Gene expression patterns associated with p53 status in breast cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE3178 | GEO | 2007/02/20
SECONDARY ACCESSION(S): PRJNA92723
REPOSITORIES: GEO
Similar Datasets
Project description:Breast cancer subtypes identified in genomic studies have different underlying genetic defects. Mutations in the tumor suppressor p53 occur more frequently in estrogen receptor (ER) negative, basal-like and HER2-amplified tumors than in luminal, ER positive tumors. Thus, because p53 mutation status is tightly linked to other characteristics of prognostic importance, it is difficult to identify p53's independent prognostic effects. The relation between p53 status and subtype can be better studied by combining data from primary tumors with data from isogenic cell line pairs (with and without p53 function). In this study, the p53-dependent gene expression signatures of four cell lines (MCF-7, ZR-75-1, and two immortalized human mammary epithelial cell lines) were identified by comparing p53-RNAi transduced cell lines to their parent cell lines. Cell lines were treated with vehicle only or doxorubicin to identify p53 responses in both non-induced and induced states. Each cell line displayed unique patterns of gene expression, but cell type specific trends were evident. A common gene expression signature associated with p53 loss across all four cell lines was identified. This signature showed overlap with the signature of p53 loss in primary breast tumors and predicted relapse-free survival and overall survival in independent test data sets. Experiment Overall Design: We analyzed 48 arrays performed using 48 polyA RNA samples. RNAs were collected from cell lines treated with an IC50 dose of doxorubicin hydrochloride or with a feeding control. Each cell line had its own reference which represented the second sample on the dual channel array. These untreated RNAs were prepared by pooling four harvests of that cell line at 60-80% confluence and 48h after feeding
2008-06-12 | E-GEOD-3178 | biostudies-arrayexpress
Project description:Purpose. Temporal and local fluctuations in oxygen levels observed within tumors represent stressful conditions requiring adaptive mechanisms that provide tumor cells with phenotypic alterations to survive and proliferate in this hostile environment. The analysis of the transcriptome associated with such cycling hypoxia could thus represent a prognostic biomarker of cancer progression. Patients and Methods. We exposed 20 cell lines derived from various tissues to repeated periods of hypoxia/reoxygenation in order to determine a transcriptomic signature of cycling hypoxia (CycHyp). We then used clinical data sets from 2,150 patients with primary breast cancer to estimate a prognostic Cox proportional hazard model and to assess the prognostic performance of the CycHyp signature on independent samples. Results. The prognostic potential of the CycHyp signature was validated in patients independently of the receptor status of the tumors (HR=1.97; p = 1.8e-12). The discriminating capacity of the CycHyp signature was further increased in the ER+ HER2- patient populations (HR = 2.34, p = 9e-12) including those with a node negative status receiving or not a treatment (HR = 3.32 and 5.51; p= 5.61e-10 and 8.15e-11, respectively). We also documented the capacity of the CycHyp signature to outperform existing prognostic gene signatures with significantly higher BCR and concordance index. We also showed that the CycHyp signature could identify ER-positive node-negative breast cancer patients at high risk based on conventional clinico-pathologic criteria but who could have been spared from chemotherapy and inversely those patients classified at low risk based on the same criteria but who presented a negative outcome. Conclusion. This study demonstrates that a gene signature derived from the transcriptomic adaptation of tumor cells to cycling hypoxia is prognostic of breast cancer and offers a unique decision making tool to complement the discrimination of breast cancer patients based on anatomo-pathological evaluation. The prognostic value of CycHyp further confirms the link between cycling hypoxia and cancer progression, and thereby paves the way for a broad applicability to evaluate cancer patient outcomes.
2015-11-16 | GSE42416 | GEO
Project description:We used deep sequencinge technology to profile the transcriptome, gene copy number, and CpG island methylation status simultaneously in eight commonly used breast cell lines to develop a model for how these genomic features are integrated in estrogen receptor positive (ER+) and negative breast cancer. Total mRNA sequence, gene copy number, and genomic CpG island methylation were carried out using the Illumina Genome Analyzer. Sequences were mapped to the human genome to obtain digitized gene expression data, DNA copy number in reference to the non-tumor cell line (MCF10A), and methylation status of 21,570 CpG islands to identify differentially expressed genes that were correlated with methylation or copy number changes. These were evaluated in a dataset from 129 primary breast tumors. Gene expression in cell lines was dominated by ER-associated genes. ER+ and ER- cell lines formed two distinct, stable clusters, and 1,873 genes were differentially expressed in the two groups. Part of chromosome 8 was deleted in all ER- cells and part of chromosome 17 amplified in all ER+ cells. These loci encoded 30 genes that were overexpressed in ER+ cells; 9 of these genes were overexpressed in ER+ tumors. We identified 149 differentially expressed genes that exhibited differential methylation of one or more CpG islands within 5kb of the 5' end of the gene and for which mRNA abundance was inversely correlated with CpG island methylation status. In primary tumors we identified 84 genes that appear to be robust components of the methylation signature that we identified in ER+ cell lines. Our analyses reveal a global pattern of differential CpG island methylation that contributes to the transcriptome landscape of ER+ and ER- breast cancer cells and tumors. The role of gene amplification/deletion appears to more modest, although several potentially significant genes appear to be regulated by copy number aberrations. 8 commonly used breast cancer cell lines were sequenced for mRNA expression, CpG methylation and DNA copy number
2011-03-16 | E-GEOD-27003 | biostudies-arrayexpress
Project description:A microarray targeting promoters of cancer-related genes was used to evaluate DNA methylation at 935 CpG sites in 517 invasive breast tumors from the Carolina Breast Cancer Study (CBCS), a population-based study of invasive breast cancer. Concensus clustering using methylation (β) values for the 167 most variant CpG loci defined 4 clusters differing most distinctly in hormone receptor (HR) status, intrinsic subtype (luminal versus basal-like) and p53 mutation status. Supervised analyses for HR status, subtype, and p53 status identified differentially methylated CpG loci with considerable overlap (n=266). Concensus clustering also defined a hypermethylated luminal-enriched tumor cluster 3; gene ontology analysis of cluster 3 hypermethylated loci revealed enrichment for developmental genes, including homeobox domain genes (HOXB13, PAX6, IPF1, EYA4, DLK1, IHH, ISL1, TBX1, SOX1, SOX17). The hypermethylated luminal-enriched cluster 3 independently predicted poorer survival in multivariate Cox proportional hazard analysis, and this finding was confirmed in analysis of luminal A tumors. This study demonstrates epigenetic heterogeneity among breast tumors of a single intrinsic subtype, and shows that epigenetic patterns are strongly associated with HR status, subtype, and p53 mutation status. Among HR+ tumors, a gene signature characterized by hypermethylation of developmental genes may have prognostic value. Genes differentially methylated between clinically-important tumor subsets have roles in differentiation, development, and tumor growth and may be critical to inducing and maintaining tumor phenotypes and clinical outcomes. 517 breast tumors, 9 normal breast tissues
2015-04-07 | E-GEOD-51557 | biostudies-arrayexpress
Project description:We used deep sequencinge technology to profile the transcriptome, gene copy number, and CpG island methylation status simultaneously in eight commonly used breast cell lines to develop a model for how these genomic features are integrated in estrogen receptor positive (ER+) and negative breast cancer. Total mRNA sequence, gene copy number, and genomic CpG island methylation were carried out using the Illumina Genome Analyzer. Sequences were mapped to the human genome to obtain digitized gene expression data, DNA copy number in reference to the non-tumor cell line (MCF10A), and methylation status of 21,570 CpG islands to identify differentially expressed genes that were correlated with methylation or copy number changes. These were evaluated in a dataset from 129 primary breast tumors. Gene expression in cell lines was dominated by ER-associated genes. ER+ and ER- cell lines formed two distinct, stable clusters, and 1,873 genes were differentially expressed in the two groups. Part of chromosome 8 was deleted in all ER- cells and part of chromosome 17 amplified in all ER+ cells. These loci encoded 30 genes that were overexpressed in ER+ cells; 9 of these genes were overexpressed in ER+ tumors. We identified 149 differentially expressed genes that exhibited differential methylation of one or more CpG islands within 5kb of the 5' end of the gene and for which mRNA abundance was inversely correlated with CpG island methylation status. In primary tumors we identified 84 genes that appear to be robust components of the methylation signature that we identified in ER+ cell lines. Our analyses reveal a global pattern of differential CpG island methylation that contributes to the transcriptome landscape of ER+ and ER- breast cancer cells and tumors. The role of gene amplification/deletion appears to more modest, although several potentially significant genes appear to be regulated by copy number aberrations.
2011-03-16 | GSE27003 | GEO
Project description:A microarray targeting promoters of cancer-related genes was used to evaluate DNA methylation at 935 CpG sites in 517 invasive breast tumors from the Carolina Breast Cancer Study (CBCS), a population-based study of invasive breast cancer. Concensus clustering using methylation (β) values for the 167 most variant CpG loci defined 4 clusters differing most distinctly in hormone receptor (HR) status, intrinsic subtype (luminal versus basal-like) and p53 mutation status. Supervised analyses for HR status, subtype, and p53 status identified differentially methylated CpG loci with considerable overlap (n=266). Concensus clustering also defined a hypermethylated luminal-enriched tumor cluster 3; gene ontology analysis of cluster 3 hypermethylated loci revealed enrichment for developmental genes, including homeobox domain genes (HOXB13, PAX6, IPF1, EYA4, DLK1, IHH, ISL1, TBX1, SOX1, SOX17). The hypermethylated luminal-enriched cluster 3 independently predicted poorer survival in multivariate Cox proportional hazard analysis, and this finding was confirmed in analysis of luminal A tumors. This study demonstrates epigenetic heterogeneity among breast tumors of a single intrinsic subtype, and shows that epigenetic patterns are strongly associated with HR status, subtype, and p53 mutation status. Among HR+ tumors, a gene signature characterized by hypermethylation of developmental genes may have prognostic value. Genes differentially methylated between clinically-important tumor subsets have roles in differentiation, development, and tumor growth and may be critical to inducing and maintaining tumor phenotypes and clinical outcomes.
2015-04-07 | GSE51557 | GEO
Project description:The biological tumor samples (ie, breast tumor specimens) consisted of freshly frozen breast tumors from a population-based cohort of 315 women representing 65% of all breast cancers resected in Uppsala County, Sweden, from January 1, 1987 to December 31, 1989. Estrogen receptor status was determined by biochemical assay as part of the routine clinical procedure. An experienced pathologist determined the Elston-Ellis grades of the tumors, classifying the tumors into low, medium and high-grade tumors. The clinico-pathological characteristics accompanying each tumor include p53 status, ER status, tumor grade, lymph node status and patient age. Experiment Overall Design: All tumor specimens were assessed on U133 A and B arrays.
2008-04-04 | E-GEOD-3494 | biostudies-arrayexpress
Project description:The biological tumor samples (ie, breast tumor specimens) consisted of freshly frozen breast tumors from a population-based cohort of 315 women representing 65% of all breast cancers resected in Uppsala County, Sweden, from January 1, 1987 to December 31, 1989. Estrogen receptor status was determined by biochemical assay as part of the routine clinical procedure. An experienced pathologist determined the Elston-Ellis grades of the tumors, classifying the tumors into low, medium and high-grade tumors. The clinico-pathological characteristics accompanying each tumor include p53 status, ER status, tumor grade, lymph node status and patient age. Keywords: Tumor sample comparisons
2005-10-21 | GSE3494 | GEO
Project description:MCM3 is one of several genes whose expression profile is markedly altered in tamoxifen-resistant breast cancer cell lines. We observed that increased MCM3 expression is associated with tamoxifen resistance. Knockdown of MCM3 resulted in increased susceptibility of tamoxifen-resistant breast cancer cell lines. Moreover, MCM3 expression is significantly associated with clinical outcome of endocrine treated receptor positive breast cancer. To understand the effect of MCM3 on the mechanism of endocrine resistance, we performed gene expression array on tamoxifen-resistant breast cancer cell lines. Here we show that MCM3 knockdown affects the expression of hundreds of genes. Resistance to endocrine therapy in estrogen receptor-positive (ER+) breast cancer is a major clinical problem with poorly understood mechanisms. There is an unmet need for prognostic and predictive biomarkers to allow appropriate therapeutic targeting. We evaluated the mechanism by which minichromosome maintenance protein 3 (MCM3) influences endocrine resistance and its predictive/prognostic potential in ER+ breast cancer. We discovered that ER+ breast cancer cells survive tamoxifen and letrozole treatments through upregulation of minichromosome maintenance proteins (MCMs), including MCM3, which are key molecules in cell cycle and DNA replication. Lowering MCM3 expression in endocrine-resistant cells restored drug sensitivity and altered phosphorylation of cell cycle regulators, including p53(Ser315,33), CHK1(Ser317) and cdc25b(Ser323), suggesting that the interaction of MCM3 with cell cycle proteins is an important mechanism of overcoming replicative stress and anti-proliferative effects of endocrine treatments. Evaluation of MCM3 levels in primary tumors from four independent cohorts of breast cancer patients receiving adjuvant tamoxifen mono-therapy or no adjuvant treatment, including the Stockholm tamoxifen (STO-3) trial, showed MCM3 to be an independent prognostic adding information beyond Ki67. In addition, MCM3 was shown to be a predictive marker of response to endocrine treatment. Our study reveals a coordinated signaling network centered around MCM3 that limits response to endocrine therapy in ER+ breast cancer and identifies MCM3 as a clinically useful prognostic and predictive biomarker that allows personalized treatment of ER+ breast cancer patients.
2020-11-17 | GSE148878 | GEO
Project description:Purpose: There is an unmet clinical need for biomarkers to identify breast cancer patients who are at increased risk of developing brain metastases. The objective is to identify gene signatures and biological pathways associated with HER2+ brain metastasis. Experimental Design: Gene expression of 19 HER2+ breast cancer brain metastases was compared with HER2+ nonmetastatic primary tumors. Gene Set Enrichment Analysis was used to identify a signature, which was evaluated for correlation with BRCA1 mutation status and clinical outcome using published microarray datasets and for correlation with pharmacological inhibition by a PARP inhibitor and temozolomide using published microarray datasets of breast cancer cell lines. Results: A BRCA1 Deficient-Like (BD-L) gene signature is significantly correlated with HER2+ metastases in both our and an independent cohort. BD-L signature is enriched in BRCA1 mutation carrier primary tumors and HER2-/ER- sporadic tumors, but high values are found in a subset of ER+ and HER2+ tumors. Elevated BD-L signature in primary tumors is associated with increased risk of overall relapse, brain relapse, and decreased survival. The BD-L signature correlates with pharmacologic response to PARP inhibitor and temozolomide in two independent microarray datasets, and the signature outperformed four published gene signatures of BRCA1/2 deficiency. Conclusions: The BD-L signature is enriched in breast cancer brain metastases and identifies a subset of primary tumors with increased propensity for brain metastasis. Furthermore, this signature may serve as a biomarker to identify sporadic breast cancer patients who could benefit from a therapeutic combination of PARP inhibitor and temozolomide. Gene expression of 19 HER2+ human breast cancer brain metastases was compared with gene expression of 19 HER2+ nonmetastatic primary human breast tumors.
2014-04-24 | E-GEOD-43837 | biostudies-arrayexpress