Publication Details
Overview
 
 
Adhithya Narayanan Srinivasan, Mónica Vara Pérez, Selene De Sutter, Sophia Leduc, Wietse Geens, Xenia Geeraerts, Daliya Kancheva, Ria Roelandt, Michaël Bruneau, Sandra Tuyaerts, Latoya Stevens, Bart Neyns, Jef Vandemeulebroucke, Johnny Duerinck, Kiavash Movahedi
 

Unpublished contribution to conference

Abstract 

Glioblastoma (GBM) is an aggressive form of primary brain tumor characterized by its dismal prognosis, representing an unmet clinical need. GBM exhibits profound inter- and intra-tumoral heterogeneity, which drives its malignancy and resistance to therapy. However, the contribution of the tumor microenvironment in shaping this heterogeneity remains to be fully elucidated. Here, we aim to unravel the cellular heterogeneity of immune, stromal and malignant cells within distinct spatially-defined human GBM tumor regions. The region of interests were defined by combining Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) with machine learning algorithms. These distinct regions were biopsied using neuronavigation-guided surgery, then frozen for single-cell experiments and stored as Formalin-Fixed Paraffin-Embedded tissue samples for spatial analysis. Single nuclei RNA sequencing (snRNA-seq) was performed on 44 biopsied regions from 9 patients, including longitudinal samples from two patients following disease recurrence. Our ongoing analysis has highlighted profound regional heterogeneity in terms of cancer and immune cell activation and infiltration. By integrating MRI/PET-based multimodal imaging with snRNAseq and AI, we aim to identify novel tumor areas relevant to surgical tumor resection as well as (immuno)therapy resistance. This work will provide a framework for follow-up studies that aim to develop new therapeutic breakthroughs for GBM patients.

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