Person: TURANLI, BESTE
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TURANLI
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BESTE
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Publication Metadata only Transcriptomic-Guided Drug Repositioning Supported by a New Bioinformatics Search Tool: geneXpharma(MARY ANN LIEBERT, INC, 2017) TURANLI, BESTE; Turanli, Beste; Gulfidan, Gizem; Arga, Kazim YalcinDrug repositioning is an innovative approach to identify new therapeutic indications for existing drugs. Drug repositioning offers the promise of reducing drug development timeframes and costs, and because it involves drugs that are already in the clinic, it might remedy some of the drug safety challenges traditionally associated with drug candidates that are not yet available in the clinic. The gene-by-drug interactions are an important dimension of optimal drug repositioning and development strategies. While gene-by-drug interactions have been curated and presented in various databases, novel bioinformatics tools and approaches are timely, and required with a specific focus to support drug positioning. We report, in this study, the design of a public web-accessible transcriptomic-/gene expression-guided pharmaceuticals search tool, geneXpharma (www.genexpharma.org). GeneXpharma is a public platform with user-centric interface that provides statistically evaluated gene expressions and their drug interactions for 48 diseases under seven different disease categories. GeneXpharma is designed and organized to generate hypotheses on druggable genome within the disease-gene-drug triad and thus, help repositioning of drugs against diseases. The search system accommodates various entry points using drugs, genes, or diseases, which then enable researchers to extract drug repurposing candidates and readily export for further evaluation. Future developments aim to improve the geneXpharma algorithm, enrich its content, and enhance the website interface through addition of network visualizations and graphical display items. Bioinformatics search tools can help enable the convergence of drug repositioning and gene-by-drug interactions so as to further optimize drug development efforts in the future.Publication Metadata only Differential Protein Interactome in Esophageal Squamous Cell Carcinoma Offers Novel Systems Biomarker Candidates with High Diagnostic and Prognostic Performance(MARY ANN LIEBERT, INC, 2021) TURANLI, BESTE; Gulfidan, Gizem; Beklen, Hande; Sinha, Indu; Kucukalp, Fulya; Caloglu, Buse; Esen, Ipek; Turanli, Beste; Ayyildiz, Dilara; Arga, Kazim Yalcin; Sinha, RaghuEsophageal squamous cell carcinoma (ESCC) is among the most dangerous cancers with high mortality and lack of robust diagnostics and personalized/precision therapeutics. To achieve a systems-level understanding of tumorigenesis, unraveling of variations in the protein interactome and determination of key proteins exhibiting significant alterations in their interaction patterns during tumorigenesis are crucial. To this end, we have described differential protein-protein interactions and differentially interacting proteins (DIPs) in ESCC by utilizing the human protein interactome and transcriptome. Furthermore, DIP-centered modules were analyzed according to their potential in elucidation of disease mechanisms and improvement of efficient diagnostic, prognostic, and treatment strategies. Seven modules were presented as potential diagnostic, and 16 modules were presented as potential prognostic biomarker candidates. Importantly, our findings also suggest that 30 out of the 53 repurposed drugs were noncancer drugs, which could be used in the treatment of ESCC. Interestingly, 25 of these, proposed as novel drug candidates here, have not been previously associated in a context of esophageal cancer. In this context, risperidone and clozapine were validated for their growth inhibitory potential in three ESCC lines. Our findings offer a high potential for the development of innovative diagnostic, prognostic, and therapeutic strategies for further experimental studies in line with predictive diagnostics, targeted prevention, and personalization of medical services in ESCC specifically, and personalized cancer care broadly.Publication Metadata only Past, present, and future of therapies for pituitary neuroendocrine tumors: need for omics and drug repositioning guidance(2022-03-01) ERDOĞAN, ONUR; ARĞA, KAZIM YALÇIN; BOZKURT, SÜHEYLA; BAYRAKLI, FATİH; YILMAZ, BETÜL; TURANLI, BESTE; Aydin B., Yildirim E., ERDOĞAN O., ARĞA K. Y., Yilmaz B., BOZKURT S., BAYRAKLI F., TURANLI B.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.Publication Metadata only A Network-Based Cancer Drug Discovery: From Integrated Multi-Omics Approaches to Precision Medicine(BENTHAM SCIENCE PUBL LTD, 2018) TURANLI, BESTE; Turanli, Beste; Karagoz, Kubra; Gulfidan, Gizem; Sinha, Raghu; Mardinoglu, Adil; Arga, Kazim YalcinA complex framework of interacting partners including genetic, proteomic, and metabolic networks that cooperate to mediate specific functional phenotypes drives human biological processes. Recent technological and analytical advances in omic sciences allow the identification and elucidation of reprogramming biological functions in response to perturbations in cells and tissues. To understand such a complex system, biological networks are generated to reduce the complexity into relatively simple models, and the integration of these molecular networks from different perspectives is implemented for a holistic interpretation of the entire system. Ultimately, network-based methods will effectively facilitate the development and improvement of precision medicine by directing therapies based on the underlying biology of a given patient's disease. The goal of precision medicine is to identify novel therapeutic strategies that can be optimized for each disease type or each patient based on the underlying genetic, environmental, and lifestyle factors. Pharmaco-omics analyses based on an integration of pharmacology and various omics data types can be employed to develop effective treatment strategies using particular drugs and doses that are tailored to each individual. In the current review, we first present the core elements of network-based systems biology in the context of pharmaco-omics followed by integration of multi-omics data using various biological networks. Next, we provide an opening into precise medicine and drug targeting based on network approaches. Lastly, we review the current significant efforts as well as the accomplishments and limitations in precise drug targeting with the utility of network-based guided drug discovery methods for effective treatment of breast cancer.Publication Metadata only Idiopathic Pulmonary Fibrosis Molecular Substrates Revealed by Competing Endogenous RNA Regulatory Networks(2023-01-01) TURANLI, BESTE; Kircali M. F., TURANLI B.Idiopathic pulmonary fibrosis (IPF) is a chronic progressive fibrotic disease of the lung with poor prognosis. Fibrosis results from remodeling of the interstitial tissue. A wide range of gene expression changes are observed, but the role of micro RNAs (miRNAs) and circular RNAs (circRNA) is still unclear. Therefore, this study aimed to establish an messenger RNA (mRNA)-miRNA-circRNA competing endogenous RNA (ceRNA) regulatory network to uncover novel molecular signatures using systems biology tools. Six datasets were used to determine differentially expressed genes (DEGs) and miRNAs (DEmiRNA). Accordingly, protein-protein, mRNA-miRNA, and miRNA-circRNA interactions were constructed. Modules were determined and further analyzed in the Drug Gene Budger platform to identify potential therapeutic compounds. We uncovered common 724 DEGs and 278 DEmiRNAs. In the protein-protein interaction network, TMPRSS4, ESR2, TP73, CLEC4E, and TP63 were identified as hub protein coding genes. The mRNA-miRNA interaction network revealed two modules composed of ADRA1A, ADRA1B, hsa-miR-484 and CDH2, TMPRSS4, and hsa-miR-543. The DEmiRNAs in the modules further analyzed to propose potential circRNA regulators in the ceRNA network. These results help deepen the understanding of the mechanisms of IPF. In addition, the molecular leads reported herein might inform future innovations in diagnostics and therapeutics research and development for IPF.