Deciphering the molecular mechanism and crosstalk between Parkinson's disease and breast cancer through multi-omics and drug repurposing approach

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.

IUPHAR review - Data-driven computational drug repurposing approaches for opioid use disorder

Opioid Use Disorder (OUD) is a chronic and relapsing condition characterized by the misuse of opioid drugs, causing significant morbidity and mortality in the United States. Existing medications for OUD are limited, and there is an immediate need to discover treatments with enhanced safety and efficacy. Drug repurposing aims to find new indications for existing medications, offering a time-saving and cost-efficient alternative strategy to traditional drug discovery. Computational approaches have been developed to further facilitate the drug repurposing process. In this paper, we reviewed state-of-the-art data-driven computational drug repurposing approaches for OUD and discussed their advantages and potential challenges. We also highlighted promising repurposed candidate drugs for OUD that were identified by computational drug repurposing techniques and reviewed studies supporting their potential mechanisms of action in treating OUD.

Dissecting the functional significance of HSP90AB1 and other heat shock proteins in countering glioblastomas and ependymomas using omics analysis and drug prediction using virtual screening

Heat shock proteins (HSPs) are the evolutionary family of proteins that are highly conserved and present widely in various organisms and play an array of important roles and cellular functions. Currently, very few or no studies are based on the systematic analysis of the HSPs in Glioblastoma (GBMs) and ependymomas. We performed an integrated omics analysis to predict the mutual regulatory differential HSP signatures that were associated with both glioblastoma and ependymomas. Further, we explored the various common dysregulated biological processes operating in both the tumors, and were analyzed using functional enrichment, gene ontology along with the pathway analysis of the predicted HSPs. We established an interactome network of protein-protein interaction (PPIN) to identify the hub HSPs that were commonly associated with GBMs and ependymoma. To understand the mutual molecular mechanism of the HSPs in both malignancies, transcription factors, and miRNAs overlapping with both diseases were explored. Moreover, a transcription factor-miRNAs-HSPs coregulatory network was constructed along with the prediction of potential candidate drugs that were based on perturbation-induced gene expression analysis. Based on the RNA-sequencing data, HSP90AB1 was identified as the most promising target among other predicted HSPs. Finally, the ranking of the drugs was arranged based on various drug scores. In conclusion, this study gave a spotlight on the mutual targetable HSPs, biological pathways, and regulatory signatures associated with GBMs and ependymoma with an improved understanding of crosstalk involved. Additionally, the role of therapeutics was also explored against HSP90AB1. These findings could potentially be able to explain the interplay of HSP90AB1 and other HSPs within these two malignancies.

Apoptosis Genes as a Key to Identification of Inverse Comorbidity of Huntington's Disease and Cancer

Cancer and neurodegenerative disorders present overwhelming challenges for healthcare worldwide. Epidemiological studies showed a decrease in cancer rates in patients with neurodegenerative disorders, including the Huntington disease (HD). Apoptosis is one of the most important processes for both cancer and neurodegeneration. We suggest that genes closely connected with apoptosis and associated with HD may affect carcinogenesis. We applied reconstruction and analysis of gene networks associated with HD and apoptosis and identified potentially important genes for inverse comorbidity of cancer and HD. The top 10 high-priority candidate genes included APOE, PSEN1, INS, IL6, SQSTM1, SP1, HTT, LEP, HSPA4, and BDNF. Functional analysis of these genes was carried out using gene ontology and KEGG pathways. By exploring genome-wide association study results, we identified genes associated with neurodegenerative and oncological disorders, as well as their endophenotypes and risk factors. We used publicly available datasets of HD and breast and prostate cancers to analyze the expression of the identified genes. Functional modules of these genes were characterized according to disease-specific tissues. This integrative approach revealed that these genes predominantly exert similar functions in different tissues. Apoptosis along with lipid metabolism dysregulation and cell homeostasis maintenance in the response to environmental stimulus and drugs are likely key processes in inverse comorbidity of cancer in patients with HD. Overall, the identified genes represent the promising targets for studying molecular relations of cancer and HD.