Active repurposing of drug candidates for melanoma based on GWAS, PheWAS and a wide range of omics data

Genomic strategies for drug repurposing

Functional genomics, a multidisciplinary subject, investigates the functions of genes and their products in biological systems to better understand diseases and find new drugs. Drug repurposing is an economically efficient approach that entails discovering novel therapeutic applications for already-available medications. Genomics enables the identification of illness and therapeutic molecular characteristics and interactions, which in turn facilitates the process of drug repurposing. Techniques like gene expression profiling and Mendelian randomization are helpful in identifying possible medication candidates. Progress in computer science allows for the investigation and modeling of gene expression networks that involve large amounts of data. The amalgamation of data concerning DNA, RNA, and protein functions bears similarity to pharmacogenomics, a crucial aspect in crafting cancer therapeutics. Functional genomics in drug discovery, particularly for cancer, is still not thoroughly investigated, despite the existence of a significant amount of literature on the subject. Next-generation sequencing and proteomics present highly intriguing opportunities. Publicly available databases and mining techniques facilitate the development of cancer treatments based on functional genomics. Broadening the exploration and utilization of functional genomics holds significant potential for advancing drug discovery and repurposing, particularly within the realm of oncology.

Genetic and Epigenetic Landscape for Drug Development in Polycystic Ovary Syndrome

The treatment of polycystic ovary syndrome (PCOS) faces challenges as all known treatments are merely symptomatic. The US Food and Drug Administration has not approved any drug specifically for treating PCOS. As the significance of genetics and epigenetics rises in drug development, their pivotal insights have greatly enhanced the efficacy and success of drug target discovery and validation, offering promise for guiding the advancement of PCOS treatments. In this context, we outline the genetic and epigenetic advancement in PCOS, which provide novel insights into the pathogenesis of this complex disease. We also delve into the prospective method for harnessing genetic and epigenetic strategies to identify potential drug targets and ensure target safety. Additionally, we shed light on the preliminary evidence and distinctive challenges associated with gene and epigenetic therapies in the context of PCOS.

Aspirin-Fisetin Combinatorial Treatment Exerts Cytotoxic and Anti-Migratory Activities in A375 Malignant Melanoma Cells

Background and Objectives: Malignant melanoma (MM) remains one of the most aggressive cancers worldwide, presenting a limited number of therapeutic options at present. Aspirin (ASA), a broadly used non-steroid anti-inflammatory medicine, has recently emerged as a candidate for repurposing in cancer management, due to its therapeutic potential in the treatment of several neoplasms which include MM. Fisetin (FIS) is a flavonoid phytoestrogen instilled with multispectral pharmacological activities, including a potent anti-melanoma property. The present study aimed to assess the potential improved anti-neoplastic effect resulting from the association of ASA and FIS for MM therapy. Materials and Methods: The study was conducted using the A375 cell line as an experimental model for MM. Cell viability was assessed via the MTT test. Cell morphology and confluence were evaluated using bright-field microscopy. The aspect of cell nuclei and tubulin fibers was observed through immunofluorescence staining. The irritant potential and the anti-angiogenic effect were determined on the chorioallantoic membrane of chicken fertilized eggs. Results: The main findings related herein demonstrated that the ASA 2.5 mM + FIS (5, 10, 15, and 20 µM) combination exerted a higher cytotoxicity in A375 MM cells compared to the individual compounds, which was outlined by the concentration-dependent and massive reduction in cell viability, loss of cell confluence, cell shrinkage and rounding, apoptotic-like nuclear features, constriction and disruption of tubulin filaments, increased apoptotic index, and suppressed migratory ability. ASA 2.5 mM + FIS 20 µM treatment lacked irritant potential on the chorioallantoic membrane and inhibited blood-vessel formation in ovo. Conclusion: These results stand as one of the first contributions presenting the anti-melanoma effect of the ASA + FIS combinatorial treatment.

Novel strategies for drug repurposing

Synthetic biology, precision medicine, and nanobiotechnology are the three main emerging areas that drive translational innovation toward commercialization. There are several strategies used in precision medicine and drug repurposing is one of the key approaches as it addresses the challenges in drug discovery (high cost and time). Here, we provide a perspective on various new approaches to drug repurposing for cancer precision medicine. We report here our optimized wound healing methodology that can be used to validate drug sensitivity and drug repurposing. Using HeLa as our benchmark, we demonstrated that the assay can be applied to identify drugs that limit cell proliferation. From a future perspective, this assay can be expanded to ex vivo culturing of solid tumors in 2D culture and leukemia in 3D culture.

The landscape of the methodology in drug repurposing using human genomic data: a systematic review

The process of drug development is expensive and time-consuming. In contrast, drug repurposing can be introduced to clinical practice more quickly and at a reduced cost. Over the last decade, there has been a significant expansion of large biobanks that link genomic data to electronic health record data, public availability of various databases containing biological and clinical information and rapid development of novel methodologies and algorithms in integrating different sources of data. This review aims to provide a thorough summary of different strategies that utilize genomic data to seek drug-repositioning opportunities. We searched MEDLINE and EMBASE databases to identify eligible studies up until 1 May 2023, with a total of 102 studies finally included after two-step parallel screening. We summarized commonly used strategies for drug repurposing, including Mendelian randomization, multi-omic-based and network-based studies and illustrated each strategy with examples, as well as the data sources implemented. By leveraging existing knowledge and infrastructure to expedite the drug discovery process and reduce costs, drug repurposing potentially identifies new therapeutic uses for approved drugs in a more efficient and targeted manner. However, technical challenges when integrating different types of data and biased or incomplete understanding of drug interactions are important hindrances that cannot be disregarded in the pursuit of identifying novel therapeutic applications. This review offers an overview of drug repurposing methodologies, providing valuable insights and guiding future directions for advancing drug repurposing studies.

Analysis of differential gene immune infiltration and clinical characteristics of skin cutaneous melanoma based on systems biology and drug repositioning methods to identify drug candidates for skin cutaneous melanoma

Skin cutaneous melanoma (SKCM) has a low early detection rate and a high mortality rate. There are many problems such as side effects and drug resistance in existing therapeutic drugs. Current studies have confirmed that SKCM pathogenesis-related genes promote the invasion and metastasis of cutaneous melanoma, but their roles in the tumor microenvironment (TME) remain unclear. Network pharmacology provides new opportunities for drug repurposing and repositioning, and is a fast, safe, and inexpensive drug discovery method to find new drugs for the treatment of SKCM. In this study, based on 3 databases (KEGG, OMIM, and Genotype) to obtain SKCM-related genes, and TCGA SKCM dataset, SKCM differential genes in GSE3189 and GSE46517 were intersected to identify SKCM pathogenesis-related differential genes, and the differential genes were immune infiltration and analysis, For survival analysis, a prognostic nomogram risk model was constructed based on the results of multivariate Cox regression analysis for risk stratification and prognosis prediction, then focused on the differential expression of ZC3H12A and its effect on TME. Finally, the protein interaction network method was used to quantify the similarity between 684 drug targets and skin melanoma, and to screen out drugs similar to skin melanoma. Based on 3 databases of KEGG, OMIM, and Genotype, 294 SKCM-related genes and 18 SKCM pathogenesis-related differential genes were obtained, and 18 SKCM pathogenesis-related differential genes were significantly correlated with TME. The constructed prognostic nomogram risk model predicted performance better and provided valuable information for immunotherapy. Multivariate Cox regression analysis and K-M analysis showed that ZC3H12A was a differentially expressed gene affecting the prognosis of SKCM and promoted the infiltration of anti-tumor immune cells CD8 + T cells, B cells, and DC cells. Based on the analysis of the protein interaction network method, 43 drugs were found to have high potential in the treatment of SKCM, and the literature search of these 43 drugs was carried out, and 21 drugs were found to have experimental verification for the treatment of SKCM. Taken together, the differential genes associated with the pathogenesis of SKCM have important roles in the tumor immune microenvironment, clinicopathological features, and prognosis, especially ZC3H12A has a potential role in identifying early SKCM patients. At the same time, it provides a new strategy for the drug development of SKCM and provides a basis for the reuse of SKCM drugs.

Oncogenic signaling pathways and hallmarks of cancer in Korean patients with acral melanoma

Acral melanoma (AM), a rare subtype of cutaneous melanoma, shows higher incidence in Asians, including Koreans, than in Caucasians. However, the genetic modification associated with AM in Koreans is not well known and has not been comprehensively investigated in terms of oncogenic signaling, and hallmarks of cancer. We performed whole-exome and RNA sequencing for Korean patients with AM and acquired the genetic alterations and gene expression profiles. KIT alterations (previously known to be recurrent alterations in AM) and CDK4/CCND1 copy number amplifications were identified in the patients. Genetic and transcriptomic alterations in patients with AM were functionally converge to the hallmarks of cancer and oncogenic pathways, including 'proliferative signal persistence', 'apoptotic resistance', and 'activation of invasion and metastasis', despite the heterogeneous somatic mutation profiles of Korean patients with AM. This study may provide a molecular understanding for therapeutic strategy for AM.

Melanoma 2.0. Skin cancer as a paradigm for emerging diagnostic technologies, computational modelling and artificial intelligence

We live in an unprecedented time in oncology. We have accumulated samples and cases in cohorts larger and more complex than ever before. New technologies are available for quantifying solid or liquid samples at the molecular level. At the same time, we are now equipped with the computational power necessary to handle this enormous amount of quantitative data. Computational models are widely used helping us to substantiate and interpret data. Under the label of systems and precision medicine, we are putting all these developments together to improve and personalize the therapy of cancer. In this review, we use melanoma as a paradigm to present the successful application of these technologies but also to discuss possible future developments in patient care linked to them. Melanoma is a paradigmatic case for disruptive improvements in therapies, with a considerable number of metastatic melanoma patients benefiting from novel therapies. Nevertheless, a large proportion of patients does not respond to therapy or suffers from adverse events. Melanoma is an ideal case study to deploy advanced technologies not only due to the medical need but also to some intrinsic features of melanoma as a disease and the skin as an organ. From the perspective of data acquisition, the skin is the ideal organ due to its accessibility and suitability for many kinds of advanced imaging techniques. We put special emphasis on the necessity of computational strategies to integrate multiple sources of quantitative data describing the tumour at different scales and levels.

Current Knowledge in Skin Metabolomics: Updates from Literature Review

Metabolomic profiling is an emerging field consisting of the measurement of metabolites in a biological system. Since metabolites can vary in relation to different stimuli, specific metabolic patterns can be closely related to a pathological process. In the dermatological setting, skin metabolomics can provide useful biomarkers for the diagnosis, prognosis, and therapy of cutaneous disorders. The main goal of the present review is to present a comprehensive overview of the published studies in skin metabolomics. A search for journal articles focused on skin metabolomics was conducted on the MEDLINE, EMBASE, Cochrane, and Scopus electronic databases. Only research articles with electronically available English full text were taken into consideration. Studies specifically focused on cutaneous microbiomes were also excluded from the present search. A total of 97 papers matched all the research criteria and were therefore considered for the present work. Most of the publications were focused on inflammatory dermatoses and immune-mediated cutaneous disorders. Skin oncology also turned out to be a relevant field in metabolomic research. Only a few papers were focused on infectious diseases and rarer genetic disorders. All the major metabolomic alterations published so far in the dermatological setting are described extensively in this review.

StarGazer: A Hybrid Intelligence Platform for Drug Target Prioritization and Digital Drug Repositioning Using Streamlit

Target prioritization is essential for drug discovery and repositioning. Applying computational methods to analyze and process multi-omics data to find new drug targets is a practical approach for achieving this. Despite an increasing number of methods for generating datasets such as genomics, phenomics, and proteomics, attempts to integrate and mine such datasets remain limited in scope. Developing hybrid intelligence solutions that combine human intelligence in the scientific domain and disease biology with the ability to mine multiple databases simultaneously may help augment drug target discovery and identify novel drug-indication associations. We believe that integrating different data sources using a singular numerical scoring system in a hybrid intelligent framework could help to bridge these different omics layers and facilitate rapid drug target prioritization for studies in drug discovery, development or repositioning. Herein, we describe our prototype of the StarGazer pipeline which combines multi-source, multi-omics data with a novel target prioritization scoring system in an interactive Python-based Streamlit dashboard. StarGazer displays target prioritization scores for genes associated with 1844 phenotypic traits, and is available via https://github.com/AstraZeneca/StarGazer.

The Anticancer Potential of Doxycycline and Minocycline-A Comparative Study on Amelanotic Melanoma Cell Lines

Malignant melanoma is still a serious medical problem. Relatively high mortality, a still-growing number of newly diagnosed cases, and insufficiently effective methods of therapy necessitate melanoma research. Tetracyclines are compounds with pleiotropic pharmacological properties. Previously published studies on melanotic melanoma cells ascertained that minocycline and doxycycline exerted an anti-melanoma effect. The purpose of the study was to assess the anti-melanoma potential and mechanisms of action of minocycline and doxycycline using A375 and C32 human amelanotic melanoma cell lines. The obtained results indicate that the tested drugs inhibited proliferation, decreased cell viability, and induced apoptosis in amelanotic melanoma cells. The treatment caused changes in the cell cycle profile and decreased the intracellular level of reduced thiols and mitochondrial membrane potential. The exposure of A375 and C32 cells to minocycline and doxycycline triggered the release of cytochrome c and activated initiator and effector caspases. The anti-melanoma effect of analyzed drugs appeared to be related to the up-regulation of ERK1/2 and MITF. Moreover, it was noticed that minocycline and doxycycline increased the level of LC3A/B, an autophagy marker, in A375 cells. In summary, the study showed the pleiotropic anti-cancer action of minocycline and doxycycline against amelanotic melanoma cells. Considering all results, it could be concluded that doxycycline was a more potent drug than minocycline.

Drug Repurposing in Oncology, an Attractive Opportunity for Novel Combinatorial Regimens

The costs of developing, validating and buying new drugs are dramatically increasing. On the other hand, sobering economies have difficulties in sustaining their healthcare systems, particularly in countries with an elderly population requiring increasing welfare. This conundrum requires immediate action, and a possible option is to study the large, already present arsenal of drugs approved and to use them for innovative therapies. This possibility is particularly interesting in oncology, where the complexity of the cancer genome dictates in most patients a multistep therapeutic approach. In this review, we discuss a) Computational approaches; b) preclinical models; c) currently ongoing or already published clinical trials in the drug repurposing field in oncology; and d) drug repurposing to overcome resistance to previous therapies.

Repurposing of Drug Candidates for Treatment of Skin Cancer

Skin cancers are highly prevalent malignancies that affect millions of people worldwide. These include melanomas and nonmelanoma skin cancers. Melanomas are among the most dangerous cancers, while nonmelanoma skin cancers generally exhibit a more benign clinical pattern; however, they may sometimes be aggressive and metastatic. Melanomas typically appear in body regions exposed to the sun, although they may also appear in areas that do not usually get sun exposure. Thus, their development is multifactorial, comprising endogenous and exogenous risk factors. The management of skin cancer depends on the type; it is usually based on surgery, chemotherapy, immunotherapy, and targeted therapy. In this respect, oncological treatments have demonstrated some progress in the last years; however, current therapies still present various disadvantages such as little cell specificity, recurrent relapses, high toxicity, and increased costs. Furthermore, the pursuit of novel medications is expensive, and the authorization for their clinical utilization may take 10-15 years. Thus, repositioning of drugs previously approved and utilized for other diseases has emerged as an excellent alternative. In this mini-review, we aimed to provide an updated overview of drugs' repurposing to treat skin cancer and discuss future perspectives.

Nano-ellagic acid: inhibitory actions on aldose reductase and α-glucosidase in secondary complications of diabetes, strengthened by in silico docking studies

Increased blood sugar levels in prolonged diabetes lead to secondary complications such as retinopathy, neuropathy, and nephropathy, which gradually end in death. Synthesis of nano-phytomedicines from active phytoconstituents for novel emerging applications in the field of pharmaceuticals is of huge interest among researchers. In the present investigation, encapsulated ellagic acid (NEA) was synthesized at four different concentrations (0.2%, 0.3%, 0.4%, 0.5%) using ZnO nanoparticles as encapsulating agent. The surface morphology (fiber-like structures) of the nanoparticles were determined by scanning electron microscopy (SEM) and particle size (161-297 nm) and zeta potential (- 54.9-38.4 mV) were determined by dynamic light scattering technique. Further, the α-glucosidase and aldose reductase enzymes were significantly inhibited by the 0.4% of NEA compared to the other concentrations which strengthened our studies in overcoming the secondary complications of diabetes. The interaction analysis between ellagic acid and insulin receptor found Hit 1 among 10 executed ∆G score and energy of - 5.76, - 4.63 kcal/mol and formed polar bond with Arg 113 with - 1.175 Å distance. The residues Arg115, Lys116, Phe118, Ile115, Arg1131, Arg1155, Ile1157, Lys1165 and Phe1186 were found in ligand-protein interactions. ADME/T analysis of hit 1 was within the acceptable range without any toxic functional groups, providing a framework for developing novel therapeutics.

Drug Research Meets Network Science: Where Are We?

Network theory provides one of the most potent analysis tools for the study of complex systems. In this paper, we illustrate the network-based perspective in drug research and how it is coherent with the new paradigm of drug discovery. We first present data sources from which networks are built, then show some examples of how the networks can be used to investigate drug-related systems. A section is devoted to network-based inference applications, i.e., prediction methods based on interactomes, that can be used to identify putative drug-target interactions without resorting to 3D modeling. Finally, we present some aspects of Boolean networks dynamics, anticipating that it might become a very potent modeling framework to develop in silico screening protocols able to simulate phenotypic screening experiments. We conclude that network applications integrated with machine learning and 3D modeling methods will become an indispensable tool for computational drug discovery in the next years.

Drug targets for COVID-19 therapeutics: Ongoing global efforts

The current global pandemic COVID-19 caused by the SARS-CoV-2 virus has already inflicted insurmountable damage both to the human lives and global economy. There is an immediate need for identification of effective drugs to contain the disastrous virus outbreak. Global efforts are already underway at a war footing to identify the best drug combination to address the disease. In this review, an attempt has been made to understand the SARS-CoV-2 life cycle, and based on this information potential druggable targets against SARS-CoV-2 are summarized. Also, the strategies for ongoing and future drug discovery against the SARS-CoV-2 virus are outlined. Given the urgency to find a definitive cure, ongoing drug repurposing efforts being carried out by various organizations are also described. The unprecedented crisis requires extraordinary efforts from the scientific community to effectively address the issue and prevent further loss of human lives and health.

Repurposing Drugs for Skin Cancer

Drug repurposing is the process of developing existing or abandoned drugs for a different disease. Repurposing can circumvent higher costs and times associated with conventional drug discovery strategies because toxicity and pharmacokinetics profiles are typically already established. This brief review focuses on efforts to repurpose drugs for skin cancer and includes reuse of antihypertensives, anthelmintics and antifungals among a range of other medicines. Repurposing not only ushers promising known drugs for new indications, the process of repurposing can uncover new mechanistic insights in the pathogenesis of disease and uncover new opportunities for pharmaceutical intervention.