A bioinformatics approach to identifying ulcerative colitis patients at-risk of developing colorectal cancer

Abstract

Introduction
Patients with ulcerative colitis (UC) have an increased risk of developing colorectal cancer (UC-CRC), attributed to chronic inflammation and treatment refractory disease. Approximately 10% of UC patients will develop UC-CRC, yet there are no biomarkers of disease progression nor a distinct understanding of disease pathology leading to cancer. Furthermore, UC-CRC development contrasts sporadic colorectal cancer (sCRC) and poses the question if sCRC and UC-CRC are distinct entities.

Methods
Using meta-analysis, we combined molecular mapping algorithm GECA, with publicly available transcriptomic datasets, to map UC phenotypes against sCRC with predefined consensus molecular subgroup of colorectal cancer (CMS) classifications, to determine UC molecular similarity to sCRC. Using multiomics, we sought to identify a molecular phenotype of UC patients at-risk of UC-CRC progression. Finally, we compared UC progressor and non-progressors to UC-CRC to derive a gene-list representing changes associated with neoplastic progression.

Results
Results show the previously unclassified CMS NA group was enriched for UC at-risk phenotypes including neoplastic UC, accounting for 25% of samples analysed. Multiomics and meta-analysis determined the CMS NA group was a unique molecular subgroup with distinctive features, reflecting published characteristics of UC-CRC. Our gene list identified loss of interferon gamma (IFNγ) signalling as UC progressed to UC-CRC indicating loss of immune surveillance. We constructed a ‘timeline’ to progression of immune infiltrates indicating loss of CD8 T-cells and increased T-regulatory cells as UC progresses to UC-CRC, reflected in the CMS NA group.

Discussion
We identified UC-CRC as a distinct disease entity from sCRC. UC-CRC and UC at-risk patients are enriched in the CMS NA group, a previously undefined CRC subgroup which we have characterised molecularly for the first time. We identified loss of IFNγ signalling as UC progresses to UC-CRC represented by our gene-list, which has potential as a marker of cancer occurrence in UC patients.

Thesis is embargoed until 31 December 2025.

Date of Award	Dec 2023
Original language	English
Awarding Institution	Queen's University Belfast
Supervisor	Richard Kennedy (Supervisor) & Jaine Blayney (Supervisor)