Public Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.
J Cell Mol Med. 2023 Sep;27(18):2684-2700. doi: 10.1111/jcmm.17849. Epub 2023 Aug 9.
Splicing factors (SFs) are proteins that control the alternative splicing (AS) of RNAs, which have been recognized as new cancer hallmarks. Their dysregulation has been found to be involved in many biological processes of cancer, such as carcinogenesis, proliferation, metastasis and senescence. Dysregulation of SFs has been demonstrated to contribute to the progression of prostate cancer (PCa). However, a comprehensive analysis of the prognosis value of SFs in PCa is limited. In this work, we systematically analysed 393 SFs to deeply characterize the expression patterns, clinical relevance and biological functions of SFs in PCa. We identified 53 survival-related SFs that can stratify PCa into two de nove molecular subtypes with distinct mRNA expression and AS-event expression patterns and displayed significant differences in pathway activity and clinical outcomes. An SF-based classifier was established using LASSO-COX regression with six key SFs (BCAS1, LSM3, DHX16, NOVA2, RBM47 and SNRPN), which showed promising prognosis-prediction performance with a receiver operating characteristic (ROC) >0.700 in both the training and testing datasets, as well as in three external PCa cohorts (DKFZ, GSE70769 and GSE21035). CRISPR/CAS9 screening data and cell-level functional analysis suggested that LSM3 and DHX16 are essential factors for the proliferation and cell cycle progression in PCa cells. This study proposes that SFs and AS events are potential multidimensional biomarkers for the diagnosis, prognosis and treatment of PCa.
剪接因子（SFs）是控制 RNA 可变剪接（AS）的蛋白质，已被认为是癌症的新标志。它们的失调已被发现参与癌症的许多生物学过程，如癌变、增殖、转移和衰老。SFs 的失调已被证明有助于前列腺癌（PCa）的进展。然而，SFs 在 PCa 中的预后价值的综合分析是有限的。在这项工作中，我们系统地分析了 393 个 SFs，以深入描述 SFs 在 PCa 中的表达模式、临床相关性和生物学功能。我们确定了 53 个与生存相关的 SFs，这些 SFs可以将 PCa 分为两个新的分子亚型，具有不同的 mRNA 表达和 AS 事件表达模式，并且在途径活性和临床结果方面显示出显著差异。我们使用 LASSO-COX 回归和六个关键 SFs（BCAS1、LSM3、DHX16、NOVA2、RBM47 和 SNRPN）建立了基于 SF 的分类器，该分类器在训练和测试数据集以及三个外部 PCa 队列（DKFZ、GSE70769 和 GSE21035）中具有有前途的预后预测性能，ROC > 0.700。CRISPR/CAS9 筛选数据和细胞水平功能分析表明，LSM3 和 DHX16 是 PCa 细胞增殖和细胞周期进展的必需因素。这项研究表明，SFs 和 AS 事件是 PCa 诊断、预后和治疗的潜在多维生物标志物。
