Royal College of Surgeons in Ireland
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Identification, validation and biological characterisation of novel glioblastoma tumour microenvironment subtypes: implications for precision immunotherapy

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posted on 2023-02-20, 11:26 authored by Kieron WhiteKieron White, Kate Connor, M Meylan, A Bougoüin, Manuela Salvucci, F Bielle, Alice O'FarrellAlice O'Farrell, Kieron SweeneyKieron Sweeney, L Weng, G Bergers, Patrick DickerPatrick Dicker, D M Ashley, E S Lipp, J T Low, J Zhao, P Wen, R Prins, M Verreault, A Idbaih, Archita BiswasArchita Biswas, Jochen PrehnJochen Prehn, D Lambrechts, I Arijs, F Lodi, G Dilcan, M Lamfers, S Leenstra, F Fabro, I Ntafoulis, J M Kros, Jane CryanJane Cryan, Francesca BrettFrancesca Brett, E Quissac, A Beausang, S MacNally, P O'Halloran, J Clerkin, O Bacon, A Kremer, R Tching Chi Yen, F S Varn, R G W Verhaak, C Sautès-Fridman, W H Fridman, Annette ByrneAnnette Byrne

Background: New precision medicine therapies are urgently required for glioblastoma (GBM). However, to date, efforts to subtype patients based on molecular profiles have failed to direct treatment strategies. We hypothesised that interrogation of the GBM tumour microenvironment (TME) and identification of novel TME-specific subtypes could inform new precision immunotherapy treatment strategies.

Materials and methods: A refined and validated microenvironment cell population (MCP) counter method was applied to >800 GBM patient tumours (GBM-MCP-counter). Specifically, partition around medoids (PAM) clustering of GBM-MCP-counter scores in the GLIOTRAIN discovery cohort identified three novel patient clusters, uniquely characterised by TME composition, functional orientation markers and immune checkpoint proteins. Validation was carried out in three independent GBM-RNA-seq datasets. Neoantigen, mutational and gene ontology analysis identified mutations and uniquely altered pathways across subtypes. The longitudinal Glioma Longitudinal AnalySiS (GLASS) cohort and three immunotherapy clinical trial cohorts [treatment with neoadjuvant/adjuvant anti-programmed cell death protein 1 (PD-1) or PSVRIPO] were further interrogated to assess subtype alterations between primary and recurrent tumours and to assess the utility of TME classifiers as immunotherapy biomarkers.

Results: TMEHigh tumours (30%) displayed elevated lymphocyte, myeloid cell immune checkpoint, programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 transcripts. TMEHigh/mesenchymal+ patients featured tertiary lymphoid structures. TMEMed (46%) tumours were enriched for endothelial cell gene expression profiles and displayed heterogeneous immune populations. TMELow (24%) tumours were manifest as an 'immune-desert' group. TME subtype transitions upon recurrence were identified in the longitudinal GLASS cohort. Assessment of GBM immunotherapy trial datasets revealed that TMEHigh patients receiving neoadjuvant anti-PD-1 had significantly increased overall survival (P = 0.04). Moreover, TMEHigh patients treated with adjuvant anti-PD-1 or oncolytic virus (PVSRIPO) showed a trend towards improved survival.

Conclusions: We have established a novel TME-based classification system for application in intracranial malignancies. TME subtypes represent canonical 'termini a quo' (starting points) to support an improved precision immunotherapy treatment approach.


European Union’s Horizon 2020 and 2021 research and innovation programme under the Marie Skłodowska-Curie ITN initiatives [grant number #766069]

GLIOTRAIN (http://www. and ‘GLIORESOLVE’ projects [grant number #101073386]

Paolo Iacovelli memorial endowment

Beaumont Hospital Foundation

Brain Tumour Ireland


Champions Oncology (Baltimore, USA)



The original article is available at

Published Citation

White K. et al. Identification, validation and biological characterisation of novel glioblastoma tumour microenvironment subtypes: implications for precision immunotherapy. Ann Oncol. 2022:S0923-7534(22)04743-3

Publication Date

6 December 2022

PubMed ID



  • Beaumont Hospital
  • Pathology
  • Physiology and Medical Physics
  • Public Health and Epidemiology




  • Published Version (Version of Record)