Research Paper Advance Articles
Exploration of the immune cell infiltration-related gene signature in the prognosis of melanoma
- 1 Hubei Key Laboratory of Tumor Biological Behaviors, Zhongnan Hospital of Wuhan University, Wuhan 430071, Hubei, China
- 2 Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan 430071, Hubei, China
- 3 Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, Hubei, China
Received: May 21, 2020 Accepted: November 10, 2020 Published: January 10, 2021https://doi.org/10.18632/aging.202279
How to Cite
Copyright: © 2021 Zeng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Melanoma is a life-threatening form of skin cancer with an elevated risk of metastasis and high mortality rates. The prognosis and clinical outcomes of cancer immunotherapy in melanoma patients are influenced by immune cell infiltration in the tumor microenvironment (TME) and the expression of genetic factors. Despite reports suggesting that immune-classification may have a better prediction of prognosis compared to the American Joint Committee on Cancer/Union for International Cancer Control (AJCC/UICC) TNM-classification, the definition of Immunoscore in melanoma is becoming a difficult challenge. In this study, we established and verified a 7-gene prognostic signature. Melanoma patients from the Cancer Genome Atlas (TCGA) were separated into a low-risk group and a high-risk group using the median risk score. Receiver operating characteristic (ROC) analysis for overall survival (OS) showed that the area under the curve (AUC) was 0.701 for 1 year, 0.726 for 3 years, and 0.745 for 5 years, respectively. Moreover, a nomogram was constructed as a practical prognostic tool, and the AUC was 0.829 for 3 years, and 0.803 for 5 years, respectively. Furthermore, we validated the above results in two datasets from the Gene Expression Omnibus (GEO) database and the relationship between 7-gene prognostic signature and immune infiltration estimated.
TME: Tumor microenvironment; AJCC/UICC: American Joint Committee on Cancer/Union for International Cancer Control; TCGA: The Cancer Genome Atlas; ROC: Receiver operating characteristic; OS: Overall survival; AUC: Area under the curve; DSS: Disease-specific survival; PFS: Progression-free survival; GEO: Gene Expression Omnibus; PD-L1: programmed death-ligand 1; TIICs: Tumour infiltrating immune cells; ssGSEA: Single-sample gene set enrichment; ESTIMATE: Estimation of Stromal and Immune cells in Malignant Tumor tissues using the Expression data; HLA: Human leukocyte antigen; GSEA: Gene set enrichment analysis; GO analysis: Gene ontology analysis; KEGG: Kyoto Encyclopedia of Genes and Genomes; DEGs: Differentially expressed genes; STRING: Search Tool for the Retrieval of Interacting Genes database; PPI: Protein-protein interaction; MCODE: Molecular Complex Detection; WGCNA: Weighted gene co-expression network analysis; BP: Biological processes; CC: Cellular components; MF: Molecular functions; LASSO: Least Absolute Shrinkage and Selection Operator; GSVA: Gene Set Variation Analysis; FDR: False discovery rate; TOM: Topological overlap matrix; TIMER: Tumor Immune Estimation Resource; HR: Hazard ratio.