Purpose: We tested global gene transcriptome changes by RNA-sequencing analysis in the offspring breast tumors of SV40 transgenic mice to further identify key epigenetic-controlled genes in regulation of the prenatal/maternal BSp diet-mediated early breast cancer prevention. Method: Mouse offspring mammary tumor mRNA from control and maternal BSp treatment were generated by deep sequencing, in duplicate or triplicate, using Illumina NextSeq500 platform (GPL19057). The sequence reads that passed quality filters were analyzed. We utilized the R/Bioconductor package DESeq to evaluate differential gene expression for sequence count data by the use of negative binomial distributio. qRTâ€“PCR validation was performed using TaqMan and SYBR Green assays. Conclusions: Our data showed differential transcriptome distribution in the breast tumors of mouse offspring between the control and prenatal/maternal BSp treatment groups. Overall design: Total RNA obtained from the offspring breast tumors of SV40 transgenic mice with mothers fed either control or BSp diets, and analyzed by Illumina NextSeq500 platform (GPL19057).
Temporal Efficacy of a Sulforaphane-Based Broccoli Sprout Diet in Prevention of Breast Cancer through Modulation of Epigenetic Mechanisms.
Age, Cell line, Treatment, SubjectView Samples
Due to limited bio-availability of Fe, plants evolved adaptive alterations in development regulated at the transcriptional level. We investigated the early transcriptional response to Fe deficiency.
Early iron-deficiency-induced transcriptional changes in Arabidopsis roots as revealed by microarray analyses.
Specimen partView Samples
Several recently emerging ChIP-seq (chromatin immunoprecipitation followed by sequencing) based methods perform chemical steps on bead-bound immunoprecipitated chromatin, posing a challenge for generating similarly treated input controls required for bioinformatics and data quality analyses. Here we present a versatile method for producing technique-specific input controls for ChIP-based methods that utilize additional bead-bound processing steps. Application of this method allowed for discovery of a novel CTCF binding motif from ChIP-exo data. Overall design: HeLa cells were transfected with either a scrambled siRNA or one of two CTCF siRNAs (Thermo Fisher Scientific ? Life technologies) using Lipofectamine RNAiMAX (Thermo Fisher Scientific - Life technologies) and incubated for 24 hr.
PAtCh-Cap: input strategy for improving analysis of ChIP-exo data sets and beyond.
Cell line, SubjectView Samples
The emerging correlation between aberrant DNA methylation patterns leading to transcriptional responses that promote and progress many cancers has prompted an interest in discerning the associated regulatory mechanisms. ZBTB33 (also known as Kaiso) is a specialized transcription factor that selectively recognizes mCpG-containing sites as well as a sequence-specific DNA target (termed the KBS) utilizing three Cys2His2 zinc fingers. Increasing reports link ZBTB33 overexpression and transcriptional activities with metastatic potential and poor prognosis, though the specific cellular consequences appear to be dependent on disease phenotype. There is currently little mechanistic insight into how various cellular phenotypes are then able to harness the transcriptional capabilities of ZBTB33 to differentially promote and progress the disease state. Here we have mechanistically interrogated the cell cycle responses mediated by the transcriptional activities of ZBTB33 in two different cell lines. Utilizing a series of ZBTB33 depletion and overexpression studies, we have determined that in HeLa cells ZBTB33 directly occupies the promoter regions of cyclin D1 and cyclin E1 in a KBS and methyl-specific manner, respectively, inducing increased proliferation by promoting RB1 hyper-phosphorylation, allowing for E2F transcriptional activity that coordinates an accelerated G1- to S-phase transition. Conversely, in HEK293 cells ZBTB33 indirectly regulates Cyclin E abundance resulting in reduced RB1 phosphorylation, decreased E2F activity and a decelerated transition through G1-phase. Thus, we have identified a novel mechanism by which ZBTB33 directly mediates the highly coordinated cyclin D1/cyclin E1/RB1/E2F signaling pathway controlling the passage through the G1-phase restriction point and accelerating cellular proliferation in a cancer cell line. Overall design: Determination of cellular and transcriptional consequences for ZBTB33 depletion in HeLa cells.
Cell-specific Kaiso (ZBTB33) Regulation of Cell Cycle through Cyclin D1 and Cyclin E1.
Cell line, SubjectView Samples
Ovarian carcinoma has the highest mortality rate among gynecological malignancies. In this project, we investigated the hypothesis that molecular markers are able to predict outcome of ovarian cancer independently of classical clinical predictors, and that these molecular markers can be validated using independent data sets. We applied a semi-supervised method for prediction of patient survival. Microarrays from a cohort of 80 ovarian carcinomas (TOC cohort) were used for the development of a predictive model, which was then evaluated in an entirely independent cohort of 118 carcinomas (Duke cohort). A 300 gene ovarian prognostic index (OPI) was generated and validated in a leave-one-out approach in the TOC cohort (Kaplan-Meier analysis, p=0.0087). In a second validation step the prognostic power of the OPI was confirmed in an independent data set (Duke cohort, p=0.0063). In multivariate analysis, the OPI was independent of the postoperative residual tumour, the main clinico-pathological prognostic parameter with an adjusted hazard ratio of 6.4 (TOC cohort, CI 1.8 23.5, p=0.0049) and 1.9 (Duke cohort, CI 1.2 3.0, p=0.0068). We constructed a combined score of molecular data (OPI) and clinical parameters (residual tumour), which was able to define patient groups with highly significant differences in survival. The integrated analysis of gene expression data as well as residual tumour can be used for optimised assessment of prognosis. As traditional treatment options are limited, this analysis may be able to optimise clinical management and to identify those patients that would be candidates for new therapeutic strategies.
A prognostic gene expression index in ovarian cancer - validation across different independent data sets.
Specimen part, Disease stageView Samples
Hypertension remains a poorly understood condition, and the understanding of the sympathetic nervous systems role in this disease remains even more limited. In this study, RNA-sequencing is used to identify transcriptomal differences in the sympathetic stellate ganglia between the 16-week-old normotensive wistar strain and the spontaneously hypertensive rat strain.This dataset should allow for further molecular characterisation of hypertensive changes in a cardiac-innervating sympathetic ganglion. Overall design: Comparison of normotensive and hypertensive rat stellate ganglia. 4 biological replicates for both 16 week wistar and SHR stellate ganglia samples were contrasted
Neurotransmitter Switching Coupled to β-Adrenergic Signaling in Sympathetic Neurons in Prehypertensive States.
No sample metadata fieldsView Samples
Transcriptome profiling using RNA-seq of ß-TC3 cell, a mouse pancreatic cell line used in the study of novel Cis-regulatory elements for the Pax6 gene . Overall design: Total RNA was collected and a Illumina sequencing libraries prepared from two biological replicates of cultured ß-TC3 cells.
Functional characteristics of novel pancreatic Pax6 regulatory elements.
Cell line, SubjectView Samples
Transcriptome profiling using RNA-seq of MV+, a mouse lens epithelium cell line expressing Pax6 and RAG renal adenocarcinoma cell line which does not express Pax6. Overall design: Total RNA was collected and a Illumina sequencing libraries prepared from three biological replicates of cultured MV+ and RAG cells.
Polymer Simulations of Heteromorphic Chromatin Predict the 3D Folding of Complex Genomic Loci.
Cell line, SubjectView Samples
Gene expression analysis of two different mouse keratinocytes using RNA-Seq Overall design: RNA was collected and analyzed for two biological replicates each from two different mouse keratinocyte cell lines
Evolutionary re-wiring of p63 and the epigenomic regulatory landscape in keratinocytes and its potential implications on species-specific gene expression and phenotypes.
Specimen part, Cell line, SubjectView Samples
Alveolar rhabdomyosarcomas (ARMS) are aggressive soft-tissue sarcomas affecting children and young adults. Most ARMS tumors express the PAX3-FKHR or PAX7-FKHR (PAX-FKHR) fusion genes resulting from the t(2;13) or t(1;13) chromosomal translocations, respectively. However, up to 25% of ARMS tumors are fusion negative, making it unclear whether ARMS represent a single disease or multiple clinical and biological entities with a common phenotype. To test to what extent PAX-FKHR determine class and behavior of ARMS, we used oligonucleotide microarray expression profiling on 139 primary rhabdomyosarcoma tumors and an in vitro model. We found that ARMS tumors expressing either PAX-FKHR gene share a common expression profile distinct from fusion-negative ARMS and from the other rhabdomyosarcoma variants. We also observed that PAX-FKHR expression above a minimum level is necessary for the detection of this expression profile. Using an ectopic PAX3-FKHR and PAX7-FKHR expression model, we identified an expression signature regulated by PAX-FKHR that is specific to PAX-FKHR-positive ARMS tumors. Data mining for functional annotations of signature genes suggested a role for PAX-FKHR in regulating ARMS proliferation and differentiation. Cox regression modeling identified a subset of genes within the PAX-FKHR expression signature that segregated ARMS patients into three risk groups with 5-year overall survival estimates of 7%, 48%, and 93%. These prognostic classes were independent of conventional clinical risk factors. Our results show that PAX-FKHR dictate a specific expression signature that helps define the molecular phenotype of PAX-FKHR-positive ARMS tumors and, because it is linked with disease outcome in ARMS patients, determine tumor behavior.
Identification of a PAX-FKHR gene expression signature that defines molecular classes and determines the prognosis of alveolar rhabdomyosarcomas.
Sex, Age, Specimen part, Disease, Disease stageView Samples