Clinical applications of aptamers and nucleic acid therapeutics in haematological malignancies

Haematological malignancies result from a heterogeneous mix of genetic mutations and chromosome aberrations and translocations. Targeted therapies, such as the anti-CD20 antibody rituximab, or the BCR-ABL1 inhibitor imatinib, have proven to be effective treatments in the management of some of these malignancies, though relapsing or refractory disease is still common. Nucleic acid-based therapies have also entered the clinical arena, providing an alternative, complementary approach. The forerunner of these therapies were the antisense oligonucleotides, but their scope has expanded to include short-interfering RNA (siRNA), microRNA, decoy oligonucleotides and aptamers. These can be used either as monotherapeutics, in conjunction with current chemotherapy regimens, or in combination with each other to improve therapeutic efficacy. Not only can these nucleic acid-based therapies silence target genes, they also have the potential of restoring gene function. While challenges remain in delivering effective doses of nucleic acid in vivo, these are steadily being met, suggesting an optimistic future in the treatment of haematological malignancies. This review summarizes the application of nucleic acid-based therapeutics, particularly aptamers, in the diagnosis and treatment of haematological malignancies.

Current protein-based anti-angiogenic therapeutics

 Angiogenesis is a complex multistep process of formation of new blood vessels. Interactions between several cellular factors including growth factors, cytokines and haematopoietic factors lead to activation of various cellular pathways, finally resulting in extracellular matrix (ECM) degradation, endothelial cell proliferation, survival and migration. Normally, angiogenesis is an essential requirement for vascular development in growing embryos as well as in adult tissues, where this process depends on the intricate balance between the activities of the pro- and anti-angiogenic factors. Abnormal angiogenesis results in aberrant vasculature leading to various pathological conditions. The most important factor implicated in angiogenic processes in vascular endothelial growth factor (VEGF) and its family of ligands and receptors. Several anti-angiogenic drugs have been developed and many more are currently in different phases of clinical trials, which target various angiogenesis-inducing agents, including VEGF, VEGF receptors, angiopoietins and ECM components such as integrins. Anti-angiogenic therapy can be divided into gene-based therapy and protein-based therapy. Gene-based therapies include use of antisense oligonucleotides, siRNA, aptamers, catalytic oligonucleotides including ribozymes and DNAzymes and transcription decoys. Protein-based therapeutics includes monoclonal antibodies, peptidomimetics, fusion proteins and decoy receptors. The later class of therapeutics has several advantages over gene-based and small molecule drugs, including specificity and complexity in functions, better tolerability, less interference with normal biological processes and lesser adverse effects due to decreased immune response by virtue of being mostly body's natural proteins. This review provides a comprehensive overview of angiogenesis and on the current protein-based anti-angiogenic therapeutics under research and in the clinic.

Identification of novel therapeutics for complex diseases from genome-wide association data

Human genome sequencing has enabled the association of phenotypes with genetic loci, but our ability to effectively translate this data to the clinic has not kept pace. Over the past 60 years, pharmaceutical companies have successfully demonstrated the safety and efficacy of over 1,200 novel therapeutic drugs via costly clinical studies. While this process must continue, better use can be made of the existing valuable data. In silico tools such as candidate gene prediction systems allow rapid identification of disease genes by identifying the most probable candidate genes linked to genetic markers of the disease or phenotype under investigation. Integration of drug-target data with candidate gene prediction systems can identify novel phenotypes which may benefit from current therapeutics. Such a drug repositioning tool can save valuable time and money spent on preclinical studies and phase I clinical trials.

Novel therapeutics for cononary artery disease from genome-wide association study data

Abstract
Background: Coronary artery disease (CAD), one of the leading causes of death globally, is influenced by both environmental and genetic risk factors. Gene-centric genome-wide association studies (GWAS) involving cases and controls have been remarkably successful in identifying genetic loci contributing to CAD. Modern in silico platforms, such as candidate gene prediction tools, permit a systematic analysis of GWAS data to identify candidate genes for complex diseases like CAD. Subsequent integration of drug-target data from drug databases with the predicted candidate genes can potentially identify novel therapeutics suitable for repositioning towards treatment of CAD.
Methods: Previously, we were able to predict 264 candidate genes and 104 potential therapeutic targets for CAD using Gentrepid (www.gentrepid.org), a candidate gene prediction platform with two bioinformatic modules to reanalyze Wellcome Trust Case-Control Consortium GWAS data. In an expanded study, using five bioinformatics modules on the same data, Gentrepid predicted 647 candidate genes and successfully replicated 55% of the candidate genes identified by the more powerful CARDIoGRAMplusC4D consortium meta-analysis. Hence, Gentrepid was capable of enhancing lower quality genotype-phenotype data, using an independent knowledgebase of existing biological data. Here, we used our methodology to integrate drug data from three drug databases: the Therapeutic Target Database, PharmGKB and Drug Bank, with the 647 candidate gene predictions from Gentrepid. We utilized known CAD targets, the scientific literature, existing drug data and the CARDIoGRAMplusC4D meta-analysis study as benchmarks to validate Gentrepid predictions for CAD.
Results: Our analysis identified a total of 184 predicted candidate genes as novel therapeutic targets for CAD, and 981 novel therapeutics feasible for repositioning in clinical trials towards treatment of CAD. The benchmarks based on known CAD targets and the scientific literature showed that our results were significant (p < 0.05).
Conclusions: We have demonstrated that available drugs may potentially be repositioned as novel therapeutics for the treatment of CAD. Drug repositioning can save valuable time and money spent on preclinical and phase I clinical studies.

Motivating undergraduate students via online learning to develop clinical competencies

Background: Online learning is becoming increasingly common for undergraduate health professions.Aims: To examine the effect of an online hypertension management module in motivating undergraduate pharmacystudents to further develop clinical competencies during future clinical placements.Method: The module focuses on approaches to counselling techniques for chronic disease management. It iscomplemented by therapeutics lectures, counselling tutorial and an objective structured clinical examination. A studentsurvey, constructed based on the Theory of Planned Behaviour, was undertaken after completion of the assessment.Results: Sixty two percent reported increased motivation to practice what they had learnt during placements, and amajority also reported improved attitudes and perceived self-efficacy. Levels of motivation had significant moderatecorrelations with improved appreciation of counselling techniques (r=0.489, p<0.001), and confidence to furtherpractice blood pressure counselling (r=0.411, p<0.001).Conclusion: Increased motivation to manage hypertension during future placements appears correlated with perceivedself-efficacy and engagement with the learning concepts.

Copper as a target for prostate cancer therapeutics: copper-ionophore pharmacology and altering systemic copper distribution

Copper-ionophores that elevate intracellular bioavailable copper display significant therapeutic utility against prostate cancer cells in vitro and in TRAMP (Transgenic Adenocarcinoma of Mouse Prostate) mice. However, the pharmacological basis for their anticancer activity remains unclear, despite impending clinical trails. Herein we show that intracellular copper levels in prostate cancer, evaluated in vitro and across disease progression in TRAMP mice, were not correlative with copper-ionophore activity and mirrored the normal levels observed in patient prostatectomy tissues (Gleason Score 7 & 9). TRAMP adenocarcinoma cells harbored markedly elevated oxidative stress and diminished glutathione (GSH)-mediated antioxidant capacity, which together conferred selective sensitivity to prooxidant ionophoric copper. Copper-ionophore treatments [CuII(gtsm), disulfiram & clioquinol] generated toxic levels of reactive oxygen species (ROS) in TRAMP adenocarcinoma cells, but not in normal mouse prostate epithelial cells (PrECs). Our results provide a basis for the pharmacological activity of copper-ionophores and suggest they are amendable for treatment of patients with prostate cancer. Additionally, recent in vitro and mouse xenograft studies have suggested an increased copper requirement by prostate cancer cells. We demonstrated that prostate adenocarcinoma development in TRAMP mice requires a functional supply of copper and is significantly impeded by altered systemic copper distribution. The presence of a mutant copper-transporting Atp7b protein (tx mutation: A4066G/Met1356Val) in TRAMP mice changed copper-integration into serum and caused a remarkable reduction in prostate cancer burden (64% reduction) and disease severity (grade), abrogating adenocarcinoma development. Implications for current clinical trials are discussed.

Novel therapeutics for complex diseases from genome-wide association data

The development of novel therapies is essential to lower the burden of complex diseases. The purpose of this study is to identify novel therapeutics for complex diseases using bioinformatic methods. Bioinformatic tools such as candidate gene prediction tools allow identification of disease genes by identifying the potential candidate genes linked to genetic markers of the disease. Candidate gene prediction tools can only identify candidates for further research, and do not identify disease genes directly. Integration of drug-target datasets with candidate gene data-sets can identify novel potential therapeutics suitable for repositioning in clinical trials. Drug repositioning can save valuable time and money spent in therapeutic development of complex diseases.