STAT1 and IL-7 as potential diagnostic biomarkers for distinguishing high-grade from low-grade serous ovarian cancer: a multi-cohort analysis.
High-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.
Transcriptome 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.
Seventy-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).
STAT1 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.
Transcriptome 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.
Seventy-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).
STAT1 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.
Authors
Wu Wu, Zhuang Zhuang, Zhan Zhan, Chen Chen, Xie Xie, Zhou Zhou, Huang Huang, Sheng Sheng, Wang Wang, Chen Chen, Wu Wu, Ke Ke
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