differentially expressed proteins, i.e., haptoglobin, S100A9, serpin B1, apolipoprotein A-I, apolipoprotein A-IV, apolipoprotein C-II, alpha-1-acid glycoprotein 1 and 2, and transthyretin. Western immunoblotting confirmed haptoglobin upregulation in the RE group. STRING protein network predicted the inflammatory cytokines, i.e., interferon gamma (IFN-γ), interleukin-1 beta (IL-1β) and tumor necrosis factor alpha (TNF-α), play roles in pathophysiology in RE patients. Cytokine immunoassay (n = 24, 18 RE vs. 6 controls) exhibited plasma IFN-γ was upregulated in RE patients as compared to the healthy individuals (median IQR; 2.9 2.9, 4.9 vs. 1.32 0.8, 1.5 pg/mL, p = 0.0013), and plasma IL-1β was significantly downregulated in patients (1.0 0.2, 1.9 vs. 4.5 1.9, 11.0 pg/mL, p = 0.01). TNF-α had no difference between groups. The results suggest that haptoglobin may be associated with oxidative brain damage, while IFN-γ and IL-1β may be involved with neuroinflammation.
Alterations in plasma haptoglobin, IFN-γ, and IL-1β were associated with RE patients. Future studies using a combination of these candidate biomarkers may help predict the intractability of epilepsy in pediatric populations.
Over the past decades, several study programs have conducted genetic testing in cancer patients to identify potential genetic targets for the development of precision therapeutic strategies. These ...biomarker-driven trials have demonstrated improved clinical outcomes and progression-free survival rates in various types of cancers, especially for adult malignancies. However, similar progress in pediatric cancers has been slow due to their distinguished mutation profiles compared to adults and the low frequency of recurrent genomic alterations. Recently, increased efforts to develop precision medicine for childhood malignancies have led to the identification of genomic alterations and transcriptomic profiles of pediatric patients which presents promising opportunities to study rare and difficult-to-access neoplasms. This review summarizes the current state of known and potential genetic markers for pediatric solid tumors and provides perspectives on precise therapeutic strategies that warrant further investigations.
Tumor-homing peptides (THPs) are small peptides that can recognize and bind cancer cells specifically. To gain a better understanding of THPs' functional mechanisms, the accurate identification and ...characterization of THPs is required. Although some computational methods for in silico THP identification have been proposed, a major drawback is their lack of model interpretability. In this study, we propose a new, simple and easily interpretable computational approach (called SCMTHP) for identifying and analyzing tumor-homing activities of peptides via the use of a scoring card method (SCM). To improve the predictability and interpretability of our predictor, we generated propensity scores of 20 amino acids as THPs. Finally, informative physicochemical properties were used for providing insights on characteristics giving rise to the bioactivity of THPs via the use of SCMTHP-derived propensity scores. Benchmarking experiments from independent test indicated that SCMTHP could achieve comparable performance to state-of-the-art method with accuracies of 0.827 and 0.798, respectively, when evaluated on two benchmark datasets consisting of Main and Small datasets. Furthermore, SCMTHP was found to outperform several well-known machine learning-based classifiers (e.g., decision tree, k-nearest neighbor, multi-layer perceptron, naive Bayes and partial least squares regression) as indicated by both 10-fold cross-validation and independent tests. Finally, the SCMTHP web server was established and made freely available online. SCMTHP is expected to be a useful tool for rapid and accurate identification of THPs and for providing better understanding on THP biophysical and biochemical properties.
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