Tumour gene expression signature in primary melanoma predicts long-term outcomes

Manik Garg, Dominique-Laurent Couturier, Jérémie Nsengimana, Nuno A. Fonseca, Matthew Wongchenko, Yibing Yan, Martin Lauss, Göran B. Jönsson, Julia Newton-Bishop, Christine Parkinson, Mark R. Middleton, D. Timothy Bishop, Sarah McDonald, Nikki Stefanos, John Tadross, Ismael A. Vergara, Serigne Lo, Felicity Newell, James S. Wilmott, John F. Thompson, Georgina V. Long, Richard A. Scolyer, Pippa Corrie, David J. Adams, Alvis Brazma and Roy Rabbie ()
Additional contact information
Manik Garg: European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)
Dominique-Laurent Couturier: University of Cambridge, Li Ka Shing Centre, Robinson Way
Jérémie Nsengimana: University of Leeds School of Medicine
Nuno A. Fonseca: Universidade do Porto, Rua Padre Armando Quintas
Matthew Wongchenko: Oncology Biomarker Development, Genentech Inc.
Yibing Yan: Oncology Biomarker Development, Genentech Inc.
Martin Lauss: Lund University Cancer Center, Lund University
Göran B. Jönsson: Lund University Cancer Center, Lund University
Julia Newton-Bishop: University of Leeds School of Medicine
Christine Parkinson: Cambridge University Hospitals NHS Foundation Trust
Mark R. Middleton: University of Oxford
D. Timothy Bishop: University of Leeds School of Medicine
Sarah McDonald: Cambridge University Hospitals NHS Foundation Trust
Nikki Stefanos: Cambridge University Hospitals NHS Foundation Trust
John Tadross: Cambridge University Hospitals NHS Foundation Trust
Ismael A. Vergara: The University of Sydney
Serigne Lo: The University of Sydney
Felicity Newell: QIMR Berghofer Medical Research Institute
James S. Wilmott: The University of Sydney
John F. Thompson: The University of Sydney
Georgina V. Long: The University of Sydney
Richard A. Scolyer: The University of Sydney
Pippa Corrie: Cambridge University Hospitals NHS Foundation Trust
David J. Adams: Experimental Cancer Genetics, The Wellcome Sanger Institute
Alvis Brazma: European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)
Roy Rabbie: Cambridge University Hospitals NHS Foundation Trust

Nature Communications, 2021, vol. 12, issue 1, 1-14

Abstract: Abstract 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

Date: 2021
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DOI: 10.1038/s41467-021-21207-2

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