Tumour gene expression signature in primary melanoma predicts long-term outcomes: A prospective multicentre study

Abstract

PurposePredicting outcomes after resection of primary melanoma remains crude, primarily based on tumour thickness. We explored gene expression signatures for their ability to better predict outcomes.MethodsDifferential expression analysis of 194 primary melanomas resected from patients who either developed distant metastasis (n=89) or did not (n=105) was performed. We identified 121 metastasis-associated genes that were included in our prognostic signature, “Cam_121”. Several machine learning classification models were trained using nested leave- one-out cross validation (LOOCV) to test the signature’s capacity to predict metastases, as well as regression models to predict survival. The prognostic accuracy was externally validated in two independent datasets.ResultsCam_121 performed significantly better in predicting distant metastases than any of the models trained with the clinical covariates alone (pAccuracy=4.92×10−3), as well as those trained with two published prognostic signatures. Cam_121 expression score was strongly associated with progression-free survival (HR=1.7, p=3.44×10−6), overall survival (HR=1.73, p=7.71×10−6) and melanoma-specific survival (HR=1.59, p=0.02). Cam_121 expression score also negatively correlated with measures of immune cell infiltration (ρ=−0.73, p<2.2×10−16), with a higher score representing reduced tumour lymphocytic infiltration and a higher absolute 5-year risk of death in stage II melanoma.ConclusionsThe Cam_121 primary melanoma gene expression signature outperformed currently available alternatives in predicting the risk of distant recurrence. The signature confirmed (using unbiased approaches) the central prognostic importance of immune cell infiltration in long-term patient outcomes and could be used to identify stage II melanoma patients at highest risk of metastases and poor survival who might benefit most from adjuvant therapies.Translational relevancePredicting outcomes after resection of primary melanoma is currently based on traditional histopathological staging, however survival outcomes within these disease stages varies markedly. Since adjuvant systemic therapies are now being used routinely, accurate prognostic information is needed to better risk stratify patients and avoid unnecessary use of high cost, potentially harmful drugs, as well as to inform future adjuvant strategies. The Cam_121 gene expression signature appears to have this capability and warrants evaluation in prospective clinical trials.

Cooperation between melanoma cell states promotes metastasis through heterotypic cluster formation

“…Bulk RNA-seq data from 194 primary melanoma patients were extracted from the phase III adjuvant AVAST-M melanoma cohort (Corrie et al, 2018;Garg et al, 2020). Variance stabilizing transformation (VST) was applied to the raw counts using the varianceStabilizingTransformation function from the package DESeq2 (Love et al, 2014) (v1.22.2).…”

“…VST normalized expression data were used as a continuous variable in a multivariate Cox regression model, using the coxph function of the survival package (Therneau, 2020;Therneau and Grambsch, 2000) (v2.42-3) Performance Status), NClass (regional lymph involvement) and treatment (bevacizumab or placebo) (Garg et al, 2020).…”

Cell state diversity promotes metastasis through heterotypic cluster formation in melanoma

“…Bulk RNA-seq data from 194 primary melanoma patients was extracted from the phase III adjuvant AVAST-M melanoma cohort (Corrie et al, 2018;Garg et al, 2020). Variance stabilizing transformation (VST) was applied to the raw counts using the varianceStabilizingTransformation function from the package DESeq2 (Love et al, 2014) (v1.22.2).…”

“…Progression-free survival was calculated as the time from diagnosis to the last follow-up or death/progression to metastatic disease, whichever occurred first. The following clinical covariates were considered in the multivariate Cox regression model; age at diagnosis, gender, stage (AJCC 7 th edition), ECOG (Eastern Cooperative Oncology Group Performance Status), NClass (regional lymph involvement) and treatment (bevacizumab or placebo) (Garg et al, 2020).…”