Le-Bin Song1, Jiao-Chen Luan2, Qi-Jie Zhang2, Lin Chen1, Hao-Yang Wang1, Xue-Chen Cao1, Ning-Hong Song2,3, Yan Lu1. 1. Department of Dermatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China. 2. Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China. 3. The Affiliated Kezhou People's Hospital of Nanjing Medical University, Kezhou, Xinjiang, China.
Abstract
BACKGROUND: Cutaneous melanoma is defined as one of the most aggressive skin tumors in the world. An increasing body of evidence suggested an indispensable association between immune-associated gene (IAG) signature and melanoma. This article is aimed at formulating an IAG signature to estimate prognosis of melanoma. METHODS: 434 melanoma patients were extracted from The Cancer Genome Atlas (TCGA) database, and 1811 IAGs were downloaded from the ImmPort database in our retrospective study. The Cox regression analysis and LASSO regression analysis were utilized to establish a prognostic IAG signature. The Kaplan-Meier (KM) survival analysis was performed, and the time-dependent receiver operating characteristic curve (ROC) analysis was further applied to assess the predictive value. Besides, the propensity score algorithm was utilized to balance the confounding clinical factors between the high- and low-risk groups. RESULTS: A total of six prognostic IAGs comprising of INHA, NDRG1, IFITM1, LHB, GBP2, and CCL8 were eventually filtered out. According to the KM survival analysis, the results displayed a shorter overall survival (OS) in the high-risk group compared to the low-risk group. In the multivariate Cox model, the gene signature was testified as a remarkable prognostic factor (HR = 45.423, P < 0.001). Additionally, the ROC curve analyses were performed which demonstrated our IAG signature was superior to four known biomarkers mentioned in the study. Moreover, the IAG signature was significantly related to immunotherapy-related biomarkers. CONCLUSION: Our study demonstrated that the six IAG signature played a critical role in the prognosis and immunotherapy of melanoma, which might help clinicians predict patients' survival and provide individualized treatment.
BACKGROUND: Cutaneous melanoma is defined as one of the most aggressive skin tumors in the world. An increasing body of evidence suggested an indispensable association between immune-associated gene (IAG) signature and melanoma. This article is aimed at formulating an IAG signature to estimate prognosis of melanoma. METHODS: 434 melanoma patients were extracted from The Cancer Genome Atlas (TCGA) database, and 1811 IAGs were downloaded from the ImmPort database in our retrospective study. The Cox regression analysis and LASSO regression analysis were utilized to establish a prognostic IAG signature. The Kaplan-Meier (KM) survival analysis was performed, and the time-dependent receiver operating characteristic curve (ROC) analysis was further applied to assess the predictive value. Besides, the propensity score algorithm was utilized to balance the confounding clinical factors between the high- and low-risk groups. RESULTS: A total of six prognostic IAGs comprising of INHA, NDRG1, IFITM1, LHB, GBP2, and CCL8 were eventually filtered out. According to the KM survival analysis, the results displayed a shorter overall survival (OS) in the high-risk group compared to the low-risk group. In the multivariate Cox model, the gene signature was testified as a remarkable prognostic factor (HR = 45.423, P < 0.001). Additionally, the ROC curve analyses were performed which demonstrated our IAG signature was superior to four known biomarkers mentioned in the study. Moreover, the IAG signature was significantly related to immunotherapy-related biomarkers. CONCLUSION: Our study demonstrated that the six IAG signature played a critical role in the prognosis and immunotherapy of melanoma, which might help clinicians predict patients' survival and provide individualized treatment.
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