Radiogenomic-Based Survival Risk Stratification of Tumor Habitat on Gd-T1w MRI Is Associated with Biological Processes in Glioblastoma
Radiogenomic-Based Survival Risk Stratification of Tumor Habitat on Gd-T1w MRI Is Associated with Biological Processes in Glioblastoma
复制标题
DOI：
10.1158/1078-0432.ccr-19-2556
复制
发表时间：
2020-04-01
影响因子：
11.5
通讯作者：
Tiwari, Pallavi
中科院分区：
文献类型：
--
作者：
Beig, Niha;Bera, Kaustav;Tiwari, Pallavi
目的：(I)利用常规MRI上肿瘤栖息地的放射性特征建立生存风险评分，以预测胶质母细胞瘤的无进展生存(PFS)；(Ii)通过研究放射基因组与分子信号通路的关系，获得这些预后放射学特征的生物学基础。实验设计：203例接受Gd-T1w、T2w、T2w-FLAIR治疗的患者来自3个队列：癌症影像档案(TCIA；n=130)、常春藤GAP(n=32)和克利夫兰诊所(n=41)。获得了TCIA队列中相应患者的基因表达谱。对于每项研究，在对肿瘤亚室(坏死核心、强化肿瘤、瘤周水肿)进行专家分割后，从所有MRI方案的每个亚室提取936个3D放射学特征。使用COX回归模型，为每种方案制定放射学风险评分(RRS)，以预测训练队列(n=130)和抵抗队列(n=73)上的PFS。进一步通过基因本体论和单样本基因集浓缩分析确定与RRS特征相关的特定分子信号通路网络。结果：来自肿瘤栖息地的25个放射学特征产生了RRS。RRS与临床(年龄和性别)和分子特征(MGMT和IDH状态)相结合，导致训练的一致性指数为0.0001.81(P<；0)，测试集的一致性指数为0.84(P=0.0 3)。放射基因组学分析表明，RRS特征与细胞分化、细胞黏附和血管生成的信号通路有关，这是导致GBM化疗耐药的原因。结论：常规Gd-T1wMRI的放射学特征也可能与影响GBM化疗反应的关键生物学过程显著相关。
Purpose: To (i) create a survival risk score using radiomic features from the tumor habitat on routine MRI to predict progression-free survival (PFS) in glioblastoma and (ii) obtain a biological basis for these prognostic radiomic features, by studying their radio-genomic associations with molecular signaling pathways.Experimental Design: Two hundred three patients with pretreatment Gd-T1w, T2w, T2w-FLAIR MRI were obtained from 3 cohorts: The Cancer Imaging Archive (TCIA; n = 130), Ivy GAP (n = 32), and Cleveland Clinic (n = 41). Gene-expression profiles of corresponding patients were obtained for TCIA cohort. For every study, following expert segmentation of tumor sub-compartments (necrotic core, enhancing tumor, peritumoral edema), 936 3D radiomic features were extracted from each subcompartment across all MRI protocols. Using Cox regression model, radiomic risk score (RRS) was developed for every protocol to predict PFS on the training cohort (n = 130) and evaluated on the holdout cohort (n = 73). Further, Gene Ontology and single-sample gene set enrichment analysis were used to identify specific molecular signaling pathway networks associated with RRS features.Results: Twenty-five radiomic features from the tumor habitat yielded the RRS. A combination of RRS with clinical (age and gender) and molecular features (MGMT and IDH status) resulted in a concordance index of 0.81 (P < 0.0001) on training and 0.84 (P = 0.03) on the test set. Radiogenomic analysis revealed associations of RRS features with signaling pathways for cell differentiation, cell adhesion, and angiogenesis, which contribute to chemoresistance in GBM.Conclusions: Our findings suggest that prognostic radiomic features from routine Gd-T1w MRI may also be significantly associated with key biological processes that affect response to chemotherapy in GBM.