Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Ribosome profiling of cell line models of human breast cancer

ABSTRACT: 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

ORGANISM(S): Homo sapiens

PROVIDER: GSE126736 | GEO | 2019/12/05

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Ribosome profiling of wild-type and loc1- cells in S. cerevisiae

Project description:We performed ribosome profiling of wild-type and loc1- cells. We found that approximately 1500 genes exhibit increased translational efficiencies in the absence of Loc1, indicating that Loc1 is required for their translational repression. Examination of translational efficiencies by comparing ribosome footprints and mRNA abundances in two different cell lines.

2014-01-01 | E-GEOD-34438 | biostudies-arrayexpress

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.

2014-07-24 | GSE42125 | GEO

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

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

Expression and exosome incorporation of microRNA by leukemia versus nonmalignant hematopoietic progenitors

Project description:Exosomes are paracrine regulators of the tumor microenvironment. However, their complex cargo can hamper an understanding of their specific action in target cells. We therefore sought to identify the changes in exosome miRNA content that occur with malignant transformation by comparing two myeloid cancer cell lines to their nonmalignant predecessors, CD34+ human hematopoietic progenitor cells. We employed microarrays to evaluate which miRNA are present at altered concentrations before and after transformation as well as before and after incorporation into exosomes.

2016-08-18 | GSE85769 | 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

Ribosome profiling of wild-type and loc1- cells in S. cerevisiae

2014-01-01 | GSE34438 | GEO

RNA-seq of total and polysomal RNA of clk-1(qm30) mutants in Caenorhabditis elegans

Project description:This study uses total and polysomal RNA-sequencing to show that the translational efficiencies of specific mRNAs change depending on the mitochondrial activity in longer-lived C. elegans.

2018-09-05 | E-MTAB-7166 | biostudies-arrayexpress

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

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

2016-06-02 | GSE82132 | GEO

Impact of EFP on translational efficiency of specific amino acid motifs in E. coli using a plasmid-based dual reporter system

Project description:Impact of EFP on translational efficiency of specific motifs

| PRJEB77738 | ENA