high expression of usp22 predicts poor prognosis and advanced clinicopathological features in solid tumors: a meta-analysis

high expression of usp22 predicts poor prognosis and advanced clinicopathological features in solid tumors: a meta-analysis

;Yang XH;Zang H;Luo Y;Wu J;Fang Z;Zhu W;Li Y
jurnal tam 2018 Vol. Volume 11 pp. 3035-3046
224
xh2018oncotargetshigh

Abstract

Xiaohui Yang,1,* Haiyang Zang,2,* Yingbin Luo,1 Jianchun Wu,1 Zhihong Fang,1 Weikang Zhu,1 Yan Li1 1Department of Oncology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China; 2Department of Spleen and Stomach, Xinyi Municipal Hospital of Traditional Chinese Medicine, Xinyi, Jiangsu, China *These authors contributed equally to this work Introduction: The expression of USP22 has been demonstrated to play a pivotal role in solid tumors. However, the prognostic value of USP22 still remains unknown. Materials and methods: A systematic meta-analysis was performed to assess the prognostic value of USP22 in cancers. A literature collection was conducted from inception to June 8, 2017 by searching PubMed, Cochrane Library, Embase, Ovid and Web of Science databases. The pooled hazard ratio (HR) and odds ratio (OR) were used to correlate high expression of USP22 with overall survival (OS) and clinicopathological features. Results: The results, pooled by 19 studies with 2,876 cases, indicated that high expression of USP22 predicted poor OS (HR=2.48, 95% CI: 2.11–2.84, p<0.001) and disease-free survival (DFS; HR=2.55, 95% CI: 2.05–3.05, p<0.001) of cancer patients. Furthermore, high expression of USP22 was also significantly associated with advanced clinicopathological parameters, including tumor stage, tumor differentiation, metastasis, nodal status and tumor size. Conclusion: Our finding revealed that USP22 might be an indicator of poor prognosis and advanced clinicopathological features of solid tumors and could be served as a novel biomarker. Keywords: carcinoma, USP22, prognosis, biomarker, meta-analysis

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