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The landscape of genomic copy number alterations in colorectal cancer and their consequences on gene expression levels and disease outcome

Research output: Contribution to journalArticle


Thomas Ried, Gerrit A. Meijer, David J. Harrison, Godfrey Grech, Sebastià Franch-Expósito, Romina Briffa, Beatriz Carvalho, Jordi Camps

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Aneuploidy, the unbalanced state of the chromosome content, represents a hallmark of most solid tumors, including colorectal cancer. Such aneuploidies result in tumor specific genomic imbalances, which emerge in premalignant precursor lesions. Moreover, increasing levels of chromosomal instability have been observed in adenocarcinomas and are maintained in distant metastases. A number of studies have systematically integrated copy number alterations with gene expression changes in primary carcinomas, cell lines, and experimental models of aneuploidy. In fact, chromosomal aneuploidies target a number of genes conferring a selective advantage for the metabolism of the cancer cell. Copy number alterations not only have a positive correlation with expression changes of the majority of genes on the altered genomic segment, but also have effects on the transcriptional levels of genes genome-wide. Finally, copy number alterations have been associated with disease outcome; nevertheless, the translational applicability in clinical practice requires further studies. Here, we (i) review the spectrum of genetic alterations that lead to colorectal cancer, (ii) describe the most frequent copy number alterations at different stages of colorectal carcinogenesis, (iii) exemplify their positive correlation with gene expression levels, and (iv) discuss copy number alterations that are potentially involved in disease outcome of individual patients.


Original languageEnglish
Pages (from-to)48-61
Number of pages14
JournalMolecular Aspects of Medicine
Early online date6 Aug 2019
Publication statusPublished - Oct 2019

    Research areas

  • Colorectal cancer, Colorectal adenomas, Copy number alterations, Aneuploidy, Gene expression, Biomarkers

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