Mamrot Jared, Hall Nathan E, Lindley Robyn A
GMDx Group Ltd, Melbourne, Victoria, Australia.
Department of Obstetrics and Gynaecology, Monash University, Clayton, VIC, Australia.
Oncotarget. 2021 Apr 13;12(8):845-858. doi: 10.18632/oncotarget.27934.
Somatic mutation signatures are an informative facet of cancer aetiology, however they are rarely useful for predicting patient outcome. The aim of this study is to evaluate the utility of a panel of 142 mutation-signature-associated metrics (P142) for predicting cancer progression in patients from a 'TCGA PanCancer Atlas' cohort. The P142 metrics are comprised of AID/APOBEC and ADAR deaminase associated SNVs analyzed for codon context, strand bias, and transitions/transversions. TCGA tumor-normal mutation data was obtained for 10,437 patients, representing 31 of the most prevalent forms of cancer. Stratified random sampling was used to split patients into training, tuning and validation cohorts for each cancer type. Cancer specific machine learning (XGBoost) models were built using the output from the P142 panel to predict patient Progression Free Survival (PFS) status as either "High PFS" or "Low PFS". Predictive performance of each model was evaluated using the validation cohort. Models accurately predicted PFS status for several cancer types, including adrenocortical carcinoma, glioma, mesothelioma, and sarcoma. In conclusion, the P142 panel of metrics successfully predicted cancer progression status in patients with some, but not all cancer types analyzed. These results pave the way for future studies on cancer progression associated signatures.
体细胞突变特征是癌症病因学中一个具有参考价值的方面，然而它们很少能用于预测患者的预后。本研究的目的是评估一组142个与突变特征相关的指标（P142）在预测“TCGA泛癌图谱”队列患者癌症进展方面的效用。P142指标由针对密码子上下文、链偏好以及转换/颠换分析的AID/APOBEC和ADAR脱氨酶相关的单核苷酸变异组成。获取了10437名患者的TCGA肿瘤-正常组织突变数据，这些患者代表了31种最常见的癌症形式。采用分层随机抽样将患者按癌症类型分为训练、调整和验证队列。使用P142指标组的输出构建癌症特异性机器学习（XGBoost）模型，以预测患者的无进展生存期（PFS）状态为“高PFS”或“低PFS”。使用验证队列评估每个模型的预测性能。模型准确预测了几种癌症类型的PFS状态，包括肾上腺皮质癌、胶质瘤、间皮瘤和肉瘤。总之，P142指标组成功预测了部分（但并非所有）所分析癌症类型患者的癌症进展状态。这些结果为未来关于癌症进展相关特征的研究铺平了道路。
