Person: TURANLI, BESTE
Loading...
Email Address
Birth Date
Research Projects
Organizational Units
Job Title
Last Name
TURANLI
First Name
BESTE
Name
46 results
Search Results
Now showing 1 - 10 of 46
Publication Open Access Drug repositioning via host-pathogen protein-protein interactions for the treatment of cervical cancer(2023-01-25) TURANLI, BESTE; Kori M., Turanli B., Arga K. Y.Introduction: Integrating interaction data with biological knowledge can be a critical approach for drug development or drug repurposing. In this context, hostpathogen-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.Publication Open Access Repositioning of anti-inflammatory drugs for the treatment of cervical cancer sub-types(2022-06-01) TURANLI, BESTE; ARĞA, KAZIM YALÇIN; Kori M., ARĞA K. Y., Mardinoglu A., TURANLI B.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.Publication Open Access Drug Repositioning for Effective Prostate Cancer Treatment(FRONTIERS MEDIA SA, 2018-05-15) TURANLI, BESTE; Turanli, Beste; Grotli, Morten; Boren, Jan; Nielsen, Jens; Uhlen, Mathias; Arga, Kazim Y.; Mardinoglu, AdilDrug 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-kappa B inhibition, Wnt/beta - Catenin pathway inhibition, DNMT1 inhibition, and GSK-3 beta 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.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 Systems biology perspective for elucidation of secreted protein biomarkers in alzheimer’s disease(2022-10-11) TURANLI, BESTE; TURANLI B.Publication Metadata only Drug repositioning for cancer therapy by the employment of systems biology(2019-10-01) TURANLI, BESTE; ARĞA, KAZIM YALÇIN; TURANLI B., GULFİDAN G., Mardinoğlu A., ARĞA K. Y.Publication Open Access Identification of Prognostic Biomarker Signatures and Candidate Drugs in Colorectal Cancer: Insights from Systems Biology Analysis(MDPI, 2019-01-17) TURANLI, BESTE; Rahman, Md Rezanur; Islam, Tania; Gov, Esra; Turanli, Beste; Gulfidan, Gizem; Shahjaman, Md; Banu, Nilufa Akhter; Mollah, Md Nurul Haque; Arga, Kazim Yalcin; Moni, Mohammad AliBackground 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.Publication Open Access Systems-level biomarkers identification and drug repositioning in colorectal cancer(2021-07-15) TURANLI, BESTE; Beklen, Hande; Yildirim, Esra; Kori, Medi; Turanli, Beste; Arga, Kazim YalcinPublication Metadata only Comparative study on understanding molecular signatures of ALL and philedelphia positive ALL in adults(2022-11-16) TURANLI, BESTE; BUDAK B., KİRAZ Y., TURANLI B.Acute lymphoblastic leukemia (ALL) is known to be a very heterogeneous disease together with identified various genetic abnormalities that causes the disease to be formed. ALL is also known with its low survival rates. The most commonly seen subtype of ALL is Philadelphia positive ALL (Ph+ALL) which carries BCR/ABL translocation which is considered as high-risk and the most aggressive subtype. Ph+ ALL subtype presents drug resistance phenomenon as an obstacle in the treatment process. Moreover, there has not been novel treatments developed or proposed for the treatment of ALL. In this study, we aimed to compare the molecular profiles of ALL and Ph+ALL by integrating data from multiple biomolecular levels. We statistically analyzed 8 ALL and 4 Ph+ALL-associated transcriptomic datasets using the R/Bioconductor (www.bioconductor.org) software platform. As a result of this meta-analysis, we found 799 differentially expressed genes (DEGs) for ALL and 295 DEGs for Ph+ALL. We associated DEGs with reporter molecules receptor, transcription factor, miRNA, metabolites in addition to reconstruction of protein-protein interaction networks. We also identified hub proteins according to degree and betweenness centrality. CDKN1A, HSP90AA1, PCNA, PIK3R1, SMARCA4, YWHAB, and YWHAE in ALL; LYN and RANBP9 in Ph+ALL were prominent as hub proteins. In addition, we aimed to find a novel and effective therapeutics by using drug repurposing strategy. The results elucidated by this project will further use in in vitro validation tests and may pave the way for new clinical trials and clinical applications.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.