Unsupervised Analysis of Array Comparative Genomic Hybridization Data from Early-Onset Colorectal Cancer Reveals Equivalence with Molecular Classification and Phenotypes

Publication date: January 2017
Source:Neoplasia, Volume 19, Issue 1
Author(s): María Arriba, Juan L. García, Daniel Rueda, Jessica Pérez, Lorena Brandariz, Oana A. Nutu, Laura Alonso, Yolanda Rodríguez, Miguel Urioste, Rogelio González-Sarmiento, José Perea
AIM: To investigate whether chromosomal instability (CIN) is associated with tumor phenotypes and/or with global genomic status based on MSI (microsatellite instability) and CIMP (CpG island methylator phenotype) in early-onset colorectal cancer (EOCRC). METHODS: Taking as a starting point our previous work in which tumors from 60 EOCRC cases (≤45 years at the time of diagnosis) were analyzed by array comparative genomic hybridization (aCGH), in the present study we performed an unsupervised hierarchical clustering analysis of those aCGH data in order to unveil possible associations between the CIN profile and the clinical features of the tumors. In addition, we evaluated the MSI and the CIMP statuses of the samples with the aim of investigating a possible relationship between copy number alterations (CNAs) and the MSI/CIMP condition in EOCRC. RESULTS: Based on the similarity of the CNAs detected, the unsupervised analysis stratified samples into two main clusters (A, B) and four secondary clusters (A1, A2, B3, B4). The different subgroups showed a certain correspondence with the molecular classification of colorectal cancer (CRC), which enabled us to outline an algorithm to categorize tumors according to their CIMP status. Interestingly, each subcluster showed some distinctive clinicopathological features. But more interestingly, the CIN of each subcluster mainly affected particular chromosomes, allowing us to define chromosomal regions more specifically affected depending on the CIMP/MSI status of the samples. CONCLUSIONS: Our findings may provide a basis for a new form of classifying EOCRC according to the genomic status of the tumors.



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