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• W2604302794 endingPage "e1295903" @default.
• W2604302794 startingPage "e1295903" @default.
• W2604302794 abstract "Glioblastoma (GBM) is resistant to most multimodal therapies. Clinical success of immune-checkpoint inhibitors (ICIs) has spurred interest in applying ICIs targeting CTLA4, PD1 or IDO1 against GBM. This amplifies the need to ascertain GBM's intrinsic susceptibility (or resistance) toward these ICIs, through clinical biomarkers that may also guide and prioritize preclinical testing. Here, we interrogated the TCGA and/or REMBRANDT human patient-cohorts to predict GBM's predisposition toward ICIs. We exploited various broad clinical biomarkers, including mutational or predicted-neoantigen burden, pre-existing or basal levels of tumor-infiltrating T lymphocytes (TILs), differential expression of immune-checkpoints within the tumor and their correlation with particular TILs/Treg-associated functional signature and prognostic impact of differential immune-checkpoint expression. Based on these analyses, we found that predictive biomarkers of ICI responsiveness exhibited inconsistent patterns in GBM patients, i.e., they either predicted ICI resistance (as compared with typical ICI-responsive cancer-types like melanoma, lung cancer or bladder cancer) or susceptibility to therapeutic targeting of CTLA4 or IDO1. On the other hand, our comprehensive literature meta-analysis and preclinical testing of ICIs using an orthotopic GL261-glioma mice model, indicated significant antitumor properties of anti-PD1 antibody, whereas blockade of IDO1 or CTLA4 either failed or provided very marginal advantage. These trends raise the need to better assess the applicability of ICIs and associated biomarkers for GBM." @default.
• W2604302794 created "2017-04-14" @default.
• W2604302794 creator A5025153030 @default.
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• W2604302794 creator A5091862786 @default.
• W2604302794 date "2017-03-03" @default.
• W2604302794 modified "2023-10-16" @default.
• W2604302794 title "Preclinical efficacy of immune-checkpoint monotherapy does not recapitulate corresponding biomarkers-based clinical predictions in glioblastoma" @default.
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• W2604302794 doi "https://doi.org/10.1080/2162402x.2017.1295903" @default.
• W2604302794 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5414887" @default.
• W2604302794 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28507806" @default.
• W2604302794 hasPublicationYear "2017" @default.
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