Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value

PLoS Med. 2013;10(5):e1001453. doi: 10.1371/journal.pmed.1001453. Epub 2013 May 21.

Abstract

Background: Colon cancer (CC) pathological staging fails to accurately predict recurrence, and to date, no gene expression signature has proven reliable for prognosis stratification in clinical practice, perhaps because CC is a heterogeneous disease. The aim of this study was to establish a comprehensive molecular classification of CC based on mRNA expression profile analyses.

Methods and findings: Fresh-frozen primary tumor samples from a large multicenter cohort of 750 patients with stage I to IV CC who underwent surgery between 1987 and 2007 in seven centers were characterized for common DNA alterations, including BRAF, KRAS, and TP53 mutations, CpG island methylator phenotype, mismatch repair status, and chromosomal instability status, and were screened with whole genome and transcriptome arrays. 566 samples fulfilled RNA quality requirements. Unsupervised consensus hierarchical clustering applied to gene expression data from a discovery subset of 443 CC samples identified six molecular subtypes. These subtypes were associated with distinct clinicopathological characteristics, molecular alterations, specific enrichments of supervised gene expression signatures (stem cell phenotype-like, normal-like, serrated CC phenotype-like), and deregulated signaling pathways. Based on their main biological characteristics, we distinguished a deficient mismatch repair subtype, a KRAS mutant subtype, a cancer stem cell subtype, and three chromosomal instability subtypes, including one associated with down-regulated immune pathways, one with up-regulation of the Wnt pathway, and one displaying a normal-like gene expression profile. The classification was validated in the remaining 123 samples plus an independent set of 1,058 CC samples, including eight public datasets. Furthermore, prognosis was analyzed in the subset of stage II-III CC samples. The subtypes C4 and C6, but not the subtypes C1, C2, C3, and C5, were independently associated with shorter relapse-free survival, even after adjusting for age, sex, stage, and the emerging prognostic classifier Oncotype DX Colon Cancer Assay recurrence score (hazard ratio 1.5, 95% CI 1.1-2.1, p = 0.0097). However, a limitation of this study is that information on tumor grade and number of nodes examined was not available.

Conclusions: We describe the first, to our knowledge, robust transcriptome-based classification of CC that improves the current disease stratification based on clinicopathological variables and common DNA markers. The biological relevance of these subtypes is illustrated by significant differences in prognosis. This analysis provides possibilities for improving prognostic models and therapeutic strategies. In conclusion, we report a new classification of CC into six molecular subtypes that arise through distinct biological pathways.

Publication types

  • Multicenter Study
  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Biomarkers, Tumor / genetics*
  • Chi-Square Distribution
  • Cluster Analysis
  • Colonic Neoplasms / classification
  • Colonic Neoplasms / genetics*
  • Colonic Neoplasms / mortality
  • Colonic Neoplasms / pathology
  • Colonic Neoplasms / surgery
  • Female
  • France
  • Gene Expression Profiling* / methods
  • Gene Expression Regulation, Neoplastic
  • Genetic Predisposition to Disease
  • Genetic Testing* / methods
  • Humans
  • Kaplan-Meier Estimate
  • Logistic Models
  • Lymphatic Metastasis
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Neoplasm Staging
  • Phenotype
  • Precision Medicine
  • Predictive Value of Tests
  • Prognosis
  • Proportional Hazards Models
  • RNA, Messenger / analysis
  • Reproducibility of Results
  • Risk Assessment
  • Risk Factors
  • Time Factors
  • Young Adult

Substances

  • Biomarkers, Tumor
  • RNA, Messenger

Grants and funding

The Ligue Nationale Contre le Cancer, a non-governmental charity organization, through the Cartes d'Identité Tumeurs program, funded experiments from sample extraction to transcriptome and genome arrays, mutational characterization, and statistical analyses. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.