Research output per year
Research output per year
Tim R. de Back, Tan Wu, Pascale J.M. Schafrat, Sanne Ten Hoorn, Miaomiao Tan, Lingli He, Sander R. van Hooff, Jan Koster, Lisanne E. Nijman, Geraldine R. Vink, Inès J. Beumer, Clara C. Elbers, Kristiaan J. Lenos, Dirkje W. Sommeijer, Xin Wang, Louis Vermeulen*
Research output: Contribution to journal › Article › Academic › peer-review
Consensus Molecular Subtype (CMS) classification of colorectal cancer (CRC) tissues is complicated by RNA degradation upon formalin-fixed paraffin-embedded (FFPE) preservation. Here, we present an FFPE-curated CMS classifier. The CMSFFPE classifier was developed using genes with a high transcript integrity in FFPE-derived RNA. We evaluated the classification accuracy in two FFPE-RNA datasets with matched fresh-frozen (FF) RNA data, and an FF-derived RNA set. An FFPE-RNA application cohort of metastatic CRC patients was established, partly treated with anti-EGFR therapy. Key characteristics per CMS were assessed. Cross-referenced with matched benchmark FF CMS calls, the CMSFFPE classifier strongly improved classification accuracy in two FFPE datasets compared with the original CMSClassifier (63.6% versus 40.9% and 83.3% versus 66.7%, respectively). We recovered CMS-specific recurrence-free survival patterns (CMS4 versus CMS2: hazard ratio 1.75, 95% CI 1.24–2.46). Key molecular and clinical associations of the CMSs were confirmed. In particular, we demonstrated the predictive value of CMS2 and CMS3 for anti-EGFR therapy response (CMS2&3: odds ratio 5.48, 95% CI 1.10–27.27). The CMSFFPE classifier is an optimized FFPE-curated research tool for CMS classification of clinical CRC samples.
Original language | English |
---|---|
Article number | e202402730 |
Number of pages | 17 |
Journal | Life Science Alliance |
Volume | 7 |
Issue number | 8 |
DOIs | |
Publication status | Published - Aug 2024 |
Research output: Contribution to journal › Comment/Letter to the editor › Academic › peer-review