Image-Based Consensus Molecular Subtyping Refines Prognostication in Stage II/III Colorectal Cancer: A Retrospective Analysis of the SCOT Trial
Year: 2026
Type: article
Abstract: Purpose Risk stratification in localized colorectal cancer (CRC) remains inadequate. Transcriptome-based classifiers such as consensus molecular subtyping (CMS) improve this, but are challenging to implement. We determined the performance of a novel image-based method for CRC CMS subtyping (imCMS) using routine pathology images from the SCOT trial and investigated association of imCMS subtypes with clinicopathologic and tumor molecular and immune factors, treatment benefit, and survival. Methods We applied a novel imCMS classifier to stage II/III CRCs from the SCOT trial (ISRCTN59757862) which examined 3 versus 6 months of adjuvant oxaliplatin-based chemotherapy following curative-intent surgery. We determined correlates of imCMS subgroups and investigated imCMS prognostic and predictive value for CRC recurrence-free interval, overall survival (OS), and survival after CRC recurrence (SAR) by univariable and multivariable Cox regression. Results A total of 2,816 cases were informative for imCMS classification, of which 664 (24%) were imCMS1 (immune), 987 (35%) imCMS2 (canonical), 433 (15%) imCMS3 (metabolic), 653 (23%) imCMS4 (mesenchymal), and 79 (3%) of mixed subtype. Analysis confirmed expected associations of imCMS1 with deficient DNA mismatch repair (dMMR) and imCMS3 with KRAS mutation and revealed substantially lower intraepithelial CD8 + and intrastromal FoxP3 + T-cell infiltrate (CD8 IE -FoxP3 IS ) in imCMS4 tumors. imCMS classification was strongly prognostic independent of clinicopathologic factors, dMMR, and CD8 IE -FoxP3 IS in multivariable analysis but did not predict differential benefit from chemotherapy duration or regimen. The combination of imCMS with CD8 IE -FoxP3 IS groups defined CRC subgroups with substantially different recurrence risk. Analysis of OS and SAR revealed notable discordance in imCMS3 and imCMS4 prognostic value before and after relapse. Conclusion imCMS classification improves CRC prognostication beyond existing tumor factors and is potentially deliverable in clinical practice. imCMS prediction of therapeutic benefit requires further study.
Source: Journal of Clinical Oncology
DOI: 10.1200/jco-25-02761
Authors: Maxime W. Lafarge, Andrea Harkin, Tim Iveson, Mark Saunders, David J. Adams, Karin Oien, Noori Maka, Kathryn Gilroy, Jennifer Hay, Bernard Hild, Ingrid Berg, Joanne Edwards, Owen Sansom, Caroline Kelly, Ian Tomlinson, Rachel Kerr, Timothy S. Maughan, Enric Domingo, David Church, Viktor H. Koelzer, David Church, Enric Domingo, Joanne Edwards, Bengt Glimelius, Ismail Gogenur, Andrea Harkin, Jen Hay, Timothy Iveson, Emma Jaeger, Caroline Kelly, Rachel Kerr, Noori Maka, Hannah Morgan, Karin Oien, Clare Orange, Claire Palles, Campbell Roxburgh, Owen Sansom, Mark Saunders, Ian Tomlinson, Richard Adams, Simon Bach, Andrew Beggs, Andrew Blake, Louise Brown, Francesca Buffa, Peter Campbell, Jean-Baptiste Cazier, Aikaterini Chatzipli, Enric Domingo, Philip Dunne, Claire Hardy, Paul Harkin, Geoffrey Higgins, Jim Hill, Christopher Holmes, Dennis Horgan, Richard Kaplan, Richard Kennedy, Viktor Koelzer, Mark Lawler, Simon Leedham, Timothy Maughan, Ultan McDermott, Gillies McKenna, Gary Middleton, Dion Morton, Graeme Murray, Philip Quirke, Keara Redmond, Susan Richman, James Robineau, Manuel Salto-Tellez, Leslie Samuel, David Sebag-Montefiore, Matthew Seymour, Richard Sullivan, Ian Tomlinson, Steven Walker, Nicholas West, Celina Whalley, Richard Wilson, Chieh-Hsi Wu, Michael Youdell, Enric Domingo, Viktor H. Koelzer, Maxime Lafarge, Tim Maughan, Jens Rittscher, Korsuk Sirinukunwattana
Institutions: University of Basel, University Hospital of Basel, University of Glasgow, University of Southampton, The Christie NHS Foundation Trust, Wellcome Sanger Institute, Queen Elizabeth University Hospital, Cancer Research UK Scotland Institute, University of Zurich, Cancer Research UK, University of Oxford, Oxford University Hospitals NHS Trust, University Hospital Zurich, University of Leeds, Varian Medical Systems (United States), Medical Research Council
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Funders: Amgen, Bristol-Myers Squibb, AstraZeneca, GlaxoSmithKline, Varian Medical Systems, Universität Basel, Ludwig Institute for Cancer Research, Merck KGaA, NHS Greater Glasgow and Clyde, Moderna, Cancer Research UK, National Institute for Health and Care Research, University of Southampton, University of Oxford, University of Glasgow, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Cancerfonden, Leids Universitair Medisch Centrum, Oxford University Hospitals NHS Foundation Trust, Universität Zürich, Uppsala Universitet, Universitätsspital Zürich, Sjællands Universitetshospital, Medical Research Council, NIHR Oxford Biomedical Research Centre
OpenAlex ID: W7225402171