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Expression data from two breast cancer cell lines

ABSTRACT: During cancer progression, carcinoma cells encounter a variety of cytotoxic stresses such as hypoxia, nutrient deprivation, and low pH as a result of inadequate vascularization. To maintain survival and growth in the face of these physiologic stressors, a set of adaptive response pathways are induced. One adaptive pathway well studied in other contexts is the unfolded protein response (UPR), of which XBP1 is an important component. We used microarrays to detect transcriptome profile changes after XBP1 knockdown in breast cancer cell lines, and identify genes and pathways regulated by XBP1, which could help elucidate how XBP1 mediates the adaptive response of breast cancer to cytotoxic stresses. We extracted RNA and hybridized it to Affymetrix microarrays in two breast cancer cell lines (T47D and MDA-MB-231) under treated (hypoxia and glucose deprivation) or untreated conditions with XBP1 knockdown or not.

ORGANISM(S): Homo sapiens

SUBMITTER: Liu Xiaole

PROVIDER: S-ECPF-GEOD-49953 | biostudies-other |

REPOSITORIES: biostudies-other

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Project description:Breast cancer is a genetically and phenotypically complex disease. To understand the role of microRNAs in this molecular complexity, we performed miRNA expression analysis in a cohort of molecularly well-characterized human breast cancer (BC) cell lines to discover miRNAs associated with the most common molecular subtypes and the most frequent genetic aberrations.Using a microarray carrying LNA™ modified oligonucleotide capture probes (Exiqon), expression levels of 725 human miRNAs were measured in 51 BC cell lines. MiRNA expression was explored by unsupervised cluster analysis and then associated with the molecular subtypes and genetic aberrations commonly present in breast cancer. Unsupervised cluster analysis using the most variably expressed miRNAs divided the 51 BC cell lines into a major and a minor cluster predominantly mirroring the luminal and basal intrinsic subdivision of BC cell lines. One hundred and thirteen miRNAs were differentially expressed between these two main clusters of which half were related to the ER-status of the cell lines. Forty miRNAs were differentially expressed between basal-like and normal-like/claudin-low cell lines. Within the luminal-group of cell lines, 39 miRNAs were associated with ERBB2 overexpression and 24 miRNAs with E-cadherin gene mutations, which are frequent in this subtype of BC cell lines. In contrast, 31 different miRNAs were associated with E-cadherin promoter hypermethylation, which, contrary to E-cadherin mutation, is exclusively observed in BC cell lines that are not of luminal origin. The differential expression of 30 miRNAs were associated with p16INK4 status while only a few differentially expressed miRNAs were associated with BRCA1, or PIK3CA/PTEN, TP53 mutation status of the cell lines (P-value < 0.05). Twelve miRNAs were associated with DNA copy number variation of the respective locus. Luminal-basal and epithelial-mesenchymal associated miRNAs determine the overall subdivision of miRNA transcriptome of BC cell lines. Specific sets of miRNAs were associated with ERBB2 overexpression, p16INK4aor E-cadherin mutation or E-cadherin methylation status, which implies that these miRNAs may contribute to the driver role of the genetic aberrations. Additionally, miRNAs, which are located in a genomic region showing recurrent genetic aberrations, may themselves play a driver role in breast carcinogenesis or contribute to a driver gene in their vicinity. In short, our study provides detailed molecular miRNA portraits of BC cell lines, which can be exploited for functional studies of clinically important miRNAs. Affymetrix plus2PM arrays were hybridized according to the manufacturer's procedure using RNA extracted from 52 cultured breast cancer cell lines. Most cellines were analyzed in triplicate. Gene expression data in log2 scale arrays were calculated and associated with diverse characteristics. This submission represents the gene expression component of the study only

Project description:Cultured cancer cells exhibit substantial phenotypic heterogeneity when measured in a variety of ways such as sensitivity to drugs or the capacity to grow under various conditions. Among these, the ability to exhibit anchorage-independent cell growth (colony forming capacity in semisolid media), has been considered to be fundamental in cancer biology, because it has been connected with tumor cell aggressiveness in vivo such as tumorigenic and metastatic potentials, and also utilized as a marker for in vitro transformation. Although multiple genetic factors for anchorage-independence have been identified, the molecular basis for this capacity is still largely unknown. To investigate the molecular mechanisms underlying anchorage independent cell growth, we have used genome-wide DNA microarray studies to develop an expression signature associated with this phenotype. Using this signature, we identify a program of activated mitochondrial biogenesis associated with the phenotype of anchorage-independent growth and importantly, we demonstrate that this phenotype predicts potential for metastasis in primary breast and lung tumors. Keywords: Breast cancer cell lines with various colony-forming ability To develop an expression signature reflecting the capacity for anchorage-independent cell growth, we first carried out colony formation assays with 19 breast cancer cell lines in suspension culture dish with methyl-cellulose containing media. Starting with 20,000 plated cells, five cell lines (MDA-MB-361, HCC38, ZR75, Hs578T and BT483) gave rise to less than 20 colonies, while 8 cell lines (MCF7, MDA-MB-231, BT20, SKBR3, MDA-MB-435s, T47D and BT474) showed formation of more than 500 colonies. The rest of the cell lines showed an intermediate phenotype in colony forming ability (20-200 colonies; HCC1143, HCC1806, HCC1428, MDA-MB-453, CAMA1, BT549 and MDA-MB-157). Among 19 cell lines, 11 cell lines have duplicates of expression data in a different batch. We removed the batch effect of this Affymetrix expression data using ComBat according to the instruction of http://statistics.byu.edu/johnson/ComBat/Abstract.html. Therefore, this dataset is a combined and standardized data that are originally RMA formatted.

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Expression data from two breast cancer cell lines

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