Chemotaxis of cancer cells in three-dimensional environment monitored label-free by quantitative phase digital holographic microscopy

2017 ◽  
Author(s):  
Björn Kemper ◽  
Jürgen Schnekenburger ◽  
Steffi Ketelhut
Keyword(s):  
Cancer Cells ◽  
Three Dimensional ◽  
Digital Holographic Microscopy ◽  
Label Free ◽  
Quantitative Phase ◽  
Holographic Microscopy

scholarly journals Subpopulations of Organoid-Forming Cells Have Different Motility

2020 ◽  
Vol 10 (13) ◽  
pp. 4673
Author(s):  
David Gomez Jimenez ◽  
Sofia Carreira Santos ◽  
Lennart Greiff ◽  
Kersti Alm ◽  
Malin Lindstedt
Keyword(s):  
Tumor Cells ◽  
Three Dimensional ◽  
Cell Aggregation ◽  
Digital Holographic Microscopy ◽  
Optical Parameters ◽  
Label Free ◽  
Light Passing ◽  
Tumorigenic Potential ◽  
Holographic Microscopy ◽  
Tumor Organoids

Cancer stem cells from oropharyngeal squamous cell carcinoma (OPSCC) have the ability to self-renew and differentiate into heterogeneous three-dimensional structures carrying features of tumor cells. Here, we describe a simple and label-free method for generating tumor organoids, and imaging them using live digital holographic microscopy (DHM) on the basis of the phase shift caused by light passing through the cells. We show early events of cell aggregation during tumor-organoid formation, and display their heterogeneity in terms of optical parameters up to an optical volume of 105 µm3. Lastly, by sorting OPSCC epithelial cells, we demonstrate that CD44+ cells displayed greater motility and tumor-forming capacity than those of CD44− cells. These results were in line with previous reports highlighting increased invasive and tumorigenic potential in tumor cells expressing high levels of CD44. Our method provides insight into the formation of tumor organoids, and could be used to assess stemness-associated biomarkers and drug screenings on the basis of tumor organoids.

scholarly journals Deep learning with digital holographic microscopy discriminates apoptosis and necroptosis

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Joost Verduijn ◽  
Louis Van der Meeren ◽  
Dmitri V. Krysko ◽  
André G. Skirtach
Keyword(s):  
Cell Death ◽  
Deep Learning ◽  
Cancer Cells ◽  
Cell Biology ◽  
Learning Algorithm ◽  
Digital Holographic Microscopy ◽  
Label Free ◽  
Deep Learning Algorithm ◽  
Regulated Cell Death ◽  
Holographic Microscopy

AbstractRegulated cell death modalities such as apoptosis and necroptosis play an important role in regulating different cellular processes. Currently, regulated cell death is identified using the golden standard techniques such as fluorescence microscopy and flow cytometry. However, they require fluorescent labels, which are potentially phototoxic. Therefore, there is a need for the development of new label-free methods. In this work, we apply Digital Holographic Microscopy (DHM) coupled with a deep learning algorithm to distinguish between alive, apoptotic and necroptotic cells in murine cancer cells. This method is solely based on label-free quantitative phase images, where the phase delay of light by cells is quantified and is used to calculate their topography. We show that a combination of label-free DHM in a high-throughput set-up (~10,000 cells per condition) can discriminate between apoptosis, necroptosis and alive cells in the L929sAhFas cell line with a precision of over 85%. To the best of our knowledge, this is the first time deep learning in the form of convolutional neural networks is applied to distinguish—with a high accuracy—apoptosis and necroptosis and alive cancer cells from each other in a label-free manner. It is expected that the approach described here will have a profound impact on research in regulated cell death, biomedicine and the field of (cancer) cell biology in general.

scholarly journals Morphological Measurement of Living Cells in Methanol with Digital Holographic Microscopy

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Yunxin Wang ◽  
Yishu Yang ◽  
Dayong Wang ◽  
Liting Ouyang ◽  
Yizhuo Zhang ◽  
...  
Keyword(s):  
Morphological Change ◽  
Optical Thickness ◽  
Hela Cells ◽  
Living Cells ◽  
Digital Holographic Microscopy ◽  
Phase Image ◽  
Toxicity Screening ◽  
Label Free ◽  
Quantitative Phase ◽  
Holographic Microscopy

Cell morphology is the research foundation in many applications related to the estimation of cell status, drug response, and toxicity screening. In biomedical field, the quantitative phase detection is an inevitable trend for living cells. In this paper, the morphological change of HeLa cells treated with methanol of different concentrations is detected using digital holographic microscopy. The compact image-plane digital holographic system is designed based on fiber elements. The quantitative phase image of living cells is obtained in combination with numerical analysis. The statistical analysis shows that the area and average optical thickness of HeLa cells treated with 12.5% or 25% methanol reduce significantly, which indicates that the methanol with lower concentration could cause cellular shrinkage. The area of HeLa cells treated with 50% methanol is similar to that of normal cells(P>0.05), which reveals the fixative effect of methanol with higher concentration. The maximum optical thickness of the cells treated with 12.5%, 25%, and 50% methanol is greater than that of untreated cells, which implies the pyknosis of HeLa cells under the effect of methanol. All of the results demonstrate that digital holographic microscopy has supplied a noninvasive imaging alternative to measure the morphological change of label-free living cells.

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