Research Paper Volume 15, Issue 7 pp 2503—2524

NCAPG as a novel prognostic biomarker in numerous cancers: a meta-analysis and bioinformatics analysis

Jie Lin1, *, , Gangyi Li2, *, , Yanping Bai1, , Yingjun Xie1, ,

  • 1 Department of Hepatobiliary and Pancreatic Surgery, Jilin University Second Hospital, Jilin 130000, China
  • 2 Department of Corneal Refraction, Jilin University Second Hospital, Jilin 130000, China
* Equal contribution

Received: September 12, 2022       Accepted: March 21, 2023       Published: March 29, 2023      

https://doi.org/10.18632/aging.204621
How to Cite

Copyright: © 2023 Lin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Background: Identification of effective biomarkers for cancer prognosis is a primary research challenge. Recently, several studies have reported the relationship between NCAPG and the occurrence of various tumors. However, none have combined meta-analytical and bioinformatics approaches to systematically assess the role of NCAPG in cancer.

Methods: We searched four databases, namely, PubMed, Web of Science, Embase, and the Cochrane Library, for relevant articles published before April 30, 2022. The overall hazard ratio or odds ratio and 95% confidence intervals were calculated to assess the relationship between NCAPG expression and cancer survival prognosis or clinical characteristics. Furthermore, the aforementioned results were validated using the GEPIA2, Kaplan-Meier plotter, and PrognoScan databases.

Results: The meta-analysis included eight studies with 1096 samples. The results showed that upregulation of NCAPG was correlated with poorer overall survival (hazard ratio = 2.90, 95% confidence interval = 2.06–4.10, P < 0.001) in the cancers included in the study. Subgroup analysis showed that in some cancers, upregulation of NCAPG was correlated with age, distant metastasis, lymph node metastasis, TNM stage, relapse, differentiation, clinical stage, and vascular invasion. These results were validated using the GEPIA2, UALCAN, and PrognoScan databases. We also explored the processes of NCAPG methylation and phosphorylation.

Conclusion: Dysregulated NCAPG expression is associated with the clinical prognostic and pathological features of various cancers. Therefore, NCAPG can serve as a human cancer therapeutic target and a new potential prognostic biomarker.

Abbreviations

BC: Breast cancer; NSCLC: Non-small cell lung cancer; GC: Gastric cancer; HCC: Hepatocellular carcinoma; IHC: Immunohistochemistry; RNA-Seq: RNA sequence; CP: Clinicopathological parameters; CI: Confidence interval; K-M: Kaplan-Meier curve; REP: Reported; NOS: Newcastle–Ottawa Scale; BRCA: Breast cancer; GBM: Glioblastoma; LIHC: Liver cancer; LUAD: Lung cancer; LUSC: Lung squamous cell carcinoma; STAD: Stomach adenocarcinoma; OS: Over survival; PFS: Progression Free Survival; DFS: Disease Free Survival; DSS: Disease Specific Survival; RFS: Recurrence Free Survival; PPS: Post-progression Survival; DMPS: Disease Median Progression Survival; FP: Free Progression; CeRNA: Competing endogenous RNAs; P: Phosphorylation; Ser: Serine; H8: HEAT 8; H9: HEAT 9; PR: Polar Residues; BAR: Basic and Acidic Residues.