Biosensors developed to detect whether cancer is likely to spread
A new study out of the University of California San Diego School of Medicine is reporting the development of novel biosensors that can detect the metastatic potential of individual cancer cells. It's hoped the research can be used to produce a system that can accurately let doctors know how likely a cancer is to spread, helping inform what treatment to administer.
"Cancer would not be so devastating if it did not metastasize," explains Pradipta Ghosh, senior author on the new study. "Although there are many ways to detect metastasis once it has occurred, there has been nothing available to 'see' or 'measure' the potential of a tumor cell to metastasize in the future."
When a cancer spreads from its primary location to other parts of the body it becomes incredibly difficult to treat, so it is vital to find an effective biomarker that indicates a cancer's metastatic potential. The new research homed in on single protein that in metastatic cancer cells presented a very unique modification.
The team then engineered a novel biosensor that could effectively monitor the progression of this unique protein modification and trigger a fluorescent signal to indicate a measurement of the cell's metastatic tendency. Essentially, the sensor lights up when it meets a cell likely to metastasize.
"We have the potential not only to obtain information on single cell level, but also to see the plasticity of the process occurring in a single cell," says Ghosh. "This kind of imaging can be used when we are delivering treatment to see how individual cells are responding."
At this stage the researchers present the work as a proof of concept, only demonstrated in cultured tumor cells and not in a living body. Further work on the sensor technology is needed before any in vivo studies can be completed. Nevertheless, this is an exciting roadmap for a future diagnostic device that could literally monitor a tumor in real time inside a human body, notifying doctors when the cancer is most likely to start spreading.
The research was published in the journal iScience.
Source: University of California San Diego School of Medicine
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