Neuroblastoma (NB) is the third most prevalent tumor that mostly influences infants and young children. Although different treatments have been developed for the treatment of NB, high-risk patients have been reported to have low survival rates. Currently, long noncoding RNAs (lncRNAs) have shown an attractive potential in cancer research and a party of investigations have been performed to understand mechanisms underlying tumor development through lncRNA dysregulation. Researchers have just newly initiated to exhibit the involvement of lncRNAs in NB pathogenesis. In this review article, we tried to clarify the point we stand with respect to the involvement of lncRNAs in NB. Moreover, implications for the pathologic roles of lncRNAs in the development of NB have been discussed. It seems that some of these lncRNAs have promising potential to be applied as biomarkers for NB prognosis and treatment.

The tumor microenvironment (TME) is well-defined target for understanding tumor progression and various cell types. Major elements of the tumor microenvironment are the followings: endothelial cells, fibroblasts, signaling molecules, extracellular matrix, and infiltrating immune cells. MicroRNAs (miRNAs) are a group of small noncoding RNAs with major functions in the gene expression regulation at post-transcriptional level that have also appeared to exerts key functions in the cancer initiation/progression in diverse biological processes and the tumor microenvironment. This study summarized various roles of miRNAs in the complex interactions between the tumor and normal cells in their microenvironment.

In all species, dihydrofolate reductase (DHFR) is an essential enzyme that regulates the cellular amount of tetrahydrofolate. Human DHFR (hDHFR) activity inhibition results in tetrahydrofolate depletion and cell death. This property has made hDHFR a therapeutic target for cancer. Methotrexate is a well-known hDHFR inhibitor, but its administration has shown some light to severe adverse effects. Therefore, we aimed to find new potential hDHFR inhibitors using structure-based virtual screening, ADMET prediction, molecular docking, and molecular dynamics simulations. Here, we used the PubChem database to find all compounds with at least 90% structural similarity to known natural DHFR inhibitors. To explore their interaction pattern and estimate their binding affinities, the screened compounds (2023) were subjected to structure-based molecular docking against hDHFR. The fifteen compounds that showed higher binding affinity to the hDHFR than the reference compound (methotrexate) displayed important molecular orientation and interactions with key residues in the enzyme's active site. These compounds were subjected to Lipinski and ADMET prediction. PubChem CIDs: 46886812 and 638190 were identified as putative inhibitors. In addition, molecular dynamics simulations revealed that the binding of compounds (CIDs: 46886812 and 63819) stabilized the hDHFR structure and caused minor conformational changes. Our findings suggest that two compounds (CIDs: 46886812 and 63819) could be promising potential inhibitors of hDHFR in cancer therapy.Communicated by Ramaswamy H. Sarma.

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.

Melanoma is the most aggressive form of skin cancer resulting from genetic mutations in melanocytes. Several factors have been considered to be involved in melanoma progression, including genetic alteration, processes of damaged DNA repair, and changes in mechanisms of cell growth and proliferation. Epigenetics is the other factor with a crucial role in melanoma development. Epigenetic changes have become novel targets for treating patients suffering from melanoma. These changes can alter the expression of microRNAs and their interaction with target genes, which involves cell growth, differentiation, or even death. Given these circumstances, we conducted the present review to discuss the melanoma risk factors and represent the current knowledge about the factors related to its etiopathogenesis. Moreover, various epigenetic pathways, which are involved in melanoma progression, treatment, and chemo-resistance, as well as employed epigenetic factors as a solution to the problems, will be discussed in detail.

Background: Non-small cell lung cancer (NSCLC) is the principal subtype of lung cancer. Among all therapeutic options, platinum-based chemotherapy agents, especially Cisplatin, are still commonly used treatment for NSCLC patients. However, developing chemoresistance in NSCLC cells often gives rise to chemotherapy failure. Therefore, more studies are required to shed light on gene interaction and cellular pathways involved in initiating and developing resistance to platinum-based chemotherapy in NSCLC. Hence, it is urgent to find the key genes, microRNA (miRNAs), and potential molecular mechanisms implicated in chemoresistance and present markers to predict response to platinum-based chemotherapy in NSCLC patients. Methods: The microarray datasets GSE6410, GSE7035, GSE14814, GSE26704, GSE73302 were downloaded from the Gene Expression Omnibus (GEO) database and were analyzed using R software. Functional and pathway enrichment analyses were performed using the Enrich R site. Then, the protein-protein interaction (PPI) network and hub genes were obtained using the Cytoscape software. Further, the miRSystem database was performed to predict the miRNAs regulating the hub genes. Moreover, Cytoscape software and the CytoHubba plugin were used to construct the miRNA-target interaction network and hub modules. Finally, the Kaplan-Meier curve was used to demonstrate the survival curves and assess the association of the genes signature with clinical outcomes. Results: A total of 142 differentially expressed genes (DEGs) were found. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses present the p53 signaling pathway as the most significant pathway. Besides, from the top ten terms obtained of Biological Process, Molecular Function, and Cellular Component, the first ones, including cholesterol biosynthetic process, the extrinsic component of external side of plasma membrane, cytokine activity, were selected respectively. Based on the PPI network, the ten nodes with the highest degree were screened as hub genes. In addition, from the miRNA-target regulatory network in Cytoscape, ten hub nodes were found. Ultimately, according to Kaplan-Meier curve, BTG2 and TP53I3 with p-value <0.05 were associated with a better prognosis. Conclusions: In the present study, DEGs, candidate miRNAs, and underlying mechanisms involved in chemoresistance were identified to suggest potential biomarkers to provide new clues for the prediction of response to platinum-based chemotherapy.

Type 1 diabetes (T1D) occurs as a consequence of an autoimmune attack against pancreatic β- cells. Due to a lack of a clear understanding of the T1D pathogenesis, the identification of effective therapies for T1D is the active area in the research. The study purpose was to prioritize potential drugs and targets in T1D via systems biology approach. Gene expression data of peripheral blood mononuclear cells (PBMCs) and pancreatic β-cells in T1D were analyzed and differential expressed genes were integrated with protein-protein interactions (PPI) data. Multiple topological centrality parameters of extracted query-query PPI (QQPPI) networks were calculated and the interaction of more central proteins with drugs was investigated. Molecular docking was performed to further predict the interactions between drugs and the binding sites of targets. Central proteins were identified by the analysis of PBMC (MYC, ERBB2, PSMA1, ABL1 and HSP90AA1) and pancreatic β-cells (HSP90AB1, ESR1, RELA, RAC1, NFKB1, NFKB2, IKBKE, ARRB2 and SRC) QQPPI networks. Thirteen drugs which targeted eight central proteins were identified by further analysis of drug-target interactions. Some drugs which investigated for diabetes treatment in the experimental models of T1D were prioritized by literature verification, including melatonin, resveratrol, lapatinib, geldanamycin, eugenol and fostaminib. Finally, according on molecular docking analysis, lapatinib-ERBB2 and eugenol-ESR1 exhibited highest and lowest binding energy, respectively. This study presented promising results for the prioritization of potential drug-targets which might facilitate T1D targeted therapy and its drug discovery process more effectively.