Suppr超能文献

可变剪接:卵巢癌的一个新治疗靶点。

Alternative Splicing: A New Therapeutic Target for Ovarian Cancer.

机构信息

89674Zhongnan Hospital of Wuhan University, Wuhan, China.

Hubei Key Laboratory of Tumor Biological Behaviors, Wuhan, China.

出版信息

Technol Cancer Res Treat. 2022 Jan-Dec;21:15330338211067911. doi: 10.1177/15330338211067911.

Abstract

Increasing evidences have shown that abnormal alternative splicing (AS) events are closely related to the prognosis of various tumors. However, the role of AS in ovarian cancer (OV) is poorly understood. This study aims to explore the correlation between AS and the prognosis of OV and establish a prognostic model for OV. We downloaded the RNA-seq data of OV from The Cancer Genome Atlas databases and assessed cancer-specific AS through the SpliceSeq software. Then systemically investigated the overall survival (OS)-related AS and splicing factors (SFs) by bioinformatics analysis. The nomogram was established based on the clinical information, and the clinical practicability of the nomogram was verified through the calibration curve. Finally, a splicing correlation network was constructed to reveal the relationship between OS-related AS and SFs. A total of 48,049 AS events were detected from 10,582 genes, of which 1523 were significantly associated with OS. The area under the curve of the final prediction model was 0.785, 0.681, and 0.781 in 1, 3, and 5 years, respectively. Moreover, the nomogram showed high calibration and discrimination in OV patients. Spearman correlation analysis was used to determine 8 SFs significantly related to survival, including major facilitator superfamily domain containing 11, synaptotagmin binding cytoplasmic RNA interacting protein, DEAH-box helicase 35, CWC15, integrator complex subunit 1, LUC7 like 2, cell cycle and apoptosis regulator 1, and heterogeneous nuclear ribonucleoprotein A2/B1. This study provides a prognostic model related to AS in OV, and constructs an AS-clinicopathological nomogram, which provides the possibility to predict the long-term prognosis of OV patients. We have explored the wealth of RNA splicing networks and regulation patterns related to the prognosis of OV, which provides a large number of biomarkers and potential targets for the treatment of OV. Put forward the potential possibility of interfering with the AS of OV in the comprehensive treatment of OV.

摘要

越来越多的证据表明,异常的选择性剪接 (AS) 事件与各种肿瘤的预后密切相关。然而,AS 在卵巢癌 (OV) 中的作用仍知之甚少。本研究旨在探讨 AS 与 OV 预后的相关性,并建立 OV 的预后模型。 我们从癌症基因组图谱数据库中下载了 OV 的 RNA-seq 数据,并通过 SpliceSeq 软件评估了癌症特异性 AS。然后通过生物信息学分析系统地研究了与总体生存 (OS) 相关的 AS 和剪接因子 (SFs)。基于临床信息建立了列线图,并通过校准曲线验证了列线图的临床实用性。最后,构建了一个剪接相关网络,以揭示 OS 相关 AS 与 SFs 之间的关系。 从 10582 个基因中检测到 48049 个 AS 事件,其中 1523 个与 OS 显著相关。最终预测模型的曲线下面积在 1、3 和 5 年内分别为 0.785、0.681 和 0.781。此外,该列线图在 OV 患者中显示出较高的校准和区分度。Spearman 相关性分析确定了与生存显著相关的 8 个 SFs,包括主要易化因子超家族结构域 11、突触结合细胞质 RNA 相互作用蛋白、DEAH 盒解旋酶 35、CWC15、整合复合物亚基 1、LUC7 样 2、细胞周期和凋亡调节剂 1 和异质核核糖核蛋白 A2/B1。 本研究提供了一个与 OV 中 AS 相关的预后模型,并构建了一个 AS-临床病理列线图,为预测 OV 患者的长期预后提供了可能。我们已经探索了与 OV 预后相关的丰富的 RNA 剪接网络和调控模式,为 OV 的治疗提供了大量的生物标志物和潜在的靶点。在 OV 的综合治疗中提出了干扰 OV 的 AS 的潜在可能性。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验