Identification of Pyrvinium, an Anthelmintic Drug, as a Novel Anti-Adipogenic Compound Based on the Gene Expression Microarray and Connectivity Map

The Role and Mechanism of Action of Mitophagy in Various Liver Diseases

Significance: Liver disease is one of the biggest threats to public health, affecting as much as 5.5 million people worldwide. Mitochondrial dysfunction is associated with various acute and chronic liver diseases. Mitophagy, a selective form of autophagy for damaged/excessive mitochondria, plays a key role either in the pathogenesis or in maintaining hepatic homeostasis in response to various liver diseases. Recent Advances: Significant progress has been achieved to ascertain the causes of liver disease. The conserved pathways for mitochondrial degradation via mitophagy, the deregulation of mitophagy in liver diseases, and pharmacological or genetic maneuvers that alter the mitophagic flux for liver disease treatment have been widely studied but yet to be comprehensively reviewed. Critical Issues: Liver disease is considered a leading cause of mortality globally, causing the heavy burden of disability and the increased health care utilization that needs to be settled urgently. Mitophagy plays an important role in protecting liver from tissue damage to maintain hepatic homeostasis or in pathogenesis of liver disease. Elaborating mitophagy implicated in the pathogenesis of liver disease, as well as potential therapeutic regimens by targeting mitophagy is of great significance for the understanding and treatment of liver disease. Future Directions: This review comprehensively describes the distinct mitophagy signaling pathways and their interplay with various liver diseases. Given that mitophagy affects a wide array of physiological processes, a deeper understanding of how to modulate mitophagy could provide innovative avenues for precise therapy. Future studies based on pharmacologically or genetically targeting mitophagy-relevant factors will uncover the links between intact mitophagic responses and hepatic homeostasis in physiological and pathological settings. This will allow us to overcome obstacles of applying mitophagy as the therapeutic target in the clinic. Antioxid. Redox Signal. 38, 529-549.

Predicting Novel Drug Candidates for Pancreatic Neuroendocrine Tumors via Gene Signature Comparison and Connectivity Mapping

INTRODUCTION

There is a paucity of effective treatment options for advanced pancreatic neuroendocrine tumors (pNETs). Genome-wide analyses may allow for potential drugs to be identified based on differentially expressed genes (DEGs).

METHODS

Oligo microarray data of RNA expression profiling of pNETs and normal pancreas tissues were downloaded from the Gene Expression Omnibus. Functional and pathway enrichment information of the DEGs was obtained using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. Corresponding homologous proteins were analyzed and potential therapeutic drugs for pNETs were identified using the Connectivity Map and Drug-Gene Interaction Database.

RESULTS

Assessment of raw data from 12,610 pNET genes demonstrated that 1082 and 380 genes were upregulated and downregulated, respectively, compared with normal pancreas tissue. Upregulated pathways were associated with nitrogen metabolism (i.e., GABAergic synapse, and graft-versus-host disease), whereas downregulated pathways included C-type leptin receptor signaling pathway, pertussis and AMPK signaling pathway. In particular, the protein-protein interaction analysis revealed 10 upregulated hub genes (DYNLL1, GNB5, GNB2, GNG4, GNAI2, GNAI1, HIST2H2BE, NUP107, NUP133, and SNAP25) and 10 downregulated hub genes (CXCL8, F2, CXCL2, GCG, SST, INS, GALR3, CCL20, ADRA2B, and CXCL6). Using the Drug-Gene Interaction Database, candidate drugs for pNETs treatment included 3 EGFR inhibitors (canertinib, erlotinib, WZ-4-145), as well as other cell-signaling pathway inhibitors such as AG-592, acarbose, lonidamine, azacytidine, rottlerin, and HU-211.

CONCLUSION

Using available genetic atlas data, potential drug candidates for treatment of pNETs were identified based on differentially expressed genes. These results may help focus efforts on identifying targeted agents with therapeutic efficacy to treat patients with pNETs.

Identification of small molecules as novel anti-adipogenic compounds based on Connectivity Map

Several physiological and pathological conditions such as aging, obesity, diabetes, anorexia nervosa are associated with increased adipogenesis in the bone marrow. A lack of effective drugs hinder the improved treatment for aberrant accumulation of bone marrow adipocytes. Given the higher costs, longer duration and sometimes lack of efficacy in drug discovery, computational and experimental strategies have been used to identify previously approved drugs for the treatment of diseases, also known as drug repurposing. Here, we describe the method of small molecule-prioritization by employing adipocyte-specific genes using the connectivity map (CMap). We then generated transcriptomic profiles using human mesenchymal stromal cells under adipogenic differentiation with the treatment of prioritized compounds, and identified emetine and kinetin-riboside to have a potent inhibitory effect on adipogenesis. Overall, we demonstrated a proof-of-concept method to identify repurposable drugs capable of inhibiting adipogenesis, using the Connectivity Map.

Pyrvinium pamoate regulates MGMT expression through suppressing the Wnt/β-catenin signaling pathway to enhance the glioblastoma sensitivity to temozolomide

Temozolomide (TMZ) is the mainstream chemotherapeutic drug for treating glioblastoma multiforme (GBM), but the intrinsic or acquired chemoresistance to TMZ has become the leading clinical concern, which is related to the repair of DNA alkylation sites by O⁶-methylguanine-DNA methyltransferase (MGMT). Pyrvinium pamoate (PP), the FDA-approved anthelminthic drug, has been reported to inhibit the Wnt/β-catenin pathway within numerous cancer types, and Wnt/β-catenin signaling pathway can modulate the expression of MGMT gene. However, whether PP affects the expression of MGMT and enhances TMZ sensitivity in GBM cells remains unclear. In the present study, we found that PP and TMZ had synergistic effect on inhibiting the viability of GBM cells, and PP induced inhibition of MGMT and enhanced the TMZ chemosensitivity of GBM cells through down-regulating Wnt/β-catenin pathway. Moreover, the overexpression of MGMT or β-catenin weakened the synergy between PP and TMZ. The mechanism of PP in inhibiting the Wnt pathway was indicated that PP resulted in the degradation of β-catenin via the AKT/GSK3β/β-catenin signaling axis. Moreover, Ser552 phosphorylation in β-catenin, which promotes its nuclear accumulation and transcriptional activity, is blocked by PP that also inhibits the Wnt pathway to some extent. The intracranial GBM mouse model also demonstrated that the synergy between PP and TMZ could be achieved through down-regulating β-catenin and MGMT, which prolonged the survival time of tumor-bearing mice. Taken together, our data suggest that PP may serve as the prospect medicine to improve the chemotherapeutic effect on GBM, especially for chemoresistant to TMZ induced by MGMT overexpression.

Evaluation of connectivity map shows limited reproducibility in drug repositioning

The Connectivity Map (CMap) is a popular resource designed for data-driven drug repositioning using a large transcriptomic compendium. However, evaluations of its performance are limited. We used two iterations of CMap (CMap 1 and 2) to assess their comparability and reliability. We queried CMap 2 with CMap 1-derived signatures, expecting CMap 2 would highly prioritize the queried compounds; the success rate was 17%. Analysis of previously published prioritizations yielded similar results. Low recall is caused by low differential expression (DE) reproducibility both between CMaps and within each CMap. DE strength was predictive of reproducibility, and is influenced by compound concentration and cell-line responsiveness. Reproducibility of CMap 2 sample expression levels was also lower than expected. We attempted to identify the "better" CMap by comparison with a third dataset, but they were mutually discordant. Our findings have implications for CMap usage and we suggest steps for investigators to limit false positives.

The FDA-Approved Anthelmintic Pyrvinium Pamoate Inhibits Pancreatic Cancer Cells in Nutrient-Depleted Conditions by Targeting the Mitochondria

Pancreatic ductal adenocarcinoma (PDAC) is a lethal aggressive cancer, in part due to elements of the microenvironment (hypoxia, hypoglycemia) that cause metabolic network alterations. The FDA-approved antihelminthic pyrvinium pamoate (PP) has previously been shown to cause PDAC cell death, although the mechanism has not been fully determined. We demonstrated that PP effectively inhibited PDAC cell viability with nanomolar IC50 values (9-93 nmol/L) against a panel of PDAC, patient-derived, and murine organoid cell lines. In vivo, we demonstrated that PP inhibited PDAC xenograft tumor growth with both intraperitoneal (IP; P < 0.0001) and oral administration (PO; P = 0.0023) of human-grade drug. Metabolomic and phosphoproteomic data identified that PP potently inhibited PDAC mitochondrial pathways including oxidative phosphorylation and fatty acid metabolism. As PP treatment reduced oxidative phosphorylation (P < 0.001), leading to an increase in glycolysis (P < 0.001), PP was 16.2-fold more effective in hypoglycemic conditions similar to those seen in PDAC tumors. RNA sequencing demonstrated that PP caused a decrease in mitochondrial RNA expression, an effect that was not observed with established mitochondrial inhibitors rotenone and oligomycin. Mechanistically, we determined that PP selectively bound mitochondrial G-quadruplexes and inhibited mitochondrial RNA transcription in a G-quadruplex-dependent manner. This subsequently led to a 90% reduction in mitochondrial encoded gene expression. We are preparing to evaluate the efficacy of PP in PDAC in an IRB-approved window-of-opportunity trial (IND:144822).

Salidroside promoted osteogenic differentiation of adipose-derived stromal cells through Wnt/β-catenin signaling pathway

BACKGROUND

Bone disease causes short-term or long-term physical pain and disability. It is necessary to explore new drug for bone-related disease. This study aimed to explore the role and mechanism of Salidroside in promoting osteogenic differentiation of adipose-derived stromal cells (ADSCs).

METHODS

ADSCs were isolated and treated with different dose of Salidroside. Cell count kit-8 (CCK-8) assay was performed to assess the cell viability of ADSCs. Then, ALP and ARS staining were conducted to assess the early and late osteogenic capacity of ADSCs, respectively. Then, differentially expressed genes were obtained by R software. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the differentially expressed genes were further analyzed. The expression of OCN, COL1A1, RUNX2, WNT3A, and β-catenin were measured by real-time PCR and Western blot analysis. Last, β-catenin was silenced by small interfering RNA.

RESULTS

Salidroside significantly increased the ADSCs viability at a dose-response manner. Moreover, Salidroside enhanced osteogenic capacity of ADSCs, which are identified by enhanced ALP activity and calcium deposition. A total of 543 differentially expressed genes were identified between normal and Salidroside-treated ADSCs. Among these differentially expressed genes, 345 genes were upregulated and 198 genes were downregulated. Differentially expressed genes enriched in the Wnt/β-catenin signaling pathway. Western blot assay indicated that Salidroside enhanced the WNT3A and β-catenin expression. Silencing β-catenin partially reversed the promotion effects of Salidroside. PCR and Western blot results further confirmed these results.

CONCLUSION

Salidroside promoted osteogenic differentiation of ADSCs through Wnt/β-catenin signaling pathway.

Murine in vitro cellular models to better understand adipogenesis and its potential applications

Adipogenesis has been extensively studied using in vitro models of cellular differentiation, enabling long-term regulation of fat cell metabolism in human adipose tissue (AT) material. Many studies promote the idea that manipulation of this process could potentially reduce the prevalence of obesity and its related diseases. It has now become essential to understand the molecular basis of fat cell development to tackle this pandemic disease, by identifying therapeutic targets and new biomarkers. This review explores murine cell models and their applications for study of the adipogenic differentiation process in vitro. We focus on the benefits and limitations of different cell line models to aid in interpreting data and selecting a good cell line model for successful understanding of adipose biology.

Potential Molecular Mechanisms and Drugs for Aconitine-Induced Cardiotoxicity in Zebrafish through RNA Sequencing and Bioinformatics Analysis

Background

Accumulating evidence suggests that cardiotoxicity is one of the main manifestations of aconitine (AC) poisoning. However, the molecular mechanism of AC-induced cardiotoxicity remains unclear, there is little direct evidence for therapeutic targets and drugs of AC-induced cardiotoxicity.

Material/Methods

Zebrafish were exposed to AC to evaluate cardiotoxicity by calculating the heart rates and observing the changes of cardiac and vascular structure. RNA-seq (RNA sequencing) and bioinformatics analysis were used to obtain differentially expressed genes (DEGs). The anti-AC cardiotoxicity compound was identified via connectivity map (CMAP) analysis and molecular docking.

Results

AC-induced cardiotoxicity in zebrafish predominantly included arrhythmias, extended sinus venous and bulbus arteriosus (SV-BA) distance, and larger pericardial edema aera. A total of 1380 DEGs were identified by RNA-seq and bioinformatics analysis. cyclin-dependent kinase-1 (CDK1) was screened as the hub gene and the most potential therapeutic target due to its significant downregulation in cardiotoxicity based on protein-protein interaction (PPI) and drug-gene interaction (DGIdb) network analysis. Cell cycle signal pathway was the most significant pathways identified in the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Furthermore, the expression of CDK1 was validated in the Gene Expression Omnibus (GEO) database GSE71906, GSE65705, and GSE95140. Finally, heptaminol was identified as a novel anti-AC cardiotoxicity compound via CMAP analysis and molecular docking.

Conclusions

Totally, hub genes and key pathways identified in this study can aid in the understanding of the molecular changes in AC-induced cardiotoxicity. Meanwhile, we provide a systematic method to explore drug toxicity prevention and treatment.

Identifying drug candidates for hepatocellular carcinoma based on differentially expressed genes

The prognosis for patients with advanced hepatocellular carcinoma (HCC) is extremely poor, mainly due to rapid progression and a paucity of effective drugs. Genome-wide analysis allows for potential drugs to be explored based on differentially expressed genes (DEGs). However, drug candidates and DEGs in HCC are largely unknown. In this study, we investigated DEGs and prognostication using The Cancer Genome Atlas (TCGA), the International Cancer Genome Consortium (ICGC), the Gene Expression Omnibus (GEO), and immunohistochemical staining. Protein-protein interaction networks between DEGs were also analyzed to clarify 12 hub genes and query online databases for potential HCC therapeutic drugs. We found that 885 of 3219 DEGs from a TCGA dataset were associated with prognosis. We clarified 12 hub genes that were overexpressed in tumor samples and significantly associated with poor overall survival (OS) in HCC patients. These findings were validated using GEO and ICGC cohorts. Moreover, promising drug candidates targeted against HCC were predicted using online databases. Collectively, the upregulation of 12 hub genes was associated with poor prognosis for patients with HCC, and focusing on their expression may advance efforts towards targeted HCC therapies.

High-Throughput Transcriptome Profiling in Drug and Biomarker Discovery

The development of new drugs is multidisciplinary and systematic work. High-throughput techniques based on “-omics” have driven the discovery of biomarkers in diseases and therapeutic targets of drugs. A transcriptome is the complete set of all RNAs transcribed by certain tissues or cells at a specific stage of development or physiological condition. Transcriptome research can demonstrate gene functions and structures from the whole level and reveal the molecular mechanism of specific biological processes in diseases. Currently, gene expression microarray and high-throughput RNA-sequencing have been widely used in biological, medical, clinical, and drug research. The former has been applied in drug screening and biomarker detection of drugs due to its high throughput, fast detection speed, simple analysis, and relatively low price. With the further development of detection technology and the improvement of analytical methods, the detection flux of RNA-seq is much higher but the price is lower, hence it has powerful advantages in detecting biomarkers and drug discovery. Compared with the traditional RNA-seq, scRNA-seq has higher accuracy and efficiency, especially the single-cell level of gene expression pattern analysis can provide more information for drug and biomarker discovery. Therefore, (sc)RNA-seq has broader application prospects, especially in the field of drug discovery. In this overview, we will review the application of these technologies in drug, especially in natural drug and biomarker discovery and development. Emerging applications of scRNA-seq and the third generation RNA-sequencing tools are also discussed.

Cellular Stress-Modulating Drugs Can Potentially Be Identified by in Silico Screening with Connectivity Map (CMap)

Accompanied by increased life span, aging-associated diseases, such as metabolic diseases and cancers, have become serious health threats. Recent studies have documented that aging-associated diseases are caused by prolonged cellular stresses such as endoplasmic reticulum (ER) stress, mitochondrial stress, and oxidative stress. Thus, ameliorating cellular stresses could be an effective approach to treat aging-associated diseases and, more importantly, to prevent such diseases from happening. However, cellular stresses and their molecular responses within the cell are typically mediated by a variety of factors encompassing different signaling pathways. Therefore, a target-based drug discovery method currently being used widely (reverse pharmacology) may not be adequate to uncover novel drugs targeting cellular stresses and related diseases. The connectivity map (CMap) is an online pharmacogenomic database cataloging gene expression data from cultured cells treated individually with various chemicals, including a variety of phytochemicals. Moreover, by querying through CMap, researchers may screen registered chemicals in silico and obtain the likelihood of drugs showing a similar gene expression profile with desired and chemopreventive conditions. Thus, CMap is an effective genome-based tool to discover novel chemopreventive drugs.