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Recent Advances in Biosensor Technology for Early-Stage Detection of Hepatocellular Carcinoma-Specific Biomarkers: An Overview

  • Raja Chinnappan*
  • , Tariq Makhzoum
  • , Momo Arai
  • , Amro Hajja
  • , Farah Abul Rub
  • , Ibrahim Alodhaibi
  • , Mohammed Alfuwais
  • , Muhammad Affan Elahi
  • , Eman Abdullah Alshehri
  • , Lohit Ramachandran
  • , Naresh Kumar Mani
  • , Shugufta Abrahim
  • , Mohammad Shabab Mir
  • , Khaled Al-Kattan
  • , Tanveer Ahmad Mir
  • , Ahmed Yaqinuddin*
  • *Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract

Hepatocellular carcinoma is currently the most common malignancy of the liver. It typically occurs due to a series of oncogenic mutations that lead to aberrant cell replication. Most commonly, hepatocellular carcinoma (HCC) occurs as a result of pre-occurring liver diseases, such as hepatitis and cirrhosis. Given its aggressive nature and poor prognosis, the early screening and diagnosis of HCC are crucial. However, due to its plethora of underlying risk factors and pathophysiologies, patient presentation often varies in the early stages, with many patients presenting with few, if any, specific symptoms in the early stages. Conventionally, screening and diagnosis are performed through radiological examination, with diagnosis confirmed by biopsy. Imaging modalities tend to be limited by their requirement of large, expensive equipment; time-consuming operation; and a lack of accurate diagnosis, whereas a biopsy’s invasive nature makes it unappealing for repetitive use. Recently, biosensors have gained attention for their potential to detect numerous conditions rapidly, cheaply, accurately, and without complex equipment and training. Through their sensing platforms, they aim to detect various biomarkers, such as nucleic acids, proteins, and even whole cells extracted by a liquid biopsy. Numerous biosensors have been developed that may detect HCC in its early stages. We discuss the recent updates in biosensing technology, highlighting its competitive potential compared to conventional methodology and its prospects as a tool for screening and diagnosis.

Original languageEnglish
Article number1519
JournalDiagnostics
Volume14
Issue number14
DOIs
Publication statusPublished - 07-2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Clinical Biochemistry

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