A novel efficient drug repurposing framework through drug-disease association data integration using convolutional neural networks.

Drug repurposing is an exciting field of research toward recognizing a new FDA-approved drug target for the treatment of a specific disease. It has received extensive attention regarding the tedious, time-consuming, and highly expensive procedure with a high risk of failure of new drug discovery. Data-driven approaches are an important class of methods that have been introduced for identifying a candidate drug against a target disease. In the present study, a model is proposed illustrating the integration of drug-disease association data for drug repurposing using a deep neural network. The model, so-called IDDI-DNN, primarily constructs similarity matrices for drug-related properties (three matrices), disease-related properties (two matrices), and drug-disease associations (one matrix). Then, these matrices are integrated into a unique matrix through a two-step procedure benefiting from the similarity network fusion method. The model uses a constructed matrix for the prediction of novel and unknown drug-disease associations through a convolutional neural network. The proposed model was evaluated comparatively using two different datasets including the gold standard dataset and DNdataset. Comparing the results of evaluations indicates that IDDI-DNN outperforms other state-of-the-art methods concerning prediction accuracy.

Long non-coding RNAs as potential biomarkers or therapeutic targets in gastric cancer.

Aim: This study aimed to find lncRNAs and mRNAs that were expressed differently by combining microarray datasets from different studies. This was done to find important target genes in gastric cancer for anti-cancer therapy. Background: Gastric cancer (GC) is the fourth most frequent and second-most deadly malignancy worldwide. Thus, genetic diagnosis and treatment should focus on genetic and epigenetic variables. Based on several studies, disordered expression of non-coding RNAs (ncRNAs), such as lncRNAs, regulate gastric cancer invasion and metastasis. Besides, lncRNAs cooperatively regulate gene expression and GC progression. Methods: We obtained differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) from three GC tissue microarray datasets by meta-analysis and screened genes using the "Limma" package. Then, using the RNAInter database, we allocated DEmRNAs to each DElncRNA. ClusterProfiler and GOplot programs were used to analyze function enrichment pathways and gene ontologies for final DEmRNAs. Results: A total of 9 differentially expressed lncRNAs (DElncRNAs) (5 up-regulated and 4 down-regulated), and 856 DEmRNAs (451 up-regulated and 405 down-regulated) between tumor and adjacent normal samples were found. Finally, 117 differentially expressed mRNAs were predicted as interactors of six DElncRNAs (H19, WT1-AS, EMX2OS, HOTAIR, ZEB1-AS1, and LINC00261). Conclusion: In order to promote cancer therapeutics and give knowledge on the process of carcinogenesis, our study projected a network of drug-gene interactions for discovered genes and presented relevant prospective biomarkers for the prognosis of patients with stomach cancer.

Tracing drugs from discovery to disposal.

The life cycle of a drug begins with discovery and ends with its disposal. Drug discovery companies, drug manufacturers, regulatory agencies, suppliers, pharmacies, patients, healthcare providers, and many more are involved in this process. Transparency, traceability, automation, and data security are some of the most crucial factors affecting how effectively and safely the transactions are conducted across all parties involved in the cycle. By contrast, scalability, energy consumption, regulation, standards, and complexity hamper the adoption of new technology that is expected to fulfil these requirements. Here, we highlight how blockchain technology can track, accelerate, and boost the efficiency of incredibly complicated operations, such as pharmaceutical development.

Characterization of a novel androgen receptor gene variant identified in an Iranian family with complete androgen insensitivity syndrome (CAIS): a molecular dynamics simulation study.

Androgen insensitivity syndrome (AIS) is a common form of 46, XY disorder in sex development disease (DSD). It is due to the androgen receptor (AR) gene mutations and includes clinical subgroups of complete AIS (CAIS) and partial AIS (PAIS), along with a vast area of clinical heterogeneity of completely normal female external genitalia to male infertility. In this study, the Whole Exome Sequencing (WES) was utilized to detect the cause of DSD in a consanguineous Iranian family with two female patients with normal external genitalia and 46, XY karyotype. Sanger sequencing was applied to validate the candidate variant. Next, we predicted the structural alteration induced by the variant on AR protein using bioinformatics analysis such as molecular dynamic (MD) and molecular docking simulations. WES results identified a novel hemizygous p.L763V variant in the AR gene in the proband that was compatible with the X-linked recessive pattern of inheritance. Bioinformatics studies confirmed the loss of AR function. Based on the American College of Medical Genetics and Genomics (ACMG) guidelines, it was categorized as pathogenic. This study broadens the AR mutation spectrum and introduces the novel p.L763V missense pathogenic variant leading to AR failure to bind to its ligand, and the resulting CAIS clinical subgroup. This study presents a prosperous application of WES and bioinformatics analysis to recognize the underlying cause of DSD in Iran, necessary for its clinical/psychological management.Communicated by Ramaswamy H. Sarma.

In vitro and Pharmacoinformatics-based phytochemical screening for anticancer impacts of pistachio hull essential oil on AGS, PLC/PRF/5, and CACO2 cell lines.

BACKGROUND: The essential oil of pistacia vera (cv. Ohadi) hull (PHEO) was checked using gas chromatography mass spectrometry (GC/MS) analysis. It was studied the genes of the wnt pathway with a certain concentration of PHEO on Human gastric cancer (AGS), human hepatocellular carcinoma (PLC/PRF/5), and human colon cancer (CACO2) cell lines. METHODS AND RESULTS: After evaluating the survival rate of cancer cells by MTT test and determining IC50, pistachio hull essential oil (PHEO) was used for 24-hours to treat the cells. After RNA extraction, the expression of wnt pathway genes was evaluated by Real-Time PCR. Considering the crucial role of ß-catenin accumulation and its effect on the progression of gastrointestinal cancers, Western blot analysis was also used to determine the effect of PHEO in protein expression of ß-catenin inhibition. Also, an in silico analysis was carried out to investigate the effect of PHEO extracted compounds on protein expression of ß-catenin and FZD7 inhibition. According to the results, wnt pathway genes were changed in samples treated using PHEO. The results showed the up-regulation of GSK-3ß and down-regulation of Wnt-1, LEF-1, TCF1, and CTNNB1 genes compared to the control. CONCLUSION: We showed inhibition of ß-catenin protein in cancer cell lines. Four compounds of PHEO were suggested to have an inhibition effect on ß-catenin and FZD7. These compounds can be useful in the treatment of gastrointestinal cancers. Altogether, the inhibitory role of ß-catenin protein can be very effective and can be considered one of the therapeutic goals in the treatment of gastrointestinal cancers.

In silico targeting breast cancer biomarkers by applying rambutan (Nephelium lappaceum) phytocompounds.

Worldwide, breast cancer is the leading type of cancer among women. Overexpression of various prognostic indicators, including nuclear receptors, is linked to breast cancer features. To date, no effective drug has been discovered to block the proliferation of breast cancer cells. This study has been designed to discover target-based small molecular-like natural drug candidates that have anti-cancer potential without causing any serious side effects. A comprehensive substrate-based drug design was carried out to discover the potential plant compounds against the target breast cancer biomarkers including phytochemicals screening, active site identification, molecular docking, pharmacokinetic (PK) properties prediction, toxicity prediction, and molecular dynamics (MD) simulation approaches. Twenty plant compounds extracted from the rambutan (Nephelium lappaceum) were obtained from PubChem Database; and screened against the breast cancer biomarkers including estrogen receptor (ER), progesterone receptor (PR), and androgen receptor (AR). The best docking interaction was chosen based on the higher binding affinity. Analyzing the pharmacokinetic properties and toxicity prediction results indicated that the fifteen selected plant compounds have good potency without toxicity and are safe for humans. Four phytochemicals with a higher binding affinity were chosen for each breast cancer biomarker to study their stability in interaction with the target proteins using MD simulation. Among the above compounds, Ellagic acid showed the high binding affinity against all three breast cancer biomarkers.Communicated by Ramaswamy H. Sarma.

Isolation of Cells and Exosomes from Glioblastoma Tissue to Investigate the Effects of Ascorbic Acid on the c-Myc, HIF-1α, and Lnc-SNHG16 Genes.

Glioblastoma multiforme (GBM) is incurable with routine treatments. Ascorbic acid (Asc) has antioxidant and anti-cancer properties. However, its specific anti-cancer mechanisms are only partially understood. In this study, the effect of Asc on the c-Myc, HIF-1α, and lnc-SNHG16 genes in GBM cells and their exosomes was investigated. Cells isolated from the tissue were characterized by the immunocytochemistry method (GFAP+). The cell-doubling time was determined, and FBS-free medium supplemented with Asc (5 mM) was added to the cells. The extracted exosomes in the cell culture medium were scanned by electron microscopy, Zetasizer, and BCA assay. The expression of lnc-SNHG16 in the exosomes and c-Myc and HIF-1α in the treated and control cells was evaluated by real-time PCR. The interactions between Asc and the c-Myc and HIF-1α proteins were studied using the molecular docking method. The cells showed 90-100% GFAP+ in passage 4, with a cell-doubling time of 4.8 days. Exosomal vesicles measuring 98.25-105.9 were observed. Zetasizer results showed a sharp pick at 90 nm. Protein quantitation showed 3.812 µg/ml protein in the exosomes. Lnc-SNHG16 expression was reduced (P = 0.041), and c-Myc was upregulated (P = 0.002). The expression of HIF-1α was not significant in the treated cells. Also, Asc was able to interact and affect c-Myc and HIF-1α. Asc exerts its effect by reducing lnc-SNHG16 expression in exosomes, upregulating c-Myc in GBM cells, and interacting with HIF-1α and c-Myc. Further research is necessary to achieve a full understanding of these findings.

Self-amplifying mRNA vaccines: Mode of action, design, development and optimization.

The mRNA-based vaccines are quality-by-design (QbD) immunotherapies that provide safe, tunable, scalable, streamlined and potent treatment possibilities against different types of diseases. The self-amplifying mRNA (saRNA) vaccines, as a highly advantageous class of mRNA vaccines, are inspired by the intracellular self-multiplication nature of some positive-sense RNA viruses. Such vaccine platforms provide a relatively increased expression level of vaccine antigen(s) together with self-adjuvanticity properties. Lined with the QbD saRNA vaccines, essential optimizations improve the stability, safety, and immunogenicity of the vaccine constructs. Here, we elaborate on the concepts and mode-of-action of mRNA and saRNA vaccines, articulate the potential limitations or technical bottlenecks, and explain possible solutions or optimization methods in the process of their design and development.

Mitohormesis and mitochondrial dynamics in the regulation of stem cell fate.

The ability of stem cells for self-renewing, differentiation, and regeneration of injured tissues is believed to occur via the hormetic modulation of nuclear/mitochondrial signal transductions. The evidence now indicates that in damaged tissues, the mitochondria set off the alarm under oxidative stress conditions, hence they are the central regulators of stem cell fate decisions. This review aimed to provide an update to a broader concept of stem cell fate in stress conditions of damaged tissues, and insights for the mitochondrial hormesis (mitohormesis), including the integrated stress response (ISR), mitochondrial dynamics, mitochondria uncoupling, unfolded protein response, and mitokines, with implications for the control of stem cells programing in a successful clinical cell therapy.

Novel targets to overcome antiangiogenesis therapy resistance in glioblastoma multiforme: Systems biology approach and suggestion of therapy by galunisertib.

Glioblastoma multiforme (GBM) is a tumor with high microvessel density. Antiangiogenesis therapy (AAT) resistance occurs due to the complex mechanisms involved in angiogenesis, with increased chances of recurrence. The vascular endothelial growth factor (VEGF) pathway is the main pathway of angiogenesis, and anti-VEGF drugs have been ineffective in controlling it. New oncogenes in the VEGF signaling pathway may be new candidates for angiogenesis targeting. Oncogene candidates were chosen using gene expression profiles and databases. Then oncogenes were subjected to gene set enrichment analysis (GSEA) and survival analysis (SA). Molecular docking was conducted to evaluate the interaction of the oncogenes with galunisertib. NRAS, AKT1, and HSPB1 were the most effective oncogenes upregulating genes that play a role in GBM expression in the VEGF signaling pathway. The VEGF and MAPK signaling pathways were found to be effective using GSEA and Kyoto Encyclopedia Gene and Genome pathway analysis. Survival analyses revealed that patients with high HSPB1 expression had poorer overall survival rates than those with low HSPB1 expression. Galunisertib exhibits intermolecular interactions with 6DV5, 5UHV, and 3O96 (binding energy -8.0, -8.6, and -10.3 kcal/mol, respectively). The current AAT should be restrategized to suppress the numerous angiogenic elements to manage angiogenesis and combat AAT resistance in GBM. In silico analysis indicated that NRAS, AKT1, and HSPB1 genes can be the main oncogenes in the VEGF signaling pathway and galunisertib strongly interacts with these genes. Consequently, the use of galunisertib to overcome AAT in GBM in combination therapy can be assessed.

The protective effect of N-acetylcysteine on antimycin A-induced respiratory chain deficiency in mesenchymal stem cells.

Transplantation of mesenchymal stem cells (MSCs) is an effective treatment in tissue injuries though it is limited due to the early death of stem cells within the first few days. The main reason could be a deficiency in the respiratory chain of injured tissues which is linked to the oxidative stress (OS) and disruption of energy metabolism. The disruption in energy metabolism and OS both inhibit the homing of stem cells in the hypoxic micro-environment, however on other hand, the key functions of stem cells are mainly regulated by their cellular redox status and energy metabolism. Because of that, strategies are being developed to improve the bio-functional properties of MSCs, including preconditioning of the stem cells in hypoxic conditions and pretreatment of antioxidants. To achieve this purpose, in this study N-acetylcysteine (NAC) was used for the protection of cells from oxidative stress and the disruption in energy metabolism was induced by Antimycin A (AMA) via blocking the cytochrome C complex. Then several parameters were analyzed, including cell viability/apoptosis, mitochondrial membrane potential, and redox molecular homeostasis. Based on our findings, upon the exposure of the MSCs to the conditions of deficient respiratory chain, the cells failed to scavenge the free radicals, and energy metabolism was disrupted. The use of NAC was found to alleviate the DNA damage, cell apoptosis, and oxidative stress via Nrf2/Sirt3 pathway though without any effect on the mitochondrial membrane potential. It means that antioxidants protect the cells from OS but the problem of ATP metabolism yet remains unresolved in the hypoxic conditions.

Clinical Manifestations Associated with the Domain-Containing Protein 2 Gene Mutation in an Iranian Family with Spastic Paraplegia 54.

INTRODUCTION: Spastic paraplegia type 54 (SPG54) is an autosomal recessive disorder caused by bi-allelic mutations in the DDHD-domain-containing protein 2 (DDHD2) gene. Worldwide, over 24 SPG54 families and 24 pathogenic variants have been reported. Our study aimed to describe the clinical and molecular findings of a pediatric patient from a consanguineous Iranian family with significant motor development delay, walking problems, paraplegia, and optic atrophy. METHODS: The patient was a 7-year-old boy with severe neurodevelopmental and psychomotor problems. Neurological examinations, laboratory tests, electroencephalography, computed tomography scan, and brain magnetic resonance scan (MRI) were carried out for clinical evaluation. Whole-exome sequencing and in silico analysis were undertaken to identify the genetic cause of the disorder. RESULTS: The neurological examination showed developmental delay, spasticity in the lower extremities, ataxia, foot contractures, and deep tendon reflexes in the extremities. The computed tomography scan was normal, but MRI revealed corpus callosum thinning with atrophic changes in the white matter. The genetic study reported a homozygous variant (c.856 C>T, p.Gln286Ter) in the DDHD2 gene. The homozygous state was confirmed by direct sequencing in the proband and his 5-year-old brother. This variant was not reported as a pathogenic variant in the literature or genetic databases and was predicted to affect the function of the DDHD2 protein. CONCLUSION: The clinical symptoms in our cases were similar to the previously reported phenotype of SPG54. Our results deepen the molecular and clinical spectrum of SPG54 to facilitate future diagnoses.

Pharmacoinformatics-based phytochemical screening for anticancer impacts of yellow sweet clover, Melilotus officinalis (Linn.) Pall.

To date, much attention has been paid to phytochemicals because of their diverse pharmacological effects on a variety of diseases such as cancer. In this regard, computer-aided drug design, as a cost- and time-effective approach, is primarily applied to investigate the drug candidates before their further costly in vitro and in vivo experimental evaluations. Accordingly, different signaling pathways and proteins can be targeted using such strategies. As a key protein for the initiation of eukaryotic DNA replication, mini-chromosome maintenance complex component 7 (MCM7) overexpression is related to the initiation and progression of aggressive malignancies. The current study was conducted to identify new potential natural compounds from the yellow sweet clover, Melilotus officinalis (Linn.) Pall, by examining the potential of 40 isolated phytochemicals against MCM7 protein. A structure-based pharmacophore model to the protein active site cavity was generated and followed by virtual screening and molecular docking. Overall, four compounds were selected for further evaluation based on their binding affinities. Our analyses revealed that two novel compounds, namely rosmarinic acid (PubChem CID:5281792) and melilotigenin (PubChem CID:14059499) might be druggable and offer safe usage in human. The stability of these two protein-ligand complex structures was confirmed through molecular dynamics simulation. The findings of this study reveal the potential of these two phytochemicals to serve as anticancer agents, while further pharmacological experiments are required to confirm their effectiveness against human cancers.

A novel multi-objective metaheuristic algorithm for protein-peptide docking and benchmarking on the LEADS-PEP dataset.

Protein-peptide interactions have attracted the attention of many drug discovery scientists due to their possible druggability features on most key biological activities such as regulating disease-related signaling pathways and enhancing the immune system's responses. Different studies have utilized some protein-peptide-specific docking algorithms/methods to predict protein-peptide interactions. However, the existing algorithms/methods suffer from two serious limitations which make them unsuitable for protein-peptide docking problems. First, it seems that the prevalent approaches require to be modified and remodeled for weighting the unbounded forces between a protein and a peptide. Second, they do not employ state-of-the-art search algorithms for detecting the 3D pose of a peptide relative to a protein. To address these restrictions, the present study aims to introduce a novel multi-objective algorithm, which first generates some potential 3D poses of a peptide, and then, improves them through its operators. The candidate solutions are further evaluated using Multi-Objective Pareto Front (MOPF) optimization concepts. To this end, van der Waals, electrostatic, solvation, and hydrogen bond energies between the atoms of a protein and designated peptide are computed. To evaluate the algorithm, it is first applied to the LEADS-PEP dataset containing 53 protein-peptide complexes with up to 53 rotatable branches/bonds and then compared with three popular/efficient algorithms. The obtained results indicate that the MOPF-based approaches which reduce the backbone RMSD between the original and predicted states, achieve significantly better results in terms of the success rate in predicting the near-native conditions. Besides, a comparison between the different types of search algorithms reveals that efficient ones like the multi-objective Trader/differential evolution algorithm can predict protein-peptide interactions better than the popular algorithms such as the multi-objective genetic/particle swarm optimization algorithms.

Role of cellulose family in fibril organization of collagen for forming 3D cancer spheroids: In vitro and in silico approach.

Introduction: Cell aggregation of three-dimensional (3D) culture systems (the so-called spheroids) are designed as in vitro platform to represent more accurately the in vivo environment for drug discovery by using semi-solid media. The uniform multicellular tumor spheroids can be generated based on the interaction of cells with extracellular matrix (ECM) macromolecules such as collagen and integrin. This study aimed to investigate the possible interactions between the cellulose family and collagen using both in vitro and in silico approaches. Methods: The 3D microtissue of JIMT-1 cells was generated using hanging drop method to study the effects of charge and viscosity of the medium containing cellulose family. To determine the mode of interaction between cellulose derivatives (CDs) and collagen-integrin, docking analysis and molecular simulation were further performed using open source web servers and chemical simulations (GROMACS), respectively. Results: The results confirmed that the addition of CDs into the 3D medium can promote the formation of solid spheroids, where methylcellulose (MC) yielded uniform spheroids compared to carboxymethyl cellulose (CMC). Moreover, the computational analysis showed that MC interacted with both integrin and collagen, while sodium carboxymethyl cellulose (NaCMC) only interacted with collagen residues. The stated different behaviors in the 3D culture formation and collagen interaction were found in the physicochemical properties of CDs. Conclusion: Based on in vitro and in silico findings, MC is suggested as an important ECM-mimicking entity that can support the semi-solid medium and promote the formation of the uniform spheroid in the 3D culture.

Psychrophilic enzymes: structural adaptation, pharmaceutical and industrial applications.

Psychrophiles are cold-living microorganisms synthesizing enzymes that are permanently active at almost near-zero temperatures. Psychrozymes are supposed to be structurally more flexible than their homologous proteins. This structural flexibility enables these proteins to undergo conformational changes during catalysis and improve catalytic efficiency at low temperatures. The outstanding characteristics of the psychrophilic enzymes have attracted the attention of the scientific community to utilize them in a wide variety of industrial and pharmaceutical applications. In this review, we first highlight the current knowledge of the cold-adaptation mechanisms of the psychrophiles. In the sequel, we describe the potential applications of the enzymes in different biotechnological processes specifically, in the production of industrial and pharmaceutical products. KEY POINTS: • Methods that organisms have evolved to survive and proliferate at cold environments. • The economic benefits due to their high activity at low and moderate temperatures. • Applications of the psychrophiles in biotechnological and pharmaceutical industry.

A domain-based vaccine construct against SARS-CoV-2, the causative agent of COVID-19 pandemic: development of self-amplifying mRNA and peptide vaccines.

Introduction: Coronavirus disease 2019 (COVID-19) is undoubtedly the most challenging pandemic in the current century with more than 293,241 deaths worldwide since its emergence in late 2019 (updated May 13, 2020). COVID-19 is caused by a novel emerged coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Today, the world needs crucially to develop a prophylactic vaccine scheme for such emerged and emerging infectious pathogens. Methods: In this study, we have targeted spike (S) glycoprotein, as an important surface antigen to identify its B- and T-cell immunodominant regions. We have conducted a multi-method B-cell epitope (BCE) prediction approach using different predictor algorithms to discover the most potential BCEs. Besides, we sought among a pool of MHC class I and II-associated peptide binders provided by the IEDB server through the strict cut-off values. To design a broad-coverage vaccine, we carried out a population coverage analysis for a set of candidate T-cell epitopes and based on the HLA allele frequency in the top most-affected countries by COVID-19 (update 02 April 2020). Results: The final determined B- and T-cell epitopes were mapped on the S glycoprotein sequence, and three potential hub regions covering the largest number of overlapping epitopes were identified for the vaccine designing (I531-N711; T717-C877; and V883-E973). Here, we have designed two domain-based constructs to be produced and delivered through the recombinant protein- and gene-based approaches, including (i) an adjuvanted domain-based protein vaccine construct (DPVC), and (ii) a self-amplifying mRNA vaccine (SAMV) construct. The safety, stability, and immunogenicity of the DPVC were validated using the integrated sequential (i.e. allergenicity, autoimmunity, and physicochemical features) and structural (i.e. molecular docking between the vaccine and human Toll-like receptors (TLRs) 4 and 5) analysis. The stability of the docked complexes was evaluated using the molecular dynamics (MD) simulations. Conclusion: These rigorous in silico validations supported the potential of the DPVC and SAMV to promote both innate and specific immune responses in preclinical studies.

Nanobody-based therapeutics against colorectal cancer: Precision therapies based on the personal mutanome profile and tumor neoantigens.

Monoclonal antibodies and vaccines have widely been studied for the immunotherapy of cancer, while their large size appears to limit their functionality in solid tumors, in large part due to unique properties of tumor microenvironment such as high pressure of tumor interstitial fluid. To tackle such limitations, smaller formats of antibodies have been developed, including antigen-binding fragments, single-chain variable fragments, single variable domain of camelid antibody (so-called nanobody (Nb) or VHH). Of these, Nbs offer great immunotherapy potentials because of their advantageous physicochemical and pharmacological features, including small size, high stability, and excellent tissue penetration. Besides, the therapeutic impacts of Nbs can be improved by their modifications and functionalizations (e.g., PEGylation and conjugation to the Fc domain, peptide tags, drugs, toxins, aptamers, and radionuclides). This review aims to provide comprehensive insights into key signaling networks of colorectal cancer and discuss Nb-based precision immunotherapy of colorectal cancer.

Epitope-based vaccine design: a comprehensive overview of bioinformatics approaches.

Computational epitope-based vaccine design is the cornerstone of vaccine development. Owing to the selection of proper compositions [antigens (Ags), epitopes, peptide linkers, and intramolecular adjuvants], epitope-based vaccines are considered a cost- and time-effective approach resulting in the development of vaccines with maximal therapeutic efficacy and minimal adverse reactions. In this review, we provide insights into in silico epitope-based vaccine design and highlight vaccinology procedures used for the development of the next-generation vaccines with high effectiveness.

In silico design of a triple-negative breast cancer vaccine by targeting cancer testis antigens.

Introduction: Triple-negative breast cancer (TNBC) is an important subtype of breast cancer, which occurs in the absence of estrogen, progesterone and HER-2 receptors. According to the recent studies, TNBC may be a cancer testis antigen (CTA)-positive tumor, indicating that the CTA-based cancer vaccine can be a treatment option for the patients bearing such tumors. Of these antigens (Ags), the MAGE-A family and NY-ESO-1 as the most immunogenic CTAs are the potentially relevant targets for the development of an immunotherapeutic way of the breast cancer treatment. Methods: In the present study, immunoinformatics approach was used to design a multi-epitope peptide vaccine to combat the TNBC. The vaccine peptide was constructed by the fusion of three crucial components, including the CD8+ cytotoxic T lymphocytes (CTLs) epitopes, helper epitopes and adjuvant. The epitopes were predicted from the MAGE-A and NY-ESO-1 Ags. In addition, the granulocyte-macrophage-colony-stimulating factor (GM-CSF) was used as an adjuvant to promote the CD4+ T cells towards the T-helper for more strong induction of CTL responses. The components were conjugated by proper linkers. Results: The vaccine peptide was examined for different physiochemical characteristics to confirm the safety and immunogenic behavior. Furthermore, the 3D-structure of the vaccine peptide was predicted based on the homology modeling approach using the MODELLER v9.17 program. The vaccine structure was also subjected to the molecular dynamics simulation study for structure refinement. The results verified the immunogenicity and safety profile of the constructed vaccine as well as its capability for stimulating both the cellular and humoral immune responses. Conclusion: Based on our in-silico analyses, the proposed vaccine may be considered for the immunotherapy of TNBC.