Noninvasive evaluation of neutrophil extracellular traps signature predicts clinical outcomes and immunotherapy response in hepatocellular carcinoma

Hongjie Xin; Qianwei Lai; Yuchen Zhou; Jian He; Yangda Song; Minjun Liao; Jiarun Sun; Meng Li; Mingxia Zhang; Weifang Liang; Yang Bai; Yongyuan Zhang; Yuanping Zhou

doi:10.3389/fimmu.2023.1134521

Noninvasive evaluation of neutrophil extracellular traps signature predicts clinical outcomes and immunotherapy response in hepatocellular carcinoma

Front Immunol. 2023 Jul 13:14:1134521. doi: 10.3389/fimmu.2023.1134521. eCollection 2023.

Authors

Hongjie Xin¹, Qianwei Lai¹, Yuchen Zhou², Jian He¹, Yangda Song^{1

3}, Minjun Liao^{1

3}, Jiarun Sun^{1

3}, Meng Li^{1

3}, Mingxia Zhang³, Weifang Liang³, Yang Bai¹, Yongyuan Zhang⁴, Yuanping Zhou¹

Affiliations

¹ Department of Gastroenterology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
² Department of General Surgery, Cancer Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China.
³ Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China.
⁴ HBVtech, Germantown, MD, United States.

Abstract

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 (P<0.001). Notably, the RNETS was competent in predicting disease-free survival (DFS) and OS in cohort 4 (P<0.001). In cohort 5, the RNETS was found to be an independent risk factor for progression-free survival (PFS) (P<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.

Keywords: computed tomography; hepatocellular carcinoma; neutrophil extracellular traps; prognosis; programmed death receptor-1; radiomics.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Carcinoma, Hepatocellular* / diagnosis
Carcinoma, Hepatocellular* / therapy
Extracellular Traps*
Humans
Immune Checkpoint Inhibitors / therapeutic use
Immunotherapy
Liver Neoplasms* / diagnosis
Liver Neoplasms* / therapy
Retrospective Studies

Substances

Immune Checkpoint Inhibitors

Grants and funding

This study was supported by the grants from the National Natural Science Foundation of China (81772923). The funding agency has no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.