Release date: 2014-07-18
Despite some amazing results in medical development, cancer is still the number one killer of human beings, putting a heavy burden on our medical system. Diagnosing and intervening cancer early in the disease is key to reducing human and economic losses.
Researchers from Arizona State University have developed an innovative disease detection technology that can detect several common cancers based on cancer-induced immune responses. They named it immunosignaturing technology. The findings were published in the July 14th issue of the Proceedings of the National Academy of Sciences (PNAS).
"There have been some interesting results from immunolabeling over the years, but the introduction of this technology into the scientific community requires great patience," said Phillip Stafford, lead author of the paper, Arizona State University.
To date, only a small number of cancer biomarkers have been approved by the FDA for clinical use, and the approved biomarker effects are often very limited. There are many problems. For example, the body's immune response to cancer is quite complex, and there is a big difference between patients and patients, in addition to the type and stage of cancer.
Individual biomarkers often lack the sensitivity and resolution required for a positive diagnosis. Diagnostic molecules such as RNA, DNA, proteins or peptides are often present in extremely small amounts after dilution in the blood, making accurate diagnosis particularly challenging. Despite the large amount of research devoted to establishing better pre-symptoms of disease symptoms, it has been disappointing.
Immunolabeling technology utilizes a different approach. Instead of adopting a simplified biomarker paradigm, it relies on a composite system to analyze all antibodies circulating in the blood at a given time.
This technique relies on a chip in which thousands of randomly generated peptides are printed on glass slides. When a small drop of blood (less than 1 microliter of blood is needed) is spread across the chip, the antibodies in the blood selectively bind to the peptide on the chip, forming an immunologically active image, the immunolabel.
Since peptide sequences are random and independent of any naturally occurring disease antigen, the authors believe that this simple platform has the potential to be applied to a variety of disease types. This is much better than highly specific bioassays because only one biomarker antibody can be detected, which often has a large number of errors and is not sensitive enough.
Current research assesses the ability of immunolabeling techniques to identify multiple diseases. The team obtained 20 samples from 5 groups of cancer patients, together with samples from 20 healthy controls, calibrated the results and established reference immunolabels. Subsequently, they conducted a blinded assessment of 120 independent samples involving the same disease. The results confirmed that the accuracy reached 95%.
To further assess the ability of immunolabeling, they tested more than 1,500 historical samples covering 14 different diseases, including 12 cancers. 75% of the samples were used in the training phase and the remaining 25% were used for blind testing. The researchers confirmed that the average diagnostic accuracy was over 98%, indicating that the immunolabel is suitable for classifying multiple diseases at the same time.
Specifically, in one experiment, researchers were able to detect and distinguish a complex heterogeneous disease, stage IV breast cancer, from four other cancers and healthy controls. In the second experiment, the researchers identified 14 diseases and healthy controls by immunolabeling. The cancers tested included 3 different stages of breast cancer, 4 different brain cancers, 2 pancreatic cancers, ovarian cancer, and 2 different blood cancers.
Compared to traditional methods for detecting one-to-one molecular recognition events, only one or a small number of analytes can be evaluated. Immunolabeling provides an attractive method for capturing disease complexity and greatly improves detection.
Source: Biopass
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