This cohort study utilized transcriptome RNA-seq data from the GEO database (GSE27651, GSE126132), including 55 patients with high-grade serous ovarian carcinoma (HGSOC) and 13 with low-grade serous ovarian carcinoma (LGSOC) in an independent merged cohort. The analysis compared LGSOC versus HGSOC to evaluate the diagnostic performance of STAT1 and IL-7, with secondary outcomes assessing correlations with tumor-infiltrating immune cells and protein expression via immunohistochemistry (IHC). Follow-up, intervention or exposure, and safety data were not reported.
In the train group, STAT1 achieved an AUC of 0.908 and IL-7 an AUC of 0.842 for diagnostic performance. In the independent merged cohort, STAT1 had an AUC of 0.703 (95% CI: 0.517–0.889) and IL-7 an AUC of 0.706 (95% CI: 0.501–0.912). Protein expression analysis via IHC showed significantly higher STAT1 expression in HGSOC tissues (P < 0.05) and lower IL-7 expression (P < 0.05). Correlations included a strong positive correlation between STAT1 expression and M1 macrophages (rho = 0.688, q = 9.9×10^-8) and a negative correlation trend for IL-7 with neutrophils (rho = –0.372, raw P = 0.0048, q = 0.100).
Safety and tolerability were not reported. Key limitations include that clinical utility—particularly in multi-gene combinations—requires prospective validation. The study design is observational, so causality cannot be inferred. In practice, STAT1 and IL-7 may serve as ancillary diagnostic biomarkers in histologically ambiguous cases, but their use should be approached cautiously until further validation.
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BackgroundHigh-Grade Serous Ovarian Carcinoma (HGSOC) and Low-Grade Serous Ovarian Carcinoma (LGSOC) are distinct subtypes of epithelial ovarian cancer with significant differences in pathogenesis and prognosis, posing challenges for precise diagnosis. Identifying reliable biomarkers is crucial for improving differential diagnosis and clinical management.MethodsTranscriptome RNA-seq data of HGSOC and LGSOC were obtained from the GEO database (GSE27651, GSE126132). Differentially expressed immune-related genes (DIRGs) were identified. Functional enrichment analysis and protein-protein interaction (PPI) network construction were performed. The Least Absolute Shrinkage and Selection Operator (LASSO) regression and multiple Support Vector Machine Recursive Feature Elimination (mSVM-RFE) algorithms were used to select predictive genes. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curves, and a nomogram was developed. Findings were validated in an independent dataset and via immunohistochemistry (IHC). The CIBERSORT algorithm assessed correlations between key DIRGs and tumor-infiltrating immune cells, with false discovery rate (FDR) correction applied for multiple testing.ResultsSeventy-one DIRGs were identified in HGSOC versus LGSOC, predominantly enriched in cytokine-mediated signaling, cytokine-cytokine receptor interaction, and JAK-STAT pathways. STAT1 and IL-7 were selected as diagnostic biomarkers, with area under the curve (AUC) values of 0.908 and 0.842 in the train group. Respectively, validation in an independent merged cohort (GSE14001, GSE73168, GSE146965; 55 HGSOC, 13 LGSOC) yielded AUCs of 0.703 (95% CI: 0.517–0.889) for STAT1 and 0.706 (95% CI: 0.501–0.912) for IL-7. IHC confirmed significantly higher STAT1 and lower IL-7 protein expression in HGSOC tissues (P < 0.05). Immune microenvironment analysis revealed that HGSOC exhibited significantly higher fractions of naïve B cells, M2 macrophages, and neutrophils, and lower fractions of resting memory CD4+ T cells and eosinophils after FDR correction (all q < 0.05). STAT1 expression was strongly positively correlated with M1 macrophages (ρ = 0.688, q = 9.9×10-8), and showed correlation trends with other immune cell types that did not remain significant after FDR correction. IL-7 expression exhibited a negative correlation trend with neutrophils (ρ = –0.372, raw P = 0.0048, q = 0.100).ConclusionSTAT1 and IL-7 are consistently differentially expressed between HGSOC and LGSOC and may serve as ancillary diagnostic biomarkers in histologically ambiguous cases. However, their clinical utility—particularly in multi-gene combinations—requires prospective validation.