Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Pancreatic, Small-intestinal and Pulmonary Neuroendocrine Tumors

ABSTRACT: Purpose: The primary origin of neuroendocrine tumor metastases can be difficult to determine by histopathology alone, but is critical for therapeutic decision making. DNA methylation-based profiling is now routinely used in the diagnostic workup of brain tumors. This has been enabled by the availability of cost-efficient array-based platforms. We have extended these efforts to augment histopathological diagnosis in neuroendocrine tumors. Experimental Design and Results: We compiled data of 69 small-intestinal, pulmonary, and pancreatic neuroendocrine tumors. These data were used to build a ridge regression calibrated random forest classification algorithm (NEN-ID) that predicts the origin of tumor samples with high accuracy (> 95%). The model was validated during 3x3 nested cross validation and tested in a local (n=26) and external (n=172) cohort. In addition, we show that our diagnostic approach is robust across a range of possible confounding experimental parameters such as tumor purity and array quality. A software infrastructure and online user interface was built to make the model available to the scientific community. Conclusions: This DNA methylation-based prediction model can be used in the workup for patients with neuroendocrine tumors of unknown primary. To facilitate validation and clinical implementation, we provide a user-friendly, publicly available web-based version of NEN-ID.

PROVIDER: EGAS00001004878 | EGA |

REPOSITORIES: EGA

ACCESS DATA

Json Xml

Similar Datasets

Gene expression data of organoids derived from neuroendocrine carcinomas

Project description:Gastroentero-pancreatic neuroendocrine neoplasm(GEP-NEN) is consisted of neuroendocrine tumor and neuroendocrine carcinoma, which is a lethal, but under-investigated disease owing to its rarity. We established an organoid library of GEP-NEN and added their comprehensive molecular characterization.

2020-12-21 | GSE142720 | GEO

Distinct Function for ASCL1 and NEUROD1 in Pulmonary Neuroendocrine Tumors (RNA-seq)

Project description:Small cell lung carcinoma (SCLC) and large cell neuroendocrine carcinoma (LCNEC) are high-grade pulmonary neuroendocrine tumors. The neural basic helix-loop-helix (bHLH) transcription factors ASCL1 and NEUROD1 have been shown to play crucial roles in promoting the malignant behavior and survival of human SCLC cell lines. In this study, we find ASCL1 and NEUROD1 identify distinct neuroendocrine tumors, bind distinct genomic loci, and regulate mostly distinct genes. ASCL1 and NEUROD1 are often bound in super-enhancers that are associated with highly expressed genes in their respective SCLC cell lines suggesting different cell lineage of origin for these tumors. ASCL1 targets oncogenic genes such as MYCL1, RET, and NFIB, while NEUROD1 targets the oncogenic gene MYC. Although ASCL1 and NEUROD1 regulate different genes, many of these gene targets commonly contribute to neuroendocrine and cell migration function. ASCL1 in particular also regulates genes in the NOTCH pathway and genes important in cell-cycle dynamics. Finally, we demonstrate ASCL1 but not NEUROD1 is required for SCLC and LCNEC tumor formation in current in vivo genetic mouse models of pulmonary neuroendocrine tumors RNA-seq analysis performed on two ASCL1high and two NEUROD1high human SCLC cell lines to identify gene expression patterns in these cells. Also, we performed RNA-seq in mouse neuroendocrine lung tumors obtained from Trp53;Rb1;Rbl2 triple knockout model mice treated with Adeno-CMVCRE intratracheally.

2016-07-21 | E-GEOD-69393 | biostudies-arrayexpress

Multigene panel test in 44 Homo sapiens patients with either digestive system neuroendocrine Neoplasm (NEN) or medullary thryoid gland carcinoma samples

Project description:The DNA isolated from 44 either frozen or FFPE Neuroendocrine Neoplasm (NEN) was analysed by NGS, to identify genes more likely to be subject to sequence variations among 523 cancer-related ones.

2022-06-30 | E-MTAB-11529 | biostudies-arrayexpress

SCLC LCNEC FFPE LMD

Project description:Small-cell lung carcinoma (SCLC) and large-cell neuroendocrine lung carcinoma (LCNEC) are high-grade lung neuroendocrine tumors (NET). However, comparative protein expression within SCLC and LCNEC remains unclear. Here, protein expression profiles were obtained via mass spectrometry-based proteomic analysis.

2019-05-14 | PXD013583 | JPOST Repository

Distinct Function for ASCL1 and NEUROD1 in Pulmonary Neuroendocrine Tumors (ChIP-seq)

Project description:Small cell lung carcinoma (SCLC) and large cell neuroendocrine carcinoma (LCNEC) are high-grade pulmonary neuroendocrine tumors. The neural basic helix-loop-helix (bHLH) transcription factors ASCL1 and NEUROD1 have been shown to play crucial roles in promoting the malignant behavior and survival of human SCLC cell lines. In this study, we find ASCL1 and NEUROD1 identify distinct neuroendocrine tumors, bind distinct genomic loci, and regulate mostly distinct genes. ASCL1 and NEUROD1 are often bound in super-enhancers that are associated with highly expressed genes in their respective SCLC cell lines suggesting different cell lineage of origin for these tumors. ASCL1 targets oncogenic genes such as MYCL1, RET, and NFIB, while NEUROD1 targets the oncogenic gene MYC. Although ASCL1 and NEUROD1 regulate different genes, many of these gene targets commonly contribute to neuroendocrine and cell migration function. ASCL1 in particular also regulates genes in the NOTCH pathway and genes important in cell-cycle dynamics. Finally, we demonstrate ASCL1 but not NEUROD1 is required for SCLC and LCNEC tumor formation in current in vivo genetic mouse models of pulmonary neuroendocrine tumors ChIP-seq analysis performed on three ASCL1high and two NEUROD1high human SCLC cell lines to identify ASCL1 and/or NEUROD1 binding sites in these two types of cells. Also, we performed ChIP-seq for Ascl1 binding sites in mouse neuroendocrine lung tumors obtained from Trp53;Rb1;Rbl2 triple knockout model mice treated with Adeno-CMVCRE intratracheally.

2016-07-21 | E-GEOD-69394 | biostudies-arrayexpress

SmallRNAs profile in 60 Neuroendocrine Neoplasms (NEN) and 3 sera derived from NEN patients

Project description:SmallRNAs profile in 60 Neuroendocrine Neoplasms (NEN) and 3 sera derived from NEN patients

| PRJEB51922 | ENA

MYC drives temporal evolution of small cell lung cancer subtypes by reprogramming neuroendocrine fate [Human SCLC biopsy]

Project description:Small cell lung cancer (SCLC) is a neuroendocrine tumor treated clinically as a single disease with poor outcomes. Distinct SCLC molecular subtypes have been defined based on expression of lineage-related transcription factors: ASCL1, NEUROD1, POU2F3 or YAP1, but their origins remain unknown. We developed an in vitro model of MYC-driven SCLC tumor cell progression, and performed a time-series analysis of single-cell transcriptome profiling to reveal that MYC drives the dynamic evolution of SCLC subtypes. Analyses of these single-cell RNA seq data reveal that MYC promotes a temporal shift from an ASCL1-to-NEUROD1-to-YAP1+ state from a neuroendocrine cell of origin. MYC activates Notch signaling to dedifferentiate tumor cells to non-neuroendocrine fates. Additional single-cell RNA sequencing of 4RPM tumors reveal individual tumors to consist of cells at nearly every stage of RPM tumor evolution modeled in vitro. With the single-cell RNA sequencing of this human SCLC liver biopsy, along with IHC on a panel of 21 human biopsies, we show that human SCLC exhibits intratumoral SCLC subtype heterogeneity, suggesting this dynamic evolution occurs in patient tumors. Together, these single-cell RNA sequencing data support our conclusions that genetics, cell of origin, and tumor cell plasticity determine SCLC subtype.

2020-05-28 | GSE150766 | GEO

MYC drives temporal evolution of small cell lung cancer subtypes by reprogramming neuroendocrine fate [Single Cell RNA seq on RPM time-series cells and 4 RPM bulk tumors]

Project description:Small cell lung cancer (SCLC) is a neuroendocrine tumor treated clinically as a single disease with poor outcomes. Distinct SCLC molecular subtypes have been defined based on expression of lineage-related transcription factors: ASCL1, NEUROD1, POU2F3 or YAP1, but their origins remain unknown. Here, we develop an in vitro model of MYC-driven SCLC tumor cell progression and perform a time-series analysis of single-cell transcriptome profiling to reveal that MYC drives the dynamic evolution of SCLC subtypes. Analyses of these single-cell RNA seq data reveal that MYC promotes a temporal shift from an Ascl1-to-Neurod1-to-Yap1+ state from a neuroendocrine cell of origin. They also support our findings that MYC activates Notch signaling to dedifferentiate tumor cells to non-neuroendocrine fates. Additional single-cell RNA sequencing of 4 bulk Rb1/Trp53/MycT58A (RPM) tumors reveal individual tumors to consist of cells at nearly every stage of RPM tumor evolution modeled in vitro. Together, these single-cell RNA sequencing data place 3 of 4 SCLC subtypes on a defined trajectory and suggest that genetics, cell of origin, and tumor cell plasticity determine SCLC subtype.

2020-05-28 | GSE149179 | GEO

Integrated miRNAs profiling, DNA methylation, and RNA expression in gastroenteropancreatic neuroendocrine neoplasias [miRNA]

Project description:Background: Neuroendocrine neoplasms (NENs) are mutationally quiet, and epigenetic mechanisms drive their development and progression. We aim to comprehensively characterize the microRNA (miRNA) profile of NENs, and explore downstream targets and their epigenetic modulation. Material and Methods: In total, 84 cancer-related miRNAs were analyzed in 84 NEN samples from lung and gastroenteropancreatic GEP origin, and their prognostic value was evaluated by univariate and multivariate models. Transcriptomics (N=63) and methylomics (N=30) were performed to predict miRNA target genes, signaling pathways and regulatory CpG sites. Findings were validated in The Cancer Genome Atlas (TCGA) cohorts and in NEN cell lines. Results: We identified a signature of eight miRNAs that stratified patients in three prognostic groups (5-year survival of 80%, 66% and 36%). Expression of the eight-miRNA gene signature correlated with 71 target genes involved in PI3K-Akt and TNFα-NF-kB signaling. Of these, 28 were associated with survival and validated in silico and in vitro. Finally, we identified five CpG sites involved in the epigenetic regulation of these eight miRNAs. Conclusion: In brief, we identified an 8-miRNA signature able to predict survival of patients with GEP and lung NENs, and identified genes and regulatory mechanisms driving prognosis in NEN patient.

2023-03-31 | GSE211482 | GEO

Integrated miRNAs profiling, DNA methylation, and RNA expression in gastroenteropancreatic neuroendocrine neoplasias [mRNA]

2023-03-31 | GSE211485 | GEO