High expression of centromere protein A and its molecular mechanism and clinical significance in prostate cancer: A study based on data mining and immunohistochemistry
Fang-Cheng Jiang, Gao-Qiang Zhai, Jia-Lin Liu, Rui-Gong Wang, Yuan-Ping Yang, Harivignesh Murugesan, Xiao-Xiang Yu, Xiu-Fang Du, Juan He, Zhen-Bo Feng, Shang Ling Pan, Gang Chen, Sheng-Hua Li, Zhi-Guang Huang
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引用次数: 0
Abstract
The progression of prostate cancer (PCa) leads to poor prognosis. However, the molecular mechanism of PCa is still not completely clear. This study aimed to elucidate the important role of centromere protein A (CENPA) in PCa. Large numbers of bulk RNA sequencing (RNA-seq) data and in-house immunohistochemistry data were used in analysing the expression level of CENPA in PCa and metastatic PCa (MPCa). Single-cell RNA-seq data was used to explore the expression status of CENPA in different prostate subpopulations. Enrichment analysis was employed to detect the function of CENPA in PCa. Clinicopathological parameters analysis was utilised in analysing the clinical value of CENPA. The results showed that CENPA was upregulated in PCa (standardised mean difference [SMD] = 0.83, p = 0.001) and MPCa (SMD = 0.61, p = 0.029). CENPA was overexpressed in prostate cancer stem cells (CSCs) with androgen receptor (AR) negative compared to epithelial cells with AR positive. CENPA may influence the development of PCa through affecting cell cycle. Patients with nodal metastasis had higher expression level of CENPA. And patients with high CENPA expression had poor disease-free survival. Taken together, Overexpression of CENPA may influence the development of PCa by regulating cell cycle and promoting metastasis.
期刊介绍:
IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells.
The scope includes the following topics:
Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.