Tumour gene expression signature in primary melanoma predicts long-term outcomes.
Manik GargDominique-Laurent CouturierJeremie NsengimanaNuno A FonsecaMatthew J WongchenkoYibing YanMartin LaussGöran B JönssonJulia Newton-BishopChristine ParkinsonMark Ross MiddletonD Timothy Timothy BishopSarah McDonaldNikki StefanosJohn A TadrossIsmael A VergaraSerigne N LôFelicity NewellJames S WilmottJohn F ThompsonGeorgina V LongRichard A ScolyerPippa CorrieDavid J AdamsAlvis BrazmaRoy RabbiePublished in: Nature communications (2021)
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.
Keyphrases
- machine learning
- gene expression
- clinical trial
- genome wide
- early stage
- lymph node
- dna methylation
- skin cancer
- end stage renal disease
- poor prognosis
- newly diagnosed
- artificial intelligence
- phase ii
- study protocol
- systematic review
- resistance training
- healthcare
- single cell
- big data
- prognostic factors
- transcription factor
- copy number
- neoadjuvant chemotherapy
- peritoneal dialysis
- patient reported outcomes
- high intensity
- basal cell carcinoma
- social media
- genome wide analysis
- meta analyses