Hepatoma-Derived Growth Factor and Non-Coding Rna Network in Ovarian Cancer Patients Publisher



R Ganjali REZA ; S Nasiri Zeidi SETAREH ; N Zamani NARGES ; Z Shakerardekani ZEINAB ; M Elahimanesh MOHAMMAD ; N Hosseinkhan NAZANIN ; M Nourbakhsh MITRA
Source: Biochemistry and Biophysics Reports Published:2025

Abstract

Background: Ovarian cancer (OC) remains the most lethal gynecologic malignancy due to late diagnosis and limited effective biomarkers. Hepatoma-derived growth factor (HDGF) has emerged as an oncogene implicated in tumor progression, yet its regulation and clinical potential in OC remains underexplored. Recent evidence suggests that long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) may modulate oncogenic pathways through competing endogenous RNA (ceRNA) networks. Methods and results: Fifty ovarian cancer and fifty normal ovarian tissue samples were analyzed for HDGF, miR-345-5p, and LINC00839 expression using qRT-PCR. Bioinformatic tools were employed to predict RNA-RNA interactions and reconstruct a ceRNA network. Statistical analyses examined expression correlations and diagnostic performance via ROC curve. HDGF and LINC00839 were significantly upregulated, while miR-345-5p was downregulated in OC tissues (p < 0.001). HDGF expression correlated positively with LINC00839 (r = 0.70) and inversely with miR-345-5p (r = −0.58), suggesting a regulatory axis where LINC00839 sponges miR-345-5p to derepress HDGF. Elevated HDGF levels were associated with larger tumor size, advanced FIGO stage, and metastasis. ROC analysis revealed that HDGF serum level (AUC = 0.88) has promising diagnostic potential, albeit lower than CA-125 and HE4. Conclusion: Our study highlights the LINC00839–miR-345-5p–HDGF axis as a key regulatory network in ovarian cancer. HDGF may serve as a clinically relevant biomarker for disease progression, while LINC00839 and miR-345-5p represent promising therapeutic targets. These findings provide a foundation for future investigations into ceRNA-based diagnostics and treatments in OC. © 2025 Elsevier B.V., All rights reserved.