Related Experiment Video
Updated: Jul 31, 2025
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Cross-cohort analysis identified an immune checkpoint-based signature to predict the clinical outcomes of
Liang Zeng1, Hui Xu1, Shu-Hua Li2
1Department of Pathology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, National Children's Medical Center for South Central Region, Guangzhou, China.
Background:
Neuroblastoma (NB) places a substantial health burden on families worldwide. This study aimed to develop an immune checkpoint-based signature (ICS) based on the expression of immune checkpoints to better assess patient survival risk and potentially guide patient selection for immunotherapy of NB.
Methods:
Immunohistochemistry integrated with digital pathology was used to determine the expression levels of 9 immune checkpoints in 212 tumor tissues used as the discovery set. The GSE85047 dataset (n=272) was used as a validation set in this study. In the discovery set, the ICS was constructed using a random forest algorithm and confirmed in the validation set to predict overall survival (OS) and event-free survival (EFS). Kaplan-Meier curves with a log-rank test were drawn to compare the survival differences. A receiver operating characteristic (ROC) curve was applied to calculate the area under the curve (AUC).
Results:
Seven immune checkpoints, including PD-L1, B7-H3, IDO1, VISTA, T-cell immunoglobulin and mucin domain containing-3 (TIM-3), inducible costimulatory molecule (ICOS) and costimulatory molecule 40 (OX40), were identified as abnormally expressed in NB in the discovery set. OX40, B7-H3, ICOS and TIM-3 were eventually selected for the ICS model in the discovery set, and 89 patients with high risk had an inferior OS (HR 15.91, 95% CI 8.87 to 28.55, p<0.001) and EFS (HR 4.30, 95% CI 2.80 to 6.62, p<0.001). Furthermore, the prognostic value of the ICS was confirmed in the validation set (p<0.001). Multivariate Cox regression analysis demonstrated that age and the ICS were independent risk factors for OS in the discovery set (HR 6.17, 95% CI 1.78 to 21.29 and HR 1.18, 95% CI 1.12 to 1.25, respectively). Furthermore, nomogram A combining the ICS and age demonstrated significantly better prognostic value than age alone in predicting the patients' 1-year, 3-year and 5-year OS in the discovery set (1 year: AUC, 0.891 (95% CI 0.797 to 0.985) vs 0.675 (95% CI 0.592 to 0.758); 3 years: 0.875 (95% CI 0.817 to 0.933) vs 0.701 (95% CI 0.645 to 0.758); 5 years: 0.898 (95% CI 0.851 to 0.940) vs 0.724 (95% CI 0.673 to 0.775), respectively), which was confirmed in the validation set.
Conclusions:
We propose an ICS that significantly differentiates between low-risk and high-risk patients, which might add prognostic value to age and provide clues for immunotherapy in NB.
