Septin9 gene methylation in plasma for gastric cancer detection: a systematic review and meta-analysis

OBJECTIVE: To evaluate the plasma-based methylated Septin9 (mSEPT9) diagnostic accuracy for gastric cancer (GC) and analyze its performance across different subgroups. METHODS: Through comprehensive computer searching, we systematically collected clinical trials on the diagnostic efficacy of plasma mSEPT9 in GC. The search scope covered PubMed, Web of Science, the Cochrane Library, Embase, CNKI, WanFang Data and VIP databases from their establishments to 31 August 2025. Study quality was rigorously assessed with the assistance of Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). Meta-analysis via Stata 17.0 and Meta-Disc 1.4 was performed. RESULTS: This study included 9 articles containing 10 studies, encompassing 3,120 participants. Meta-analysis revealed a pooled sensitivity of 0.40 (95%CI: 0.34-0.47), specificity of 0.94 (95%CI: 0.91-0.96), diagnostic odds ratio of 11.10 (95%CI: 6.42-19.18), area under the curve of 0.78 (95%CI: 0.74-0.82). Meta-regression identified sample size and positive criteria algorithm as potential contributors to heterogeneity in sensitivity, although the associations were only of borderline statistical significance. Other covariables were not significantly associated with heterogeneity. CONCLUSION: Plasma mSEPT9 demonstrated high specificity and relatively low sensitivity in GC. The assay may be unsuitable for general population screening but showed promise as an adjunctive marker in high-risk patients. Heterogeneity and geographical concentration may influence the assessment of mSEPT9. PROTOCOL REGISTRATION: www.crd.york.ac.uk/prospero identifier is CRD420251140125.

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Journal
Biomarkers in Medicine
Published
2026-06-12
DOI
https://doi.org/10.1080/17520363.2026.2685066
Primary Topic
Epigenetics and DNA Methylation
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article
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article

Septin9 gene methylation in plasma for gastric cancer detection: a systematic review and meta-analysis

Jiaqi Kang, Shan He, Yuxing Wang, Ping Zhang
Biomarkers in Medicine
Epigenetics and DNA Methylation
article

Septin9 gene methylation in plasma for gastric cancer detection: a systematic review and meta-analysis

Jiaqi Kang, Shan He, Yuxing Wang, Ping Zhang
article en

Abstract

OBJECTIVE: To evaluate the plasma-based methylated Septin9 (mSEPT9) diagnostic accuracy for gastric cancer (GC) and analyze its performance across different subgroups. METHODS: Through comprehensive computer searching, we systematically collected clinical trials on the diagnostic efficacy of plasma mSEPT9 in GC. The search scope covered PubMed, Web of Science, the Cochrane Library, Embase, CNKI, WanFang Data and VIP databases from their establishments to 31 August 2025. Study quality was rigorously assessed with the assistance of Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). Meta-analysis via Stata 17.0 and Meta-Disc 1.4 was performed. RESULTS: This study included 9 articles containing 10 studies, encompassing 3,120 participants. Meta-analysis revealed a pooled sensitivity of 0.40 (95%CI: 0.34-0.47), specificity of 0.94 (95%CI: 0.91-0.96), diagnostic odds ratio of 11.10 (95%CI: 6.42-19.18), area under the curve of 0.78 (95%CI: 0.74-0.82). Meta-regression identified sample size and positive criteria algorithm as potential contributors to heterogeneity in sensitivity, although the associations were only of borderline statistical significance. Other covariables were not significantly associated with heterogeneity. CONCLUSION: Plasma mSEPT9 demonstrated high specificity and relatively low sensitivity in GC. The assay may be unsuitable for general population screening but showed promise as an adjunctive marker in high-risk patients. Heterogeneity and geographical concentration may influence the assessment of mSEPT9. PROTOCOL REGISTRATION: www.crd.york.ac.uk/prospero identifier is CRD420251140125.

Biomarkers in Medicine
Beijing University of Chinese Medicine (CN), Wangjing Hospital of China Academy of Chinese Medical Sciences (CN), China Academy of Chinese Medical Sciences (CN)
Openalex Percentile: Top 10%
Epigenetics and DNA Methylation
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