Royal College of Surgeons in Ireland
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Preclinical interrogation of novel immunotherapy treatment strategies in glioblastoma (GBM) using a novel clinically relevant disease model

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posted on 2023-11-28, 11:48 authored by James Clerkin

Reliable and clinically faithful pre-clinical glioblastoma (GBM) models are essential for the screening of new therapies and to understand treatment resistance mechanisms. Historically models have failed to predict response in the clinical setting. As a result, many clinical trials fail to meet their primary endpoint, despite promising preclinical data. Moreover, current GBM models seldom incorporate surgical resection and/or standard of care chemotherapy treatment, commonly employing young animals whose immune contexture differs from older patients. Here, we have established an orthotopic GBM model, which employs the syngeneic, mesenchymal-NFpp10a-cell line, in both young and aged mice. We have characterised the model in response to standard of care (SOC) resection and temozolomide (TMZ) treatment. We have further studied response to experimental treatments with anti-PD1 (adjuvant and neoadjuvant). NFpp10a-Luc2 expressing cells were orthotopically implanted into C57BL/6-mice (male and female, aged [>18months] and young [6-8weeks]) and weekly bioluminescence imaging (BLI) performed to monitor tumour growth. Several therapeutic interventions were subsequently assessed to study anti-tumour efficacy and overall survival (OS). The treatment panel included (1) surgical resection of tumour (Sweeney et al., 2014), (2) TMZ therapy (oral gavage; 50 mg/kg; 5 consecutive days in each 28-day cycle) (3) Anti-PD1 therapy (intraperitoneal; 250 ug; day 10, 12 & 14 post-tumour implantation), (4) Neoadjuvant (NA) anti-PD1 therapy (intraperitoneal; 100 ug; Day 5 and 3 pre-tumour resection), Response to therapy was assessed via longitudinal BLI. Tissue collected postmortem has undergone bulk RNA sequencing. Transcriptomic data underwent microenvironment cell population (MCP) analyses to determine the absolute abundance of eight immune and two stromal cell populations within tumours and to study how these populations changed following treatment. Gene set enrichment analysis (GSEA) was further employed to determine gene expression pathway changes We demonstrated survival advantage in aged mice undergoing surgical resection (Resection:33.5 days vs Non-Resection: 18 days; p= 0.0166) and observed age to be a significant prognostic factor (Young:62 days vs Aged: 22 days; p=0.0002). Subsequently, we observed that TMZ and anti-PD1 monotherapy had no impact on NFpp10-Luc2 growth (TMZ-overall: p=0.9001, anti-PD1-overall: p=0.7933) or survival (TMZ- overall: p=0.3035, anti-PD1-overall: p=0.6328). Neoadjuvant anti-PD1 treated mice 21 demonstrated no significant survival advantage compared to IgG control (33 days vs 35 days; p=0.9429) or BLI signal (p=0.1703). NFpp10a forms immune-cold TME relative to commonly employed models. Neoadjuvant anti-PD1 induced influx of CD8+ T cells, B cells and monocytes into the TME and was associated with upregulation of CXCR3 in gene set enrichment analysis (p=0.0045). Overall, we have, for the first time, established and characterised response of the NFpp10a-C57BL/6 model to surgical resection, TMZ and anti-PD1 therapy in young and aged mice. We have shown that the model is markedly insensitive to intervention with chemotherapy and immune checkpoint therapy, mirroring what is seen clinically in patients. The model may therefore be employed in future pre-clinical studies to guide clinical trials in the setting of mesenchymal GBM. 

History

First Supervisor

Prof. Annette Byrne

Second Supervisor

Mr. David O’Brien

Third Supervisor

Prof. Jochen Prehn

Comments

Submitted for the Award of Doctor of Medicine to RCSI University of Medicine and Health Sciences, 2022

Published Citation

Clerkin, J,. Preclinical Interrogation of Novel Immunotherapy Treatment Strategies in Glioblastoma (GBM) Using a Novel Clinically Relevant Disease Model. [MD Thesis] Dublin: RCSI University of Medicine and Health Sciences; 2022

Degree Name

  • Doctor of Medicine (MD)

Date of award

2022-11-30

Programme

  • Doctor of Medicine (MD)

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