Identification of Three Genes Associated with Metastasis in Melanoma and Construction of a Predictive Model: A Multiracial Identification

Abstract

The aim of this study was to identify hub genes associated with metastasis and prognosis in melanoma. Weighted gene coexpression network analysis (WGCNA) was performed to screen and identify hub genes. ROC and K-M analyses were used to verify the hub genes in the internal and external data sets. The risk score model and nomogram model were constructed based on the IHC result. Through WGCNA, the three hub genes, SNRPD2, SNRPD3, and EIF4A3, were identified. In the external data set, the hub genes identified were associated with the worse prognosis (TCGA, SNRPD2, $P\le 0.02$ ; SNRPD3, $P=0.12$ ; EIF4A3, $P=0.11$ ; GSE65904, SNRPD2, $P=0.04$ ; SNRPD3, $P=0.10$ ; EIF4A3, $P<0.01$ ; GSE19234, SNRPD2, $P<0.01$ ; SNRPD3, $P<0.01$ ; EIF4A3, $P<0.01$ ). In the GSE8401, we found that the hub genes were highly expressed in the metastasis compared with the nonmetastasis group (SNRPD2, $988.5\pm 47.83$ vs. $738.4\pm 35.35$ , $P<0.01$ ; SNRPD3, $502.7\pm 25.7$ vs. $416.4\pm 23.88$ , $P=0.02$ ; EIF4A3, $567.6\pm 19.56$ vs. $495.2\pm 21.1$ , $P=0.01$ ). Moreover, the hub genes were identified by the IHC in our data set. The result was similar with the external data set. The hub genes could predict the metastasis and prognosis in the Chinese MM patients. Finally, the GSEA and Pearson analysis demonstrated that the SNRPD2 was associated with the immunotherapy. The three hub genes were identified and validated in MM patients in external and internal data sets. The risk factor model was constructed and verified as a powerful model to predict metastasis and prognosis in MM patients.