Transcriptomic-Guided Drug Repositioning Supported by a New Bioinformatics Search Tool: geneXpharma

Integrated systems biology analysis of acute lymphoblastic leukemia: unveiling molecular signatures and drug repurposing opportunities

Acute lymphoblastic leukemia (ALL) is a hematological malignancy characterized by aberrant proliferation and accumulation of lymphoid precursor cells within the bone marrow. The tyrosine kinase inhibitor (TKI), imatinib mesylate, has played a significant role in the treatment of Philadelphia chromosome-positive ALL (Ph + ALL). However, the achievement of durable and sustained therapeutic success remains a challenge due to the development of TKI resistance during the clinical course.The primary objective of this investigation is to propose a novel and efficacious treatment approach through drug repositioning, targeting ALL and its Ph + subtype by identifying and addressing differentially expressed genes (DEGs). This study involves a comprehensive analysis of transcriptome datasets pertaining to ALL and Ph + ALL in order to identify DEGs associated with the progression of these diseases to identify possible repurposable drugs that target identified hub proteins.The outcomes of this research have unveiled 698 disease-related DEGs for ALL and 100 for Ph + ALL. Furthermore, a subset of drugs, specifically glipizide for Ph + ALL, and maytansine and isoprenaline for ALL, have been identified as potential candidates for therapeutic intervention. Subsequently, cytotoxicity assessments were performed to confirm the in vitro cytotoxic effects of these selected drugs on both ALL and Ph + ALL cell lines.In conclusion, this study offers a promising avenue for the management of ALL and Ph + ALL through drug repurposed drugs. Further investigations are necessary to elucidate the mechanisms underlying cell death, and clinical trials are recommended to validate the promising results obtained through drug repositioning strategies.

Exploring cutting-edge strategies for drug repurposing in female cancers - An insight into the tools of the trade

Female cancers, which include breast and gynaecological cancers, represent a significant global health burden for women. Despite advancements in research pertinent to unearthing crucial pathological characteristics of these cancers, challenges persist in discovering potential therapeutic strategies. This is further exacerbated by economic burdens associated with de novo drug discovery and clinical intricacies such as development of drug resistance and metastasis. Drug repurposing, an innovative approach leveraging existing FDA-approved drugs for new indications, presents a promising avenue to expedite therapeutic development. Computational techniques, including virtual screening and analysis of drug-target-disease relationships, enable the identification of potential candidate drugs. Integration of diverse data types, such as omics and clinical information, enhances the precision and efficacy of drug repurposing strategies. Experimental approaches, including high-throughput screening assays, in vitro, and in vivo models, complement computational methods, facilitating the validation of repurposed drugs. This review highlights various target mining strategies based on analysis of differential gene expression, weighted gene co-expression, protein-protein interaction network, and host-pathogen interaction, among others. To unearth drug candidates, the technicalities of leveraging information from databases such as DrugBank, STITCH, LINCS, and ChEMBL, among others are discussed. Further in silico validation techniques encompassing molecular docking, pharmacophore modelling, molecular dynamic simulations, and ADMET analysis are elaborated. Overall, this review delves into the exploration of individual case studies to offer a wide perspective of the ever-evolving field of drug repurposing, emphasizing the multifaceted approaches and methodologies employed for the same to confront female cancers.

Comparative analysis of diisononyl phthalate and di(isononyl)cyclohexane-1,2 dicarboxylate plasticizers in regulation of lipid metabolism in 3T3-L1 cells

Diisononyl phthalate (DINP) and di(isononyl)cyclohexane-1,2-dicarboxylate (DINCH) are plasticizers introduced to replace previously used phthalate plasticizers in polymeric products. Exposure to DINP and DINCH has been shown to impact lipid metabolism. However, there are limited studies that address the mechanisms of toxicity of these two plasticizers. Here, a comparative toxicity analysis has been performed to evaluate the impacts of DINP and DINCH on 3T3-L1 cells. The preadipocyte 3T3-L1 cells were exposed to 1, 10, and 100 μM of DINP or DINCH for 10 days and assessed for lipid accumulation, gene expression, and protein analysis. Lipid staining showed that higher concentrations of DINP and DINCH can induce adipogenesis. The gene expression analysis demonstrated that both DINP and DINCH could alter the expression of lipid-related genes involved in adipogenesis. DINP and DINCH upregulated Pparγ, Pparα, C/EBPα Fabp4, and Fabp5, while both compounds significantly downregulated Fasn and Gata2. Protein analysis showed that both DINP and DINCH repressed the expression of FASN. Additionally, we analyzed an independent transcriptome dataset encompassing temporal data on lipid differentiation within 3T3-L1 cells. Subsequently, we derived a gene set that accurately portrays significant pathways involved in lipid differentiation, which we subsequently subjected to experimental validation through quantitative polymerase chain reaction. In addition, we extended our analysis to encompass a thorough assessment of the expression profiles of this identical gene set across 40 discrete transcriptome datasets that have linked to diverse pathological conditions to foreseen any potential association with DINP and DINCH exposure. Comparative analysis indicated that DINP could be more effective in regulating lipid metabolism.

PaSTe. Blockade of the Lipid Phenotype of Prostate Cancer as Metabolic Therapy: A Theoretical Proposal

BACKGROUND

Prostate cancer is the most frequently diagnosed malignancy in 112 countries and is the leading cause of death in eighteen. In addition to continuing research on prevention and early diagnosis, improving treatments and making them more affordable is imperative. In this sense, the therapeutic repurposing of low-cost and widely available drugs could reduce global mortality from this disease. The malignant metabolic phenotype is becoming increasingly important due to its therapeutic implications. Cancer generally is characterized by hyperactivation of glycolysis, glutaminolysis, and fatty acid synthesis. However, prostate cancer is particularly lipidic; it exhibits increased activity in the pathways for synthesizing fatty acids, cholesterol, and fatty acid oxidation (FAO).

OBJECTIVE

Based on a literature review, we propose the PaSTe regimen (Pantoprazole, Simvastatin, Trimetazidine) as a metabolic therapy for prostate cancer. Pantoprazole and simvastatin inhibit the enzymes fatty acid synthase (FASN) and 3-hydroxy-3-methylglutaryl- coenzyme A reductase (HMGCR), therefore, blocking the synthesis of fatty acids and cholesterol, respectively. In contrast, trimetazidine inhibits the enzyme 3-β-Ketoacyl- CoA thiolase (3-KAT), an enzyme that catalyzes the oxidation of fatty acids (FAO). It is known that the pharmacological or genetic depletion of any of these enzymes has antitumor effects in prostatic cancer.

RESULTS

Based on this information, we hypothesize that the PaSTe regimen will have increased antitumor effects and may impede the metabolic reprogramming shift. Existing knowledge shows that enzyme inhibition occurs at molar concentrations achieved in plasma at standard doses of these drugs.

CONCLUSION

We conclude that this regimen deserves to be preclinically evaluated because of its clinical potential for the treatment of prostate cancer.

Immune cell-specific and common molecular signatures in rheumatoid arthritis through molecular network approaches

Rheumatoid arthritis (RA) is an autoimmune disorder and common symptom of RA is chronic synovial inflammation. The pathogenesis of RA is not fully understood. Therefore, we aimed to identify underlying common and distinct molecular signatures and pathways among ten types of tissue and cells obtained from patients with RA. In this study, transcriptomic data including synovial tissues, macrophages, blood, T cells, CD4+T cells, CD8+T cells, natural killer T (NKT), cells natural killer (NK) cells, neutrophils, and monocyte cells were analyzed with an integrative and comparative network biology perspective. Each dataset yielded a list of differentially expressed genes as well as a reconstruction of the tissue-specific protein-protein interaction (PPI) network. Molecular signatures were identified by a statistical test using the hypergeometric probability density function by employing the interactions of transcriptional regulators and PPI. Reporter metabolites of each dataset were determined by using genome-scale metabolic networks. It was defined as the common hub proteins, novel molecular signatures, and metabolites in two or more tissue types while immune cell-specific molecular signatures were identified, too. Importantly, miR-155-5p is found as a common miRNA in all tissues. Moreover, NCOA3, PRKDC and miR-3160 might be novel molecular signatures for RA. Our results establish a novel approach for identifying immune cell-specific molecular signatures of RA and provide insights into the role of common tissue-specific genes, miRNAs, TFs, receptors, and reporter metabolites. Experimental research should be used to validate the corresponding genes, miRNAs, and metabolites.

Epigenomic and transcriptomic landscaping unraveled candidate repositioned therapeutics for non-functioning pituitary neuroendocrine tumors

PURPOSE

Non-functioning pituitary neuroendocrine tumors are challengingly diagnosed tumors in the clinic. Transsphenoidal surgery remains the first-line treatment. Despite the development of state-of-the-art techniques, no drug therapy is currently approved for the treatment. There are also no randomized controlled trials comparing therapeutic strategies or drug therapy for the management after surgery. Therefore, novel therapeutic interventions for the therapeutically challenging NF-PitNETs are urgently needed.

METHODS

We integrated epigenome and transcriptome data (both coding and non-coding) that elucidate disease-specific signatures, in addition to biological and pharmacological data, to utilize rational pathway and drug prioritization in NF-PitNETs. We constructed an epigenome- and transcriptome-based PPI network and proposed hub genes. The signature-based drug repositioning based on the integration of multi-omics data was performed.

RESULTS

The construction of a disease-specific network based on three different biological levels revealed DCC, DLG5, ETS2, FOXO1, HBP1, HMGA2, PCGF3, PSME4, RBPMS, RREB1, SMAD1, SOCS1, SOX2, YAP1, ZFHX3 as hub proteins. Signature-based drug repositioning using hub proteins yielded repositioned drug candidates that were confirmed in silico via molecular docking. As a result of molecular docking simulations, palbociclib, linifanib, trametinib, eplerenone, niguldipine, and zuclopenthixol showed higher binding affinities with hub genes compared to their inhibitors and were proposed as potential repositioned therapeutics for the management of NF-PitNETs.

CONCLUSION

The proposed systems' biomedicine-oriented multi-omics data integration for drug repurposing to provide promising results for the construction of effective clinical therapeutics. To the best of our knowledge, this is the first study reporting epigenome- and transcriptome-based drug repositioning for NF-PitNETs using in silico confirmations.

Drug repositioning via host-pathogen protein-protein interactions for the treatment of cervical cancer

Introduction

Integrating interaction data with biological knowledge can be a critical approach for drug development or drug repurposing. In this context, host-pathogen-protein-protein interaction (HP-PPI) networks are useful instrument to uncover the phenomena underlying therapeutic effects in infectious diseases, including cervical cancer, which is almost exclusively due to human papillomavirus (HPV) infections. Cervical cancer is one of the second leading causes of death, and HPV16 and HPV18 are the most common subtypes worldwide. Given the limitations of traditionally used virus-directed drug therapies for infectious diseases and, at the same time, recent cancer statistics for cervical cancer cases, the need for innovative treatments becomes clear.

Methods

Accordingly, in this study, we emphasize the potential of host proteins as drug targets and identify promising host protein candidates for cervical cancer by considering potential differences between HPV subtypes (i.e., HPV16 and HPV18) within a novel bioinformatics framework that we have developed. Subsequently, subtype-specific HP-PPI networks were constructed to obtain host proteins. Using this framework, we next selected biologically significant host proteins. Using these prominent host proteins, we performed drug repurposing analysis. Finally, by following our framework we identify the most promising host-oriented drug candidates for cervical cancer.

Results

As a result of this framework, we discovered both previously associated and novel drug candidates, including interferon alfacon-1, pimecrolimus, and hyaluronan specifically for HPV16 and HPV18 subtypes, respectively.

Discussion

Consequently, with this study, we have provided valuable data for further experimental and clinical efforts and presented a novel bioinformatics framework that can be applied to any infectious disease.

Repositioning of Anti-Inflammatory Drugs for the Treatment of Cervical Cancer Sub-Types

Cervical cancer is the fourth most commonly diagnosed cancer worldwide and, in almost all cases is caused by infection with highly oncogenic Human Papillomaviruses (HPVs). On the other hand, inflammation is one of the hallmarks of cancer research. Here, we focused on inflammatory proteins that classify cervical cancer patients by considering individual differences between cancer patients in contrast to conventional treatments. We repurposed anti-inflammatory drugs for therapy of HPV-16 and HPV-18 infected groups, separately. In this study, we employed systems biology approaches to unveil the diagnostic and treatment options from a precision medicine perspective by delineating differential inflammation-associated biomarkers associated with carcinogenesis for both subtypes. We performed a meta-analysis of cervical cancer-associated transcriptomic datasets considering subtype differences of samples and identified the differentially expressed genes (DEGs). Using gene signature reversal on HPV-16 and HPV-18, we performed both signature- and network-based drug reversal to identify anti-inflammatory drug candidates against inflammation-associated nodes. The anti-inflammatory drug candidates were evaluated using molecular docking to determine the potential of physical interactions between the anti-inflammatory drug and inflammation-associated nodes as drug targets. We proposed 4 novels anti-inflammatory drugs (AS-601245, betamethasone, narciclasin, and methylprednisolone) for the treatment of HPV-16, 3 novel drugs for the treatment of HPV-18 (daphnetin, phenylbutazone, and tiaprofenoic acid), and 5 novel drugs (aldosterone, BMS-345541, etodolac, hydrocortisone, and prednisolone) for the treatment of both subtypes. We proposed anti-inflammatory drug candidates that have the potential to be therapeutic agents for the prevention and/or treatment of cervical cancer.

Past, Present, and Future of Therapies for Pituitary Neuroendocrine Tumors: Need for Omics and Drug Repositioning Guidance

Innovation roadmaps are important, because they encourage the actors in an innovation ecosystem to creatively imagine multiple possible science future(s), while anticipating the prospects and challenges on the innovation trajectory. In this overarching context, this expert review highlights the present unmet need for therapeutic innovations for pituitary neuroendocrine tumors (PitNETs), also known as pituitary adenomas. Although there are many drugs used in practice to treat PitNETs, many of these drugs can have negative side effects and show highly variable outcomes in terms of overall recovery. Building innovation roadmaps for PitNETs' treatments can allow incorporation of systems biology approaches to bring about insights at multiple levels of cell biology, from genes to proteins to metabolites. Using the systems biology techniques, it will then be possible to offer potential therapeutic strategies for the convergence of preventive approaches and patient-centered disease treatment. Here, we first provide a comprehensive overview of the molecular subtypes of PitNETs and therapeutics for these tumors from the past to the present. We then discuss examples of clinical trials and drug repositioning studies and how multi-omics studies can help in discovery and rational development of new therapeutics for PitNETs. Finally, this expert review offers new public health and personalized medicine approaches on cases that are refractory to conventional treatment or recur despite currently used surgical and/or drug therapy.

Overcoming Drug Resistance in Advanced Prostate Cancer by Drug Repurposing

Prostate cancer (PCa) is the second most common cancer in men. Common treatments include active surveillance, surgery, or radiation. Androgen deprivation therapy and chemotherapy are usually reserved for advanced disease or biochemical recurrence, such as castration-resistant prostate cancer (CRPC), but they are not considered curative because PCa cells eventually develop drug resistance. The latter is achieved through various cellular mechanisms that ultimately circumvent the pharmaceutical’s mode of action. The need for novel therapeutic approaches is necessary under these circumstances. An alternative way to treat PCa is by repurposing of existing drugs that were initially intended for other conditions. By extrapolating the effects of previously approved drugs to the intracellular processes of PCa, treatment options will expand. In addition, drug repurposing is cost-effective and efficient because it utilizes drugs that have already demonstrated safety and efficacy. This review catalogues the drugs that can be repurposed for PCa in preclinical studies as well as clinical trials.

MicroRNA-Mediated Drug Repurposing Unveiled Potential Candidate Drugs for Prolactinoma Treatment

INTRODUCTION

Prolactinomas, also called lactotroph adenomas, are the most encountered type of hormone-secreting pituitary neuroendocrine tumors in the clinic. The preferred first-line therapy is a medical treatment with dopamine agonists (DAs), mainly cabergoline, to reduce serum prolactin levels, tumor volume, and mass effect. However, in some cases, patients have displayed DA resistance with aggressive tumor behavior or are faced with recurrence after drug withdrawal. Also, currently used therapeutics have notorious side effects and impair the life quality of the patients.

METHODS

Since the amalgamation of clinical and laboratory data besides tumor histopathogenesis and transcriptional regulatory features of the tumor emerges to exhibit essential roles in the behavior and progression of prolactinomas; in this work, we integrated mRNA- and microRNA (miRNA)-level transcriptome data that exploit disease-specific signatures in addition to biological and pharmacological data to elucidate a rational prioritization of pathways and drugs in prolactinoma.

RESULTS

We identified 8 drug candidates through drug repurposing based on mRNA-miRNA-level data integration and evaluated their potential through in vitro assays in the MMQ cell line. Seven repurposed drugs including 5-fluorocytosine, nortriptyline, neratinib, puromycin, taxifolin, vorinostat, and zileuton were proposed as potential drug candidates for the treatment of prolactinoma. We further hypothesized possible mechanisms of drug action on MMQ cell viability through analyzing the PI3K/Akt signaling pathway and cell cycle arrest via flow cytometry and Western blotting.

DISCUSSION

We presented the transcriptomic landscape of prolactinoma through miRNA and mRNA-level data integration and proposed repurposed drug candidates based on this integration. We validated our findings through testing cell viability, cell cycle phases, and PI3K/Akt protein expressions. Effects of the drugs on cell cycle phases and inhibition of the PI3K/Akt pathway by all drugs gave us promising output for further studies using these drugs in the treatment of prolactinoma. This is the first study that reports miRNA-mediated repurposed drugs for prolactinoma treatment via in vitro experiments.

Differential Interactome Based Drug Repositioning Unraveled Abacavir, Exemestane, Nortriptyline Hydrochloride, and Tolcapone as Potential Therapeutics for Colorectal Cancers

There is a critical requirement for alternative strategies to provide the better treatment in colorectal cancer (CRC). Hence, our goal was to propose novel biomarkers as well as drug candidates for its treatment through differential interactome based drug repositioning. Differentially interacting proteins and their modules were identified, and their prognostic power were estimated through survival analyses. Drug repositioning was carried out for significant target proteins, and candidate drugs were analyzed via in silico molecular docking prior to in vitro cell viability assays in CRC cell lines. Six modules (mAPEX1, mCCT7, mHSD17B10, mMYC, mPSMB5, mRAN) were highlighted considering their prognostic performance. Drug repositioning resulted in eight drugs (abacavir, ribociclib, exemestane, voriconazole, nortriptyline hydrochloride, theophylline, bromocriptine mesylate, and tolcapone). Moreover, significant in vitro inhibition profiles were obtained in abacavir, nortriptyline hydrochloride, exemestane, tolcapone, and theophylline (positive control). Our findings may provide new and complementary strategies for the treatment of CRC.

Discovery of Potent SARS-CoV-2 Inhibitors from Approved Antiviral Drugs via Docking and Virtual Screening

BACKGROUND

Coronavirus Disease 2019 (COVID-19) pandemic continues to threaten patients, societies and healthcare systems around the world. There is an urgent need to search for possible medications.

OBJECTIVE

This article intends to use virtual screening and molecular docking methods to find potential inhibitors from existing drugs that can respond to COVID-19.

METHODS

To take part in the current research investigation and to define a potential target drug that may protect the world from the pandemic of corona disease, a virtual screening study of 129 approved drugs was carried out which showed that their metabolic characteristics, dosages used, potential efficacy and side effects are clear as they have been approved for treating existing infections. Especially 12 drugs against chronic hepatitis B virus, 37 against chronic hepatitis C virus, 37 against human immunodeficiency virus, 14 anti-herpesvirus, 11 anti-influenza, and 18 other drugs currently on the market were considered for this study. These drugs were then evaluated using virtual screening and molecular docking studies on the active site of the (SARS-CoV-2) main protease (6lu7). Once the efficacy of the drug is determined, it can be approved for its in vitro and in vivo activity against the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which can be beneficial for the rapid clinical treatment of patients. These drugs were considered potentially effective against SARS-CoV-2 and those with high molecular docking scores were proposed as novel candidates for repurposing. The N3 inhibitor cocrystallized with protease (6lu7) and the anti-HIV protease inhibitor Lopinavir were used as standards for comparison.

RESULTS

The results suggest the effectiveness of Beclabuvir, Nilotinib, Tirilazad, Trametinib and Glecaprevir as potent drugs against SARS-CoV-2 since they tightly bind to its main protease.

CONCLUSION

These promising drugs can inhibit the replication of the virus; hence, the repurposing of these compounds is suggested for the treatment of COVID-19. No toxicity measurements are required for these drugs since they were previously tested prior to their approval by the FDA. However, the assessment of these potential inhibitors as clinical drugs requires further in vivo tests of these drugs.

Discovery of Potent SARS-CoV-2 Inhibitors from Approved Antiviral Drugs via Docking and Virtual Screening

Background:

Coronavirus Disease 2019 (COVID-19) pandemic continues to threaten patients, societies and healthcare systems around the world. There is an urgent need to search for possible medications.

Objective:

This article intends to use virtual screening and molecular docking methods to find potential inhibitors from existing drugs that can respond to COVID-19.

Methods:

To take part in the current research investigation and to define a potential target drug that may protect the world from the pandemic of corona disease, a virtual screening study of 129 approved drugs was carried out which showed that their metabolic characteristics, dosages used, potential efficacy and side effects are clear as they have been approved for treating existing infections. Especially 12 drugs against chronic hepatitis B virus, 37 against chronic hepatitis C virus, 37 against human immunodeficiency virus, 14 anti-herpesvirus, 11 anti-influenza, and 18 other drugs currently on the market were considered for this study. These drugs were then evaluated using virtual screening and molecular docking studies on the active site of the (SARS-CoV-2) main protease (6lu7). Once the efficacy of the drug is determined, it can be approved for its in vitro and in vivo activity against the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which can be beneficial for the rapid clinical treatment of patients.

:

These drugs were considered potentially effective against SARS-CoV-2 and those with high molecular docking scores were proposed as novel candidates for repurposing. The N3 inhibitor cocrystallized with protease (6lu7) and the anti-HIV protease inhibitor Lopinavir were used as standards for comparison.

Results:

The results suggest the effectiveness of Beclabuvir, Nilotinib, Tirilazad, Trametinib and Glecaprevir as potent drugs against SARS-CoV-2 since they tightly bind to its main protease.

Conclusion:

These promising drugs can inhibit the replication of the virus; hence, the repurposing of these compounds is suggested for the treatment of COVID-19. No toxicity measurements are required for these drugs since they were previously tested prior to their approval by the FDA. However, the assessment of these potential inhibitors as clinical drugs requires further in vivo tests of these drugs.

The Repertoire of Glycan Alterations and Glycoproteins in Human Cancers

Cancer as the leading cause of death worldwide has many issues that still need to be addressed. Since the alterations on the glycan compositions or/and structures (i.e., glycosylation, sialylation, and fucosylation) are common features of tumorigenesis, glycomics becomes an emerging field examining the structure and function of glycans. In the past, cancer studies heavily relied on genomics and transcriptomics with relatively little exploration of the glycan alterations and glycoprotein biomarkers among individuals and populations. Since glycosylation of proteins increases their structural complexity by several orders of magnitude, glycome studies resulted in highly dynamic biomarkers that can be evaluated for cancer diagnosis, prognosis, and therapy. Glycome not only integrates our genetic background with past and present environmental factors but also offers a promise of more efficient patient stratification compared with genetic variations. Therefore, studying glycans holds great potential for better diagnostic markers as well as developing more efficient treatment strategies in human cancers. While recent developments in glycomics and associated technologies now offer new possibilities to achieve a high-throughput profiling of glycan diversity, we aim to give an overview of the current status of glycan research and the potential applications of the glycans in the scope of the personalized medicine strategies for cancer.

Integrative transcriptomics analysis of lung epithelial cells and identification of repurposable drug candidates for COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease, more commonly COVID-19 has emerged as a world health pandemic. There are couples of treatment methods for COVID-19, however, well-established drugs and vaccines are urgently needed to treat the COVID-19. The new drug discovery is a tremendous challenge; repurposing of existing drugs could shorten the time and expense compared with de novo drug development. In this study, we aimed to decode molecular signatures and pathways of the host cells in response to SARS-CoV-2 and the rapid identification of repurposable drugs using bioinformatics and network biology strategies. We have analyzed available transcriptomic RNA-seq COVID-19 data to identify differentially expressed genes (DEGs). We detected 177 DEGs specific for COVID-19 where 122 were upregulated and 55 were downregulated compared to control (FDR<0.05 and logFC ≥ 1). The DEGs were significantly involved in the immune and inflammatory response. The pathway analysis revealed the DEGs were found in influenza A, measles, cytokine signaling in the immune system, interleukin-4, interleukin -13, interleukin -17 signaling, and TNF signaling pathways. Protein-protein interaction analysis showed 10 hub genes (BIRC3, ICAM1, IRAK2, MAP3K8, S100A8, SOCS3, STAT5A, TNF, TNFAIP3, TNIP1). The regulatory network analysis showed significant transcription factors (TFs) that target DEGs, namely FOXC1, GATA2, YY1, FOXL1, NFKB1. Finally, drug repositioning analysis was performed with these 10 hub genes and showed that in silico validated three drugs with molecular docking. The transcriptomics signatures, molecular pathways, and regulatory biomolecules shed light on candidate biomarkers and drug targets which have potential roles to manage COVID-19. ICAM1 and TNFAIP3 were the key hubs that have demonstrated good binding affinities with repurposed drug candidates. Dabrafenib, radicicol, and AT-7519 were the top-scored repurposed drugs that showed efficient docking results when they tested with hub genes. The identified drugs should be further evaluated in molecular level wet-lab experiments in prior to clinical studies in the treatment of COVID-19.

Systems biology based drug repositioning for development of cancer therapy

Drug repositioning is a powerful method that can assists the conventional drug discovery process by using existing drugs for treatment of a disease rather than its original indication. The first examples of repurposed drugs were discovered serendipitously, however data accumulated by high-throughput screenings and advancements in computational biology methods have paved the way for rational drug repositioning methods. As chemotherapeutic agents have notorious side effects that significantly reduce quality of life, drug repositioning promises repurposed noncancer drugs with little or tolerable adverse effects for cancer patients. Here, we review current drug-related data types and databases including some examples of web-based drug repositioning tools. Next, we describe systems biology approaches to be used in drug repositioning for effective cancer therapy. Finally, we highlight examples of mostly repurposed drugs for cancer treatment and provide an overview of future expectations in the field for development of effective treatment strategies.

Multi-Omic Data Interpretation to Repurpose Subtype Specific Drug Candidates for Breast Cancer

Triple-negative breast cancer (TNBC), which is largely synonymous with the basal-like molecular subtype, is the 5th leading cause of cancer deaths for women in the United States. The overall prognosis for TNBC patients remains poor given that few treatment options exist; including targeted therapies (not FDA approved), and multi-agent chemotherapy as standard-of-care treatment. TNBC like other complex diseases is governed by the perturbations of the complex interaction networks thereby elucidating the underlying molecular mechanisms of this disease in the context of network principles, which have the potential to identify targets for drug development. Here, we present an integrated "omics" approach based on the use of transcriptome and interactome data to identify dynamic/active protein-protein interaction networks (PPINs) in TNBC patients. We have identified three highly connected modules, EED, DHX9, and AURKA, which are extremely activated in TNBC tumors compared to both normal tissues and other breast cancer subtypes. Based on the functional analyses, we propose that these modules are potential drivers of proliferation and, as such, should be considered candidate molecular targets for drug development or drug repositioning in TNBC. Consistent with this argument, we repurposed steroids, anti-inflammatory agents, anti-infective agents, cardiovascular agents for patients with basal-like breast cancer. Finally, we have performed essential metabolite analysis on personalized genome-scale metabolic models and found that metabolites such as sphingosine-1-phosphate and cholesterol-sulfate have utmost importance in TNBC tumor growth.

Drug Targeting and Biomarkers in Head and Neck Cancers: Insights from Systems Biology Analyses

The head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers in the world, but robust biomarkers and diagnostics are still not available. This study provides in-depth insights from systems biology analyses to identify molecular biomarker signatures to inform systematic drug targeting in HNSCC. Gene expression profiles from tumors and normal tissues of 22 patients with histological confirmation of nonmetastatic HNSCC were subjected to integrative analyses with genome-scale biomolecular networks (i.e., protein-protein interaction and transcriptional and post-transcriptional regulatory networks). We aimed to discover molecular signatures at RNA and protein levels, which could serve as potential drug targets for therapeutic innovation in the future. Eleven proteins, 5 transcription factors, and 20 microRNAs (miRNAs) came into prominence as potential drug targets. The differential expression profiles of these reporter biomolecules were cross-validated by independent RNA-Seq and miRNA-Seq datasets, and risk discrimination performance of the reporter biomolecules, BLNK, CCL2, E4F1, FOSL1, ISG15, MMP9, MYCN, MYH11, miR-1252, miR-29b, miR-29c, miR-3610, miR-431, and miR-523, was also evaluated. Using the transcriptome guided drug repositioning tool, geneXpharma, several candidate drugs were repurposed, including antineoplastic agents (e.g., gemcitabine and irinotecan), antidiabetics (e.g., rosiglitazone), dermatological agents (e.g., clocortolone and acitretin), and antipsychotics (e.g., risperidone), and binding affinities of the drugs to their potential targets were assessed using molecular docking analyses. The molecular signatures and repurposed drugs presented in this study warrant further attention for experimental studies since they offer significant potential as biomarkers and candidate therapeutics for precision medicine approaches to clinical management of HNSCC.

Identification of Prognostic Biomarker Signatures and Candidate Drugs in Colorectal Cancer: Insights from Systems Biology Analysis

Background and objectives: Colorectal cancer (CRC) is the second most common cause of cancer-related death in the world, but early diagnosis ameliorates the survival of CRC. This report aimed to identify molecular biomarker signatures in CRC. Materials and Methods: We analyzed two microarray datasets (GSE35279 and GSE21815) from the Gene Expression Omnibus (GEO) to identify mutual differentially expressed genes (DEGs). We integrated DEGs with protein–protein interaction and transcriptional/post-transcriptional regulatory networks to identify reporter signaling and regulatory molecules; utilized functional overrepresentation and pathway enrichment analyses to elucidate their roles in biological processes and molecular pathways; performed survival analyses to evaluate their prognostic performance; and applied drug repositioning analyses through Connectivity Map (CMap) and geneXpharma tools to hypothesize possible drug candidates targeting reporter molecules. Results: A total of 727 upregulated and 99 downregulated DEGs were detected. The PI3K/Akt signaling, Wnt signaling, extracellular matrix (ECM) interaction, and cell cycle were identified as significantly enriched pathways. Ten hub proteins (ADNP, CCND1, CD44, CDK4, CEBPB, CENPA, CENPH, CENPN, MYC, and RFC2), 10 transcription factors (ETS1, ESR1, GATA1, GATA2, GATA3, AR, YBX1, FOXP3, E2F4, and PRDM14) and two microRNAs (miRNAs) (miR-193b-3p and miR-615-3p) were detected as reporter molecules. The survival analyses through Kaplan–Meier curves indicated remarkable performance of reporter molecules in the estimation of survival probability in CRC patients. In addition, several drug candidates including anti-neoplastic and immunomodulating agents were repositioned. Conclusions: This study presents biomarker signatures at protein and RNA levels with prognostic capability in CRC. We think that the molecular signatures and candidate drugs presented in this study might be useful in future studies indenting the development of accurate diagnostic and/or prognostic biomarker screens and efficient therapeutic strategies in CRC.

Drug Repositioning for Effective Prostate Cancer Treatment

Drug repositioning has gained attention from both academia and pharmaceutical companies as an auxiliary process to conventional drug discovery. Chemotherapeutic agents have notorious adverse effects that drastically reduce the life quality of cancer patients so drug repositioning is a promising strategy to identify non-cancer drugs which have anti-cancer activity as well as tolerable adverse effects for human health. There are various strategies for discovery and validation of repurposed drugs. In this review, 25 repurposed drug candidates are presented as result of different strategies, 15 of which are already under clinical investigation for treatment of prostate cancer (PCa). To date, zoledronic acid is the only repurposed, clinically used, and approved non-cancer drug for PCa. Anti-cancer activities of existing drugs presented in this review cover diverse and also known mechanisms such as inhibition of mTOR and VEGFR2 signaling, inhibition of PI3K/Akt signaling, COX and selective COX-2 inhibition, NF-κB inhibition, Wnt/β-Catenin pathway inhibition, DNMT1 inhibition, and GSK-3β inhibition. In addition to monotherapy option, combination therapy with current anti-cancer drugs may also increase drug efficacy and reduce adverse effects. Thus, drug repositioning may become a key approach for drug discovery in terms of time- and cost-efficiency comparing to conventional drug discovery and development process.