中性粒细胞胞外诱捕网特征的无创评估可预测肝细胞癌的临床结局和免疫治疗反应。
Noninvasive evaluation of neutrophil extracellular traps signature predicts clinical outcomes and immunotherapy response in hepatocellular carcinoma.
机构信息
Department of Gastroenterology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Department of General Surgery, Cancer Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China.
出版信息
Front Immunol. 2023 Jul 13;14:1134521. doi: 10.3389/fimmu.2023.1134521. eCollection 2023.
BACKGROUND
Neutrophil extracellular traps (NETs) have been shown to play a pivotal role in promoting metastasis and immune escape in hepatocellular carcinoma (HCC). Therefore, noninvasive tests to detect the formation of NETs in tumors can have significant implications for the treatment and prognoses of patients. Here, we sought to develop and validate a computed tomography (CT)-based radiomics model to predict the gene expression profiles that regulate the formation of NETs in HCC.
METHODS
This study included 1133 HCC patients from five retrospective cohorts. Based on the mRNA expression levels of 69 biomarkers correlated with NET formation, a 6-gene score (NETs score, NETS) was constructed in cohort 1 from TCIA database (n=52) and validated in cohort 2 (n=232) from ICGC database and cohort 3 (n=365) from TCGA database. And then based on the radiomics features of CT images, a radiomics signature (RNETS) was developed in cohort 1 to predict NETS status (high- or low-NETS). We further employed two cohorts from Nanfang Hospital (Guangzhou, China) to evaluate the predictive power of RNETS in predicting prognosis in cohort 4 (n=347) and the responses to PD-1 inhibitor of HCC patients in cohort 5 (n=137).
RESULTS
For NETS, in cohort 1, the area under the curve (AUC) values predicting 1, 2, and 3-year overall survival (OS) were 0.836, 0.879, and 0.902, respectively. The low-NETS was associated with better survival and higher levels of immune cell infiltration. The RNETS yielded an AUC value of 0.853 in distinguishing between high-NETS or low-NETS and patients with low-RNETS were associated with significantly longer survival time in cohort 1 (<0.001). Notably, the RNETS was competent in predicting disease-free survival (DFS) and OS in cohort 4 (<0.001). In cohort 5, the RNETS was found to be an independent risk factor for progression-free survival (PFS) (<0.001). In addition, the objective response rate of HCC patients treated with PD-1 inhibitor was significantly higher in the low-RNETS group (27.8%) than in the high-RNETS group (10.8%).
CONCLUSIONS
This study revealed that RNETS as a radiomics biomarker could effectively predict prognosis and immunotherapy response in HCC patients.
背景
中性粒细胞胞外诱捕网（NETs）已被证明在促进肝癌（HCC）转移和免疫逃逸中发挥关键作用。因此，能够检测肿瘤中 NETs 形成的非侵入性测试对患者的治疗和预后具有重要意义。在这里，我们试图开发和验证一种基于计算机断层扫描（CT）的放射组学模型，以预测调节 HCC 中 NETs 形成的基因表达谱。
方法
本研究纳入了来自五个回顾性队列的 1133 名 HCC 患者。基于与 NET 形成相关的 69 个生物标志物的 mRNA 表达水平，在 TCIA 数据库（n=52）的队列 1 中构建了 6 个基因评分（NETs 评分，NETS），并在 ICGC 数据库的队列 2（n=232）和 TCGA 数据库的队列 3（n=365）中进行了验证。然后，基于 CT 图像的放射组学特征，在队列 1 中开发了放射组学特征（RNETS），以预测 NETS 状态（高 NETS 或低 NETS）。我们还利用来自中国南方医院的两个队列（广州），在队列 4（n=347）中评估 RNETS 预测预后的能力，并在队列 5（n=137）中评估 HCC 患者对 PD-1 抑制剂的反应。
结果
对于 NETS，在队列 1 中，预测 1、2 和 3 年总生存期（OS）的 AUC 值分别为 0.836、0.879 和 0.902。低 NETS 与更好的生存和更高水平的免疫细胞浸润相关。RNETS 区分高 NETS 或低 NETS 的 AUC 值为 0.853，队列 1 中低 RNETS 患者的生存时间明显更长（<0.001）。值得注意的是，RNETS 在预测队列 4 的无病生存期（DFS）和 OS 方面具有良好的效能（<0.001）。在队列 5 中，RNETS 被发现是进展无进展生存期（PFS）的独立危险因素（<0.001）。此外，接受 PD-1 抑制剂治疗的 HCC 患者的客观缓解率在低 RNETS 组（27.8%）明显高于高 RNETS 组（10.8%）。
结论
本研究表明，RNETS 作为一种放射组学生物标志物，可以有效地预测 HCC 患者的预后和免疫治疗反应。
Zotero 插件