Prognostic Gene Expression Signature in Patients With Distinct Glioma Grades
| Autor: | Abdallah Badou, Dounia Chraa, Saadia Ait Ssi, Souha Sahraoui, Khadija El Azhary, Daniel Olive |
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| Přispěvatelé: | Université Hassan II [Casablanca] (UH2MC), Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC), CHU Ibn Rochd [Casablanca], University Hassan II [Casablanca], NUNES, Jacques A |
| Rok vydání: | 2021 |
| Předmět: |
[SDV.IMM] Life Sciences [q-bio]/Immunology
Immunology Brain tumor [SDV.CAN]Life Sciences [q-bio]/Cancer Biology immune response Transcriptome Lymphocytes Tumor-Infiltrating Immune system [SDV.CAN] Life Sciences [q-bio]/Cancer Glioma Gene expression Biomarkers Tumor Tumor Microenvironment medicine Humans Immunology and Allergy Gene Original Research Brain Neoplasms RC581-607 Prognosis medicine.disease Survival Analysis tumour-infiltrating immune cell Gene Expression Regulation Neoplastic Tumor Escape Multivariate Analysis Cancer research [SDV.IMM]Life Sciences [q-bio]/Immunology biomarker Biomarker (medicine) Immunologic diseases. Allergy |
| Zdroj: | Frontiers in Immunology Frontiers in Immunology, 2021, 12, ⟨10.3389/fimmu.2021.685213⟩ Frontiers in Immunology, Vol 12 (2021) |
| ISSN: | 1664-3224 |
| DOI: | 10.3389/fimmu.2021.685213 |
| Popis: | BackgroundGlioma is the most common type of primary brain tumor in adults. Patients with the most malignant form have an overall survival time of MethodsWe integrated into our study glioma transcriptomic datasets from the Cancer Genome Atlas (TCGA) cohort (154 GBM and 516 LGG patients). LM22 immune signature was built using CIBERSORT. Hierarchical clustering and UMAP dimensional reduction algorithms were applied to identify clusters among glioma patients either in an unsupervised or supervised way. Furthermore, differential gene expression (DGE) has been performed to unravel the top expressed genes among the identified clusters. Besides, we used the least absolute shrinkage and selection operator (LASSO) and Cox regression algorithm to set up the most valuable prognostic factor.ResultsOur study revealed, following gene enrichment analysis, the presence of two distinct groups of patients. The first group, defined as cluster 1, was characterized by the presence of immune cells known to exert efficient antitumoral immune response and was associated with better patient survival, whereas the second group, cluster 2, which exhibited a poor survival, was enriched with cells and molecules, known to set an immunosuppressive pro-tumoral microenvironment. Interestingly, we revealed that gene expression signatures were also consistent with each immune cluster function. A strong presence of activated NK cells was revealed in cluster 1. In contrast, potent immunosuppressive components such as regulatory T cells, neutrophils, and M0/M1/M2 macrophages were detected in cluster 2, where, in addition, inhibitory immune checkpoints, such as PD-1, CTLA-4, and TIM-3, were also significantly upregulated. Finally, Cox regression analysis further corroborated that tumor-infiltrating cells from cluster 2 exerted a significant impact on patient prognosis.ConclusionOur work brings to light the tight implication of immune components on glioma patient prognosis. This would contribute to potentially developing better immune-based therapeutic approaches. |
| Databáze: | OpenAIRE |
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