The Prognostic Importance of Ki-67 in Gastrointestinal Carcinomas: A Meta-analysis and Multi-omics Approach

J Gastrointest Cancer. 2024 Feb 27. doi: 10.1007/s12029-024-01022-w. Online ahead of print.

Abstract

Purpose: This study aimed to determine if Ki-67, a commonly used marker to measure tumor proliferation, is a reliable prognostic factor in various types of gastrointestinal (GI) cancers based on current high-quality multivariable evidence.

Methods: A comprehensive search was conducted in PubMed, Embase, Scopus, and ISI Web of Science databases to investigate the association between Ki-67 positivity and overall survival (OS) and disease/recurrence-free survival (DFS/RFS) in GI cancers. Heterogeneity was assessed using Chi-square-based Q and I2 analyses and publication bias using funnel plots and Egger's analysis. In addition, Ki-67 levels in different GI cancers were examined by different platforms. The prognostic capability of Ki-67, gene ontology (GO), and pathway enrichment analysis were obtained from GEPIA2 and STRING.

Results: Totally, 61 studies, involving 13,034 patients, were deemed eligible for our evaluation. The combined hazard ratios (HRs) demonstrated the prediction ability of overexpressed Ki-67 for a worse OS (HR: 1.67, P < 0.001; HR: 1.37, P = 0.021) and DFS/RFS (HR: 2.06, P < 0.001) in hepatocellular and pancreatic malignancies, respectively, as confirmed by multi-omics databases. However, similar correlation was not found in esophageal, gastric, and colorectal cancers. Furthermore, most of the associations were identified to be robust based on different subcategories and publication bias assessment. Finally, enriched Ki-67-related genes were found to be involved in various important signaling pathways, such as cell cycle, P53 signaling network, and DNA damage responses.

Conclusion: This study supports that Ki-67 can serve as an independent prognostic biomarker for pancreatic and hepatocellular malignancies in clinical settings.

Keywords: Gastrointestinal cancers; Ki-67; Meta-analysis; Multi-omics platforms; Prognostic value.

Publication types

  • Review