Automated deformability cytometry technique was developed for cancer diagnostic and cell research applications.
Scientists report on a mechanical phenotyping approach to diagnosing disorders such as cancer, which involves slamming cells against a wall of fluid and effectively measuring how much they deform on impact. In addition to its potential applications in disease diagnosis, the University of California, Los Angeles (UCLA)-led team that developed the technique believes it could have widespread utility for the study of cell biology in a variety of clinical and research settings.
The researchers’ approach is based on an automated microfluidic-based deformability cytometry platform that they claim can image, measure, and analyze 2,000 cells per second as they are aligned toward and hit a fluid wall. Reporting in PNAS, the investigators first used the platform to detect the presence of rare metastatic cancer cells in pleural fluids. Detecting whether cancer cells are present in such samples to help diagnose metastasis is difficult using traditional cytological examination techniques because of the high density of white blood cells, and presence of other cell types such benign mesothelial cells. However, using the deformability cytometry platform the researchers were able to detect the presence of even very low numbers of malignant cells because these are much more deformable than the other cell types found in pleural effusions.
The technique was similarly able to determine states of acute and chronic inflammation by measuring the increased levels of deformability displayed by activated white blood cells. Overall, the technique was found to predict disease state in patients with cancer and immune activation with a sensitivity of 91% and a specificity of 86%.
To demonstrate the utility of the platform for applications in cell research, the researchers subsequently demonstrated its capacity to discriminate between undifferentiated human embryonic stem cells and their differentiated progeny, without the need to evaluate cell biomarkers. Essentially the undifferentiated stem cells are much more deformable than ESC-derived differentiated cells.
“This approach allows us to analyze cells at throughputs orders of magnitude faster than previously reported biophysical flow cytometers and single-cell mechanics tools,” state authors Dino Di Carlo, Ph.D., and colleagues. “Microfluidic deformability cytometry brings the statistical accuracy of traditional flow cytometric techniques to label-free biophysical biomarkers, enabling applications in clinical diagnostics, stem cell characterization and single-cell biophysics.”
The team reports its technique and experimental results in a paper titled “Hydrodynamic stretching of single cells for large population mechanical phenotyping.”