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基于免疫相关基因的系统构建和验证模型预测卵巢癌预后。

Systematic Construction and Validation of an Immune-Related Gene-Based Model to Predict Prognosis for Ovarian Cancer.

机构信息

Obstetrics and Gynecology Hospital of Fudan University, 200082 Shanghai, China.

Shanghai Key Laboratory of Female Reproductive Endocrine-Related Diseases, Shanghai, China 200082.

出版信息

Biomed Res Int. 2022 Apr 21;2022:7356992. doi: 10.1155/2022/7356992. eCollection 2022.

DOI:10.1155/2022/7356992
PMID:35496047
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9050317/
Abstract

Ovarian cancer (OC) is a malignancy with poor prognosis, stubborn resistance, and frequent recurrence. Recently, it has been widely recognized that immune-related genes (IRGs) have demonstrated their indispensable importance in the occurrence and progression of OC. Given this, this study aimed to identify IRGs with predictive value and build a prognostic model for a more accurate assessment. First, we obtained transcriptome and clinical information of ovarian samples from both TCGA and GTEx databases. After integration, we figured out 10 genes as immune-related prognostic genes (IRPGs) by performing the univariate Cox regression analysis. Subsequently, we established a TF-associated network to investigate its internal mechanism. The prognosis model consisting of 5 IRPGs was constructed later by lasso regression analysis. The comparison of the score with the clinical factors validated its independence and superiority in OC's prognosis. Moreover, the association between the signature and immune cell infiltration demonstrated its ability to image the immune situation of the tumor microenvironment. Finally, the reliability of the risk model was confirmed by the GEO cohort. Together, our study has constructed an independent prognostic model for OC, which may deepen the understanding of the immune microenvironment and help present novel biomarkers or ideas for targeted therapy.

摘要

卵巢癌（OC）是一种预后不良、顽固耐药和频繁复发的恶性肿瘤。最近，人们广泛认识到免疫相关基因（IRGs）在 OC 的发生和发展中具有不可或缺的重要性。有鉴于此，本研究旨在鉴定具有预测价值的 IRGs，并构建一个预后模型，以更准确地评估 OC。首先，我们从 TCGA 和 GTEx 数据库中获取了卵巢样本的转录组和临床信息。整合后，我们通过单因素 Cox 回归分析确定了 10 个免疫相关预后基因（IRPGs）。随后，我们建立了一个 TF 相关网络来研究其内在机制。然后通过lasso 回归分析构建了由 5 个 IRPGs 组成的预后模型。与临床因素的评分比较验证了其在 OC 预后中的独立性和优越性。此外，该特征与免疫细胞浸润的相关性表明其能够对肿瘤微环境的免疫情况进行成像。最后，GEO 队列验证了风险模型的可靠性。总之，本研究构建了一个 OC 的独立预后模型，这可能加深对免疫微环境的理解，并为靶向治疗提供新的生物标志物或思路。

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2
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Biosci Rep. 2021 Jan 29;41(1). doi: 10.1042/BSR20202564.
3
Prognostic Model of Colorectal Cancer Constructed by Eight Immune-Related Genes.
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4
Immunotherapy for Ovarian Cancer: Adjuvant, Combination, and Neoadjuvant.卵巢癌的免疫治疗：辅助、联合和新辅助治疗。
Front Immunol. 2020 Oct 6;11:577869. doi: 10.3389/fimmu.2020.577869. eCollection 2020.
5
Identification of an immune-related gene-based signature to predict prognosis of patients with gastric cancer.基于免疫相关基因的特征识别以预测胃癌患者的预后
World J Gastrointest Oncol. 2020 Aug 15;12(8):857-876. doi: 10.4251/wjgo.v12.i8.857.
6
Identification of the prognostic value of immune gene signature and infiltrating immune cells for esophageal cancer patients.鉴定免疫基因特征和浸润免疫细胞对食管癌患者的预后价值。
Int Immunopharmacol. 2020 Oct;87:106795. doi: 10.1016/j.intimp.2020.106795. Epub 2020 Jul 21.
7
Ovarian Cancer: An Overview.卵巢癌概述。
Radiol Technol. 2020 Jul;91(6):561-575.
8
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J Transl Med. 2020 Feb 11;18(1):67. doi: 10.1186/s12967-020-02255-6.
9
Altered expression profile of circular RNAs in conjunctival melanoma.结膜黑色素瘤中环状 RNA 的表达谱改变。
Epigenomics. 2019 May;11(7):787-804. doi: 10.2217/epi-2019-0029. Epub 2019 Mar 20.
10
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Cells. 2019 Feb 19;8(2):177. doi: 10.3390/cells8020177.