The combination of neoantigen quality and T lymphocyte infiltrates identifies glioblastomas with the longest survival

Jing Zhang,Jason K Sa,Do-Hyun Nam,Michele Ceccarelli,Anna Lasorella,Francesca P Caruso,Sune Justesen,Peter Sims,Antonio Iavarone

doi:10.1038/s42003-019-0369-7

Abstract

Glioblastoma (GBM) is resistant to multimodality therapeutic approaches. A high burden of tumor-specific mutant peptides (neoantigens) correlates with better survival and response to immunotherapies in selected solid tumors but how neoantigens impact clinical outcome in GBM remains unclear. Here, we exploit the similarity between tumor neoantigens and infectious disease-derived immune epitopes and apply a neoantigen fitness model for identifying high-quality neoantigens in a human pan-glioma dataset. We find that the neoantigen quality fitness model stratifies GBM patients with more favorable clinical outcome and, together with CD8+ T lymphocytes tumor infiltration, identifies a GBM subgroup with the longest survival, which displays distinct genomic and transcriptomic features. Conversely, neither tumor neoantigen burden from a quantitative model nor the isolated enrichment of CD8+ T lymphocytes were able to predict survival of GBM patients. This approach may guide optimal stratification of GBM patients for maximum response to immunotherapy.

Highlights

Glioblastoma (GBM) is resistant to multimodality therapeutic approaches
This study describes such strategy using a computational approach for the identification of GBM patients harboring high-quality neoantigens that, together with CD8+ T lymphocyte infiltrates, perform optimally in identifying patients with the longest survival and a functionally activated tumor immune microenvironment
This information might be of clinical importance for the accurate stratification of the subgroup of GBM patients having the best probability to benefit from immunotherapies

Summary

Introduction

Glioblastoma (GBM) is resistant to multimodality therapeutic approaches. A high burden of tumor-specific mutant peptides (neoantigens) correlates with better survival and response to immunotherapies in selected solid tumors but how neoantigens impact clinical outcome in GBM remains unclear. The recognized unique genetic landscape and the biological features of the GBM microenvironment led to the exclusion of high-grade glioma patients from several multi-cancer studies that have characterized tumor immunity and reinforced the notion that a lymphocyte depleted and immunosuppressive microenvironment is a distinctive feature of malignant gliomas[14]. In this manuscript, we present the application of a neoantigen quality model for the accurate prediction of immunogenic neoantigens in IDH wild-type GBM, the largest and most aggressive group of high-grade gliomas. The unique immunogenic attributes of this GBM subgroup informs on a cohort of patients who are optimally outfitted to mount the most effective responses following immunotherapy treatments

Methods

Results

Conclusion