Evidence Hub

CircZNF609 as a potential prognostic biomarker across multiple cancers: a systematic review and meta-analysis with ceRNA network exploration

Li M, Tu S, Qian K, Chen R, Wei L, Li P

Frontiers in oncology, 2026

791 participants

Abstract

Background: CircZNF609 (hsa_circ_0000615), a back-spliced transcript derived from the ZNF609 gene locus, has garnered increasing attention for its functional roles in tumor progression across multiple cancer types. However, no pan-cancer meta-analysis has systematically evaluated its prognostic value and association with clinicopathological aggressiveness. We therefore performed this systematic review and meta-analysis to synthesize all available clinical evidence addressing this critical gap.

Methods: We systematically retrieved literature from five databases (PubMed, Web of Science, Embase, the Cochrane Library and CNKI) up to April 2, 2026. Hazard ratios (HRs) and odds ratios (ORs) with 95% confidence intervals (CIs) were synthesized to quantify the link between circZNF609 levels and overall survival (OS) or clinicopathological variables. Heterogeneity assessment, sensitivity analysis, and publication bias evaluation were also performed. Additionally, a circZNF609-mediated ceRNA network was reconstructed based on experimentally validated targets.

Results: A total of 12 studies involving 791 patients were included in this meta-analysis. Elevated circZNF609 expression was significantly associated with worse overall survival (HR = 2.31, 95% CI:1.74-3.07, P P P P = 0.493) and Egger's regression test (P = 0.197) indicated no significant publication bias. Mechanistically, the reconstructed ceRNA network suggested that circZNF609 may exert oncogenic effects via cell-cycle and…

How strong is the evidence?

Evidence Hub reads this as a meta-analysis. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 791 participants or records.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free