Identification of Key Gene and Pathways for the Prediction of Peritoneal Metastasis of Gastric Cancer by Co-expression Analysis

Peritoneal metastasis is the most common pattern in advanced gastric cancer and can predict poor disease prognosis. Early detection of peritoneal tumor dissemination is restricted by small peritoneal deposits. Therefore, it is critical to identify a novel predictive marker and to explore the potenti...

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Veröffentlicht in:Journal of Cancer 2020-01, Vol.11 (10), p.3041-3051
Hauptverfasser: Zhang, Simeng, Zang, Dan, Cheng, Yu, Li, Zhi, Yang, Bowen, Guo, Tianshu, Liu, Yunpeng, Qu, Xiujuan, Che, Xiaofang
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container_end_page 3051
container_issue 10
container_start_page 3041
container_title Journal of Cancer
container_volume 11
creator Zhang, Simeng
Zang, Dan
Cheng, Yu
Li, Zhi
Yang, Bowen
Guo, Tianshu
Liu, Yunpeng
Qu, Xiujuan
Che, Xiaofang
description Peritoneal metastasis is the most common pattern in advanced gastric cancer and can predict poor disease prognosis. Early detection of peritoneal tumor dissemination is restricted by small peritoneal deposits. Therefore, it is critical to identify a novel predictive marker and to explore the potential mechanism associated with this process. In the present study, one module that correlated with peritoneal metastasis was identified. Enrichment analysis indicated that the Focal adhesion and the PI3K-Akt signaling pathway were the most significant pathways. Following network and Molecular Complex Detection (MCODE) analysis, the hub-gene cluster that consisted of 19 genes was selected. Methionine sulfoxide reductase B3 ( ) was identified as a seed gene. Survival analysis indicated that high expression levels of were independent predictors of peritoneal disease-free survival (pDFS) as determined by univariate (HR 8.559, 95% CI; 3.339-21.937; P
doi_str_mv 10.7150/jca.39645
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Early detection of peritoneal tumor dissemination is restricted by small peritoneal deposits. Therefore, it is critical to identify a novel predictive marker and to explore the potential mechanism associated with this process. In the present study, one module that correlated with peritoneal metastasis was identified. Enrichment analysis indicated that the Focal adhesion and the PI3K-Akt signaling pathway were the most significant pathways. Following network and Molecular Complex Detection (MCODE) analysis, the hub-gene cluster that consisted of 19 genes was selected. Methionine sulfoxide reductase B3 ( ) was identified as a seed gene. Survival analysis indicated that high expression levels of were independent predictors of peritoneal disease-free survival (pDFS) as determined by univariate (HR 8.559, 95% CI; 3.339-21.937; P&lt;.001) and multivariate Cox analysis (HR 3.982, 95% CI; 1.509-10.509; P=.005). Furthermore, patients with high levels of exhibited a significantly lower Overall Survival (OS) (log-rank P = 0.007). The external validation was performed by the (The Cancer Genome Atlas (TCGA)) (log-rank P = 0.037) and Kaplan Meier-plotter (KMplotter) (log-rank P = 0.031) data. experiments confirmed that MSRB3 was a critical protein in regulating gastric cancer cell proliferation and migration. In conclusion, High expression levels of in GC can predict peritoneal metastasis and recurrence as well as poor prognosis. 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Furthermore, patients with high levels of exhibited a significantly lower Overall Survival (OS) (log-rank P = 0.007). The external validation was performed by the (The Cancer Genome Atlas (TCGA)) (log-rank P = 0.037) and Kaplan Meier-plotter (KMplotter) (log-rank P = 0.031) data. experiments confirmed that MSRB3 was a critical protein in regulating gastric cancer cell proliferation and migration. In conclusion, High expression levels of in GC can predict peritoneal metastasis and recurrence as well as poor prognosis. 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subjects Antibodies
Gastric cancer
Gene expression
Kinases
Medical prognosis
Metastasis
Proteins
Research Paper
Software
Survival analysis
title Identification of Key Gene and Pathways for the Prediction of Peritoneal Metastasis of Gastric Cancer by Co-expression Analysis
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