Df6c55ab-ecf8-4600-b96f-6ae569b3410c - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001006975 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Matrices of counts from single-cell RNA-seq data for 15 samples from patients with ovarian cancer, 5 samples for each of the 3 tumor immune phenotypes (Infiltrated, Excluded and Desert). Dissociated cells from each tumor sample have been sorted to isolate live cells from the 3 compartments: tumor, immune and stromal. Each of the compartments has been analyzed separately by scRNAseq, excluding some desert tumors for which cells from the stromal and immune compartments have been pooled. Sequencing was performed using 10X Genomics Chromium Single Cell platform (v2 Chemistry).
| EGAD00001006974 | EGA
Project description:Cancer cells often metastasize by undergoing an epithelial-mesenchymal transition (EMT). Although abundance of CD8+ T-cells in the tumor microenvironment correlates with improved survival, mesenchymal cancer cells acquire greater resistance to antitumor immunity in some cancers. We hypothesized the EMT modulates the immune response to ovarian cancer. Here we show that cancer cells from infiltrated/inflamed tumors possess more mesenchymal cells, than excluded and desert tumors. We also noted high expression of LGALS3 is associated with EMT in vivo, a finding validated with in vitro EMT models. Dissecting the cellular communications among populations in the tumor revealed that mesenchymal cancer cells in infiltrated tumors communicate through LGALS3 to LAG3 receptor expressed by CD8+ T cells. We found CD8+ T cells express high levels of LAG3, a marker of T cell exhaustion. The results indicate that EMT in ovarian cancer cells promotes interactions between cancer cells and T cells through the LGALS3 - LAG3 axis, which could increase T cell exhaustion in infiltrated tumors, dampening antitumor immunity.
2023-11-07 | GSE247098 | GEO
Project description:We use a laser to implant tumor cells in a regular pattern on the ears of the animal. When GFP expressing tumor cells are implanted in a CD4-Cre Tdtomato mouse we can perform live imaging of red T Cells trafficking in and out of each micro-tumor of the array. Thanks to live imaging we were able to classified each of the implanted tumors as: 1-Rejected tumors (no GFP+ tumor cells anymore but lots of immune cells), 2- Inflamed tumors (GFP+ tumors infiltrated with lots of immune cells), 3-Excluded Tumors (GFP+ tumors with immune cells segregated around the tumor area) or Desert tumors (GFP+ tumor cells without any immune cells). As these tumors are implanted just under the epidermis, we were able to biopsy them out and pool them by categories (Rejected, Inflamed, Excluded and Desert). We froze down biopsies of pooled tumors for each category (Rejected, Inflamed, Excluded and Desert) and extracted DNA. We wish to characterize these 4 kinds of tumors (DNA seq) to evaluate how much tumors grown in the same animals from a clonal KPP tumor cell line differ from each other in terms of mutation load.
2023-02-17 | GSE222540 | GEO
Project description:Diverse tumour immune phenotypes with distinct T cell infiltration patterns result in different responses to cancer immunotherapies. However, the key determinants and biology underpinning these phenotypes remain elusive. Here, we provide a high-resolution dissection of the tumour microenvironment representative of different tumour immune phenotypes. By performing single-cell RNA sequencing (scRNAseq) of the tumour, immune, and stromal compartments from 15 ovarian cancer patients, we characterized the diverse cellular and functional phenotypes, as well as dynamic interplay within and between these components. Infiltrated and excluded tumours markedly differed from desert tumours in several tumour cell intrinsic features, including high interferon response, antigen presentation and oxidative phosphorylation. Moreover, these tumours were characterized by tumour associated macrophage (TAM)-like myeloid subsets, while desert tumours were enriched in myeloid derived suppressive cell (MDSC)-like myeloid subsets. Infiltrated and excluded tumours differed in their T cell composition and fibroblast subsets. While dysfunctional CD8+ GZMB T cells and IL1-activated fibroblasts (IL1 CAFs) were associated with infiltrated tumours, pre-dysfunctional CD8+ GZMK T cells and TGFB-activated fibroblasts (TGFB CAFs) were enriched in excluded tumours. These findings validated in bulk transcriptomic profiles of 1071 ovarian tumours and using in situ hybridization. Furthermore, our study revealed chemokine receptor-ligand interactions within and across compartments as potential mechanisms mediating immune cell infiltration, exemplified by the tumour cell-T cell crosstalk via a CXC16-CXCR6 axis, stromal-immune cell crosstalk via CXCL12/14-CXCR4 signalling, and TAM-like macrophage-T cell crosstalk through CXCR3-CXCL9/10/11 signalling. Our in-depth characterization of the tumour environment and intercellular interactions provides novel insights into potential molecular mechanisms that shape the distinct biology of tumour immune phenotypes. Our findings may inform novel therapeutic strategies for potentially shifting tumours along the immunity continuum to improve clinical benefit from cancer immunotherapies.
| EGAS00001004935 | EGA
Project description:Immunotherapy is applied to breast cancer to resolve the limitations of survival gain in existing treatment modalities. With immunotherapy, a tumor can be classified into immune-inflamed, excluded and desert based on the distribution of immune cells. We assessed the clinicopathological features, each subtype’s prognostic value and differentially expressed proteins between immune subtypes.
2024-06-16 | PXD043902 | Pride
Project description:Mechanisms of immune dysregulation against established tumors are relatively well understood. Much less is known about the role of immune effectors against cancer precursor lesions. Endometrioid and clear cell ovarian tumors may partly derive from endometriosis, a commonly diagnosed chronic inflammatory disease. We performed here the most comprehensive immune gene expression analysis of pelvic inflammation in endometriosis and endometriosis-associated ovarian cancer (EAOC). RNA was extracted from 120 paraffin tissue blocks comprising of normal endometrium (n=32), benign endometriosis (n=30), atypical endometriosis (n=15) and EAOC (n=43). Serous tumors (n=15) were included as non-endometriosis associated controls. The immune microenvironment was profiled using Nanostring and the nCounter® GX Human Immunology Kit, comprising probes for a total of 511 immune genes. Please note that 3 normal endometrium samples did not pass the array quality filtering and therefore excluded in the data analyses.
2015-01-07 | E-GEOD-57545 | biostudies-arrayexpress
Project description:One key barrier to improving efficacy of personalized cancer immunotherapies that are dependent on the tumor antigenic landscape remains patient stratification. While patients with CD3+CD8+ T cell inflamed tumors typically show better response to immune checkpoint inhibitors, it is still unknown if the repertoire of HLA bound peptides presented in highly inflamed and non-inflamed tumors is substantially different. We surveyed 61 tumor regions and adjacent non-malignant lung tissues from eight lung cancer patients and performed deep antigen discovery combining immunopeptidomics, genomics, bulk and spatial transcriptomics and explored the heterogeneous expression and presentation of tumor (neo)antigens. Here we associated diverse immune cell populations with the immunopeptidome in CD3+CD8+ T cell excluded, infiltrated, highly- and lowly-inflamed tumors. We found evidence for lower immune-editing and higher presentation efficiency of tumor-associated antigens in lowly-inflamed and CD3+CD8+ T cell excluded tumors. This could have implications for the choice of combination therapies tailored to the patient’s mutanome and microenvironment.
2023-03-21 | PXD034772 | Pride
Project description:The immune phenotype of a tumor is a key predictor of its response to immunotherapy. Patients who respond to immune checkpoint blockade generally present with tumors infiltrated by T cells, a phenotype referred to as ‘inflamed’. However, not all inflamed tumors respond to therapy, and even lower response rates occur among patients with tumors that lack T cells (‘desert’) or that spatially exclude T cells to the periphery of the tumor lesion (‘excluded’). Despite the importance of these tumor immune phenotypes in patients, little is known about their development, heterogeneity or dynamics due to the technical difficulty of modeling and tracking these features in situ. Here, we introduce STAMP (skin tumor array by microporation), a preclinical approach that combines in vivo high-throughput time-lapse imaging with next generation sequencing of tumor arrays. Using this approach, we follow the early formation of thousands of tumors to show that development of a given immune phenotype is not under strict control of tumor genetics or transcriptional state, but is also influenced by local features of the tumor microenvironment. Only the spatial organization of T cells, specifically early infiltration of T cells recruited by fibroblasts and monocytes into the core of a tumor, was predictive of functional T cell attack and tumor rejection. Evaluating the dynamic immune-history of tumors revealed that early conversion to the immune inflamed phenotype was predictive of therapy-induced or spontaneous tumor regression. Thus, STAMP captures the dynamic and complex relationships of spatial, cellular and molecular components of tumor progression and has the potential to translate therapeutic concepts into successful clinical strategies.
2023-02-17 | GSE223365 | GEO
Project description:The immune phenotype of a tumor is a key predictor of its response to immunotherapy. Patients who respond to immune checkpoint blockade generally present with tumors infiltrated by T cells, a phenotype referred to as ‘inflamed’. However, not all inflamed tumors respond to therapy, and even lower response rates occur among patients with tumors that lack T cells (‘desert’) or that spatially exclude T cells to the periphery of the tumor lesion (‘excluded’). Despite the importance of these tumor immune phenotypes in patients, little is known about their development, heterogeneity or dynamics due to the technical difficulty of modeling and tracking these features in situ. Here, we introduce STAMP (skin tumor array by microporation), a preclinical approach that combines in vivo high-throughput time-lapse imaging with next generation sequencing of tumor arrays. Using this approach, we follow the early formation of thousands of tumors to show that development of a given immune phenotype is not under strict control of tumor genetics or transcriptional state, but is also influenced by local features of the tumor microenvironment. Only the spatial organization of T cells, specifically early infiltration of T cells recruited by fibroblasts and monocytes into the core of a tumor, was predictive of functional T cell attack and tumor rejection. Evaluating the dynamic immune-history of tumors revealed that early conversion to the immune inflamed phenotype was predictive of therapy-induced or spontaneous tumor regression. Thus, STAMP captures the dynamic and complex relationships of spatial, cellular and molecular components of tumor progression and has the potential to translate therapeutic concepts into successful clinical strategies.
2023-02-17 | GSE222585 | GEO
Project description:The immune phenotype of a tumor is a key predictor of its response to immunotherapy1–4. Patients who respond to immune checkpoint blockade generally present with tumors infiltrated by T cells, a phenotype referred to as ‘inflamed’5–7. However, not all inflamed tumors respond to therapy, and even lower response rates occur among patients with tumors that lack T cells (‘desert’) or that spatially exclude T cells to the periphery of the tumor lesion (‘excluded’)8. Despite the importance of these tumor immune phenotypes in patients, little is known about their development, heterogeneity or dynamics due to the technical difficulty of modeling and tracking these features in situ. Here, we introduce STAMP (skin tumor array by microporation), a preclinical approach that combines in vivo high-throughput time-lapse imaging with next generation sequencing of tumor arrays. Using this approach, we follow the early formation of thousands of tumors to show that development of a given immune phenotype is not under strict control of tumor genetics or transcriptional state, but is also influenced by local features of the tumor microenvironment. Only the spatial organization of T cells, specifically early infiltration of T cells recruited by fibroblasts and monocytes into the core of a tumor, was predictive of functional T cell attack and tumor rejection. Evaluating the dynamic immune-history of tumors revealed that early conversion to the immune inflamed phenotype was predictive of therapy-induced or spontaneous tumor regression. Thus, STAMP captures the dynamic and complex relationships of spatial, cellular and molecular components of tumor progression and has the potential to translate therapeutic concepts into successful clinical strategies.
2023-02-17 | GSE222230 | GEO