In Annals of translational medicine
BACKGROUND : Molecular profiling with next-generation sequencing (NGS) has been applied in multiple solid tumors, including melanomas, to identify potential drug targets. However, the association between clinical outcomes and the molecular alterations has not yet been fully clarified.
METHODS : A total of 108 patients with melanoma were included in this study, 95 of whom had both sequencing data and clinical outcomes were collected. We analyzed the genetic alterations of 108 malignant melanoma patients using the OncoCare panel, which covers 559 genes.
RESULTS : A model was also established to predict side effects through a combination analysis of clinical data and somatic variants, yielding an area under the receiver operating characteristic curve (AUROC) score of 0.8. We also identified epidermal growth factor receptor (EGFR) mutation was excellent predictor for progression-free survival (PFS) for patient who received immunotherapy (log-rank P=0.01), while tumor mutation burden (TMB) was found to not be significantly associated with PFS (log-rank P=0.87). Combining clinical features with genetic analysis, we found that patients carrying both DNA POLD1/ALOX12B or POLD1/PTPRT mutations had a significantly lower survival rate.
CONCLUSIONS : Overall, these results demonstrate the benefits of applying NGS clinical panels and shed light on future directions of personalized therapeutics for the treatment of melanoma.
Sun Wei, Zhao Fang, Hu Tu, Wu Zhiqiang, Xu Yu, Dong Yan, Zheng Biqiang, Wang Chunmeng, Yan Wangjun, Zhu Xiaoli, Wu Jian, McKay Michael J, Arozarena Imanol, Alos Llucia, Teixido Cristina, Chen Yong
2022-Nov
Melanoma, genetic alterations, machine learning, next-generation sequencing panels (NGS panels), prognostic predictors
