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Molecular profiling related to poor prognosis in thyroid carcinoma. Combining gene expression data and biological information

Oncogene volume 27, pages 1554–1561 (2008)Cite this article

Abstract

Undifferentiated and poorly differentiated thyroid tumors are responsible for more than half of thyroid cancer patient deaths in spite of their low incidence. Conventional treatments do not obtain substantial benefits, and the lack of alternative approaches limits patient survival. Additionally, the absence of prognostic markers for well-differentiated tumors complicates patient-specific treatments and favors the progression of recurrent forms. In order to recognize the molecular basis involved in tumor dedifferentiation and identify potential markers for thyroid cancer prognosis prediction, we analysed the expression profile of 44 thyroid primary tumors with different degrees of dedifferentiation and aggressiveness using cDNA microarrays. Transcriptome comparison of dedifferentiated and well-differentiated thyroid tumors identified 1031 genes with >2-fold difference in absolute values and false discovery rate of <0.15. According to known molecular interaction and reaction networks, the products of these genes were mainly clustered in the MAPkinase signaling pathway, the TGF-β signaling pathway, focal adhesion and cell motility, activation of actin polymerization and cell cycle. An exhaustive search in several databases allowed us to identify various members of the matrix metalloproteinase, melanoma antigen A and collagen gene families within the upregulated gene set. We also identified a prognosis classifier comprising just 30 transcripts with an overall accuracy of 95%. These findings may clarify the molecular mechanisms involved in thyroid tumor dedifferentiation and provide a potential prognosis predictor as well as targets for new therapies.

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Acknowledgements

This work was supported by FIS Project nos. PI052509, PI041313, ISCIII CIBER-BBN and ISCIII CIBER-ER from the Spanish Ministry of Health, and Project BIO 2005-01078 from the Spanish Ministry of Education and Science, and National Institute of Bioinformatics (www.inab.org), a platform of Genoma España. Cristina Montero-Conde is a recipient of a predoctoral fellowship from the Basque Country Government.

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Authors and Affiliations

  1. Hereditary Endocrine Cancer Research Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain

    C Montero-Conde & M Robledo

  2. Research Institute, Santa Creu and Sant Pau Hospital, Barcelona, Spain

    J M Martín-Campos

  3. Biochemistry and Molecular Biology Department, Autonomous University of Barcelona (UAB), Barcelona, Spain

    J M Martín-Campos

  4. Pathology Service, Santa Creu and Sant Pau Hospital, Barcelona, Spain

    E Lerma

  5. Endocrinology Unit, Hospital of Sabadell, Spain

    G Gimenez

  6. Department of Pathology and Molecular Genetics, Arnau de Vilanova Hospital (IRBLLEIDA), Lleida, Spain

    J L Martínez-Guitarte & X Matías-Guiu

  7. Pathology Service, Hospital of Sabadell, Spain

    N Combalía

  8. Bioinformatics Department, Centro de Investigación Príncipe Felipe (CIPF), Valencia, Spain

    D Montaner & J Dopazo

  9. ISCIII Center for Biomedical Research on Rare Diseases (CIBERER), Spain

    J Dopazo & M Robledo

  10. Functional Genomics Node INB, Spain

    J Dopazo

  11. Department of Endocrinology and Nutrition, Santa Creu and Sant Pau Hospital, Barcelona, Spain

    A de Leiva & D Mauricio

  12. ISCIII CIBER-BBN, Spain

    A de Leiva

  13. Department of Endocrinology, Arnau de Vilanova Hospital (IRBLLEIDA), Lleida, Spain

    D Mauricio

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  1. C Montero-Conde
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Corresponding authors

Correspondence to M Robledo or D Mauricio.

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Supplementary Information accompanies the paper on the Oncogene website (http://www.nature.com/onc).

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Montero-Conde, C., Martín-Campos, J., Lerma, E. et al. Molecular profiling related to poor prognosis in thyroid carcinoma. Combining gene expression data and biological information. Oncogene 27, 1554–1561 (2008). https://doi.org/10.1038/sj.onc.1210792

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