Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Novel Statistical Approaches for Survival Analysis of RNA-Sequencing Data(Bentham Science Publ Ltd, 2026) Cephe, Ahu; Karabulut, Erdem; Zararsız, Gözde Ertürk; Sezgin, Ahmet; Koçhan, NeclaIntroduction/Objective Accurate patient survival predictions are vital for effective cancer treatments. Precision medicine uses gene expression data to improve prognosis by considering genetic variability. Predicting survival in cancer patients using high-dimensional gene expression data, such as RNA-sequencing (RNA-seq), attracted much attention in recent years. However, the literature contains limited algorithms for survival modeling that account for the high dimensionality, heterogeneity, and correlated genes of RNA-seq data. This study aims to develop novel approaches for predicting survival and identifying biomarkers using RNA-seq data.Introduction/Objective Accurate patient survival predictions are vital for effective cancer treatments. Precision medicine uses gene expression data to improve prognosis by considering genetic variability. Predicting survival in cancer patients using high-dimensional gene expression data, such as RNA-sequencing (RNA-seq), attracted much attention in recent years. However, the literature contains limited algorithms for survival modeling that account for the high dimensionality, heterogeneity, and correlated genes of RNA-seq data. This study aims to develop novel approaches for predicting survival and identifying biomarkers using RNA-seq data.Methods Survival data of RNA-seq is first transformed into binary classification data using a stacking algorithm. Then, block-based priority-Lasso and IPF-Lasso algorithms are applied to the dataset, which includes two distinct types of variables. Additionally, sample weights obtained from the voom transformation are incorporated. Our approaches, named voomStackLasso, are tested on 12 real datasets from the TCGA database. We used Harrell's concordance index and the integrated Brier score to evaluate model performance, and the number of selected features to assess model sparsity.Results The results indicated that the voomStackLasso algorithms demonstrated comparable or superior performance compared to other existing survival algorithms. Furthermore, we have introduced an R package called MLSeqSurv, which allows for the utilization of both established survival algorithms from the literature and voomStackLasso algorithms for RNA-seq data.Conclusion This study introduces two new algorithms for the survival analysis of RNA-seq data. Additionally, this study has led to new research directions for applying both existing and newly developed classification algorithms to the survival analysis of RNA-seq data.Article Identification of Potential Dual HDAC6 and HSP90 Inhibitors for the Treatment of Cancer Using Molecular Docking, Molecular Dynamics and MM/PBSA Studies: A Comprehensive In Silico Study(Bentham Science Publ Ltd, 2026) Yucel, Muhsin Samet; Akcok, IsmailBackground Histone deacetylase 6 (HDAC6) and heat shock protein 90 (Hsp90) are crucial therapeutic targets in cancer research with their interconnected roles in regulating protein homeostasis and cellular processes. The interaction of these proteins within the cytosolic complex plays a critical role in regulating cancer cell survival and progression. Notably, current studies highlight that the simultaneous inhibition of HDAC6 and Hsp90 can produce synergistic effects and offer a promising therapeutic potential for combating malignant cancers.Objective The objective of this study was to explore potential compounds that can inhibit both HDAC6 and Hsp90 proteins.Methods In this study, a number of in-silico computational techniques were employed. A total of 791 molecules, sharing at least 30% similarity with previously identified four HDAC inhibitors, were obtained from the ZINC15 database and subjected to docking on HDAC6 and Hsp90 proteins. The top eight ligands demonstrating the best binding scores against both targets, with panobinostat and ganetespib serving as reference compounds for HDAC6 and Hsp90, respectively, were selected for further analysis. Subsequently, ADME prediction and molecular dynamics simulations were conducted on the selected ligands.Results A detailed molecular docking, molecular dynamics simulations and ADME studies have revealed that ZINC27653366 exhibited the highest inhibitory potential against both Hsp90 and HDAC6 target proteins, making it the most promising inhibitor.Conclusion In conclusion, although additional in vitro and in vivo studies are required for the validation, in silico evaluation of ZINC27653366 may position it as a promising candidate for the treatment of different types of cancers.Article G-S a Prior Biological Knowledge-Based Pattern Detection and Enrichment Framework for Multi-Omics Data Integration(MDPI, 2025-11-29) Unlu Yazici, Miray; Bakir-Gungor, Burcu; Yousef, MalikThe rapid advancements in high-throughput technologies have led to a dramatic increase in diverse -omics data types, enabling comprehensive analyses, especially for complex diseases like cancer. Despite the development of multi-omics approaches, the challenges of scaling integration to massive, heterogeneous -omics datasets suggest that novel computational tools need to be designed. In this study, we propose an approach for integrating microRNA (miRNA) and messenger RNA (mRNA) expression data, incorporating prior biological knowledge (PBK). This approach scores and ranks groups of miRNAs and their associated genes using cross-validation iterations. The proposed method incorporates a Pattern detection (P) component to identify molecular motifs unique to each biological group. The analysis also facilitates the visualization of the groups, facilitating the identification of co-occurring groups and their characteristic features across iterations. Furthermore, the groups are scored using an over-representation analysis through a new Enrichment (E) component in each iteration. The clusters of the groups based on the Enrichment Scores (ESs) are visualized in a heatmap to obtain novel insights into the collective behavior and dependencies of the groups, aiming to understand the molecular mechanisms of complex diseases. The developed G-S-M-E tool not only provides performance metrics and biological scores at the group level but also offers comprehensive insights into intricate multi-omics interactions. In summary, our study emphasizes the importance of mathematical and data science methodologies in elucidating intricate multi-omics integration, yielding a formalized approach that deepens our comprehension of complex diseases.Article Toward the Design of New Α-Carboline Derivatives Against Anaplastic Lymphoma Kinase (Alk): A Comprehensive in Silico Approach(Wiley-VCH Verlag GmbH, 2025-11) Sari, Ceyhun; Akcok, IsmailAfter the first description of anaplastic lymphoma kinase (ALK) in an anaplastic large cell lymphoma cell line as a nucleophosmin (NPM) fusion partner, ALK and its various fusion partners have been implicated in numerous cancers such as non-small cell lung cancer (NSCLC), anaplastic large cell lymphoma (ALCL), neuroblastoma, and rhabdomyosarcoma. In the last decade, several compounds targeting ALK have been developed and approved by the Food and Drug Administration (FDA). Despite the advances of generations of ALK inhibitors, a recent study highlighted that around half of the ALK-positive NSCLC patients will go through disease progression in response to first-line alectinib, which is a second-generation ALK inhibitor. In this study, we aimed to propose a novel alpha-carboline compound targeting the ALK tyrosine kinase domain to be used against various types of cancer in which ALK fusion proteins may be involved. In this regard, we designed more than 200 alpha-carboline derivatives and investigated their binding properties against ALK tyrosine kinase by using in silico protocols consisting of molecular docking studies, molecular dynamics simulations, MM/PBSA binding free energy calculation, and essential dynamics analysis. Considering the obtained results, we developed two promising candidates, compounds 208 & 209 with -9.05 and -9.80 binding energies, respectively, which demonstrated improved binding profiles over the course of a 300 ns simulation.Book Part Citation - Scopus: 1Sustainable Strategies for Cancer Phytomedicine: Balancing Efficacy and the Environment Responsibility(Springer Nature, 2025) Sari, Sibel; Saylan, DemetCancer is a complex disease, with approximately six million new cases reported annually. Despite the numerous treatment strategies employed worldwide, the severity of cancer continues to increase. Conventional cancer treatments, such as surgery, radiotherapy, and chemotherapy, are standard practices, but their clinical success is constrained by toxic side effects leading to damage to healthy tissues, unavoidable off-target effects, and significant cancer recurrence resulting from incomplete surgical removal. Therefore, interest in alternative therapies sourced primarily from natural products is increasing. The popularity of phytomedicine in cancer treatment approaches is increasing because of its efficacy, affordability, accessibility, and minimal adverse effects. Additionally, green chemistry approaches can be used to synthesize a wide array of anticancer drugs with various chemical structures, enhancing their therapeutic efficacy while minimizing or eliminating side effects and toxicity. The enhanced efficacy of cancer medicines made from plants is achieved via molecular innovations that support precise targeting. Various drug delivery systems that aim to reduce environmental pollution while reducing waste can be optimized for better results in therapy through nanotechnology. The delivery of effective cancer therapies while preserving the environment for generations to come is the objective of this approach, which includes green chemistry, sustainable production, and molecular developments. © 2025 Elsevier B.V., All rights reserved.Book Part Citation - Scopus: 1Measurement of Autophagic Activity in Cancer Cells With Flow Cytometric Analysis Using Cyto-Id Staining(Humana Press Inc., 2024) Şansaçar, Merve; Gencer Akçok, Emel BaşakAutophagy is an evolutionarily conserved process providing the energy that cells need to survive, especially in stress situations, through catabolic processes. Considering the dual role of autophagy in cancer cells depending on the cellular context, it is crucial to comprehend the effect of drug candidates put forward to prevent cancer through the autophagy pathway. The CYTO-ID® Autophagy Detection Kit allows a rapid, specific and quantitative measurement of autophagic activity at the cellular level using a 488 nm-excitable green fluorescent detection reagent via flow cytometer. In this chapter, we present the CYTO-ID® Autophagy Detection method with a stepwise protocol to monitor the autophagy flux after the application of any compound to suspension cancer cell lines with flow cytometric analysis. © 2025 Elsevier B.V., All rights reserved.Article Efficacy of Combinatorial Inhibition of Hedgehog and Autophagy Pathways on the Survival of AML Cell Lines(Academic Press inc Elsevier Science, 2025-08) Sansacar, Merve; Pepe, Nihan Aktas; Akcok, Emel Basak Gencer; El Khatib, Mona; Gencer Akçok, Emel BaşakAcute myeloid leukemia (AML) is a common hematopoietic disease that results from diverse genetic abnormalities. Dysregulation of important signaling pathways, including the PI3K/AKT/mTOR, Wnt and Hedgehog pathways, plays crucial roles in the development of AML. Hedgehog pathway (Hh) is a conserved signaling pathway that is crucial throughout embryogenesis. Hh plays an important role in the regulation of autophagy, known as the cellular recycling process of organelles and unwanted proteins. Many studies have noted that the modulation of autophagy could act as a survival mechanism in AML. Considering the pivotal role of autophagy and Hh signaling in AML, understanding the relationship between these pathways is important for overcoming leukemia. Therefore, we examined the efficacy of Hh inhibition by GLI-ANTagonist 61 (GANT61) in MOLM-13 and CMK cells via 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenil-2H-tetrazolium bromide (MTT) cell viability assays. GANT61 resulted in decreased cell viability in both cell lines. Therefore, we focused on the outcome of autophagy modulation in AML cells. We observed that the autophagy inhibitors ammonium chloride (NH4CI), chloroquine (CQ), and nocodazole led to a significant reduction in the proliferation of both cell lines. Cotreatment with autophagy pathway inhibitors and GANT61 synergistically affected both AML cell lines. Moreover, dual targeting of these pathways resulted in arrest at the G0/G1 phase in MOLM-13 cells but not in CMK cells. Furthermore, the combination of nocodazole and GANT61 increased the expression level of LC3B-II in both cell lines. Compared with that in the untreated control cells, the GLI1 gene expression level in both cell lines was significantly lower after GANT61 and autophagy cotreatment. In conclusion, targeting Hh and autophagy could be a favorable option to combat AML.Article Anticancer Effect of Ethanolic Yellow Hawthorn Extract on Chronic Myeloid Leukemia Cells and Acute Myeloid Leukemia Cells(Ondokuz Mayis Universitesi, 2025) Arslan, Ayşe Nur; Akçok, IsmailCancer is a disease characterized by abnormal cell growth and invasion and metastasis of these cells to other tissues or organs of the body. Natural products have been used for centuries as drugs or in drug development, especially for the treatment of cancer. Besides, extracting natural products with several bioactive compounds has a promising effect on cancer treatment. In this study, we aimed to investigate the anticancer effect of the ethanolic extract of yellow hawthorn fruits on K562 (Chronic Myeloid Leukemia) and MOLM-13 (Acute Myeloid Leukemia) cell lines. The antiproliferative effect of the ethanolic extract of yellow hawthorn fruits was investigated in time-and dose-dependent manners. The Annexin-V/Propidium Iodide (PI) double staining was used to examine the apoptosis. Furthermore, cell cycle analysis is conducted by PI staining. The cell viability of K562 and MOLM-13 cell lines was significantly reduced by the ethanolic extract of yellow hawthorn fruits with IC50 values of 9144 µg/mL and 3515 µg/mL in 48-hour incubation time, respectively. Moreover, the results showed that the ethanolic extract of yellow hawthorn fruits caused an increased apoptosis by 12.7-and 8.87-fold changes in K562 and MOLM-13 cell lines compared to control groups, respectively. Ethanolic extract of yellow hawthorn fruit has reduced cell proliferation, induced apoptosis and arrested the cell cycle at G0/G1 phase by 71% in MOLM-13 and at G2/M phase by 80.3% and G0/G1 phase by 38.2 % in K562 cells. Further studies should be conducted to elucidate the mechanism of the effect of yellow hawthorn fruit on these cancer cells. © 2025 Elsevier B.V., All rights reserved.