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Medical imaging can give doctors a clear picture of what’s happening inside the body. This can help them recognise diseases early and start treatment immediately, which is better for the patient. Also, medical imaging can help doctors understand how diseases get worse and develop new ways to treat them.
With this, researchers from the Cancer Science Institute of Singapore (CSI Singapore) at the National University of Singapore (NUS), led by Assistant Professor Anand Jeyasekharan, have found a unique combination of oncogenes that could predict treatment resistance and, therefore, bad outcomes for patients with Diffuse large B cell lymphoma (DLBCL), the most common type of blood cancer in Singapore and around the world.
The most up-to-date technology can find this unique oncogenic mix, which shows that the cancer is resistant to treatment. However, the researchers went a step further and made a simple mathematical formula that could predict the percentage of cells based on information from well-known diagnostic methods. This makes it possible for this oncogene indicator to be used regularly in clinical practice.
Oncogenes are very important in the development of cancer because they control the production of “bad” oncoproteins that help cancer grow and stay alive and affect how well the treatment works. But cancers often have more than one of these oncogenes, and not every cancer cell has every oncogene.
Since oncogenes are usually studied one at a time, not much is known about how the “co-existence” of oncogenes in certain types of cancer cells affects a cancer patient’s chance of life. To address this knowledge deficit, the research team investigated whether and how oncogenes collaborate to resist treatment in DLBCL.
Immunohistochemistry, which measures MYC, BCL2, and BCL6, three oncogenes, is frequently used in clinical practice to detect high-risk DLBCL cases. Immunohistochemistry, on the other hand, is unable to concurrently detect these three oncogenes, making it impossible to spot cell subgroups that have oncogenic combinations.
Hence, the researchers used cutting-edge imaging technology known as multispectral microscopy with quantitative immunofluorescence to overcome this obstacle. This technique enables researchers to stain, photograph, and quantify several proteins in a single sample.
This is accomplished by the excitation of various proteins with various light wavelengths, enabling distinct visualisation of each protein. Since the method is quantitative, it is possible to gauge how much of each protein is present.
Multispectral microscopy with quantitative immunofluorescence would not be achievable without digital technology. This technique requires the ability to record, store, process, and analyse images at such high quality. With the help of digital technology, it is now feasible to analyse proteins in a much more in-depth and quantitative manner, which has improved knowledge of the molecular alterations linked to cancer.
Compared to older imaging technologies, this one has several benefits. First, it enables researchers to examine a variety of proteins at once, which can help them develop a more thorough understanding of the molecular alterations linked to cancer. Second, because the method is quantitative, scientists can quantify each protein and utilise that information to find biomarkers that can be used to detect and monitor the development of cancer.
In addition, this technology can completely alter how cancer is discovered and treated. This technology could result in the creation of fresh and more potent cancer treatments by giving researchers a more thorough grasp of the molecular alterations linked to cancer.