Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death globally. At-risk individuals are advised to undergo periodic HCC screening. If identified at an early state, surgical resection offers a favorable prognosis. However, most patients have advanced disease at the time of diagnosis with an estimated 5-year survival rates <20%. The lack of surveillance and insufficient early diagnostic precision are blamed for the poor prognosis and high mortality of HCC.
Most HCC patients are often not diagnosed until advanced stages because of two main reasons: the inability of early HCC lesions to produce overt symptoms and the additional complexity layer due to the presence of cirrhosis. This offers limited therapeutic options and reduced survival rates. This problem can be effectively solved by decreasing the barriers for high-risk patients to comply with monitoring and surveillance programs that promote early HCC diagnosis. Early-stage HCC detection requires high-risk patients to frequently measure serum biomarkers like C-reactive protein, which is difficult to achieve due to inaccessibility and high costs of tests.
Given the limitations of the current screening techniques, more portable, affordable and highly sensitive techniques are urgently needed for rapid and early HCC detection. Although a number of point-of-care test technologies for HCC detection have been proposed, numerous shortcomings still limit their practical applications. The discovery of the giant magnetoresistive (GMR) effects has given rise to many technologies and devices. It has been identified as a potential phenomenon for developing biosensors for early HCC diagnosis.
On this account, Dr. Chengyang Yao, Dr. Elaine Ng and Professor Shan Wang from Stanford University developed a new automated and mobile GMR biosensor system for early HCC diagnosis. The device design was based on the design of the previous GMR biosensors and custom electronic and microfluidic systems were incorporated to perform wash steps and liquid manipulations. Its design and implementation process, underlying working principle and unique advantages were studied and discussed both quantitatively and qualitatively. Finally, its usability and efficacy for HCC detection were verified through multiplexed C-reactive protein and alpha-fetoprotein tests. The work is currently published in the research journal, Biosensors and Bioelectronics.
The authors demonstrated the GMR biosensor’s capability to simultaneously detect and quantify different HCC-related biomarkers with ease and improved accuracy. Specifically, it performed an automated assay within 28 minutes, indicating its feasibility and reliability. Compared to other testing techniques, users only needed to add the test sample manually into the disposable cartridge and press the button provided on the smartphone app without having to either directly interact with liquid reagents or possess lab skills. The test achieved the standard lab test level requirements in terms of limit, dynamic range and linearity.
In summary, the design and implementation of an automated GMR biosensor for early HCC detection was demonstrated and successfully tested. Given its fantastic high sensitivity, portability and ease of use, the presented GMR biosensor is an ideal platform for quick, rapid and early HCC detection at point-of-care, especially in regions with limited resources. This platform is also versatile and has vast possibilities, including detection of DNA biomarkers. In a statement to Medicine Innovates, Dr. Chengyang Yao, first author explained that in general clinical practice has demonstrated that diagnosing the tumors in early stages is key to improve the survival of patient. the proposed biosensor would be instrumental strategy and may prove to be crucial in future clinical management of this fatal disease.
Additionally, Dr. Yao and his team have expanded the sensing technology to detect DNA targets and are developing an automated way to perform on-chip polymerase chain reaction and GMR detection. With the unparalleled multiplexing capabilities, multiple DNA targets are being detected at once, from the same sample.
Yao, C., Ng, E., & Wang, S. (2022). An automated and mobile magnetoresistive biosensor system for early hepatocellular carcinoma diagnosis. Biosensors And Bioelectronics, 202, 113982.