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Immunological Profiling of Mutational and Transcriptional Subgroups in Pediatric and Adult High-Grade Gliomas

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Immunological Profiling of Mutational and Transcriptional Subgroups in Pediatric and Adult High-Grade Gliomas Author Manuscript Published OnlineFirst on July 2, 2019; DOI: 10.1158/2326-6066.CIR-18-0939 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Immunological profiling of mutational and transcriptional subgroups in pediatric and adult high-grade gliomas Michael Bockmayr1,2,4, Frederick Klauschen2, Cecile L. Maire3, Stefan Rutkowski1, Manfred Westphal3, Katrin Lamszus3, Ulrich Schüller1,4,5*, Malte Mohme3* 1 Department of Pediatric Hematology and Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany 2 Charité – University Medicine Berlin, Humboldt University Berlin and Berlin Institute of Health, Institute of Pa- thology, Berlin, Germany 3 Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany 4 Research Institute Children's Cancer Center Hamburg, Hamburg, Germany. 5 Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany * these authors contributed equally Corresponding Authors: Malte Mohme, M.D. Department of Neurosurgery University Medical Center Hamburg-Eppendorf Martinistr. 52, 20246 Hamburg, Germany Tel.: +49 40 7410-0 Fax: +49 40 7410-58121 [email protected] Ulrich Schüller, M.D. Research Institute Children´s Cancer Center Hamburg Martinistr. 52, N63 (HPI), 20251 Hamburg, Germany Tel.: +49 40 4260 51240 Fax.: +49 40 7410 40350 [email protected] Words: 5468 (excl. abstract, translational relevance) Running Title: Immune profiling of pediatric and adult gliomas Key Words: high-grade glioma, glioblastoma, K27, G34, T cells, immune, gene ex- pression, immune profile Downloaded from cancerimmunolres.aacrjournals.org on September 24, 2021. © 2019 American Association for Cancer Research. Author Manuscript Published OnlineFirst on July 2, 2019; DOI: 10.1158/2326-6066.CIR-18-0939 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Abstract Immunological treatment strategies are under investigation for high-grade gliomas. In order to invigorate a tumor-specific immune response it is required to determine relevant immuno- logical pathways. We therefore investigated the immunological phenotypes within different subgroups of high-grade gliomas, with focus on rare genetic subgroups of pediatric and ado- lescent patients to identify potentially targetable mechanisms. We gathered published gene expression data from 1135 high-grade glioma patients and applied a machine learning tech- nique to determine their transcriptional (mesenchymal, classical, neural, proneural) and mu- tational (K27, G34, IDH, WT) subtype. Gene signatures of infiltrating immune cells and func- tional immune pathways were evaluated in correlation to histological diagnosis, age, tran- scriptional, and mutational subgroups. Our analysis identified four distinct microenvironmen- tal signatures of immune cell infiltration (immune 1-4), which can be stratified into vascular, monocytic/stromal, monocytic/T cell– and APC/NK/T cell–dominated immune clusters. Im- mune cell expression profiles correlated with transcriptional and mutational subgroups but were independent of age and histological diagnosis. By including functional pathways and correlating the expression of immunostimulatory and -inhibitory receptor-ligand interactions, we were able to define the immunological microenvironment and identify possible immuno- logical subtypes associated with poor prognosis. In addition, comparison of overall survival with the immunological landscape and with checkpoint molecules revealed correlations within the transcriptional and mutational subgroups, highlighting the potential application of PD- 1/PD-L1 checkpoint inhibition in K27-mutated tumors. Our study shows that transcriptional and mutational subgroups are characterized by distinct immunological tumor microenviron- ments, demonstrating the immunological heterogeneity within high-grade gliomas and sug- gesting an immune-specific stratification for upcoming immunotherapy trials. 2 Downloaded from cancerimmunolres.aacrjournals.org on September 24, 2021. © 2019 American Association for Cancer Research. Author Manuscript Published OnlineFirst on July 2, 2019; DOI: 10.1158/2326-6066.CIR-18-0939 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Introduction High-grade gliomas are defined by aggressive and infiltrative growth, reducing the life expectancy in pediatric and adult patients (1). Despite multimodal treatment, including neu- rosurgical resection and combination of radio- and chemotherapy, tumor recurrence is a cer- tainty (1). Although treatment modalities such as immunotherapeutic approaches with check- point inhibitors have failed to show efficacy in a phase III study in recurrent glioblastomas (2,3), ongoing studies are trying to harness the ability of the immune system to counteract tumor growth and induce long-term remission (4). To identify which patients might benefit from checkpoint inhibition or other immunotherapeutic approaches, such as tumor vaccines, chimeric antigen receptor (CAR) T-cell therapy, autologous T-cell transfer or cytolytic virus injections, we must better understand the glioma-specific immune microenvironment (5). Large scale immunological profiling of gene expression data in other cancer entities has yielded information to improve precision immunotherapy (6–8). Unfortunately, the intricate cellular, genetic, and transcriptional heterogeneity of malignant gliomas adds complexity to efforts to define targetable immunological profiles (9,10). The WHO classification in 2016 identified subcategories among high-grade gliomas (11). Molecular profiling, especially by isocitrate dehydrogenase (IDH) gene mutation analy- sis (12), improves understanding of subgroup-specific aggressiveness and prediction of overall survival in adult patients. Transcriptomic studies have identified additional subgroups. Phillips et al. described different molecular subgroups of astrocytoma and their prognostic relevance, then Verhaak and colleagues refined this classification by introducing a gene ex- pression-based molecular classification of glioblastoma that stratifies tumors into mesen- chymal, classical, neural and proneural subgroups (13,14). These groups share features of biological aggressiveness and response to therapy (13). The proneural subgroup was further subdivided into cGIMP and non-cGIMP methylated tumors (15). The neural subtype has been excluded in many subsequent studies due to suspected contamination of tumor sam- ples with normal tissue (14,16). In addition to the groups defined by transcriptional subtypes or mutations in the IDH gene in adult tumors, genomic sequencing studies also identified lineage-defining aberra- tions, such as the somatic mutations of the histone 3 variants in the positions G34 and K27 (17–19). Furthermore, pediatric glioblastoma can be stratified by additional molecular sub- groups according to their RTK or MYCN pathway aberrations (19). The K27 and G34 muta- tions in histone 3 were predominantly found in pediatric and adolescent glioblastoma, high- lighting their biological distinctiveness and the need to stratify high-grade gliomas according to their mutational profile. 3 Downloaded from cancerimmunolres.aacrjournals.org on September 24, 2021. © 2019 American Association for Cancer Research. Author Manuscript Published OnlineFirst on July 2, 2019; DOI: 10.1158/2326-6066.CIR-18-0939 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Accumulating data suggest that molecularly distinct glioma subgroups differ in their tumor microenvironment and their immuno-stromal profiles (20,21). Investigations of the TCGA dataset, predominantly including IDH wild-type glioblastomas, revealed heterogeneity in the composition of the immune environment between mutational and transcriptional sub- groups (22). Wang and colleagues demonstrated a subgroup-dependent macro- phage/microglia infiltration according to the gene-signature, with increased infiltration in NF1- mutated tumors (23). This was also confirmed by gene-enrichment analysis for transcription- al subtypes by Doucette et al. (24) and by our group by gene-expression profiling for different molecular subgroups in medulloblastoma (25). Our analysis evaluates the subtype-specific immune microenvironment across a co- hort of pediatric and adult high-grade gliomas, comparing mutational and transcriptional pro- files in order to identify immune infiltration patterns and functional pathways mediating local immunosuppression. Materials and Methods All data analyses were performed using the statistical programming language R (26) including the packages survival, caret, randomForest, igraph, gplots and Rtsne [https://CRAN.R-project.org/package=survival, https://CRAN.R-project.org/package=caret, http://igraph.org, https://CRAN.R-project.org/package=gplots, http://www.jmlr.org/papers/v9/vandermaaten-08a.html, https://cran.r- project.org/package=randomForest]. Datasets, preprocessing and batch effect removal Raw gene expression data (.CEL files) from high-grade gliomas including eight series on the Affymetrix Human Genome U133 Plus 2.0 Array and one series on the Affymetrix HT_HG-U133A array were downloaded from Gene Expression Omnibus (GEO) (Fig.1a and Supplementary Table S1)(27). To minimize batch effects, the fRMA normalization, which includes a batch effect cor- rection, was used as implemented in the R-package fRMA (28) using the input vectors from the
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