Potential Small Molecule Drugs Research Articles

Identification of novel candidate genes and small molecule drugs in ovarian cancer by bioinformatics strategy.

BackgroundOvarian cancer (OC) is the most lethal type of malignancies in the female reproductive system. This study aimed to identify novel biomarkers and potential small molecule drugs in OC by integrating two expression profile datasets.MethodsGSE18520 and GSE14407 from the Gene Expression Omnibus (GEO) database were selected and the overlapped differentially expressed genes (DEGs) were detected. The Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analysis were performed to establish the protein-protein interaction (PPI) network of DEGs and identified the hub genes. Gene Expression Profiling Interactive Analysis (GEPIA), Oncomine database and The Human Protein Atlas (HPA) were used to validate the expression of the identified hub genes. The prognostic value of these hub genes were evaluated by the Kaplan Meier plotter online tool. The expression of NCAPG was further explored by immunohistochemistry in our OC tissues. Moreover, CMap database was used to look for prospective small compounds with therapeutic efficacy based on OC RNA-seq.ResultsA total of 433 DEGs were identified. The DEGs were mainly enriched in negative regulation of transcription and pathways in cancer. A PPI network was constructed with 344 nodes and 1,596 interactions. The top ten module genes were chosen as hub genes. Among which, survival analysis showed that patients with high expression of CCNB1, TOP2A, NUSAP1, NCAPG, KIF20A and DLGAP5 had poorer survival results than those with low expression. These six genes were all overexpressed in OC tissue by means of bioinformatics analysis. In our clinical patients, the expression rate of NCAPG in OC tissues was significantly higher than that in benign serous ovarian cystadenoma and borderline serous ovarian cystadenoma tissues. Meanwhile, several small molecules with potential therapeutic efficacy against OC were identified in our study.ConclusionsBy means of bioinformatics analysis, we identified six real hub genes and indicated a group of candidate small molecule drugs as adjunctive agents for OC. They could be the potential novel biomarkers for the diagnosis and promising therapeutic targets of OC.

Epigenetic Alterations of DNA Methylation and miRNA Contribution to Lung Adenocarcinoma.

This study focused on the epigenetic alterations of DNA methylation and miRNAs for lung adenocarcinoma (LUAD) diagnosis and treatment using bioinformatics analyses. DNA methylation data and mRNA and miRNA expression microarray data were obtained from The Cancer Genome Atlas (TCGA) database. The differentially methylated genes (DMGs), differentially expressed genes (DEGs), and differentially expressed miRNAs were analyzed by using the limma package. The DAVID database performed GO and KEGG pathway enrichment analyses. Using STRING and Cytoscape, we constructed the protein–protein interaction (PPI) network and achieved visualization. The online analysis tool CMap was used to identify potential small-molecule drugs for LUAD. In LUAD, 607 high miRNA-targeting downregulated genes and 925 low miRNA-targeting upregulated genes, as well as 284 hypermethylated low-expression genes and 315 hypomethylated high-expression genes, were obtained. They were mainly enriched in terms of pathways in cancer, neuroactive ligand–receptor interaction, cAMP signaling pathway, and cytosolic DNA-sensing pathway. In addition, 40 upregulated and 84 downregulated genes were regulated by both aberrant alternations of DNA methylation and miRNAs. Five small-molecule drugs were identified as a potential treatment for LUAD, and five hub genes (SLC2A1, PAX6, LEP, KLF4, and FGF10) were found in PPI, and two of them (SLC2A1 and KLF4) may be related to the prognosis of LUAD. In summary, our study identified a series of differentially expressed genes associated with epigenetic alterations of DNA methylation and miRNA in LUAD. Five small-molecule drugs and five hub genes may be promising drugs and targets for LUAD treatment.

Rheumatoid Arthrities: Etiology Pathophysiology and Modern Treatments

Rheumatoid arthritis (RA) is an autoimmune disease that affects the joints. Age, gender, genetics, and environmental exposure are all factors (cigarette smoking, air pollutants, and occupational). If untreated, felty syndrome, rheumatoid vasculitis, and irreversible joint damage might occur, necessitating splenectomy. Because there is no cure for RA, treatment seeks to reduce pain and prevent further damage. To develop effective RA treatments, researchers must first understand how the disease advances in people and how pathogenic pathways influence this progression. Modern pharmacologic therapy have made tremendous progress in obtaining illness remission without joint deformity (including conventional and biological treatments as well as novel potential small-molecule disease-modifying drugs). Despite this, many RA patients do not respond well to conventional treatments, necessitating the development of novel drugs. This comprehensive review of current advancements covers RA causation, disease-modifying drugs, and prospective RA therapeutics. This section summarises the various RA-related therapies available in the past and now.

Discovery of Novel Inhibitors for Mycobacterium tuberculosis D‐alanine: D‐alanine Ligase through Virtual Screening

Tuberculosis (TB), although not as common in high‐income countries due to vaccines and antibiotic therapy, remains one of the highest causes of death in low‐income countries. However, overuse of antibiotics has led to the emergence of antibiotic‐resistant strains of the disease. To offset these issues, potential small molecule drug compounds must be identified to combat this bacteria in order to further the drug development process. Tuberculosis can be caused by a variety of other strains of the bacterium, but Mycobacterium tuberculosis is the most common and the most virulent. The D‐alanine:D‐alanine ligase (Ddl) enzyme is an attractive target for drug discovery as it catalyzes a crucial reaction that is necessary for the survival of the bacteria: the formation of the D‐alanyl‐D‐alanine dipeptide from adenosine triphosphate (ATP) and two D‐alanine amino acids. This dipeptide complex then plays a pivotal role in crosslinking peptidoglycan chains during the assembly of the bacterial cell wall. Drugs that target Ddl currently exist on the market, but antibiotic resistance has reduced their efficacy. A crystallography structure of Ddl from M. tuberculosis(PDB ID: 3LWB) was used in conjunction with the virtual screening program GOLD (Genetic Optimization for Ligand Docking by the Cambridge Crystallographic Data Center) and ICM (Internal Coordinate Mechanics by Molsoft) to search for ligands that had a predicted strong binding affinity to the enzyme’s active site. Both the D‐alanine and the ATP sites were targeted in this study. Various ligand libraries were screened and ranked based on binding interactions with the active site. The docking poses of the top‐ranking ligands were further verified through the molecular visualization program PyMol (Schrodinger). The highest‐ranking ligand targeting the ATP site from GOLD, SAM001246657, came from the National Institutes of Health’s Clinical Collection library (NIH) and received an overall fitness score of 104.4. The highest‐ranking compound from the ICM screen targeting the ATP site was SPB06710SC from the HitFinder 9 library and received a score of ‐36.32. For the D‐alanine site, the highest docking ligand from GOLD was ZINC14539627 with a score of 100.77. From ICM, the highest scoring ligand was ZINC11535505 with a score of ‐32.27. Both ligands are from the Zinc ChemBridge library. The inhibitory effects of these top‐scoring ligands may be further validated through wet‐lab research using binding assays and enzyme inhibition assays.

Identification of Potential Biomarkers and Small Molecule Drugs for Cutaneous Melanoma Using Integrated Bioinformatic Analysis.

Background: Cutaneous melanoma (CM) is a type of skin cancer with a high fatality rate, and its pathogenesis has not yet been fully elucidated. Methods: We obtained the gene expression datasets of CM through the Gene Expression Omnibus (GEO) database. Subsequently, robust rank aggregation (RRA) method was used to identify differentially expressed genes (DEGs) between CM cases and normal skin controls. Gene functional annotation was performed to explore the potential function of the DEGs. We built the protein–protein interaction (PPI) network by the Interactive Gene database retrieval tool (STRING) and selected hub modules by Molecular Complexity Detection (MCODE). We furthered and validated our results using the TCGA-GTEX dataset. Finally, potential small molecule drugs were predicted by CMap database and verified by molecular docking method. Results: A total of 135 DEGs were obtained by RRA synthesis analysis. GMPR, EMP3, SLC45A2, PDZD2, NPY1R, DLG5 and ADH1B were screened as potential targets for CM. Furazolidone was screened as a potential small molecule drug for the treatment of CM, and its mechanism may be related to the inhibition of CM cell proliferation by acting on GMPR. Conclusion: We identified seven prognostic therapeutic targets associated with CM and furazolidone could be used as a potential drug for CM treatment, providing new prognostic markers, potential therapeutic targets and small molecule drugs for the treatment and prevention of CM.

Inferences of carboplatin response-related signature by integrating multiomics data in ovarian serous cystadenocarcinoma.

Platinum-based chemotherapy, especially carboplatin, is the primary measure to treat patients with ovarian cancer (OC). However, OC patients still have an adverse prognosis due to emergency of chemotherapy resistance. Ovarian serous cystadenocarcinoma (OSC) is the most common histological subtype of OC. Therefore, identifying the key factors that affect chemotherapy resistance and searching novel treatments had become a top priority. In this study, we analyzed carboplatin response-related mRNA, miRNA, DNA methylation, and alternative splicing (AS) and established a drug-resistant signature for carboplatin in OSC. This drug-resistant signature was obviously higher in resistant group than in non-resistant group and had accuracy predictive performance, which demonstrated that this signature could be considered as a superior indicator for OSC patients with carboplatin resistance. Furthermore, we selected three potential small molecule drugs including liranaftate, siguazodan, and tramiprostate to inhibit carboplatin resistance of OSC. In addition, we also identified ZINC00000205417, ZINC00000140928, and ZINC00021908260 were potential small molecule compounds for SLC17A7 based on Molecular Operating Environment (MOE) virtual screening. Finally, we confirmed the drug-like properties of these small molecule drugs via evaluating absorption, distribution, metabolism, elimination, and toxicity (ADMET) property. In summary, the signature could be used as biomarker for carboplatin resistance and small molecule drugs targeting these genes could improve clinical treatment for OSC in the future.

Identification of Molecular Subtypes and Potential Small-Molecule Drugs for Esophagus Cancer Treatment Based on m6A Regulators.

Background Esophagus cancer (ESCA) is the sixth most frequent cancer in males, with 5-year overall survival of 15%–25%. RNA modifications function critically in cancer progression, and m6A regulators are associated with ESCA prognosis. This study further revealed correlations between m6A and ESCA development. Methods Univariate Cox regression analysis and consensus clustering were applied to determine molecular subtypes. Functional pathways and gene ontology terms were enriched by gene set enrichment analysis. Protein-protein interaction (PPI) analysis on differentially expressed genes (DEGs) was conducted for hub gene screening. Public drug databases were employed to study the interactions between hub genes and small molecules. Results Three molecular subtypes related to ESCA prognosis were determined. Based on multiple analyses among molecular subtypes, 146 DEGs were screened, and a PPT network of 15 hub genes was visualized. Finally, 8 potential small-molecule drugs (BMS-754807, gefitinib, neratinib, zuclopenthixol, puromycin, sulfasalazine, and imatinib) were identified for treating ESCA. Conclusions This study applied a new approach to analyzing the relation between m6A and ESCA prognosis, providing a reference for exploring potential targets and drugs for ESCA treatment.

A novel signature based on autophagy-related lncRNA for prognostic prediction and candidate drugs for lung adenocarcinoma.

BackgroundAutophagy inhibits tumorigenesis by limiting inflammation. Various lncRNAs are associated with tumour biological processes, including lung adenocarcinoma (LUAD), but the role of autophagy-related lncRNAs (ARlncRNAs) in LUAD has not been fully elucidated. Thus, this study aimed to construct a prognostic signature based on ARlncRNAs for LUAD.MethodsThe RNA-seq (FPKM) data and clinical information of LUAD patients were downloaded from The Cancer Genome Atlas (TCGA) database. After differentially expressed lncRNAs in tumour and normal groups were identified, cox regression analyses were performed to construct a prognostic signature which was then assessed through independent prognostic analysis and functional enrichment analysis. Moreover, based on the mRNAs co-expressed with the ARlncRNAs, several potential small molecule drugs were explored in the Connectivity map (Cmap).ResultsA signature consisting of seven ARlncRNAs (FAM83A−AS1, LINC01116, ILF3-DT, EBLN3P, AL161785.1, AC092279.1 and AC026355.2) was constructed to predict overall survival (OS) for LUAD. The signature was identified to be independent by the cox regression analysis and obtained the largest area under the curve (AUC =0.721) in the receiver operating characteristic (ROC). Six small molecule drugs (MS-275, methotrexate, desipramine, benzbromarone, rifampicin and doxazosin) were selected from Cmap.ConclusionsA novel ARlncRNA signature for LUAD prognostic prediction was constructed, which had better efficacy than the TNM stage and used to propose potential therapeutic regimens for LUAD patients.

Distinct binding interactions trigger opposite conformational modulations on pathogenic and wildtype Huntingtin exon 1 proteins.

Abnormal elongation of the polyglutamine tract transforms exon 1 of the Huntingtin protein (Htt-exon-1) from wildtype to pathogenic form, and causes Huntington's disease. As an intrinsically disordered protein, the structural ensemble of Htt-exon-1 is highly heterogeneous and the detailed conformation of toxic species is still under debate. Ispinesib, a potential small-molecule drug, has been identified to selectively link the pathogenic Htt-exon-1 into the autophagosome to degrade, thus opening an innovative therapeutic direction. However, the molecular mechanisms behind this selectivity remain largely elusive. Herein, we carry out extensive molecular dynamics simulations with an enhanced sampling method to investigate the ispinesib inducing conformational changes of pathogenic and wildtype Htt-exon-1 and the corresponding binding mechanisms. Our simulations reveal that the ispinesib binding induces opposite conformational changes in pathogenic and wildtype Htt-exon-1, i.e., the 'entropy collapse' with significant reduction of β-sheets versus the 'entropy expansion' with a slight increase of α-helices. Network analyses further reveal that there are two stable binding sites in the pathogenic Htt-exon-1, while the binding on the wildtype Htt-exon-1 is highly dynamic and non-specific. These dramatic differences originate from the underlying distinct binding interactions. More specifically, stronger hydrogen bonds serve as the specific binding anchors in pathogenic Htt-exon-1, while stronger hydrophobic interactions dominate in the dynamic binding with wildtype Htt-exon-1. Our simulations provide an atomistic mechanism for the ispinesib selective binding on the pathogenic Htt-exon-1, and further shed light on the general mechanisms of small molecule modulation on intrinsically disordered proteins.

Therapeutic Efficacy of Antibacterial Ocellatin Peptides- A Comprehensive Review

Antimicrobial peptides (AMPs), ascribed to their decreased microbial drug resistance, can be employed as potent small-molecule drugs to treat various diseases. AMPs have been conserved in a wide variety of living organisms as a result of the evolution of the innate immune system. Notably, Ocellatin AMPs derived from South American Leptodactylus genus frogs have a higher therapeutic efficacy against infections. Inhibitory activity of Ocellatin AMPs against bacterial membranes is determined by the dynamic interplay of peptide cationic, hydrophobicity, helicity, and amphipathicity. Another advantage of using AMPs as drug candidates is their cell selectivity that is non-hemolytic to human cells. Ocellatin AMPs with optimal hydrophobic residues would therefore be a recommended therapeutic candidate. Henceforth, such AMPs could be used as an alternative strategy in curbing antimicrobial resistance. It is noteworthy that the therapeutic efficacy of Ocellatins is to be appreciated for its broad application as it has been proved to be active against several humans, animal, and plant bacterial pathogens.

Bioinformatics analyses of the pathogenesis and new biomarkers of chronic obstructive pulmonary disease.

Background:Chronic obstructive pulmonary disease (COPD) is one of the major cause of global death. The purpose of our analysis was to detect a more reliable biomarker and small-molecule drug candidates and to identify the precise mechanisms involved in COPD.Methods:Three data sets were downloaded from the Gene Expression Omnibus database and analysed by Gene Expression Omnibus 2R. Functional enrichment analyses were performed by Metascape. We use the STRING data to build a protein–protein interaction network. The targets of differentially expressed microRNA (DE miRNA) were predicted by the miRWalk database. Small-molecule drugs were predicted on connectivity map.Results:A total of 181 differentially expressed genes and 35 DE miRNAs were confirmed. The protein–protein interaction network including all integrated differentially expressed genes was constructed, and 4 modules were filtrated. The module genes were relative to immune, inflammatory and oxidative stress functions according to a pathway analysis. The top 20 key genes were screened. Among the DE miRNAs found to be regulating key genes, miR-194-3p, MiR-502-5p, MiR-5088-5p, MiR-3127-5p, and miR-23a-5p might be the most significant due to their high number of connecting nodes in COPD. In addition, cephaeline, emetine, gabapentin, and amrinone were found to be potential drugs to treat COPD patients.Conclusion:Our study suggests that miR-194-3p, miR-502-5p, and miR-23a-5p might participate in the nosogenesis of COPD. In addition, 4 potential small-molecule drugs were considered potentially useful for treating COPD patients.

Abstract 11102: Ginsenoside Rb2 Alleviated Atherosclerosis Progression by Inhibiting M1 Macrophages Polarization Induced by Microrna-216a

Background: It has been reported that microRNA-216a (miR-216a) advanced atherosclerosis progression by promoting macrophage polarization to M1 pro-inflammation phenotype. Ginsenoside Rb2 (Rb2) is the major pharmacologically active compound extracted from ginseng. Bioinformatics predicted that Rb2 had a high affinity with miR-216a. In the present study, we aimed to investigate the effect of Rb2 on macrophages in atherosclerosis progression induced by miR-216a. Methods: ApoE -/- mice with miR-216a adenovirus infection and Rb2 intraperitoneal injection were used to explore the effect of Rb2 on miR-216a-mediated atherosclerosis development in vivo. Oil red O, Hematoxylin-Eosin (HE) and Masson's trichrome staining were performed to assess the thoracic aortic plaque progression and stability. Immunohistochemical staining was used to detect the M1 macrophages in plaque. Furthermore, macrophages transfected with miR-216a and treatment with Rb2 were used to explore the mechanism of Rb2 on M1 polarization in vitro. Neutral red phagocytic experiment and cholesterol efflux assay were performed to assess the role of Rb2 in lipid accumulation of M1 macrophages. Results: The results in ApoE -/- mice showed that Rb2 alleviated miR-216a-mediated atherosclerosis lesion area by 33%, and promoted plaque stability with a lipid accumulation decrease by 55% and a collage content increase by 250%. We further observed that Rb2 inhibited M1 macrophages in plaque by 76%. Mechanistically, the data from macrophages revealed that Rb2 reserved miR-216a-mediated Smad3 and IκBα protein expression to inhibit NF-κB-responsive genes, including M1 maker monocyte chemotactic protein-1 (MCP1) and tumor necrosis factor alpha (TNFα), and Rb2 attenuated miR-216a-mediated lipid deposit in M1 macrophages by decreasing lipid uptake and promoting cholesterol efflux. Conclusion: Our results first time showed that Rb2 alleviated atherosclerosis progression and stability induced by miR-216a. By inhibiting M1 macrophage polarization through Smad3/IκBα, Rb2 decreases lipid accumulation and increases collage content increase in plaque. The Rb2 could serve as a potential small molecule drug for atherosclerosis associated M1 polarization.

The regulatory pattern of target gene expression by aberrant enhancer methylation in glioblastoma

BackgroundGlioblastoma multiforme (GBM) is the most common and aggressive primary malignant brain tumor with grim prognosis. Aberrant DNA methylation is an epigenetic mechanism that promotes GBM carcinogenesis, while the function of DNA methylation at enhancer regions in GBM remains poorly described.ResultsWe integrated multi-omics data to identify differential methylation enhancer region (DMER)-genes and revealed global enhancer hypomethylation in GBM. In addition, a DMER-mediated target genes regulatory network and functional enrichment analysis of target genes that might be regulated by hypomethylation enhancer regions showed that aberrant enhancer regions could contribute to tumorigenesis and progression in GBM. Further, we identified 22 modules in which lncRNAs and mRNAs synergistically competed with each other. Finally, through the construction of drug-target association networks, our study identified potential small-molecule drugs for GBM treatment.ConclusionsOur study provides novel insights for understanding the regulation of aberrant enhancer region methylation and developing methylation-based biomarkers for the diagnosis and treatment of GBM.

Identification and validation of tumor microenvironment-related lncRNA prognostic signature for uveal melanoma.

To investigate the role of tumor microenvironment (TME)-related long non-coding RNA (lncRNA) in uveal melanoma (UM), probable prognostic signature and potential small molecule drugs using bioinformatics analysis. UM expression profile data were downloaded from the Cancer Genome Atlas (TCGA) and bioinformatics methods were used to find prognostic lncRNAs related to UM immune cell infiltration. The gene expression profile data of 80 TCGA specimens were analyzed using the single sample Gene Set Enrichment Analysis (ssGSEA) method, and the immune cell infiltration of a single specimen was evaluated. Finally, the specimens were divided into high and low infiltration groups. The differential expression between the two groups was analyzed using the R package 'edgeR'. Univariate, multivariate and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analyses were performed to explore the prognostic value of TME-related lncRNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional analyses were also performed. The Connectivity Map (CMap) data set was used to screen molecular drugs that may treat UM. A total of 2393 differentially expressed genes were identified and met the criteria for the low and high immune cell infiltration groups. Univariate Cox analysis of lncRNA genes with differential expression identified 186 genes associated with prognosis. Eight prognostic markers of TME-included lncRNA genes were established as potentially independent prognostic elements. Among 269 differentially expressed lncRNAs, 69 were up-regulated and 200 were down-regulated. Univariate Cox regression analysis of the risk indicators and clinical characteristics of the 8 lncRNA gene constructs showed that age, TNM stage, tumor base diameter, and low and high risk indices had significant prognostic value. We screened the potential small-molecule drugs for UM, including W-13, AH-6809 and Imatinib. The prognostic markers identified in this study are reliable biomarkers of UM. This study expands our current understanding of the role of TME-related lncRNAs in UM genesis, which may lay the foundations for future treatment of this disease.

Quantitative Measurement of the Affinity of Toxic and Nontoxic Misfolded Protein Oligomers for Lipid Bilayers and of its Modulation by Lipid Composition and Trodusquemine.

Many neurodegenerative diseases are associated with the self-assembly of peptides and proteins into fibrillar aggregates. Soluble misfolded oligomers formed during the aggregation process, or released by mature fibrils, play a relevant role in neurodegenerative processes through their interactions with neuronal membranes. However, the determinants of the cytotoxicity of these oligomers are still unclear. Here we used liposomes and toxic and nontoxic oligomers formed by the same protein to measure quantitatively the affinity of the two oligomeric species for lipid membranes. To this aim, we quantified the perturbation to the lipid membranes caused by the two oligomers by using the fluorescence quenching of two probes embedded in the polar and apolar regions of the lipid membranes and a well-defined protein–oligomer binding assay using fluorescently labeled oligomers to determine the Stern–Volmer and dissociation constants, respectively. With both approaches, we found that the toxic oligomers have a membrane affinity 20–25 times higher than that of nontoxic oligomers. Circular dichroism, intrinsic fluorescence, and FRET indicated that neither oligomer type changes its structure upon membrane interaction. Using liposomes enriched with trodusquemine, a potential small molecule drug known to penetrate lipid membranes and make them refractory to toxic oligomers, we found that the membrane affinity of the oligomers was remarkably lower. At protective concentrations of the small molecule, the binding of the oligomers to the lipid membranes was fully prevented. Furthermore, the affinity of the toxic oligomers for the lipid membranes was found to increase and slightly decrease with GM1 ganglioside and cholesterol content, respectively, indicating that physicochemical properties of lipid membranes modulate their affinity for misfolded oligomeric species.

Novel Aptamer-Based Small-Molecule Drug Screening Assay to Identify Potential Sclerostin Inhibitors against Osteoporosis.

A novel aptamer-based competitive drug screening platform for osteoporosis was devised in which fluorescence-labeled, sclerostin-specific aptamers compete with compounds from selected chemical libraries for the binding of immobilized recombinant human sclerostin to achieve high-throughput screening for potential small-molecule sclerostin inhibitors and to facilitate drug repurposing and drug discovery. Of the 96 selected inhibitors and FDA-approved drugs, six were shown to result in a significant decrease in the fluorescence intensity of the aptamer, suggesting a higher affinity toward sclerostin compared with that of the aptamer. The targets of these potential sclerostin inhibitors were correlated to lipid or bone metabolism, and several of the compounds have already been shown to be potential osteogenic activators, indicating that the aptamer-based competitive drug screening assay offered a potentially reliable strategy for the discovery of target-specific new drugs. The six potential sclerostin inhibitors suppressed the level of both intracellular and/or extracellular sclerostin in mouse osteocyte IDG-SW3 and increased alkaline phosphatase activity in IDG-SW3 cells, human bone marrow-derived mesenchymal stem cells and human fetal osteoblasts hFOB1.19. Potential small-molecule drug candidates obtained in this study are expected to provide new therapeutics for osteoporosis as well as insights into the structure–activity relationship of sclerostin inhibitors for rational drug design.

Identification of a Novel Immune Landscape Signature for Predicting Prognosis and Response of Endometrial Carcinoma to Immunotherapy and Chemotherapy.

Uterine Corpus Endometrial Carcinoma (UCEC) is the most common gynecological cancer. Here, we have investigated the significance of immune-related genes in predicting the prognosis and response of UCEC patients to immunotherapy and chemotherapy. Based on the Cancer Genome Atlas (TCGA) database, the single-sample gene-set enrichment analysis (ssGSEA) scores was utilized to obtain enrichment of 29 immune signatures. Univariate, multivariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were performed to generate an immune-related prognostic signature (IRPS). The biological functions of IRPS-associated genes were evaluated using GSEA, Tumor Immune Estimation Resource (TIMER) Database analysis, Mutation analysis, Immunophenoscore (IPS) analysis, Gene Expression Profiling Interactive Analysis (GEPIA), Genomics of Drug Sensitivity in Cancer (GDSC) and Immune Cell Abundance Identifier (ImmuCellAI). Potential small molecule drugs for UCEC were predicted using the connectivity map (Cmap). The mRNA and protein expression levels of IRPS-associated genes were tested via quantitative real-time PCR (qPCR) and immunohistology. Two immune-related genes (CCL13 and KLRC1) were identified to construct the IRPS. Both genes were related to the prognosis of UCEC patients (P < 0.05). The IRPS could distinguish patients with different prognosis and was closely associated with the infiltration of several types of immune cells. Our findings showed that patients with low IRPS benefited more from immunotherapy and developed stronger response to several chemotherapies, which was also confirmed by the results of ImmuCellAI. Finally, we identified three small molecular drugs that might improve the prognosis of patients with high IRPS. IRPS can be utilized to predict the prognosis of UCEC patients and provide valuable information about their therapeutic response to immunotherapy and chemotherapy.

Emerging Gene and Small Molecule Therapies for the Neurodevelopmental Disorder Angelman Syndrome

Angelman syndrome (AS) is a rare (~1:15,000) neurodevelopmental disorder characterized by severe developmental delay and intellectual disability, impaired communication skills, and a high prevalence of seizures, sleep disturbances, ataxia, motor deficits, and microcephaly. AS is caused by loss-of-function of the maternally inherited UBE3A gene. UBE3A is located on chromosome 15q11–13 and is biallelically expressed throughout the body but only maternally expressed in the brain due to an RNA antisense transcript that silences the paternal copy. There is currently no cure for AS, but advancements in small molecule drugs and gene therapies offer a promising approach for the treatment of the disorder. Here, we review AS and how loss-of-function of the maternal UBE3A contributes to the disorder. We also discuss the strengths and limitations of current animal models of AS. Furthermore, we examine potential small molecule drug and gene therapies for the treatment of AS and associated challenges faced by the therapeutic design. Finally, gene therapy offers the opportunity for precision medicine in AS and advancements in the treatment of this disorder can serve as a foundation for other single-gene neurodevelopmental disorders.

Identification of potential core genes and pathways predicting pathogenesis in head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) is the most common subtype of head and neck cancer; however, its pathogenesis and potential therapeutic targets remain largely unknown. In the present study, we analyzed three gene expression profiles and screened differentially expressed genes (DEGs) between HNSCC and normal tissues. The DEGs were subjected to gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), protein–protein interaction (PPI), and survival analyses, while the connectivity map (CMap) database was used to predict candidate small molecules that may reverse the biological state of HNSCC. Finally, we measured the expression of the most relevant core gene in vitro and examined the effect of the top predicted potential drug against the proliferation of HNSCC cell lines. Among the 208 DEGs and ten hub genes identified, CDK1 and CDC45 were associated with unfavorable HNSCC prognosis, and three potential small molecule drugs for treating HNSCC were identified. Increased CDK1 expression was confirmed in HNSCC cells, and menadione, the top predicted potential drug, exerted significant inhibitory effects against HNSCC cell proliferation and markedly reversed CDK1 expression. Together, the findings of the present study suggest that the ten hub genes and pathways identified may be closely related to HNSCC pathogenesis. In particular, CDK1 and CDC45 overexpression could be reliable biomarkers for predicting unfavorable prognosis in patients with HNSCC, while the new candidate small molecules identified by CMap analysis provide new avenues for the development of potential drugs to treat HNSCC.

Integrated bioinformatics analysis reveals novel key biomarkers and potential candidate small molecule drugs in gestational diabetes mellitus.

Gestational diabetes mellitus (GDM) is the metabolic disorder that appears during pregnancy. The current investigation aimed to identify central differentially expressed genes (DEGs) in GDM. The transcription profiling by array data (E-MTAB-6418) was obtained from the ArrayExpress database. The DEGs between GDM samples and non-GDM samples were analyzed. Functional enrichment analysis were performed using ToppGene. Then we constructed the protein–protein interaction (PPI) network of DEGs by the Search Tool for the Retrieval of Interacting Genes database (STRING) and module analysis was performed. Subsequently, we constructed the miRNA–hub gene network and TF–hub gene regulatory network. The validation of hub genes was performed through receiver operating characteristic curve (ROC). Finally, the candidate small molecules as potential drugs to treat GDM were predicted by using molecular docking. Through transcription profiling by array data, a total of 869 DEGs were detected including 439 up-regulated and 430 down-regulated genes. Functional enrichment analysis showed these DEGs were mainly enriched in reproduction, cell adhesion, cell surface interactions at the vascular wall and extracellular matrix organization. Ten genes, HSP90AA1, EGFR, RPS13, RBX1, PAK1, FYN, ABL1, SMAD3, STAT3 and PRKCA were associated with GDM, according to ROC analysis. Finally, the most significant small molecules were predicted based on molecular docking. This investigation identified hub genes, signal pathways and therapeutic agents, which might help us, enhance our understanding of the mechanisms of GDM and find some novel therapeutic agents for GDM.