Anglia Ruskin Research Online (ARRO)
Browse

A quantitative image analysis for the cellular cytoskeleton during in vitro tumor growth

Download (1.15 MB)
journal contribution
posted on 2023-08-30, 14:59 authored by Mohammad A. Al-Mamun, Worawut Srisukkham, Dewan Md Farid, Lorna Ravenhill, Li Zhang, Mohammed Alamgir Hossain, Rosemary Bass
The cellular cytoskeleton is a dynamic subcellular structure that can be a marker of key biological phenomena including cell division, organelle movement, shape changes and locomotion during the avascular tumor phase. Little attention is paid to quantify changes in the cytoskeleton while nuclei and cytoplasmic both are present in subcellular microscopic images. In this paper, we proposed a quantitative image analysis method to analyze subcellular cytoskeletal changes using a texture analysis method preceded by segmentation of nuclei, cytoplasm and ruffling regions (area except nuclei and cytoplasm). To test and validate this model we hypothesized that Mammary Serine Protease Inhibitor (maspin) acts as cytoskeleton regulator that mediates cell-extracellular matrix (ECM) adhesion in tumor. Maspin-a tumor suppressor gene shows multiple tumor suppressive properties such as increasing tumor cell apoptosis and reducing migration, proliferation, invasion, and overall tumor metastasis. The proposed method obtained separated ruffling regions from segmentation steps and then adopted gray–level histograms (GLH) and grey-level co-occurrence matrix (GLCM) texture analysis techniques. In order to verify the reliability, the proposed texture analysis method was used to compare the control and maspin expressing cells grown on different ECM components: plastic, collagen I, fibronectin and laminin. The results show that the texture parameters extracted reflect the different cytoskeletal changes. These changes indicate that maspin acts as a regulator of the cell-ECM enhancement process, while it reduces the cell migration. Overall, this paper not only presents a quantitative image analysis approach to analyze subcellular cytoskeletal architectures but also provides a comprehensive tool for the biologist, pathologist, cancer specialist, and computer scientist to understand cellular and subcellular organization of cells. In long term, this method can be extended to be used in live cell tracking in vivo, image informatics based point-of-care expert system and quantification of various complex architectures in organisms.

History

Refereed

  • Yes

Volume

92

Page range

39-51

Publication title

Expert Systems with Applications

ISSN

0957-4174

Publisher

Elsevier

File version

  • Accepted version

Language

  • eng

Legacy posted date

2017-11-28

Legacy creation date

2017-11-30

Legacy Faculty/School/Department

ARCHIVED Faculty of Science & Technology (until September 2018)

Usage metrics

    ARU Outputs

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC