Systemic Nanomechanical Single-Cell Profiling Reveals Mechanophenotype Transitions Under Therapeutic Perturbation
- Journal
- Advanced science (Weinheim, Baden-Wurttemberg, Germany) (Q1)
- Published
- 17 July 2026
- Study design
- Unclassified
- Evidence level
- Level 5, Expert Opinion (CEBM 5)
- Authors
- Minhee Ku, Jinwon Kwon, Nara Yoon, Hyung Kwon Byeon, Jaemoon Yang
- PMID
- 42467926
- DOI
- 10.1002/advs.76613
Why clinicians should know about it
- Picked for Histology (paper of the day, 18 July 2026).
Abstract
Mechanical remodeling of cancer cells plays a critical role in regulating invasive behavior, yet its quantitative relationship with therapeutic response remains insufficiently defined. Here, we systematically characterize drug-induced mechanophenotype changes at the single-cell level using an integrated nanomechanical profiling approach that combines atomic force microscopy-based force mapping of fixed cells, high-resolution imaging, and cytomorphometric analysis under room-temperature conditions. Pharmacological perturbation induces pronounced cytoskeletal reorganization accompanied by increased cortical stiffness and surface roughness. Systemic multivariate analysis identifies 11 biophysical parameters associated with invasive capacity, with nucleus modulus, cytoskeletal network density, and cortical roughness emerging as dominant contributors. Dimensionality reduction (principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA)) reveals a distinct mechanophenotype transition characterized by elevated stiffness and suppressed protrusive activity. Especially, reduced invasiveness correlates with increased cortical roughness and reorganization of perinuclear cytoskeletal structures, indicating that these features define a quantitative mechanical signature of phenotypic reprogramming. This integrated mechanical signature enables discrimination between invasive and noninvasive states at the single-cell level. These results establish nanomechanical profiling as a quantitative framework for assessing drug-induced phenotypic transitions and provide a complementary approach to conventional molecular assays for evaluating therapeutic response in cancer cells.
Abstract as published, via PubMed.
For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.