Nano Cantilevers Detect Specific Tumor Mutations

Cancers arise from different types of genetic mutations that occur in a variety of places of the human genome. Some cancers types are known to have a single identifying mutation of a gene, cancerous cell RNA is slightly different from its healthy counterpart. Some cancer medications only work on tumors with specific mutations, so identifying them is key to deciding on a therapy regimen.

Following up on this, researchers at the Swiss Nanoscience Institute of the University of Basel the Ludwig Institute for Cancer Research in Lausanne developed nano-scale cantilevers coated with DNA molecules that can bind to the RNA from sample cells. When the binding occurs, the cantilevers shift due to the change in the mechanical stress, the angle of which is detected using a laser. The system doesn’t require any amplification or labeling of the molecules, making it rapid, easy and cheap to use.

From Alpha Galileo:

In experiments the researchers could show that cells carrying this genetic mutation can be distinguished from others lacking the mutation. RNA of cells from a cell culture was tested in concentrations similar to those in tissue samples. Since the researchers could detect the mutation in RNA stemming from different cell lines, the method actually works independent of the origin of samples.

Dr. François Huber, first author of the publication, explains: “The technique can also be applied to other types of cancer that depend on mutations in individual genes, for example in gastrointestinal tumors and lung cancer. This shows the wide application potential in cancer diagnostics and personalized health care.” Co-author Dr. Donata Rimoldi adds: “Only the interdisciplinary approach in medicine, biology and physics allows to apply novel nanotechnology methods in medicine for the benefit of patients.”

Press release: Nanosensors support skin cancer therapy

Abstract in Nature Nanotechnology: Direct detection of a BRAF mutation in total RNA from melanoma cells using cantilever arrays