Predicting the Risk of Melanoma Metastasis Using an Immune Risk Score in the Melanoma Cohort

Yang Sheng; Cheng Yanping; Liu Tong; Liu Ning; Liu Yufeng; Liang Geyu

doi:10.3389/fbioe.2020.00206

Predicting the Risk of Melanoma Metastasis Using an Immune Risk Score in the Melanoma Cohort

Front Bioeng Biotechnol. 2020 Mar 31:8:206. doi: 10.3389/fbioe.2020.00206. eCollection 2020.

Authors

Yang Sheng¹, Cheng Yanping¹, Liu Tong¹, Liu Ning², Liu Yufeng², Liang Geyu¹

Affiliations

¹ Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, China.
² Department of Plastic and Reconstructive Surgery, The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, China.

Abstract

Melanoma is a highly aggressive cancer, attracting increasing attention worldwide. The 5-year survival rate of patients with metastatic melanoma is low. Therefore, it is critical to identify potential effective biomarkers for diagnosis of melanoma metastasis. In the present study, the melanoma cohort and immune genes were obtained from the Cancer Genome Atlas (TCGA) database and the ImmPort database, respectively. Then, we constructed the immune risk score (IRS) using univariate and multivariate logistic analysis. The area under the curve (AUC) of IRS in sequencing samples and the initial diagnosis patients was 0.90 and 0.80, respectively. Besides, IRS could add benefits for metastasis diagnosis. For sequencing samples, IRS (OR = 16.35, 95% CI = 8.74-30.59) increased the odds for melanoma metastasis. Similar results were obtained in the initial diagnosis patients (OR = 8.93, 95% CI = 3.53-22.61). A composite nomogram was built based on IRS and clinical information with well-fitted calibration curves. We further used other independent melanoma cohorts from Gene Expression Omnibus (GEO) databases to confirm the reliability and validity of the IRS (AUC > 0.75, OR > 1.04, and P value < 0.01 in all cohorts). In conclusion, IRS is significantly associated with melanoma metastasis and can be a novel effective signature for predicting the metastasis risk.

Keywords: immune risk score; metastasis risk; metastatic melanoma; nomogram; primary melanoma.