Huisheng Liang1,2, Yuquan Bai3, Hailong Wang2,4, Xiangjun Yang1. 1. Department of Gynecology and Obstetrics, The Affiliated Zhongshan Hospital of Xiamen University, Xiamen, China. 2. Organ Transplantation Institute, School of Medicine, Xiamen University, Xiamen, China. 3. Department of Thoracic Surgery, West China Hospital of Sichuan University, Chengdu, China. 4. Department of Basic Medicine, School of Medicine, Xiamen University, Xiamen, China.
Abstract
BACKGROUND: Ovarian cancer (OC), one of the most prevalent gynecological malignancies, is characterized by late detection and dismal prognosis. Recent studies show that long non-coding RNAs (lncRNAs) in competitive endogenous RNA (ceRNA) networks influence immune infiltration and cancer prognosis. However, the function of lncRNA in OC immune infiltration and prognosis remains unclear. METHODS: Transcriptomes of 378 OC samples and clinical data were retrieved from the TCGA repository. Modules related to immune cells were identified using weighted gene co-expression network analysis (WGCNA). Functional enrichment analysis and survival analysis were then performed for the identification of immune-related lncRNAs in the brown module using Cox regression model. Finally, a ceRNA network was constructed by using the lncRNAs and mRNAs from the brown module. RESULTS: We found lncRNAs and mRNAs in the brown module to be significantly associated with immune cells in OC and identified 4 lncRNAs as potential OC prognostic markers. We further established that lncRNAs in the ceRNA network influence OC immune infiltration and prognosis by regulating miRNA, ultimately modulating mRNA levels. CONCLUSION: We have identified 4 lncRNAs as independent immune prognostic factors for OC. Furthermore, our findings offer novel insight into lncRNAs as OC immune and prognostic biomarkers.
BACKGROUND: Ovarian cancer (OC), one of the most prevalent gynecological malignancies, is characterized by late detection and dismal prognosis. Recent studies show that long non-coding RNAs (lncRNAs) in competitive endogenous RNA (ceRNA) networks influence immune infiltration and cancer prognosis. However, the function of lncRNA in OC immune infiltration and prognosis remains unclear. METHODS: Transcriptomes of 378 OC samples and clinical data were retrieved from the TCGA repository. Modules related to immune cells were identified using weighted gene co-expression network analysis (WGCNA). Functional enrichment analysis and survival analysis were then performed for the identification of immune-related lncRNAs in the brown module using Cox regression model. Finally, a ceRNA network was constructed by using the lncRNAs and mRNAs from the brown module. RESULTS: We found lncRNAs and mRNAs in the brown module to be significantly associated with immune cells in OC and identified 4 lncRNAs as potential OC prognostic markers. We further established that lncRNAs in the ceRNA network influence OC immune infiltration and prognosis by regulating miRNA, ultimately modulating mRNA levels. CONCLUSION: We have identified 4 lncRNAs as independent immune prognostic factors for OC. Furthermore, our findings offer novel insight into lncRNAs as OC immune and prognostic biomarkers.
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