Characterization of Aging-Related Genes to Predict Prognosis and Evaluate the Tumor Immune Microenvironment in Malignant Melanoma

Author:

Zeng Ni1ORCID,Guo Chenrui2ORCID,Wang Yajun2ORCID,Li Lin1ORCID,Chen Xi3ORCID,Gao Shaoying4ORCID,Jiang Feng5ORCID,Cao Bilan1ORCID

Affiliation:

1. Department of Dermatology, Affiliated Hospital of Zunyi Medical University, Zunyi 563003, China

2. Department of Abdominal Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi 563003, China

3. Department of Endocrinology, Taizhou Clinical Medical School of Nanjing Medical University (Taizhou People’s Hospital), Taizhou, Jiangsu, China

4. Department of Plastic Surgery, Affiliated Hospital of Zunyi Medical University, Zunyi 563003, China

5. Department of Neonatology, Obstetrics and Gynecology Hospital of Fudan University, No. 419, Fangxie Road, Shanghai 200011, China

Abstract

Objective. Malignant melanoma (MM) is one of the most malignant types of skin cancer and its incidence and mortality rates are increasing worldwide. Aging is well recognized as a significant risk factor for cancer. However, few studies have analyzed in depth the association between aging-related genes (AGs) and malignant melanoma prognosis with tumor immune microenvironment. Methods. Here, we downloaded 471 MM patients from The Cancer Genome Atlas (TCGA) with RNA sequence and clinicopathological data. 58 AGs from the TCGA dataset were examined using Cox regression and the LASSO assay. As a result, a gene signature for aging-related genes was created. The time-dependent ROC curve and Kaplan–Meier analysis were calculated to determine its predictive capability. Moreover, we created a nomogram for the clinicopathologic variables and the AGs gene signature to determine overall survival (OS). We also explored the association between three immune checkpoints, immune cell infiltration, and the aging-related gene signature. Results. We established an aging risk model to identify and predict the immune microenvironment in malignant melanoma. Then we developed and validated a prognosis risk model using three AGs (CSNK1E, C1QA, and SOD-2) in the GSE65904 dataset. The aging signature was positively associated with clinical and molecular characteristics and can be used as a prognostic factor for malignant melanoma. The low aging risk score was associated with a poor prognosis and indicated an immunosuppressive microenvironment. Conclusions. To summarize, we established and validated a model of aging risk based on three aging-related genes that acted as an independent prognostic predictor of overall survival. Besides, it also characterized the immune response in the malignant melanoma microenvironment and could provide a potential indicator of individualized immunotherapy in malignant melanoma.

Publisher

Hindawi Limited

Subject

Oncology

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