Multimodal Mapping of the Immune Landscape in Human Pancreatic Cancer
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PROVIDER: PRJNA649823 | ENA |
REPOSITORIES: ENA
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Project description:Multimodal Mapping of the Immune Landscape in Human Pancreatic Cancer
| PRJNA649824 | ENA
Project description:Multimodal Mapping of the Tumor and Peripheral Blood Immune Landscape in Human Pancreatic Cancer
| PRJNA655238 | ENA
Project description:This is a human single cell sequencing repository of pancreatic cancer tumor tissue and PBMCs of pancreatic cancer patients. The goal of this study was to thorough map the immune landscape of pancreatic ductal adenocarinoma patient tumors and peripheral blood.
2020-10-01 | GSE155698 | GEO
Project description:Pancreatic ductal adenocarcinoma (PDA) is characterized by an immune-suppressive tumor microenvironment that renders it largely refractory to immunotherapy. We implemented a multimodal analysis approach to elucidate the immune landscape in PDA. Using a combination of CyTOF, single-cell RNA sequencing, and multiplex immunohistochemistry on patient tumors, matched blood, and non-malignant samples, we uncovered a complex network of immune-suppressive cellular interactions. These experiments revealed heterogeneous expression of immune checkpoint receptors in individual patient's T cells and increased markers of CD8+ T cell dysfunction in advanced disease stage. Tumor-infiltrating CD8+ T cells had an increased proportion of cells expressing an exhausted expression profile that included upregulation of the immune checkpoint TIGIT, a finding that we validated at the protein level. Our findings point to a profound alteration of the immune landscape of tumors, and to patient-specific immune changes that should be taken into account as combination immunotherapy becomes available for pancreatic cancer.
| S-EPMC8294470 | biostudies-literature
Project description:Pancreatic ductal adenocarcinoma (PDAC) has complex tumor immune microenvironment (TIME), the clinical values of which remains to be explored. This study aimed to delineate the immune landscape of PDAC and determine the clinical value of immune features in TIME. There was a significant difference in immune profiles between PDAC and adjacent normal pancreatic tissues. Several novel immune features were captured by quantitative pathology analysis on mIHC, some of which were significantly correlated to the prognosis of PDAC patients. A risk score-based prognostic model was developed according to these immune features. We also drew a user-friendly nomogram plot to predict the overall survival of patients by combining risk score and clinicopathologic features. Both mIHC and scRNA-seq analyses showed the expression of PD-L1 was scarce in PDAC. We found that PD1+ cells were distributed in different T cell subpopulations, not enriched in a specific subpopulation. In addition, there were other conserved receptor-ligand pairs (CCL5-SDC1/4) besides PD1-PD-L1 interaction between PD1+ T cells and PD-L1+ tumor cells. Our findings reveal the immune landscape of PDAC and highlight the significant value of combined application of mIHC and scRNA-seq in uncovering TIME, which might provide new clues for developing immunotherapy strategies.
2022-09-13 | GSE212966 | GEO
Project description:Chordomas are cancers from the axial skeleton presenting immunological hallmarks of unknown significance. In recent years, some clinical trials demonstrated that chordomas can respond to immunotherapy. We present a comprehensive characterisation of immunological features of 76 chordomas through application of a multimodal approach comprising transcriptional profiling, multidimensional immunophenotyping and TCR profiling. Chordomas generally presented an immune “hot” microenvironment in comparison to other sarcomas, as indicated by the immunologic constant of rejection transcriptional signature. We identified two distinct groups of chordomas based on T cell infiltration. The highly infiltrated group was further characterised by high dendritic cell infiltration and the presence of multicellular immune aggregates in tumours, whereas low T cell infiltration was associated with lower overall cell densities of immune and stromal cells. Interestingly, patients with higher T cell infiltration displayed a more pronounced clonal enrichment of the T cell receptor repertoire compared to those with low T cell counts. Furthermore, we observed that the majority of chordomas maintained HLA class I expression. Our findings shed light on the natural immunity against chordomas. Understanding their immune landscape could guide the development and application of immunotherapies in a tailored manner, ultimately leading to an improved clinical outcome for chordoma patients.
2024-01-26 | GSE239531 | GEO
Project description:Atherosclerotic plaques are complex tissues composed of a heterogeneous mixture of cells. However, our understanding of the comprehensive transcriptional and phenotypical landscape of the cells within these lesions is limited. To characterize the landscape of human carotid atherosclerosis in greater detail, we combined cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) and single-cell RNA sequencing (scRNA-seq) to classify all cell types within lesions (n=21; 13 symptomatic) to achieve a comprehensive multimodal understanding of the cellular identities of atherosclerosis and their association with clinical pathophysiology. We identified 25 cell populations, each with a unique multi-omic signature, including macrophages, T cells, NK cells, mast cells, B cells, plasma cells, neutrophils, dendritic cells, endothelial cells, fibroblasts, and smooth muscle cells (SMCs). Among the macrophages, we identified 2 proinflammatory subsets enriched in IL1B or C1Q expression, 2 TREM2 positive foam cells (one expressing inflammatory genes), and subpopulations with a proliferative gene signature and SMC-specific gene signature with fibrotic pathways upregulated. Further characterization revealed various subsets of SMCs and fibroblasts, including SMC-derived foam cells. These foamy SMCs were localized in the deep intima of coronary atherosclerotic lesions. Utilizing CITE-seq data, we developed a flow cytometry panel, using cell surface proteins CD29, CD142, and CD90, to isolate SMC-derived cells from lesions. Lastly, we observed reduced proportions of efferocytotic macrophages, classically activated endothelial cells, and contractile and modulated SMC-derived cells, while inflammatory SMCs were enriched in plaques of clinically symptomatic vs asymptomatic patients. Our multimodal atlas of cell populations within atherosclerosis provides novel insights into the diversity, phenotype, location, isolation, and clinical relevance of the unique cellular composition of human carotid atherosclerosis. These findings facilitate both the mapping of cardiovascular disease susceptibility loci to specific cell types as well as the identification of novel molecular and cellular therapeutic targets for the treatment of the disease.
2024-04-12 | GSE253902 | GEO
Project description:Atherosclerotic plaques are complex tissues composed of a heterogeneous mixture of cells. However, our understanding of the comprehensive transcriptional and phenotypical landscape of the cells within these lesions is limited. To characterize the landscape of human carotid atherosclerosis in greater detail, we combined cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) and single-cell RNA sequencing (scRNA-seq) to classify all cell types within lesions (n=21; 13 symptomatic) to achieve a comprehensive multimodal understanding of the cellular identities of atherosclerosis and their association with clinical pathophysiology. We identified 25 cell populations, each with a unique multi-omic signature, including macrophages, T cells, NK cells, mast cells, B cells, plasma cells, neutrophils, dendritic cells, endothelial cells, fibroblasts, and smooth muscle cells (SMCs). Among the macrophages, we identified 2 proinflammatory subsets enriched in IL1B or C1Q expression, 2 TREM2 positive foam cells (one expressing inflammatory genes), and subpopulations with a proliferative gene signature and SMC-specific gene signature with fibrotic pathways upregulated. Further characterization revealed various subsets of SMCs and fibroblasts, including SMC-derived foam cells. These foamy SMCs were localized in the deep intima of coronary atherosclerotic lesions. Utilizing CITE-seq data, we developed a flow cytometry panel, using cell surface proteins CD29, CD142, and CD90, to isolate SMC-derived cells from lesions. Lastly, we observed reduced proportions of efferocytotic macrophages, classically activated endothelial cells, and contractile and modulated SMC-derived cells, while inflammatory SMCs were enriched in plaques of clinically symptomatic vs asymptomatic patients. Our multimodal atlas of cell populations within atherosclerosis provides novel insights into the diversity, phenotype, location, isolation, and clinical relevance of the unique cellular composition of human carotid atherosclerosis. These findings facilitate both the mapping of cardiovascular disease susceptibility loci to specific cell types as well as the identification of novel molecular and cellular therapeutic targets for the treatment of the disease.
2024-04-12 | GSE253903 | GEO
Project description:Surgery still remains the mainstay of treatment for localized colorectal cancer. However, nearly 30% of patients with localized colorectal cancer (stage II and stage III) will present with recurrence. Tumor progression is mediated by both intrinsic genetic changes and by extrinsic epigenetic and host environmental factors, including interactions with the immune system. Several studies demonstrated that tumor infiltrating memory T-cells and type, density and location of infiltrating T cells are better predictors of disease-free survival in patients with CRC compared to the standard TNM staging. These data suggest that tumor invasion and progression are more accurately predicted by immune response in the primary tumor. In addition, mismatch repair (MMR)-deficient tumors are characterized a priori by a higher frequency of tumor infiltrating lymphocytes and are associated with significantly improved prognosis. Recently, Stotz et al showed that the preoperative lymphocyte to monocyte ratio in peripheral blood samples predicts clinical outcome in patients with stage III colon cancer. So far there is no comprehensive analysis of the immune-landscape in CRC.
The aim of the current project is to identify a comprehensive panel of immunomarkers in localized colorectal cancer (stage II and stage III) applicable for the detection of patients at high risk of recurrence. For the first time, specific tumor-infiltrating immune cells, mismatch repair protein expression in tumor tissue and preoperative blood based inflammatory markers from routine blood counts in corresponding peripheral blood samples and known clinicopathological features will be correlated with outcome in 300 localized CRC patients.
| 2166592 | ecrin-mdr-crc
Project description:The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single-cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce ‘weighted-nearest neighbor’ analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity.
2021-01-15 | GSE164378 | GEO