Immune microenvironments differ in immune characteristics and outcome of glioblastoma multiforme
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PROVIDER: PRJNA505674 | ENA |
REPOSITORIES: ENA
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Project description:Understanding the interactions between tumors and the host immune system holds great promise to uncover biomarkers for targeted therapies, predict the prognosis of patients and guide clinical treatment. However, the immune signatures of glioblastoma multiforme (GBM) remain largely unstudied in terms of systematic analyses. We aimed to classify GBM samples according to immune-related genes and complement the existing immunotherapy system knowledge. In this study, we designed a strategy to identify 3 immune subtypes representing 3 different immune microenvironments (M1-M3) and associated with prognosis. The three subtypes were significantly different in terms of specific immune characteristics (immune cell subpopulations, immune responses, immune cells and checkpoint gene interactions). In additional, somatic alterations and methylation changes were identified that correlated with genes related to a worse prognosis subtype in the microenvironment. More importantly, in M3 (worst prognosis subtype) and M2 (best prognosis subtype), the interaction between immune cells and checkpoint genes was different, and this had an important effect on the prognosis. Finally, we used risk scores of immune cells and checkpoint genes to evaluate the prognosis of GBM patients and validated the results with 3 independent datasets. Disordered interactions between immune cells and checkpoint genes result in a change in the immune microenvironment and affects the prognosis of patients. We propose that a better understanding of the immune microenvironment of advanced cancers may provide new insights into immunotherapy.
2019-06-20 | GSE122586 | GEO
Project description:Understanding the interactions between tumors and the host immune system holds great promise to uncover biomarkers for targeted therapies, predict the prognosis of patients and guide clinical treatment. However, the immune signatures of glioblastoma multiforme (GBM) remain largely unstudied in terms of systematic analyses. We aimed to classify GBM samples according to immune-related genes and complement the existing immunotherapy system knowledge. In this study, we designed a strategy to identify 3 immune subtypes representing 3 different immune microenvironments (M1-M3) and associated with prognosis. The 3 subtypes were significantly different in terms of specific immune characteristics (immune cell subpopulations, immune responses, immune cells, and checkpoint gene interactions). In additional, copy number variations and methylation changes were identified that correlated with genes related to a worse prognosis subtype in the microenvironment. More importantly, in M3 (worst prognosis subtype) and M2 (best prognosis subtype), the interaction between immune cells and checkpoint genes was different, which had an important effect on the prognosis. Finally, we used risk scores of immune cells and checkpoint genes to evaluate the prognosis of GBM patients and validated the results with 3 independent datasets. Disordered interactions between immune cells and checkpoint genes result in a change in the immune microenvironment and affects the prognosis of patients. We propose that a better understanding of the immune microenvironment of advanced cancers may provide new insights into immunotherapy.
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Project description:Interaction of hematopoietic progenitors with the thymic stromal microenvironment induces them to proliferate, adopt the T cell fate, and asymmetrically diverge into multiple T lineages. Progenitors at various developmental stages are stratified among different regions of the thymus, implying that the corresponding microenvironments differ from one another, and provide unique sets of signals to progenitors migrating between them. The nature of these differences remains undefined. Here we use novel physical and computational approaches to characterize these stromal subregions, distinguishing gene expression in microdissected tissues from that of their lymphoid constituents. Using this approach, we comprehensively map gene expression in functionally distinct stromal microenvironments, and identify clusters of genes that define each region. Quite unexpectedly, we find that the central cortex lacks distinctive features of its own, and instead appears to function by sequestering unique microenvironments found at the cortical extremities, and modulating the relative proximity of progenitors moving between them. 4 to 6 weeks old male C57bl6/J were used for microdissection of 3 thymic cortical subregions and thymic medulla or for sorting cortical and medullary thymocytes. These samples were used for subsequent RNA purification, labeling and hybridization to Affymetrix arrays
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Project description:Congenital glioblastoma multiforme (cGBM) historically has been considered an aggressive tumor of infancy requiring extensive chemotherapy to achieve cure. We report on 4 patients at our institution with cGBMs who were treated with surgery and chemotherapy (carboplatin and etoposide every 21 days for 2-6 cycles). Four of four patients are progression free at a median time of 27.5 months (22-103 months). To characterize the molecular biology of cGBM, we compared the gene expression profiles of 3 cGBMs to 12 pediatric and 6 primary adult glioblastomas collected at our institution. Unsupervised hierarchical clustering showed cGBMs grouped together with other high-grade gliomas. cGBMs demonstrated marked similarity to both pediatric and adult GBMs, with only a total of 31 differentially expressed genes identified (FDR < 0.05). Unique molecular features of congenital GBMs identified included over-expression of multiple genes involved in glucose metabolism and tissue hypoxia pathways. Four tyrosine kinases were also mong the up-regulated genes (RET, RASGRF2, EFNA5, ALK). Thus, at our institution congenital GBMs, while similar both histologically and molecularly to other GBMs, appear to have a good prognosis with surgery in combination with relatively moderate chemotherapy. Further study is needed to determine if the few gene expression differences that were identified may contribute to the better survival seen in these tumors compared to pediatric or adult GBMs. Key Words: glioblastoma; congenital; pediatric; gene expression; microarray
2012-05-21 | GSE32374 | GEO
Project description:Interaction of hematopoietic progenitors with the thymic stromal microenvironment induces them to proliferate, adopt the T cell fate, and asymmetrically diverge into multiple T lineages. Progenitors at various developmental stages are stratified among different regions of the thymus, implying that the corresponding microenvironments differ from one another, and provide unique sets of signals to progenitors migrating between them. The nature of these differences remains undefined. Here we use novel physical and computational approaches to characterize these stromal subregions, distinguishing gene expression in microdissected tissues from that of their lymphoid constituents. Using this approach, we comprehensively map gene expression in functionally distinct stromal microenvironments, and identify clusters of genes that define each region. Quite unexpectedly, we find that the central cortex lacks distinctive features of its own, and instead appears to function by sequestering unique microenvironments found at the cortical extremities, and modulating the relative proximity of progenitors moving between them.
2009-11-24 | GSE18281 | GEO
Project description:Congenital glioblastoma multiforme (cGBM) historically has been considered an aggressive tumor of infancy requiring extensive chemotherapy to achieve cure. We report on 4 patients at our institution with cGBMs who were treated with surgery and chemotherapy (carboplatin and etoposide every 21 days for 2-6 cycles). Four of four patients are progression free at a median time of 27.5 months (22-103 months). To characterize the molecular biology of cGBM, we compared the gene expression profiles of 3 cGBMs to 12 pediatric and 6 primary adult glioblastomas collected at our institution. Unsupervised hierarchical clustering showed cGBMs grouped together with other high-grade gliomas. cGBMs demonstrated marked similarity to both pediatric and adult GBMs, with only a total of 31 differentially expressed genes identified (FDR < 0.05). Unique molecular features of congenital GBMs identified included over-expression of multiple genes involved in glucose metabolism and tissue hypoxia pathways. Four tyrosine kinases were also mong the up-regulated genes (RET, RASGRF2, EFNA5, ALK). Thus, at our institution congenital GBMs, while similar both histologically and molecularly to other GBMs, appear to have a good prognosis with surgery in combination with relatively moderate chemotherapy. Further study is needed to determine if the few gene expression differences that were identified may contribute to the better survival seen in these tumors compared to pediatric or adult GBMs. Key Words: glioblastoma; congenital; pediatric; gene expression; microarray Molecular profiling of 18 AT/RT patient tumor samples was performed using Affymetrix U133 Plus2 GeneChips. Data were background corrected and normalized using gcRMA (as implemented in Bioconductor). Unsupervised agglomerative hierarchical clustering was performed to identify subsets of AT/RTs with similar gene expression. Limma (moderated t-tests; Bioconductor) was used to identify signature genes for each cluster. Bioinformatics web tool DAVID was used to identify enriched biological processes for each cluster. Survival was analyzed using Kaplan-Meier curves and Cox Hazard Ratio. Bioinformatics tools Gene Set Enrichment (GSEA) and Ingenuity Pathways Analysis were also used to gain further insight into cluster differences.
2012-05-20 | E-GEOD-32374 | biostudies-arrayexpress
Project description:Distinct immune microenvironments between primary and paired metastatic tumors in gastric cancer patients
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Project description:We present an exceptional responder case of a patient with high-grade serous ovarian cancer, treated with multiple chemotherapy regimens, who exhibited regression of some metastatic lesions with concomitant progression of other lesion during a treatment-free period. Using an immunogenomics approach, we found that progressing metastases were infiltrated by CD8+ and CD4+ T cells, exhibited oligoclonal expansion of specific T-cell subsets, and showed indications of neoepitope depletion. These findings imply that multiple distinct tumor immune microenvironments co-exist within a single individual and may explain in part the heterogenous fates of metastatic lesions often observed in the clinic post therapy. The goal of this particular experiment was quantify RNA expression using microarrays, and then evaluate differentially expressed genes and pathways between the different tumor samples.
2017-07-14 | GSE92780 | GEO