Development of a macrophages-related 4-gene signature and nomogram for the overall survival prediction of hepatocellular carcinoma based on WGCNA and LASSO algorithm.

Lasso(编程语言) 癌症研究 肿瘤科 比例危险模型 微阵列分析技术 内科学 生存分析 基因表达谱 无线电技术 微阵列 转录组 基因表达 基因 特征选择 接收机工作特性 计算生物学
作者
Zichang Yang,Quan Zi,Kang Xu,Chunli Wang,Qingjia Chi
出处
期刊:International Immunopharmacology [Elsevier]
卷期号:90: 107238- 被引量:7
标识
DOI:10.1016/j.intimp.2020.107238
摘要

BACKGROUND Immune system instability and poor prognosis are the two major clinical performance of hepatocellular carcinoma (HCC). Abnormal expression of MiR-424-5p has been reported to accelerate the progression of liver cancer, but it mediated immune cell infiltration imbalance is still unknown. We aim to mine the immune-related genes (IRGs) targeted by miR-424-5p and construct a multi-gene signature to improve the prognostic prediction of HCC. METHODS The HCC-related data of the cancer genome atlas (TCGA) database and the GSE14520 dataset of the gene expression omnibus (GEO) database were downloaded as the discovery dataset and the validation dataset, respectively. Weighted gene co-expression network analysis (WGCNA), the deconvolution algorithm of CIBERSORT and LASSO algorithm participated in the identification of IRGs and the development of prognostic signature and nomogram. RESULTS Our study found that the abundance of macrophages M0, M1 and M2 are all drastically changed during the cancerous process. A total of 920 macrophages infiltration-related LRGs were identified and a novel 4-gene signature (CDCA8, CBX2, UCK2 and SOCS2) with superior prognostic independence was established. The prognostic signature based risk score has superior capability to identify high-risk patients and predict overall survival (p < 0.001; AUC = 0.798 for 1 year; AUC = 0.748 for 3 years; AUC = 0.721 for 5 years). And it (C-index = 0.726) has a better prognostic potential than the TNM stage (C-index = 0.619), which is widely adopted in clinical practice. Additionally, the nomogram formed by combining the risk score and TNM stage further improved the accuracy of survival prediction (C-index = 0.733). CONCLUSION In summary, the immune landscape with abnormal infiltration of macrophages may be one of the prelude to the cancerous process. The novel macrophages-related 4-gene signature is expected to become a potential prognostic marker in liver cancer.
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