Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Single-cell landscape analysis reveals distinct regression trajectories and novel prognostic biomarkers in primary neuroblastoma

ABSTRACT: Single-cell landscape analysis reveals distinct regression trajectories and novel prognostic biomarkers in primary neuroblastoma

PROVIDER: PRJNA1212194 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR32039612_1.fastq.gz	Fastqsanger.gz
	SRR32039612_2.fastq.gz	Fastqsanger.gz
	SRR32039613_1.fastq.gz	Fastqsanger.gz
	SRR32039613_2.fastq.gz	Fastqsanger.gz
	SRR32039614_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 46

Similar Datasets

Single-cell landscape analysis reveals distinct regression trajectories and novel prognostic biomarkers in primary neuroblastoma

Project description:Neuroblastoma (NB) is the most common extracranial malignant solid tumor in children, and its clinical manifestations and prognosis vary greatly. NB has a unique ability to spontaneously differentiate and regress, which provides potential directions for therapeutic interventions. To investigate the heterogeneity of tumors, we performed single-cell transcriptome sequencing on 19 tumor samples and 3 adrenal tissue samples, including 2 cases of familial neuroblastoma.

2025-03-01 | GSE287352 | GEO

Novel prognostic biomarkers in central neurocytoma

Project description:Novel prognostic biomarkers in central neurocytoma

| PRJNA1216957 | ENA

Single-cell landscape analysis reveals distinct regression trajectories and novel prognostic biomarkers in primary neuroblastoma.

Project description:Neuroblastoma (NB), which is the most common pediatric extracranial solid tumor, varies widely in its clinical presentation and outcome. NB has a unique ability to spontaneously differentiate and regress, suggesting a potential direction for therapeutic intervention. However, the underlying mechanisms of regression remain largely unknown, and more reliable prognostic biomarkers are needed for predicting trajectories for NB. We performed scRNA-seq analysis on 17 NB clinical samples and three peritumoral adrenal tissues. Primary NB displayed varied cell constitution, even among tumors of the same pathological subtype. Copy number variation patterns suggested that neuroendocrine cells represent the malignant cell type. Based on the differential expression of sets of related marker genes, a subgroup of neuroendocrine cells was identified and projected to differentiate into a subcluster of benign fibroblasts with highly expressed CCL2 and ZFP36, supporting a progressive pathway of spontaneous NB regression. We also identified prognostic markers (STMN2, TUBA1A, PAGE5, and ETV1) by evaluating intra-tumoral heterogeneity. Lastly, we determined that ITGB1 in M2-like macrophages was associated with favorable prognosis and may serve as a potential diagnostic marker and therapeutic target. In conclusion, our findings reveal novel mechanisms underlying regression and potential prognostic markers and therapeutic targets of NB.

| S-EPMC9485279 | biostudies-literature

Prognostic biomarkers of antipsychotic-induced weight gain

Project description:Prognostic biomarkers of antipsychotic-induced weight gain

| PRJNA661304 | ENA

Hox-C9 activates the intrinsic pathway of apoptosis and is associated with spontaneous regression in neuroblastoma [tumor_genex_44k]

Project description:Single-color gene expression profiles from 649 neuroblastoma tumors were generated using 44K oligonucleotide microarrays. We aimed at determining the association of class I HOX gene expression patterns with prognostic markers in neuroblastoma.We investigated the functional consequences of HOXC9 re-expression on neuroblastoma growth and programmed cell death. One-color gene expression analysis. Single-color gene expression profiles from 649 neuroblastoma tumors were generated using 44K oligonucleotide microarrays. Stages were classified according to the International Neuroblastoma Staging System. The expression patterns of the 39 class I HOX genes were analyzed in 649 neuroblastoma samples by microarrays, and the association with prognostic markers was determined.

2013-03-28 | E-GEOD-45547 | biostudies-arrayexpress

The Discovery and Validation of AML Prognostic Biomarkers

Project description:The Discovery and Validation of AML Prognostic Biomarkers

| PRJNA805341 | ENA

The Discovery and Validation of AML Prognostic Biomarkers

Project description:The Discovery and Validation of AML Prognostic Biomarkers

| PRJNA805342 | ENA

Array CGH analysis of 56 primary gastric cancers for elucidating prognostic biomarkers

Project description:Array CGH analysis was done with 56 primary gastric cancers to elucidate prognostic biomarkers on the BAC basis. Using the extracted genomic DNA from 56 primary gastric cancers, array CGH was done to elucidate the prognostic biomarkers.

2010-08-10 | E-GEOD-15436 | biostudies-arrayexpress

Telomerase is a prognostic marker of poor outcome and a therapeutic target in neuroblastoma

Project description:The aim of this study is to determine the clinical relevance of telomerase activation versus ALT as biomarkers in pre-treatment neuroblastoma, and to assess the potential value of telomerase as a therapeutic target. Therefore, the genomic status of TERT and MYCN was assessed in 457 pretreatment neuroblastomas by fluorescence-in-situ-hybridization. ALT was examined in 273/457 tumors by detection of ALT-associated promyelocytic leukemia nuclear bodies, and TERT expression was determined by 4x44k microarrays in 223 of these. The presence of activated telomerase, i.e., TERT rearrangements, MYCN amplification, or high TERT expression without these alterations, was associated with poorest overall survival, and was an independent prognostic marker in multivariable analyses.

2019-09-16 | E-MTAB-8248 | biostudies-arrayexpress

Rapid identification of prognostic imaging biomarkers for non-small cell lung cancer by leveraging public gene expression microarray data

Project description:To rapidly identify new prognostic imaging biomarkers, we propose a bioinformatics approach that integrates gene expression and image data and leverages public gene expression data. We demonstrate our approach in non-small cell lung carcinoma patients for whom CT, PET/CT and gene expression data are available but without clinical follow-up. We extracted 180 image features and 56 high quality gene expression clusters, represented by metagenes. 115 image features were expressed in terms of metagenes, using sparse linear regression and cross-validation, with an accuracy of 65-86%. After mapping the signatures to a public gene expression dataset, 26 image features were significantly associated with recurrence-free survival and 22 with overall survival. A multivariate analysis identified multiple image features that were prognostic, independent of clinical covariates. Identifying prognostic imaging biomarkers by linking images and gene expression with outcomes in public gene expression datasets promises to accelerate the role of imaging in personalized medicine.

2012-06-01 | GSE28827 | 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