Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Gene expression profile at single cell level of breast cancer patient-derived xenograft models

ABSTRACT: We profiled the tumor heterogeneity of individual primary tumor of breast cancer using a set of patient derived xenograft models with different metastatic potentials. This data set gives insights into the transcriptional tumor heterogeneity and how these are changing in regard to varying metastatic phenotypes.

ORGANISM(S): Homo sapiens

PROVIDER: GSE211145 | GEO | 2022/08/15

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Gene expression profile at single cell level of breast cancer patient-derived xenograft models using SMART-seq and MULTI-seq

Project description:We profiled the tumor heterogeneity of individual primary tumor of breast cancer using a set of patient derived xenograft models with different metastatic potentials. This data set gives insights into the transcriptional tumor heterogeneity and how these are changing in regard to varying metastatic phenotypes.

2022-08-12 | GSE210283 | GEO

Gene expression profile at single cell level of matched primary tumor and metastatic cells of breast cancer patient-derived xenograft models

Project description:We profiled the tumor heterogeneity of individual primary tumor and matched metastatic cells of breast cancer using a set of patient derived xenograft models with different metastatic potentials. This data set gives insights into the transcriptional tumor heterogeneity, the transcriptional differences between primary tumor and matched metastatic cells and how these are changing in regard to varying metastatic phenotypes.

2022-08-15 | GSE211146 | GEO

Expression data from the orthotopic tumors of MES-SA

Project description:The spontaneous pulmonary metastasis model of human uterine sarcoma was established using GFP-expressed MES-SA cells. Several sublines with different metastatic potentials were generated by in vivo passaging. We used microarrays to identify the metastatic-related genes using the orthotopic tumors with different metastatic potentials. Orthotopic transplanted uterine sarcoma were observed after 3 weeks post-transplantation and the xenografted tumor reached about 2000 mm3 in additional 3 weeks. After 6 weeks post-transplantation, the animals were sacrificed under isoflurane anesthesia, and the tumors were resected. The GFP-positive regions were collected using Leica MZ10F fluorescent stereomicroscope. This study compared the gene expression profiling between the orthotopic tumors with high (H)- and low (L)-metastatic potentials.

2014-12-08 | E-GEOD-63937 | biostudies-arrayexpress

Transcription profiling of human melanoma to develop a gene signature for aggression of melanoma metastases based on a xenograft mouse model

Project description:Metastasis is the deadliest phase of cancer progression. Experimental models using immunodeficient mice have been used to gain insights into the mechanisms of metastasis. We report here the identification of a âmetastasis aggressiveness gene expression signatureâ derived using human melanoma cells selected based on their metastatic potentials in a xenotransplant metastasis model. Comparison with expression data from human melanoma patients shows that this metastasis gene signature correlates with the aggressiveness of melanoma metastases in human patients. Many genes encoding secreted and membrane proteins are included in the signature, suggesting the importance of tumor-microenvironment interactions during metastasis. Experiment Overall Design: parental cell line vs xenograft model

2008-06-15 | E-GEOD-7929 | biostudies-arrayexpress

Expression in prospectively purified human prostate orthotopic xenograft tumor cells with varying S/TFE

Project description:This SuperSeries is composed of the following subset Series: GSE25690: Global analysis of mRNA expression in prospectively purified human prostate orthotopic xenograft tumor cells with varying S/TFE. GSE25691: Global analysis of miRNA expression in prospectively purified human prostate orthotopic xenograft tumor cells with varying S/TFE. Refer to individual Series

2010-12-06 | E-GEOD-25692 | biostudies-arrayexpress

Expression data from the orthotopic tumors of MES-SA

2014-12-08 | GSE63937 | GEO

An Engineered Niche Delineates Metastatic Potential of Breast Cancer

Project description:We aimed to identify metastatic disease prior to the formation of an overt secondary tumor in triple-negative breast cancer using sister cell lines 4T1 (metastatic), 4T07 (invasive, non-metastatic), and 67NR (non-metastatic). We used a porous, polycaprolactone scaffold, that serves as an engineered metastatic niche, to identify metastatic disease through the changing microenvironment.

2023-11-06 | GSE233001 | GEO

APOBEC mutagenesis and copy number alterations are drivers of proteogenomic tumor evolution and heterogeneity in metastatic thoracic tumors

Project description:Intratumor mutational heterogeneity has been documented in primary non-small cell lung cancer. Here, we elucidate mechanisms of tumor evolution and heterogeneity in metastatic thoracic tumors (lung adenocarcinoma and thymic carcinoma) using whole-exome and transcriptome sequencing, SNP array for copy number alterations (CNA) and mass spectrometry-based quantitative proteomics of metastases obtained by rapid autopsy. APOBEC-mutagenesis, promoted by increased expression of APOBEC3 region transcripts and associated with a high-risk germline APOBEC3 variant, strongly correlated with mutational tumor heterogeneity. TP53 mutation status was associated with APOBEC hypermutator status. Interferon pathways were enriched in tumors with high APOBEC mutagenesis and IFN- induced expression of APOBEC3B in lung adenocarcinoma cells in culture suggesting a role for the immune microenvironment in the generation of mutational heterogeneity. CNA occurring late in tumor evolution correlated with downstream transcriptomic and proteomic heterogeneity, although global proteomic heterogeneity was significantly greater than transcriptomic and CNA heterogeneity. These results illustrate key mechanisms underlying multi-dimensional heterogeneity in metastatic thoracic tumors.

2019-05-07 | PXD012845 | Pride

Liu2019 - Logistic Regression models to predict intrinsic resistance to anti-PD1 ICB in Ipilimumab treated and Ipilimumab naive patients with metastatic melanoma.

Project description:In this comprehensive study, the authors have developed concise models integrating clinical, genomic and transcriptomic features to predict intrinsic resistance to anti-PD1 Immune Checkpoint Blockade (ICB) treatment in individual tumors. It's important to note that their validation was performed in smaller, independent cohorts, constrained by data availability. The authors have developed two Logistic Regression based models for Ipilimumab treated and Ipilimumab naive patients with metastatic melanoma. The main predictive features for the Ipilimumab treated patients are MHC-II HLA, LDH at treatment initiation and the presence of lymph node metastases (LN met), chosen using forward selection methodology. The main predictive features for the Ipilimumab naive patients are tumor heterogeneity, tumor ploidy and tumor purity, chosen using forward selection methodology. Please note that in these models, the output ‘1’ means progressive disease (PD) and ‘0’ means non-PD. The original GitHub repository can be accessed at https://github.com/vanallenlab/schadendorf-pd1

2023-11-17 | MODEL2310150001 | BioModels

Single cell RNA-seq of an native and engineered metastatic niche in a metastatic breast cancer murine model

Project description:Metastatic lesions are typically not found until patients self-report symptoms or they become radiologically evident. We have developed an engineered metastatic niche (scaffold) that recruits aggressive tumor cells prior to their colonization in other organs. The engineered niche can be monitored for dynamic gene expression, and changes at this site are analogous to those in a native metastatic site (lung) for triple negative breast cancer (4T1 cells). We were able to develop a 10-gene signature from the scaffold that accurately monitors disease progression and recurrence or resistance to resection therapy. This data set acts to dissect the heterogeneity of the cell populations in the engineered and native metastatic niche and identify the cell types that contribute to the success of the signature.

2022-08-02 | E-MTAB-8503 | biostudies-arrayexpress

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