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Journal of Cancer Research and Clinical Oncology

, Volume 139, Issue 2, pp 249–258 | Cite as

A nine-gene signature predicting clinical outcome in cutaneous melanoma

  • G. Brunner
  • M. Reitz
  • A. Heinecke
  • A. Lippold
  • C. Berking
  • L. Suter
  • J. Atzpodien
Original Paper

Abstract

Purpose

Current histopathological staging of cutaneous melanoma is limited in predicting outcome, and complementary molecular markers are not available for prognostic assessment. The purpose of this study was to identify a quantitative gene expression score in primary melanoma and adjacent stroma that can be used in clinical routine to define, at the time of diagnosis, patient risk and need for therapy.

Methods

Expression of 92 candidate genes was quantified by RT-PCR in a training subset of 38 fresh-frozen melanomas. Correlation of gene expression with overall survival (OS) was evaluated using univariate regression analysis. Expression analysis of 11 prognostically significant genes in the complete training cohort of 91 melanomas yielded nine genes predicting outcome. Results were confirmed in a validation cohort of 44 melanomas.

Results

We identified a nine-gene signature associated with OS and distant metastasis-free survival. The signature comprised risk and protective genes and was applicable to melanoma samples across all AJCC stages in the presence of adjacent stroma. A signature-based risk score predicted OS in both the training cohort (multivariate regression analysis: p = 0.0004, hazard ratio 3.83) and the validation cohort, independently of AJCC staging. Consequently, when combining risk score and AJCC staging, patients in the AJCC intermediate-risk stages, IIA/B or IIIA, were re-classified either to low or high risk.

Conclusions

Our gene score defines patient risk and need for therapy in melanoma. The score has the potential to be utilized in clinical routine, since it is quantitative, robust, simple, and independent of AJCC stage and sample purity.

Keywords

Melanoma Prognosis Gene signature Gene expression profiling RT-PCR 

Notes

Acknowledgments

The authors would like to thank Tamara Berger and Maryla Brode for excellent technical assistance, as well as the patients and Surgical Departments of the Skin Cancer Center Hornheide for valuable support of the melanoma biobank of the Department of Cancer Research. This work was supported by grants from the Förderverein Hornheide e.V.

Conflict of interest

We declare that we have no conflict of interest.

Supplementary material

432_2012_1322_MOESM1_ESM.xls (24 kb)
Supplementary material 1 (XLS 24 kb)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • G. Brunner
    • 1
  • M. Reitz
    • 4
  • A. Heinecke
    • 5
  • A. Lippold
    • 2
  • C. Berking
    • 6
  • L. Suter
    • 1
  • J. Atzpodien
    • 3
  1. 1.Department of Cancer ResearchSkin Cancer Center Hornheide-MünsterMünsterGermany
  2. 2.Department of Documentation and StatisticsSkin Cancer Center Hornheide-MünsterMünsterGermany
  3. 3.Department of Medical OncologySkin Cancer Center Hornheide-MünsterMünsterGermany
  4. 4.European Institute for Tumor Immunology and PreventionSassenbergGermany
  5. 5.Department of Medical Informatics and BioinformaticsWestfälische Wilhelms UniversityMünsterGermany
  6. 6.Department of Dermatology and AllergologyLudwig Maximilians UniversityMunichGermany

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