Abstract
BackgroundOvarian cancer (OC) is a gynecological oncology that has a poor prognosis and high mortality. This study is conducted to identify the key genes implicated in the prognosis of OC by bioinformatic analysis.MethodsGene expression data (including 568 primary OC tissues, 17 recurrent OC tissues, and 8 adjacent normal tissues) and the relevant clinical information of OC patients were downloaded from The Cancer Genome Atlas database. After data preprocessing, cluster analysis was conducted using the ConsensusClusterPlus package in R. Using the limma package in R, differential analysis was performed to identify feature genes. Based on Kaplan-Meier (KM) survival analysis, prognostic seed genes were selected from the feature genes. After key prognostic genes were further screened by cluster analysis and KM survival analysis, they were performed functional enrichment analysis and multivariate survival analysis. Using the survival package in R, cox regression analysis was conducted for the microarray data of GSE17260 to validate the key prognostic genes.ResultsA total of 3668 feature genes were obtained, among which 75 genes were identified as prognostic seed genes. Then, 25 key prognostic genes were screened, including AXL, FOS, KLF6, WDR77, DUSP1, GADD45B, and SLIT3. Especially, AXL and SLIT3 were enriched in ovulation cycle. Multivariate survival analysis showed that the key prognostic genes could effectively differentiate the samples and were significantly associated with prognosis. Additionally, GSE17260 confirmed that the key prognostic genes were associated with the prognosis of OC.ConclusionAXL, FOS, KLF6, WDR77, DUSP1, GADD45B, and SLIT3 might affect the prognosis of OC.
Highlights
Ovarian cancer (OC) is a gynecological oncology that has a poor prognosis and high mortality
Li et al declared that chemokine receptor 4 (CXCR4) plays a critical role in cisplatin-based chemotherapy for patients with epithelial ovarian cancer (EOC) and can be seen as a prognostic factor [5]
After trying different log2 fold change (FC) value for screening gene set, we found that |log2FC| > 0.7 was the most optimal threshold
Summary
Ovarian cancer (OC) is a gynecological oncology that has a poor prognosis and high mortality. Ovarian cancer (OC), which ranks seventh in incidence and eighth in mortality among tumors in women, is characterized by pelvic pain, bloating, loss of appetite, and abdominal swelling [1]. OC usually has a poor prognosis and high mortality, and most cases are diagnosed at advanced stages as there lacks effective detection means [4]. Li et al declared that chemokine receptor 4 (CXCR4) plays a critical role in cisplatin-based chemotherapy for patients with epithelial ovarian cancer (EOC) and can be seen as a prognostic factor [5]. Previous studies demonstrated that high Beclin 1 expression in protein level can be a prognostic factor of OC [8, 9]. Califano et al deemed that obesity evaluated by Body Mass Index combined with high mobility group A2
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