Heterogeneity and chimerism of endothelial cells revealed by single cell transcriptome in orthotopic liver tumors
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus Homo sapiens
PROVIDER: GSE150226 | GEO | 2020/05/11
REPOSITORIES: GEO
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Project description:The liver is a common host organ for cancer, either through lesions that arise in liver epithelial cells [e.g., hepatocellular carcinoma (HCC)] or as a site of metastasis by tumors arising in other organs (e.g., colorectal cancer). However, the changes that occur in liver stromal cells in response to cancer have not been fully characterized, nor has it been determined whether the different sources of liver cancer induce distinct stromal changes. Here, we performed single-cell profiling of liver stromal cells from mouse models of induced spontaneous liver cancer or implanted colorectal liver metastases, with a focus on tumor endothelial cells (ECs). While ECs in liver tissue adjacent to cancerous lesions (so-called adjacent normal) corresponded to liver zonation phenotypes, their transcriptomes were also clearly altered by the presence of a tumor. In comparison, tumor EC transcriptomes show stronger similarities to venous than sinusoidal ECs. Further, tumor ECs, independent of tumor origin, formed distinct clusters displaying conserved "tip-like" or "stalk-like" characteristics, similar to ECs from subcutaneous tumors. However, they also carried liver-specific signatures found in normal liver ECs, suggesting an influence of the host organ on tumor ECs. Our results document gene expression signatures in ECs in liver cancer and show that the host organ, and not the site of tumor origin (liver versus colorectal), is a primary determinant of EC phenotype. In addition, primarily in tumors, we further defined a cluster of chimeric cells that expressed both myeloid and endothelial cell markers and might play a role in tumor angiogenesis.
| S-EPMC7525283 | biostudies-literature
Project description:Heterogeneity and chimerism of endothelial cells revealed by single cell transcriptome in orthotopic liver tumors
| PRJNA631541 | ENA
Project description:BACKGROUND & AIMS: In approximately 70% of patients with hepatocellular carcinoma (HCC) treated by resection or ablation, disease recurs within 5 years. Although gene expression signatures have been associated with outcome, there is no method to predict recurrence based on combined clinical, pathology, and genomic data (from tumor and cirrhotic tissue). We evaluated gene expression signatures associated with outcome in a large cohort of patients with early stage (Barcelona-Clinic Liver Cancer 0/A), single-nodule HCC and heterogeneity of signatures within tumor tissues. METHODS: We assessed 287 HCC patients undergoing resection and tested genome-wide expression platforms using tumor (n = 287) and adjacent nontumor, cirrhotic tissue (n = 226). We evaluated gene expression signatures with reported prognostic ability generated from tumor or cirrhotic tissue in 18 and 4 reports, respectively. In 15 additional patients, we profiled samples from the center and periphery of the tumor, to determine stability of signatures. Data analysis included Cox modeling and random survival forests to identify independent predictors of tumor recurrence. RESULTS: Gene expression signatures that were associated with aggressive HCC were clustered, as well as those associated with tumors of progenitor cell origin and those from nontumor, adjacent, cirrhotic tissues. On multivariate analysis, the tumor-associated signature G3-proliferation (hazard ratio [HR], 1.75; P = .003) and an adjacent poor-survival signature (HR, 1.74; P = .004) were independent predictors of HCC recurrence, along with satellites (HR, 1.66; P = .04). Samples from different sites in the same tumor nodule were reproducibly classified. CONCLUSIONS: We developed a composite prognostic model for HCC recurrence, based on gene expression patterns in tumor and adjacent tissues. These signatures predict early and overall recurrence in patients with HCC, and complement findings from clinical and pathology analyses. Center and peripheral portions of hepatocellular carcinoma tumors as well as surrounding non-tumor cirrhotic liver tissues were obtained from fresh frozen surgically resected tissues, and isolated total RNA samples were analyzed for genome-wide expression profiles.
2014-03-25 | E-GEOD-56140 | biostudies-arrayexpress
Project description:BACKGROUND & AIMS: In approximately 70% of patients with hepatocellular carcinoma (HCC) treated by resection or ablation, disease recurs within 5 years. Although gene expression signatures have been associated with outcome, there is no method to predict recurrence based on combined clinical, pathology, and genomic data (from tumor and cirrhotic tissue). We evaluated gene expression signatures associated with outcome in a large cohort of patients with early stage (Barcelona-Clinic Liver Cancer 0/A), single-nodule HCC and heterogeneity of signatures within tumor tissues. METHODS: We assessed 287 HCC patients undergoing resection and tested genome-wide expression platforms using tumor (n = 287) and adjacent nontumor, cirrhotic tissue (n = 226). We evaluated gene expression signatures with reported prognostic ability generated from tumor or cirrhotic tissue in 18 and 4 reports, respectively. In 15 additional patients, we profiled samples from the center and periphery of the tumor, to determine stability of signatures. Data analysis included Cox modeling and random survival forests to identify independent predictors of tumor recurrence. RESULTS: Gene expression signatures that were associated with aggressive HCC were clustered, as well as those associated with tumors of progenitor cell origin and those from nontumor, adjacent, cirrhotic tissues. On multivariate analysis, the tumor-associated signature G3-proliferation (hazard ratio [HR], 1.75; P = .003) and an adjacent poor-survival signature (HR, 1.74; P = .004) were independent predictors of HCC recurrence, along with satellites (HR, 1.66; P = .04). Samples from different sites in the same tumor nodule were reproducibly classified. CONCLUSIONS: We developed a composite prognostic model for HCC recurrence, based on gene expression patterns in tumor and adjacent tissues. These signatures predict early and overall recurrence in patients with HCC, and complement findings from clinical and pathology analyses.
2014-03-25 | GSE56140 | GEO
Project description:The goal of this study was to gain insight into the molecular heterogeneity of capillary endothelial cells derived from different organs by microarray profiling of freshly isolated cells and identify transcription factors that may determine the specific gene expression profile of endothelial cells from different tissues. The study focused on heart endothelial cells and presents a validated signature of 31 genes that are highly enriched in heart endothelial cells. Within this signature 5 transcription factors were identified and the optimal combination of these transcription factors was determined for specification of the heart endothelial fingerprint. From three tissue types (mouse brain, heart and liver), we collected five freshly isolated endothelial cell samples each. For each brain sample we pooled RNA from 6 mice. For each heart sample we pooled RNA from 4 mice. For each liver sample we pooled RNA from 2 mice. The three endothelial subtypes were then compared. For each subtype, specific gene profiles were defined by determining the genes that were highly enriched versus the other two endothelial subtypes.
2015-02-19 | E-GEOD-48209 | biostudies-arrayexpress
Project description:Despite the critical role of translation in the multi-level gene expression regulation program that controls the protein abundance, a high-resolution view on the landscapes of gene translation in cancer has been missing. We used the technique of ribosome profiling to dissect the translatomes of human liver tumors and their adjacent normal tissues. Our results, as a novel resource, revealed genome-wide abnormalities of translation efficiencies in tumors and context-dependent non-canonical ORFs.
2019-06-14 | GSE112705 | GEO
Project description:In sprouting angiogenesis, a key process involved in the development and the intravasation of tumor tissues, the growth of vessel sprouts, is determined by migration of single endothelial cells (ECs). This paper presents an on-chip assaying method to investigate the migration of individual ECs by simulating vessel sprouts with microchannels. When chemical stimulus is present, ECs were observed to migrate individually toward the source of factors instead of migrating collectively. The validity of this method is shown by inducing EC migration with glioma cell coculture and culture media doped with vascular endothelial growth factor (VEGF) 165. A positive correlation between cell displacement and VEGF 165 concentration was observed. Difference in migrating ability among cells was reflected by tracking single cells, which could reveal cell heterogeneity in susceptibility to stimulus.
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Project description:Endothelial cells from nine steady state tissues and two regenerating tissues (bone marrow and liver) were intravitally labeld, isolated via flow sorting, and immediately processed for RNA extraction. When of sufficient quality, the RNA was amplified and hybridized. For comparison, Human Emybryonic Stem Cell-derived Endothelial cells (hESC-ECs) were differentiated and isolated based on similarities to the adult mouse counterparts. Endothelial cells were labeled via intravitally labeling of the vascular bed 8 minutes prior to sacrifice with minimally three markers to identify endothelial cells followed by flow sorting.
2013-07-15 | E-GEOD-47067 | biostudies-arrayexpress
Project description:Gastrointestinal stromal tumor (GIST) is the most common mesenchymal tumor of the human gastrointestinal tract. In this study, we performed single-cell RNA sequencing (RNA-seq) on intra- and peri-tumor tissues from GIST patients with the aim of discovering the heterogeneity of tumor cells in GIST and their interactions with other cells. We found four predominating cell types in GIST tumor tissue, including T cells, macrophages, tumor cells, and NK cells. Tumor cells could be clustered into two groups: one was highly proliferating and associated with high risk of metastasis, the other seemed "resting" and associated with low risk. Their clinical relevance and prognostic values were confirmed by RNA-seq of 65 GIST samples. T cells were the largest cell type in our single-cell data. Two groups of CD8+ effector memory (EM) cells were in the highest clonal expansion and performed the highest cytotoxicity but were also the most exhausted among all T cells. A group of macrophages were found polarized to possess both M1 and M2 signatures, and increased along with tumor progression. Cell-to-cell interaction analysis revealed that adipose endothelial cells had high interactions with tumor cells to facilitate their progression. Macrophages were at the center of the tumor microenvironment, recruiting immune cells to the tumor site and having most interactions with both tumor and nontumor cells. In conclusion, we obtained an overview of the GIST microenvironment and revealed the heterogeneity of each cell type and their relevance to risk classifications, which provided a novel theoretical basis for learning and curing GISTs.
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Project description:Intratumoral heterogeneity is an inherent feature of most human cancers and has profound implications for cancer therapy. As a result, there is an emergent need to explore previously unmapped mechanisms regulating distinct subpopulations of tumor cells and to understand their contribution to tumor progression and treatment response. Aberrant platelet-derived growth factor receptor beta (PDGFRβ) signaling in cancer has motivated the development of several antagonists currently in clinical use, including imatinib, sunitinib, and sorafenib. The discovery of a novel ligand for PDGFRβ, platelet-derived growth factor (PDGF)-DD, opened the possibility of a previously unidentified signaling pathway involved in tumor development. However, the precise function of PDGF-DD in tumor growth and invasion remains elusive. Here, making use of a newly generated Pdgfd knockout mouse, we reveal a functionally important malignant cell heterogeneity modulated by PDGF-DD signaling in pancreatic neuroendocrine tumors (PanNET). Our analyses demonstrate that tumor growth was delayed in the absence of signaling by PDGF-DD. Surprisingly, ablation of PDGF-DD did not affect the vasculature or stroma of PanNET; instead, we found that PDGF-DD stimulated bulk tumor cell proliferation by induction of paracrine mitogenic signaling between heterogeneous malignant cell clones, some of which expressed PDGFRβ. The presence of a subclonal population of tumor cells characterized by PDGFRβ expression was further validated in a cohort of human PanNET. In conclusion, we demonstrate a previously unrecognized heterogeneity in PanNET characterized by signaling through the PDGF-DD/PDGFRβ axis.
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