Single-cell characterization of human GBM reveals regional differences in tumor-infiltrating leukocyte activation.
Philip SchmassmannJulien RouxSteffen DettlingSabrina A HoganTala ShekarianTomás A MartinsMarie-Françoise RitzSylvia HerterMarina BacacGregor HutterPublished in: eLife (2023)
Glioblastoma (GBM) harbors a highly immunosuppressive tumor microenvironment (TME) which influences glioma growth. Major efforts have been undertaken to describe the TME on a single-cell level. However, human data on regional differences within the TME remain scarce. Here, we performed high-depth single-cell RNA sequencing (scRNAseq) on paired biopsies from the tumor center, peripheral infiltration zone and blood of five primary GBM patients. Through analysis of >45,000 cells, we revealed a regionally distinct transcription profile of microglia (MG) and monocyte-derived macrophages (MdMs) and an impaired activation signature in the tumor-peripheral cytotoxic-cell compartment. Comparing tumor-infiltrating CD8 + T cells with circulating cells identified CX3CR1 high and CX3CR1 int CD8 + T cells with effector and memory phenotype, respectively, enriched in blood but absent in the TME. Tumor CD8 + T cells displayed a tissue-resident memory phenotype with dysfunctional features. Our analysis provides a regionally resolved mapping of transcriptional states in GBM-associated leukocytes, serving as an additional asset in the effort towards novel therapeutic strategies to combat this fatal disease.
Keyphrases
- single cell
- rna seq
- endothelial cells
- induced apoptosis
- high throughput
- cell cycle arrest
- end stage renal disease
- transcription factor
- newly diagnosed
- dendritic cells
- peripheral blood
- induced pluripotent stem cells
- working memory
- quality improvement
- pluripotent stem cells
- stem cells
- inflammatory response
- prognostic factors
- patient safety
- oxidative stress
- peritoneal dialysis
- spinal cord injury
- optical coherence tomography
- electronic health record
- artificial intelligence
- immune response
- deep learning
- big data
- cell therapy