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Tumor immune infiltration estimated from gene expression profiles predicts colorectal cancer relapse.
Kamal, Yasmin; Dwan, Dennis; Hoehn, Hannah J; Sanz-Pamplona, Rebeca; Alonso, M Henar; Moreno, Victor; Cheng, Chao; Schell, Michael J; Kim, Youngchul; Felder, Seth I; Rennert, Hedy S; Melas, Marilena; Lazaris, Charalampos; Bonner, Joseph D; Siegel, Erin M; Shibata, David; Rennert, Gad; Gruber, Stephen B; Frost, H Robert; Amos, Christopher I; Schmit, Stephanie L.
Afiliação
  • Kamal Y; Department of Biomedical Data Sciences, Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
  • Dwan D; Department of Biomedical Data Sciences, Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
  • Hoehn HJ; Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
  • Sanz-Pamplona R; Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat, Barcelona, Spain.
  • Alonso MH; Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain.
  • Moreno V; Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat, Barcelona, Spain.
  • Cheng C; Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain.
  • Schell MJ; Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona, Spain.
  • Kim Y; Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat, Barcelona, Spain.
  • Felder SI; Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain.
  • Rennert HS; Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona, Spain.
  • Melas M; Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA.
  • Lazaris C; Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
  • Bonner JD; Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA.
  • Siegel EM; Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Columbus, OH, USA.
  • Shibata D; Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Columbus, OH, USA.
  • Rennert G; Department of Gastrointestinal Oncology, H. Lee Moffitt Cancer Center and Research Institute.
  • Gruber SB; Department of Community Medicine & Epidemiology, Lady Davis Carmel Medical Center, Ruth & Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology.
  • Frost HR; Steve and Cindy Rasmussen Institute for Genomic Medicine, Lady Davis Carmel Medical Center and Technion Faculty of Medicine, Clalit National Cancer Control Center, Haifa, Israel.
  • Amos CI; Department of Medical Oncology and Therapeutics Research, Center for Precision Medicine, City of Hope National Medical Center, Duarte, CA, USA.
  • Schmit SL; Nationwide Children's Hospital, Columbus, OH, USA.
Oncoimmunology ; 10(1): 1862529, 2021 03 09.
Article em En | MEDLINE | ID: mdl-33763292
ABSTRACT
A substantial fraction of patients with stage I-III colorectal adenocarcinoma (CRC) experience disease relapse after surgery with curative intent. However, biomarkers for predicting the likelihood of CRC relapse have not been fully explored. Therefore, we assessed the association between tumor infiltration by a broad array of innate and adaptive immune cell types and CRC relapse risk. We implemented a discovery-validation design including a discovery dataset from Moffitt Cancer Center (MCC; Tampa, FL) and three independent validation datasets (1) GSE41258 (2) the Molecular Epidemiology of Colorectal Cancer (MECC) study, and (3) GSE39582. Infiltration by 22 immune cell types was inferred from tumor gene expression data, and the association between immune infiltration by each cell type and relapse-free survival was assessed using Cox proportional hazards regression. Within each of the four independent cohorts, CD4+ memory activated T cell (HR 0.93, 95% CI 0.90-0.96; FDR = 0.0001) infiltration was associated with longer time to disease relapse, independent of stage, microsatellite instability, and adjuvant therapy. Based on our meta-analysis across the four datasets, 10 innate and adaptive immune cell types associated with disease relapse of which 2 were internally validated using multiplex immunofluorescence. Moreover, immune cell type infiltration was a better predictors of disease relapse than Consensus Molecular Subtype (CMS) and other expression-based biomarkers (Immune-AICMCC238.1-238.9; CMS-AICMCC 241.0). These data suggest that transcriptome-derived immune profiles are prognostic indicators of CRC relapse and quantification of both innate and adaptive immune cell types may serve as candidate biomarkers for predicting prognosis and guiding frequency and modality of disease surveillance.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Colorretais / Transcriptoma Tipo de estudo: Prognostic_studies / Risk_factors_studies / Systematic_reviews Limite: Humans Idioma: En Revista: Oncoimmunology Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Colorretais / Transcriptoma Tipo de estudo: Prognostic_studies / Risk_factors_studies / Systematic_reviews Limite: Humans Idioma: En Revista: Oncoimmunology Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos