The spread of invasive cancer cells from a tumor's original site to distant parts of the body is known as metastasis. It is the leading cause of death in people with cancer. University of California San Diego School of Medicine researchers have designed sensors that can detect and measure the metastatic potential of single cancer cells.
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. The researchers engineered biosensors designed to monitor multiple signaling programs that drive tumor metastasis; upon sensing those signals a fluorescent signal would be turned on only when tumor cells acquired high potential to metastasize, and therefore turn deadly.
Cancer cells alter normal cell communications by hijacking one of many signaling pathways to permit metastasis to occur. As the tumor cells adapt to the environment or cancer treatment, predicting which pathway will be used becomes difficult. By comparing proteins and protein modifications in normal versus all cancer tissues, the researchers identified a particular protein and its unique modification called tyrosine-phosphorylated CCDC88A (GIV/Girdin) that is only present in solid tumor cells. Comparative analyses indicated that this modification could represent a point of convergence of multiple signaling pathways commonly hijacked by tumor cells during metastasis.
The team used novel engineered biosensors and sophisticated microscopes to monitor the modification of GIV and found that, indeed, fluorescent signals reflected a tumor cell's metastatic tendency. They were then able to measure the metastatic potential of single cancer cells and account for the unknowns of an evolving tumor biology through this activity. The result was the development of Fluorescence Resonance Energy Transfer (FRET) biosensors.
Although highly aggressive and adaptive, very few cancer cells metastasize, and that metastatic potential comes and goes. If metastasis can be predicted, this data could be used to personalize treatment to individual patients. For example, patients whose cancer is not predicted to metastasize or whose disease could be excised surgically might be spared from highly toxic therapies. Patients whose cancer is predicted to spread aggressively might be treated with precision medicine to target the metastatic cells.