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 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300 previously unpublished samples, we identify cancer cell and tumor archetypes and suggest the tumor microenvironment as a major prognostic determinant that can be influenced by the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.

[1]  Yujin Hoshida,et al.  Nearest Template Prediction: A Single-Sample-Based Flexible Class Prediction with Confidence Assessment , 2010, PloS one.

[2]  A. Sivachenko,et al.  Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples , 2013, Nature Biotechnology.

[3]  Marianne Huebner,et al.  Predictors of recurrence free survival for patients with stage II and III colon cancer , 2014, BMC Cancer.

[4]  T. Hamilton,et al.  Cutting edge: clustered AU-rich elements are the target of IL-10-mediated mRNA destabilization in mouse macrophages. , 1999, Journal of immunology.

[5]  Mark Lawler,et al.  Challenging the Cancer Molecular Stratification Dogma: Intratumoral Heterogeneity Undermines Consensus Molecular Subtypes and Potential Diagnostic Value in Colorectal Cancer , 2016, Clinical Cancer Research.

[6]  E. Birney,et al.  eFORGE: A Tool for Identifying Cell Type-Specific Signal in Epigenomic Data , 2016, Cell reports.

[7]  A. Duval,et al.  Evaluation of tumor microsatellite instability using five quasimonomorphic mononucleotide repeats and pentaplex PCR. , 2002, Gastroenterology.

[8]  R. Simon,et al.  Gene expression profiling reveals a massive, aneuploidy-dependent transcriptional deregulation and distinct differences between lymph node-negative and lymph node-positive colon carcinomas. , 2007, Cancer research.

[9]  Jeffrey S. Morris,et al.  The Consensus Molecular Subtypes of Colorectal Cancer , 2015, Nature Medicine.

[10]  Thomas Lengauer,et al.  ROCR: visualizing classifier performance in R , 2005, Bioinform..

[11]  Andrew E. Teschendorff,et al.  ChAMP: 450k Chip Analysis Methylation Pipeline , 2014, Bioinform..

[12]  Dimitris Anastassiou,et al.  Human cancer cells express Slug-based epithelial-mesenchymal transition gene expression signature obtained in vivo , 2011, BMC Cancer.

[13]  Ivo L. Hofacker,et al.  AREsite: a database for the comprehensive investigation of AU-rich elements , 2010, Nucleic Acids Res..

[14]  Giacomo Puppa,et al.  TNM staging system of colorectal carcinoma: a critical appraisal of challenging issues. , 2010, Archives of pathology & laboratory medicine.

[15]  Z. Modrušan,et al.  Deconvolution of Blood Microarray Data Identifies Cellular Activation Patterns in Systemic Lupus Erythematosus , 2009, PloS one.

[16]  Kathleen R. Cho,et al.  Mutant KRAS promotes hyperplasia and alters differentiation in the colon epithelium but does not expand the presumptive stem cell pool. , 2011, Gastroenterology.

[17]  J. Marshall Risk assessment in Stage II colorectal cancer. , 2010, Oncology.

[18]  Eytan Domany,et al.  Association of survival and disease progression with chromosomal instability: A genomic exploration of colorectal cancer , 2009, Proceedings of the National Academy of Sciences.

[19]  M. Daly,et al.  PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes , 2003, Nature Genetics.

[20]  Cole Trapnell,et al.  TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions , 2013, Genome Biology.

[21]  T. Ørntoft,et al.  A DERL3-associated defect in the degradation of SLC2A1 mediates the Warburg effect , 2014, Nature Communications.

[22]  Emmanouil T. Dermitzakis,et al.  Putative cis-regulatory drivers in colorectal cancer , 2014, Nature.

[23]  Pornpimol Charoentong,et al.  Characterization of the immunophenotypes and antigenomes of colorectal cancers reveals distinct tumor escape mechanisms and novel targets for immunotherapy , 2015, Genome Biology.

[24]  Gary D Bader,et al.  Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation , 2010, PloS one.

[25]  Benno Schwikowski,et al.  Biomolecular Interaction Networks Cytoscape : A Software Environment for Integrated Models of , 2003 .

[26]  Hans Clevers,et al.  Single-cell messenger RNA sequencing reveals rare intestinal cell types , 2015, Nature.

[27]  L. Aaltonen,et al.  Serrated carcinomas form a subclass of colorectal cancer with distinct molecular basis , 2007, Oncogene.

[28]  G. Inghirami,et al.  Stromal contribution to the colorectal cancer transcriptome , 2015, Nature Genetics.

[29]  Adrian L. Harris,et al.  Hypoxia — a key regulatory factor in tumour growth , 2002, Nature Reviews Cancer.

[30]  B. Vogelstein,et al.  A genetic model for colorectal tumorigenesis , 1990, Cell.

[31]  N. Winter,et al.  Mycobacteria-Infected Dendritic Cells Attract Neutrophils That Produce IL-10 and Specifically Shut Down Th17 CD4 T Cells through Their IL-10 Receptor , 2013, The Journal of Immunology.

[32]  Scott R. Presnell,et al.  A transcriptomic reporter assay employing neutrophils to measure immunogenic activity of septic patients’ plasma , 2014, Journal of Translational Medicine.

[33]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[34]  V. Georgoulias,et al.  Prognostic and predictive significance of MSI in stages II/III colon cancer. , 2014, World journal of gastroenterology.

[35]  R. Rigby,et al.  Production of interleukin (IL)‐10 and IL‐12 by murine colonic dendritic cells in response to microbial stimuli , 2005, Clinical and experimental immunology.

[36]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[37]  A. Teschendorff,et al.  Using high-density DNA methylation arrays to profile copy number alterations , 2014, Genome Biology.

[38]  H. Zoghbi,et al.  Requirement of Math1 for Secretory Cell Lineage Commitment in the Mouse Intestine , 2001, Science.

[39]  Alex E. Lash,et al.  Gene Expression Omnibus: NCBI gene expression and hybridization array data repository , 2002, Nucleic Acids Res..

[40]  Renaud Gaujoux,et al.  CellMix: a comprehensive toolbox for gene expression deconvolution , 2013, Bioinform..

[41]  J. Massagué,et al.  TGF-beta directly targets cytotoxic T cell functions during tumor evasion of immune surveillance. , 2005, Cancer cell.

[42]  Jen Jen Yeh,et al.  Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma , 2015, Nature Genetics.

[43]  Renaud Gaujoux,et al.  A flexible R package for nonnegative matrix factorization , 2010, BMC Bioinformatics.

[44]  B. Leggett,et al.  Role of the serrated pathway in colorectal cancer pathogenesis. , 2010, Gastroenterology.

[45]  Jill P. Mesirov,et al.  Subclass Mapping: Identifying Common Subtypes in Independent Disease Data Sets , 2007, PloS one.

[46]  R. Palmqvist,et al.  Beta-catenin expression in relation to genetic instability and prognosis in colorectal cancer. , 2007, Oncology reports.

[47]  Mira Ayadi,et al.  Gene Expression Classification of Colon Cancer into Molecular Subtypes: Characterization, Validation, and Prognostic Value , 2013, PLoS medicine.

[48]  Cole Trapnell,et al.  Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. , 2010, Nature biotechnology.

[49]  Ash A. Alizadeh,et al.  Robust enumeration of cell subsets from tissue expression profiles , 2015, Nature Methods.

[50]  G. Getz,et al.  Inferring tumour purity and stromal and immune cell admixture from expression data , 2013, Nature Communications.

[51]  P. Jung,et al.  Dependency of colorectal cancer on a TGF-β-driven program in stromal cells for metastasis initiation. , 2012, Cancer cell.

[52]  J. Mesirov,et al.  GenePattern 2.0 , 2006, Nature Genetics.