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Nat Commun ; 12(1): 1137, 2021 02 18.
Artículo en Inglés | MEDLINE | ID: mdl-33602918

RESUMEN

Adjuvant systemic therapies are now routinely used following resection of stage III melanoma, however accurate prognostic information is needed to better stratify patients. We use differential expression analyses of primary tumours from 204 RNA-sequenced melanomas within a large adjuvant trial, identifying a 121 metastasis-associated gene signature. This signature strongly associated with progression-free (HR = 1.63, p = 5.24 × 10-5) and overall survival (HR = 1.61, p = 1.67 × 10-4), was validated in 175 regional lymph nodes metastasis as well as two externally ascertained datasets. The machine learning classification models trained using the signature genes performed significantly better in predicting metastases than models trained with clinical covariates (pAUROC = 7.03 × 10-4), or published prognostic signatures (pAUROC < 0.05). The signature score negatively correlated with measures of immune cell infiltration (ρ = -0.75, p < 2.2 × 10-16), with a higher score representing reduced lymphocyte infiltration and a higher 5-year risk of death in stage II melanoma. Our expression signature identifies melanoma patients at higher risk of metastases and warrants further evaluation in adjuvant clinical trials.


Asunto(s)
Perfilación de la Expresión Génica , Regulación Neoplásica de la Expresión Génica , Melanoma/genética , Bases de Datos Genéticas , Humanos , Aprendizaje Automático , Análisis Multivariante , Estadificación de Neoplasias , Pronóstico , Supervivencia sin Progresión , Modelos de Riesgos Proporcionales , Reproducibilidad de los Resultados , Factores de Tiempo , Resultado del Tratamiento
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