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MRI 衍生的放射组学评估肿瘤浸润巨噬细胞能够预测胶质瘤的免疫表型、免疫治疗反应和生存

英文原题:MRI-derived radiomics assessing tumor-infiltrating macrophages enable prediction of immune-phenotype, immunotherapy response and survival in glioma.

PubMed 2024/01/31(内容时间) Biomark Res Q1 · IF 14.6(JCR 2025)

研究概要

放射组学模型可在HGG患者中通过MRI图像无创评估TAM的绝对密度。值得注意的是,我们的RIB模型是首个被证实能够预测胶质瘤患者从DC疫苗中获益生存的免疫放射组学模型,从而为通过放射组学指导治疗决策和监测患者治疗过程提供了一种新工具。

研究思路结论见上方概要

肿瘤免疫微环境可影响免疫治疗的预后和治疗反应。我们旨在开发一种用于高级别胶质瘤(HGG)的非侵入性影像组学特征,以预测肿瘤相关巨噬细胞(TAMs)的绝对密度,TAMs是HGG微环境中的主要免疫细胞。我们还旨在评估该特征与肿瘤免疫表型以及对免疫治疗反应之间的关联。

在这项回顾性研究中,共纳入来自三个独立队列的379例HGG患者,采用mRMR特征排序方法和LASSO分类器构建了一个名为放射组学免疫生物标志物(RIB)的放射组学模型,用于预测M2样TAM的绝对密度。其中,来自TCGA微阵列队列的145例患者被随机分配至训练集(N=101)和内部验证集(N=44),而从华山医院招募的免疫表型队列(N=203)和免疫治疗队列(N=31,患者来自一项接受DC疫苗治疗的前瞻性临床试验)被用作两个外部验证集。免疫治疗队列还用于评估RIB与免疫治疗反应之间的关系。利用TAM细胞的RNA测序数据进行放射基因组学分析,以寻找功能注释。

一个用于M2样TAM的11特征影像组学模型被开发出来,并在四个HGG患者数据集中进行了验证(曲线下面积=0.849、0.719、0.674和0.671),使用的是增强后T1加权(T1CE)MRI图像。RIB评分高的患者表现出强烈的炎症反应。由TAM表达的四个枢纽基因(SLC7A7、RNASE6、HLA-DRB1和CD300A)被鉴定出与RIB密切相关,为生物学解释提供了重要证据。仅RIB评分高的个体显示出从DC疫苗中获得生存获益[DC疫苗 vs. 安慰剂:中位无进展生存期(mPFS),10.0个月 vs. 4.5个月,HR=0.17,P=0.0056,95%CI=0.041-0.68;中位总生存期(mOS),15.0个月 vs. 7.0个月,HR=0.17,P=0.0076,95%CI=0.04-0.68]。多因素分析也证实,DC疫苗治疗是高RIB评分组中改善生存的独立因素。然而,在低RIB评分组中,DC疫苗与生存改善无关。此外,基于RIB评分和临床因素的影像组学列线图能够有效预测1年、2年和3年生存率,ROC曲线分析证实了这一点(1年、2年和3年生存的AUC分别为0.705、0.729和0.684)。

展开英文摘要原文

BACKGROUND: The tumor immune microenvironment can influence the prognosis and treatment response to immunotherapy. We aimed to develop a non-invasive radiomic signature in high-grade glioma (HGG) to predict the absolute density of tumor-associated macrophages (TAMs), the preponderant immune cells in the microenvironment of HGG. We also aimed to evaluate the association between the signature, and tumor immune phenotype as well as response to immunotherapy. METHODS: In this retrospective setting, total of 379 patients with HGG from three independent cohorts were included to construct a radiomic model named Radiomics Immunological Biomarker (RIB) for predicting the absolute density of M2-like TAM using the mRMR feature ranking method and LASSO classifier. Among them, 145 patients from the TCGA microarray cohort were randomly allocated into a training set (N=101) and an internal validation set (N=44), while the immune-phenotype cohort (N=203) and the immunotherapy-treated cohort (N=31, patients from a prospective clinical trial treated with DC vaccine) recruited from Huashan Hospital were used as two external validation sets. The immunotherapy-treated cohort was also used to evaluate the relationship between RIB and immunotherapy response. Radiogenomic analysis was performed to find functional annotations using RNA sequencing data from TAM cells. RESULTS: An 11-feature radiomic model for M2-like TAM was developed and validated in four datasets of HGG patients (area under the curve = 0.849, 0.719, 0.674, and 0.671) using MRI images of post contrast enhanced T1-weighted (T1CE). Patients with high RIB scores had a strong inflammatory response. Four hub-genes (SLC7A7, RNASE6, HLA-DRB1 and CD300A) expressed by TAM were identified to be closely related to the RIB, providing important evidence for biological interpretation. Only individuals with a high RIB score were shown to have survival benefits from DC vaccine [DC vaccine vs. Placebo: median progression-free survival (mPFS), 10.0 mos vs. 4.5 mos, HR=0.17, P=0.0056, 95%CI=0.041-0.68; median overall survival (mOS), 15.0 mos vs. 7.0 mos, HR=0.17, P =0.0076, 95%CI=0.04-0.68]. Multivariate analyses also confirmed that treatment by DC vaccine was an independent factor for improved survival in the high RIB score group. However, in the low RIB score group, DC vaccine was not associated with improved survival. Furthermore, a radiomic nomogram based on the RIB score and clinical factors could efficiently predict the 1-, 2-, and 3-year survival rates, as confirmed by ROC curve analysis (AUC for 1-, 2- and 3-year survival: 0.705, 0.729 and 0.684, respectively). CONCLUSIONS: The radiomic model could allow for non-invasive assessment of the absolute density of TAM from MRI images in HGG patients. Of note, our RIB model is the first immunological radiomic model confirmed to have the ability to predict survival benefits from DC vaccine in gliomas, thereby providing a novel tool to inform treatment decisions and monitor patient treatment course by radiomics.

论文信息

作者
Chen D、Zhang R、Huang X、Ji C、Xia W、Qi Y、Yang X、Lin L
第一作者单位
Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.China
通讯作者单位
Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China. yu_yao@fudan.edu.cn.China
期刊
Biomarker research2024 Jan 31
原文标识
PubMed 38291499 · DOI 10.1186/s40364-024-00560-6