Peptide-Based Treatment: A Promising Cancer Therapy

Polymeric microneedle advancements in macromolecule drug delivery: current trends, challenges, and future perspectives

Microneedles (MNs) offer a transformative solution for delivering macromolecules, including proteins, RNA, and peptides. These are critical in treating complex diseases but face significant challenges such as immunogenicity, poor stability, high molecular weight, and delivery efficiency. Unlike conventional methods, MNs efficiently bypass biological barriers like the stratum corneum, enabling precise and minimally invasive transdermal drug delivery. This review explores various MN types such as solid, coated, hollow, hydrogel-forming, and dissolving and their therapeutic applications in cancer immunotherapy, diabetes management, and osteoporosis treatment. For instance, dissolving MNs have been employed for transdermal insulin delivery, enhancing patient compliance and therapeutic outcomes. Similarly, hydrogel MNs have shown promise in sustained drug release for immunotherapy applications. By addressing cost and scalability issues, polymeric MNs demonstrate significant potential for clinical translation, paving the way for innovations in macromolecule delivery, diagnostics, and personalised medicine. This review underscores the pivotal role of MNs in redefining drug delivery systems, offering improved efficacy, patient comfort, and accessibility.

Main methods and tools for peptide development based on protein-protein interactions (PPIs)

Protein-protein interactions (PPIs) regulate essential physiological and pathological processes. Due to their large and shallow binding surfaces, PPIs are often considered challenging drug targets for small molecules. Peptides offer a viable alternative, as they can bind these targets, acting as regulators or mimicking interaction partners. This review focuses on competitive peptides, a class of orthosteric modulators that disrupt PPI formation. We provide a concise yet comprehensive overview of recent advancements in in-silico peptide design, highlighting computational strategies that have improved the efficiency and accuracy of PPI-targeting peptides. Additionally, we examine cutting-edge experimental methods for evaluating PPI-based peptides. By exploring the interplay between computational design and experimental validation, this review presents a structured framework for developing effective peptide therapeutics targeting PPIs in various diseases.

Investigating the effect of rAzurin loaded mesoporous silica nanoparticles enwrapped with chitosan-folic acid on breast tumor regression in BALB/C mice

This study aimed to examine how mesoporous silica nanoparticles-chitosan-folic acid impacted the release of recombinant Azurin within the tumor environment. The goal was to trigger apoptosis and stimulate immune responses against both transformed and normal cells in BALB/c mice. The study found that the use of rAzu-MSNs-CS-FA, a specific formulation containing mesoporous silica nanoparticles-chitosan-folic acid, resulted in pH-responsive behavior and slower release of rAzurin compared to other groups. This formulation inhibited MCF7 cells at higher concentrations, induced apoptosis in cells, and caused DNA degradation. It also increased the uptake efficiency of rAzurin and stimulated the secretion of TNF-α, INF-γ, and IL-4 while inhibiting the secretion of IL-6. Furthermore, it regulated the expression of specific genes (upregulating tlr3 and downregulating tlr2, 4, and 9). In animal studies with BALB/c mice, the rAzu-MSNs-CS-FA formulation led to tumor regression and decreased tumor volume over 21 days. Overall, this formulation showed promising results in inducing cytotoxic effects against cancer cells, promoting apoptosis, and eliciting appropriate immune responses, suggesting its potential as a valuable therapy for breast cancer.

Bacterial Proteins and Peptides as Potential Anticancer Agents: A Novel Search for Protein-based Therapeutics

Tumor diseases remain among the world's primary causes of death despite substantial advances in cancer diagnosis and treatment. The adverse chemotherapy problems and sensitivity towards drugs for some cancer types are among the most promising challenges in modern treatment. Finding new anti-cancer agents and drugs is, therefore, essential. A significant class of biologically active substances and prospective medications against cancer is comprised of bacterial proteins and peptides. Among these bacterial peptides, some of them, such as anti-cancer antibiotics and many toxins like diphtheria are widely being used in the treatment of cancer. In contrast, the remaining bacterial peptides are either in clinical trials or under research in vitro studies. This study includes the most recent information on the characteristics and mechanism of action of the bacterial peptides that have anti-cancer activities, some of which are now being employed in cancer therapy while some are still undergoing research.

Design and investigation of interactions of novel peptide conjugates of purine and pyrimidine derivatives with EGFR and its mutant T790M/L858R: an in silico and laboratory study

Peptide-based therapeutics have been gaining attention due to their ability to actively target tumor cells. Additionally, several varieties of nucleotide derivatives have been developed to reduce cell proliferation and induce apoptosis of tumor cells. In this work, we have developed novel peptide conjugates with newly designed purine analogs and pyrimidine derivatives and explored the binding interactions with the kinase domain of wild-type EGFR and its mutant EGFR [L858R/ T790M] which are known to be over-expressed in tumor cells. The peptides explored included WNWKV (derived from sea cucumber) and LARFFS, which in previous work was predicted to bind to Domain I of EGFR. Computational studies conducted to explore binding interactions include molecular docking studies, molecular dynamics simulations and MMGBSA to investigate the binding abilities and stability of the complexes. The results indicate that conjugation enhanced binding capabilities, particularly for the WNWKV conjugates. MMGBSA analysis revealed nearly twofold higher binding toward the T790M/L858R double mutant receptor. Several conjugates were shown to have strong and stable binding with both wild-type and mutant EGFR. As a proof of concept, we synthesized pyrimidine conjugates with both peptides and determined the KD values using SPR analysis. The results corroborated with the computational analyses. Additionally, cell viability and apoptosis studies with lung cancer cells expressing the wild-type and double mutant proteins revealed that the WNWKV conjugate showed greater potency than the LARFFS conjugate, while LARFFS peptide alone showed poor binding to the kinase domain. Thus, we have designed peptide conjugates that show potential for further laboratory studies for developing therapeutics for targeting the EGFR receptor and its mutant T790M/L858R.

Peptide hemolytic activity analysis using visual data mining of similarity-based complex networks

Peptides are promising drug development frameworks that have been hindered by intrinsic undesired properties including hemolytic activity. We aim to get a better insight into the chemical space of hemolytic peptides using a novel approach based on network science and data mining. Metadata networks (METNs) were useful to characterize and find general patterns associated with hemolytic peptides, whereas Half-Space Proximal Networks (HSPNs), represented the hemolytic peptide space. The best candidate HSPNs were used to extract various subsets of hemolytic peptides (scaffolds) considering network centrality and peptide similarity. These scaffolds have been proved to be useful in developing robust similarity-based model classifiers. Finally, using an alignment-free approach, we reported 47 putative hemolytic motifs, which can be used as toxic signatures when developing novel peptide-based drugs. We provided evidence that the number of hemolytic motifs in a sequence might be related to the likelihood of being hemolytic.

ACP-CapsPred: an explainable computational framework for identification and functional prediction of anticancer peptides based on capsule network

Cancer is a severe illness that significantly threatens human life and health. Anticancer peptides (ACPs) represent a promising therapeutic strategy for combating cancer. In silico methods enable rapid and accurate identification of ACPs without extensive human and material resources. This study proposes a two-stage computational framework called ACP-CapsPred, which can accurately identify ACPs and characterize their functional activities across different cancer types. ACP-CapsPred integrates a protein language model with evolutionary information and physicochemical properties of peptides, constructing a comprehensive profile of peptides. ACP-CapsPred employs a next-generation neural network, specifically capsule networks, to construct predictive models. Experimental results demonstrate that ACP-CapsPred exhibits satisfactory predictive capabilities in both stages, reaching state-of-the-art performance. In the first stage, ACP-CapsPred achieves accuracies of 80.25% and 95.71%, as well as F1-scores of 79.86% and 95.90%, on benchmark datasets Set 1 and Set 2, respectively. In the second stage, tasked with characterizing the functional activities of ACPs across five selected cancer types, ACP-CapsPred attains an average accuracy of 90.75% and an F1-score of 91.38%. Furthermore, ACP-CapsPred demonstrates excellent interpretability, revealing regions and residues associated with anticancer activity. Consequently, ACP-CapsPred presents a promising solution to expedite the development of ACPs and offers a novel perspective for other biological sequence analyses.

Virtual high throughput screening of natural peptides against ErbB1 and ErbB2 to identify potential inhibitors for cancer chemotherapy

Human epidermal growth factor receptors (EGFR), namely ErbB1/HER1, ErbB2/HER2/neu, ErbB3/HER3, and ErbB4/HER4, the trans-membrane family of tyrosine kinase receptors, are overexpressed in many types of cancers. These receptors play an important role in cell proliferation, differentiation, invasion, metastasis and angiogenesis including unregulated activation of cancer cells. Overexpression of ErbB1 and ErbB2 that occurs in several types of cancers is associated with poor prognosis leading to resistance to ErbB1-directed therapies. In this connection, promising strategy to overcome the disadvantages of the existing chemotherapeutic drugs is the use of short peptides as anticancer agents. In the present study, we have performed virtual high throughput screening of natural peptides against ErbB1 and ErbB2 to identify potential dual inhibitors and identified five inhibitors based on their binding affinities, ADMET analysis, MD simulation studies and calculation of free energy of binding. These natural peptides could be further exploited for developing drugs for treating cancer.Communicated by Ramaswamy H. Sarma.

Bispecific fibrous glue synergistically boosts vascular normalization and antitumor immunity for advanced renal carcinoma therapy

Immune checkpoint blockade therapy represented by programmed cell death ligand 1 (PD-L1) inhibitor for advanced renal carcinoma with an objective response rate (ORR) in patients is less than 20%. It is attributed to abundant tumoral vasculature with abnormal structure limiting effector T cell infiltration and drug penetration. We propose a bispecific fibrous glue (BFG) to regulate tumor immune and vascular microenvironments simultaneously. The bispecific precursor glue peptide-1 (pre-GP1) can penetrate tumor tissue deeply and self-assemble into BFG in the presence of neuropilin-1 (NRP-1) and PD-L1. The resultant fibrous glue is capable of normalizing tumoral vasculature as well as restricting immune escape. The pre-GP1 retains a 6-fold higher penetration depth than that of antibody in the multicellular spheroids (MCSs) model. It also shows remarkable tumor growth inhibition (TGI) from 19% to 61% in a murine advanced large tumor model compared to the clinical combination therapy. In addition, in the orthotopic renal tumor preclinical model, the lung metastatic nodules are reduced by 64% compared to the clinically used combination. This pre-GP1 provides a promising strategy to control the progression and metastasis of advanced renal carcinoma.

Tumor-Homing Peptides as Crucial Component of Magnetic-Based Delivery Systems: Recent Developments and Pharmacoeconomical Perspective

According to data from the World Health Organization (WHO), cancer is considered to be one of the leading causes of death worldwide, and new therapeutic approaches, especially improved novel cancer treatment regimens, are in high demand. Considering that many chemotherapeutic drugs tend to have poor pharmacokinetic profiles, including rapid clearance and limited on-site accumulation, a combined approach with tumor-homing peptide (THP)-functionalized magnetic nanoparticles could lead to remarkable improvements. This is confirmed by an increasing number of papers in this field, showing that the on-target peptide functionalization of magnetic nanoparticles improves their penetration properties and ensures tumor-specific binding, which results in an increased clinical response. This review aims to highlight the potential applications of THPs in combination with magnetic carriers across various fields, including a pharmacoeconomic perspective.

Neoantigen Identification and Dendritic Cell-Based Vaccines for Lung Cancer Immunotherapy

Immunotherapies can treat many cancers, including difficult-to-treat cases such as lung cancer. Due to its tolerability, long-lasting therapeutic responses, and efficacy in a wide spectrum of patients, immunotherapy can also help to treat lung cancer, which has few treatment choices. Tumor-specific antigens (TSAs) for cancer vaccinations and T-cell therapies are difficult to discover. Neoantigens (NeoAgs) from genetic mutations, irregular RNA splicing, protein changes, or viral genetic sequences in tumor cells provide a solution. NeoAgs, unlike TSAs, are non-self and can cause an immunological response. Next-generation sequencing (NGS) and bioinformatics can swiftly detect and forecast tumor-specific NeoAgs. Highly immunogenic NeoAgs provide personalized or generalized cancer immunotherapies. Dendritic cells (DCs), which originate and regulate T-cell responses, are widely studied potential immunotherapeutic therapies for lung cancer and other cancers. DC vaccines are stable, reliable, and safe in clinical trials. The purpose of this article is to evaluate the current status, limitations, and prospective clinical applications of DC vaccines, as well as the identification and selection of major histocompatibility complex (MHC) class I and II genes for NeoAgs. Our goal is to explain DC biology and activate DC manipulation to help researchers create extremely potent cancer vaccines for patients.

Increased interaction between connexin43 and microtubules is critical for glioblastoma stem-like cell maintenance and tumorigenicity

Glioblastoma (GBM) is the most common primary tumor of the central nervous system. One major challenge in GBM treatment is the resistance to chemotherapy and radiotherapy observed in subpopulations of cancer cells, including GBM stem-like cells (GSCs). These cells hold the ability to self-renew or differentiate following treatment, participating in tumor recurrence. The gap junction protein connexin43 (Cx43) has complex roles in oncogenesis and we have previously demonstrated an association between Cx43 and GBM chemotherapy resistance. Here, we report, for the first time, increased direct interaction between non-junctional Cx43 with microtubules in the cytoplasm of GSCs. We hypothesize that non-junctional Cx43/microtubule complexing is critical for GSC maintenance and survival and sought to specifically disrupt this interaction while maintaining other Cx43 functions, such as gap junction formation. Using a Cx43 mimetic peptide of the carboxyl terminal tubulin-binding domain of Cx43 (JM2), we successfully ablated Cx43 interaction with microtubules in GSCs. Importantly, administration of JM2 significantly decreased GSC survival in vitro , and limited GSC-derived tumor growth in vivo . Together, these results identify JM2 as a novel peptide drug to ablate GSCs in GBM treatment.

Recent advances in stimuli-responsive tailored nanogels for cancer therapy; from bench to personalized treatment

To improve the quality of health in a personalized manner, better control over pharmacologically relevant cargo formulation, organ-specific targeted delivery, and on-demand release of therapeutic agents is crucial. Significant work has been put into designing and developing revolutionary nanotherapeutics approaches for the effective monitoring and personalized treatment of disease. Nanogel (NG) has attracted significant interest because of its tremendous potential in cancer therapy and its environmental stimuli responsiveness. NG is considered a next-generation delivery technology due to its benefits like as size tunability, high loading, stimuli responsiveness, prolonged drug release via in situ gelling mechanisms, stability, and its potential to provide personalized therapy from the investigation of human genes and the genes in various types of cancers and its association with a selective anticancer drug. Stimuli-responsive NGs can be used as smart nanomedicines to detect and treat cancer and can be tuned as personalized medicine as well. This comprehensive review article's major objectives include the challenges of NGs' clinical translation for cancer treatment as well as its early preclinical successes and prospects.

Fundamental Uses of Peptides as a New Model in Both Treatment and Diagnosis

An amino acid short chain is known as a peptide. Peptide bonds are the connections that hold the amino acids of a peptide together in a particular order. Characteristically, the shorter length of peptides helps to identify them from proteins. Different ways are used to classify peptides, including chain length, source of peptides, or their biological functions. The fact that peptides serve several purposes suggests that there is a foundation for improvement in peptide production and structure to enhance action. In addition, many patents on peptides for therapeutic and diagnostic approaches have been obtained. This review aims to give an overview of peptides used recently in treatment and diagnosis.

Capillary electrophoresis in the analysis of therapeutic peptides-A review

Therapeutic peptides are a growing class of innovative drugs with high efficiency and a low risk of adverse effects. These biomolecules fall within the molecular mass range between that of small molecules and proteins. However, their inherent instability and potential for degradation underscore the importance of reliable and effective analytical methods for pharmaceutical quality control, therapeutic drug monitoring, and compliance testing. Liquid chromatography-mass spectrometry (LC-MS) has long time been the "gold standard" conventional method for peptide analysis, but capillary electrophoresis (CE) is increasingly being recognized as a complementary and, in some cases, superior, highly efficient, green, and cost-effective alternative technique. CE can separate peptides composed of different amino acids owing to differences in their net charge and size, determining their migration behavior in an electric field. This review provides a comprehensive overview of therapeutic peptides that have been used in the clinical environment for the last 25 years. It describes the properties, classification, current trends in development, and clinical use of therapeutic peptides. From the analytical point of view, it discusses the challenges associated with the analysis of therapeutic peptides in pharmaceutical and biological matrices, as well as the evaluation of CE as a whole and the comparison with LC methods. The article also highlights the use of microchip electrophoresis, nonaqueous CE, and nonconventional hydrodynamically closed CE systems and their applications. Overall, the article emphasizes the importance of developing new CE-based analytical methods to ensure the high quality, safety, and efficacy of therapeutic peptides in clinical practice.

Therapeutic applications of carbon nanomaterials in renal cancer

Carbon nanomaterials (CNMs), including carbon nanotubes (CNTs), graphene, and nanodiamonds (NDs), have shown great promise in detecting and treating numerous cancers, including kidney cancer. CNMs can increase the sensitivity of diagnostic techniques for better kidney cancer identification and surveillance. They enable targeted medicine delivery specifically to tumour locations, with little effect on healthy tissue. Because of their unique chemical and physical characteristics, they can avoid the body's defence mechanisms, making it easier to accumulate where tumours exist. Consequently, CNMs provide more effective drug delivery to kidney cancer cells. It also helps in improving the efficacy of treatment. This review explores the potential of several CNMs in improving therapeutic strategies for kidney cancer. We briefly covered the physicochemical properties and therapeutic applications of CNMs. Additionally, we discussed how structural modifications in CNMs enhance their precision in treating renal cancer. A thorough overview of CNM-based gene, peptide, and drug delivery strategies for the treatment of renal cancer is presented in this review. It covers information on other CNM-based therapeutic approaches, such as hyperthermia, photodynamic therapy, and photoacoustic therapy. Also, the interactions of CNMs with the tumour microenvironment (TME) are explored, including modulation of the immune response, regulation of tumour hypoxia, interactions between CNMs and TME cells, effects of TME pH on CNMs, and more. Finally, potential side effects of CNMs, such as toxicity, bio corona formation, enzymatic degradation, and biocompatibility, are also discussed.

Membrane-Active Peptides and Their Potential Biomedical Application

Membrane-active peptides (MAPs) possess unique properties that make them valuable tools for studying membrane structure and function and promising candidates for therapeutic applications. This review paper provides an overview of the fundamental aspects of MAPs, focusing on their membrane interaction mechanisms and potential applications. MAPs exhibit various structural features, including amphipathic structures and specific amino acid residues, enabling selective interaction with multiple membranes. Their mechanisms of action involve disrupting lipid bilayers through different pathways, depending on peptide properties and membrane composition. The therapeutic potential of MAPs is significant. They have demonstrated antimicrobial activity against bacteria and fungi, making them promising alternatives to conventional antibiotics. MAPs can selectively target cancer cells and induce apoptosis, opening new avenues in cancer therapeutics. Additionally, MAPs serve as drug delivery vectors, facilitating the transport of therapeutic cargoes across cell membranes. They represent a fascinating class of biomolecules with significant potential in basic research and clinical applications. Understanding their mechanisms of action and designing peptides with enhanced selectivity and efficacy will further expand their utility in diverse fields. Exploring MAPs holds promise for developing novel therapeutic strategies against infections, cancer, and drug delivery challenges.

DNA Hydrogel-Based Nanocomplexes with Cancer-Targeted Delivery and Light-Triggered Peptide Drug Release for Cancer-Specific Therapeutics

Cancer therapies based on chemotherapeutic drug delive ries have been the most facilitated studies. Recently, peptide drugs have emerged as anticancer drugs due to their less immunogenicity and lower production costs compared with other synthetics. However, still, the side effects of these chemotherapeutics on healthy tissues have been a great concern to deal with, and these side effects are usually caused by off-targeted delivery and unwanted leakage. In addition, peptides are easily degraded by enzyme attacks during delivery. To address these concerns, here, we developed a robust, cancer-specific peptide drug delivery system with negligible cytotoxicity in in vitro. A peptide drug delivery vehicle (Dgel-PD-AuNP-YNGRT) was constructed by stepwise functionalization on a nanoscale DNA hydrogel (Dgel). A cell-penetrating anticancer peptide drug, Buforin IIb, was loaded within the Dgel network via electrostatic attraction followed by AuNP assembly. The AuNPs were employed as photothermal reagents for light-triggered peptide drug release. An additional peptide, including a cancer-targeting YNGRT sequence, was also bound on the Dgel for cancer-cell-targeted delivery. According to the results obtained from the studies employing cancer cells as well as normal cells, Dgel-PD-AuNP-YNGRT nanocomplexes could be delivered specifically to cancer cells, activated by light illumination, and release anticancer peptide drugs to kill cancer cells with no cytotoxicity and negligible hazardous effect on normal cell lines. The obtained cell viability assay suggests that at a high intensity (15 W/cm²), photothermally triggered released peptide drug has shown up to 44% higher kill than only peptide drug treatments in cancer cells. Similarly, the Bradford assay demonstrated that up to 90% of peptide drugs were released with our engineered Dgel-PD-AuNP-YNGRT nanocomplex. The Dgel-PD-AuNP-YNGRT nanocomplex may serve as an ideal anticancer peptide drug delivery platform for safe, cancer-specific targeting and efficient peptide drug delivery in cancer therapy.

Designing multi-epitope vaccine against important colorectal cancer (CRC) associated pathogens based on immunoinformatics approach

BACKGROUND

It seems that several members of intestinal gut microbiota like Streptococcus bovis, Bacteroides fragilis, Helicobacter pylori, Fusobacterium nucleatum, Enterococcus faecalis, Escherichia coli, Peptostreptococcus anaerobius may be considered as the causative agents of Colorectal Cancer (CRC). The present study used bioinformatics and immunoinformatics approaches to design a potential epitope-based multi-epitope vaccine to prevent CRC with optimal population coverage.

METHODS

In this study, ten amino acid sequences of CRC-related pathogens were retrieved from the NCBI database. Three ABCpred, BCPREDS and LBtope online servers were considered for B cells prediction and the IEDB server for T cells (CD4⁺ and CD8⁺) prediction. Then, validation, allergenicity, toxicity and physicochemical analysis of all sequences were performed using web servers. A total of three linkers, AAY, GPGPG, and KK were used to bind CTL, HTL and BCL epitopes, respectively. In addition, the final construct was subjected to disulfide engineering, molecular docking, immune simulation and codon adaptation to design an effective vaccine production strategy.

RESULTS

A total of 19 sequences of different lengths for linear B-cell epitopes, 19 and 18 sequences were considered as epitopes of CD4⁺ T and CD8⁺ cells, respectively. The predicted epitopes were joined by appropriate linkers because they play an important role in producing an extended conformation and protein folding. The final multi-epitope construct and Toll-like receptor 4 (TLR4) were evaluated by molecular docking, which revealed stable and strong binding interactions. Immunity simulation of the vaccine showed significantly high levels of immunoglobulins, helper T cells, cytotoxic T cells and INF-γ.

CONCLUSION

Finally, the results showed that the designed multi-epitope vaccine could serve as an excellent prophylactic candidate against CRC-associated pathogens, but in vitro and animal studies are needed to justify our findings for its use as a possible preventive measure.

Accelerating the Discovery of Anticancer Peptides through Deep Forest Architecture with Deep Graphical Representation

Cancer is one of the leading diseases threatening human life and health worldwide. Peptide-based therapies have attracted much attention in recent years. Therefore, the precise prediction of anticancer peptides (ACPs) is crucial for discovering and designing novel cancer treatments. In this study, we proposed a novel machine learning framework (GRDF) that incorporates deep graphical representation and deep forest architecture for identifying ACPs. Specifically, GRDF extracts graphical features based on the physicochemical properties of peptides and integrates their evolutionary information along with binary profiles for constructing models. Moreover, we employ the deep forest algorithm, which adopts a layer-by-layer cascade architecture similar to deep neural networks, enabling excellent performance on small datasets but without complicated tuning of hyperparameters. The experiment shows GRDF exhibits state-of-the-art performance on two elaborate datasets (Set 1 and Set 2), achieving 77.12% accuracy and 77.54% F1-score on Set 1, as well as 94.10% accuracy and 94.15% F1-score on Set 2, exceeding existing ACP prediction methods. Our models exhibit greater robustness than the baseline algorithms commonly used for other sequence analysis tasks. In addition, GRDF is well-interpretable, enabling researchers to better understand the features of peptide sequences. The promising results demonstrate that GRDF is remarkably effective in identifying ACPs. Therefore, the framework presented in this study could assist researchers in facilitating the discovery of anticancer peptides and contribute to developing novel cancer treatments.

Self-Assembling Peptide-Based Functional Biomaterials

Peptides can self-assemble into various hierarchical nanostructures through noncovalent interactions and form functional materials exhibiting excellent chemical and physical properties, which have broad applications in bio-/nanotechnology. The self-assembly mechanism, self-assembly morphology of peptide supramolecular architecture and their various applications, have been widely explored which have the merit of biocompatibility, easy preparation, and controllable functionality. Herein, we introduce the latest research progress of self-assembling peptide-based nanomaterials and review their applications in biomedicine and optoelectronics, including tissue engineering, anticancer therapy, biomimetic catalysis, energy harvesting. We believe that this review will inspire the rational design and development of novel peptide-based functional bio-inspired materials in the future.

Antimicrobial peptides with anticancer activity: Today status, trends and their computational design

Some antimicrobial peptides have been shown to be able to inhibit the proliferation of cancer cell lines. Various strategies for treating cancers with active peptides have been pursued. According to the reports, anticancer peptides are important therapeutic peptides, which can act through two distinct pathways: they either just create pores in the cell membrane, or they have a vital intracellular target. In this review, publications up to Sep. 2021 had extracted form Scopus and PubMed using "antimicrobial peptide" and "anticancer peptide" as keywords. In second step, "computational design" related publications extracted. Among publications, those have similar scopes were classified and selected based on mechanisms of action and application. In this review, the most recent advances in the field of antimicrobial peptides with anti-cancer activities have been summarized. Freely available webservers such as AntiCP, ACPP, iACP, iACP-GAEnsC, ACPred are discussed here. In conclusion, despite some limitations of ACPs such as production cost and challenges, short half-life and toxicity on normal cells, the beneficial properties of AMPs make some of them good therapeutic agents for cancer therapy. Towards designing novel ACPs, the computational methods have substantial position and have been used progressively, today.

Patient-derived xenografts or organoids in the discovery of traditional and self-assembled drug for tumor immunotherapy

In addition to the rapid development of immune checkpoint inhibitors, there has also been a surge in the development of self-assembly immunotherapy drugs. Based on the immune target, traditional tumor immunotherapy drugs are classified into five categories, namely immune checkpoint inhibitors, direct immune modulators, adoptive cell therapy, oncolytic viruses, and cancer vaccines. Additionally, the emergence of self-assembled drugs with improved precision and environmental sensitivity offers a promising innovation approach to tumor immunotherapy. Despite rapid advances in tumor immunotherapy drug development, all candidate drugs require preclinical evaluation for safety and efficacy, and conventional evaluations are primarily conducted using two-dimensional cell lines and animal models, an approach that may be unsuitable for immunotherapy drugs. The patient-derived xenograft and organoids models, however, maintain the heterogeneity and immunity of the pathological tumor heterogeneity.

Structural, spectroscopic, in silico, in vitro and DNA binding evaluations of tyrosyl-lysyl-threonine

The main objective of the present study is to investigate the molecular structure and DNA binding interaction of the tyrosyl-lysyl-threonine (YKT) tripeptide, which has anticancer, antioxidant and analgesic properties, using various in silico (MD, QM, molecular docking), spectroscopic (UV, FT-IR, FTIR-ATR, Raman, gel electrophoresis) and in vitro (MCF-7 and HeLa cancer cell lines and BEAS-2B cell line) methods. The optimized geometry, vibrational wavenumbers, molecular electrostatic potential (MEP), natural bond orbital (NBO) and HOMO-LUMO (highest occupied molecular orbital- lowest unoccupied molecular orbital) calculations were carried out with Density Functional Theory (DFT) using B3LYP/6-311++G(d,p) basis set to indicate conformational, vibrational and intramolecular charge transfer characteristics. The assignment of all fundamental theoretical vibration wavenumbers was performed using potential energy distribution analysis (PED). DNA is a significant pharmacological target of drugs in several diseases such as cancer. For this reason, molecular docking calculation was used to elucidate the binding and interaction between YKT tripeptide and DNA at the atomic level. Also, the dynamic behaviors of YKT and DNA was examined using MD simulations. Besides, the interaction of YKT with DNA was experimentally examined by UV titration method and agarose gel electrophoresis method. Experimental results showed that YKT was intercalatively and electrostatically bound to CT-DNA (Calf thymus DNA) and cleavage pBR322 DNA in the presence of H₂O₂. The pharmacokinetic profile of YKT was also obtained. Cytotoxic effect of YKT was evaluated on MCF-7, HeLa and BEAS-2B cell lines. Hence, these studies about YKT tripeptide may pave the way for the development of various cancer drugs. Communicated by Ramaswamy H. Sarma.

Multi-Layered PLGA-PEI Nanoparticles Functionalized with TKD Peptide for Targeted Delivery of Pep5 to Breast Tumor Cells and Spheroids

PURPOSE

Peptide-based therapy is a promising strategy for cancer treatment because of its low drug resistance. However, the major challenge is their inability to target cancer cells specifically. So, a targeted nano-delivery system that could deliver therapeutic peptides selectively to cancer cells to stimulate their action is highly desirable. This study aims to deliver the antitumor peptide, Pep5, to breast tumor cells selectively using a targeting peptide functionalised multi-layered PLGA-PEI nanoparticles.

METHODS

In this study, Pep5 entrapped PLGA-PEI (Pep5-PPN) dual layered nanoparticles were developed. These nanoparticles were decorated with TKD (Pep5-TPPN) on their surface for site-specific delivery of Pep5 to breast tumor cells. The particles were then characterized using various instrumental analyses. In vitro cytotoxicity of the particles was evaluated in estrogen receptor positive (ER+ve) and triple negative breast cancer (TNBC) cells. An ex vivo tumor spheroid model was used to analyze the antitumor activity of the particles.

RESULTS

Uniformly round Pep5-TPPN particles were synthesized with an average diameter of 420.8 ± 14.72 nm. The conjugation of PEI over Pep5-PLGA nanoparticles shifted the zeta potential from -11.6 ± 2.16 mV to +20.01 ± 2.97 mV. In vitro cytotoxicity analysis proved that TKD conjugation to nanoparticles enhanced the antitumor activity of Pep5 in tested breast cancer cells. Pep5-TPPN induced cytoskeletal damage and apoptosis in the tested cells, which showed that the mechanism of action of Pep5 is conserved but potentiated. Active targeting of Pep5 suppressed the tumor growth in ex vivo spheroid models.

CONCLUSION

A multi-layered nanoparticle functionalized with dual peptide was fabricated for active tumor targeting, which stimulated Pep5 activity to reduce the tumor growth in vitro and ex vivo.

Anticancer peptides mechanisms, simple and complex

Peptide therapy has started since 1920s with the advent of insulin application, and now it has emerged as a new approach in treatment of diseases including cancer. Using anti-cancer peptides (ACPs) is a promising way of cancer therapy as ACPs are continuing to be approved and arrived at major pharmaceutical markets. Traditional cancer treatments face different problems like intensive adverse effects to patient's body, cell resistance to conventional chemical drugs and in some worse cases the occurrence of cell multidrug resistance (MDR) of cancerous tissues against chemotherapy. On the other hand, there are some benefits conceived for peptides usage in treatment of diseases specifically cancer, as these compounds present favorable characteristics such as smaller size, high activity, low immunogenicity, good biocompatibility in vivo, convenient and rapid way of synthesis, amenable to sequence modification and revision and there is no limitation for the type of cargo they carry. It is possible to achieve an optimum molecular and functional structure of peptides based on previous experience and bank of peptide motif data which may result in novel peptide design. Bioactive peptides are able to form pores in cell membrane and induce necrosis or apoptosis of abnormal cells. Moreover, recent researches have focused on the tumor recognizing peptide motifs with the ability to permeate to cancerous cells with the aim of cancer treatment at earlier stages. In this strategy the most important factors for addressing cancer are choosing peptides with easy accessibility to tumor cell without cytotoxicity effect towards normal cells. The peptides must also meet acceptable pharmacokinetic requirements. In this review, the characteristics of peptides and cancer cells are discussed. The various mechanisms of peptides' action proposed against cancer cells make the next part of discussion. It will be followed by giving information on peptides application, various methods of peptide designing along with introducing various databases. Future aspects of peptides for employing in area of cancer treatment come as conclusion at the end.

Dendrimer-based delivery of macromolecules for the treatment of brain tumor

Brain tumor represents the most lethal form of cancer with the highest mortality and morbidity rates irrespective of age and sex. Advancements in macromolecule-based therapy (such as nucleic acids and peptides) have shown promising roles in the treatment of brain tumor where the phenomenon of severe toxicities due to the conventional chemotherapeutic agents can be circumvented. Despite its preclinical progress, successful targeting of these macromolecules across the blood-brain barrier without altering their physical and chemical characteristics is of great challenge. With the advent of nanotechnology, nowadays targeted delivery of therapeutics is being explored extensively and these macromolecules, including peptides and nucleic acids, have shown initial success in the treatment, where dendrimer has shown its potential for optimal delivery. Dendrimers are being favored as a mode of drug delivery due to their nano-spherical size and structure, high solubilization potential, multivalent surface, and high loading capacity, where biomolecule resembling characteristics of dendritic 3D structures has shown effective delivery of various therapeutic agents to the brain. Armed with targeting ligands to these dendrimers further expedite the transportation of these multifunctional shuttles specifically to the glioblastoma cells. Thus, a focus has been made in this review on therapeutic applications of dendrimer platforms in brain tumor treatment. The future development of dendrimers as a potential platform for nucleic acid and peptide delivery and its promising clinical application could provide effective and target-specific treatment against brain tumors.

Towards in vivo photomediated delivery of anticancer peptides: Insights from pharmacokinetic and -dynamic data

An in vivo study of a photoswitchable cytotoxic peptide LMB040 has been undertaken on a chemically induced hepatocellular carcinoma model in immunocompetent rats. We analysed the pharmacokinetic profile of the less toxic photoform ("ring-closed" dithienylethene) of the compound in tumors, plasma, and healthy liver. Accordingly, the peptide can reach a tumor concentration sufficiently high to exert a cytotoxic effect upon photoconversion into the more active ("ring-open") photoform. Tissue morphology, histology, redox state of the liver, and hepatic biochemical parameters in blood serum were analysed upon treatment with (i) the less active photoform, (ii) the in vivo light-activated alternative photoform, and (iii) compared with a reference chemotherapeutic 5-fluorouracil. We found that application of the less toxic form followed by a delayed in vivo photoconversion into the more toxic ring-open form of LMB040 led to a higher overall survival of the animals, and signs of enhanced immune response were observed compared to the untreated animals.

Recent progress of dendritic cell-derived exosomes (Dex) as an anti-cancer nanovaccine

Although cancer vaccines such as dendritic cell (DC) vaccines and peptide vaccines have become appealing and attractive anticancer immunotherapy options in recent decades, some obstacles have hindered their successful application in the clinical setting. The difficulties associated with the high cost of DC preparation, storage of DC vaccines, tumor-mediated immunosuppressive environment, identification of specific tumor antigens, and high degradation of antigen peptides in vivo limit the clinical application and affect the outcomes of these cancer vaccines. Recently, nanocarriers have been considered as a new approach for vaccine delivery. As biogenic nanocarriers, exosomes are small membrane vesicles secreted by cells that carry various proteins, RNAs, and lipids. More importantly, DC-derived exosomes (Dex) express tumor antigens, MHC molecules, and co-stimulatory molecules on their surface, which trigger the release of antigen-specific CD4⁺ and CD8⁺ T cells. With their membrane structure, Dex can avoid high degradation while ensuring favorable biocompatibility and biosafety in vivo. In addition, Dex can be stored in vitro for a longer period, which facilitates a significant reduction in production costs. Furthermore, they have shown better antitumor efficacy in preclinical studies compared with DC vaccines owing to their higher immunogenicity and stronger resistance to immunosuppressive effects. However, the clinical efficacy of Dex vaccines remains limited. In this review, we aimed to evaluate the efficacy of Dex as an anticancer nanovaccine.

Experimental Study of Potential CD8+ Trivalent Synthetic Peptides for Liver Cancer Vaccine Development Using Sprague Dawley Rat Models

Background. Liver cancer (LC) is the most devastating disease affecting a large set of populations in the world. The mortality due to LC is escalating, indicating the lack of effective therapeutic options. Immunotherapeutic agents may play an important role against cancer cells. As immune cells, especially T lymphocytes, which are part of cancer immunology, the design of vaccine candidates for cytotoxic T lymphocytes may be an effective strategy for curing liver cancer. Results. In our study, based on an immunoinformatics approach, we predicted potential T cell epitopes of MHC class I molecules using integrated steps of data retrieval, screening of antigenic proteins, functional analysis, peptide synthesis, and experimental in vivo investigations. We predicted the binding affinity of epitopes LLECADDRADLAKY, VSEHRIQDKDGLFY, and EYILSLEELVNGMY of LC membrane-bounded extracellular proteins including butyrophilin-like protein-2 (BTNL2), glypican-3 (GPC3), and serum albumin (ALB), respectively, with MHC class I molecules (allele: HLA-A $\ast$ 01:01). These T cell epitopes rely on the level of their binding energy and antigenic properties. We designed and constructed a trivalent immunogenic model by conjugating these epitopes with linkers to activate cytotoxic T cells. For validation, the nonspecific hematological assays showed a significant rise in the count of white blood cells ( $5\times {10}^9/\text{l}$ ), lymphocytes ( $13\times {10}^9/\text{l}$ ), and granulocytes ( $5\times {10}^9/\text{l}$ ) compared to the control after administration of trivalent peptides. Specific immunoassays including granzyme B and IgG ELISA exhibited the significant concentration of these effector molecules in blood serum, indicating the activity of cytotoxic T cells. Granzyme concentration increased to 1050 pg/ml at the second booster dose compared to the control (95 pg/ml), while the concentration of IgG raised to 6 g/l compared to the control (2 g/l). Conclusion. We concluded that a potential therapeutic trivalent vaccine can activate and modulate the immune system to cure liver cancer on the basis of significant outcomes of specific and nonspecific assays.

What Zebrafish and Nanotechnology Can Offer for Cancer Treatments in the Age of Personalized Medicine

Cancer causes millions of deaths each year and thus urgently requires the development of new therapeutic strategies. Nanotechnology-based anticancer therapies are a promising approach, with several formulations already approved and in clinical use. The evaluation of these therapies requires efficient in vivo models to study their behavior and interaction with cancer cells, and to optimize their properties to ensure maximum efficacy and safety. In this way, zebrafish is an important candidate due to its high homology with the human genoma, its large offspring, and the ease in developing specific cancer models. The role of zebrafish as a model for anticancer therapy studies has been highly evidenced, allowing researchers not only to perform drug screenings but also to evaluate novel therapies such as immunotherapies and nanotherapies. Beyond that, zebrafish can be used as an “avatar” model for performing patient-derived xenografts for personalized medicine. These characteristics place zebrafish in an attractive position as a role model for evaluating novel therapies for cancer treatment, such as nanomedicine.

Anti-cancer peptide-based therapeutic strategies in solid tumors

BACKGROUND

Nowadays, conventional medical treatments such as surgery, radiotherapy, and chemotherapy cannot cure all types of cancer. A promising approach to treat solid tumors is the use of tumor-targeting peptides to deliver drugs or active agents selectively.

RESULT

Introducing beneficial therapeutic approaches, such as therapeutic peptides and their varied methods of action against tumor cells, can aid researchers in the discovery of novel peptides for cancer treatment. The biomedical applications of therapeutic peptides are highly interesting. These peptides, owing to their high selectivity, specificity, small dimensions, high biocompatibility, and easy modification, provide good opportunities for targeted drug delivery. In recent years, peptides have shown considerable promise as therapeutics or targeting ligands in cancer research and nanotechnology.

CONCLUSION

 This study reviews a variety of therapeutic peptides and targeting ligands in cancer therapy. Initially, three types of tumor-homing and cell-penetrating peptides (CPPs) are described, and then their applications in breast, glioma, colorectal, and melanoma cancer research are discussed.

Designing a Novel Functional Peptide With Dual Antimicrobial and Anti-inflammatory Activities via in Silico Methods

As spider venom is composed of various bioactive substances, it can be utilized as a platform for discovering future therapeutics. Host defense peptides are great candidates for developing novel antimicrobial agents due to their multifunctional properties. In this study, novel functional peptides were rationally designed to have dual antibacterial and anti-inflammatory activities with high cytocompatibility. Based on a template sequence from the transcriptome of spider Agelena koreana, a series of via in silico analysis were conducted, incorporating web-based machine learning tools along with the alteration of amino acid residues. Two peptides, Ak-N’ and Ak-N’m, were designed and were subjected to functional validation. The peptides inhibited gram-negative and gram-positive bacteria by disrupting the outer and bacterial cytoplasmic membrane. Moreover, the peptides down-regulated the expression of pro-inflammatory mediators, tumor necrosis factor-α, interleukin (IL)-1β, and IL6. Along with low cytotoxicity, Ak-N’m was shown to interact with macrophage surface receptors, inhibiting both Myeloid differentiation primary response 88-dependent and TIR-domain-containing adapter-inducing interferon-β-dependent pathways of Toll-like receptor 4 signaling on lipopolysaccharide-stimulated THP-1-derived macrophages. Here, we rationally designed functional peptides based on the suggested in silico strategy, demonstrating new insights for utilizing biological resources as well as developing therapeutic agents with enhanced properties.

HSPB8 is a Potential Prognostic Biomarker that Correlates With Immune Cell Infiltration in Bladder Cancer

Background: Heat shock protein B8 (HSPB8) is expressed in various cancers. However, the functional and clinicopathological significance of HSPB8 expression in bladder cancer (BC) remains unclear. The present study sought to elucidate the clinicopathological features and prognostic value of HSPB8 in BC.

Methods: A BC RNA-seq data set was obtained from The Cancer Genome Atlas Urothelial Bladder Carcinoma (TCGA-BLCA) database, and the external validation dataset GSE130598 was downloaded from the GEO database. Samples in the TCGA-BLCA were categorized into two groups based on HSPB8 expression. Differentially expressed genes (DEGs) between the two groups were defined as HSPB8 co-expressed genes. Gene set enrichment analysis (GSEA), protein-protein interaction networks, and mRNA-microRNA (miRNA) interaction networks were generated to predict the function and interactions of genes that are co-expressed with HSPB8. Finally, we examined immune cell infiltration and constructed a survival prediction model for BC patients.

Results: The expression level of HSBP8 has a significant difference between cancer samples and normal samples, and its diagnosis effect was validated by the ROC curve. 446 differential expressed genes between HSBP8 high-expression and HSBP8 low expression groups were identified. Gene enrichment analysis and GSEA analysis show that these differential gene functions are closely related to the occurrence and development of BC and the metabolic pathways of BC. The cancer-related pathways included Cytokine-cytokine receptor Interaction, Focal adhesion, and Proteoglycans in cancer. PPI and protein-coding gene-miRNA network visualized the landscape for these tightly bounded gene interactions. Immune cell infiltration shows that B cells, CD4+T cells, and CD8+T cells have strongly different infiltration levels between the HSBP8 high exp group and low exp group. The survival prediction model shows that HSBP8 has strong prognosis power in the BLCA cohort.

Conclusion: Identifying DEGs may enhance understanding of BC development’s causes and molecular mechanisms. HSPB8 may play an essential role in BC progression and prognosis and serve as a potential biomarker for BC treatment.

PLP2-derived peptide Rb4 triggers PARP-1-mediated necrotic death in murine melanoma cells

Malignant melanoma is the main cause of death in patients with skin cancer. Overexpression of Proteolipid protein 2 (PLP2) increased tumor metastasis and the knockdown of PLP2 inhibited the growth and metastasis of melanoma cells. In the present work, we studied the antitumor activity of peptide Rb4 derived from protein PLP2. In vitro, Rb4 induced F-actin polymerization, prevented F-actin depolymerization and increased the ER-derived cytosolic calcium. Such effects were associated with necrosis of murine melanoma B16F10-Nex2 cells and with inhibition of the viability of human cancer cell lines. Loss of plasma membrane integrity, dilation of mitochondria, cytoplasm vacuolation and absence of chromatin condensation characterized tumor cell necrosis. Cleavage of PARP-1 and inhibition of RIP1 expression were also observed. In vivo, peptide Rb4 reduced the lung metastasis of tumor cells and delayed the subcutaneous melanoma growth in a syngeneic model. Rb4 induced the expression of two DAMPs molecules, HMGB1 and calreticulin, in B16F10-Nex2. Our results suggest that peptide Rb4 acts directly on tumor cells inducing the expression of DAMPs, which trigger the immunoprotective effect in vivo against melanoma cells. We suggest that peptide Rb4 is a promising compound to be developed as an anticancer drug.

Rough Set Based Classification and Feature Selection Using Improved Harmony Search for Peptide Analysis and Prediction of Anti-HIV-1 Activities

AIDS, which is caused by the most widespread HIV-1 virus, attacks the immune system of the human body, and despite the incredible endeavors for finding proficient medication strategies, the continuing spread of AIDS and claiming subsequent infections has not yet been decreased. Consequently, the discovery of innovative medicinal methodologies is highly in demand. Some available therapies, based on peptides, proclaim the treatment for several deadly diseases such as AIDS and cancer. Since many experimental types of research are restricted by the analysis period and expenses, computational methods overcome the issues effectually. In computational technique, the peptide residues with anti-HIV-1 activity are predicted by classification method, and the learning process of the classification is improved with significant features. Rough set-based algorithms are capable of dealing with the gaps and imperfections present in real-time data. In this work, feature selection using Rough Set Improved Harmony Search Quick Reduct and Rough Set Improved Harmony Search Relative Reduct with Rough Set Classification framework is implemented to classify Anti-HIV-1 peptides. The primary objective of the proposed methodology is to predict the peptides with an anti-HIV-1 activity using effective feature selection and classification algorithms incorporated in the proposed framework. The results of the proposed algorithms are comparatively studied with existing rough set feature selection algorithms and benchmark classifiers, and the reliability of the algorithms implemented in the proposed framework is measured by validity measures, such as Precision, Recall, F-measure, Kulczynski Index, and Fowlkes–Mallows Index. The final results show that the proposed framework analyzed and classified the peptides with a high predictive accuracy of 96%. In this study, we have investigated the ability of a rough set-based framework with sequence-based numeric features to classify anti-HIV-1 peptides, and the experimentation results show that the proposed framework discloses the most satisfactory solutions, where it rapidly congregates in the problem space and finds the best reduct, which improves the prediction accuracy of the given dataset.

In Silico Studies of Tumor Targeted Peptide-Conjugated Natural Products for Targeting Over-Expressed Receptors in Breast Cancer Cells Using Molecular Docking, Molecular Dynamics and MMGBSA Calculations

In this work, in silico studies were carried out for the design of diterpene and polyphenol-peptide conjugates to potentially target over-expressed breast tumor cell receptors. Four point mutations were induced into the known tumor-targeting peptide sequence YHWYGYTPQN at positions 1, 2, 8 and 10, resulting in four mutated peptides. Each peptide was separately conjugated with either chlorogenate, carnosate, gallate, or rosmarinate given their known anti-tumor activities, creating dual targeting compounds. Molecular docking studies were conducted with the epidermal growth factor receptor (EGFR), to which the original peptide sequence is known to bind, as well as the estrogen receptor (ERα) and peroxisome proliferator-activated receptor (PPARα) using both Autodock Vina and FireDock. Based on docking results, peptide conjugates and peptides were selected and subjected to molecular dynamics simulations. MMGBSA calculations were used to further probe the binding energies. ADME studies revealed that the compounds were not CYP substrates, though most were Pgp substrates. Additionally, most of the peptides and conjugates showed MDCK permeability. Our results indicated that several of the peptide conjugates enhanced binding interactions with the receptors and resulted in stable receptor-ligand complexes; Furthermore, they may successfully target ERα and PPARα in addition to EGFR and may be further explored for synthesis and biological studies for therapeutic applications.

Selective targeting of the novel CK-10 nanoparticles to the MDA-MB-231 breast cancer cells

The main objective of this project was to formulate novel decorated amphiphilic PLGA nanoparticles aiming for the selective delivery of the novel peptide (CK-10) to the cancerous/tumor tissue. Novel modified microfluidic techniques were used to formulate the nanoparticles. This technique was modified by using of Nano Assemblr associated with salting out of the organic solvent using K₂HPO₄. This modification is associated with higher peptide loading efficiencies, smaller size and higher uniformity. Size, zeta potential & qualitative determination of the adsorbed targeting ligands were measured by dynamic light scattering and laser anemometry techniques using the zeta sizer. Quantitative estimation of the adsorbed targeting ligands was done by colorimetry and spectrophotometric techniques. Qualitative and quantitative uptakes of the various PLGA nanoparticles were examined by the fluorescence microscope and the flow cytometer while the cytotoxic effect of the nanoparticles was measured by the colorimetric MTT assay. PLGA/poloxamer.FA, PLGA/poloxamer.HA, and PLGA/poloxamer.Tf have breast cancer MDA. MB321 cellular uptakes 83.8, 75.43 & 69.37 % which are higher than those of the PLGA/B cyclodextrin.FA, PLGA/B cyclodextrin.HA and PLGA/B cyclodextrin.Tf 80.87, 74.47 & 64.67 %. Therefore, PLGA/poloxamer.FA and PLGA/poloxamer.HA show higher cytotoxicity than PLGA/ poloxamer.Tf with lower breast cancer MDA-MB-231 cell viabilities 30.74, 39.15 & 49.23 %, respectively. The design of novel decorated amphiphilic CK-10 loaded PLGA nanoparticles designed by the novel modified microfluidic technique succeeds in forming innovative anticancer formulations candidates for therapeutic use in aggressive breast cancers.

Evaluation of Copper-64-Labeled αvβ6-Targeting Peptides: Addition of an Albumin Binding Moiety to Improve Pharmacokinetics

The incorporation of non-covalent albumin binding moieties (ABMs) into radiotracers results in increased circulation time, leading to a higher uptake in the target tissues such as the tumor, and, in some cases, reduced kidney retention. We previously developed [¹⁸F]AlF NOTA-K(ABM)-α_vβ₆-BP, where α_vβ₆-BP is a peptide with high affinity for the cell surface receptor integrin α_vβ₆ that is overexpressed in several cancers, and the ABM is an iodophenyl-based moiety. [¹⁸F]AlF NOTA-K(ABM)-α_vβ₆-BP demonstrated prolonged blood circulation compared to the non-ABM parent peptide, resulting in high, α_vβ₆-targeted uptake with continuously improving detection of α_vβ₆(+) tumors using PET/CT. To further extend the imaging window beyond that of fluorine-18 (t_1/2 = 110 min) and to investigate the pharmacokinetics at later time points, we radiolabeled the α_vβ₆-BP with copper-64 (t_1/2 = 12.7 h). Two peptides were synthesized without (1) and with (2) the ABM and radiolabeled with copper-64 to yield [⁶⁴Cu]1 and [⁶⁴Cu]2, respectively. The affinity of [^natCu]1 and [^natCu]2 for the integrin α_vβ₆ was assessed by enzyme-linked immunosorbent assay. [⁶⁴Cu]1 and [⁶⁴Cu]2 were evaluated in vitro (cell binding and internalization) using DX3puroβ6 (α_vβ₆(+)), DX3puro (α_vβ₆(-)), and pancreatic BxPC-3 (α_vβ₆(+)) cells, in an albumin binding assay, and for stability in both mouse and human serum. In vivo (PET/CT imaging) and biodistribution studies were done in mouse models bearing either the paired DX3puroβ6/DX3puro or BxPC-3 xenograft tumors. [⁶⁴Cu]1 and [⁶⁴Cu]2 were synthesized in ≥97% radiochemical purity. In vitro, [^natCu]1 and [^natCu]2 maintained low nanomolar affinity for integrin α_vβ₆ (IC₅₀ = 28 ± 3 and 19 ± 5 nM, respectively); [⁶⁴Cu]1 and [⁶⁴Cu]2 showed comparable binding to α_vβ₆(+) cells (DX3puroβ6: ≥70%, ≥42% internalized; BxPC-3: ≥19%, ≥12% internalized) and ≤3% to the α_vβ₆(-) DX3puro cells. Both radiotracers were ≥98% stable in human serum at 24 h, and [⁶⁴Cu]2 showed a 6-fold higher binding to human serum protein than [⁶⁴Cu]1. In vivo, selective uptake in the α_vβ₆(+) tumors was observed with tumor visualization up to 72 h for [⁶⁴Cu]2. A 3-5-fold higher α_vβ₆(+) tumor uptake of [⁶⁴Cu]2 vs [⁶⁴Cu]1 was observed throughout, at least 2.7-fold improved BxPC-3-to-kidney and BxPC-3-to-blood ratios, and 2-fold improved BxPC-3-to-stomach ratios were noted for [⁶⁴Cu]2 at 48 h. Incorporation of an iodophenyl-based ABM into the α_vβ₆-BP ([⁶⁴Cu]2) prolonged circulation time and resulted in improved pharmacokinetics, including increased uptake in α_vβ₆(+) tumors that enabled visualization of α_vβ₆(+) tumors up to 72 h by PET/CT imaging.

Advancement and Strategies for the Development of Peptide-Drug Conjugates: Pharmacokinetic Modulation, Role and Clinical Evidence Against Cancer Management

Currently, many new treatment strategies are being used for the management of cancer. Among them, chemotherapy based on peptides has been of great interest due to the unique features of peptides. This review discusses the role of peptide and peptides analogues in the treatment of cancer, with special emphasis on their pharmacokinetic modulation and research progress. Low molecular weight, targeted drug delivery, enhanced permeability, etc., of the peptide-linked drug conjugates, lead to an increase in the effectiveness of cancer therapy. Various peptides have recently been developed as drugs and vaccines with an altered pharmacokinetic parameter which has subsequently been assessed in different phases of the clinical study. Peptides have made a great impact in the area of cancer therapy and diagnosis. Targeted chemotherapy and drug delivery techniques using peptides are emerging as excellent tools in minimizing problems with conventional chemotherapy. It can be concluded that new advances in using peptides to treat different types of cancer have been shown by different clinical studies indicating that peptides could be used as an ideal therapeutic method in treating cancer due to the novel advantages of peptides. The development of identifying and synthesizing novel peptides could provide a promising choice to patients with cancer.

Synthetic and immunological studies on the OCT4 immunodominant motif antigen-based anti-cancer vaccine

Objective: Cancer stem cell is one of the important causes of tumorigenesis as well as a drug target in the treatment of malignant tumor. However, at present, there is no immune vaccine targeting these cells. Octamer-binding transcription factor 4 (OCT4), a marker of embryonic stem cells and germ cells, often highly expresses in the early stages of tumorigenesis and is therefore a good candidate for cancer vaccine development.

Methods: To identify the optimal carrier and adjuvant combination, we chemically synthesized and linked three different OCT4 epitope antigens to a carrier protein, keyhole limpet hemocyanin (KLH), combined with Toll-like receptor 9 agonist (TLR9).

Results: Immunization with OCT4-3 + TLR9 produced the strongest immune response in mice. In prevention assays, significant tumor growth inhibition was achieved in BABL/c mice treated with OCT4-3 + TLR9 (P < 0.01). Importantly, the results showed that cytotoxic T lymphocyte activity and the inhibition of tumor growth were enhanced in mice immunized with OCT4-3 combined with TLR9. Meanwhile, multiple cytokines [such as interferon (IFN)-γ (P < 0.05), interleukin (IL)-12 (P < 0.05), IL-2 (P < 0.01), and IL-6 (P < 0.05)] promoting cellular immune responses were shown to be greatly enhanced in mice immunized with OCT4-3 + TLR9. Moreover, we considered safety considerations in terms of the composition of the vaccines to help facilitate the development of effective next-generation vaccines.

Conclusions: Collectively, these experiments demonstrated that combination therapy with TLR9 agonist induced a tumor-specific adaptive immune response, leading to the suppression of primary tumor growth in testis embryonic carcinoma.

Purified recombinant human Chromogranin A N46 peptide with remarkable anticancer effect on human colon cancer cells

Human Chromogranin A N46 (CGA-N46) is a weak cationic α-helical peptide with wide-spectrum antibacterial, fungal, and anticancer activities. In this study, the recombinant human CGA-N46 peptide was expressed successfully in Escherichia coli. The gene of CGA-N46 was cloned into the expression vector pET-15b without a fusion tag at the N terminus and the peptide was expressed using Isopropyl-β-d-thiogalactoside (IPTG) as an inducer. Using 8 M guanidinium HCl, inclusion bodies containing the peptide were purified and solubilized. The rhCGA-N46 peptide was purified using Q-FF anion exchange column. The cytotoxicity of the purified rhCGA-N46 peptide was investigated on WI-38 human lung normal cell line. The anticancer activity was studied on human colon cancer cell line; HCT-116 cell line. Besides, the possible involvement of rhCGA-N46 peptide in regulating apoptotic signal pathways was analyzed by detecting the expression levels of BCL2, BID, and CAS-8 in the treated cells. The results concluded that the active peptide recovery was up to 41.98%. The purified rhCGA-N46 was safe on normal cells with IC₅₀ = 227.74 µg/ml (40.67 µM) and had an obvious anticancer effect on colon cancer cells with IC₅₀ = 1.997 µg/ml (356.6 nM). The expression level of BCL2 was down-regulated and BID and CAS-8 were up-regulated significantly in treated HCT-116 cells compared to untreated. In conclusion, the rhCGA-N46 peptide was produced successfully in the native form with promising anti-colon cancer activity.

xDeep-AcPEP: Deep Learning Method for Anticancer Peptide Activity Prediction Based on Convolutional Neural Network and Multitask Learning

Cancer is one of the leading causes of death worldwide. Conventional cancer treatment relies on radiotherapy and chemotherapy, but both methods bring severe side effects to patients, as these therapies not only attack cancer cells but also damage normal cells. Anticancer peptides (ACPs) are a promising alternative as therapeutic agents that are efficient and selective against tumor cells. Here, we propose a deep learning method based on convolutional neural networks to predict biological activity (EC50, LC50, IC50, and LD50) against six tumor cells, including breast, colon, cervix, lung, skin, and prostate. We show that models derived with multitask learning achieve better performance than conventional single-task models. In repeated 5-fold cross validation using the CancerPPD data set, the best models with the applicability domain defined obtain an average mean squared error of 0.1758, Pearson's correlation coefficient of 0.8086, and Kendall's correlation coefficient of 0.6156. As a step toward model interpretability, we infer the contribution of each residue in the sequence to the predicted activity by means of feature importance weights derived from the convolutional layers of the model. The present method, referred to as xDeep-AcPEP, will help to identify effective ACPs in rational peptide design for therapeutic purposes. The data, script files for reproducing the experiments, and the final prediction models can be downloaded from http://github.com/chen709847237/xDeep-AcPEP. The web server to directly access this prediction method is at https://app.cbbio.online/acpep/home.

Copper-binding anticancer peptides from the piscidin family: an expanded mechanism that encompasses physical and chemical bilayer disruption

In the search for novel broad-spectrum therapeutics to fight chronic infections, inflammation, and cancer, host defense peptides (HDPs) have garnered increasing interest. Characterizing their biologically-active conformations and minimum motifs for function represents a requisite step to developing them into efficacious and safe therapeutics. Here, we demonstrate that metallating HDPs with Cu2+ is an effective chemical strategy to improve their cytotoxicity on cancer cells. Mechanistically, we find that prepared as Cu2+-complexes, the peptides not only physically but also chemically damage lipid membranes. Our testing ground features piscidins 1 and 3 (P1/3), two amphipathic, histidine-rich, membrane-interacting, and cell-penetrating HDPs that are α-helical bound to membranes. To investigate their membrane location, permeabilization effects, and lipid-oxidation capability, we employ neutron reflectometry, impedance spectroscopy, neutron diffraction, and UV spectroscopy. While P1-apo is more potent than P3-apo, metallation boosts their cytotoxicities by up to two- and seven-fold, respectively. Remarkably, P3-Cu2+ is particularly effective at inserting in bilayers, causing water crevices in the hydrocarbon region and placing Cu2+ near the double bonds of the acyl chains, as needed to oxidize them. This study points at a new paradigm where complexing HDPs with Cu2+ to expand their mechanistic reach could be explored to design more potent peptide-based anticancer therapeutics.