Alternative splicing of pre-mRNA transcripts is an important regulatory mechanism that increases the diversity of gene products in eukaryotes. Various studies have linked specific transcript isoforms to altered drug response in cancer; however, few algorithms have incorporated splicing information into drug response prediction. In this study, we evaluated whether basal-level splicing information could be used to predict drug sensitivity by constructing doxorubicin-sensitivity classification models with splicing and expression data. We detailed splicing differences between sensitive and resistant cell lines by implementing quasi-binomial generalized linear modeling (QBGLM) and found altered inclusion of 277 skipped exons. We additionally conducted RNA-binding protein (RBP) binding motif enrichment and differential expression analysis to characterize cis- and trans-acting elements that potentially influence doxorubicin response-mediating splicing alterations. Our results showed that a classification model built with skipped exon data exhibited strong predictive power. We discovered an association between differentially spliced events and epithelial-mesenchymal transition (EMT) and observed motif enrichment, as well as differential expression of RBFOX and ELAVL RBP family members. Our work demonstrates the potential of incorporating splicing data into drug response algorithms and the utility of a QBGLM approach for fast, scalable identification of relevant splicing differences between large groups of samples.

mRNA前体转录本的可变剪接是增加真核生物基因产物多样性的重要调控机制。各种研究已将特定的转录亚型与癌症中药物反应的改变联系起来。然而，很少有算法将剪接信息纳入药物反应预测。在这项研究中，我们评估了基础水平剪接信息是否可用于预测药物敏感性通过构建具有剪接和表达数据的多柔比星敏感性分类模型。我们通过实施准二项式广义线性建模 (QBGLM) 详细说明了敏感细胞系和抗性细胞系之间的剪接差异，并发现 277 个跳过的外显子的包含发生了改变。我们还进行了 RNA 结合蛋白 (RBP) 结合基序富集和差异表达分析，以表征顺式和反式-可能影响多柔比星反应介导剪接改变的作用元件。我们的结果表明，使用跳过的外显子数据构建的分类模型表现出强大的预测能力。我们发现了差异剪接事件与上皮间质转化 (EMT) 和观察到的基序富集以及RBFOX和ELAVL RBP 家族成员的差异表达之间的关联。我们的工作展示了将剪接数据整合到药物反应算法中的潜力，以及 QBGLM 方法在快速、可扩展地识别大量样本之间的相关剪接差异方面的实用性。