TY - JOUR
T1 - A consensus molecular subtypes classification strategy for clinical colorectal cancer tissues
AU - de Back, Tim R.
AU - Wu, Tan
AU - Schafrat, Pascale J.M.
AU - Hoorn, Sanne Ten
AU - Tan, Miaomiao
AU - He, Lingli
AU - van Hooff, Sander R.
AU - Koster, Jan
AU - Nijman, Lisanne E.
AU - Vink, Geraldine R.
AU - Beumer, Inès J.
AU - Elbers, Clara C.
AU - Lenos, Kristiaan J.
AU - Sommeijer, Dirkje W.
AU - Wang, Xin
AU - Vermeulen, Louis
N1 - Publisher Copyright:
© 2024, Life Science Alliance, LLC. All rights reserved.
PY - 2024/8
Y1 - 2024/8
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85194125678
U2 - 10.26508/lsa.202402730
DO - 10.26508/lsa.202402730
M3 - Article
C2 - 38782602
AN - SCOPUS:85194125678
VL - 7
JO - Life Science Alliance
JF - Life Science Alliance
IS - 8
M1 - e202402730
ER -