Expression profile of Gastro-Entero-Pancreatic Neuroendocrine Tumors (GEP-NET)
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE98894 | GEO | 2018/02/25
REPOSITORIES: GEO
Similar Datasets
Project description:Part I - SI-NET tumors High Resolution Isoelectric Focusing (HiRIEF) LC-MS and relative quantification by iTRAQ 8-plex was used to analyze 14 small intestinal neuroendocrine tumors (SI-NETs). The data was obtained from two separate TMT10plex sets and linked by a single internal pooled standard. The internal pooled standard was made by combining equal aliquots of the tryptic peptide mixtures from each of the 14 tissue samples. iTRAQ set1 was composed of 7 SI-NET samples, all from different individuals, and internal pooled standard labelled as follows: Channel 113 (sample Screen-1 with liver metastasis), Channel 114 (sample Screen-8 with liver metastasis), Channel 115 (sample Screen-3 with liver metastasis), Channel 116 (sample Screen-2 with liver metastasis), Channel 117 (sample Screen-5 no liver metastasis), Channel 118 (sample Screen-4 no liver metastasis), Channel 119 (sample Screen-10 no liver metastasis), Channel 121 (internal pooled standard). iTRAQ set2 was composed of 7 SI-NET samples, all from different individuals, and internal pooled standard labelled as follows: Channel 113 (sample Screen-7 with liver metastasis), Channel 114 (sample Screen-11 with liver metastasis), Channel 115 (sample Screen-13 with liver metastasis), Channel 116 (sample Screen-6 no liver metastasis), Channel 117 (sample Screen-12 no liver metastasis), Channel 118 (sample Screen-9 no liver metastasis), Channel 119 (sample Screen-14 no liver metastasis), Channel 121 (internal pooled standard). Part II - time course profiling in cell lines High Resolution Isoelectric Focusing (HiRIEF) LC-MS and relative quantification by TMT 10-plex was used to analyze cellular response to the neddylation inhibitor pevonedistat (MLN4924) at different timepoints in two SI-NET (small intestinal neuroendocrine tumors) cell lines. The data was obtained from two separate TMT 10-plex experiments. TMT set1 includes a time course experiment upon pevonedistat treatment of CNDT2 cells with harvests at 2h, 6h, 12h and 24h after treatment as well as of untreated control cells. Isobaric tag labelling of peptide samples with TMT10plex was used as follows. Biological duplicate controls (TMT channels 126, 127N), duplicate 2h (127C, 128N), duplicate 6h (128C, 129N), duplicate 12h (129C, 130N) and duplicate 24h (130C, 131) samples were employed. TMT set2 includes a time course experiment upon pevonedistat treatment of HC45 cells with harvests at 2h, 6h, 12h and 24h after treatment as well as of untreated control cells. Isobaric tag labelling of peptide samples with TMT10plex was used as follows. Biological duplicate controls (TMT channels 126, 127N), duplicate 2h (127C, 128N), duplicate 6h (128C, 129N), duplicate 12h (129C, 130N) and duplicate 24h (130C, 131) samples were employed.
2020-12-09 | PXD009877 | Pride
Project description:This study aims to elucidate the transcriptomic changes and metabolic reprogramming in gastroenteropancreatic neuroendocrine tumor (GEP-NET) cells following PIKfyve inhibition, using both genetic (CRISPR-mediated knockdown) and pharmacological (Apilimod treatment) approaches. The research focuses on the impact of PIKfyve inhibition on lipid metabolism, cholesterol homeostasis, and mTOR signaling in QGP-1, BON-1, and GOT-1 cell lines. By analyzing RNA sequencing data from these experimental conditions, we seek to identify differentially expressed genes and enriched pathways associated with PIKfyve inhibition. This investigation is part of a broader effort to develop novel combination therapies that could potentially overcome resistance to mTOR inhibitors, the current standard of care for advanced GEP-NETs. The study's findings may provide insights into the therapeutic potential of targeting PIKfyve-driven lipid metabolism in combination with mTOR inhibition, potentially offering new strategies to improve treatment efficacy and patient outcomes in GEP-NETs and other mTOR-driven cancers.
2026-01-26 | GSE293842 | GEO
Project description:This study aims to elucidate the transcriptomic changes and metabolic reprogramming in gastroenteropancreatic neuroendocrine tumor (GEP-NET) cells following PIKfyve inhibition, using both genetic (CRISPR-mediated knockdown) and pharmacological (Apilimod treatment) approaches. The research focuses on the impact of PIKfyve inhibition on lipid metabolism, cholesterol homeostasis, and mTOR signaling in QGP-1, BON-1, and GOT-1 cell lines. By analyzing RNA sequencing data from these experimental conditions, we seek to identify differentially expressed genes and enriched pathways associated with PIKfyve inhibition. This investigation is part of a broader effort to develop novel combination therapies that could potentially overcome resistance to mTOR inhibitors, the current standard of care for advanced GEP-NETs. The study's findings may provide insights into the therapeutic potential of targeting PIKfyve-driven lipid metabolism in combination with mTOR inhibition, potentially offering new strategies to improve treatment efficacy and patient outcomes in GEP-NETs and other mTOR-driven cancers.
2026-01-26 | GSE293843 | GEO
Project description:Effect of pharmacologic or genetic PIKFYVE inhibition in GEP-NET [CRISPR]
| PRJNA1246578 | ENA
Project description:Effect of pharmacologic or genetic PIKFYVE inhibition in GEP-NET [RNA-Seq]
| PRJNA1246577 | ENA
Project description:The aim of the study is to analyze the pattern of miRNA expression in the peripheral blood of GEP-NET patients (liquid biopsy) in order to identify a prognostic miRNA signature that correlates with 18FDG–PET status thus, with tumor metabolism and clinical parameeters such as 68Gallium-PET SUVmax.
| EGAS00001007227 | EGA
Project description:BackgroundGrade 3 gastro-entero-pancreatic neuroendocrine tumors (G3 GEP-NET) are poorly characterized in terms of molecular features and response to treatments.MethodsPatients with G3 GEP-NET were included if they received capecitabine and temozolomide (CAPTEM) or oxaliplatin with either 5-fluorouracile (FOLFOX) or capecitabine (XELOX) as first-line treatment (chemotherapy cohort). G3 NET which successfully undergone next-generation sequencing (NGS) were included in the NGS cohort.ResultsIn total, 49 patients were included in the chemotherapy cohort: 15 received CAPTEM and 34 received FOLFOX/XELOX. Objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) were 42.9%, 9.0 months, and 33.6 months, respectively. Calculating a Ki67 cutoff using ROC curve analysis, tumors with Ki67 ≥ 40% had lower ORR (51.2% vs. 0%; p = 0.007) and shorter PFS (10.6 months vs. 4.4 months; p < 0.001) and OS (49.4 months vs. 10.0 months; p = 0.023). In patients who received FOLFOX/XELOX as a first-line treatment, ORR, PFS, and OS were 38.2%, 7.9 months, and 30.0 months, respectively. In the NGS cohort (N = 13), the most mutated genes were DAXX/ATRX (N = 5, 38%), MEN1 (N = 4, 31%), TP53 (N = 4, 31%), AKT1 (N = 2, 15%), and PIK3CA (N = 1, 8%).ConclusionsFOLFOX/XELOX chemotherapy is active as the first-line treatment of patients with G3 GEP-NET. The mutational landscape of G3 NET is more similar to well-differentiated NETs than NECs.
| S-EPMC10178589 | biostudies-literature
Project description:GEP signatures of primary breast cells radiation treated.
| PRJNA435496 | ENA
Project description:Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are rare and heterogeneous tumors presenting a wide spectrum of different clinical and biological characteristics. In these tumors, the histological evaluation is a crucial element of clinical management. Currently, tumor grading, determined by Ki-67 staining and mitotic counts, is the most reliable predictor of prognosis. This scoring method is time-consuming and a high reproducibility cannot be achieved. Novel approaches are needed to support histological evaluation and prognosis. In this study, starting from a microarray analysis, we defined the miRNAs signature for poorly differentiated NETs (G3) compared to well differentiated NETs (G1 and G2) consisting of 56 deregulated miRNAs. Moreover, we identified 8 miRNAs that were expressed in all GEP-NETs grades but at different level. Among these miRNAs, we found miR-96-5p that raised its expression levels from grade 1 to grade 3; inversely, its target FOXO1 was decrease from grade 1 to grade 3. Our results reveal that the miRNAs expression profile of GEP-NET correlates their expression with grading showing a potential advantage of miRNA quantification to aid clinicians in the classification of common GEP-NETs subtypes.
2020-08-04 | GSE135034 | GEO