Author
Listed:
- 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
Newcastle University)
- 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
The University of Sydney)
- Serigne Lo
(The University of Sydney
The University of Sydney
Imam Abdulrahman Bin Faisal University)
- Felicity Newell
(QIMR Berghofer Medical Research Institute)
- James S. Wilmott
(The University of Sydney
The University of Sydney)
- John F. Thompson
(The University of Sydney
The University of Sydney
The University of Sydney)
- Georgina V. Long
(The University of Sydney
The University of Sydney
Royal North Shore and Mater Hospitals)
- Richard A. Scolyer
(The University of Sydney
The University of Sydney
Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital and New South Wales Health Pathology)
- 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
Experimental Cancer Genetics, The Wellcome Sanger Institute)
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
Suggested Citation
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, 2021.
"Tumour gene expression signature in primary melanoma predicts long-term outcomes,"
Nature Communications, Nature, vol. 12(1), pages 1-14, December.
Handle:
RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-21207-2
DOI: 10.1038/s41467-021-21207-2
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