Abstract
High-grade serous ovarian cancer (HGSOC) is the biggest cause of gynecological cancer-related mortality because of its extremely metastatic nature. This study aimed to explore and evaluate the characteristics of candidate factors associated with the metastasis and progression of HGSOC. Transcriptomic data of HGSOC patients' samples collected from primary tumors and matched omental metastatic tumors were obtained from three independent studies in the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were selected to evaluate the effects on the prognosis and progression of ovarian cancer using data from The Cancer Genome Atlas (TCGA) database. Hub genes' immune landscapes were estimated by the Tumor Immune Estimation Resource (TIMER) database. Finally, using 25 HGSOC patients' cancer tissues and 10 normal fallopian tube tissues, immunohistochemistry (IHC) was performed to quantify the expression levels of hub genes associated with International Federation of Gynecology and Obstetrics (FIGO) stages. Fourteen DEGs, ADIPOQ , ALPK2 , BARX1 , CD37 , CNR2 , COL5A3 , FABP4 , FAP , GPR68 , ITGBL1 , MOXD1 , PODNL1 , SFRP2 , and TRAF3IP3 , were upregulated in metastatic tumors in every database while CADPS , GATA4 , STAR , and TSPAN8 were downregulated. ALPK2 , FAP , SFRP2 , GATA4 , STAR , and TSPAN8 were selected as hub genes significantly associated with survival and recurrence. All hub genes were correlated with tumor microenvironment infiltration, especially cancer-associated fibroblasts and natural killer (NK) cells. Furthermore, the expression of FAP and SFRP2 was positively correlated with the International Federation of Gynecology and Obstetrics (FIGO) stage, and their increased protein expression levels in metastatic samples compared with primary tumor samples and normal tissues were confirmed by IHC ( P = 0.0002 and P = 0.0001, respectively). This study describes screening for DEGs in HGSOC primary tumors and matched metastasis tumors using integrated bioinformatics analyses. We identified six hub genes that were correlated with the progression of HGSOC, particularly FAP and SFRP2 , which might provide effective targets to predict prognosis and provide novel insights into individual therapeutic strategies for HGSOC.
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