Ontology-led molecular classification of colorectal cancer uncovers distinct tumour subtypes with therapeutic and clinical relevance

Student thesis: Doctoral ThesisDoctor of Philosophy


Colorectal cancer (CRC) is a multifaceted and heterogeneous disease. The molecular profiling of CRC has made it possible to detect tumours with unique biological features. Gene expression-based signatures have been at the forefront of cancer research in providing valuable prognostic and predictive information. However, these published signatures rarely make any clinical impact.

This thesis utilises in silico methods to interrogate a pre-existing gene signature and evaluate the underlying CRC biology defined by the stratification based on the gene signatures. Additionally, accessing the published gene signatures, a new classification system was developed that defines pathway-driven tumours for patient stratification and tested its prognostic value.

A transcriptional breast cancer (BC) originated DNA Damage Immune Response (DDIR) assay, revealed overlapping proinflammatory-like tumour biology in CRC, but with no clinical benefit from oxaliplatin (Chapter 3). Utilising transcriptional gene signatures from the gene set database, pathway-level unsupervised class discovery and classifier development from KRAS mutant CRC revealed three groups, named KM1, KM2 and KM3 (Chapter 4). The biological and prognostic evaluation revealed that KM1 were MYC driven cell-cycle activated, tubular, LGR5+ stem-like tumours with good prognosis, KM2 were stromal/immune rich, of serrated origin and regenerative stem-like biology with diverse pathway activation, including TGF-β activation, EMT and immune responses, and an intermediate prognosis. A novel finding of this classification was KM3, with large repression of pathways such as cell cycle, EMT, KRAS signalling activity, but elevation in neurotransmitter- and enteroendocrine-like biology, highly differentiated tumours, the potential inclusion of epigenetic dysregulation in maintaining stem plasticity, and a clinically worse prognosis (Chapter 5).

In summary, this thesis provides a new pathway-driven classifier for CRC that includes a novel, previously uncharacterised subset of CRC subtype as KM3 with clinically poor outcome, which provides a unique biological phenotype that needs further research to translate into the clinic.

Thesis embargoed until 31 July 2025.
Date of AwardJul 2022
Original languageEnglish
Awarding Institution
  • Queen's University Belfast
SponsorsNorthern Ireland Department for the Economy
SupervisorPhilip Dunne (Supervisor), Daniel Longley (Supervisor) & Mark Lawler (Supervisor)


  • Colorectal cancer
  • computational biology
  • molecular classification
  • cancer
  • bioinformatics
  • personalised medicine
  • precision medicine
  • colon cancer
  • gene expression signature
  • tumour microenvironment
  • tumour hetereogeneity
  • signalling
  • cancer subtyping
  • transcriptomics
  • epigenetics

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