Breast cancers with HER2 overexpression are sensitive to drugs targeting the receptor or its kinase activity. HER2-targeting drugs are initially effective against HER2- positive breast cancer, but resistance inevitably occurs. We previously found that nuclear factor kappa B is hyper-activated in the subset of HER-2 positive breast cancer cells and tissue specimens. In this study, we report that constitutively active NF-B rendered HER2-positive cancer cells resistant to anti-HER2 drugs, and cells selected for Lapatinib resistance up-regulated NF-B. In both circumstances, cells were anti-apoptotic and grew rapidly as xenografts. Lapatinib-resistant cells were refractory to HER2 and NF-B inhibitors alone but were sensitive to their combination, suggesting a novel therapeutic strategy. A subset of NF-B-responsive genes was overexpressed in HER2-positive and triple-negative breast cancers, and patients with this NF-B signature had poor clinical outcome. Anti-HER2 drug resistance may be a consequence of NF-B activation, and selection for resistance results in NF-B activation, suggesting this transcription factor is central to oncogenesis and drug resistance. Clinically, the combined targeting of HER2 and NF-B suggests a potential treatment paradigm for patients who relapse after anti-HER2 therapy. Patients with these cancers may be treated by simultaneously suppressing HER2 signaling and NF-B activation.
NF-κB activation-induced anti-apoptosis renders HER2-positive cells drug resistant and accelerates tumor growth.
Specimen part
View SamplesComparatative gene expression analysis for CD4 T cell subsets isolated from peripheral blood and palatine tonsils
A methodology for global validation of microarray experiments.
Specimen part
View SamplesDNA microarrays are popular tools for measuring gene expression of biological samples. This ever increasing popularity is ensuring that a large number of microarray studies are conducted, many of which with data publicly available for mining by other investigators. Under most circumstances, validation of differential expression of genes is performed on a gene to gene basis. Thus, it is not possible to generalize validation results to the remaining majority of non-validated genes or to evaluate the overall quality of these studies. <br></br> We have devised an approach for the global validation of DNA microarray experiments that will allow researchers to evaluate the general quality of their experiment and to extrapolate validation results of a subset of genes to the remaining non-validated genes. We applied this method to a microarray experiment validated with quantitative real time polymerase chain reaction. The experiment consists of three biological replicate treatments of mouse 3T3-L1 preadipocytes with the steroid hormone dexamethasone for 3 hours. Total RNA was extracted from each of our three treatment and three control samples, and we labeled and hybridized five aliquots of each sample to Affymetrix MGU74Av2 microarrays, for a total of 30 microarrays.<br></br> We illustrate why the popular strategy of selecting only the most differentially expressed genes for validation generally fails as a global validation strategy and propose random-stratified sampling as a better gene selection method. We also illustrate shortcomings of often-used validation indices such as overlap of significant effects and the correlation coefficient and recommend the concordance correlation coefficient (CCC) as an alternative.
A methodology for global validation of microarray experiments.
Cell line, Subject, Compound
View SamplesInterferon (IFN) beta-1a is an approved treatment for relapsing remitting multiple sclerosis (RRMS) and has been examined for use in secondary progressive multiple sclerosis (SPMS). However, no information regarding blood transcriptional changes induced by IFN treatment in SPMS patients is available.
Transcriptional response to interferon beta-1a treatment in patients with secondary progressive multiple sclerosis.
Sex, Age, Treatment
View SamplesAnalysis of Allelic bias in clonal lymphoblastoid cells. Abstract: In mammals, numerous autosomal genes are subject to mitotically stable monoallelic expression (MAE), including genes that play critical roles in a variety of human diseases. Due to challenges posed by the clonal nature of MAE, very little is known about its regulation; in particular, no molecular features have been specifically linked to MAE. Here we report an approach that distinguishes MAE genes in human cells with great accuracy: a chromatin signature consisting of chromatin marks associated with active transcription (H3K36me3) and silencing (H3K27me3) simultaneously occurring in the gene body. The MAE signature is present in ~20% of ubiquitously expressed genes and over 30% of tissue-specific genes across cell types. Notably, it is enriched among key developmental genes that have bivalent chromatin structure in pluripotent cells. Our results open a new approach to the study of MAE that is independent of polymorphisms, and suggest that MAE is linked to cell differentiation. Overall design: Poly A purified total RNA was used for library construction using a method described by Parkhomchuk et. al. NAR 2009. The library was strand-specific but the pipeline for data analysis does not assume the library is strand-specific.
Chromatin signature of widespread monoallelic expression.
No sample metadata fields
View Samplesbulk breast tumor RNA from patient
X chromosomal abnormalities in basal-like human breast cancer.
No sample metadata fields
View SamplesGene expression for 47 human breast tumor cases;
X chromosomal abnormalities in basal-like human breast cancer.
No sample metadata fields
View SamplesFemale BRCA1 mutation carriers have a nearly 80% probability of developing breast cancer during their life-time. We hypothesized that the breast epithelium at risk in BRCA1 mutation carriers harbors mammary epithelial cells (MECs) with altered proliferation and differentiation properties.
Altered proliferation and differentiation properties of primary mammary epithelial cells from BRCA1 mutation carriers.
No sample metadata fields
View SamplesUsing BCR-ABL-induced chronic myeloid leukemia (CML) as a disease model for leukemia stem cells (LSCs), we showed that BCR-ABL down-regulates the B lymphoid kinase (Blk) gene in leukemia stem cells in CML mice and that Blk functions as a tumor suppressor in LSCs and suppresses LSC function. Inhibition of this Blk pathway accelerates CML development, whereas increased activity of the Blk pathway delays CML development. To identify the pathways in which Blk regulates function of LSCs, we performed a comparative DNA microarray analysis using total RNA isolated from non-BCR-ABL-expressing Lin-Sca-1+c-Kit+, BCR-ABL- and BCR-ABL-Blk expressing LSCs. This analysis revealed a large group of candidate genes that exhibited changes in the levels of transcription in the Blk expressing LSCs, and uncovered the molecular mechanisms by which Blk suppresses LSCs and CML development.
The Blk pathway functions as a tumor suppressor in chronic myeloid leukemia stem cells.
Age, Specimen part
View SamplesThis work uses a time series in order to decipher gene relationships and consequently to build core regulatory networks involved in Arabidopsis root adaptation to NO3- provision. The experimental approach has been to monitor genome response to NO3- at 3, 6, 9, 12, 15 and 20 min, using ATH1 chips. This high-resolution time course analysis demonstrated that the previously known primary nitrate response is actually preceded by very fast (within 3 min) gene expression modulation, involving genes/functions needed to prepare plants to use/reduce NO3-. State-space modeling (a machine learning approach) has been used to successfully predict gene behavior in unlearnt conditions.
Predictive network modeling of the high-resolution dynamic plant transcriptome in response to nitrate.
Specimen part, Treatment
View Samples