基于TCGA/TCIA的CT放射组学预测膀胱癌经典致癌信号通路的状态

Prediction of Status in Classical Oncogenic Signaling Pathways in Bladder Cancer Based on TCGA/TCIA-CT Radiomics

目的探讨基于癌症基因组图谱(TCGA)/癌症成像档案馆(TCIA)的CT放射组学对膀胱癌(BLCA)经典致癌信号通路状态无创预测的价值。方法从TCGA/TCIA公共数据库筛选的69例BLCA患者(训练队列55例,验证队列14例)回顾性地纳入本研究,并用于分析放射组学与P13K、RTK RAS、NOTCH以及TP53经典致癌信号通路状态的关系。基于增强CT动脉期影像提取1130个放射学特征。最小绝对收缩和选择算子回归算法(LASSO)用于开发放射组学评分。放射组学评分的性能、校准得到了确认验证。结果4条致癌信号通路均表现为40%以上的状态改变阳性率,基于7,4,5和7个特征分别开发CT放射组学评分,并在训练队列和验证队列中均表现中度以上预测性能[曲线下面积(AUC)>0.70],具有良好的校准一致性。NOTCH与RTK RAS放射组学评分存在正相关关系(r=0.41,P<0.001),与P13K存在负相关关系(r=-0.60,P<0.001),反映了通路间可能存在协同或互斥作用。结论放射组学具有无创性预测BLCA经典致癌信号通路状态的价值,为肿瘤的靶向治疗疗效监测提供潜在的非侵入性手段。

Objective To explore the value of TCGA/TCIA-CT radiomics for the noninvasive prediction of the status of classical oncogenic signaling pathways in bladder cancer(BLCA).Methods Sixty-nine BLCA patients(55 in the training cohort and 14 in the validation cohort)screened from the TCGA/TCIA public database were retrospectively included in this study and used to analyze the relationship of radiomics with P13K,RTK RAS,NOTCH,and TP53 classical oncogenic signaling pathway status.1130 radiomics features were extracted based on enhanced CT arterial phase images.Least absolute shrinkage and selection operator algorithm was used to develop radiomics scores.The performance,calibration of radiomics scores were confirmed and validated.Results All 4 oncogenic signaling pathways exhibited a positive rate of 40%or more.CT radiomics scores were developed based on 7,4,5 and 7 features and showed moderate or higher predictive performance(AUC>O.70)in both training and validation cohorts with good calibration agreement.There was a positive correlation between NOTCH and RTK RAS radiomic scores(r=0.41,P<0.001)and a negative correlation with P13K(r=-0.60,P<0.001),reflecting possible synergistic or mutually exclusive effects between pathways.Conclusion Radiomics has the value of predicting the status of BLCA classical oncogenic signaling pathways,providing a potential non-invasive means of monitoring the effectiveness of targeted tumor therapy.