Vol. 2 No. 2 (2024)

  • Open Access

    Review

    Article ID: 1254

    Recent progress in Nanomaterial based biosensors for the detection of cancer biomarkers in human fluids

    by Razu Shahazi, Amirul Islam Saddam, Md Rakibul Islam, Mohammed Muzibur Rahman, Giti Paimard, Ajoy Kumer, Md. Mahmud Alam, Md. Kawsar Mahamud

    Nano Carbons, Vol.2, No.2, 2024; 426 Views

    Cancer is a global health challenge, and early detection is crucial for effective treatment to improve patient outcomes. In recent years, nanomaterial-based biosensors have emerged as powerful tools for the detection of cancer biomarkers in human fluids. This article highlights the recent progress in biosensor technology for the detection of cancer biomarkers, focusing on advancements in sensitivity, selectivity, multiplexed detection, liquid biopsies, point-of-care testing, wearable biosensors, and integration with artificial intelligence (AI). Recent advancements have significantly improved the sensitivity and selectivity of biosensors, allowing for the detection of low concentrations of cancer biomarkers in complex biological samples. Novel sensing technologies, such as nanomaterial-based sensors and aptamer-based sensors, have played a crucial role in enhancing biosensor performance. Multiplexed biosensors have the ability to simultaneously detect multiple cancer biomarkers, providing comprehensive diagnostic information. This capability is particularly valuable for accurate cancer diagnosis and prognosis. Liquid biopsies, which involve the detection of cancer biomarkers in circulating tumor cells, cell-free DNA, or exosomes present in body fluids, have gained considerable attention. Biosensors have played a pivotal role in the development of liquid biopsy technologies, offering non-invasive and real-time monitoring of cancer progression, treatment response, and the emergence of drug resistance. The integration of biosensors with AI algorithms has shown great potential. AI can analyze and interpret biosensor data, identifying patterns, correlations, and biomarker signatures that may be difficult to detect with traditional methods.

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