SNP6 and expression profiling of papillary carcinoma of the breast
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Charlotte Ng
PROVIDER: E-GEOD-55640 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series The SNP and expression datasets represent the same samples (i.e., the 26 SNP6 samples are a subset of the 28 expression samples)
2014-10-31 | E-GEOD-57549 | biostudies-arrayexpress
Project description:Expression profiling of papillary carcinoma of the breast and grade- and ER-matched cases of invasive ductal breast cancer To identify differential expression between papillary carcinomas of the breast and grade- and ER-matched invasive ductal breast cancers, we performed expression profiling of 16 cases of papillary carcinomas of the breast and 16 cases of grade- and ER-matched invasive ducatal carcinoma of no special subtype. We further reviewed the papillary carcinomas of the breast and classified them into 3 subtypes, namely, invasive papillary carcinoma, encapsulated papillary carcinoma and solid papillary carcinoma. We also performed a hypothesis-generating comparison of differential expression between the 3 subtypes of papillary carcinoma of the breast. Expression profiling of 16 cases of papillary carcinioma of the brest and 16 cases of invasive ducal carcinomas using the Illumina HT-12 v4 arrays
2014-06-20 | E-GEOD-55639 | biostudies-arrayexpress
Project description:SNP6 profiling of papillary carcinoma of the breast Affymetrix SNP6 arrays were performed according ro manufacturer's directions on DNA extracted from 16 papillary carcinomas of the breast.
2014-06-20 | E-GEOD-55638 | biostudies-arrayexpress
Project description:SNP6 profiling of metaplastic breast carcinoma Metaplastic breast carcinoma (MBC) is a rare and aggressive histologic type of breast cancer, preferentially displaying a triple-negative phenotype (i.e. lacking estrogen receptor, progesterone receptor and HER2 expression). We sought to define the transcriptomic heterogeneity of MBCs on the basis of current gene expression microarray-based classifiers and to determine whether MBCs display gene copy number profiles consistent with those of BRCA1-associated breast cancers.
2014-10-31 | E-GEOD-57548 | biostudies-arrayexpress
Project description:Aromatase inhibitors are first-line postmenopausal agents for estrogen receptor alpha (ERa)-positive breast cancer. However, there is considerable response heterogeneity and women frequently relapse. Estrogen deprivation does not completely arrest ERa activity, and transactivation of the unliganded receptor may continue through cross-talk with growth factor pathways. In contrast with aromatase inhibitors, the selective ER downregulator fulvestrant also abrogates ligand-independent ERa activity. The benefit of fulvestrant as an alternative, combination, or sequential therapy to aromatase inhibitor has been reported, but molecular mechanisms underpinning its relative efficacy remain unclear and biomarkers for patient selection are lacking. This study demonstrates, for the first time, that the overall transcriptional response to fulvestrant is of greater magnitude than estrogen deprivation, consistent with its clinical efficacy and more complete blockade of estrogenic signaling. Using a robust integrative approach, we identify a subset of genes differentially affected by fulvestrant that comprises distinct biologic networks, correlates with antiproliferative response, and has potential utility as predictive biomarkers for fulvestrant. Global gene expression profiles from ERα-positive breast carcinomas before and during presurgical treatment with fulvestrant (n = 38) or anastrozole (n = 81), and corresponding in vitro models, were compared. Transcripts responding differently to fulvestrant and estrogen deprivation were identified and integrated using Gene Ontology, pathway and network analyses to evaluate their potential significance. --------------------------------- This represents the data for fulvestrant only
2015-08-07 | E-GEOD-71791 | biostudies-arrayexpress
Project description:Genomic rearrangements typically occur progressively during tumor development. Recent findings, however, suggest an alternative mechanism, involving chromosome shattering and reshuffling ('chromothripsis'), for which no genetic basis has yet been described. Whole-genome sequencing of a Sonic-Hedgehog medulloblastoma (SHH-MB) brain tumor from a patient with a germline TP53 mutation (Li-Fraumeni syndrome) revealed massive, complex rearrangements resulting from chromothripsis. Integrating TP53 status with genomic rearrangement data in additional medulloblastomas revealed a striking association between TP53 mutation and chromothripsis in SHH-MBs. Unexpectedly, five seemingly sporadic SHH-MB patients with chromothripsis harbored TP53 germline mutations – findings relevant for clinical management. Analysis of additional tumor entities substantiated a link between TP53 mutation and chromothripsis, beyond general genomic instability. Among these, we observed a strong association between somatic TP53 mutations and chromothripsis in acute myeloid leukemia. These findings implicate p53 in the initiation of, or cellular reaction to, chromothripsis – a novel role for the 'guardian of the genome'. The DNA copy-number profiles of 11 primary medulloblastoma samples were analyzed on the Affymetrix Mapping250K Nsp array, together with data from 70 primary samples taken from GSE21140. Data from diploid reference samples were taken from GSE9222. Additionally, DNA copy-number profiles for 19 additional medulloblastoma samples were generated on the Affymetrix SNP6 platform with matched blood samples.
2012-01-20 | E-GEOD-34258 | biostudies-arrayexpress
Project description:Conventional high-grade osteosarcoma is a primary malignant bone tumor, which is most prevalent in adolescence. Survival rates of osteosarcoma patients have not improved significantly in the last 25 years. Aiming to increase this survival rate, a variety of model systems are used to study osteosarcomagenesis and to test new therapeutic agents. Such model systems are typically generated from an osteosarcoma primary tumor, but undergo many changes due to culturing or interactions with a different host species, which may result into differences in gene expression between primary tumor cells, and tumor cells from the model system. We aimed to investigate whether gene expression profiles of osteosarcoma cell lines and xenografts are still comparable to those of the primary tumor. Osteosarcoma can be subdivided into several histological subtypes, of which osteoblastic, chondroblastic, and fibroblastic osteosarcoma are the most frequent ones. Using nearest shrunken centroids classification, we have generated an expression profile that can predict these histological subtypes in both osteosarcoma biopsies (n=66), as well as in two osteosarcoma model systems, i.e. osteosarcoma cell lines (n=13) and xenografts (n=18). Based on the preservation of mRNA expression profiles that are characteristic for the histological subtype we propose that these model systems are representative to the primary tumor from which they are derived. Genome-wide expression profiling was performed on pre-treatment diagnostic biopsies of 76 resectable high-grade osteosarcoma patients from the EuroBoNet consortium (www.eurobonet.eu). Samples with a main histological subtype (n=66) were selected for subsequent subtype analyses. Out of the EuroBoNeT panel of 19 cell lines, 13 cell lines were recorded to belong to a main histological subtype. This set of 13 cell lines contained 4 cell lines derived from fibroblastic, and 9 cell lines derived from osteoblastic osteosarcomas. The 13 osteosarcoma cell lines IOR/MOS, IOR/OS10, IOR/OS14, IOR/OS15, IOR/OS18, IOR/OS9, IOR/SARG, KPD, MG-63, MHM, OHS, OSA, and ZK-58 were maintained in RPMI 1640 (Invitrogen, Carlsbad, CA, USA) supplemented with 10% fetal calf serum and 1% Penicillin/Streptomycin (Invitrogen) as previously described (PMID: 19787792). The osteosarcoma xenograft model is described in Kresse et al. (PMID: 21713766) In short, human tumors were implanted directly from patient samples and successively passaged subcutaneously in nude mice. Eighteen different xenografts were used, of which 3 were derived from chondroblastic, and 15 from osteoblastic osteosarcomas. Osteosarcoma and xenograft tissue was handled as previously described in Buddingh, Kuijjer et al. (PMID: 21372215) Osteosarcoma cell lines were prepared as in Ottaviano et al. (PMID: 19787792) RNA isolation, synthesis of cDNA, cRNA amplification, and hybridization of cRNA onto the Illumina Human-6 v2.0 Expression BeadChips were performed as described in Buddingh, Kuijjer, et al. (PMID: 21372215) Microarray data processing and quality control were performed using the statistical language R as described in Buddingh, Kuijjer, et al. (PMID: 21372215) We performed a factorial LIMMA analysis comparing 50 osteoblastic, 9 chondroblastic, and 7 fibroblastic osteosarcomas pre-chemotherapy biopsies. Probes with Benjamini and Hochberg False discovery rate-adjusted P-values < 0.05 were considered to be significantly differentially expressed. The gene expression profile was generated on the dataset of biopsies using Bioconductor package PAMR. Internal cross-validation was performed 50 times. A threshold was selected where the error rate of the prediction profile was minimal. The minimum error rate was representative of 50 independent simulations. In order to minimize optimization bias, we validated the profile on an independent dataset of osteosarcoma biopsies (n=5), containing 1 chondroblastic osteosarcoma and 4 osteoblastic osteosarcomas. We subsequently applied the validated prediction profile to two independent datasets, the first consisting of gene expression data of osteosarcoma cell lines, the second of xenografts. Expression of the probes that composed the prediction profile was verified using a factorial LIMMA analysis, comparing chondroblastic, fibroblastic, and osteoblastic osteosarcoma biopsy samples.
2011-09-20 | E-GEOD-30699 | biostudies-arrayexpress
Project description:We performed genome-wide gene expression data of high-grade osteosarcoma samples. In order to detect osteosarcoma drivers, we integrated these data with copy number data. We performed two different methods - a non-paired and a paired integrative analysis. Genome-wide gene expression analysis was performed on 84 pre-treatment high-grade osteosarcoma diagnostic biopsies, of which 29 overlapped with the 32 samples used for copy number analysis. Two different sets of control samples were used for comparison: osteoblasts (n=3) and mesenchymal stem cells (n=12, GEO accession number GSE28974).
2012-03-27 | E-GEOD-33382 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
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Project description:This study evaluates the gene expression patterns in 36 decidual samples of women having gone through different types of child birth. The samples were profiled on Illumina Human HT-12_v4 BeadArrays. The analysis includes quality control and exploratory analysis of the dataset, followed by the identification of differentially expressed genes (DEGs) and finally, functional analysis for enrichment of KEGG pathways and GO terms amongst the DEGs. The statistical analysis was performed for six comparisons: Term labour (TL) vs Term not labour (TNL), TL vs Preterm labour (PTL), TL vs Preterm non-labour (PTNL), TNL vs PTL, TNL vs PTNL and PTL vs PTNL. This study evaluates the gene expression levels from decidual samples obtained from women giving birth with different types of labour. The dataset was composed of 36 Illumina Human HT-12_v4 expression BeadArrays.
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