Tim R de Back, Tan Wu, Pascale Jm 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
{"title":"临床结直肠癌组织分子亚型分类共识策略。","authors":"Tim R de Back, Tan Wu, Pascale Jm 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","doi":"10.26508/lsa.202402730","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":18081,"journal":{"name":"Life Science Alliance","volume":"7 8","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11116811/pdf/","citationCount":"0","resultStr":"{\"title\":\"A consensus molecular subtypes classification strategy for clinical colorectal cancer tissues.\",\"authors\":\"Tim R de Back, Tan Wu, Pascale Jm 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\",\"doi\":\"10.26508/lsa.202402730\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":18081,\"journal\":{\"name\":\"Life Science Alliance\",\"volume\":\"7 8\",\"pages\":\"\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2024-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11116811/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Life Science Alliance\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.26508/lsa.202402730\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/8/1 0:00:00\",\"PubModel\":\"Print\",\"JCR\":\"Q1\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Life Science Alliance","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.26508/lsa.202402730","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/8/1 0:00:00","PubModel":"Print","JCR":"Q1","JCRName":"BIOLOGY","Score":null,"Total":0}
A consensus molecular subtypes classification strategy for clinical colorectal cancer tissues.
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.
期刊介绍:
Life Science Alliance is a global, open-access, editorially independent, and peer-reviewed journal launched by an alliance of EMBO Press, Rockefeller University Press, and Cold Spring Harbor Laboratory Press. Life Science Alliance is committed to rapid, fair, and transparent publication of valuable research from across all areas in the life sciences.