Immune response-associated gene profiling in Japanese melanoma patients using multi-omics analysis

Project High-tech Omics-based Patient Evaluation (HOPE), including comprehensive whole-exome sequencing (WES) and gene expression profiling (GEP) using freshly resected tumor specimens, has been in progress since its implementation in 2014. Among a total of 1,685 cancer patients, 13 melanoma patients were registered in the HOPE Project and were characterized using multi-omics analyses. Among the 13 melanoma patients, 4 were deceased, and 9 were alive. The mean overall survival (OS) and relapse-free survival (RFS) times of the melanoma patients were 16.9 and 14.7 months, respectively. Previously, we developed an immune response-associated gene list, which consisted of 164 genes in Project HOPE, for evaluating the immunological status. In the present study, the association of immune response-associated gene expression with immunological parameters, such as programmed death-ligand 1 (PD-L1) and CD8 expression levels, single nucleotide variant (SNV) number, and Vogelstein driver gene mutation number, was investigated. With respect to PD-L1 expression, both immuno-suppression and immuno-stimulation-related genes were upregulated in PD-L1-positive melanomas. In contrast, regarding Vogelstein driver mutations, several T-cell activation-related genes were significantly downregulated in the high driver gene mutation group. In addition, many T-cell activation-related genes were upregulated in the CD8-positive melanomas. The correlation of immune response-associated gene expression with the survival time of the melanoma patients was investigated. Eight specific genes were commonly identified as genes that were significantly correlated for both the overall OS and RFS time, which could be possible prognostic factors for melanoma patients. These results revealed that an immune response-associated gene panel could be an informative tool for evaluating the immunological status prior to clinical immunotherapy in the upcoming era of genomic cancer medicine.