Mechanical properties of cancer cells depend on number of passages: Atomic force microscopy indentation study

Dokukin, Maxim; Guz, Nataliia; Sokolov, Igor

doi:10.7567/jjap.56.08lb01

Cited by 16 publications

(12 citation statements)

References 48 publications

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“…34 The ability of the model to distinguish contributions of long polysaccharide molecules to the PB layer and the corrugations of the pericellular membrane (microridges and microvilli) was demonstrated using Guinea pig fibroblast cells. 35 The utility of the brush model was confirmed in the study of cancer cells, 6,25,[35][36][37] aging, 38 the dependence of cell mechanics on cell passages, 36 etc.…”

Section: Introductionmentioning

confidence: 91%

Cell mechanics can be robustly derived from AFM indentation data using the brush model: error analysis

Makarova

Sokolov

2022

Nanoscale

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Section: Introductionmentioning

confidence: 91%

Cell mechanics can be robustly derived from AFM indentation data using the brush model: error analysis

Makarova

Sokolov

2022

Nanoscale

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“…It's worth noting that there are both large and small round cells. According to the literature of previous researchers, the small round cells may adhere to the substrate loosely but the large round cells can adhere to the substrate firmly (Dokukin et al, 2017) [Figure 3C(I)]. In this article, all the cells selected for the experiments were firmly attached.…”

Section: Different Cytoskeleton Network Structures Of Cells With Different Adherent Morphologiesmentioning

confidence: 84%

“…In order to reduce the changes in the mechanical properties of cells during the culture process (Dokukin et al, 2017), cells between passage 6 and passage 10 were used for experiments. The cells were seeded in 35 × 10 mm Petri dish (Corning).…”

Section: Cell Preparation For Afm Experimentsmentioning

confidence: 99%

AFM Force Relaxation Curve Reveals That the Decrease of Membrane Tension Is the Essential Reason for the Softening of Cancer Cells

Ren

Gao

Han

2021

Front. Cell Dev. Biol.

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Differences in stiffness constitute an extremely important aspect of the mechanical differences between cancer cells and normal cells, and atomic force microscopy (AFM) is the most commonly used tool to characterize the difference in stiffness. However, the process of mechanical characterization using AFM has been controversial and the influence of the membrane tension on AFM measurement results was often ignored. Here, a physical model involving a simultaneous consideration of the effects of the cell membrane, cytoskeleton network and cytosol was proposed. We carried out a theoretical analysis of AFM force relaxation curves, and as a result solved many of the remaining controversial issues regarding AFM-based mechanical characterization of cells, and provided a quantitative solution for the membrane tension measured using AFM indentation experiments for the first time. From the results of experiments on cells with different adherent shapes and different pairs of normal cells and cancer cells, we found additional force provided by membrane tension to be the main component of the force applied to the AFM probe, with decreased cell membrane tension being the essential reason for the greater softness of cancer cells than of normal cells. Hence, regulating membrane tension may become an important method for regulating the behavior of cancer cells.

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“…The passage numbers used for the 4 cell lines in this manuscript were below 20. The variation in the properties of cell lines can still be considered stable 46,47 . The culture environment was kept constant during the cell cultures.…”

Section: Cell Culturementioning

confidence: 99%

Scalable nanolaminated SERS multiwell cell culture assay

et al. 2020

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This paper presents a new cell culture platform enabling label-free surface-enhanced Raman spectroscopy (SERS) analysis of biological samples. The platform integrates a multilayered metal-insulator-metal nanolaminated SERS substrate and polydimethylsiloxane (PDMS) multiwells for the simultaneous analysis of cultured cells. Multiple cell lines, including breast normal and cancer cells and prostate cancer cells, were used to validate the applicability of this unique platform. The cell lines were cultured in different wells. The Raman spectra of over 100 cells from each cell line were collected and analyzed after 12 h of introducing the cells to the assay. The unique Raman spectra of each cell line yielded biomarkers for identifying cancerous and normal cells. A kernel-based machine learning algorithm was used to extract the high-dimensional variables from the Raman spectra. Specifically, the nonnegative garrote on a kernel machine classifier is a hybrid approach with a mixed nonparametric model that considers the nonlinear relationships between the higher-dimension variables. The breast cancer cell lines and normal breast epithelial cells were distinguished with an accuracy close to 90%. The prediction rate between breast cancer cells and prostate cancer cells reached 94%. Four blind test groups were used to evaluate the prediction power of the SERS spectra. The peak intensities at the selected Raman shifts of the testing groups were selected and compared with the training groups used in the machine learning algorithm. The blind testing groups were correctly predicted 100% of the time, demonstrating the applicability of the multiwell SERS array for analyzing cell populations for cancer research.

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Mechanical properties of cancer cells depend on number of passages: Atomic force microscopy indentation study

Cited by 16 publications

References 48 publications

Cell mechanics can be robustly derived from AFM indentation data using the brush model: error analysis

Cell mechanics can be robustly derived from AFM indentation data using the brush model: error analysis

AFM Force Relaxation Curve Reveals That the Decrease of Membrane Tension Is the Essential Reason for the Softening of Cancer Cells

Scalable nanolaminated SERS multiwell cell culture assay

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