Sylviane Olschwang

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.

This collaborative study suggests that not only is the presence of a codon 12 glycine to valine mutation important for cancer progression but also that it predispose to more aggressive biological behaviour in patients with advanced colorectal cancer.

BACKGROUND: Although an increased cancer risk in Peutz-Jeghers syndrome is established, data on the spectrum of tumors associated with the disease and the influence of germ-line STK11/LKB1 (serine/threonine kinase) mutation status are limited. EXPERIMENTAL DESIGN: We analyzed the incidence of cancer in 419 individuals with Peutz-Jeghers syndrome, and 297 had documented STK11/LKB1 mutations. RESULTS: Ninety-six cancers were found among individuals with Peutz-Jeghers syndrome. The risk for developing cancer at ages 20, 30, 40, 50, 60, and 70 years was 2%, 5%, 17%, 31%, 60%, and 85%, respectively. The most common cancers represented in this analysis were gastrointestinal in origin, gastroesophageal, small bowel, colorectal, and pancreatic, and the risk for these cancers at ages 30, 40, 50, and 60 years was 1%, 9%, 15%, and 33%, respectively. In women with Peutz-Jeghers syndrome, the risk of breast cancer was substantially increased, being 8% and 31% at ages 40 and 60 years, respectively. Kaplan-Meier analysis showed that cancer risks were similar in Peutz-Jeghers syndrome patients with identified STK11/LKB1 mutations and those with no detectable mutation (log-rank test of difference chi2 = 0.62; 1 df; P = 0.43). Furthermore, the type or site of STK11/LKB1 mutation did not significantly influence cancer risk. CONCLUSIONS: The results from our study provide quantitative information on the spectrum of cancers and risks of specific cancer types associated with Peutz-Jeghers syndrome.