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.
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.
Authors: Adam I Riker; Steven A Enkemann; Oystein Fodstad; Suhu Liu; Suping Ren; Christopher Morris; Yaguang Xi; Paul Howell; Brandon Metge; Rajeev S Samant; Lalita A Shevde; Wenbin Li; Steven Eschrich; Adil Daud; Jingfang Ju; Jaime Matta Journal: BMC Med Genomics Date: 2008-04-28 Impact factor: 3.063
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Authors: M Bittner; P Meltzer; Y Chen; Y Jiang; E Seftor; M Hendrix; M Radmacher; R Simon; Z Yakhini; A Ben-Dor; N Sampas; E Dougherty; E Wang; F Marincola; C Gooden; J Lueders; A Glatfelter; P Pollock; J Carpten; E Gillanders; D Leja; K Dietrich; C Beaudry; M Berens; D Alberts; V Sondak Journal: Nature Date: 2000-08-03 Impact factor: 49.962
Authors: Suping Ren; Suhu Liu; Paul Howell; Yaguang Xi; Steven A Enkemann; Jingfang Ju; Adam I Riker Journal: Cancer Control Date: 2008-07 Impact factor: 3.302
Authors: Douglas Grossman; Nwanneka Okwundu; Edmund K Bartlett; Michael A Marchetti; Megan Othus; Daniel G Coit; Rebecca I Hartman; Sancy A Leachman; Elizabeth G Berry; Larissa Korde; Sandra J Lee; Menashe Bar-Eli; Marianne Berwick; Tawnya Bowles; Elizabeth I Buchbinder; Elizabeth M Burton; Emily Y Chu; Clara Curiel-Lewandrowski; Julia A Curtis; Adil Daud; Dekker C Deacon; Laura K Ferris; Jeffrey E Gershenwald; Kenneth F Grossmann; Siwen Hu-Lieskovan; John Hyngstrom; Joanne M Jeter; Robert L Judson-Torres; Kari L Kendra; Caroline C Kim; John M Kirkwood; David H Lawson; Philip D Leming; Georgina V Long; Ashfaq A Marghoob; Janice M Mehnert; Michael E Ming; Kelly C Nelson; David Polsky; Richard A Scolyer; Eric A Smith; Vernon K Sondak; Mitchell S Stark; Jennifer A Stein; John A Thompson; John F Thompson; Suraj S Venna; Maria L Wei; Susan M Swetter Journal: JAMA Dermatol Date: 2020-09-01 Impact factor: 10.282
Authors: Helena Cirenajwis; Henrik Ekedahl; Martin Lauss; Katja Harbst; Ana Carneiro; Jens Enoksson; Frida Rosengren; Linda Werner-Hartman; Therese Törngren; Anders Kvist; Erik Fredlund; Pär-Ola Bendahl; Karin Jirström; Lotta Lundgren; Jillian Howlin; Åke Borg; Sofia K Gruvberger-Saal; Lao H Saal; Kari Nielsen; Markus Ringnér; Hensin Tsao; Håkan Olsson; Christian Ingvar; Johan Staaf; Göran Jönsson Journal: Oncotarget Date: 2015-05-20
Authors: Erling Mellerup; Ole A Andreassen; Bente Bennike; Henrik Dam; Srdjan Djurovic; Thomas Hansen; Martin Balslev Jorgensen; Lars Vedel Kessing; Pernille Koefoed; Ingrid Melle; Ole Mors; Thomas Werge; Gert Lykke Moeller Journal: PLoS One Date: 2015-11-20 Impact factor: 3.240