4.7 Article

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

期刊

INTERNATIONAL IMMUNOPHARMACOLOGY
卷 90, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.intimp.2020.107238

关键词

Hepatocellular carcinoma; microRNA; TCGA; GEO; Prognostic signature; Macrophages

资金

  1. National Natural Science Foundation of China [11602181]
  2. Fundamental Research Funds for the Central Universities [WUT: 2018IB005]
  3. Open Project of the State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University [SKLKF201606]
  4. Visiting Scholar Foundation of Key Laboratory of Biorheological Science and Technology (Chongqing University), Ministry of Education [CQKLBST-2018-006, CQKLBST-2018-009]

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The study identified drastic changes in macrophage infiltration during the progression of hepatocellular carcinoma. A novel 4-gene signature was established for prognostic prediction, showing superior prognostic independence.
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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