Evidence map›Paper›PMID 41765894›Full record

ArticleJournal of ovarian research2026

IgG Gal-ratio, a promising serum biomarker for detecting ovarian cancer in as early as stage I disease.

Yi-Sheng Wang, Xiao-Ning Chen, Xiao-Yan Zhang, Yue-Fei Wang, Shi-Fang Ren, Cong-Jian Xu

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Article in Journal of ovarian research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Yi-Sheng Wang *Obstetrics and Gynecology Hospital of Fudan University, Shanghai, P.R. China.
Xiao-Ning Chen *Key Laboratory of Glycoconjugate Research Ministry of Public Health, Shanghai, P.R. China.
Xiao-Yan ZhangObstetrics and Gynecology Hospital of Fudan University, Shanghai, P.R. China.
Yue-Fei WangObstetrics and Gynecology Hospital of Fudan University, Shanghai, P.R. China.
Shi-Fang RenKey Laboratory of Glycoconjugate Research Ministry of Public Health, Shanghai, P.R. China. renshifang@fudan.edu.cn.
Cong-Jian Xu *Obstetrics and Gynecology Hospital of Fudan University, Shanghai, P.R. China. xucj@hotmail.com.

Funding

National Key Research and Development Program of China 2016YFC1303101Shanghai Science and Technology Development Program 15DZ1941002
6 · The paper itself

Abstract

backgroundEarly detection of epithelial ovarian cancer (EOC) is hampered by the absence of an ideal serum biomarker. This study aimed to further validate the utility of IgG Gal-ratio in pre-operative diagnosis of ovarian cancer.

methodsSerum samples were collected from patients presenting with pelvic mass or elevated serum CA125 levels before surgery at the Obstetrics & Gynecology Hospital of Fudan University between June 2017 and December 2019. IgG was purified from these samples and incubated with PNGase F to release IgG N-glycans. Oligosaccharides from each sample were analyzed and quantified using MALDI-QIT-TOF MS and tandem MS. The IgG Gal-ratio was calculated as G0/ (G1 + G2 × 2), where G0, G1, and G2 represent the intensities of biantennary, core-fucosylated structures with zero, one, and two galactose residues, respectively. The levels of IgG Gal-ratio were compared among patients with EOC, ovarian borderline tumors (BOT), and benign gynecological conditions using Student’s t-test. Receiver operating characteristic curve were plotted, and sensitivity and specificity were calculated to assess the diagnostic power of IgG Gal-ratio for ovarian cancer.

resultsA total of 113 primary EOC patients, 13 BOT patients, and 728 patients with benign gynecological conditions (including ovarian cysts, endometrioma, teratoma, pelvic inflammatory diseases, adenomyoma, uterine myoma, and pelvic tuberculosis et, al.) were included in this study. IgG Gal-ratio was significantly higher in EOC patients compared to those with BOT or benign conditions (0.69 ± 0.41 vs. 0.38 ± 0.17 vs. 0.30 ± 0.13, p < 0.001). A similar trend was observed in serous BOT (n = 9) compared to benign conditions (0.44 ± 0.17 vs. 0.30 ± 0.13, p = 0.003). IgG Gal-ratio demonstrated comparable performance to CA125 in differentiating ovarian cancer from non-malignant gynecological conditions (AUC = 0.871 vs. 0.872). For early detection, IgG Gal-ratio outperformed CA125 in detecting stage I EOC patients (AUC = 0.835 vs. 0.761). Combination of these two markers (Gal-CA125 = IgG Gal-ratio × CA125) provide higher specificity in detecting stage I ovarian cancer than CA125 alone (59.9% vs. 32.9%) at a fixed sensitivity of 90.0%.

conclusionThe IgG Gal-ratio is a robust serum biomarker for discriminating EOC patients from those with BOT or benign gynecological conditions, offering a promising tool for early detection and diagnosis.

Indexed as

Biomarkers, TumorImmunoglobulin GOvarian NeoplasmsAdultAgedCA-125 AntigenEarly Detection of CancerFemaleHumansMiddle AgedNeoplasm StagingROC CurveBiomarkers, TumorCA-125 AntigenImmunoglobulin GAgalactosylated IgGIgG Gal-ratioOvarian cancerPre-operative diagnosisSerum biomarker

Identifiers

PMID41765894
PMCPMC13059560

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.