Cancer Detected by Dynamic Morphology Tracking on Aptamer-Grafted Surfaces

The surface receptors are found in large numbers on the surface of cancer cells.

Scientists at the University of Texas (Arlington, TX, USA) and their colleagues have developed a novel cancer cell detection method based on real time cell behavior tracking on engineered surfaces. A synthetic ribonucleic acid (RNA) molecule is coated on chip surface to identify cancer cells. The one-step tumor cell detection approach is based on the dynamic morphological behavior tracking of cancer cells on a ligand modified surface.

The human glioblastoma (hGBM) cells showed distinctly enhanced cell movements and activity on the RNA functionalized chips. Every cell on the surface was tracked in real time for several minutes immediately after seeding until these were finally attached. Cancer cells were found to be very active in the aptamer microenvironment, changing their shapes rapidly from spherical to semi-elliptical, with much flatter spread and extending pseudopods at regular intervals.

When incubated on a functionalized surface, the balancing forces between cell surface molecules and the surface-bound aptamers together with the flexibility of the membranes caused cells to show these distinct dynamic activities and variations in their morphologies. On the other hand, healthy cells remained distinguishingly inactive on the surface over the same period. The quantitative image analysis of cell morphologies provided feature vectors that were statistically distinct between normal and cancer cells.

Samir Iqbal, PhD. the principal investigator of the study said, “The initial results hold great potential for applications like cancer screening. A multiple chip based device targeting several proteins can lead to a generic cancer diagnostic platform. The advantage of the technology compared to others is that it is suitable for a quick diagnosis. Once matured, the method has potential to serve as an additional modality to identify tumor cells based on their physical behavior from blood samples or biopsy specimen directly drawn from patients.” The study was published on November 16, 2015, in the journal TECHNOLOGY.

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