External stimulations of cells by hormones, growth factors or cytokines activate signal transduction pathways that subsequently induce a rearrangement of cellular gene expression. The representation and analysis of changes in the gene response is complicated, and essentially consists of multiple layered temporal responses. In such situations, matrix factorization techniques may provide efficient tools for the detailed temporal analysis. Related methods applied in bioinformatics intentionally do not take prior knowledge into account. In signal processing, factorization techniques incorporating data properties like second-order spatial and temporal structures have shown a robust performance. However, large-scale biological data rarely imply a natural order that allows the definition of an autocorrelation function. We therefore develop the concept of graph-autocorrelation. We encode prior knowledge like transcriptional regulation, protein interactions or metabolic pathways as a weighted directed graph. By linking features along this underlying graph, we introduce a partial ordering of the samples to define an autocorrelation function. Using this framework as constraint to the matrix factorization task allows us to set up the fast and robust graph decorrelation (GraDe) algorithm. To analyze the alterations in the gene response in IL-6 stimulated primary mouse hepatocytes by GraDe, a time-course microarray experiment was performed. Extracted gene expression profiles show that IL-6 activates genes involved in cell cycle progression and cell division in a time-resolved manner. On the contrary, genes linked to metabolic and apoptotic processes are down-regulated indicating that IL-6 mediated priming rendered hepatocytes more responsive towards cell proliferation and reduces expenses for the energy household.
Knowledge-based matrix factorization temporally resolves the cellular responses to IL-6 stimulation.
Specimen part, Treatment, Time
View SamplesBy WHO 2008, CEBPA-mutated AML became a provisional subentity, but it remains to be clarified how CEBPAmut AML with multilineage dysplasia (MLD; 50% dysplastic cells in 2-3 lineages) but no other MDS-related feature should be classified. We investigated 108 CEBPAmut AML (15.7-87.6 years) for the impact of MLD and genetic features. MLD-positive patients differed from MLD-negative only by lower mean WBC counts (p=0.004), but not by other blood values, biologic characteristics, cytogenetic risk profiles, or additional molecular markers (NPM1mut, FLT3-ITD/TKD, RUNX1, MLL-PTD, IDH1/2). Biallelic CEBPAmut differed from wild-type-cases by differential expression of 213 genes, but did not differ significantly between MLD-positive/-negative patients. Survival outcomes were improved for females and those <60 years, intermediate versus adverse karyotypes (p=0.021), and for biallelic versus monoallelic/homozygous CEBPAmut (p=0.060) in case of FLT3-ITD-negativity. In contrast, 2-year OS (MLD+: 56.5%; MLD-: 65.5%) and 2-year EFS (MLD+: 13.8 months; MLD-: 16.3 months) did not differ significantly between MLD-positive/-negative patients. By univariable Cox regression analysis, gender, age, WBC count and MRC-cytogenetic risk category only were prognostically relevant for OS, while MLD was irrelevant. Therefore, CEBPAmut AML patients should be characterized only according to mut-status, cytogenetic risk groups, or additional mutations, whereas dysplasia is not relevant for this subtype.
Multilineage dysplasia does not influence prognosis in CEBPA-mutated AML, supporting the WHO proposal to classify these patients as a unique entity.
Specimen part, Disease, Disease stage
View SamplesPrimary mediastinal B-cell lymphoma (PMBL) and classical Hodgkin lymphoma (cHL) share a frequent constitutive activation of Janus-activated kinase (JAK) / signal transducer and activator of transcription (STAT) signaling pathway. Due to complex non-linear relations within the pathway, key dynamic properties remained to be identified to predict possible strategies for intervention. To untangle these features, we used dynamic pathway modeling that employs model development and calibration based on extensive quantitative data generation. Quantitative data were collected on JAK/STAT pathway signaling components in two lymphoma-derived cell lines, MedB-1 and L1236, representative of PMBL and cHL, respectively. We showed that the amounts of STAT5 and STAT6 are higher whereas the amount of SHP1 is lower in the two lymphoma cell lines compared to B cells from healthy donors. Distinctively, L1236 cells harbor more JAK2 and less SHP1 molecules per cell than MedB-1 or control cells. In our experimental setting interleukin-13 (IL13) stimulation levels remained constant over time. In MedB-1 cells surface IL13 receptor alpha 2 had a strong IL13-sequestering/decoy function. In both lymphoma cell lines we observed IL13-induced activation of interleukin-4 receptor alpha, JAK2 and STAT5, but not of STAT6, which was highly phosphorylated even without stimulus. Furthermore, the known STAT-inducible negative regulators CISH and SOCS3 were up-regulated within 2 hours in MedB-1 but not in L1236 cells. Global transcription profiling revealed 11 early and 16 sustained common genes up-regulated by IL13 in both lymphoma cell lines. Based on this detailed information we established two individual mathematical models, MedB-1 and L1236 model, which were able to describe the respective experimental data. Sensitivity analysis of the model identified six possible therapeutic targets able to reduce gene expression levels in L1236 cells and three in MedB-1 cells. By inhibition of STAT5 phosphorylation we successfully validated one of the predicted targets demonstrating the potential of the approach in guiding target identification for highly deregulated signaling networks in cancer cells. We established mathematical models of the JAK/STAT pathway in two lymphoma cell types (PMBL and cHL), able to reproduce experimental data and to predict possible therapeutic targets.
Dynamic mathematical modeling of IL13-induced signaling in Hodgkin and primary mediastinal B-cell lymphoma allows prediction of therapeutic targets.
Cell line, Time
View SamplesThis SuperSeries is composed of the SubSeries listed below.
BRAFV600E-Associated Gene Expression Profile: Early Changes in the Transcriptome, Based on a Transgenic Mouse Model of Papillary Thyroid Carcinoma.
Sex, Age
View SamplesBRAFV600E mutation is the most frequent molecular event in papillary thyroid carcinoma. The relation of this genetic alteration with the factors od poor prognosis has been reported as well as its influence on PTC gene signature. However human material disables distinction of cancer causes from its effect.
BRAFV600E-Associated Gene Expression Profile: Early Changes in the Transcriptome, Based on a Transgenic Mouse Model of Papillary Thyroid Carcinoma.
Sex, Age
View SamplesBRAFV600E mutation is the most frequent molecular event in papillary thyroid carcinoma. The relation of this genetic alteration with the factors od poor prognosis has been reported as well as its influence on PTC gene signature. However human material disables distinction of cancer causes from its effect.
BRAFV600E-Associated Gene Expression Profile: Early Changes in the Transcriptome, Based on a Transgenic Mouse Model of Papillary Thyroid Carcinoma.
Sex, Age
View SamplesTo generate an unbiased view of changes to the retinal gene network in Neurog2 retinal mutants, we generated and compared the P2 transcriptomes from control, heterozygote and mutant mice. A pair of P2 retinas from each biologic replicate were used to produce libraries for high throughput sequencing (n = 5 biologic replicates/genotype). Reads were aligned with BWA and Bowtie programs to the mm10 genome. Aligned reads were then analyzed for differentially expressed transcripts using the CuffDiff program in the Galaxy online bioinformatics package (www.usegalaxy.org). Overall design: Total RNA from Neurog2CKO/CKO(wildtype; n = 5), Chx10Cre;Neurog2CKO/+(heterozygote; n = 5), and Chx10Cre;Neurog2CKO/CKO(mutant; n = 5) P2 retinas.
Requirements for Neurogenin2 during mouse postnatal retinal neurogenesis.
Specimen part, Cell line, Subject
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Cytokeratin-19 positivity is acquired along cancer progression and does not predict cell origin in rat hepatocarcinogenesis.
Specimen part
View SamplesSilencing HoxA1 in vivo by intraductal delivery of nanoparticle-formulated siRNA reduced mammary tumor incidence by 75% , reduced cell proliferation, and prevented loss of ER and PR expression.
Silencing HoxA1 by intraductal injection of siRNA lipidoid nanoparticles prevents mammary tumor progression in mice.
Age, Specimen part
View SamplesAnalysis of early changes in the R-H model of carcinogenesis in order to investigate the relationship between oval cell proliferation and preneoplastic foci
Cytokeratin-19 positivity is acquired along cancer progression and does not predict cell origin in rat hepatocarcinogenesis.
Specimen part
View Samples