Department of Radiation Oncology, Gustave Roussy, Villejuif, Île-de-France, France.
Institut Gustave Roussy, Inserm, Radiothérapie Moléculaire et Innovation Thérapeutique, Paris-Saclay University, Villejuif, Île-de-France, France.
J Immunother Cancer. 2020 Nov;8(2). doi: 10.1136/jitc-2020-001429.
Combining radiotherapy (RT) with immuno-oncology (IO) therapy (IORT) may enhance IO-induced antitumor response. Quantitative imaging biomarkers can be used to provide prognosis, predict tumor response in a non-invasive fashion and improve patient selection for IORT. A biologically inspired CD8 T-cells-associated radiomics signature has been developed on previous cohorts. We evaluated here whether this CD8 radiomic signature is associated with lesion response, whether it may help to assess disease spatial heterogeneity for predicting outcomes of patients treated with IORT. We also evaluated differences between irradiated and non-irradiated lesions.
Clinical data from patients with advanced solid tumors in six independent clinical studies of IORT were investigated. Immunotherapy consisted of 4 different drugs (antiprogrammed death-ligand 1 or anticytotoxic T-lymphocyte-associated protein 4 in monotherapy). Most patients received stereotactic RT to one lesion. Irradiated and non-irradiated lesions were delineated from baseline and the first evaluation CT scans. Radiomic features were extracted from contrast-enhanced CT images and the CD8 radiomics signature was applied. A responding lesion was defined by a decrease in lesion size of at least 30%. Dispersion metrices of the radiomics signature were estimated to evaluate the impact of tumor heterogeneity in patient's response.
A total of 94 patients involving multiple lesions (100 irradiated and 189 non-irradiated lesions) were considered for a statistical interpretation. Lesions with high CD8 radiomics score at baseline were associated with significantly higher tumor response (area under the receiving operating characteristic curve (AUC)=0.63, p=0.0020). Entropy of the radiomics scores distribution on all lesions was shown to be associated with progression-free survival (HR=1.67, p=0.040), out-of-field abscopal response (AUC=0.70, p=0.014) and overall survival (HR=2.08, p=0.023), which remained significant in a multivariate analysis including clinical and biological variables.
These results enhance the predictive value of the biologically inspired CD8 radiomics score and suggests that tumor heterogeneity should be systematically considered in patients treated with IORT. This CD8 radiomics signature may help select patients who are most likely to benefit from IORT.
将放射治疗（RT）与免疫肿瘤学（IO）治疗（IORT）相结合可能会增强 IO 诱导的抗肿瘤反应。定量成像生物标志物可用于提供预后，以无创方式预测肿瘤反应，并改善 IORT 患者的选择。以前的队列已经开发出了一种受生物启发的 CD8 T 细胞相关放射组学特征。在这里，我们评估了该 CD8 放射组学特征是否与病变反应相关，是否可以帮助评估疾病的空间异质性，从而预测接受 IORT 治疗的患者的结果。我们还评估了照射和未照射病变之间的差异。
研究了六个独立的 IORT 临床研究中晚期实体瘤患者的临床数据。免疫疗法包括 4 种不同的药物（单独使用抗程序性死亡配体 1 或抗细胞毒性 T 淋巴细胞相关蛋白 4）。大多数患者接受立体定向 RT 治疗一个病灶。从基线和第一次评估 CT 扫描中勾画照射和未照射的病变。从增强 CT 图像中提取放射组学特征，并应用 CD8 放射组学特征。通过病灶大小至少减少 30%来定义反应性病灶。估计放射组学特征的分散指标，以评估肿瘤异质性对患者反应的影响。
对总共 94 名涉及多个病灶（100 个照射病灶和 189 个未照射病灶）的患者进行了统计解释。基线时 CD8 放射组学评分较高的病灶与更高的肿瘤反应显著相关（接受者操作特征曲线下面积（AUC）=0.63，p=0.0020）。所有病灶上放射组学评分分布的熵被证明与无进展生存期（HR=1.67，p=0.040）、场外远隔反应（AUC=0.70，p=0.014）和总生存期（HR=2.08，p=0.023）相关，这在包括临床和生物学变量的多变量分析中仍然具有显著性。
这些结果增强了受生物启发的 CD8 放射组学评分的预测价值，并表明在接受 IORT 治疗的患者中应系统地考虑肿瘤异质性。该 CD8 放射组学特征可能有助于选择最有可能从 IORT 中受益的患者。
