TY - JOUR
T1 - The combination of neoantigen quality and T lymphocyte infiltrates identifies glioblastomas with the longest survival
AU - Zhang, Jing
AU - Caruso, Francesca P.
AU - Sa, Jason K.
AU - Justesen, Sune
AU - Nam, Do Hyun
AU - Sims, Peter
AU - Ceccarelli, Michele
AU - Lasorella, Anna
AU - Iavarone, Antonio
N1 - Funding Information:
We are grateful to Luciano Garofano and Fulvio D’Angelo for sharing computational methods. This work was supported by NIH U54CA193313 and R01CA131126 to A.L.; R01CA178546, U54CA193313, R01CA179044, R01CA190891, R01NS061776 and The Chemotherapy Foundation to A.I. and AIRC IG 2018-ID 21846 to M.C.
Publisher Copyright:
© 2019, The Author(s).
PY - 2019/12/1
Y1 - 2019/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85071047399&partnerID=8YFLogxK
U2 - 10.1038/s42003-019-0369-7
DO - 10.1038/s42003-019-0369-7
M3 - Article
C2 - 31044160
AN - SCOPUS:85071047399
SN - 2399-3642
VL - 2
JO - Communications Biology
JF - Communications Biology
IS - 1
M1 - 135
ER -
