Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Network Analysis of Breast Cancer Progression and Reversal with a Tree-Evolving Network Algorithm

ABSTRACT: The HMT3522 progression series of breast cells has been used to discover the roles of tissue architecture, microenvironment and signaling molecules in nonmalignant and malignant breast cell growth and behaviors, including the potential of various factors to cause phenotypic reversion of malignant cells to nonmalignant states. Despite many efforts to delineate key signaling pathways governing the malignant as well as the phenotypic reversion behaviors of T4 cells, much remains to be elucidated about the regulatory mechanisms underlying these cell states at the systems level. Here, we analyzed gene expression microarray profiles obtained from this progression series in both phenotypically malignant and reverted states using our newly developed tree-lineage-based network detection algorithm, Treegl. Our work suggests analysis of various conditions of reversion (including non-reverted) of the HMT3522 cells using Treegl can be a model system to study drug effects on breast cancer cells, and may become a tool for effective drug discovery and target identification.

ORGANISM(S): Homo sapiens

PROVIDER: GSE42125 | GEO | 2014/07/24

SECONDARY ACCESSION(S): PRJNA179161

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Network Analysis of Breast Cancer Progression and Reversal with a Tree-Evolving Network Algorithm

Project description:The HMT3522 progression series of breast cells has been used to discover the roles of tissue architecture, microenvironment and signaling molecules in nonmalignant and malignant breast cell growth and behaviors, including the potential of various factors to cause phenotypic reversion of malignant cells to nonmalignant states. Despite many efforts to delineate key signaling pathways governing the malignant as well as the phenotypic reversion behaviors of T4 cells, much remains to be elucidated about the regulatory mechanisms underlying these cell states at the systems level. Here, we analyzed gene expression microarray profiles obtained from this progression series in both phenotypically malignant and reverted states using our newly developed tree-lineage-based network detection algorithm, Treegl. Our work suggests analysis of various conditions of reversion (including non-reverted) of the HMT3522 cells using Treegl can be a model system to study drug effects on breast cancer cells, and may become a tool for effective drug discovery and target identification. Gene expression microarray data was obtained using Affymetrix GeneChip Human Genome U133A arrays to analyze 15 total RNA samples prepared from the HMT3522 breast cells grown in 3D lrECM and treated with various reverting agents or vehicle control.

2014-07-24 | E-GEOD-42125 | biostudies-arrayexpress

Gene expression in organized and disorganized human breast epithelial cells

2013-10-01 | GSE50444 | GEO

caArray_merco-00121: In silico dissection of cell-type-associated patterns of gene expression in prostate cancer

Project description:Prostate tumors are complex entities composed of malignant cells mixed and interacting with nonmalignant cells. However, molecular analyses by standard gene expression profiling are limited because spatial information and nontumor cell types are lost in sample preparation. We scored 88 prostate specimens for relative content of tumor, benign hyperplastic epithelium, stroma, and dilated cystic glands. The proportions of these cell types were then linked in silico to gene expression levels determined by microarray analysis, revealing unique cell-specific profiles. Gene expression differences for malignant and nonmalignant epithelial cells (tumor versus benign hyperplastic epithelium) could be identified without being confounded by contributions from stroma that dominate many samples or sacrificing possible paracrine influences. Cell-specific expression of selected genes was validated by immunohistochemistry and quantitative PCR. The results provide patterns of gene expression for these three lineages with relevance to pathogenetic, diagnostic, and therapeutic considerations. merco-00121 Assay Type: Gene Expression Provider: Affymetrix Array Designs: HG_U95Av2 Organism: Homo sapiens (ncbitax) Material Types: whole_orrganism, synthetic_RNA, organism_part, total_RNA Disease States: Normal, Prostate Cancer

2016-06-02 | E-GEOD-82132 | biostudies-arrayexpress

ribosome profiling of cell line models of human breast cancer

Project description:We performed ribosome profiling in cell line models of human breast cancer. We profiled 2 representative estrogen receptor-positive (T47D and ZR75-1) and 2 representative triple negative (SUM159PT and MDA-MB-231) cell lines. Translational profiles of a nonmalignant (Human Mammary Epithelial Cells, HMECs) and a nontumorigenic (MCF10A cells) counterparts were also analyzed. We analyzed and compared translational efficiencies, variances of the translational efficiencies, differential gene and transcript expression between malignant and non-malignant cell lines. We performed discriminative motif analysis of the 5'untranslated regions of the transcripts that are commonly transcribed in nonmalignant and malignant cells but preferentially translated in malignant cells and identified common motifs. Some of these motifs are highly similar to the RNA binding motifs of a small list of RNA interacting proteins. This approach led us to identify SRSF1 as an RNA binding protein commonly expressed among all analyzed cell lines that has a pervasive impact on the translational landscape of a representative estrogen receptor-positive and -negative cell line

2019-12-05 | GSE126736 | GEO

Gene expression in organized and disorganized human breast epithelial cells

Project description:We have reported more than a dozen microenvironmental factors whose signaling must be integrated in order to effect an organized, functional tissue morphology. In order to identify underlying commonalities in gene transcription associated with the phenotype, we compared the gene expression of organized and disorganized epithelial cells of the HMT-3522 breast cancer progression series: the non-malignant S1 cells that form polarized spheres (‘acini’), the malignant T4-2 cells that form large tumor-like clusters, and the ‘phenotypically reverted’ T4-2 cells that polarize as a result of correction of the microenvironmental signaling. 24 samples were analyzed: 5 samples were non-malignant S1 cells that formed organized spherical structures ('acini'), 5 samples were the isogenic malignant counterpart of S1 cells, namely the T4-2 cells, which grow into disorganized large cell clusters; and 14 samples of T4-2 cells that had been treated with different reverting agents, these reverting agents cause the T4-2 cells to 'revert' in phenotype so that they resemble the structures formed by S1 cells.

2013-10-01 | E-GEOD-50444 | biostudies-arrayexpress

SILAC-based Quantitative Proteomic Analysis of Secretome between Activated and Reverted Hepatic Stellate Cells

Project description:Activated hepatic stellate cell (HSC) is the main myofibroblast cell in the liver fibrosis(LF). An important characteristic of the recovery of LF is not only the apoptosis of activated HSCs but also reversal of myofibroblast-like phenotype to a quiescent-like phenotype. Understanding the changes of secreted proteins in the reversion of activated HSCs may provide the broader view of cellular regulatory networks and discover candidate markers or targets for therapeutic strategies of LF. In this study, stable isotope labeling with amino acids (SILAC) combining with LTQ-FT mass spectrometer were performed on in vitro activated HSCs and reverted HSCs to obtain a proteomic view of secretory proteins. In total, 330 proteins showed significant differences in reverted HSCs. Among these, 109 up-regulated proteins were mainly involved in amino acid metabolism pathway and glucose metabolism pathway using GeneGO/MetaCore software, while 221 down-regulated proteins are closely associated with HSCs activation, such as cytoskeleton remodeling, chemokines and cell adhesion. Additionally, a set of novel proteins associated with HSCs activation and reversion were validated by Western blotting in the cell secretion and in the sera of LF, including Vitronectin, laminin beta 1(LAMB1) and Ubiquitin conjugation factor E4B(UBE4B). Our study provided the valuable insight into the mechanisms in the reversion of activated HSCs and identified some potential biomarkers of LF in clinical studies.

2014-08-11 | PXD000773 | Pride

CD146 accelerates malignant progression of phyllodes tumor cells

Project description:Breast malignant phyllodes tumors (PTs) are rapid-progressing tumors, known to lack effective treatment and suitable prognostic markers as well as elaborate studies. Herein,we found that level of CD146 is progressively elevated with malignant progression of PTs and is an independent predictor for prognosis of PT patients.Mechanistically, CD146 activates the PI3K/AKT signaling pathway, thereby enhancing malignant behaviors of PT cells.This study unveils a CD146-PI3K/AKT axis in modulating the malignant progression of PTs, and open avenues to develop a novel target for precise prognosis and treatment for breast malignant PTs.

2023-12-01 | GSE227380 | GEO

Transcription profiling of human mammary epithelial cell lines with finite life span and immortal non-malignant cells - time series

Project description:Nonmalignant human mammary epithelial cells (HMEC) seeded in laminin-rich extracellular matrix (lrECM) form polarized acini and, in doing so, transit from a disorganized proliferating state to an organized growth-arrested state. We hypothesized that the gene expression pattern of organized and growth-arrested HMECs would share similarities with breast tumors with good prognoses. Using Affymetrix HG-U133A microarrays, we analyzed the expression of 22,283 gene transcripts in 184 (finite life span) and HMT3522 S1 (immortal nonmalignant) HMECs on successive days after seeding in a lrECM assay. Both HMECs underwent growth arrest in G0-G1 and differentiated into polarized acini between days 5 and 7. We identified gene expression changes with the same temporal pattern in both lines and examined the expression of these genes in a previously published panel of microarray data for 295 breast cancer samples. We show that genes that are significantly lower in the organized, growth-arrested HMEC than in their proliferating counterparts can be used to classify breast cancer patients into poor and good prognosis groups with high accuracy. This study represents a novel unsupervised approach to identifying breast cancer markers that may be of use clinically. Experiment Overall Design: We analyzed gene expression in 184 (finite life span) and HMT3522 S1 (immortal non-malignant) HMECs on successive days (3, 5, and 7) post-seeding in a laminin-rich extracellular matrix assay. Both HMECs underwent growth arrest in G0/G1 and differentiated into polarized acini between days 5 and 7.

2008-06-15 | E-GEOD-8096 | biostudies-arrayexpress

Sonic hedgehog medulloblastoma cells in co-culture with cerebellar organoids converge towards in vivo malignant cell states

Project description:In the malignant brain tumour, sonic hedgehog medulloblastoma the properties of cancer cells are influenced by their microenvironment, but the nature of those effects and the phenotypic consequences for the tumour are poorly understood. The aim of this study was to identify phenotypic properties of SHH-MB cells that were driven by the non-malignant tumour microenvironment. Human iPSC were differentiated to cerebellar organoids to simulate the non-malignant tumour microenvironment. Tumour spheroids were generated from two distinct, long-established SHH-MB cell lines which were co-cultured with cerebellar organoids. We profiled the cellular transcriptomes of malignant and non-malignant cells by performing droplet-based single cell RNA-seq of thousands of cells. The transcriptional profiles of tumour cells in co-culture were compared with those of malignant cells cultured in isolation and with public SHH-MB datasets of patient tumours and PDX models. Heterogeneity of cell states was observed for SHH-MB cells cultured in isolation and in co-culture. Tumour cells in co-culture activated a key marker of differentiating granule cells, NEUROD1 that was not observed in control tumour cells cultured in isolation. In malignant cells in co-culture, cancer stem cell (CSC)-like states emerged that were not observed in control cultures and closely similar or equivalent cell states could be identified in patient tumours. For both SHH-MB cell lines grown in co-culture, there was a convergence of malignant cell states towards in vivo cell states observed in SHH-MB patient tumours and PDX models that were non-cell autonomously induced by the non-malignant microenvironment.

2024-04-01 | GSE254917 | GEO

In vitro activation and reversion of human primary hepatic stellate cells

Project description:Liver fibrosis is characterized by the excessive formation and accumulation of matrix proteins as a result of wound healing in the liver. A main event during fibrogenesis is the activation of the liver resident quiescent hepatic stellate cell (qHSC). Recent studies suggest that reversion of the activated HSC (aHSC) phenotype into a quiescent-like phenotype could be a major cellular mechanism underlying fibrosis regression in the liver, thereby offering new therapeutic perspectives for the treatment of liver fibrosis. The goal of the present study is to identify experimental conditions that can revert the activated status of human HSCs and to map the molecular events associated with this phenotype reversion by gene expression profiling Transcriptomic profiling of primary human quiescent HSCs (qHSCs), in vitro activated HSCs (aHSCs) and in vitro reverted HSCs (rHSCs). The cell types come from different donors (This is detailed in the original manuscript.).

2015-08-12 | E-GEOD-68001 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

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