TR-Dizin İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/396
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Article Developing a Label Propagation Approach for Cancer Subtype Classification Problem(TUBITAK, 2021) Güner, P.; Bakir-Güngör, B.; Coşkun, M.; Şahan, Pınar GünerCancer is a disease in which abnormal cells grow uncontrollably and invade other tissues. Several types of cancer have various subtypes with different clinical and biological implications. Based on these differences, treatment methods need to be customized. The identification of distinct cancer subtypes is an important problem in bioinformatics, since it can guide future precision medicine applications. In order to design targeted treatments, bioinformatics methods attempt to discover common molecular pathology of different cancer subtypes. Along this line, several computational methods have been proposed to discover cancer subtypes or to stratify cancer into informative subtypes. However, existing works do not consider the sparseness of data (genes having low degrees) and result in an ill-conditioned solution. To address this shortcoming, in this paper, we propose an alternative unsupervised method to stratify cancer patients into subtypes using applied numerical algebra techniques. More specifically, we applied a label propagation-based approach to stratify somatic mutation profiles of colon, head and neck, uterine, bladder, and breast tumors. We evaluated the performance of our method by comparing it to the baseline methods. Extensive experiments demonstrate that our approach highly renders tumor classification tasks by largely outperforming the state-of-the-art unsupervised and supervised approaches. © 2022 Elsevier B.V., All rights reserved.Article Citation - WoS: 8Citation - Scopus: 10Lung Cancer Subtype Differentiation From Positron Emission Tomography Images(Tubitak Scientific & Technological Research Council Turkey, 2020-01-27) Ayyildiz, Oguzhan; Aydin, Zafer; Yilmaz, Bulent; Karacavus, Seyhan; Senkaya, Kubra; Icer, Semra; Kaya, Eser; Taşdemir, ArzuLung cancer is one of the deadly cancer types, and almost 85% of lung cancers are nonsmall cell lung cancer (NSCLC). In the present study we investigated classification and feature selection methods for the differentiation of two subtypes of NSCLC, namely adenocarcinoma (ADC) and squamous cell carcinoma (SqCC). The major advances in understanding the effects of therapy agents suggest that future targeted therapies will be increasingly subtype specific. We obtained positron emission tomography (PET) images of 93 patients with NSCLC, 39 of which had ADC while the rest had SqCC. Random walk segmentation was applied to delineate three-dimensional tumor volume, and 39 texture features were extracted to grade the tumor subtypes. We examined 11 classifiers with two different feature selection methods and the effect of normalization on accuracy. The classifiers we used were the k-nearest-neighbor, logistic regression, support vector machine, Bayesian network, decision tree, radial basis function network, random forest, AdaBoostM1, and three stacking methods. To evaluate the prediction accuracy we performed a leave-one-out cross-validation experiment on the dataset. We also considered optimizing certain hyperparameters of these models by performing 10-fold cross-validation separately on each training set. We found that the stacking ensemble classifier, which combines a decision tree, AdaBoostM1, and logistic regression methods by a metalearner, was the most accurate method for detecting subtypes of NSCLC, and normalization of feature sets improved the accuracy of the classification method.Article Enlightening the Molecular Mechanisms of Type 2 Diabetes With a Novel Pathway Clustering and Pathway Subnetwork Approach(Tubitak Scientific & Technological Research Council Turkey, 2022-01-01) Bakir-Gungor, Burcu; Yazici, Miray Unlu; Goy, Gokhan; Temiz, Mustafa; Ünlü Yazici, MirayType 2 diabetes mellitus (T2D) constitutes 90% of the diabetes cases, and it is a complex multifactorial disease. In the last decade, genome-wide association studies (GWASs) for T2D successfully pinpointed the genetic variants (typically single nucleotide polymorphisms, SNPs) that associate with disease risk. In order to diminish the burden of multiple testing in GWAS, researchers attempted to evaluate the collective effects of interesting variants. In this regard, pathway-based analyses of GWAS became popular to discover novel multigenic functional associations. Still, to reveal the unaccounted 85 to 90% of T2D variation, which lies hidden in GWAS datasets, new post-GWAS strategies need to be developed. In this respect, here we reanalyze three metaanalysis data of GWAS in T2D, using the methodology that we have developed to identify disease-associated pathways by combining nominally significant evidence of genetic association with the known biochemical pathways, protein-protein interaction (PPI) networks, and the functional information of selected SNPs. In this research effort, to enlighten the molecular mechanisms underlying T2D development and progress, we integrated different in silico approaches that proceed in top-down manner and bottom-up manner, and presented a comprehensive analysis at protein subnetwork, pathway, and pathway subnetwork levels. Using the mutual information based on the shared genes, the identified protein subnetworks and the affected pathways of each dataset were compared. While most of the identified pathways recapitulate the pathophysiology of T2D, our results show that incorporating SNP functional properties, PPI networks into GWAS can dissect leading molecular pathways, and it could offer improvement over traditional enrichment strategies.Article Cytotoxic and Cytostatic Effects of Targeting mTOR and Hedgehog Pathways in Acute Myeloid Leukemia(Istanbul Univ, 2022-12-29) Cicek, Enes; Kucuktas, Fulya Mina; Yenigul, Munevver; Akcok, Emel Basak GencerObjectives: Acute myeloid leukemia (AML) is a highly aggressive heterogeneous hematopoietic malignancy characterized by a rapid and abnormal proliferation of immature myeloid leukemia cells in the bone marrow and peripheral blood. Aberrant alterations in signal transduction pathways are strongly associated with the progression of AML. This study aimed to investigate cell viability and the cell cycle in AML cells by targeting the Hedgehog and mTOR signaling pathways with rapamycin and GANT61. Materials and Method: The antiproliferative effect of rapamycin and GANT61 was assessed by the MTT cell viability assay in two AML cell lines: CMK and MOLM-13. The effect of the inhibitors on cell-cycle distribution was determined using propidium iodide staining and measured with flow cytometry. Results: Rapamycin, an mTOR inhibitor, and GANT61, a Gli-1 inhibitor, decreased the cell proliferation of CMK and MOLM-13 cells. The IC20 values, which is the drug concentration that inhibits cell growth by 20%, were combined and administered to the cells. The results show the drugs to have a combinatorial inhibitory effect on CMK cells but not on MOLM-13 cells. In addition, the combination of drugs arrested the cells during the G0/G1 phase. Conclusion: This study suggests a novel combination therapy approach for AML via mTOR and Hedgehog signaling pathway inhibition using rapamycin and GANT61, respectively. It also suggest further studies be performed to reveal the mechanism of action.Article Apatinib Sensitizes Human Breast Cancer Cells Against Navitoclax and Venetoclax Despite Up-Regulated Bcl-2 and Mcl-1 Gene Expressions(Kare Publ, 2021) Kavakcioglu Yardimci, Berna; Ozgun Acar, Ozden; Semiz, Asli; Sen, Alaattin; Acar, Ozden Ozgun; Yardımcı, Berna KavakcıoğluOBJECTIVE Defects in apoptotic cell death which restrict the success of conventional cytotoxic therapies have pivotal roles in a number of pathological conditions including cancer. However, a novel drug class targeting pro-survival Bcl-2 protein family members has been developed with the understanding of the structures and interactions of Bcl-2 proteins. Within this new class, Bcl-2/Bcl-xL inhibitor Navitoclax and Bcl-2 specific inhibitor Venetoclax have been shown to demonstrate strong anticancer activities on several types of cancers. But their low affinity to other anti-apoptotic proteins limits their clinical usage. Here, we investigated the cytotoxic and apoptotic effects of Navitoclax/Venetoclax and their combinations with specific tyrosine kinase inhibitor Apatinib on estrogen receptor (ER)-positive MCF-7 and ER-negative MDA-MB-231 breast cancer cell lines. METHODS MTT assay was used for the evaluation of the inhibition of cancer cell proliferation. ELISA test and Quantitative real-time PCR assay was performed to determine the role of caspase-3, Bak, Bax, Bcl-2, Bcl-xL and Mcl-1 proteins in the inhibition of cell proliferation triggered by the tested agents. RESULTS We found that aggressive MDA-MB-231 cell line was more sensitive to all tested agents. Apatinib significantly enhanced Navitoclax/Venetoclax mediated inhibition of cell viability in both cancer cell lines despite up-regulation in the expression levels of Bcl-2 and Mcl-1 genes. We further demonstrated significant Bak/Bax and caspase-3 expression in less aggressive MCF-7 cells. CONCLUSION Our findings have impacts on Navitoclax/Venetoclax plus Apatinib based therapy for breast adenocarcinoma. On the other hand, further studies should be conducted to elucidate the mechanisms underlying synergistic effects of Navitoclax/Venetoclax plus Apatinib combinations.Article A Comparative Study of Unet Variants for Low-Grade Glioma Segmentation in Magnetic Resonance Imaging(Inonu University, 2025-06-25) Guzel, Yasin; Aydin, ZaferBrain tumors originating from glial cells are pathological entities that significantly impact quality of life and are classified based on their malignancy into low-grade gliomas (LGGs) and high-grade gliomas (HGGs). While the more aggressive HGGs have been extensively studied, LGGs are of critical importance for early diagnosis due to their potential progression to HGGs if left untreated. This has driven researchers to develop methods for the rapid and consistent diagnosis of LGGs. In this study, three models—UNet, Transformer UNet, and Super Vision UNet—were comparatively evaluated for the automatic segmentation of LGGs using magnetic resonance imaging (MRI) data. Multimodal MRI scans from 110 patients, retrieved from The Cancer Imaging Archive (TCIA), were used to train the models. Performance was evaluated using Dice Coefficient, Tversky Index, and Intersection over Union (IoU) metrics. The Super Vision UNet achieves the highest Dice (0.9115) and Tversky (0.9154) scores, while the Transformer UNet attains the highest IoU (0.8789). Both advanced models demonstrate superior segmentation performance with lower loss values compared to the conventional UNet. Visual outputs indicate that the modern architectures delineate tumor contours with greater precision. These results highlight the effectiveness and reliability of contemporary UNet-based and Transformer-based architectures in segmenting complex tumor structures such as LGGs. Integrating these models into clinical decision support systems holds promise for enhancing the speed and accuracy of the diagnostic process. © 2025 Elsevier B.V., All rights reserved.Article Citation - Scopus: 1Glucosylceramide Synthase is a Novel Biomarker of Midostaurin-Induced Cytotoxicity in Non-Mutant FLT3 Positive Acute Myeloid Leukemia Cells(Istanbul University Press, 2021-12-03) Şahin, Hande Nur; Adan, AysunObjective: Glucosylceramide (GC) synthesized by glucosylce-ramide synthase (GCS) favors cell survival and proliferation in many cancers. However, it’s role in Fms-like tyrosine kinase 3 (FLT3) non-mutant Acute Myeloid Leukemia (AML) pathogenesis is not clarified. Midostaurin, a multi-kinase inhibitor, clinically benefits FLT3-mutated AML, however, its clinical efficacy is under-estimat-ed in FLT3 non-mutant AML. This study aimed to investigate the efficacy of combination of midostaurin with GCS inhibitor in FLT3 AML cell carrying wild-type FLT3 and the underlying molecular mechanisms. Material and Method: Cytotoxic and cytostatic effects of mido-staurin, PDMP (GCS inhibitor) alone and in combination on THP1 cells were determined by MTT assay and flow cytometric propidi-um iodide (PI) staining, respectively. Calcusyn software was used to calculate combination indexes (CIs). GCS expression was checked by western blot. Results: Midostaurin downregulated GCS. Simultaneous inhibition of FLT3 and GCS resulted in suppression of cell proliferation as compared to untreated control. Combinations showed synergistic cytotoxic effects (CI<1). Co-treatments increased cell cycle population at G2/M phase. Conclusion: Inhibition of GCS enhances the efficacy of midostau-rin in FLT3 non-mutant AML, which could be a novel therapeutic approach to increase midostaurin’s limited usage in the clinic after detailed mechanistic studies. © 2023 Elsevier B.V., All rights reserved.Article Citation - Scopus: 13Paclitaxel-Loaded Polycaprolactone Nanoparticles for Lung Tumors: Formulation, Comprehensive In Vitro Characterization, and Release Kinetic Studies(University of Ankara, 2022-09-29) Ünal, Sedat; Dogan, Osman Talha; Aktaş, YeşimObjective: Today, cancer is still among the most common chronic diseases. Nanoparticular drug delivery systems prepared with biocompatible and biodegradable polymers such as polycaprolactone are rational solution for anticancer agents with poor solubility and low bioavailability. The aim of this study is to prepare paclitaxel-loaded polycaprolactone nanoparticles, which is known to be a potent anticancer, and to elucidate in vitro characteristics and release kinetic mechanisms. Material and Method: It was aimed to prepare paclitaxel-loaded polycaprolactone nanoparticles by nanoprecipitation. Preformulation studies were carried out with different molecular weights of polycaprolactone (Mw: 14.000, Mw: 80.000). Nanoparticles were coated with Chitosan or Poly-l-lysine to obtain cationic surface charge and to increase cellular interaction. Comprehensive characterization of formulations and release kinetic studies were performed. Result and Discussion: The particle size of the formulations ranged from 188 nm to 383 nm. Encapsulation efficiency increased to 77% in different formulations. SEM analysis confirmed the nanoparticles were spherical. Within the scope of in vitro release studies, the release continued for up to 96 hours and less than 50% of the therapeutic load was released in the first 24 hours. Mathematical modeling indicated that the release kinetics fit more than one model with the Korsmeyer-Peppas, Peppas-Sahlin and Weibull models, which show high correlation. © 2023 Elsevier B.V., All rights reserved.