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Published in: Cancer Cell International 1/2020

01-12-2020 | Hepatocellular Carcinoma | Primary research

High CENPM mRNA expression and its prognostic significance in hepatocellular carcinoma: a study based on data mining

Authors: Zeng-hong Wu, Dong-liang Yang

Published in: Cancer Cell International | Issue 1/2020

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Abstract

Background

Hepatocellular carcinoma (HCC) is a high mortality disease, the fifth most general cancer worldwide, and the second leading to cancer-related deaths, with more than 500,000 new patients diagnosed each year. First, the high expression of centromere M (CENPM) in mammary gland tissue of b-catenin transformed mice was identified.

Materials and methods

In our study, we evaluated the expression of CENPM in hepatocellular carcinoma based on data obtained from an online database. Multivariate analysis showed that the expression of CENPM and M classification was an independent prognostic factor for patients with hepatocellular carcinoma.

Results

Survival analysis showed that patients with high CENPM had a worse prognosis than patients with low CENPM (P < 0.01). A multivariate Cox regression hazard model showed that B cells, CD8+ T cells, macrophages, and dendritic cells infiltrated by immune cells were statistically significant in liver cancer (P < 0.05). Using the network, the 50 most frequently changed neighbor genes of CENPM were shown, and the most common change was RAD21 (18.3%).

Conclusion

Our study found that the expression of CENPM was significantly increased in patients with hepatocellular carcinoma, and it was related to a variety of clinical characteristics, its correlation with the level of immune infiltration and poor prognosis, so CENPM can be used as a useful prognosis for patients’ markers and HCC.
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Metadata
Title
High CENPM mRNA expression and its prognostic significance in hepatocellular carcinoma: a study based on data mining
Authors
Zeng-hong Wu
Dong-liang Yang
Publication date
01-12-2020
Publisher
BioMed Central
Published in
Cancer Cell International / Issue 1/2020
Electronic ISSN: 1475-2867
DOI
https://doi.org/10.1186/s12935-020-01499-y

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