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What can be learned from molecular diagnostic techniques and genetic signatures?

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Citation (Scopus)

Abstract

Liver cancer is a disease characterized by a long latency during which hepatocytes pass through a continual process of damage and regeneration leading to accumulation of genetic aberrations. Although several genes and signalling pathways involved in cell proliferation and differentiation have been implicated in hepatocellular carcinoma (HCC), widespread gaps still exist in our understanding of the molecular mechanisms of hepatocarcinogenesis. Microarray technology is a widely applied tool for studying the pathogenesis of HCC and the identification of genes, which could translate into novel diagnostic tools and therapeutic targets. Many studies have reported unique gene expression profiles in HCC that can identify transition from mild to moderate liver fibrosis and can recognize, at an early stage, dysplastic nodules likely to transform into hepatocellular tumours. This review highlights recent contributions of the microarray technology in advancing our knowledge of the molecular alterations observed at different stages of hepatocellular carcinogenesis. In the future, specific gene expression profiles can possibly predict micro-metastasis or early recurrence after resection of HCC for a better patient outcome.

Original languageEnglish (UK)
Title of host publicationClinical Dilemmas in Primary Liver Cancer
Publisherwiley
Pages60-64
Number of pages5
ISBN (Electronic)9781119962205
ISBN (Print)9780470657973
DOIs
Publication statusPublished - 1 Jan 2011

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

Keywords

  • Cluster analysis
  • Fibrosis
  • Gene expression
  • Gene signature
  • Glypican 3
  • Hepatocellular carcinoma
  • Liver cancer
  • Metastasis
  • Microarray
  • Tumour recurrence
  • Wnt signalling

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