Classified T-cell-based Single-Cell RNA Sequencing Analysis of a Human Glioblastoma Multiforme (GBM) Dataset
Laboratory Genetics and Genomics
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Primary Categories:
- Genomic Medicine
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Secondary Categories:
- Genomic Medicine
Introduction:
Glioblastoma multiforme (GBM) is the most aggressive form of central nervous system tumor known to humans. The average prognosis from the time of diagnosis is 15 to 18 months. The complexity and heterogeneity of the tumor often requires a deeper level analysis of the tumor. Single-Cell RNA sequencing analysis is a method through which the genomic architectural profile can be depicted. While depicting the transcriptomic architecture of the tumor is one way to understand the landscape of tumor composition, profiling immune cells is another way to characterize the tumor microenvironment at the micro-level. In this study, we aim to delineate different types of T-cells and their dispersion in GBM tumors.
Methods:
The sample data of four patients’ GBM tumor core and peripheral tissue was explored using Trailmaker. The Ensemble IDs of the 39 genes (i.e. ITGAE, CD69, CXCR6, MYADM, and more) were converted to gene names using g:Profiler, and further categorized into different T cell types (naïve, effector, effector memory, central memory, residential memory, exhausted, resting regulatory, effector regulatory, and Th1-like). The genes were plotted together using continuous embedding and analyzed for their location and dispersion. UMAP was used as a dimension reduction technique to visualize cell clusters.
Results:
Most of the T-cell-related-gene containing cells were localized to the upper right quadrant of the UMAP. For instance, the genes that were identified with residential memory T-cells, namely CD69, ITGAE, CXCR6, and MYADM, were mostly shown in the upper right region of the UMAP. Meanwhile, MYADM was particularly notable in other clusters as well, indicating the versatility and the lack of specificity of that specific gene toward T-cells in this sample population. Simultaneously, FOXP3, a well-recognized transcription factor in regulatory T-cells (both resting and effector) showed minimal expression providing an understanding of the minimal role of regulatory T-cells in the tumor microenvironment.
Conclusion:
This analysis provided an insight on the location and dispersion of the different cells that expressed various types of genes characterizing them as immune cells, particularly various types of T cells. Further investigation is warranted to depict a generalizable genomic architecture of the immune cells within the tumor microenvironment within human GBM.
Glioblastoma multiforme (GBM) is the most aggressive form of central nervous system tumor known to humans. The average prognosis from the time of diagnosis is 15 to 18 months. The complexity and heterogeneity of the tumor often requires a deeper level analysis of the tumor. Single-Cell RNA sequencing analysis is a method through which the genomic architectural profile can be depicted. While depicting the transcriptomic architecture of the tumor is one way to understand the landscape of tumor composition, profiling immune cells is another way to characterize the tumor microenvironment at the micro-level. In this study, we aim to delineate different types of T-cells and their dispersion in GBM tumors.
Methods:
The sample data of four patients’ GBM tumor core and peripheral tissue was explored using Trailmaker. The Ensemble IDs of the 39 genes (i.e. ITGAE, CD69, CXCR6, MYADM, and more) were converted to gene names using g:Profiler, and further categorized into different T cell types (naïve, effector, effector memory, central memory, residential memory, exhausted, resting regulatory, effector regulatory, and Th1-like). The genes were plotted together using continuous embedding and analyzed for their location and dispersion. UMAP was used as a dimension reduction technique to visualize cell clusters.
Results:
Most of the T-cell-related-gene containing cells were localized to the upper right quadrant of the UMAP. For instance, the genes that were identified with residential memory T-cells, namely CD69, ITGAE, CXCR6, and MYADM, were mostly shown in the upper right region of the UMAP. Meanwhile, MYADM was particularly notable in other clusters as well, indicating the versatility and the lack of specificity of that specific gene toward T-cells in this sample population. Simultaneously, FOXP3, a well-recognized transcription factor in regulatory T-cells (both resting and effector) showed minimal expression providing an understanding of the minimal role of regulatory T-cells in the tumor microenvironment.
Conclusion:
This analysis provided an insight on the location and dispersion of the different cells that expressed various types of genes characterizing them as immune cells, particularly various types of T cells. Further investigation is warranted to depict a generalizable genomic architecture of the immune cells within the tumor microenvironment within human GBM.