Atezolizumab_mUC

Validation analyses This code was used to develop the best-performing CART-OMC model to predict atezolizumab response using gene expression profiles from 298 atezolizumab-treated mUC patients in the IMvigor210 discovery dataset. This model was then validated on 22 mUC patients treated with atezolizumab from the Synder et al. validation dataset. This is the command line used for validation analyses: python -u GEX_validation_analyses.py -d GEX_discovery.csv -v GEX_validation.csv Arguments: -u --> Python code -d --> discovery dataset: The tabulated pharmaco-omics dataset, where columns specify patients, their corresponding drug responses (CR, PR, SD, and PD), and gene expression features. -v, --validation dataset: The tabulated pharmaco-omics dataset, where columns specify patients, their corresponding drug responses (CR, PR, SD, and PD), and gene expression features.验证分析 本代码用于构建表现最优的CART-OMC模型，依托IMvigor210发现数据集中298例接受阿替利珠单抗(atezolizumab)治疗的转移性尿路上皮癌(mUC, metastatic urothelial carcinoma)患者的基因表达谱，预测阿替利珠单抗的治疗响应。随后，该模型在Synder等人的验证数据集的22例接受阿替利珠单抗治疗的mUC患者队列中完成验证。 本次验证分析所用的命令行如下： python -u GEX_validation_analyses.py -d GEX_discovery.csv -v GEX_validation.csv 参数说明： -u：对应Python脚本 -d：发现数据集：为制表型药物组学数据集，列信息分别对应患者、对应的药物响应类型（完全缓解(CR, Complete Response)、部分缓解(PR, Partial Response)、疾病稳定(SD, Stable Disease)、疾病进展(PD, Progressive Disease)）以及基因表达特征。 -v, --validation dataset：验证数据集：为制表型药物组学数据集，列信息分别对应患者、对应的药物响应类型（完全缓解(CR, Complete Response)、部分缓解(PR, Partial Response)、疾病稳定(SD, Stable Disease)、疾病进展(PD, Progressive Disease)）以及基因表达特征。