Novel Sensor for Imaging Pancreatic β-cells for the diagnosis and prognosis of Diabetes

One-tenth of the US population has been diagnosed with diabetes. 1 in 5 people currently do not know that they are diabetic. Of those cases, 90-95% are Type II Diabetes. While Type I Diabetes accounts for only 5-10% of cases, it is the second most chronic illness in children.

Figure 1. Insulin's Role in Glucose Transportation.

Type 1 diabetes results from the death of pancreatic β-cells. β-cells produce and excrete insulin and amylin, a hormone that prevents post-meal spikes in blood glucose levels. Insulin is released from the β-cells in response to elevated blood glucose concentration and helps the body convert, use and store glucose in liver, muscle and fat cells (Figure 1). If your β-cells die, your body cannot produce insulin; Consequently, your cells will be starved and the high concentrations of glucose can trigger diabetic ketoacidosis, which can be fatal.

While Type II diabetes is the more prevalent form, there are a multitude of chronic causes that can eventually lead to β-cell death. Essentially, it’s harder to track the development of Type II diabetes. Since β-cell death is the main trigger for Type I diabetes development, it can serve as an important biomarker for diagnosis and prognosis, or treatment progression.

Figure 2. Current Imaging Techniques Targeting β-cells.

Currently, there are four methods for detection of β-cells: radiolabeled antibodies, signaling molecules, small molecule sensors, and nanoparticles (Figure 2). These detection methods can be visualized using Magnetic Resonance Imaging (MRI), Positron Emission Tomagraphy (PET), Single Photon Emission Computed Tomagraphy (SPECT) and fluorescence spectroscopy. While MRI, PET, and SPECT can give physicians an idea of the shape of organs and the location of these imaging agents, they cannot tell us the amount of β-cells present in the pancreas. Therefore, it would be useful to have a small molecule sensor that uses both fluorescence spectroscopy to help estimate β-cell concentration and PET imaging.

Figure 3. Visualizing pancreatic β-cells using PiY staining.

Previous work from Dong Yun Lee utilized a sensor called PiY for the detection of pancreatic β-cells. They injected PiY into the tail vein of a mouse and imaged the pancreatic tissue to see if β-cells were stained with the sensor. In Figure 3, the bright-field (BF) view shows the pancreatic tissue section and the PiY view shows the β-cells stained green. Since PiY selectively stained only the β-cells in the pancreatic tissue, Lee concluded that PiY could selectively target β-cells only in the pancreas. The biggest issues with this sensor was that it only worked well in ex vivo (outside of the organism) imaging, wasn't visible after 5 hours, and it was found in larger concentrations in the liver.

Figure 4. Ex vivo imaging of mouse organs using β-cell sensor, PiF.

Following the issues with PiY, Lee and Young-Tae Chang decided to use the diversity-oriented fluorescence library approach (DOFLA) to find a sensor that binds selectively to β-cells in the pancreas rather than other organs. This approach essentially screens thousands of sensors against β-cells and sees which binds the best. Using the DOLFA, they found PiF to be the best sensor for targeting β-cells. In Figure 4, Lee and Chang showed that PiF selectively bound to β-cells in the pancreas. The large volume of fluorescence in the left and right kidney can be attributed to the kidneys flushing out excess sensor.

Figure 5. In vivo PET images of [18F]PiF in mice.

After proving that PiF functioned as a highly selective small molecule fluorescence sensor for β-cells, Lee and Chang replaced the fluorine atom of PiF with a radioactive 18F isotope for PET imaging. The mice were injected with the [18F]PiF compound and subjected to PET imaging for 120 minutes (Figure 5). Lee and Chang discovered that the highest uptake of [18F]PiF occurred at 30 minutes. After 30 minutes, [18F]PiF was rapidly flushed out to the kidneys.

While this fluorescence/PET dual sensor isn't ready yet for human trials, it shows some promising work in the development of tools for the diagnosis and prognosis of diabetes. If you're interested in reading more about β-cell targeting sensors, you can read the Lee and Chang's full published paper online.