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可变剪接在卵巢癌中起独立预后因子的作用。

Alternative splicing acts as an independent prognosticator in ovarian carcinoma.

机构信息

School of Biology and Engineering, Guizhou Medical University, Guiyang, 550025, People's Republic of China.

Guiyang Maternal and Child Health Care Hospital, Guiyang Children's Hospital, Guiyang, 550025, People's Republic of China.

出版信息

Sci Rep. 2021 May 17;11(1):10413. doi: 10.1038/s41598-021-89778-0.

Abstract

Alternative splicing (AS) events associated with oncogenic processes present anomalous perturbations in many cancers, including ovarian carcinoma. There are no reliable features to predict survival outcomes for ovarian cancer patients. In this study, comprehensive profiling of AS events was conducted by integrating AS data and clinical information of ovarian serous cystadenocarcinoma (OV). Survival-related AS events were identified by Univariate Cox regression analysis. Then, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were used to construct the prognostic signatures within each AS type. Furthermore, we established a splicing-related network to reveal the potential regulatory mechanisms between splicing factors and candidate AS events. A total of 730 AS events were identified as survival-associated splicing events, and the final prognostic signature based on all seven types of AS events could serve as an independent prognostic indicator and had powerful efficiency in distinguishing patient outcomes. In addition, survival-related AS events might be involved in tumor-related pathways including base excision repair and pyrimidine metabolism pathways, and some splicing factors might be correlated with prognosis-related AS events, including SPEN, SF3B5, RNPC3, LUC7L3, SRSF11 and PRPF38B. Our study constructs an independent prognostic signature for predicting ovarian cancer patients' survival outcome and contributes to elucidating the underlying mechanism of AS in tumor development.

摘要

剪接事件(AS)与致癌过程相关,在许多癌症中包括卵巢癌都会出现异常的扰动。目前还没有可靠的特征可以预测卵巢癌患者的生存结果。在这项研究中,通过整合卵巢浆液性囊腺癌(OV)的 AS 数据和临床信息,对 AS 事件进行了全面分析。通过单变量 Cox 回归分析确定了与生存相关的 AS 事件。然后,使用最小绝对收缩和选择算子(LASSO)和多变量 Cox 回归分析在每种 AS 类型内构建预后特征。此外,我们建立了一个剪接相关网络,以揭示剪接因子和候选 AS 事件之间的潜在调控机制。确定了 730 个与生存相关的 AS 事件作为剪接相关事件,基于所有七种 AS 类型的最终预后特征可以作为独立的预后指标,并且在区分患者结局方面具有强大的效率。此外,与生存相关的 AS 事件可能与肿瘤相关途径有关,包括碱基切除修复和嘧啶代谢途径,一些剪接因子可能与预后相关的 AS 事件相关,包括 SPEN、SF3B5、RNPC3、LUC7L3、SRSF11 和 PRPF38B。我们的研究构建了一个独立的预后特征,用于预测卵巢癌患者的生存结果,并有助于阐明 AS 在肿瘤发展中的潜在机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b82/8129203/5eeafa873550/41598_2021_89778_Fig1_HTML.jpg

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