Mixing the Old with the New: Drug Repurposing for Immune Deficiency in the Era of Precision Medicine and Pediatric Genomics.

J Allergy Clin Immunol Pract. 2018 Nov - Dec;6(6):2168-2169

Authors: Schroeder HW

PMID: 30390908 [PubMed - in process]

Therapeutic research in the crystal chromosome disease Fanconi anemia.

Mutat Res. 2018 Dec;836(Pt A):104-108

Authors: Minguillón J, Surrallés J

Abstract
In the last decades there has been a great progress in understanding the pathological and genetic mechanisms involved in Fanconi anemia (FA), a rare disease characterized by chromosome fragility, congenital malformations, bone marrow failure (BMF) and high cancer predisposition. However, these advances have not gone in parallel with the development of medical treatments, with the exception of improved protocols of hematopoietic stem cell transplant (HSCT). BMF and hematological malignancies are the most important and life threatening conditions the patient suffer during the first and second decade of life, respectively, being HSCT the only curative treatment available. Solid tumors are the third hallmark of the disease, usually with poor prognosis as tumor resection is the only therapeutic option given that patients do not tolerate chemotherapy or radiation. With improved HSCT protocols, FA patient survival has increased, leading to a progressively increased number of solid malignancies in adult patients. Therapeutic research is currently focused in targeted therapies for solid tumors as well as in preventive options in the context of drug repurposing. This review summarizes current therapies and drugs used so far in clinical trials to treat Fanconi anemia, as well as the ones used in FA research with potential for future therapeutic opportunities including drugs that suppress chromosome fragility or are expected to delay the onset of BMF and cancer in Fanconi anemia.

PMID: 30389152 [PubMed - in process]

Activity of the antiarrhythmic drug amiodarone against Leishmania (L.) infantum: an in vitro and in vivo approach.

J Venom Anim Toxins Incl Trop Dis. 2018;24:29

Authors: Pinto EG, Tempone AG

Abstract
Background: Considering the high toxicity and limited therapies available for treating visceral leishmaniasis (VL), the drug repositioning approach represents a faster way to deliver new therapies to the market.
Methods: In this study, we described for the first time the activity of a potent antiarrhythmic, amiodarone (AMD), against L. (L.) infantum and its in vitro and in vivo activity.
Results: The evaluation against promastigotes has shown that amiodarone presents leishmanicidal effect against the extracellular form, with an IC50 value of 10 μM. The activity was even greater against amastigotes in comparison with promastigotes with an IC50 value of 0.5 μM. The selectivity index in relation to the intracellular form demonstrated that the antiparasitic activity was approximately 56 times higher than its toxicity to mammalian cells. Investigation of the in vivo AMD activity in the L. infantum-infected hamster model showed that 51 days after the initial infection, amiodarone was unable to reduce the parasite burden in the spleen and liver when treated for 10 consecutive days, intraperitoneally, at 50 mg/kg/day, as determined by qPCR. Although not statistically significant, AMD was able to reduce the parasite burden by 20% in the liver when treated for 10 consecutive days, orally, at 100 mg/kg/day; no reduction in the spleen was found by qPCR.
Conclusions: Our findings may help further drug design studies seeking new AMD derivatives that may provide new candidates with an in vitro selectivity close to or even greater than that observed in the prototype delivering effectiveness in the experimental model of VL.

PMID: 30386379 [PubMed]

Combined cellular and biochemical profiling to identify predictive drug response biomarkers for kinase inhibitors approved for clinical use between 2013 and 2017.

Mol Cancer Ther. 2018 Oct 31;:

Authors: Uitdehaag JCM, Kooijman JJ, de Roos JADM, Prinsen MBW, Dylus J, Willemsen-Seegers N, Kawase Y, Sawa M, de Man J, van Gerwen SJC, Buijsman RC, Zaman GJR

Abstract
Kinase inhibitors form the largest class of precision medicine. From 2013-2017, seventeen have been approved, with eight different mechanisms. We present a comprehensive profiling study of all seventeen inhibitors on a biochemical assay panel of 280 kinases and proliferation assays of 108 cancer cell lines. Drug responses of the cell lines were related to the presence of frequently recurring point mutations, insertions, deletions, and amplifications in 15 well- known oncogenes and tumor suppressor genes. Additionally, drug responses were correlated with basal gene expression levels with a focus on 383 clinically actionable genes. Cell lines harbouring actionable mutations defined in the FDA labels, such as mutant BRAF(V600E) for cobimetinib, or ALK gene translocation for ALK inhibitors, are generally 10 times more sensitive compared to wild-type cell lines. This sensitivity window is more narrow for markers which failed to meet endpoints in clinical trials, for instance CDKN2A loss for CDK4/6 inhibitors (2.7-fold), and KRAS-mutation for cobimetinib (2.3-fold). Our data underscore the rationale of a number of recently opened clinical trials, such as ibrutinib in ERBB2- or ERBB4-expressing cancers. We propose and validate new response biomarkers, such as mutation in FBXW7 or SMAD4 for EGFR and HER2 inhibitors, ETV4 and ETV5 expression for MEK inhibitors and JAK3 expression for ALK inhibitors. Potentially, these new markers could be combined to improve response rates. This comprehensive overview of biochemical and cellular selectivities of approved kinase inhibitor drugs provides a rich resource for drug repurposing, basket trial design and basic cancer research.

PMID: 30381447 [PubMed - as supplied by publisher]

A High-Throughput Screening Approach To Repurpose FDA-Approved Drugs for Bactericidal Applications against Staphylococcus aureus Small-Colony Variants.

mSphere. 2018 Oct 31;3(5):

Authors: Trombetta RP, Dunman PM, Schwarz EM, Kates SL, Awad HA

Abstract
Drug repurposing offers an expedited and economical route to develop new clinical therapeutics in comparison to traditional drug development. Growth-based high-throughput screening is concomitant with drug repurposing and enables rapid identification of new therapeutic uses for investigated drugs; however, this traditional method is not compatible with microorganisms with abnormal growth patterns such as Staphylococcus aureus small-colony variants (SCV). SCV subpopulations are auxotrophic for key compounds in biosynthetic pathways, which result in low growth rate. SCV formation is also associated with reduced antibiotic susceptibility, and the SCV's ability to revert to the normal cell growth state is thought to contribute to recurrence of S. aureus infections. Thus, there is a critical need to identify antimicrobial agents that are potent against SCV in order to effectively treat chronic infections. Accordingly, here we describe adapting an adenylate kinase (AK)-based cell death reporter assay to identify members of a Food and Drug Administration (FDA)-approved drug library that display bactericidal activity against S. aureus SCV. Four library members, daunorubicin, ketoconazole, rifapentine, and sitafloxacin, exhibited potent SCV bactericidal activity against a stable S. aureus SCV. Further investigation showed that sitafloxacin was potent against methicillin-susceptible and -resistant S. aureus, as well as S. aureus within an established biofilm. Taken together, these results demonstrate the ability to use the AK assay to screen small-molecule libraries for SCV bactericidal agents and highlight the therapeutic potential of sitafloxacin to be repurposed to treat chronic S. aureus infections associated with SCV and/or biofilm growth states.IMPORTANCE Conventional antibiotics fail to successfully treat chronic osteomyelitis, endocarditis, and device-related and airway infections. These recurring infections are associated with the emergence of SCV, which are recalcitrant to conventional antibiotics. Studies have investigated antibiotic therapies to treat SCV-related infections but have had little success, emphasizing the need to identify novel antimicrobial drugs. However, drug discovery is a costly and time-consuming process. An alternative strategy is drug repurposing, which could identify FDA-approved and well-characterized drugs that could have off-label utility in treating SCV. In this study, we adapted a high-throughput AK-based assay to identify 4 FDA-approved drugs, daunorubicin, ketoconazole, rifapentine, and sitafloxacin, which display antimicrobial activity against S. aureus SCV, suggesting an avenue for drug repurposing in order to effectively treat SCV-related infections. Additionally, this screening paradigm can easily be adapted for other drug/chemical libraries to identify compounds bactericidal against SCV.

PMID: 30381352 [PubMed - in process]

Survey of Similarity-based Prediction of Drug-protein Interactions.

Curr Med Chem. 2018 Nov 01;:

Authors: Kurgan L, Wang C

Abstract
Therapeutic activity of a significant majority of drugs is determined by their interactions with proteins. Databases of drug-protein interactions (DPIs) primarily focus on the therapeutic protein targets while the knowledge of the off-targets is fragmented and partial. One way to bridge this knowledge gap is to employ computational methods to predict protein targets for a given drug molecule, or interacting drugs for given protein targets. We survey a comprehensive set of 35 methods that were published in high-impact venues and that predict DPIs based on similarity between drugs and similarity between protein targets. We analyze the internal databases of known PDIs that these methods utilize to compute similarities, and investigate how they are linked to the 12 publicly available source databases. We discuss contents, impact and relationships between these internal and source databases, and well as the timeline of their releases and publications. The 35 predictors exploit and often combine three types of similarities that consider drug structures, drug profiles, and target sequences. We review the predictive architectures of these methods, their impact, and we explain how their internal DPIs databases are linked to the source databases. We also include a detailed timeline of the development of these predictors and discuss the underlying limitations of the current resources and predictive tools. Finally, we provide several recommendations concerning future development of the related databases and methods.

PMID: 30381061 [PubMed - as supplied by publisher]

A review of drug repositioning based chemical-induced cell line expression data.

Curr Med Chem. 2018 Nov 01;:

Authors: Wang F, Lei X, Wu FX

Abstract
Drug repositioning is an important area of biomedical research. The drug repositioning studies have shifted to computational approaches. Large-scale perturbation databases, such as the Connectivity Map and the Library of Integrated Network-Based Cellular Signatures, contain a number of chemical-induced gene expression profiles and provide great opportunities for computational biology and drug repositioning. One reason is that the profiles provided by the Connectivity Map and the Library of Integrated Network-Based Cellular Signatures databases show an overall view of biological mechanism in drugs, diseases and genes. In this article, we provide a review of the two databases and their recent applications in drug repositioning.

PMID: 30381060 [PubMed - as supplied by publisher]

In Silico Oncology Drug Repositioning and Polypharmacology.

Methods Mol Biol. 2019;1878:243-261

Authors: Cheng F

Abstract
Network-aided in silico approaches have been widely used for prediction of drug-target interactions and evaluation of drug safety to increase the clinical efficiency and productivity during drug discovery and development. Here we review the advances and new progress in this field and summarize the translational applications of several new network-aided in silico approaches we developed recently. In addition, we describe the detailed protocols for a network-aided drug repositioning infrastructure for identification of new targets for old drugs, failed drugs in clinical trials, and new chemical entities. These state-of-the-art network-aided in silico approaches have been used for the discovery and development of broad-acting and targeted clinical therapies for various complex diseases, in particular for oncology drug repositioning. In this chapter, the described network-aided in silico protocols are appropriate for target-centric drug repositioning to various complex diseases, but expertise is still necessary to perform the specific oncology projects based on the cancer targets of interest.

PMID: 30378081 [PubMed - in process]

Functional Assessment of 2,177 U.S. and International Drugs Identifies the Quinoline Nitroxoline as a Potent Amoebicidal Agent against the Pathogen Balamuthia mandrillaris.

MBio. 2018 Oct 30;9(5):

Authors: Laurie MT, White CV, Retallack H, Wu W, Moser MS, Sakanari JA, Ang K, Wilson C, Arkin MR, DeRisi JL

Abstract
Balamuthia mandrillaris is a pathogenic free-living amoeba that causes a rare but almost always fatal infection of the central nervous system called granulomatous amoebic encephalitis (GAE). Two distinct forms of B. mandrillaris-a proliferative trophozoite form and a nonproliferative cyst form, which is highly resistant to harsh physical and chemical conditions-have been isolated from environmental samples worldwide and are both observed in infected tissue. Patients suffering from GAE are typically treated with aggressive and prolonged multidrug regimens that often include the antimicrobial agents miltefosine and pentamidine isethionate. However, survival rates remain low, and studies evaluating the susceptibility of B. mandrillaris to these compounds and other potential therapeutics are limited. To address the need for more-effective treatments, we screened 2,177 clinically approved compounds for in vitro activity against B. mandrillaris The quinoline antibiotic nitroxoline (8-hydroxy-5-nitroquinoline), which has safely been used in humans to treat urinary tract infections, was identified as a lead compound. We show that nitroxoline inhibits both trophozoites and cysts at low micromolar concentrations, which are within a pharmacologically relevant range. We compared the in vitro efficacy of nitroxoline to that of drugs currently used in the standard of care for GAE and found that nitroxoline is the most potent and selective inhibitor of B. mandrillaris tested. Furthermore, we demonstrate that nitroxoline prevents B. mandrillaris-mediated destruction of host cells in cultured fibroblast and primary brain explant models also at pharmacologically relevant concentrations. Taken together, our findings indicate that nitroxoline is a promising candidate for repurposing as a novel treatment of B. mandrillaris infections.IMPORTANCE Balamuthia mandrillaris is responsible for hundreds of reported cases of amoebic encephalitis, the majority of which have been fatal. Despite being an exceptionally deadly pathogen, B. mandrillaris is understudied, leaving many open questions regarding epidemiology, diagnosis, and treatment. Due to the lack of effective drugs to fight B. mandrillaris infections, mortality rates remain high even for patients receiving intensive care. This report addresses the need for new treatment options through a drug repurposing screen to identify novel B. mandrillaris inhibitors. The most promising candidate identified was the quinoline antibiotic nitroxoline, which has a long history of safe use in humans. We show that nitroxoline kills B. mandrillaris at pharmacologically relevant concentrations and exhibits greater potency and selectivity than drugs commonly used in the current standard of care. The findings that we present demonstrate the potential of nitroxoline to be an important new tool in the treatment of life-threatening B. mandrillaris infections.

PMID: 30377287 [PubMed - in process]

Network integration of multi-tumour omics data suggests novel targeting strategies.

Nat Commun. 2018 Oct 30;9(1):4514

Authors: do Valle ÍF, Menichetti G, Simonetti G, Bruno S, Zironi I, Durso DF, Mombach JCM, Martinelli G, Castellani G, Remondini D

Abstract
We characterize different tumour types in search for multi-tumour drug targets, in particular aiming for drug repurposing and novel drug combinations. Starting from 11 tumour types from The Cancer Genome Atlas, we obtain three clusters based on transcriptomic correlation profiles. A network-based analysis, integrating gene expression profiles and protein interactions of cancer-related genes, allows us to define three cluster-specific signatures, with genes belonging to NF-κB signaling, chromosomal instability, ubiquitin-proteasome system, DNA metabolism, and apoptosis biological processes. These signatures have been characterized by different approaches based on mutational, pharmacological and clinical evidences, demonstrating the validity of our selection. Moreover, we define new pharmacological strategies validated by in vitro experiments that show inhibition of cell growth in two tumour cell lines, with significant synergistic effect. Our study thus provides a list of genes and pathways that could possibly be used, singularly or in combination, for the design of novel treatment strategies.

PMID: 30375513 [PubMed - in process]

Experimental Ebola drugs face tough test in war zone.

Nature. 2018 09;561(7721):14

Authors: Maxmen A

PMID: 30181631 [PubMed - indexed for MEDLINE]

Transcriptome-based repurposing of apigenin as a potential anti-fibrotic agent targeting hepatic stellate cells.

Sci Rep. 2017 03 03;7:42563

Authors: Hicks DF, Goossens N, Blas-García A, Tsuchida T, Wooden B, Wallace MC, Nieto N, Lade A, Redhead B, Cederbaum AI, Dudley JT, Fuchs BC, Lee YA, Hoshida Y, Friedman SL

Abstract
We have used a computational approach to identify anti-fibrotic therapies by querying a transcriptome. A transcriptome signature of activated hepatic stellate cells (HSCs), the primary collagen-secreting cell in liver, and queried against a transcriptomic database that quantifies changes in gene expression in response to 1,309 FDA-approved drugs and bioactives (CMap). The flavonoid apigenin was among 9 top-ranked compounds predicted to have anti-fibrotic activity; indeed, apigenin dose-dependently reduced collagen I in the human HSC line, TWNT-4. To identify proteins mediating apigenin's effect, we next overlapped a 122-gene signature unique to HSCs with a list of 160 genes encoding proteins that are known to interact with apigenin, which identified C1QTNF2, encoding for Complement C1q tumor necrosis factor-related protein 2, a secreted adipocytokine with metabolic effects in liver. To validate its disease relevance, C1QTNF2 expression is reduced during hepatic stellate cell activation in culture and in a mouse model of alcoholic liver injury in vivo, and its expression correlates with better clinical outcomes in patients with hepatitis C cirrhosis (n = 216), suggesting it may have a protective role in cirrhosis progression.These findings reinforce the value of computational approaches to drug discovery for hepatic fibrosis, and identify C1QTNF2 as a potential mediator of apigenin's anti-fibrotic activity.

PMID: 28256512 [PubMed - indexed for MEDLINE]

Pathway-Based Drug Repositioning for Cancers: Computational Prediction and Experimental Validation.

J Med Chem. 2018 Oct 29;:

Authors: Iwata M, Hirose L, Kohara H, Liao J, Sawada R, Akiyoshi S, Tani K, Yamanishi Y

Abstract
Developing drugs with anticancer activity and low toxic side-effects at low costs is a challenging issue for cancer chemotherapy. In this work, we propose to use molecular pathways as the therapeutic targets and develop a novel computational approach for drug repositioning for cancer treatment. We analyzed chemically induced gene expression data of 1112 drugs on 66 human cell lines and searched for drugs that inactivate pathways involved in the growth of cancer cells (cell cycle) and activate pathways that contribute to the death of cancer cells (e.g., apoptosis and p53 signaling). Finally, we performed a large-scale prediction of potential anticancer effects for all the drugs and experimentally validated the prediction results via three in vitro cellular assays that evaluate cell viability, cytotoxicity, and apoptosis induction. Using this strategy, we successfully identified several potential anticancer drugs. The proposed pathway-based method has great potential to improve drug repositioning research for cancer treatment.

PMID: 30371064 [PubMed - as supplied by publisher]

Drug repositioning as an effective therapy for protease-activated receptor 2 inhibition.

J Cell Biochem. 2018 Oct 29;:

Authors: Saqib U, Savai R, Liu D, Banerjee S, Baig MS

Abstract
Proteinase-activated receptor 2 (PAR-2) is a G protein-coupled receptor activated by both trypsin and a specific agonist peptide, SLIGKV-NH2. It has been linked to various pathologies, including pain and inflammation. Several peptide and peptidomimetic agonizts for PAR-2 have been developed exhibiting high potency and efficacy. However, the number of PAR-2 antagonists is smaller. We screened the Food and Drug Administration library of approved compounds to retrieve novel antagonists for repositioning in the PAR-2 structure. The most efficacious compound bicalutamide bound to the PAR-2 binding groove near the extracellular domain as observed in the in silico studies. Further, it showed reduced Ca2+ release in trypsin activated cells in a dose-dependent manner. Hence, bicalutamide is a novel and potent PAR-2 antagonist which could be therapeutically useful in blocking multiple pathways diverging from PAR-2 signaling. Further, the novel scaffold of bicalutamide represents a new molecular structure for PAR-2 antagonism and can serve as a basis for further drug development.

PMID: 30370939 [PubMed - as supplied by publisher]

Recent advances in genetically modified animal models of glaucoma and their roles in drug repositioning.

Br J Ophthalmol. 2018 Oct 26;:

Authors: Harada C, Kimura A, Guo X, Namekata K, Harada T

Abstract
Glaucoma is one of the leading causes of vision loss in the world. Currently, pharmacological intervention for glaucoma therapy is limited to eye drops that reduce intraocular pressure (IOP). Recent studies have shown that various factors as well as IOP are involved in the pathogenesis of glaucoma, especially in the subtype of normal tension glaucoma. To date, various animal models of glaucoma have been established, including glutamate/aspartate transporter knockout (KO) mice, excitatory amino acid carrier 1 KO mice, optineurin E50K knock-in mice, DBA/2J mice and experimentally induced models. These animal models are very useful for elucidating the pathogenesis of glaucoma and for identifying potential therapeutic targets. However, each model represents only some aspects of glaucoma, never the whole disease. This review will summarise the benefits and limitations of using disease models of glaucoma and recent basic research in retinal protection using existing drugs.

PMID: 30366949 [PubMed - as supplied by publisher]

Drug Repurposing Patent Applications July-September 2018.

Assay Drug Dev Technol. 2018 Oct 26;:

Authors: Mucke HAM

PMID: 30362814 [PubMed - as supplied by publisher]

Systems Biology: A powerful tool for drug development.

Curr Top Med Chem. 2018 Oct 25;:

Authors: Rai S, Raj U, Varadwaj PK

Abstract
The conventional way of characterizing a disease consists of correlating clinical symptoms with pathological findings. Although, this approach for many years has assisted clinicians in establishing syndromic patterns for pathophenotypes, it has major limitations as it does not consider preclinical disease states and is unable to individualize medicine. Moreover, the complexity of disease biology is the major challenge in development of effective and safe medicines. Therefore, the process of drug development must consider biological responses in both pathological and physiological conditions. Consequently, a quantitative and holistic systems biology approach could aid in understanding complex biological systems by providing an exceptional platform to integrate diverse data types with molecular as well as pathway information, leading to development of predictive models for complex diseases. Furthermore, an increase in knowledgebase of protein, genes, metabolites from high-throughputs experimental data accelerates hypothesis generation and testing in disease models. The systems biology approach also assists in predicting drug effects, repurposing of existing drugs, identifying new targets, facilitating development of personalized medicine and improving decision making and success rate of new drugs in clinical trials.

PMID: 30360720 [PubMed - as supplied by publisher]

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Quantitative and systems pharmacology 4. Network-based analysis of drug pleiotropy on coronary artery disease.

Eur J Med Chem. 2018 Oct 15;161:192-204

Authors: Fang J, Cai C, Chai Y, Zhou J, Huang Y, Gao L, Wang Q, Cheng F

Abstract
Despite recent advance of therapeutic development, coronary artery disease (CAD) remains one of the major issues to public health. The use of genomics and systems biology approaches to inform drug discovery and development have offered the possibilities for new target identification and in silico drug repurposing. In this study, we propose a network-based, systems pharmacology framework for target identification and drug repurposing in pharmacologic treatment and chemoprevention of CAD. Specifically, we build in silico models by integrating known drug-target interactions, CAD genes derived from the genetic and genomic studies, and the human protein-protein interactome. We demonstrate that the proposed in silico models can successfully uncover approved drugs and novel natural products in potentially treating and preventing CAD. In case studies, we highlight several approved drugs (e.g., fasudil, parecoxib, and dexamethasone) or natural products (e.g., resveratrol, luteolin, daidzein and caffeic acid) with new mechanism-of-action in chemical intervention of CAD by network analysis. In summary, this study offers a powerful systems pharmacology approach for target identification and in silico drug repurposing on CAD.

PMID: 30359818 [PubMed - as supplied by publisher]

Systems biology-based drug repositioning identifies digoxin as a potential therapy for groups 3 and 4 medulloblastoma.

Sci Transl Med. 2018 Oct 24;10(464):

Authors: Huang L, Garrett Injac S, Cui K, Braun F, Lin Q, Du Y, Zhang H, Kogiso M, Lindsay H, Zhao S, Baxter P, Adekunle A, Man TK, Zhao H, Li XN, Lau CC, Wong STC

Abstract
Medulloblastoma (MB) is the most common malignant brain tumor of childhood. Although outcomes have improved in recent decades, new treatments are still needed to improve survival and reduce treatment-related complications. The MB subtypes groups 3 and 4 represent a particular challenge due to their intragroup heterogeneity, which limits the options for "rational" targeted therapies. Here, we report a systems biology approach to drug repositioning that integrates a nonparametric, bootstrapping-based simulated annealing algorithm and a 3D drug functional network to characterize dysregulated driver signaling networks, thereby identifying potential drug candidates. From more than 1300 drug candidates studied, we identified five members of the cardiac glycoside family as potentially inhibiting the growth of groups 3 and 4 MB and subsequently confirmed this in vitro. Systemic in vivo treatment of orthotopic patient-derived xenograft (PDX) models of groups 3 and 4 MB with digoxin, a member of the cardiac glycoside family approved for the treatment of heart failure, prolonged animal survival at plasma concentrations known to be tolerated in humans. These results demonstrate the power of a systematic drug repositioning method in identifying a potential treatment for MB. Our strategy could potentially be used to accelerate the repositioning of treatments for other human cancers that lack clearly defined rational targets.

PMID: 30355798 [PubMed - in process]