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Lookup NU author(s): Dr Jérémie Nsengimana
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2021, The Author(s).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.
Author(s): Garg M, Couturier D-L, Nsengimana J, Fonseca NA, Wongchenko M, Yan Y, Lauss M, Jonsson GB, Newton-Bishop J, Parkinson C, Middleton MR, Bishop DT, McDonald S, Stefanos N, Tadross J, Vergara IA, Lo S, Newell F, Wilmott JS, Thompson JF, Long GV, Scolyer RA, Corrie P, Adams DJ, Brazma A, Rabbie R
Publication type: Article
Publication status: Published
Journal: Nature Communications
Online publication date: 18/02/2021
Acceptance date: 15/01/2021
Date deposited: 08/04/2021
ISSN (electronic): 2041-1723
Publisher: Nature Research
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