Ghimire Prajwal, Kinnersley Ben, Karami Golestan, Arumugam Prabhu, Houlston Richard, Ashkan Keyoumars, Modat Marc, Booth Thomas C
Department of Neurosurgery, Kings College Hospital NHS Foundation Trust, London, UK.
School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
Neurooncol Adv. 2024 Apr 5;6(1):vdae055. doi: 10.1093/noajnl/vdae055. eCollection 2024 Jan-Dec.
Immunotherapy is an effective "precision medicine" treatment for several cancers. Imaging signatures of the underlying genome (radiogenomics) in glioblastoma patients may serve as preoperative biomarkers of the tumor-host immune apparatus. Validated biomarkers would have the potential to stratify patients during immunotherapy clinical trials, and if trials are beneficial, facilitate personalized neo-adjuvant treatment. The increased use of whole genome sequencing data, and the advances in bioinformatics and machine learning make such developments plausible. We performed a systematic review to determine the extent of development and validation of immune-related radiogenomic biomarkers for glioblastoma.
A systematic review was performed following PRISMA guidelines using the PubMed, Medline, and Embase databases. Qualitative analysis was performed by incorporating the QUADAS 2 tool and CLAIM checklist. PROSPERO registered: CRD42022340968. Extracted data were insufficiently homogenous to perform a meta-analysis.
Nine studies, all retrospective, were included. Biomarkers extracted from magnetic resonance imaging volumes of interest included apparent diffusion coefficient values, relative cerebral blood volume values, and image-derived features. These biomarkers correlated with genomic markers from tumor cells or immune cells or with patient survival. The majority of studies had a high risk of bias and applicability concerns regarding the index test performed.
Radiogenomic immune biomarkers have the potential to provide early treatment options to patients with glioblastoma. Targeted immunotherapy, stratified by these biomarkers, has the potential to allow individualized neo-adjuvant precision treatment options in clinical trials. However, there are no prospective studies validating these biomarkers, and interpretation is limited due to study bias with little evidence of generalizability.
免疫疗法是几种癌症的有效“精准医学”治疗方法。胶质母细胞瘤患者潜在基因组的影像学特征（放射基因组学）可作为肿瘤宿主免疫机制的术前生物标志物。经过验证的生物标志物有可能在免疫疗法临床试验中对患者进行分层，如果试验有益，则有助于个性化新辅助治疗。全基因组测序数据的使用增加以及生物信息学和机器学习的进展使这种发展成为可能。我们进行了一项系统综述，以确定胶质母细胞瘤免疫相关放射基因组生物标志物的开发和验证程度。
按照PRISMA指南，使用PubMed、Medline和Embase数据库进行系统综述。通过纳入QUADAS 2工具和CLAIM清单进行定性分析。PROSPERO注册编号：CRD42022340968。提取的数据同质性不足，无法进行荟萃分析。
纳入了9项研究，均为回顾性研究。从感兴趣的磁共振成像体积中提取的生物标志物包括表观扩散系数值、相对脑血容量值和图像衍生特征。这些生物标志物与肿瘤细胞或免疫细胞的基因组标志物或患者生存率相关。大多数研究在进行的指标测试方面存在较高的偏倚风险和适用性问题。
放射基因组免疫生物标志物有可能为胶质母细胞瘤患者提供早期治疗选择。通过这些生物标志物进行分层的靶向免疫疗法有可能在临床试验中提供个性化的新辅助精准治疗选择。然而，目前尚无前瞻性研究验证这些生物标志物，且由于研究偏倚，其解释有限，几乎没有可推广性的证据。
