Increasing evidence suggests that aberrant alternative splicing (AS) events are associated with progression of cancer. This study evaluated the prognostic value and clarify the role of AS events in cervical cancer (CC).

Based on RNA-seq AS event data and clinical information of CC patients in The Cancer Genome Atlas (TCGA) database, we sought to identify prognosis-related AS events in this setting. We selected several survival-associated AS events to construct a prognostic predictor for CC through the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression. Moreover, Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses were performed on genes with prognosis-related AS events and constructed an AS-splicing factors (SFs) regulatory network.

2770 AS events were significantly correlated with overall survival (OS). The area under the curve (AUC) values of receiver-operator characteristic curve (ROC) for the final prognostic predictor were 0.926, 0.946 and 0.902 at 3, 5, and 10 years, respectively. These values indicated efficiency in prognostic risk stratification for patients with CC. The final prognostic predictor was an independent predictor of OS (HR: 1.24; 95% CI: 1.020–1.504; P < 0.05). The AS-SFs correlation network may reveal an underlying regulatory mechanism of AS events.

AS events are essential participants in the prognosis of CC and hold great potentials for the prognostic stratification and development of treatment strategy.

越来越多的证据表明异常可变剪接 (AS) 事件与癌症的进展有关。本研究评估了预后价值并阐明了 AS 事件在宫颈癌 (CC) 中的作用。

基于癌症基因组图谱 (TCGA) 数据库中 CC 患者的 RNA-seq AS 事件数据和临床信息，我们试图在这种情况下确定与预后相关的 AS 事件。我们通过最小绝对收缩和选择算子 (LASSO) 和多变量 Cox 回归选择了几个与生存相关的 AS 事件来构建 CC 的预后预测因子。此外，Kyoto Encyclopedia of Genes and Genomes 和 Gene Ontology 对具有预后相关 AS 事件的基因进行了分析，并构建了一个 AS 剪接因子 (SFs) 调控网络。

2770 个 AS 事件与总生存期 (OS) 显着相关。在 3 年、5 年和 10 年，最终预后预测指标的受试者-操作者特征曲线 (ROC) 的曲线下面积 (AUC) 值分别为 0.926、0.946 和 0.902。这些值表明 CC 患者预后风险分层的有效性。最终的预后预测因子是 OS 的独立预测因子（HR：1.24；95% CI：1.020–1.504；磷< 0.05)。AS-SFs 相关网络可能揭示 AS 事件的潜在调控机制。

AS 事件是 CC 预后的重要参与者，对于预后分层和治疗策略的制定具有巨大的潜力。