Analyzing hyperproduction of beta 2-microglobulin by nano biosensors: An update on potential blood biomarkers for precise detection
Beta-2-microglobulin (B2M) is a component of the major histocompatibility complex (MHC) class I molecules present on all nucleated cells. It is a small protein associated with the heavy chain of the MHC class I complex on the cell surface. Cancers, including multiple myeloma, leukemia, and lymphoma,...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | en |
| Published: |
Elsevier B.V.
2025
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| Subjects: | |
| Online Access: | https://eprints.ums.edu.my/id/eprint/44453/1/FULL%20TEXT.pdf https://eprints.ums.edu.my/id/eprint/44453/ https://doi.org/10.1016/j.microc.2025.114432 |
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| Summary: | Beta-2-microglobulin (B2M) is a component of the major histocompatibility complex (MHC) class I molecules present on all nucleated cells. It is a small protein associated with the heavy chain of the MHC class I complex on the cell surface. Cancers, including multiple myeloma, leukemia, and lymphoma, as well as inflammatory diseases, infections (such as Human immunodeficiency and Cytomegalovirus), and kidney disease, are often associated with high blood levels of B2M. However, conventional techniques are not sensitive enough to detect the concentration of biomarkers in early-stage diseases, making early-stage disease diagnosis a significant challenge. Thus, we review the benefits of using nanomaterials and nanobiosensors towards developing high sensitivity, specificity, and selective detection of biomarkers. Besides that, we include medical studies on B2M as a potential diagnosis and prognosis biomarker in several diseases. As a target or biomarker, B2M can be employed in creating nanobiosensors, which are cutting-edge instruments that integrate biological sensing and nanotechnology to identify specific molecules at extremely low concentrations. By categorizing the levels of B2M in the blood with the above complications, the current nanotechnogical-assisted biosensors can provide a platform for monoplex and multiplex sensing. In addition, the integration of machine learning and artificial intelligence in a biosensor holds the potential to revolutionize healthcare by enabling early-stage disease diagnosis, which could greatly benefit patients and healthcare providers. This advancement could lead to developing a telemedicine system with a multiplex biosensor, offering significant advantages for healthcare delivery. |
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