Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Letter Citation - WoS: 1Citation - Scopus: 2C-Met Activation Promotes Extravasation of Hepatocellular Carcinoma Cells Into 3d-Cultured Hepatocyte Cells in Lab-On Device(Elsevier, 2023) Solmaz, Gülhas; Bağcı, Gülsün; Çömez, Dehan; Topel, Hande; Yılmaz, Yeliz; Bağırsakçı, Ezgi; Güneş, Aysim; Batı Ayaz, Gizem; Tahmaz, İsmail; Bilgen, Müge; Pesen Okvur, DevrimActivation of c-Met signaling is associated with an aggressive phenotype and poor prognosis in hepatocellular carcinoma (HCC); however, its contribution to organ preference in metastasis remains unclear. In this study, using a Lab on a Chip device, we defined the role of aberrant c-Met activation in regulating the extravasation and homing capacity of HCC cells. Our studies showed that (i) c-Met overexpression and activation direct HCC cells preferentially towards the hepatocytes-enriched microenvironment, and (ii) blockage of c-Met phosphorylation by a small molecule inhibitor attenuated extravasation and homing capacity of HCC cells. These results, thus, demonstrate the role of c-Met signaling in regulating the colonization of HCC cells preferentially in the liver. © 2023 Elsevier B.V.Book Part Citation - Scopus: 1Automated Analysis of Phase-Contrast Optical Microscopy Time-Lapse Images: Application To Wound Healing and Cell Motility Assays of Breast Cancer(Elsevier, 2023) Erdem, Yusuf Sait; Ayanzadeh, Aydın; Mayalı, Berkay; Balıkçı, Muhammed; Belli, Özge Nur; Uçar, Mahmut; Yalçın Özuysal, Özden; Pesen Okvur, Devrim; Önal, Sevgi; Morani, Kenan; Iheme, Leonardo Obinna; Töreyin, Behçet UğurThis chapter describes a workflow for analyzing phase-contrast microscopy (PCM) data from two fundamental types of biomedical assays: assays for cell motility and assays for wound healing. The workflow of the analysis is composed of the methods for acquiring, restoring, segmenting, and quantifying biomedical data. In the literature, there have been separate methods aimed at specific stages of PCM data analysis. Nonetheless, there has never been a complete workflow for all stages of analysis. This work is an innovation that proposes an end-to-end workflow for image pre-processing, deep learning segmentation, tracking, and quantification stages in cell motility and wound healing assay analyses. The findings indicate that domain knowledge can be used to make simple but significant improvements to the results of cutting-edge methods. Furthermore, even for deep learning-based methods, pre-processing is clearly a necessary step in the workflow. © 2023 Elsevier Inc. All rights reserved.Article Citation - WoS: 11Citation - Scopus: 13Fli1 and Fra1 Transcription Factors Drive the Transcriptional Regulatory Networks Characterizing Muscle Invasive Bladder Cancer(Nature Research, 2023) Güneri Sözeri, Perihan Yağmur; Özden Yılmaz, Gülden; Kısım, Aslı; Çakıroğlu, Ece; Eray, Aleyna; Uzuner, Hamdiye; Karakülah, Gökhan; Pesen Okvur, Devrim; Şentürk, Şerif; Erkek Özhan, Serapis and progression of this disease. In this study, we defined the active regulatory landscape of MIBC and NMIBC cell lines using H3K27ac ChIP-seq and used an integrative approach to combine our findings with existing data. Our analysis revealed FRA1 and FLI1 as two critical transcription factors differentially regulating MIBC regulatory landscape. We show that FRA1 and FLI1 regulate the genes involved in epithelial cell migration and cell junction organization. Knock-down of FRA1 and FLI1 in MIBC revealed the downregulation of several EMT-related genes such as MAP4K4 and FLOT1. Further, ChIP-SICAP performed for FRA1 and FLI1 enabled us to infer chromatin binding partners of these transcription factors and link this information with their target genes. Finally, we show that knock-down of FRA1 and FLI1 result in significant reduction of invasion capacity of MIBC cells towards muscle microenvironment using IC-CHIP assays. Our results collectively highlight the role of these transcription factors in selection and design of targeted options for treatment of MIBC.Conference Object Detection and Restoration Pipeline for Phase Contrast Microscopy Time Series Images(IEEE, 2022) Iheme, Leonardo O.; Uçar, Mahmut; Önal, Sevgi; Yalçın Özuysal, Özden; Pesen Okvur, Devrim; Töreyin, Behçet U.; Ünay, DevrimWe propose a pre-processing pipeline for the de-tection and restoration of distorted frames in phase-contrast microscopy time-series images. The analysis is based on the average intensity values of the frames within any given time- series image. The extent of the correction of intensity variation in frames is determined by the normalization of the difference between the current frame's average intensity and the median of average intensity of all frames. Our restoration algorithm preserves regional trans-passing pixels, does not cause new distortions, and increases the histogram similarity between the distorted and non-distorted frames. The algorithm was validated on 15,395 time-series image frames from 27 experiments and the results were found to be visually and quantitatively accurate.Article Citation - WoS: 3Citation - Scopus: 6Improved Cell Segmentation Using Deep Learning in Label-Free Optical Microscopy Images(TÜBİTAK - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, 2021) Ayanzadeh, Aydın; Yalçın Özuysal, Özden; Pesen Okvur, Devrim; Önal, Sevgi; Töreyin, Behçet Uğur; Ünay, DevrimThe recently popular deep neural networks (DNNs) have a significant effect on the improvement of segmentation accuracy from various perspectives, including robustness and completeness in comparison to conventional methods. We determined that the naive U-Net has some lacks in specific perspectives and there is high potential for further enhancements on the model. Therefore, we employed some modifications in different folds of the U-Net to overcome this problem. Based on the probable opportunity for improvement, we develop a novel architecture by using an alternative feature extractor in the encoder of U-Net and replacing the plain blocks with residual blocks in the decoder. This alteration makes the model superconvergent yielding improved performance results on two challenging optical microscopy image series: a phase-contrast dataset of our own (MDA-MB-231) and a brightfield dataset from a well-known challenge (DSB2018). We utilized the U-Net with pretrained ResNet-18 as the encoder for the segmentation task. Hence, following the modifications, we redesign a novel skip-connection to reduce the semantic gap between the encoder and the decoder. The proposed skip-connection increases the accuracy of the model on both datasets. The proposed segmentation approach results in Jaccard Index values of 85.0% and 89.2% on the DSB2018 and MDA-MB-231 datasets, respectively. The results reveal that our method achieves competitive results compared to the state-of-the-art approaches and surpasses the performance of baseline approaches.Conference Object Citation - Scopus: 2Yara İyileşmesi Mikroskopi Görüntü Serilerinin Otomatik Analizi - Bir Ön-çalışma(IEEE, 2020) Mayalı, Berkay; Şaylığ, Orkun; Yalçın Özuysal, Özden; Pesen Okvur, Devrim; Töreyin, Behçet Uğur; Ünay, DevrimCollective cell analysis from microscopy image series is important for wound healing research. Computer-based automation of such analyses may help in rapid acquisition of reliable and reproducible results. In this study phase -contrast optical microscopy image series of an in-vitro wound healing essay is manually delineated by two experts and its analysis is realized, traditional image processing and deep learning based approaches for automated segmentation of wound area are developed and their perlOrmance comparisons are carried out.Conference Object Citation - Scopus: 1A Preliminary Study on Cell Motility Analysis From Phase-Contrast Microscopy Image Series(IEEE, 2020) Kayan, Emre; Kavuşan, Tarık; Önal, Sevgi; Pesen Okvur, Devrim; Yalçın Özuysal, Özden; Töreyin, Behçet Uğur; Ünay, DevrimAnalyses of morphology, polarity, and motility of cells is important for cell biology research such as metastatic and invasive capacity of cells, wound healing, and embryonic development. Automation of such analyses using image series of phase-contrast optical microscopy, which allows label-free imaging of live cells in their living environment, is a need. With this purpose, in this study image series of a cell motility experiment is manually annotated, and an automation algorithm realizing motion and shape analyses of cells using the annotated data is developed. In addition, due to the low number of annotated data at hand, a U-Net based solution is devised for automated segmentation of the cells and its performance is evaluated.Article Citation - WoS: 24Citation - Scopus: 23On-Chip Determination of Tissue-Specific Metastatic Potential of Breast Cancer Cells(Wiley, 2021) Fıratlıgil Yıldırır, Burcu; Batı Ayaz, Gizem; Tahmaz, İsmail; Bilgen, Müge; Pesen Okvur, Devrim; Yalçın Özuysal, ÖzdenMetastasis is one of the major obstacles for breast cancer patients. Limitations of current models demand the development of custom platforms to predict metastatic potential and homing choices of cancer cells. Here, two organ-on-chip platforms, invasion/chemotaxis (IC-chip) and extravasation (EX-chip) were used for the quantitative assessment of invasion and extravasation towards specific tissues. Lung, liver and breast microenvironments were simulated in the chips using tissue-specific cells embedded in matrigel. In the IC-chip, invasive MDA-MB-231, but not noninvasive MCF-7 breast cancer cells invaded into lung and liver microenvironments. In the EX-chip, MDA-MB-231 cells extravasated more into the lung compared to the liver and breast microenvironments. In addition, lung-specific MDA-MB-231 clone invaded and extravasated into the lung microenvironment more efficiently than the bone-specific clone. Both invasion/chemotaxis and extravasation results were in agreement with published clinical data. Collectively, our results show that IC-chip and EX-chip, simulating tissue-specific microenvironments, can distinguish different in vivo metastatic phenotypes, in vitro. Determination of tissue-specific metastatic potential of breast cancer cells is expected to improve diagnosis and help select the ideal therapy.Article Citation - WoS: 10Citation - Scopus: 11A New Drug Testing Platform Based on 3d Tri-Culture in Lab-On Devices(Elsevier, 2020) Gökçe, Begüm; Akçok, İsmail; Çağır, Ali; Pesen Okvur, DevrimDrug discovery has a 90% rate of failure because preclinical platforms for drug testing do not mimic the in vivo conditions. Doxorubicin (DOX) is a commonly used drug to treat breast cancer patients even though it has side effects. Lab-on-a-chip (LOC) devices provide spatial control at the micrometer scale and can thus emulate the cancer microenvironment. Here, using a multidisciplinary approach, a new drug testing platform based on 3D tri-culture in LOC devices was developed. Breast cancer cells alone or with normal mammary epithelial cells and macrophages were cultured in matrigel in LOC devices. The platform was used to test DOX and (R)-4'-methylklavuzon (KLA), which is a new anti-cancer drug candidate. Results showed that DOX and KLA were equally effective on breast cancer cells in 3D monoculture. KLA produced 26% less death for breast cancer cells than DOX in 3D tri-culture. More importantly, DOX was not selective between breast cancer cells and normal mammary epithelial cells in 3D tri- culture whereas KLA caused 56% less cell death than DOX for normal mammary epithelial cells. Results strongly recommend that 3D tri-culture in LOC devices be used for assessment of drug toxicity at the preclinical stage.Article Citation - WoS: 20Citation - Scopus: 21Breast Cancer Cells and Macrophages in a Paracrine-Juxtacrine Loop(Elsevier, 2021) Önal, Sevgi; Türker Burhan, Merve; Batı Ayaz, Gizem; Yanık, Hamdullah; Pesen Okvur, DevrimBreast cancer cells (BCC) and macrophages are known to interact via epidermal growth factor (EGF) produced by macrophages and colony stimulating factor-1 (CSF-1) produced by BCC. Despite contradictory findings, this interaction is perceived as a paracrine loop. Further, the underlying mechanism of interaction remains unclear. Here, we investigated interactions of BCC with macrophages in 2D and 3D. While both BCC and macrophages showed invasion/chemotaxis to fetal bovine serum, only macrophages showed chemotaxis to BCC in custom designed 3D cell-on-a-chip devices. These results were in agreement with gradient simulation results and ELISA results showing that macrophage-derived-EGF was not secreted into macrophage-conditioned-medium. Live cell imaging of BCC in the presence and absence of iressa showed that macrophages but not macrophage-derived-matrix modulated adhesion and motility of BCC in 2D. 3D co-culture experiments in collagen and matrigel showed that BCC changed their multicellular organization in the presence of macrophages. In custom designed 3D co-culture cell-on-a-chip devices, macrophages promoted and reduced migration of BCC in collagen and matrigel, respectively. Furthermore, adherent but not suspended BCC endocytosed EGFR when in contact with macrophages. Collectively, our data revealed that macrophages showed chemotaxis towards BCC whereas BCC required direct contact to interact with macrophage-derived-EGF. Therefore, we propose that the interaction between cancer cells and macrophages is a paracrine-juxtacrine loop of CSF-1 and EGF, respectively. © 2020 Elsevier Ltd