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. 2012 Jun 19:12:260.
doi: 10.1186/1471-2407-12-260.

Colon cancer molecular subtypes identified by expression profiling and associated to stroma, mucinous type and different clinical behavior

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Colon cancer molecular subtypes identified by expression profiling and associated to stroma, mucinous type and different clinical behavior

Beatriz Perez-Villamil et al. BMC Cancer. .

Abstract

Background: Colon cancer patients with the same stage show diverse clinical behavior due to tumor heterogeneity. We aimed to discover distinct classes of tumors based on microarray expression patterns, to analyze whether the molecular classification correlated with the histopathological stages or other clinical parameters and to study differences in the survival.

Methods: Hierarchical clustering was performed for class discovery in 88 colon tumors (stages I to IV). Pathways analysis and correlations between clinical parameters and our classification were analyzed. Tumor subtypes were validated using an external set of 78 patients. A 167 gene signature associated to the main subtype was generated using the 3-Nearest-Neighbor method. Coincidences with other prognostic predictors were assesed.

Results: Hierarchical clustering identified four robust tumor subtypes with biologically and clinically distinct behavior. Stromal components (p < 0.001), nuclear β-catenin (p = 0.021), mucinous histology (p = 0.001), microsatellite-instability (p = 0.039) and BRAF mutations (p < 0.001) were associated to this classification but it was independent of Dukes stages (p = 0.646). Molecular subtypes were established from stage I. High-stroma-subtype showed increased levels of genes and altered pathways distinctive of tumour-associated-stroma and components of the extracellular matrix in contrast to Low-stroma-subtype. Mucinous-subtype was reflected by the increased expression of trefoil factors and mucins as well as by a higher proportion of MSI and BRAF mutations. Tumor subtypes were validated using an external set of 78 patients. A 167 gene signature associated to the Low-stroma-subtype distinguished low risk patients from high risk patients in the external cohort (Dukes B and C:HR = 8.56(2.53-29.01); Dukes B,C and D:HR = 1.87(1.07-3.25)). Eight different reported survival gene signatures segregated our tumors into two groups the Low-stroma-subtype and the other tumor subtypes.

Conclusions: We have identified novel molecular subtypes in colon cancer with distinct biological and clinical behavior that are established from the initiation of the tumor. Tumor microenvironment is important for the classification and for the malignant power of the tumor. Differential gene sets and biological pathways characterize each tumor subtype reflecting underlying mechanisms of carcinogenesis that may be used for the selection of targeted therapeutic procedures. This classification may contribute to an improvement in the management of the patients with CRC and to a more comprehensive prognosis.

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Figures

Figure 1
Figure 1
Hierarchical clustering of the colon tumor samples and the 1722 selected genes A) Classification of the 89 (sample CT102 is replicated) tumor samples in four main clusters. Yellow shadow: Cluster-1, Low-stroma-subtype; green: Cluster-2, Immunoglobulin-related-subtype; red: Cluster-3, High-stroma-subtype; blue: Cluster-4, Mucinous-subtype; and brown: Cluster-5, unclassified samples. Dukes’ stages are specified below the tree. B) Each column in the heatmap represents one sample and each row represents one gene. The relative levels of gene expression within each sample against the reference pool are illustrated according to the color scale bar (4 fold induction (red); -4 fold inhibition (blue)). The principal sections of the graph that distinguish between clusters are indicated with a color bar on the right. The green bar localizes gene 270 to gene 523, a group of 253 genes with low expression in cluster 1 and high expression in cluster 3; the red bar corresponds to genes 524 to 664 a group of 140 genes, whose expression is lower in cluster 1. Blue bar localizes genes 997 to 1102 a group of 105 genes with a higher expression in cluster 4 compared to 3. Yellow bar localizes genes from 1247 to 1352 a group of 105 genes specific for cluster 2 (see Supplemental data for the list of the 1722 genes).
Figure 2
Figure 2
Immunohistochemistry with β-catenin antibody of tissue microarrays 200X amplification A, C and E; 400X amplification B,D and F. Sample from tumor CT5 corresponding to Low-stroma-subtype (A,B); Sample from tumor CT42 corresponding to High-stroma-subtype (C,D); sample from tumor CT103 corresponding to Mucinous-subtype (E,F). Note nuclear staining of β-catenin of CT5 and CT42 in contrast to membrane β-catenin staining of CT103.
Figure 3
Figure 3
Hierarchical clustering of our 84 tumor samples A) using the 17 genes that coincides in both sets out of the total of 43 genes predictor of Eschrich et al.; B) using 37 genes out of the 50 genes predictor of Garman et al.; C) using 11 of the 23 genes of the predictor of Wang et al.; D) using 17 of the 22 genes of the predictor of Lin YH et al.; E) using 115 of the 128 genes of the predictor of Jorissen RN et al.; F) using 22 of the 34 genes of the predictor of Smith JJ et al.; G) using 6 of the 7 genes of the Oncotype-DX predictor; H) using 17 of the 18 genes of the ColoPrint predictor. Blue line: tumors belonging to cluster-1 (Low-stroma-subtype). Black line: tumors from clusters-2, -3 and −4. Note that almost all samples from the Low-stroma-subtype stay together in one group.
Figure 4
Figure 4
Kaplan-Meier overall survival analysis of Eschrich patients. A: (Dukes B and C); B: (Dukes B, C and D) classified as belonging to the Low-stroma-subtype or belonging to the other tumor subtypes using the 167 genes Low-stroma-subtype predictor. Number of patients classified in each class, hazard ratio and p values are indicated.

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