Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

MicroRNA expression profile of different grade pancreatic neuroendocrine tumors

ABSTRACT: The grade of pancreatic neuroendocrine tumors principally influences therapy. Grading is currently done by the histological examination of biopsy samples, which is an invasive and time-consuming method. We performed an NGS on FFPE tumor tissue samples to find microRNAs that show a significant difference in expression according to grade, thus could be suitable for grade determination.

ORGANISM(S): Homo sapiens

PROVIDER: GSE265752 | GEO | 2024/08/02

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Shared Molecules

Only show the datasets with similarity scores above: 0.5

Threshold

0.5

Similar Datasets

microRNA profiling in different grading of gastroenteropancreatic neuroendocrine tumors (GEP-NETs)

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

RNA-Seq of 60 Neuroendocrine Neoplasm (NEN) samples with different grade and primary site

Project description:The RNA isolated from 60 Neuroendocrine Neoplasm (NEN) was analysed to identify differentially expressed transcripts and fusion transcripts. Library preparation was performed using two different kit: TruSeq Stranded Total RNA (Illumina) for frozen samples and extracted RNAs, and TruSeq RNA Exome (Illumina) for FFPE samples.

2022-06-30 | E-MTAB-11599 | biostudies-arrayexpress

Proteogenomic characterization of pancreatic neuroendocrine tumor

Project description:To characterize pancreatic neuroendocrine tumor at protein level, we performed mass spectromery-based proteome analysis using clinical FFPE tissue samples.

2024-07-10 | PXD034571 | Pride

Comprehensive Sequencing of High Grade Neuroendocrine Neoplasms

Project description:Comprehensive Sequencing of High Grade Neuroendocrine Neoplasms

| PRJNA648441 | ENA

Comprehensive Sequencing of High Grade Neuroendocrine Neoplasms

Project description:Comprehensive Sequencing of High Grade Neuroendocrine Neoplasms

| PRJNA648442 | ENA

ASCL1 is a lineage oncogene providing therapeutic targets for high-grade neuroendocrine lung cancers

Project description:ChIP-Seq analysis performed on 5 ASCL1(+) cell lines and 2 ASCL1 (-) cell lines in order to understand the transcriptome of ASCL1 as it pertains to high-grade neuroendocrine lung cancers 5 ASCL1(+) lung cancer cell lines and 2 ASCL1(-) lung cancer cell lines were compared using ChIP-Seq analysis

2014-10-01 | E-GEOD-61197 | biostudies-arrayexpress

ASCL1 is a lineage oncogene providing therapeutic targets for high-grade neuroendocrine lung cancers

2014-10-01 | GSE61197 | GEO

MicroRNA expression profile of different grade pancreatic neuroendocrine tumors

Project description:MicroRNA expression profile of different grade pancreatic neuroendocrine tumors

| PRJNA1104139 | ENA

High grade neuroendocrine lung cancer expression profile

Project description:Genomic gains and losses, particularly amplification of oncogenes and deletion of tumor suppressor genes, are critical molecular events involved in tumorigenesis and cancer progression. These genomic structural abnormalities trigger pathway alterations which activate/inactivate transcription factors along protein network, and then affect gene transcription profiles. Therefore, trace-back analysis of the pathway alteration by integrating genomic copy number, transcription profile, and known protein network data is expected to provide key information to interpret tumorigenesis and cancer progression processes. However, there are a number of pathway alteration candidates, so that it is difficult to understand overall picture. Primitive approaches such as filtering by arbitrary selection of thresholds involve a risk of overlooking important pathway alterations and their triggers. We proposed a visualization method for the trace-back analysis of pathway alterations, called a Cluster Overlap Distribution Map (CODM). We applied the CODM to trace-back analysis of pathway alterations related to subtype classifications of high grade neuroendocrine carcinoma samples; 1) small cell lung carcinoma (SCLC) vs. large cell neuroendocrine carcinoma (LCNEC), and 2) group1 vs. group2 (this is the classification based on transcription profiles and group2 has a higher survival rate than group1). By effective use of 3D and color spaces, the CODM allowed us to understand the overall picture of pathway alteration without arbitrary selection of thresholds and to extract 6 pathway alterations related to only group1 vs. groups2, 2 pathway alterations related to only SCLC vs. LCNEC, and 2 pathway alterations related to both group1 vs. group2 and SCLC vs. LCNEC. Keywords: lung cancer profile

2022-04-01 | GSE9074 | GEO

Transcriptomic analyses of high-grade neuroendocrine carcinoma of gynecologic origin

Project description:High-grade neuroendocrine carcinomas (NECs) of the cervix are rare, aggressive cancers accounting for about 1-1.5% of all cervical cancer. The 5-year survival is up to 36% for early-stage disease; however, the advanced-stage disease has <10% survival, with relapse rates exceeding 90%. These cancers are likely to have a vascular invasion and nodal or visceral metastasis. Unfortunately, NEC of the cervix affects young women with a median age of 37. High-grade NECs of other gynecologic origins are even rarer, share similar aggressive behavior and poor outcomes. We performed stranded paired-end RNA-seq of 13 samples, including 12 samples with matched whole exome sequencing (WES) data. Sites of origin for tumors in our cohort were the cervix (69%), ovary (19%), and endometrium (12%). The median number of prior lines of therapy was 1. Median PFS and OS were 1 and 12 months, respectively, indicating their highly lethal nature. Comparing transcriptomic profiles with TCGA cervical and ovarian cancers, chromatin assembly and nucleosome organization were the top GO functions for significantly over-expressed genes in our cohort. Remarkably, under-expressed genes in our cohort were enriched for protein modification and catabolic processes, and neutrophil-mediated immunity. Compared to small cell lung cancer (SCLC), our cohort showed highly distinct transcriptomic patterns, and represented the YAP1 high molecular subtype.

2021-09-01 | GSE157601 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data