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鉴定剪接变异标志作为结肠癌的一个独立因素。

Identification of an alternative splicing signature as an independent factor in colon cancer.

机构信息

Department of Orthopedic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.

Department of Pathology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.

出版信息

BMC Cancer. 2020 Sep 22;20(1):904. doi: 10.1186/s12885-020-07419-7.

Abstract

BACKGROUND

Colon cancer is a common malignant tumor with a poor prognosis. Abnormal alternative splicing (AS) events played a part in the occurrence and metastasis of the tumor. We aimed to develop a survival-associated AS signature in colon cancer.

METHODS

The Percent Spliced In values of AS events were available in The Cancer Genome Atlas (TCGA) SpliceSeq database. Univariate Cox analysis was carried out to detect the prognosis-related AS events. We created a predictive model on account of the survival-associated AS events, which was further validated with a training-testing group design. Kaplan-Meier analysis was applied to assess patient survival. The area under curve (AUC) of receiver operating characteristic (ROC) was performed to evaluate the predictive values of this model. Meanwhile, the clinical relevance of the signature and its regulatory relationship with splicing factors (SFs) were also evaluated.

RESULTS

In total, 2132 survival-related AS events were identified from colon cancer samples. We developed an eleven-AS signature, in which the 5-year AUC value was 0.911. Meanwhile, the AUC values at five years were 0.782 and 0.855 in the testing and entire cohort, respectively. Multivariate Cox regression displayed that the T category and the risk score of the signature were independent risk factors of colon cancer survival. Also, we constructed an SFs-AS network based on 11 SFs and 48 AS events.

CONCLUSIONS

We identified an eleven-AS signature of colon cancer. This signature could be treated as an independent prognostic factor.

摘要

背景

结肠癌是一种预后较差的常见恶性肿瘤。异常的选择性剪接(AS)事件在肿瘤的发生和转移中起作用。我们旨在开发一种与结肠癌生存相关的 AS 特征。

方法

TCGA SpliceSeq 数据库中提供了 AS 事件的百分比拼接值。进行单变量 Cox 分析以检测与预后相关的 AS 事件。我们基于与生存相关的 AS 事件创建了一个预测模型,并采用训练-测试组设计进行了进一步验证。Kaplan-Meier 分析用于评估患者的生存情况。接收者操作特征(ROC)曲线下面积(AUC)用于评估该模型的预测值。同时,还评估了该特征的临床相关性及其与剪接因子(SFs)的调控关系。

结果

共从结肠癌样本中鉴定出 2132 个与生存相关的 AS 事件。我们开发了一个由 11 个 AS 组成的特征,其 5 年 AUC 值为 0.911。同时,在测试集和整个队列中,该特征的 AUC 值在 5 年内分别为 0.782 和 0.855。多变量 Cox 回归显示,T 分期和特征的风险评分是结肠癌生存的独立危险因素。此外,我们还基于 11 个 SFs 和 48 个 AS 事件构建了一个 SFs-AS 网络。

结论

我们确定了结肠癌的 11 个 AS 特征。该特征可以作为独立的预后因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/152d/7510085/390e2fbe480d/12885_2020_7419_Fig1_HTML.jpg

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