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An integrative analysis focused on multi-tissue transcriptomics has not been done for asthma. Tissue-specific DEGs remain undetected in many multi-tissue analyses, which influences identification of disease-relevant pathways and potential drug candidates. Transcriptome data from 609 cases and 196 controls, generated using airway epithelium, bronchial, nasal, airway macrophages, distal lung fibroblasts, proximal lung fibroblasts, CD4+ lymphocytes, CD8+ lymphocytes from whole blood and induced sputum samples, were retrieved from Gene Expression Omnibus (GEO). Differentially regulated asthma-relevant genes identified from each sample type were used to identify (a) tissue-specific and tissue–shared asthma pathways, (b) their connection to GWAS-identified disease genes to identify candidate tissue for functional studies, (c) to select surrogate sample for invasive tissues, and finally (d) to identify potential drug candidates via connectivity map analysis. We found that inter-tissue similarity in gene expression was more pronounced at pathway/functional level than at gene level with highest similarity between bronchial epithelial cells and lung fibroblasts, and lowest between airway epithelium and whole blood samples. Although public-domain gene expression data are limited by inadequately annotated per-sample demographic and clinical information which limited the analysis, our tissue-resolved analysis clearly demonstrated relative importance of unique and shared asthma pathways, At the pathway level, IL-1b signaling and ERK signaling were significant in many tissue types, while Insulin-like growth factor and TGF-beta signaling were relevant in only airway epithelial tissue. IL-12 (in macrophages) and Immunoglobulin signaling (in lymphocytes) and chemokines (in nasal epithelium) were the highest expressed pathways. Overall, the IL-1 signaling genes (inflammatory) were relevant in the airway compartment, while pro-Th2 genes including IL-13 and STAT6 were more relevant in fibroblasts, lymphocytes, macrophages and bronchial biopsies. These genes were also associated with asthma in the GWAS catalog. Support Vector Machine showed that DEGs based on macrophages and epithelial cells have the highest and lowest discriminatory accuracy, respectively. Drug (entinostat, BMS-345541) and genetic perturbagens (KLF6, BCL10, INFB1 and BAMBI) negatively connected to disease at multi-tissue level could potentially repurposed for treating asthma. Collectively, our study indicates that the DEGs, perturbagens and disease are connected differentially depending on tissue/cell types. While most of the existing literature describes asthma transcriptome data from individual sample types, the present work demonstrates the utility of multi-tissue transcriptome data. Future studies should focus on collecting transcriptomic data from multiple tissues, age and race groups, genetic background, disease subtypes and on the availability of better-annotated data in the public domain.

Although histone deacetylase 8 (HDAC8) plays a role in glioblastoma multiforme (GBM), whether its inhibition facilitates the treatment of temozolomide (TMZ)-resistant GBM (GBM-R) remains unclear. By assessing the gene expression profiles from short hairpin RNA of HDAC8 in the new version of Connectivity Map (CLUE) and cells treated by NBM-BMX (BMX)-, an HDAC8 inhibitor, data analysis reveals that the Wnt signaling pathway and apoptosis might be the underlying mechanisms in BMX-elicited treatment. This study evaluated the efficacy of cotreatment with BMX and TMZ in GBM-R cells. We observed that cotreatment with BMX and TMZ could overcome resistance in GBM-R cells and inhibit cell viability, markedly inhibit cell proliferation, and then induce cell cycle arrest and apoptosis. In addition, the expression level of β-catenin was reversed by proteasome inhibitor via the β-catenin/ GSK3β signaling pathway to reduce the expression level of c-Myc and cyclin D1 in GBM-R cells. BMX and TMZ cotreatment also upregulated WT-p53 mediated MGMT inhibition, thereby triggering the activation of caspase-3 and eventually leading to apoptosis in GBM-R cells. Moreover, BMX and TMZ attenuated the expression of CD133, CD44, and SOX2 in GBM-R cells. In conclusion, BMX overcomes TMZ resistance by enhancing TMZ-mediated cytotoxic effect by downregulating the β-catenin/c-Myc/SOX2 signaling pathway and upregulating WT-p53 mediated MGMT inhibition. These findings indicate a promising drug combination for precision personal treating of TMZ-resistant WT-p53 GBM cells.

Pharmacologic perturbation projects, such as Connectivity Map (CMap) and Library of Integrated Network-based Cellular Signatures (LINCS), have produced many perturbed expression data, providing enormous opportunities for computational therapeutic discovery. However, there is no consensus on which methodologies and parameters are the most optimal to conduct such analysis. Aiming to fill this gap, new benchmarking standards were developed to quantitatively evaluate drug retrieval performance. Investigations of potential factors influencing drug retrieval were conducted based on these standards. As a result, we determined an optimal approach for LINCS data-based therapeutic discovery. With this approach, homoharringtonine (HHT) was identified to be a candidate agent with potential therapeutic and preventive effects on liver cancer. The antitumor and antifibrotic activity of HHT was validated experimentally using subcutaneous xenograft tumor model and carbon tetrachloride (CCL 4 )-induced liver fibrosis model, demonstrating the reliability of the prediction results. In summary, our findings will not only impact the future applications of LINCS data but also offer new opportunities for therapeutic intervention of liver cancer.

Background: Diabetic nephropathy (DN) is one of the leading causes of chronic kidney disease (CKD) worldwide, tubular injury is the driving force during the pathogenesis and progression of DN. Thus, we aim to utilize the connectivity map (CMap) with renal tubulointerstitial transcriptomic profiles of biopsy-proven DN to identify novel drugs for treating DN. Methods: We interrogated the CMap profile with tubulointerstitial transcriptomic data from renal biopsy-proven early- and late-stage DN patients to screen potential drugs for DN. Therapeutic effects of candidate drug were assessed in Murine model of diabetic kidney disease (STZ-induced CD-1 mice), and HK-2 cells and immortalized bone marrow-derived macrophages (iBMDMs). Results: We identified CAY10603, a specific inhibitor of histone deacetylase 6 (HDAC6), as a potential drug that could significantly reverse the altered genes in the tubulointerstitial component. In DN patients and mice, upregulation of HDAC6 was mainly observed in renal tubular cells and infiltrated macrophages surrounding the diluted tubules. In both early- and late-onset diabetic mice, daily CAY10603 administration effectively alleviated renal dysfunction and reduced macrophage infiltration, tubular injury and tubulointerstitial fibrosis. Mechanistically, CAY10603 suppressed NLRP3 activation in both HK-2 cells and iBMDMs. Conclusion: CAY10603 exhibited therapeutic potential for DN by suppressing NLRP3 inflammasome activation in both tubular cells and macrophages.

Berberine (BBR) is used to treat diarrhoea and gastroenteritis in the clinic. It was found to have anticolon cancer effects. To study the anticolon cancer mechanism of BBR by connectivity map (CMAP) analysis. CMAP based mechanistic prediction was conducted by comparing gene expression profiles of 10 μM BBR treated MCF-7 cells with that of clinical drugs such as helveticoside, ianatoside C, pyrvinium, gossypol and trifluoperazine. The treatment time was 12 h and two biological replications were performed. The DMSO-treated cells were selected as a control. The interaction between 100 μM BBR and target protein was measured by cellular thermal shift assay. The protein expression of 1-9 μM BBR treated SW480 cells were measured by WB assay. Apoptosis, cell cycle arrest, mitochondrial membrane potential (MMP) of 1-9 μM BBR treated SW480 cells were measured by flow cytometry and Hoechst 33342 staining methods. CMAP analysis found 14 Hsp90, HDAC, PI3K or mTOR protein inhibitors have similar functions with BBR. The experiments showed that BBR inhibited SW480 cells proliferation with IC 50 of 3.436 μM, induced apoptosis, autophage, MMP depolarization and arrested G1 phase of cell cycle at 1.0 μM. BBR dose-dependently up-regulated PTEN, while inhibited Notch1, PI3K, Akt and mTOR proteins at 1.0-9.0 μM (p < 0.05). BBR also acted synergistically with Hsp90 and HDAC inhibitor (0.01 μM) in SW480 cells at 0.5 and 1.0 μM. The integrative gene expression-based chemical genomic method using CMAP analysis may be applicable for mechanistic studies of other multi-targets drugs.

Most human cancers develop from stem and progenitor cell populations through the sequential accumulation of various genetic and epigenetic alterations. Cancer stem cells have been identified from medulloblastoma (MB), but a comprehensive understanding of MB stemness, including the interactions between the tumor immune microenvironment and MB stemness, is lacking. Here, we employed a trained stemness index model based on an existent one‐class logistic regression (OCLR) machine‐learning method to score MB samples; we then obtained two stemness indices, a gene expression‐based stemness index (mRNAsi) and a DNA methylation‐based stemness index (mDNAsi), to perform an integrated analysis of MB stemness in a cohort of primary cancer samples (n = 763). We observed an inverse trend between mRNAsi and mDNAsi for MB subgroup and metastatic status. By applying the univariable Cox regression analysis, we found that mRNAsi significantly correlated with overall survival (OS) for all MB patients, whereas mDNAsi had no significant association with OS for all MB patients. In addition, by combining the Lasso‐penalized Cox regression machine‐learning approach with univariate and multivariate Cox regression analyses, we identified a stemness‐related gene expression signature that accurately predicted survival in patients with Sonic hedgehog (SHH) MB. Furthermore, positive correlations between mRNAsi and prognostic copy number aberrations in SHH MB, including MYCN amplifications and GLI2 amplifications, were detected. Analyses of the immune microenvironment revealed unanticipated correlations of MB stemness with infiltrating immune cells. Lastly, using the Connectivity Map, we identified potential drugs targeting the MB stemness signature. Our findings based on stemness indices might advance the development of objective diagnostic tools for quantitating MB stemness and lead to novel biomarkers that predict the survival of patients with MB or the efficacy of strategies targeting MB stem cells. Here, we employed a trained stemness index model to perform an integrated analysis of medulloblastoma (MB) stemness. By combining the Lasso‐penalized Cox regression with univariate and multivariate Cox regression analyses, we identified a stemness‐related gene expression signature. Furthermore, positive correlations between gene expression‐based stemness index and prognostic copy number aberrations were detected. Analyses of the immune microenvironment revealed unanticipated correlations of MB stemness with infiltrating immune cells. Lastly, using the Connectivity Map, we identified potential drugs targeting the MB stemness signature.

Amid the establishment and optimization of Connectivity Map (CMAP), the functional relationships among drugs, genes, and diseases are further explored. This biological database has been widely used to identify drugs with common mechanisms, repurpose existing drugs, discover the molecular mechanisms of unknown drugs, and find potential drugs for some diseases. Research on traditional Chinese medicine (TCM) has entered a new era in the wake of the development of bioinformatics and other subjects including network pharmacology, proteomics, metabolomics, herbgenomics, and so on. TCM gradually conforms to modern science, but there is still a torrent of limitations. In recent years, CMAP has shown its distinct advantages in the study of the components of TCM and the synergetic mechanism of TCM formulas; hence, the combination of them is inevitable.

Osteoporosis is a common skeletal disorder characterized by low bone mass leading to increased bone fragility and fracture susceptibility. In this study, we have identified pathways that stimulate differentiation of bone forming osteoblasts from human mesenchymal stromal cells (hMSCs). Gene expression profiling was performed in hMSCs differentiated toward osteoblasts (at 6 h). Significantly regulated genes were analyzed in silico, and the Connectivity Map (CMap) was used to identify candidate bone stimulatory compounds. The signature of parbendazole matches the expression changes observed for osteogenic hMSCs. Parbendazole stimulates osteoblast differentiation as indicated by increased alkaline phosphatase activity, mineralization, and up-regulation of bone marker genes (alkaline phosphatase/ALPL,osteopontin/SPP1,and bone sialoprotein II/IBSP) in a subset of the hMSC population resistant to the apoptotic effects of parbendazole. These osteogenic effects are independent of glucocorticoids because parbendazole does not up-regulate glucocorticoid receptor (GR) target genes and is not inhibited by the GR antagonist mifepristone. Parbendazole causes profound cytoskeletal changes including degradation of microtubules and increased focal adhesions. Stabilization of microtubules by pretreatment with Taxol inhibits osteoblast differentiation. Parbendazole up-regulates bone morphogenetic protein 2 (BMP-2) gene expression and activity. Cotreatment with the BMP-2 antagonist DMH1 limits, but does not block, parbendazole-induced mineralization. Using the CMap we have identified a previously unidentified lineage-specific, bone anabolic compound, parbendazole, which induces osteogenic differentiation through a combination of cytoskeletal changes and increased BMP-2 activity.

Aging is the largest risk factor for a variety of noncommunicable diseases. Model organism studies have shown that genetic and chemical perturbations can extend both lifespan and healthspan. Aging is a complex process, with parallel and interacting mechanisms contributing to its aetiology, posing a challenge for the discovery of new pharmacological candidates to ameliorate its effects. In this study, instead of a target‐centric approach, we adopt a systems level drug repurposing methodology to discover drugs that could combat aging in human brain. Using multiple gene expression data sets from brain tissue, taken from patients of different ages, we first identified the expression changes that characterize aging. Then, we compared these changes in gene expression with drug‐perturbed expression profiles in the Connectivity Map. We thus identified 24 drugs with significantly associated changes. Some of these drugs may function as antiaging drugs by reversing the detrimental changes that occur during aging, others by mimicking the cellular defence mechanisms. The drugs that we identified included significant number of already identified prolongevity drugs, indicating that the method can discover de novo drugs that meliorate aging. The approach has the advantages that using data from human brain aging data, it focuses on processes relevant in human aging and that it is unbiased, making it possible to discover new targets for aging studies.

Although many chemopreventive studies on colorectal tumors have been reported, no effective and safe preventive agent is currently available. We searched for candidate preventive compounds against colorectal tumor comprehensively from United States Food and Drug Administration (FDA)‐approved compounds by using connectivity map (CMAP) analysis coupled with in vitro screening with colorectal adenoma (CRA) patient‐derived organoids (PDOs). We generated CRA‐specific gene signatures based on the DNA microarray analysis of CRA and normal epithelial specimens, applied them to CMAP analysis with 1309 FDA‐approved compounds, and identified 121 candidate compounds that should cancel the gene signatures. We narrowed them down to 15 compounds, and evaluated their inhibitory effects on the growth of CRA‐PDOs in vitro. We finally identified resveratrol, one of the polyphenolic phytochemicals, as a compound showing the strongest inhibitory effect on the growth of CRA‐PDOs compared with normal epithelial PDOs. When resveratrol was administered to ApcMin/+ mice at 15 or 30 mg/kg, the number of polyps (adenomas) was significantly reduced in both groups compared with control mice. Similarly, the number of polyps (adenomas) was significantly reduced in azoxymethane‐injected rats treated with 10 or 100 mg/resveratrol compared with control rats. Microarray analysis of adenomas from resveratrol‐treated rats revealed the highest change (downregulation) in expression of LEF1, a key molecule in the Wnt signaling pathway. Treatment with resveratrol significantly downregulated the Wnt‐target gene (MYC) in CRA‐PDOs. Our data demonstrated that resveratrol can be the most effective compound for chemoprevention of colorectal tumors, the efficacy of which is mediated through suppression of LEF1 expression in the Wnt signaling pathway. Resveratrol was identified as the most effective compound for chemoprevention against colorectal adenoma comprehensively from 1309 FDA‐approved compounds using connectivity map analysis and in vitro screening of patient‐derived organoids of colorectal adenoma. Resveratrol effectively inhibited development of colorectal adenoma in Apc‐deficient mice and in chemically carcinogenesis rat models by suppressing the expression of LEF1 in the Wnt signaling pathway.