Literature DB >> 26750438

Quantitative analysis of the cell-surface roughness and viscoelasticity for breast cancer cells discrimination using atomic force microscopy.

Yuhua Wang1, Chaoxian Xu1, Ningcheng Jiang1, Liqin Zheng1, Jinshu Zeng2, Caimin Qiu1, Hongqin Yang1, Shusen Xie1.   

Abstract

Breast cancer has been one of the most common malignant tumors threatening female health with high incidence. Cell mechanics is becoming an important issue and could serves as a potential indicator for early cancer diagnosis. In this study, atomic force microscopy (AFM) was applied to characterize and compare the surface nanostructure and viscoelasticity of different breast cell lines. Our results show that breast cancerous cells MCF-7 exhibit more disorganized filamentous cytoskeleton structure with increased membrane roughness compared to benign breast cells MCF-10A (P < 0.05). The viscoelastic properties, including elasticity and viscosity, are significantly different between the two cell lines. MCF-7 displays reduced elasticity and viscosity, indicating that breast cancer cells are softer and more fluid than benign counterpart. Our findings provide new insights into the biophysical changes of cells during tumor transformation and suggest it could be used for early cancer detection at single cell level. SCANNING 38:558-563, 2016.
© 2016 Wiley Periodicals, Inc. © Wiley Periodicals, Inc.

Entities:  

Keywords:  AFM; breast cancer cell; elasticity; surface roughness; viscosity

Mesh:

Year:  2016        PMID: 26750438     DOI: 10.1002/sca.21300

Source DB:  PubMed          Journal:  Scanning        ISSN: 0161-0457            Impact factor:   1.932


  11 in total

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Journal:  PLoS One       Date:  2017-12-06       Impact factor: 3.240

8.  Short-Term Degradation of Bi-Component Electrospun Fibers: Qualitative and Quantitative Evaluations via AFM Analysis.

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Journal:  J Funct Biomater       Date:  2018-03-30

9.  The head and neck cancer (HN-5) cell line properties extraction by AFM.

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Journal:  J Biol Eng       Date:  2020-03-18       Impact factor: 4.355

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Authors:  David Schwartz; Sujatha Iyengar
Journal:  Viral Immunol       Date:  2020-04       Impact factor: 2.257

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