ArticleScientific reports2019
Quantitative phase imaging reveals matrix stiffness-dependent growth and migration of cancer cells.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
- Review
- Pan-cancer analysis reveals molecular signatures for predicting matrix stiffness in solid tumors.International journal of cancer · 2026Article
- Brillouin microscopy in cancer research: a review.Journal of biomedical optics · 2025Review
- Non-destructive viability assessment of cancer cell spheroids using dynamic optical coherence tomography with trypan blue validation.Biomedical optics express · 2024Article
- Quantitative phase imaging techniques for measuring scattering properties of cells and tissues: a review-part I.Journal of biomedical optics · 2024Review
- Perspective on quantitative phase imaging to improve precision cancer medicine.Journal of biomedical optics · 2024Article
- Atomic force microscopy-mediated mechanobiological profiling of complex human tissues.Biomaterials · 2023Review
- Quantitative phase imaging for characterization of single cell growth dynamics.Lasers in medical science · 2023Review
- Characterizing viscoelastic properties of human melanoma tissue using Prony series.Frontiers in bioengineering and biotechnology · 2023Article
- White blood cell detection, classification and analysis using phase imaging with computational specificity (PICS).Scientific reports · 2022Article
- Types of spectroscopy and microscopy techniques for cancer diagnosis: a review.Lasers in medical science · 2022Review
- The gate to metastasis: key players in cancer cell intravasation.The FEBS journal · 2022Review
- The Role of Extracellular Matrix Remodeling in Skin Tumor Progression and Therapeutic Resistance.Frontiers in molecular biosciences · 2022Review
- The effect of pupil transmittance on axial resolution of reflection phase microscopy.Scientific reports · 2021Article
- Extracellular Matrix Remodeling by Fibroblast-MMP14 Regulates Melanoma Growth.International journal of molecular sciences · 2021Article
- Label-free SARS-CoV-2 detection and classification using phase imaging with computational specificity.Light, science & applications · 2021Article
- Monitoring reactivation of latent HIV by label-free gradient light interference microscopy.iScience · 2021Article
- Label-free screening of brain tissue myelin content using phase imaging with computational specificity (PICS).APL photonics · 2021Article
- Computational interference microscopy enabled by deep learning.APL photonics · 2021Article
- Integration of mechanical and ECM microenvironment signals in the determination of cancer stem cell states.Current stem cell reports · 2021Article
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer progression involves complex signals within the tumor microenvironment that orchestrate proliferation and invasive processes. The mechanical properties of the extracellular matrix (ECM) within this microenvironment has been demonstrated to influence growth and the migratory phenotype that precedes invasion. Here we present the integration of a label-free quantitative phase imaging technique, spatial light interference microscopy (SLIM)-with protein-conjugated hydrogel substrates-to explore how the stiffness of the ECM influences melanoma cells of varying metastatic potential. Melanoma cells of high metastatic potential demonstrate increased growth and velocity characteristics relative to cells of low metastatic potential. Cell velocity in the highly metastatic population shows a relative insensitivity to matrix stiffness suggesting adoption of migratory routines that are independent of mechanics to facilitate invasion. The use of SLIM and engineered substrates provides a new approach to characterize the invasive properties of live cells as a function of microenvironment parameters. This work provides fundamental insight into the relationship between growth, migration and metastatic potential, and provides a new tool for profiling cancer cells for clinical grading and development of patient-specific therapeutic regimens.
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