Literature DB >> 25564571

Development of a prognostic genetic signature to predict the metastatic risk associated with cutaneous melanoma.

Pedram Gerami1, Robert W Cook2, Jeff Wilkinson3, Maria C Russell4, Navneet Dhillon5, Rodabe N Amaria6, Rene Gonzalez6, Stephen Lyle7, Clare E Johnson2, Kristen M Oelschlager2, Gilchrist L Jackson8, Anthony J Greisinger9, Derek Maetzold2, Keith A Delman4, David H Lawson4, John F Stone3.   

Abstract

PURPOSE: The development of a genetic signature for the identification of high-risk cutaneous melanoma tumors would provide a valuable prognostic tool with value for stage I and II patients who represent a remarkably heterogeneous group with a 3% to 55% chance of disease progression and death 5 years from diagnosis. EXPERIMENTAL
DESIGN: A prognostic 28-gene signature was identified by analysis of microarray expression data. Primary cutaneous melanoma tumor tissue was evaluated by RT-PCR for expression of the signature, and radial basis machine (RBM) modeling was performed to predict risk of metastasis.
RESULTS: RBM analysis of cutaneous melanoma tumor gene expression reports low risk (class 1) or high risk (class 2) of metastasis. Metastatic risk was predicted with high accuracy in development (ROC = 0.93) and validation (ROC = 0.91) cohorts of primary cutaneous melanoma tumor tissue. Kaplan-Meier analysis indicated that the 5-year disease-free survival (DFS) rates in the development set were 100% and 38% for predicted classes 1 and 2 cases, respectively (P < 0.0001). DFS rates for the validation set were 97% and 31% for predicted classes 1 and 2 cases, respectively (P < 0.0001). Gene expression profile (GEP), American Joint Committee on Cancer stage, Breslow thickness, ulceration, and age were independent predictors of metastatic risk according to Cox regression analysis.
CONCLUSIONS: The GEP signature accurately predicts metastasis risk in a multicenter cohort of primary cutaneous melanoma tumors. Preliminary Cox regression analysis indicates that the signature is an independent predictor of metastasis risk in the cohort presented. ©2015 American Association for Cancer Research.

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Year:  2015        PMID: 25564571     DOI: 10.1158/1078-0432.CCR-13-3316

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  73 in total

1.  Association between traditional clinical high-risk features and gene expression profile classification in uveal melanoma.

Authors:  Brandon T Nguyen; Ryan S Kim; Maria E Bretana; Eric Kegley; Amy C Schefler
Journal:  Graefes Arch Clin Exp Ophthalmol       Date:  2017-11-28       Impact factor: 3.117

2.  Factors Affecting Sentinel Node Metastasis in Thin (T1) Cutaneous Melanomas: Development and External Validation of a Predictive Nomogram.

Authors:  Andrea Maurichi; Rosalba Miceli; Hanna Eriksson; Julia Newton-Bishop; Jérémie Nsengimana; May Chan; Andrew J Hayes; Kara Heelan; David Adams; Roberto Patuzzo; Francesco Barretta; Gianfranco Gallino; Catherine Harwood; Daniele Bergamaschi; Dorothy Bennett; Konstantinos Lasithiotakis; Paola Ghiorzo; Bruna Dalmasso; Ausilia Manganoni; Francesca Consoli; Ilaria Mattavelli; Consuelo Barbieri; Andrea Leva; Umberto Cortinovis; Vittoria Espeli; Cristina Mangas; Pietro Quaglino; Simone Ribero; Paolo Broganelli; Giovanni Pellacani; Caterina Longo; Corrado Del Forno; Lorenzo Borgognoni; Serena Sestini; Nicola Pimpinelli; Sara Fortunato; Alessandra Chiarugi; Paolo Nardini; Elena Morittu; Antonio Florita; Mara Cossa; Barbara Valeri; Massimo Milione; Giancarlo Pruneri; Odysseas Zoras; Andrea Anichini; Roberta Mortarini; Mario Santinami
Journal:  J Clin Oncol       Date:  2020-03-13       Impact factor: 44.544

3.  ASO Author Reflections: Gene Expression Profiling for Melanoma: Is it Ready for Prime Time?

Authors:  Aaron Kangas-Dick; Adam C Berger; Vadim Koshenkov
Journal:  Ann Surg Oncol       Date:  2021-01-21       Impact factor: 5.344

4.  Prognostic molecular testing in melanoma: ready for prime time?

Authors:  Jennifer Keller; Laurence P Diggs; Eddy C Hsueh
Journal:  Melanoma Manag       Date:  2017-07-31

Review 5.  Predicting the outcome of melanoma: can we tell the future of a patient's melanoma?

Authors:  Oriol Yélamos; Pedram Gerami
Journal:  Melanoma Manag       Date:  2015-08-10

Review 6.  The digital age of melanoma management: detection and diagnostics.

Authors:  Alexander L Fogel; Kavita Sarin
Journal:  Melanoma Manag       Date:  2015-11-26

7.  A unique gene expression signature is significantly differentially expressed in tumor-positive or tumor-negative sentinel lymph nodes in patients with melanoma.

Authors:  Ahmad A Tarhini; Theofanis Floros; Hui-Min Lin; Yan Lin; Zahra Rahman; Madeeha Ashraf; Priyanka Vallabhaneni; Cindy Sander; Uma N M Rao; Monica Panelli; William A LaFramboise; John M Kirkwood
Journal:  Melanoma Res       Date:  2017-10       Impact factor: 3.599

Review 8.  Review of diagnostic, prognostic, and predictive biomarkers in melanoma.

Authors:  Jacob S Ankeny; Brian Labadie; Jason Luke; Eddy Hsueh; Jane Messina; Jonathan S Zager
Journal:  Clin Exp Metastasis       Date:  2018-05-02       Impact factor: 5.150

Review 9.  Through the looking glass and what you find there: making sense of comparative genomic hybridization and fluorescence in situ hybridization for melanoma diagnosis.

Authors:  Jayson Miedema; Aleodor A Andea
Journal:  Mod Pathol       Date:  2020-02-17       Impact factor: 7.842

10.  Performance of Gene Expression Profile Tests for Prognosis in Patients With Localized Cutaneous Melanoma: A Systematic Review and Meta-analysis.

Authors:  Michael A Marchetti; Daniel G Coit; Stephen W Dusza; Ashley Yu; LaToya McLean; Yinin Hu; Japbani K Nanda; Konstantina Matsoukas; Silvia E Mancebo; Edmund K Bartlett
Journal:  JAMA Dermatol       Date:  2020-09-01       Impact factor: 10.282

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