Integrative molecular analysis of colorectal cancer and gastric cancer: What have we learnt?

Avani Athauda, Eva Segelov, Zohra Ali, Ian Chau

Research output: Contribution to journalReview ArticleResearchpeer-review

7 Citations (Scopus)


Gastrointestinal (GI) malignancies comprise a diverse group of cancers with varying aetiology, clinical course, management and prognosis. Advances over the last decade in molecular diagnostics in colorectal cancer (CRC) have helped to improve our understanding of the underlying complex mechanisms in the development and progression of this highly heterogenous disease. Large scale integrative analysis has identified molecularly distinct subgroups of CRC with differing clinical behaviour. It was hoped that these discoveries would fuel the development of novel drug targets and new treatments to shift the management of advanced CRC from an empirical strategy to a biomarker driven approach based on underlying molecular characteristics. However, biomarkers in current clinical practice remain limited in CRC. Gastric cancer (GC) has also been slow to benefit from biomarker discovery and development and the successful utilisation of targeted therapies, with the exception of trastuzumab in HER2 positive cancers. More recently, molecular analysis of GC has also identified distinct subgroups within these cancers with differing behaviour and therapeutic targets. In addition, our deeper understanding of the underlying molecular biology of GI cancers has led to the consideration of alterations above and beyond gene mutations. The clonal, stromal and immune characteristics of GI malignancies are increasingly recognised as important in therapeutic targeting. The challenge remains to apply the data generated through molecular exploration into clinical practice in order to provide personalised treatment to each individual patient.

Original languageEnglish
Pages (from-to)31-40
Number of pages10
JournalCancer Treatment Reviews
Publication statusPublished - 1 Feb 2019


  • Biomarkers
  • Gastrointestinal cancers
  • Gene expression profiles
  • Molecular subclassification

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