A nine-gene signature predicting clinical outcome in cutaneous melanoma
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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.
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.
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.
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.
KeywordsMelanoma Prognosis Gene signature Gene expression profiling RT-PCR
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.
- Malesh K, Parmar B, Machin D (2004) Survival analysis, a practical approach. Wiley, Chichester, p 154Google Scholar
- Zafrakas M, Petschke B, Donner A, Fritzsche F, Kristiansen G, Knüchel R, Dahl E (2006) Expression analysis of mammaglobin A (SCGB2A2) and lipophilin B (SCGB1D2) in more than 300 human tumors and matching normal tissues reveals their co-expression in gynecologic malignancies. BMC Cancer 6:88PubMedCrossRefGoogle Scholar