Molecular-subtype-specific biomarkers improve prediction of prognosis in colorectal cancer

Colorectal cancer (CRC) is characterized by major inter-tumor diversity that complicates the prediction of disease and treatment outcomes. Recent efforts help resolve this by sub-classification of CRC into natural molecular subtypes; however, this strategy is not yet able to provide clinicians with...

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Detalles Bibliográficos
Autores: Bertram Bramsen, Jesper, Heilskov Rasmussen, Mads, Ongen, Halit, Block Mattesen, Trine, Worm Ørntoft, Mai-Britt, Salling Árnadóttir, Sigrid, Sandoval, Juan, Laguna, Teresa, Vang, Søren, Øster, Bodil, Lamy, Philippe, Rørbæk Madsen, Mogens, Laurberg, Søren, Esteller, Manel, 1968-, Theophilos Dermitzakis, Emmanouil, Falck Ørntoft, Torben, Lindbjerg Andersen, Claus
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2017
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/122137
Acceso en línea:https://hdl.handle.net/2445/122137
Access Level:acceso abierto
Palabra clave:Marcadors bioquímics
Pronòstic mèdic
Càncer colorectal
Cèl·lules canceroses
Biochemical markers
Prognosis
Colorectal cancer
Cancer cells
Descripción
Sumario:Colorectal cancer (CRC) is characterized by major inter-tumor diversity that complicates the prediction of disease and treatment outcomes. Recent efforts help resolve this by sub-classification of CRC into natural molecular subtypes; however, this strategy is not yet able to provide clinicians with improved tools for decision making. We here present an extended framework for CRC stratification that specifically aims to improve patient prognostication. Using transcriptional profiles from 1,100 CRCs, including >300 previously unpublished samples, we identify cancer cell and tumor archetypes and suggest the tumor microenvironment as a major prognostic determinant that can be influenced by the microbiome. Notably, our subtyping strategy allowed identification of archetype-specific prognostic biomarkers that provided information beyond and independent of UICC-TNM staging, MSI status, and consensus molecular subtyping. The results illustrate that our extended subtyping framework, combining subtyping and subtype-specific biomarkers, could contribute to improved patient prognostication and may form a strong basis for future studies

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