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

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.

SUBMITTER: Zhang J

PROVIDER: S-EPMC6478916 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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

Zhang Jing J Caruso Francesca P FP Sa Jason K JK Justesen Sune S Nam Do-Hyun DH Sims Peter P Ceccarelli Michele M Lasorella Anna A Iavarone Antonio A

Communications biology 20190423

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 dat ...[more]

PMID: 31044160

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Project description:Glioblastomas are among the most lethal cancers; however, recent advances in survival have increased the need for better prognostic markers. microRNAs (miRNAs) hold great prognostic potential being deregulated in glioblastomas and highly stable in stored tissue specimens. Moreover, miRNAs control multiple genes representing an additional level of gene regulation possibly more prognostically powerful than a single gene. The aim of the study was to identify a novel miRNA signature with the ability to separate patients into prognostic subgroups. Samples from 40 glioblastoma patients were included retrospectively; patients were comparable on all clinical aspects except overall survival enabling patients to be categorized as short-term or long-term survivors based on median survival. A miRNome screening was employed, and a prognostic profile was developed using leave-one-out cross-validation. We found that expression patterns of miRNAs; particularly the four miRNAs: hsa-miR-107_st, hsa-miR-548x_st, hsa-miR-3125_st and hsa-miR-331-3p_st could determine short- and long-term survival with a predicted accuracy of 78%. Heatmap dendrograms dichotomized glioblastomas into prognostic subgroups with a significant association to survival in univariate (HR 8.50; 95% CI 3.06-23.62; p<0.001) and multivariate analysis (HR 9.84; 95% CI 2.93-33.06; p<0.001). Similar tendency was seen in The Cancer Genome Atlas (TCGA) using a 2-miRNA signature of miR-107 and miR-331 (miR sum score), which were the only miRNAs available in TCGA. In TCGA, patients with O6-methylguanine-DNA-methyltransferase (MGMT) unmethylated tumors and low miR sum score had the shortest survival. Adjusting for age and MGMT status, low miR sum score was associated with a poorer prognosis (HR 0.66; 95% CI 0.45-0.97; p = 0.033). A Kyoto Encyclopedia of Genes and Genomes analysis predicted the identified miRNAs to regulate genes involved in cell cycle regulation and survival. In conclusion, the biology of miRNAs is complex, but the identified 4-miRNA expression pattern could comprise promising biomarkers in glioblastoma stratifying patients into short- and long-term survivors.

Dataset Information

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

Publications

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

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