Whole-genome copy-number profile analysis as a biomarker of relapse in melanoma

Early detection of melanoma relapse is key to maximise benefit from therapies like immune checkpoint inhibitors, and inhibitors of BRAF and MEK. We explored the utility of whole-genome copy-number profiles in circulating cell-free DNA (cfDNA), as a marker of melanoma relapse.
We adapted two published copy-number aberration scoring algorithms, the Copy Number Aberration Score (CNAS) and Extreme Copy Number Aberration Score (eCNAS), exploring their utility as a biomarker of active disease and survival in cfDNA samples from the GEMS study (Genetics and Epidemiology of Melanoma in Sheffield). We found the CNAS to be a good discriminator of active disease (odds ratio, 3.1; 95% CI, 1.5-6.2; p = 0.002), and CNAS above or below the 75th percentile remained a significant discriminator in multivariable analysis for active disease (p = 0.019, with area under ROC curve of 0.90). Mortality was higher in those with CNASs above the 75th percentile than in those with lower scores (HR, 3.4; 95% CI, 1.5-7.9; p = 0.005). We then set up the MRM study (Markers of Relapse in Melanoma) and obtained serial samples for cfDNA analysis over time. High baseline CNAS scores were associated with significantly poorer survival. We examined the performance of CNAS as a biomarker of relapse, and found this to be significant predictor of relapse status at the time of blood sampling. Sensitivity/specificity analysis of logCNAS showed high specificity (83%) of a low logCNAS in correctly identifying non-relapsed status. However, the low sensitivity (58%) of this approach suggests limited ability of logCNAS to correctly identify relapsed cases. Further exploratory analyses are required to explore scoring algorithms which combine the copy-number score with other potential biomarkers (e.g. cfDNA mutation burden) to maximise sensitivity, while preserving the high specificity provided by the logCNAS score.