Atomic Force Microscopy Applications in Cancer Cell Biophysics

Atomic Force Microscopy (AFM) has emerged as a powerful tool for interrogating the biophysical properties of cancer cells at nanometre resolution. By mechanically probing the cell surface and subcellular structures, AFM reveals changes in stiffness, topography and adhesion associated with malignancy. Malignant transformation often leads to cytoskeletal reorganisation, membrane ruffling and alterations in pericellular coat composition, all of which influence the cell’s mechanical phenotype. AFM indentation assays quantify elastic modulus variations between healthy and cancerous cells, highlighting the tendency of many tumour cells to soften relative to normal counterparts. Simultaneously, high-resolution imaging modes capture nanoscale surface features—ranging from fractal topographies to discrete adhesive sites—offering novel markers for early detection and grading of metastatic potential. Advances in tapping and sub-resonance modes, including the so-called “ringing” mode, have expanded the repertoire of mechanical and compositional parameters accessible from a single scan, enabling correlative studies of adhesion, viscoelasticity and morphological heterogeneity. Integration of AFM data with machine-learning algorithms has further refined phenotypic classification, allowing robust discrimination of cell lines and detection of subtle biophysical signatures in histological sections. Collectively, these developments underscore the global significance of AFM in cancer research, with practical applications in diagnostic screening, assessment of drug responses and elucidation of tumour biomechanics.

Research from Nature Portfolio

Innovations in sub-resonance tapping modes have propelled AFM applications in cell biophysics by introducing the “ringing” mode, which captures multiple compositional channels—such as restored adhesion, pull-off distances and detachment energy—at speeds comparable to conventional modes. This approach has demonstrated enhanced contrast and reduced artefacts when imaging fixed human epithelial cells, corneocytes and implant polymers, laying the groundwork for its application to cancer cell surfaces. By exploiting the cantilever’s post-detachment oscillations, ringing mode provides simultaneous quantitative maps of adhesion and viscoelastic properties, potentially enabling direct correlation of molecular layer composition with mechanical stiffness. These multimodal datasets pave the way for integrating nanoscale mechanophenotyping into routine analyses of tumour biopsies.

Atomic Force Microscopy Applications in Cancer Cell Biophysics publication trend

The graph below shows the total number of articles in atomic force microscopy applications in cancer cell biophysics across all publications each year (not limited to Nature Index journals).

Technical terms

Atomic Force Microscopy (AFM): A scanning probe technique that measures surface topography and mechanical properties by detecting forces between a sharp tip and the sample surface.

Young’s modulus: A measure of material stiffness derived from AFM indentation, indicating resistance to elastic deformation.

Pericellular layer: The glycoprotein-rich coating surrounding the cell membrane, influencing mechanical indentation profiles.

Adhesion map: A spatially resolved image of local adhesion forces between the AFM probe and the cell surface.

Viscoelasticity: The combined viscous and elastic response of a material under deformation, measurable by dynamic AFM modes.

References

1. Mechanical Way To Study Molecular Structure of Pericellular Layer. ACS Applied Materials & Interfaces (2023).
2. Machine Learning Allows for Distinguishing Precancerous and Cancerous Human Epithelial Cervical Cells Using High-Resolution AFM Imaging of Adhesion Maps. Cells (2023).
3. Nanoscale Prognosis of Colorectal Cancer Metastasis from AFM Image Processing of Histological Sections. Cancers (2023).
4. Nanoscale compositional mapping of cells, tissues, and polymers with ringing mode of atomic force microscopy. Scientific Reports (2017).
5. Emergence of fractal geometry on the surface of human cervical epithelial cells during progression towards cancer. New Journal of Physics (2015).
6. Atomic Force Microscopy Detects the Difference in Cancer Cells of Different Neoplastic Aggressiveness via Machine Learning. Advanced NanoBiomed Research (2021).