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

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.<br><br>Methods<br>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.<br><br>Results<br>Results show the previously unclassified CMS NA group was enriched for UC at-risk phenotypes including neoplastic UC, accounting for 25% of samples analysed.