DrugR+: A comprehensive relational database for drug repurposing, combination therapy, and replacement therapy.

Comput Biol Med. 2019 May 08;109:254-262

Authors: Masoudi-Sobhanzadeh Y, Omidi Y, Amanlou M, Masoudi-Nejad A

Abstract
Drug repurposing or repositioning, which introduces new applications of the existing drugs, is an emerging field in drug discovery scope. To enhance the success rate of the research and development (R&D) process in a cost- and time-effective manner, a number of pharmaceutical companies worldwide have made tremendous investments. Besides, many researchers have proposed various methods and databases for the repurposing of various drugs. However, there is not a proper and well-organized database available. To this end, for the first time, we developed a new database based on DrugBank and KEGG data, which is named "DrugR+". Our developed database provides some advantages relative to the DrugBank, and its interface supplies new capabilities for both single and synthetic repositioning of drugs. Moreover, it includes four new datasets which can be used for predicting drug-target interactions using supervised machine learning methods. As a case study, we introduced novel applications of some drugs and discussed the obtained results. A comparison of several machine learning methods on the generated datasets has also been reported in the Supplementary File. Having included several normalized tables, DrugR + has been organized to provide key information on data structures for the repurposing and combining applications of drugs. It provides the SQL query capability for professional users and an appropriate method with different options for unprofessional users. Additionally, DrugR + consists of repurposing service that accepts a drug and proposes a list of potential drugs for some usages. Taken all, DrugR+ is a free web-based database and accessible using (http://www.drugr.ir), which can be updated through a map-reduce parallel processing method to provide the most relevant information.

PMID: 31096089 [PubMed - as supplied by publisher]

17-hydroxy wortmannin restores TRAIL's response by ameliorating increased beclin 1 level and autophagy function in TRAIL-resistant colon cancer cells.

Mol Cancer Ther. 2019 May 15;:

Authors: Dai S, Yang S, Hu X, Sun W, Tawa G, Zhu W, Schimmer AD, He C, Fang B, Zhu H, Zheng W

Abstract
Targeting of extrinsic apoptosis pathway by TNF related apoptosis-inducing ligand (TRAIL) is an attractive approach for cancer therapy. However, two TRAIL drug candidates failed in clinical trials due to lack of efficacy. We identified 17-hydroxy wortmannin (17-HW) in a drug repurposing screen that re-sensitized TRAIL's response in the resistant colon cancer cells. The deficiency of caspase-8 in drug-resistant cells along with defects in apoptotic cell death was corrected by 17-HW, an inhibitor of PIK3C3-beclin 1 (BECN1) complex and autophagy activity. Further study found that BECN1 significantly increased in the TRAIL-resistant cells, resulting in increased autophagosome formation and enhanced autophagy flux. The extracellular domain (ECD) of BECN1 directly bound to the caspase-8 catalytic subunit (p10), leading to sequestration of caspase-8 in the autophagosome and its subsequent degradation. Inhibition of BECN1 restored the caspase-8 level and TRAIL's apoptotic response in the resistant colon cancer cells. An analysis of 120 colon cancer patient tissues revealed a correlation of a subgroup of patients (30.8%, 37/120) who have high BECN1 level and low caspase-8 level with a poor survival rate. Our study demonstrates that the increased BECN1 accompanied by enhanced autophagy activity is responsible for the TRAIL resistance, and a combination of TRAIL with a PIK3C3-BECN1 inhibitor is a promising therapeutic approach for the treatment of colon cancer.

PMID: 31092562 [PubMed - as supplied by publisher]

Chromatin interactions reveal novel gene targets for drug repositioning in rheumatic diseases.

Ann Rheum Dis. 2019 May 15;:

Authors: Martin P, Ding J, Duffus K, Gaddi VP, McGovern A, Ray-Jones H, Yarwood A, Worthington J, Barton A, Orozco G

Abstract
OBJECTIVES: There is a need to identify effective treatments for rheumatic diseases, and while genetic studies have been successful it is unclear which genes contribute to the disease. Using our existing Capture Hi-C data on three rheumatic diseases, we can identify potential causal genes which are targets for existing drugs and could be repositioned for use in rheumatic diseases.
METHODS: High confidence candidate causal genes were identified using Capture Hi-C data from B cells and T cells. These genes were used to interrogate drug target information from DrugBank to identify existing treatments, which could be repositioned to treat these diseases. The approach was refined using Ingenuity Pathway Analysis to identify enriched pathways and therefore further treatments relevant to the disease.
RESULTS: Overall, 454 high confidence genes were identified. Of these, 48 were drug targets (108 drugs) and 11 were existing therapies used in the treatment of rheumatic diseases. After pathway analysis refinement, 50 genes remained, 13 of which were drug targets (33 drugs). However considering targets across all enriched pathways, a further 367 drugs were identified for potential repositioning.
CONCLUSION: Capture Hi-C has the potential to identify therapies which could be repositioned to treat rheumatic diseases. This was particularly successful for rheumatoid arthritis, where six effective, biologic treatments were identified. This approach may therefore yield new ways to treat patients, enhancing their quality of life and reducing the economic impact on healthcare providers. As additional cell types and other epigenomic data sets are generated, this prospect will improve further.

PMID: 31092410 [PubMed - as supplied by publisher]

[Anti-platelet aggregation and anti-thrombotic mechanism of Trichosanthis Fructus combined with aspirin based on network pharmacology].

Zhongguo Zhong Yao Za Zhi. 2019 Apr;44(8):1654-1659

Authors: Zou CC, Yan HY, Wang LL, Bian YY

Abstract
To explore the anti-platelet aggregation and anti-thrombotic mechanisms of Trichosanthis Fructus combined with aspirin based on network pharmacology and the validation of arteriovenous by pass model in rats. The databases of Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP),Drug Repositioning and Adverse Drug Reaction Chemical-Protein Interactome(DRAR-CPI),Universal Protein Resource(Uniprot) and the Database for Annotation,Visualization,and Integrated Discovery(DAVID) were used to predict protein targets and analyze biological pathway and signal pathway in the combination of Trichosanthis Fructus with aspirin. The effects of pretreatment with Trichosanthis Fructus pellets,aspirin pellets and their combination on thromboxane B2(TXB2),6-keto prostaglandin F1α(6-keto-PGF1α) and cyclic adenosine monophosphate(c AMP) in rat thrombotic model were studied. Through the study of network pharmacology,12 components of aspirin and Trichosanthis Fructus,including hydroxygenkwanin,quercetin and adenosine,were found to show the anti-platelet aggregation and anti-thrombosis mechanisms through9 common protein targets,such as SRC,RAC1,MAPK14,MAPK1,AKT1,and 14 common signaling pathways,such as VEGF signaling pathway. After the intervention with Trichosanthis Fructus pellets combined with aspirin pellets,the vascular endothslia growth factor(VEGF) signaling pathway can be activated to inhibit platelet aggregation and improve vascular endothelial function,and show the anti-platelet aggregation and anti-thrombosis mechanisms,which verify the results of the network pharmacology,and explain the anti-platelet aggregation and anti-thrombotic mechanisms of the combination of Trichosanthis Fructus pellets with aspirin pellets.

PMID: 31090331 [PubMed - in process]

Evaluation of emodepside in laboratory models of human intestinal nematode and schistosome infections.

Parasit Vectors. 2019 May 14;12(1):226

Authors: Karpstein T, Pasche V, Häberli C, Scandale I, Neodo A, Keiser J

Abstract
BACKGROUND: Helminthiases are very prevalent worldwide, yet their treatment and control rely on a handful of drugs. Emodepside, a marketed broad-spectrum veterinary anthelminthic with a unique mechanism of action, undergoing development for onchocerciasis is an interesting anthelmintic drug candidate. We tested the in vitro and in vivo activity of emodepside on nematode species that serve as models for human soil-transmitted helminth infection as well as on schistosomes.
METHODS: In vitro viability assays were performed over a time course of 72 hours for Trichuris muris, Necator americanus, Ancylostoma ceylanicum, Heligmosomoides polygyrus, Strongyloides ratti, Schistosoma mansoni and Schistosoma haematobium. The drug effect was determined by the survival rate for the larvae and by phenotypical scores for the adult worms. Additionally, mice infected with T. muris and hamsters harboring hookworm infection (N. americanus or A. ceylanicum) were administered orally with emodepside at doses ranging from 1.25 to 75 mg/kg. Expelled worms in the feces were counted until 3 days post-drug intake and worms residing in the intestines were collected and counted after dissection.
RESULTS: After 24 hours, emodepside was very active in vitro against both larval and adult stages of the nematodes T. muris, A. ceylanicum, N. americanus, H. polygyrus and S. ratti (IC50 < 4 µM). The good in vitro activity was confirmed in vivo. Hamsters infected with the hookworms were cured when administered orally with 2.5 mg/kg of the drug. Emodepside was also highly active in vivo against T. muris (ED50 = 1.2 mg/kg). Emodepside was moderately active on schistosomula in vitro (IC50 < 8 µM) 24 h post-drug incubation and its activity on adult S. mansoni and S. haematobium was low (IC50: 30-50 µM).
CONCLUSIONS: Emodepside is highly active against a broad range of nematode species both in vitro and in vivo. The development of emodepside for treating soil-transmitted helminth infections should be pursued.

PMID: 31088525 [PubMed - in process]

Zelnorm, an agonist of 5-Hydroxytryptamine 4-receptor, acts as a potential antitumor drug by targeting JAK/STAT3 signaling.

Invest New Drugs. 2019 May 14;:

Authors: Zhang L, Song Q, Zhang X, Li L, Xu X, Xu X, Li X, Wang Z, Lin Y, Li X, Li M, Su F, Wang X, Qiu P, Guan H, Tang Y, Xu W, Yang J, Zhao C

Abstract
The Janus kinase (JAK)/signal transducer and activator of transcription 3 (STAT3) signaling pathway plays central roles in cancer cell growth and survival. Drug repurposing strategies have provided a valuable approach for developing antitumor drugs. Zelnorm (tegaserod maleate) was originally designed as an agonist of 5-hydroxytryptamine 4 receptor (5-HT4R) and approved by the FDA for treating irritable bowel syndrome with constipation (IBS-C). Through the use of a high-throughput drug screening system, Zelnorm was identified as a JAK/STAT3 signaling inhibitor. Moreover, the inhibition of STAT3 phosphorylation by Zelnorm was independent of its original target 5-HT4R. Zelnorm could cause G1 cell cycle arrest, induce cell apoptosis and inhibit the growth of a variety of cancer cells. The present study identifies Zelnorm as a novel JAK/STAT3 signaling inhibitor and reveals a new clinical application of Zelnorm upon market reintroduction.

PMID: 31087223 [PubMed - as supplied by publisher]

Drug repurposing to overcome resistance to various therapies for colorectal cancer.

Cell Mol Life Sci. 2019 May 13;:

Authors: Fong W, To KKW

Abstract
Emergence of novel treatment modalities provides effective therapeutic options, apart from conventional cytotoxic chemotherapy, to fight against colorectal cancer. Unfortunately, drug resistance remains a huge challenge in clinics, leading to invariable occurrence of disease progression after treatment initiation. While novel drug development is unfavorable in terms of time frame and costs, drug repurposing is one of the promising strategies to combat resistance. This approach refers to the application of clinically available drugs to treat a different disease. With the well-established safety profile and optimal dosing of these approved drugs, their combination with current cancer therapy is suggested to provide an economical, safe and efficacious approach to overcome drug resistance and prolong patient survival. Here, we review both preclinical and clinical efficacy, as well as cellular mechanisms, of some extensively studied repurposed drugs, including non-steroidal anti-inflammatory drugs, statins, metformin, chloroquine, disulfiram, niclosamide, zoledronic acid and angiotensin receptor blockers. The three major treatment modalities in the management of colorectal cancer, namely classical cytotoxic chemotherapy, molecular targeted therapy and immunotherapy, are covered in this review.

PMID: 31087119 [PubMed - as supplied by publisher]

An ancient remedial repurposing: synthesis of new pinocembrin fatty acid acyl derivatives as potential antimicrobial/anti-inflammatory agents.

Nat Prod Res. 2019 Jan;33(2):162-168

Authors: Tundis R, Frattaruolo L, Carullo G, Armentano B, Badolato M, Loizzo MR, Aiello F, Cappello AR

Abstract
Five new pinocembrin derivatives (MC1-MC5) were synthesized by Steglich reaction, and investigated for their antimicrobial, antioxidant, and anti-inflammatory activity. MC2 (oleoyl derivative) and MC3 (linoleoyl derivative) have shown the highest inhibitory effects on bacterial proliferation, with MIC values of 32 μg/mL against Staphylococcus aureus. The docosahexaenoyl derivative MC5 displayed the highest anti-inflammatory activity, decreasing NO production in LPS-stimulated macrophages with an IC50 value of 15.51 μg/mL higher than the positive control diclofenac (IC50 of 39.71 μg/mL). All new synthesized compounds showed no anti-proliferative effects on RAW 264.7 cells. Results demonstrated as the introduction of fatty acid substituents improved the biological profile of pinocembrin. Moreover, the chemical nature of substituents significantly affects the bioactivity. These preliminary results outline the importance to investigate the synthesis of pinocembrin fatty acids derivatives as new and safe anti-microbial/anti-inflammatory agents.

PMID: 29463111 [PubMed - indexed for MEDLINE]

Niclosamide repositioning for treating cancer: Challenges and nano-based drug delivery opportunities.

Eur J Pharm Biopharm. 2019 May 09;:

Authors: José Barbosa E, Löbenberg R, Lima Barros de Araujo G, Araci Bou Chacra N

Abstract
Drug repositioning may be defined as a process when new biological effects for known drugs are identified, leading to recommendations for new therapeutic applications. Niclosamide, present in the Model List of Essential Medicines, from the World Health Organization, has been used since the 1960s for tapeworm infection. Several preclinical studies have been shown its impressive anticancer effects, which led to clinical trials for colon and prostate cancer. Despite high expectations, proof of efficacy and safety are still required, which are associated with diverse biopharmaceutical challenges, such as the physicochemical properties of the drug and its oral absorption, and their relationship with clinical outcomes. Nanostructured systems are innovative drug delivery strategies, which may provide interesting pharmaceutical advantages for this candidate. The aim of this review is to discuss challenges involving niclosamide repositioning for cancer diseases, and the opportunities of therapeutic benefits from nanosctrutured system formulations containing this compound.

PMID: 31078739 [PubMed - as supplied by publisher]

Disease networks and their contribution to disease understanding: A systematized review of their evolution, techniques and data sources.

J Biomed Inform. 2019 May 08;:103206

Authors: García Del Valle EP, Lagunes García G, Prieto Santamaría L, Zanin M, Menasalvas Ruiz E, Rodríguez-González A

Abstract
Over a decade ago, a new discipline called network medicine emerged as an approach to understand human diseases from a network theory point-of-view. Disease networks proved to be an intuitive and powerful way to reveal hidden connections among apparently unconnected biomedical entities such as diseases, physiological processes, signaling pathways, and genes. One of the fields that has benefited most from this improvement is the identification of new opportunities for the use of old drugs, known as drug repurposing. The importance of drug repurposing lies in the high costs and the prolonged time from target selection to regulatory approval of traditional drug development. In this document we analyze the evolution of disease network concept during the last decade and apply a data science pipeline approach to evaluate their functional units. As a result of this analysis, we obtain a list of the most commonly used functional units and the challenges that remain to be solved. This information can be very valuable for the generation of new prediction models based on disease networks.

PMID: 31077818 [PubMed - as supplied by publisher]

Adipogenesis induces growth inhibition of dedifferentiated liposarcoma.

Cancer Sci. 2019 May 08;:

Authors: Kim YJ, Yu DB, Kim M, Choi YL

Abstract
Well-differentiated liposarcoma (WDLPS) and dedifferentiated liposarcoma (DDLPS) are the most common types of liposarcoma. Although WDLPS and DDLPS patients receive intensive treatment including radical surgery and systemic therapy, their overall 5-year survival rates are 90% and 30%, respectively, indicating that DDLPS is clinically more aggressive. We examined whether adipogenic stimulation induces adipogenesis in human WDLPS/DDLPS cells by using dexamethasone, indomethacin, insulin, and 3-isobutyl-1-methylxanthine (IBMX), all putative medications or drugs. Functional in vitro experiments revealed that treatment with these four compounds induced adipogenic potency via the transcriptional and translational upregulation of genes related to the maintenance of stemness and adipogenic differentiation. Using in vivo xenograft models, we found that the induction of stemness and adipogenesis inhibited the tumorigenic potency of DDLPS. This study suggests a potential application of drug repositioning, in which adipogenesis-inducing compounds could be used to treat DDLPS patients in a clinical setting. This article is protected by copyright. All rights reserved.

PMID: 31069877 [PubMed - as supplied by publisher]

Repurposing drugs to target nonalcoholic steatohepatitis.

World J Gastroenterol. 2019 Apr 21;25(15):1783-1796

Authors: Sookoian S, Pirola CJ

Abstract
Nonalcoholic fatty liver disease (NAFLD) is a complex disorder that has evolved in recent years as the leading global cause of chronic liver damage. The main obstacle to better disease management pertains to the lack of approved pharmacological interventions for the treatment of nonalcoholic steatohepatitis (NASH) and NASH-fibrosis-the severe histological forms. Over the past decade, tremendous advances have been made in NAFLD research, resulting in the discovery of disease mechanisms and novel therapeutic targets. Hence, a large number of pharmacological agents are currently being tested for safety and efficacy. These drugs are in the initial pharmacological phases (phase 1 and 2), which involve testing tolerability, therapeutic action, and pharmacological issues. It is thus reasonable to assume that the next generation of NASH drugs will not be available for clinical use for foreseeable future. The expected delay can be mitigated by drug repurposing or repositioning, which essentially relies on identifying and developing new uses for existing drugs. Here, we propose a drug candidate selection method based on the integration of molecular pathways of disease pathogenesis into network analysis tools that use OMICs data as well as multiples sources, including text mining from the medical literature.

PMID: 31057294 [PubMed - in process]

Folate-conjugated human serum albumin-encapsulated resveratrol nanoparticles: preparation, characterization, bioavailability and targeting of liver tumors.

Artif Cells Nanomed Biotechnol. 2019 Dec;47(1):154-165

Authors: Lian B, Wu M, Feng Z, Deng Y, Zhong C, Zhao X

Abstract
This work investigated the preparation of specific targeted drug delivery systems in cancer chemotherapy by folate conjugated human serum albumin nanoparticles encapsulated resveratrol (RES) nanoparticles (FA-HSA-RESNPs). FA was coupled to HSA, and RES was encapsulated in FA-conjugated HSA by high pressure fluid nano-homogeneous emulsification. The average particle size and polydispersity index of NPs prepared under optimal conditions were 102.1 ± 4.9 nm and 0.001. The drug capsulation efficiency and drug loading efficiency were 98.36 and 14.66%, respectively. The analysis of the results of the physical characterization showed that the RES was present in the FA-HSA-RESNPs in an amorphous state. In vitro drug-release study showed that the NPs can release the drug persistently and slowly. The inhibition rate of FA-HSA-RESNPs and RES was detected using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide method to be 110.8 and 157.2 μM, respectively. The targeting ability of the FA-HSA-RESNPs for the HepG2 cell was measured by fluorescein isothiocyanate-modified albumin techniques. The uptake rate of FA-HSA-RESNPs was higher than that of the original RES. By using near-infrared imaging, in vivo activity was labeled with Cy5 fluorescent FA-HSA-RESNP confirmed FA-HSA-RESNP tumor-targeting ability. The intravenous administration bioavailability of FA-HSA-RESNPs was about 5.95-fold higher than that of the original RES.

PMID: 30686050 [PubMed - indexed for MEDLINE]

Revealing Drug-Target Interactions with Computational Models and Algorithms.

Molecules. 2019 May 02;24(9):

Authors: Zhou L, Li Z, Yang J, Tian G, Liu F, Wen H, Peng L, Chen M, Xiang J, Peng L

Abstract
BACKGROUND: Identifying possible drug-target interactions (DTIs) has become an important task in drug research and development. Although high-throughput screening is becoming available, experimental methods narrow down the validation space because of extremely high cost, low success rate, and time consumption. Therefore, various computational models have been exploited to infer DTI candidates.
METHODS: We introduced relevant databases and packages, mainly provided a comprehensive review of computational models for DTI identification, including network-based algorithms and machine learning-based methods. Specially, machine learning-based methods mainly include bipartite local model, matrix factorization, regularized least squares, and deep learning.
RESULTS: Although computational methods have obtained significant improvement in the process of DTI prediction, these models have their limitations. We discussed potential avenues for boosting DTI prediction accuracy as well as further directions.

PMID: 31052598 [PubMed - in process]

The possible repositioning of an oral anti-arthritic drug, auranofin, for Nrf2-activating therapy: The demonstration of Nrf2-dependent anti-oxidative action using a zebrafish model.

Free Radic Biol Med. 2018 02 01;115:405-411

Authors: Fuse Y, Endo Y, Araoi S, Daitoku H, Suzuki H, Kato M, Kobayashi M

Abstract
The Nrf2 pathway is a biological defense system against oxidative stress. The pharmacological activation of the Nrf2 pathway is a promising therapy for oxidative stress-related diseases, but it has been challenging to find an Nrf2 activator with acceptable toxicity. To circumvent this problem, we focused on an already approved oral anti-arthritic drug, auranofin that has been reported to have the potential to activate Nrf2. We used a zebrafish model to investigate whether auranofin has protective action against oxidative stress in vivo. Auranofin pre-treatment considerably improved the survival of zebrafish larvae that were challenged with a lethal dose of hydrogen peroxide. This protective effect was not observed in an Nrf2 mutant zebrafish strain, suggesting that the activation of the biological defense against oxidative stress was Nrf2-dependent. Auranofin-induced protection was further tested by challenges with redox-active heavy metals. A clear protective effect was observed against arsenite, a highly redox-reactive toxicant. In addition, this effect was also demonstrated to be Nrf2-dependent based on the analysis of an Nrf2 mutant strain. These results clearly demonstrate the anti-oxidative action of auranofin and encourage the repositioning of auranofin as a drug that improves oxidative stress-related pathology.

PMID: 29277393 [PubMed - indexed for MEDLINE]

Prospects for repurposing CNS drugs for cancer treatment.

Oncol Rev. 2019 Jan 14;13(1):411

Authors: Abdelaleem M, Ezzat H, Osama M, Megahed A, Alaa W, Gaber A, Shafei A, Refaat A

Abstract
Drug repurposing is the idea of using an already approved drug for another disease or disorder away from its initial use. This new approach ensures the reduction in high cost required for developing a new drug in addition to the time consumed, especially in the tumor disorders that show an unceasing rising rate with an unmet success rate of new anticancer drugs. In our review, we will review the anti-cancer effect of some CNS drugs, including both therapeutic and preventive, by searching the literature for preclinical or clinical evidence for anticancer potential of central nervous system drugs over the last 8 years period (2010-2018) and including only evidence from Q1 journals as indicated by Scimago website (www.scimagojr.com). We concluded that Some Central Nervous system drugs show a great potential as anti-cancer in vitro, in vivo and clinical trials through different mechanisms and pathways in different types of cancer that reveal a promising evidence for the repurposing of CNS drugs for new indications.

PMID: 31044029 [PubMed]

Construction and analysis of a comprehensive protein interaction network of HCV with its host Homo sapiens.

BMC Infect Dis. 2019 Apr 30;19(1):367

Authors: Farooq QUA, Khan FF

Abstract
BACKGROUND: Hepatitis C Virus is becoming a major health problem in Asia and across the globe since it is causing serious liver diseases including liver cirrhosis, chronic hepatitis and hepatocarcinoma (HCC). Protein interaction networks presents us innumerable novel insights into functional constitution of proteome and helps us finding potential candidates for targeting the drugs.
METHODS: Here we present a comprehensive protein interaction network of Hepatitis C Virus with its host, constructed by literature curated interactions. The network was constructed and explored using Cytoscape and the results were further analyzed using KEGG pathway, Gene Ontology enrichment analysis and MCODE.
RESULTS: We found 1325 interactions between 12 HCV proteins and 940 human genes, among which 21 were intraviral and 1304 were HCV-Human. By analyzing the network, we found potential human gene list with their number of interactions with HCV proteins. ANXA2 and NR4A1 were interacting with 6 HCV proteins while we found 11 human genes which were interacting with 5 HCV proteins. Furthermore, the enrichment analysis and Gene Ontology of the top genes to find the pathways and the biological processes enriched with those genes. Among the viral proteins, NS3 was interacting with most number of interactors followed by NS5A and so on. KEGG pathway analysis of three set of most HCV- associated human genes was performed to find out which gene products are involved in certain disease pathways. Top 5, 10 and 20 human genes with most interactions were analyzed which revealed some striking results among which the top 10 host genes came up to be significant because they were more related to Influenza A viral infection previously. This insight provides us with a clue that the set of genes are highly enriched in HCV but are not well studied in its infection pathway.
CONCLUSIONS: We found out a group of proteins which were rich in HCV viral pathway but there were no drugs targeting them according to the drug repurposing hub. It can be concluded that the cluster we obtained from MCODE contains potential targets for HCV treatment and could be implemented for molecular docking and drug designing further by the scientists.

PMID: 31039741 [PubMed - in process]

Molecular Network-Based Drug Prediction in Thyroid Cancer.

Int J Mol Sci. 2019 Jan 11;20(2):

Authors: Xu X, Long H, Xi B, Ji B, Li Z, Dang Y, Jiang C, Yao Y, Yang J

Abstract
As a common malignant tumor disease, thyroid cancer lacks effective preventive and therapeutic drugs. Thus, it is crucial to provide an effective drug selection method for thyroid cancer patients. The connectivity map (CMAP) project provides an experimental validated strategy to repurpose and optimize cancer drugs, the rationale behind which is to select drugs to reverse the gene expression variations induced by cancer. However, it has a few limitations. Firstly, CMAP was performed on cell lines, which are usually different from human tissues. Secondly, only gene expression information was considered, while the information about gene regulations and modules/pathways was more or less ignored. In this study, we first measured comprehensively the perturbations of thyroid cancer on a patient including variations at gene expression level, gene co-expression level and gene module level. After that, we provided a drug selection pipeline to reverse the perturbations based on drug signatures derived from tissue studies. We applied the analyses pipeline to the cancer genome atlas (TCGA) thyroid cancer data consisting of 56 normal and 500 cancer samples. As a result, we obtained 812 up-regulated and 213 down-regulated genes, whose functions are significantly enriched in extracellular matrix and receptor localization to synapses. In addition, a total of 33,778 significant differentiated co-expressed gene pairs were found, which form a larger module associated with impaired immune function and low immunity. Finally, we predicted drugs and gene perturbations that could reverse the gene expression and co-expression changes incurred by the development of thyroid cancer through the Fisher's exact test. Top predicted drugs included validated drugs like baclofen, nevirapine, glucocorticoid, formaldehyde and so on. Combining our analyses with literature mining, we inferred that the regulation of thyroid hormone secretion might be closely related to the inhibition of the proliferation of thyroid cancer cells.

PMID: 30641858 [PubMed - indexed for MEDLINE]

ClinOmicsTrailbc: a visual analytics tool for breast cancer treatment stratification.

Bioinformatics. 2019 Apr 30;:

Authors: Schneider L, Kehl T, Thedinga K, Grammes NL, Backes C, Mohr C, Schubert B, Lenhof K, Gerstner N, Daniel Hartkopf A, Wallwiener M, Kohlbacher O, Keller A, Meese E, Graf N, Lenhof HP

Abstract
MOTIVATION: Breast cancer is the second leading cause of cancer death among women. Tumors, even of the same histopathological subtype, exhibit a high genotypic diversity that impedes therapy stratification and that hence must be accounted for in the treatment decision-making process.
RESULTS: Here, we present ClinOmicsTrailbc, a comprehensive visual analytics tool for breast cancer decision support that provides a holistic assessment of standard-of-care targeted drugs, candidates for drug repositioning, and immunotherapeutic approaches. To this end, our tool analyzes and visualizes clinical markers and (epi-)genomics and transcriptomics datasets to identify and evaluate the tumor's main driver mutations, the tumor mutational burden, activity patterns of core cancer-relevant pathways, drug-specific biomarkers, the status of molecular drug targets, and pharmacogenomic influences. In order to demonstrate ClinOmicsTrailbc's rich functionality, we present three case studies highlighting various ways in which ClinOmicsTrailbc can support breast cancer precision medicine. ClinOmicsTrailbc is a powerful integrated visual analytics tool for breast cancer research in general and for therapy stratification in particular, assisting oncologists to find the best possible treatment options for their breast cancer patients based on actionable, evidence-based results.
AVAILABILITY: ClinOmicsTrailbc can be freely accessed at https://clinomicstrail.bioinf.uni-sb.de.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID: 31038669 [PubMed - as supplied by publisher]

Drug repurposing in oncology: Compounds, pathways, phenotypes and computational approaches for colorectal cancer.

Biochim Biophys Acta Rev Cancer. 2019 Apr 26;:

Authors: Nowak-Sliwinska P, Scapozza L, Altaba ARI

Abstract
The strategy of using existing drugs originally developed for one disease to treat other indications has found success across medical fields. Such drug repurposing promises faster access of drugs to patients while reducing costs in the long and difficult process of drug development. However, the number of existing drugs and diseases, together with the heterogeneity of patients and diseases, notably including cancers, can make repurposing time consuming and inefficient. The key question we address is how to efficiently repurpose an existing drug to treat a given indication. As drug efficacy remains the main bottleneck for overall success, we discuss the need for machine-learning computational methods in combination with specific phenotypic studies along with mechanistic studies, chemical genetics and omics assays to successfully predict disease-drug pairs. Such a pipeline could be particularly important to cancer patients who face heterogeneous, recurrent and metastatic disease and need fast and personalized treatments. Here we focus on drug repurposing for colorectal cancer and describe selected therapeutics already repositioned for its prevention and/or treatment as well as potential candidates. We consider this review as a selective compilation of approaches and methodologies, and argue how, taken together, they could bring drug repurposing to the next level.

PMID: 31034926 [PubMed - as supplied by publisher]