Splicing factors (SFs) are the major RNA-binding proteins (RBPs) and key molecules that regulate the splicing of mRNA molecules through binding to mRNAs. The expression of splicing factors is frequently deregulated in different cancer types, causing the generation of oncogenic proteins involved in cancer hallmarks. In this study, we investigated the genes that encode RNA-binding proteins and identified potential splicing factors that contribute to the aberrant splicing applying a random forest classification model. The result suggested 56 splicing factors were related to the prognosis of 13 cancers, two SF complexes in liver hepatocellular carcinoma, and one SF complex in esophageal carcinoma. Further systematic bioinformatics studies on these cancer prognostic splicing factors and their related alternative splicing events revealed the potential regulations in a cancer-specific manner. Our analysis found high ILF2-ILF3 expression correlates with poor prognosis in LIHC through alternative splicing. These findings emphasize the importance of SFs as potential indicators for prognosis or targets for therapeutic interventions. Their roles in cancer exhibit complexity and are contingent upon the specific context in which they operate. This recognition further underscores the need for a comprehensive understanding and exploration of the role of SFs in different types of cancer, paving the way for their potential utilization in prognostic assessments and the development of targeted therapies.

中文翻译：

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使用机器学习方法研究癌症的预后剪接因素

剪接因子 (SF) 是主要的 RNA 结合蛋白 (RBP) 和通过与 mRNA 结合来调节 mRNA 分子剪接的关键分子。剪接因子的表达在不同的癌症类型中经常失调，导致与癌症标志相关的致癌蛋白的产生。在这项研究中，我们研究了编码 RNA 结合蛋白的基因，并应用随机森林分类模型识别了导致异常剪接的潜在剪接因素。结果表明，56个剪接因子与13种癌症的预后相关，其中2个SF复合物与肝癌相关，1个SF复合物与食管癌预后相关。对这些癌症预后剪接因子及其相关选择性剪接事件的进一步系统生物信息学研究揭示了癌症特异性方式的潜在调控。我们的分析发现，ILF2-ILF3 的高表达通过选择性剪接与 LIHC 的不良预后相关。这些发现强调了 SF 作为预后潜在指标或治疗干预目标的重要性。它们在癌症中的作用表现出复杂性，并且取决于它们所处的特定环境。这一认识进一步强调需要全面了解和探索 SF 在不同类型癌症中的作用，为其在预后评估和靶向治疗开发中的潜在应用铺平道路。