Researchers have developed a graphene platform which could support the fast diagnosis of pancreatic cancer.
Pancreatic cancer is the second most fatal cancer and the seventh-leading cause of cancer deaths worldwide. Despite recent progress in cancer diagnosis and treatment, the survival rate of pancreatic cancer has only slightly improved in the past decade.
The early detection of pancreatic cancer is crucial to improving survival rates. Many patients do not show symptoms in the early stages and current diagnostic methods include imaging tests and tissue biopsies, which can be invasive, expensive, and time-consuming.
Researchers set out to develop a platform that could detect and diagnose pancreatic cancer before a patient develops advanced symptoms. Their new findings, published in the journal ACS Nano, could lead to the development of a non-invasive diagnostic tool for pancreatic cancer.
Methods of detection
The team of researchers, led by the late Professor Norbert Klein in the Department of Materials, have developed a graphene sensor platform.
This sensor holds great promise for the fast diagnosis of pancreatic cancer at early stages when the treatment options are most effective Dr Sami Ramadan Research Associate, Imperial College London
The key to developing the graphene sensor was the investigation of exosomes. Exosomes are nanoscale vesicles secreted by all cells, including cancer cells. They contain a variety of molecules, including proteins, DNAs, and RNAs, which can provide valuable information about the cell that released them.
One of the most important advantages of exosomes for cancer detection is that they can be isolated from a variety of bodily fluids, such as blood, urine, and saliva. This can allow for non-invasive and repeated sampling, which is essential for early cancer detection and the monitoring of disease progression.
Researchers found that pancreatic cancer exosomes have unique characteristics that can be used to distinguish them from exosomes released by healthy cells. Using these findings, they have engineered a sensor platform that can identify pancreatic cancer exosomes in patient blood plasma samples in only 45 minutes.
How does the sensor work?
Researchers have developed a simple and user-friendly portable platform to perform the test, with easy to read electronics that are accessible to individuals without prior experience with medical devices.
The sensor is made up of an array of graphene sensors. Each graphene sensor is coated with a different antibody specific for a different protein or other molecule found on pancreatic cancer exosomes.
A small drop of blood plasma from a patient is placed on the array. The antibodies on the sensor bind to proteins and other molecules on the pancreatic cancer exosomes, causing a change in the electrical conductivity of the graphene sensor. This change in conductivity is measured and used to identify the presence of pancreatic cancer exosomes in the blood plasma sample.
The sensor tested blood plasma samples from eighteen pancreatic cancer patients and eight people who did not have cancer. Findings indicated that the platform was able to accurately discriminate between the two groups in 100% of cases. The platform array was also able to detect pancreatic cancer exosomes at the early stages, including stages one and two.
What could this mean for the future?
The development of the graphene sensor platform could be a significant step forward in the fight against pancreatic cancer.
If the findings are confirmed in further clinical trials, this sensor could emerge as an important and non-invasive tool for diagnosing pancreatic cancer in its early stages.
This research is the legacy of the late Professor Norbert Klein. Professor Klein was the lead researcher on this project and a dear colleague in the Department of Materials. He very sadly passed away in August 2023. Read our tribute to Professor Klein.
The full article can be found at: Y. Tianyi, et al., ‘Graphene Sensor Arrays for Rapid and Accurate Detection of Pancreatic Cancer Exosomes in Patients’ Blood Plasma Samples’, ACS Nano. DOI: 10.1021/acsnano.3c01812 (Available on ACS Nano)
Article text (excluding photos or graphics) © Imperial College London.
Photos and graphics subject to third party copyright used with permission or © Imperial College London.
Department of Materials
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