A novel predictive model incorporating immune-related gene signatures for overall survival in melanoma patients

Abstract

AbstractMelanoma is the most invasive type of skin cancer, in which the immune system plays a vital role. In this study, we aimed to establish a prognostic prediction nomogram for melanoma patients that incorporates immune-related genes (IRGs). Ninety-seven differentially expressed IRGs between melanoma and normal skin were screened using gene expression omnibus database (GEO). Among these IRGs, a two-gene signature consisting of CCL8 and DEFB1 was found to be closely associated with patient prognosis using the cancer genome atlas (TCGA) database. Survival analysis verified that the IRGs score based on the signature gene expressions efficiently distinguished between high- and low-risk patients, and was identified to be an independent prognostic factor. A nomogram integrating the IRGs score, age and TNM stage was established to predict individual prognosis for melanoma. The prognostic performance was validated by the TCGA/GEO-based concordance indices and calibration plots. The area under the curve demonstrated that the nomogram was superior than the conventional staging system, which was confirmed by the decision curve analysis. Overall, we developed and validated a nomogram for prognosis prediction in melanoma based on IRGs signatures and clinical parameters, which could be valuable for decision making in the clinic.