Identification and Analysis of Gene Biomarkers for Ovarian Cancer

Area of Science:

• Oncology
• Immunology
• Genomics

Background:

• Ovarian cancer (OC) lacks reliable early diagnostic markers.
• Understanding the tumor microenvironment, including immune cell infiltration, is crucial for pathogenesis insights.

Purpose of the Study:

• To identify novel diagnostic biomarkers for ovarian cancer.
• To investigate the role of immune cell infiltration in ovarian cancer development.

Main Methods:

• Combined gene expression datasets (GSE27651, GSE26712, GSE146553) from the Gene Expression Omnibus (GEO) database.
• Utilized support vector machine, recursive feature elimination, and least absolute shrinkage and selection operator regression for biomarker identification.
• Employed immunohistochemistry for validation and CIBERSORT algorithm for immune cell infiltration analysis.

Main Results:

• Identified CLEC4M, PFKP, and SCRIB as potential diagnostic biomarkers for OC with high diagnostic accuracy (AUC > 0.89).
• Observed altered immune cell infiltration in OC, including increased follicular helper dendritic cells and decreased M2 macrophages, neutrophils, activated NK cells, and T cells.
• Found significant correlations between CLEC4M, PFKP, SCRIB and specific immune cell populations.

Conclusions:

• CLEC4M, PFKP, and SCRIB are validated as promising diagnostic biomarkers for ovarian cancer.
• The identified biomarkers and their correlations with immune cells offer potential for future research into OC mechanisms and therapeutic strategies.