Browse
Submit Data
Databases
API
Help

Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ATF3 links host adaptive-response to breast cancer metastasis

ABSTRACT: Cancer-host interactions play an important role in cancer development. We identified ATF3, an adaptive-response gene, in the host to facilitate metastasis. We also demonstrated that the macrophage is one of the key cell types for host-ATF3 to function. Furthermore, matrix metalloproteases 9 is a functionally important target gene of ATF3 in co-culture assays. Gene profiling with bioinformatics analyses indicated that ATF3 downstream gene-signatures derived from tumor-associated macrophages in a mouse model can distinguish human tumor stroma from M-bM-^@M-^\distantM-bM-^@M-^] stroma in and can stratify the patients into high- versus low-risk groups. Importantly, multivariate analyses indicated that high expression of ATF3 itself in mononuclear cells within breast tumors is an independent predictor for breast cancer-specific death in a cohort of patients. Approximately 21 days after orthotopic injection of PyMT breast cancer cells into syngeneic C57BL/6 mice (WT or ATF3 KO hosts) tumors were removed (tumors were ~1 cm cubic in volume), enzymatically digested to generate single cell suspensions, stained, and sorted for F4/80 and CD45 double positive cells by FACS. Isolated cells were lysed in TRIzol, processed to generate total RNA, and gene expression analyzed by microarray. Four replicate WT TAM samples and four replicate ATF3 KO TAM samples were analyzed.

ORGANISM(S): Mus musculus

SUBMITTER: Tsonwin Hai

PROVIDER: E-GEOD-36904 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Similar Datasets

ATF3 links host adaptive-response to breast cancer metastasis

Project description:Cancer-host interactions play an important role in cancer development. We identified ATF3, an adaptive-response gene, in the host to facilitate metastasis. We also demonstrated that the macrophage is one of the key cell types for host-ATF3 to function. Furthermore, matrix metalloproteases 9 is a functionally important target gene of ATF3 in co-culture assays. Gene profiling with bioinformatics analyses indicated that ATF3 downstream gene-signatures derived from tumor-associated macrophages in a mouse model can distinguish human tumor stroma from “distant” stroma in and can stratify the patients into high- versus low-risk groups. Importantly, multivariate analyses indicated that high expression of ATF3 itself in mononuclear cells within breast tumors is an independent predictor for breast cancer-specific death in a cohort of patients.

2013-07-10 | GSE36904 | GEO

Cancer-secreted miRNAs regulate amino-acid-induced mTORC1 signaling and fibroblast protein synthesis

Project description:Metabolic reprogramming of non-cancer cells residing in a tumor microenvironment, as a result of the adaptations to cancer-derived metabolic and non-metabolic factors, is an emerging aspect of cancer-host interaction. We show that in normal and cancer-associated fibroblasts, breast-cancer-secreted extracellular vesicles suppress mTOR signaling upon amino acid stimulation to globally reduce mRNA translation. This is through delivery of cancer-derived miR-105 and miR-204, which target RAGC, a component of Rag GTPases that regulate mTORC1 signaling. Following amino acid starvation and subsequent re-feeding, 13C-arginine labeling of de novo synthesized proteins shows selective translation of proteins that cluster to specific cellular functional pathways. The repertoire of these newly synthesized proteins is altered in fibroblasts treated with cancer-derived extracellular vesicles, in addition to the overall suppressed protein synthesis. In human breast tumors, RAGC protein levels are inversely correlated with miR-105 in the stroma. Our results suggest that through educating fibroblasts to reduce and re-prioritize mRNA translation, cancer cells rewire the metabolic fluxes of amino acid pool and dynamically regulate stroma-produced proteins during periodic nutrient fluctuations.

2020-11-24 | PXD022311 | Pride

Breast Cancer RNA-seq

Project description:RNA-seq was performed on breast cancer cell lines and primary tumors RNA-seq was performed on 28 breast cancer cell lines, 42 Triple Negative Breast Cancer (TNBC) primary tumors, and 42 Estrogen Receptor Positive (ER+) and HER2 Negative Breast Cancer primary tumors, 30 uninovlved breast tissue samples that were adjacent to ER+ primary tumors, 5 breast tissue samples from reduction mammoplasty procedures performed on patients with no known cancer, and 21 uninvolved breast tissue samples that were adjacent to TNBC primary tumors.

2014-06-11 | E-GEOD-58135 | biostudies-arrayexpress

Exosome Transfer from Stromal to Breast Cancer Cells Regulates Therapy Resistance Pathways [set 2]

Project description:Stromal communication with cancer cells can influence treatment response. We show that stromal and breast cancer (BrCa) cells utilize paracrine and juxtacrine signaling to drive chemotherapy and radiation resistance. Upon heterotypic interaction, exosomes are transferred from stromal to BrCa cells. RNA within exosomes, which are largely non-coding transcripts and transposable elements, stimulates the pattern recognition receptor RIG-I to activate STAT1-dependent anti-viral signaling. In parallel, stromal cells also activate NOTCH3 on BrCa cells. The paracrine anti-viral and juxtacrine NOTCH3 pathways converge as STAT1 facilitates transcriptional responses to NOTCH3 and expands therapy resistant tumor-initiating cells. Primary human and/or mouse BrCa analysis support the role of anti-viral/NOTCH3 pathways in NOTCH signaling and stroma-mediated resistance, which is abrogated by combination therapy with gamma secretase inhibitors. Thus, stromal cells orchestrate an intricate cross-talk with BrCa cells by utilizing exosomes to instigate anti-viral signaling. This expands BrCa subpopulations adept at resisting therapy and re-initiating tumor growth. Breast cancer cells lines and MRC5 fibroblasts were mono-cultured or co-cultured together. Cell types were separated by FACS and gene expression changes were examined using the Affymetrix Human Gene 1.0ST arrays. The effect of tumor-stromal cell interaction on different breast cancer cell types was analyzed using biological replicates. Gene expression changes resulting from knockdown of STAT1 was also investigated.

2014-10-24 | E-GEOD-60995 | biostudies-arrayexpress

Exosome Transfer from Stromal to Breast Cancer Cells Regulates Therapy Resistance Pathways [set 1]

2014-10-24 | E-GEOD-60994 | biostudies-arrayexpress

Transcription profiling of human tumor microenvironment during breast cancer progression

Project description:To better understand the role of tumor microenvironment in breast cancer progression, we combined laser capture microdissection and microarray analysis to provide a comprehensive catalog of gene expression changes in both tumor and tumor-associated stroma. Experiment Overall Design: We used LCM to isolate the epithelial and stroma compartments separately from each of 14 fresh frozen primary breast cancer biopsies. In the epithelial compartment, we captured normal (N) and malignant (DCIS or IDC or both where available) epithelium from each tissue slide. In the stroma compartment, we captured both normal stroma away from the malignant lesion (NSS) and the DCIS-associated stroma (ISS) and/or IDC-associated stroma (INVS) whenever possible.

2009-02-26 | E-GEOD-14548 | biostudies-arrayexpress

Analysis of exosome RNA from co-culture of cancer cell and stroma cell

Project description:How stroma communicates with cancer to influence treatment response is poorly understood. We show that stromal fibroblasts protect breast cancer (BrCa) against radiation and chemotherapy through an exosome-mediated anti-viral pathway and NOTCH3. Stroma increases RAB27B and transfers exosomes to BrCa. RNA within exosomes, comprised largely of non-coding transcripts and transposable elements, stimulates the pattern recognition receptor RIG-I through a 5M-bM-^@M-^Y-triphosphate motif to activate STAT1. BrCa NOTCH3 is activated in parallel by stromal JAG1 and cooperates with STAT1 to enhance transcriptional responses of NOTCH target genes and to expand therapy resistant tumor-initiating cells. Computational modeling using primary human and mouse BrCa supports the interaction of anti-viral/NOTCH3 pathways in controlling NOTCH target genes and treatment resistance, particularly in basal subtype tumors. Gamma secretase inhibitors reverse stromal protection and abrogate radiation resistance in vivo. Thus, stroma orchestrates an intricate cross-talk with BrCa by utilizing exosomes to coax anti-viral signaling that expands therapy resistant cells through druggable pathways. RNA profile of ceullar RNA and exosome of co-culture of breast caner cell line 1833 and stroma cell line MRC5.

2014-10-24 | E-GEOD-60997 | biostudies-arrayexpress

Analysis of compartment-specific gene expression in breast cancer tumors

Project description:Triple-negative primary breast cancer tumors, rich in inflammatory stroma, were laser microdissected and global mRNA expression was analyzed in stroma compartment, cancer cell compartment, and in total tumor tissue. Three FFPE breast cancer tumors wer laser microdissected and the cancer cell and stroma compartments were collected. A piece of t

2015-05-01 | E-GEOD-59772 | biostudies-arrayexpress

Expression profile of Breast Cancer tumors in Brazilian women

Project description:On the basis of prognostic information provided by the PAM50 predictor, we evaluated how samples grouped relative to the other breast tumor subtypes. mRNA samples from 24 patients were amplified, labeled, and hybridized to the Affymetrix GeneChip Human Exon 1.0 ST array. After normalization and analysis of the microarray data using PartekM-BM-. software (http://www.partek.com), we clustered all samples using the PAM50 predictor. We analyzed tumors from 24 patients with breast cancer using the Affymetrix Human Exon 1.0 ST platform. Array data was processed by AffymetrixExpression Console and analysed using Partek software

2014-05-30 | E-GEOD-58102 | biostudies-arrayexpress

Prognostic value of biomarkers EpCAM and B-crystallin is associated with lymphatic metastasis in breast cancer by iTRAQ analysis

Project description:Metastasis is responsible for the majority of deaths in a variety of cancer types, including breast cancer. Although several factors or biomarkers have been identified to predict the outcome of patients with breast cancer, few studies have been conducted to identify metastasis-associated biomarkers. Quantitative iTRAQ proteomics analysis was used to detect differentially expressed proteins between lymph node metastases and their paired primary tumor tissues from 23 patients with metastatic breast cancer. Immunohistochemistry was performed to validate the expression of two upregulated (EpCAM, FADD) and two downregulated (NDRG1, αB-crystallin) proteins in 190 paraffin-embedded tissue samples. These four proteins were further analyzed for their correlation with clinicopathological features in 190 breast cancer patients. We identified 637 differentially regulated proteins (397 upregulated and 240 downregulated) in lymph node metastases compared with their paired primary tumor tissues. Furthermore, bioinformatics analysis using GEO profiling confirmed the difference in the expression of EpCAM between metastases and primary tumors tissues. Two upregulated (EpCAM, FADD) and two downregulated (NDRG1, αB-crystallin) proteins were associated with the progression of breast cancer. Obviously, EpCAM plays a role in the metastasis of breast cancer cells to the lymph node. We further identified αB-crystallin as an independent biomarker to predict lymph node metastasis and the outcome of breast cancer patients.

2019-08-29 | PXD013931 | Pride

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