Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

Browse

Filters

2021 - 20232

Settings

Access Right: Closed AccessAuthor: search.filters.author.Pesen Okvur, Devrim

Search Results

Now showing 1 - 2 of 2
  • Book Part
    Citation - Scopus: 1
    Automated 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 Uğur
    This 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: 24
    Citation - Scopus: 23
    On-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, Özden
    Metastasis 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.