Quantification of topological features in cell meshes to explore E-cadherin dysfunction.

Area of Science:

• Cell biology
• Cancer research
• Bioinformatics

Background:

• E-cadherin is crucial for cell adhesion; its defects in cancer promote detachment, migration, and metastasis.
• E-cadherin dysfunction impacts cell topology and tissue organization, leading to abnormal cellular distribution patterns.

Purpose of the Study:

• To develop a novel quantitative approach using microscopy images to analyze abnormal cellular distribution patterns in cancer.
• To establish a network analysis method for quantifying topological features of cell-cell interactions.

Main Methods:

• Generated undirected graphs of triangles from microscopy images to represent cell positioning and structural organization.
• Employed network analysis on triangle geometric features (area, edge length, angles) and their variances compared to equilateral triangles.
• Validated the approach using synthetic networks and cells expressing wild-type and cancer-related E-cadherin mutants (A634V, R749W, P799R).

Main Results:

• The network analysis accurately reproduced cell positioning and structural organization.
• Cancer-associated E-cadherin mutants (A634V, R749W, P799R) showed more disorganized spatial distribution than wild-type cells.
• The P799R mutant exhibited significant length and angle distortions, indicating dynamic and plastic cellular interactions and abnormal cytoskeletal organization.

Conclusions:

• Topological analysis of cell network diagrams is an effective tool for quantifying changes in cell-cell interactions.
• This method can be applied to various biological processes, including tissue morphogenesis and cancer progression.
• The findings provide a new quantitative method to study the impact of E-cadherin mutations on cell behavior in cancer.