Single-cell RNA-sequencing of metastatic pancreatic neuroendocrine tumor
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE162708 | GEO | 2021/08/24
REPOSITORIES: GEO
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Project description:Background: Identification and purification of cancer stem cells (CSCs) lead to new therapeutic targets; however, there has been no study to identify and isolated pancreatic neuroendocrine tumor (pNET) CSC. Therefore the clinical significance and its target remain unknown. This study aimed to identify pNET CSCs and characterize therapeutic candidate for pNET CSCs. Methods: We isolated CSCs sorting by ALDH activity in pNET surgical section and cell lines. We verified whether these cells have the property of stemness in vivo and in vitro. Additionally in order to acquire CSC gene profile, genome-wide gene expression profiles were investigated using a microarray technique. Results: ALDHhigh cells, but not control bulk cells, formed spheres, proliferated in hypoxia as well as normoxia and promoted cell motility, which are features of CSCs. Injection of as few as 10 ALDHhigh cells led to subcutaneous tumor formation, and 105 ALDHhigh cells established metastases but not control bulk cells in mice. Comprehensive gene expression analysis revealed that genes associated with mesenchymal stem cell, including CD73, and epithelial-mesenchymal transition (EMT) were overexpressed in ALDHhigh cells. APCP, which is CD73 inhibitor, inhibited sphere formation and cell motility in ALDHhigh cells in vitro, and tumor growth inhibition were observed in ALDHhigh cells in vivo. Conclusions: We identified ALDHhigh cells of pNET and elucidated that they have stemness property. Furthermore we identified CD73 as a target of ALDHhigh cells. CD73 is a promising novel target of pNET CSCs.
2016-05-23 | GSE62079 | GEO
Project description:We report the application of single-molecule-based sequencing technology for high-throughput profiling of RNAs in human pancreatic neuroendocrine tumor (PNET) tissues. We analyzed the transcriptome maps of primary tumor sites from patients that presented metastasis or not (localized). This analysis revelaed that the immune cell and pathway-related molecular signatures were enriched in metastatic compared to localized tumors. Given the wide change of gene expression in metastatic PNETs, we analyzed the RNA-seq data using a L1000 drug-induced signature to identify pharmacologic agents that might preferentially target metastatic disease. In a separate study, we analyzed our RNA-seq data to understand the molecular basis of sexual dimorphisms in PNETs. We found that PNETs are associated with the emergence of unique sex-specific transcriptomic differences that are not observed in non-neoplastic pancreatic islet tissues.
2022-06-30 | GSE178398 | GEO
Project description:We aimed to study the interaction of PNETs and pancreatic stellate cells (PSCs) in PNET progression through exploring specific gene expression of PNETs cultured with conditional media of PSCs.
2024-02-22 | GSE167321 | GEO
Project description:Mechanisms of neuroendocrine tumor (NET) proliferation are poorly understood and therapies that effectively control NET progression and metastatic disease are limited. We found amplification of a putative oncogene, RABL6A, in primary human pancreatic NETs (PNETs) that correlated with high level RABL6A protein expression. Consistent with those results, stable silencing of RABL6A in cultured BON-1 PNET cells revealed that it is essential for their proliferation and survival. Cells lacking RABL6A predominantly arrested in G1 phase with a moderate mitotic block. Pathway analysis of microarray data suggested activation of the p53 and retinoblastoma (Rb1) tumor suppressor pathways in the arrested cells. Specific inactivation of p53 had no effect on the RABL6A knockdown phenotype, indicating RABL6A functions independent of p53 in this setting. By comparison, Rb1 inactivation restored G1 to S phase progression in RABL6A knockdown cells although it was insufficient to override the mitotic arrest and cell death caused by RABL6A loss. Thus, RABL6A promotes G1 progression in PNET cells by inactivating Rb1, an established suppressor of PNET proliferation and development. This work identifies RABL6A as a new negative regulator of Rb1 that is essential for PNET proliferation and survival. We suggest RABL6A is a new potential biomarker and target for anticancer therapy in PNET patients. Total RNA obtained from human BON-1 PNET cells with RABL6A shRNA knockdown compared to BON-1 cells expressing control vector.
2014-07-01 | E-GEOD-53778 | biostudies-arrayexpress
Project description:Mechanisms of neuroendocrine tumor (NET) proliferation are poorly understood and therapies that effectively control NET progression and metastatic disease are limited. We found amplification of a putative oncogene, RABL6A, in primary human pancreatic NETs (PNETs) that correlated with high level RABL6A protein expression. Consistent with those results, stable silencing of RABL6A in cultured BON-1 PNET cells revealed that it is essential for their proliferation and survival. Cells lacking RABL6A predominantly arrested in G1 phase with a moderate mitotic block. Pathway analysis of microarray data suggested activation of the p53 and retinoblastoma (Rb1) tumor suppressor pathways in the arrested cells. Specific inactivation of p53 had no effect on the RABL6A knockdown phenotype, indicating RABL6A functions independent of p53 in this setting. By comparison, Rb1 inactivation restored G1 to S phase progression in RABL6A knockdown cells although it was insufficient to override the mitotic arrest and cell death caused by RABL6A loss. Thus, RABL6A promotes G1 progression in PNET cells by inactivating Rb1, an established suppressor of PNET proliferation and development. This work identifies RABL6A as a new negative regulator of Rb1 that is essential for PNET proliferation and survival. We suggest RABL6A is a new potential biomarker and target for anticancer therapy in PNET patients.
2014-07-01 | GSE53778 | GEO
Project description:Patients with rare pancreatic neuroendocrine tumors (pNETs) have limited access to effective targeted agents and invariably succumb to progressive disease. MUC1-C is a druggable oncogenic protein linked to driving pan-cancers. There is no known involvement of MUC1-C in pNET progression. The present work was performed to determine if MUC1-C represents a potential target for advancing pNET treatment. We demonstrate that the MUC1 gene is upregulated in primary pNETs that progress with metastatic disease. In pNET cells, MUC1-C drives E2F- and MYC-signaling pathways necessary for survival. Targeting MUC1-C genetically and pharmacologically also inhibits self-renewal capacity and tumorigenicity. Studies of primary pNET tissues further demonstrate that MUC1-C expression associates with (i) advanced NET grade and pathological stage, (ii) metastatic disease, and (iii) decreased disease-free survival. These findings demonstrate that MUC1-C is necessary for pNET progression and is a novel target for treating these rare cancers with anti-MUC1-C agents under clinical development.
2024-05-21 | GSE267722 | GEO
Project description:Proteomic and signaling alterations among cells isolated from three sites of metastasis (liver, lung and peritoneum) from a single patient were studied using a SILAC-based quantitative proteomic strategy combined with a high resolution mass spectrometry.
2014-08-13 | PXD000750 | Pride
Project description:Metastasis occurs frequently after resection of pancreatic cancer (PaC). We hypothesized that multiparametric analysis of pre-metastatic liver biopsies will classify patients according to their metastatic risk, timing, and organ site. Liver biopsies obtained during pancreatectomy from 49 patients with localized PaC and 19 control patients with non-cancerous pancreatic lesions were analyzed combining metabolomic, tissue and single cell transcriptomics, and multiplex imaging approaches. Patients were followed prospectively (median three years) and classified into four recurrence groups; early (<6 months post resection) or late (>6 months post resection) liver metastasis (LiM), extrahepatic (EHM) metastasis, and disease-free survivors (NED). Overall, PaC livers exhibited signs of augmented inflammation, compared to controls. Enrichment of neutrophil extracellular traps (NETs), Ki-67 upregulation, and decreased liver creatine significantly distinguished those with future metastasis from NED. Patients with future LiM were characterized by scant T cell lobular infiltration, less steatosis, and higher levels of citrullinated H3, compared to patients who developed EHM metastasis, who had overexpression of interferon target genes (MX1, NR1D1) and an increase of CD11B+ NK cells. Upregulation of sortilin-1 and prominent NETs, together with the lack of T cells and a reduction in CD11B+ NK cells, differentiated patients with early-onset from those with late-onset LiM. Liver profiles of NED closely resembled those of controls. Using the above parameters, a machine learning-based model was developed that successfully predicted the metastatic outcome at the time of surgery with 78% accuracy. Therefore, multiparametric profiling of liver biopsies at the time of PaC diagnosis may determine metastatic risk and organotropism, and guide clinical stratification for optimal treatment selection.
2024-06-28 | GSE267209 | GEO
Project description:Metastasis occurs frequently after resection of pancreatic cancer (PC). We hypothesized that multiparametric analysis of pre-metastatic liver biopsies will classify patients according to their metastatic risk, timing, and organ site. Liver biopsies obtained during pancreatectomy from 49 patients with localized PC and 18 control patients with non-cancerous pancreatic lesions were analyzed combining metabolomic, tissue and single cell transcriptomics, and multiplex imaging approaches. Patients were followed prospectively (median three years) and classified into four recurrence groups; early (<6 months post resection) or late (>6 months post resection) liver metastasis (LM), extrahepatic (EH) metastasis, and disease-free survivors (NED). Overall, PC livers exhibited signs of augmented inflammation, compared to controls. Enrichment of neutrophil extracellular traps (NETs), Ki-67 upregulation, and decreased liver creatine significantly distinguished those with future metastasis from NED. Patients with future LM were characterized by scant T cell lobular infiltration, less steatosis, and higher levels of citrullinated H3, compared to patients who developed EH metastasis, who had overexpression of interferon target genes (MX1, NR1D1) and an increase of CD11B+ NK cells. Upregulation of sortilin-1 and prominent NETs, together with the lack of T cells and a reduction in CD11B+ NK cells, differentiated patients with early-onset from those with late-onset LM. Liver profiles of NED closely resembled those of controls. Using the above parameters, a machine learning-based model was developed that successfully predicted the metastatic outcome at the time of surgery with 78% accuracy. Therefore, multiparametric profiling of liver biopsies at the time of PC diagnosis may determine metastatic risk and organotropism, and guide clinical stratification for optimal treatment selection.
2024-06-28 | GSE245535 | GEO
Project description:Single-cell RNA-sequencing of metastatic pancreatic neuroendocrine tumor
| PRJNA682637 | ENA