Abstract
BACKGROUND
Despite the success of immunotherapy across the spectrum of human cancer, a successful strategy has not emerged for GBM. While PD-L1 IHC and TMB have demonstrated some utility as predictors of immunotherapy benefit, responsiveness is complexly determined by factors affecting T cell trafficking, antigen presentation, other immune checkpoints, and mediators of immune exhaustion. Thus, we set out to to characterize mediators of immune resistance and their diversity in a population of GBM patients utilizing quantitative gene expression.
METHODS
A set of 54 immunotherapy and checkpoint relevant genes and seven genes related to immune failure were selected from the literature. RNA gene counts for TCGA glioblastoma multiforme samples (N=163) were downloaded from https://portal.gdc.cancer.gov/. Annotation on subtypes and PFS values were obtained from PMID: 24120142. Gene expression normalization as FPKM, hierarchical clustering and box-plots were performed using R-3.6.0. Statistical differences of gene expression between subtypes were quantified using a TurkeyHSD test.
RESULTS
A heatmap with hierarchical clustering for immune related genes for the TCGA GBM cohort was generated including colored annotation for the subtype and progression free survival. The graph shows a rough separation into two groups, where one group of the genes is tentatively associated with mesenchymal subtype and shorter survival and showing higher expression for most immune evasion genes. However, a heterogeneity of immune evasion signatures was identified within and across subtypes. Transcripts related to antigen presentation, EZH2, and LDHA varied significantly between GBM subtypes (p < 0.05).
CONCLUSION
Gene expression analysis has utility to identify specific mediators of immune evasion and to inform the selection of combination therapies for discrete subsets of patients. A Bayesian approach to patient selection for specific immunotherapy strategies may enhance the likelihood of successful implementation of immunotherapy in the clinic.
Inactivation of AMPK leads to attenuation of antigen presentation and immune evasion in lung adenocarcinoma