Establishment and Validation of a Prognostic Immune Signature in Neuroblastoma

Yunhu Yu; Yu Zeng; Xiangping Xia; Jian-Guo Zhou; Fang Cao

doi:10.1177/10732748211033751

Establishment and Validation of a Prognostic Immune Signature in Neuroblastoma

Cancer Control. 2021 Jan-Dec:28:10732748211033751. doi: 10.1177/10732748211033751.

Authors

Yunhu Yu^{1

2}, Yu Zeng³, Xiangping Xia⁴, Jian-Guo Zhou⁵, Fang Cao⁴

Affiliations

¹ Department of Neurosurgery, the Third Affiliated Hospital of Zunyi Medical University, Zunyi, China.
² Clinical Research Center for Neurological Disease, the People's Hospital of HongHuaGang District of ZunYi, Zunyi, China.
³ Department of Cell Biology, School of Basic Medical Science, 70570Southern Medical University, Guangzhou, China.
⁴ Department of Cerebrovascular Disease, 66367Affiliated Hospital of Zunyi Medical University, Zunyi, China.
⁵ Department of Oncology, 66367Second Affiliated Hospital of Zunyi Medical University, Zunyi, China.

Abstract

Background: Neuroblastoma (NBL) is the most common extracranial solid tumor in childhood, and patients with high-risk neuroblastoma had a relatively poor prognosis despite multimodal treatment. To improve immunotherapy efficacy in neuroblastoma, systematic profiling of the immune landscape in neuroblastoma is an urgent need.

Methods: RNA-seq and according clinical information of neuroblastoma were downloaded from the TARGET database and GEO database (GSE62564). With an immune-related-gene set obtained from the ImmPort database, Immune-related Prognostic Gene Pairs for Neuroblastoma (IPGPN) for overall survival (OS) were established with the TARGET-NBL cohort and then verified with the GEO-NBL cohort. Immune cell infiltration analysis was subsequently performed. The integrated model was established with IPGPN and clinicopathological parameters. Immune cell infiltration was analyzed with the XCELL algorithm. Functional enrichment analysis was performed with clusterProfiler package in R.

Results: Immune-related Prognostic Gene Pairs for Neuroblastoma was successfully established with seven immune-related gene pairs (IGPs) involving 13 unique genes in the training cohort. In the training cohort, IPGPN successfully stratified neuroblastoma patients into a high and low immune-risk groups with different OS (HR=3.92, P = 2 × 10^-8) and event-free survival (HR=3.66, P=2 × 10^-8). ROC curve analysis confirmed its predictive power. Consistently, high IPGPN also predicted worse OS (HR=1.84, P = .002) and EFS in validation cohort (HR=1.38, P = .06) Moreover, higher activated dendritic cells, M1 macrophage, Th1 CD4⁺, and Th2 CD4⁺ T cell enrichment were evident in low immune-risk group. Further integrating IPGPN with age and stage demonstrated improved predictive performance than IPGPN alone.

Conclusion: Herein, we presented an immune landscape with IPGPN for prognosis prediction in neuroblastoma, which complements the present understanding of the immune signature in neuroblastoma.

Keywords: Immune-related prognostic gene pairs for neuroblastoma; event-free survival; immune cell infiltration; immune-related gene pairs; neuroblastoma; overall survival.

MeSH terms

Algorithms
Databases, Genetic
Female
Gene Expression Profiling
Humans
Infant
Kaplan-Meier Estimate
Male
Neoplasm Staging
Neuroblastoma / genetics*
Neuroblastoma / immunology
Neuroblastoma / mortality
Neuroblastoma / pathology*
Prognosis
Risk Factors
Tumor Microenvironment