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CEMIP as a prognostic biomarker for cancers: a meta- and bioinformatic analysis

  • Huan Chen
  • , Qingting Wang
  • , Jin Liu
  • , Yuqian Chen
  • , Qianqian Zhang
  • , Limin Chai
  • , Yan Wang
  • , Danyang Li
  • , Yuanjie Qiu
  • , Manxiang Li

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Objective: Cell migration-inducing and hyaluronan-binding protein (CEMIP) is overexpressed in several cancers and is related to prognosis in cancer patients. Here, we conducted a meta-analysis to explore the prognostic effects of CEMIP in cancer patients. Methods: Relevant published studies were systematically searched in four databases. The role of CEMIP was evaluated using pooled hazard ratios (HRs), odd ratios (ORs), and 95% confidence intervals (95% CIs). The Cancer Genome Atlas (TCGA) was used to investigate the prognostic value of CEMIP in various cancers. Results: 11 literatures with 1355 patients were included in this meta-analysis. The results showed that overexpression of CEMIP was significantly associated with poor OS (HR = 3.03; 95% CI: 2.00–4.59; p < 0.001), DFS (HR = 3.38; 95% CI: 2.41–4.74; p < 0.001). Elevated CEMIP expression is associated with advanced clinical stage, lymph node metastasis, and poor histological grade. In addition, TCGA datasets were used to verify that CEMIP was found highly expressed in multiple cancers and was associated with poorer survival. Conclusion: The results demonstrated that CEMIP could be a novel prognostic biomarker for cancer patients. However, because the included studies mainly focused on Asian populations, further research is needed to verify its applicability.

Original languageEnglish
Pages (from-to)1107-1115
Number of pages9
JournalExpert Review of Molecular Diagnostics
Volume22
Issue number12
DOIs
StatePublished - 2022
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • CEMIP
  • Meta-analysis
  • TCGA dataset
  • biomarker
  • cancers
  • prognosis

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