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GSE70124
Homo sapiens
36 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Background: Acute myeloid leukemia (AML) is driven by somatic mutations and genomic rearrangements affecting >20 genes. Many of these are recent discoveries and how this molecular heterogeneity dictates AML pathophysiology and clinical outcome remains unclear. Methods: We sequenced 111 leukemia genes for driver mutations in 1540 AML patients with cytogenetic and clinical data. We modeled AMLs genomic structure, defining genetic interactions, patterns of temporal evolution and clinical correlations. Results: We identified 5,236 driver mutations involving 77 loci, including hotspot mutations in MYC. We found 1 driver mutation in 96% patients, and 2 in 85%. Gene mutations implicated in age related clonal hematopoiesis (DNMT3A, ASXL1, TET2) were the earliest in AML evolution, followed by highly specific and ordered patterns of co-mutation in chromatin, transcription and splicing regulators, NPM1 and signaling genes. The patterns of co-mutation compartmentalize AML into 12 discrete molecular classes, each presenting with distinct clinical manifestation. Amongst these, mutations in chromatin and spliceosome genes demarcate a molecularly heterogeneous subgroup enriched for older AML patients currently classified as intermediate risk and results in adverse prognosis. Two- and three-way genetic interactions often implicating rare genes/mutation-hotspots, markedly redefined clinical response and long-term curability, with the NPM1:DNMT3A:FLT3ITD genotype (6% patients) identifying poor prognosis disease, whereas within the same class NPM1:DNMT3A:NRASG12/13 (3%) associated with favorable outlooks. Conclusions: 79% of AML is molecularly classified in 12 genomic subgroups. These represent distinct molecular phylogenies, implicating complex genotypes. Delineation of higher-order genomic relationships, guide the development of personally tailored classification, prognostication and clinical protocols. Similar studies across cancer types are warranted.
Publication Title
Genomic Classification and Prognosis in Acute Myeloid Leukemia.
Sample Metadata Fields
Specimen part, Disease
View Samples- Homo sapiens
- 82 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
PBRM1 was found to be mutated in a high percentage of clear cell RCCs. We performed knockdown of PBRM1 via siRNA and compared with scrambled control in three different RCC cell lines.
Publication Title
Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma.
Sample Metadata Fields
Specimen part, Cell line, Treatment
View Samples- Homo sapiens
- 109 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Systematic sequencing of renal carcinoma reveals inactivation of histone modifying genes.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 109 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Systematic somatic mutation screening of 4000 genes in human clear cell renal cell carcinoma. Information on corresponding somatic mutations in each sample can be found at http://www.sanger.ac.uk/genetics/CGP/Studies/.
Publication Title
Systematic sequencing of renal carcinoma reveals inactivation of histone modifying genes.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 87 Downloadable Samples
Illumina HiSeq 2000
Description
Large-scale genomic profiling efforts have facilitated the characterization of molecular alterations in cancers and aided the development of targeted kinase inhibitors for a wide array of cancer types. However, resistance to these targeted therapies invariably develops and limits their clinical efficacy. Targeting tumours with kinase inhibitors induces complex adaptive survival programs that promote the persistence of a fraction of the original cancer cell population, facilitating the eventual outgrowth of inhibitor-resistant tumour clones following clonal evolution. Here we show that the addition of a newly identified transcriptional repressor, THZ1, to targeted cancer therapy enhances cell killing and impedes the emergence of drug-resistant cell populations in cellular and in vivo cancer models with diverse genetic dependencies. We propose that targeted therapy induces a state of transcriptional dependency in a subpopulation of cells poised to become drug tolerant. THZ1 can exploit this dependency by blocking dynamic transcriptional responses, remodelling of enhancers and key signalling outputs required for tumour cell survival in the setting of targeted cancer therapies. These findings suggest that the addition of THZ1 to targeted cancer therapies is a promising broad-based strategy to hinder the emergence of drug-resistant cancer cell populations. Overall design: RNA-seq in tumor cell lines treated with targeted therapies and/or transcriptional inhibitors
Publication Title
Suppression of Adaptive Responses to Targeted Cancer Therapy by Transcriptional Repression.
Sample Metadata Fields
Specimen part, Cell line, Subject, Compound
View Samples- Arabidopsis thaliana
- 48 Downloadable Samples
- Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)
Description
Auxin-dependent transcript abundance was assayed by transferring 6 day old Arabidopsis grown on a a nylon mesh to IAA-containing or control media
Publication Title
A kinetic analysis of the auxin transcriptome reveals cell wall remodeling proteins that modulate lateral root development in Arabidopsis.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 36 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
In this study, we aim to identify candidate biomarkers which may be useful as surrogate indicators of toxicity for pre-clinical development of panPPAR-agonist drug candidates. Gene expression microarray, histopathology and clinical chemistry data were generated from liver, heart, kidney and skeletal muscles of three groups of mice administered with three different dosages of an experimental pan-peroxisome proliferator-activated receptor (pan-PPAR) agonist, PPM-201, for 14 days. The histopathology and clinical chemistry data were compared with the gene expression analysis and candidate biomarker genes were identified.
Publication Title
Simultaneous non-negative matrix factorization for multiple large scale gene expression datasets in toxicology.
Sample Metadata Fields
Specimen part, Treatment
View Samples- Homo sapiens
- 6 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
A major contributor to cancer mortality is recurrence and subsequent metastatic transformation following therapeutic intervention. In order to develop new treatment modalities or improve the efficacy of current ones it is important to understand the molecular mechanisms that promote therapy-resistance to cancer cells. One pathway that has been demonstrated to therapy resistance is autophagy, a self-digestive process that can eliminate unnecessary or damaged organelles to protect cancer cells from necrosis. Effective targeting of this pathway could lead to the development of new therapies. In our studies, we found that the VEGF-C/NRP-2 axis is involved in the activation of autophagy, which is essential for the survival of cancer cells following chemotherapy treatment. Furthermore, we identified two VEGF-C/NRP-2-regulated genes, LAMP-2 and WDFY-1 that have previously been suggested to participate in autophagy and vesicular trafficking. The upregulation of WDFY-1 upon depleted level of VEGF-C contributed to cytotoxic drug-mediated cell death. Altogether, these data suggest a link between VEGF-C/neuropilin-2 axis and cancer cell survival despite the presence of chemotherapy-induced stress.
Publication Title
Autophagy control by the VEGF-C/NRP-2 axis in cancer and its implication for treatment resistance.
Sample Metadata Fields
Cell line
View Samples- Arabidopsis thaliana
- 4 Downloadable Samples
- Illumina Genome Analyzer
Description
The trade-off between growth and immunity is crucial for survival in plants. An antagonistic interaction has been observed between the growth-promoting hormone brassinosteroid and pathogen associated molecular pattern (PAMP) signals, which induce immunity but inhibit growth, however the underlying molecular mechanism has remained unclear. The PRE-IBH1-HBI1 triple helix-loop-helix/basic helix-loop-helix (HLH/bHLH) cascade has been shown to mediate growth responses to several hormonal and environmental signals, but its downstream targets and role in immunity remain unknown. Here, we performed genome-wide analyses of HBI1 target genes in Arabidopsis. The results show that HBI1 regulates a set of genes that largely overlaps with targets of PIFs, but displays both similar and unique transcriptional activities compared to PIFs, supporting a role in fine-tuning the network through cooperation and antagonism with other DNA-binding factors of the network. Furthermore, HBI1 also negatively regulates a subset of defense response genes. Two PAMPs, flagellin and elongation factor, repressed HBI1 expression, whereas overexpression of HBI1 reduced the PAMP-induced growth inhibition, defense gene expression, reactive oxygen species (ROS) production, and flg22-induced resistance to Pseudomonas syringae pathovar tomato DC3000. These data indicate that HBI1 is a node for crosstalk between hormone and immune pathways. This study demonstrates that the PRE-IBH1-HBI1 module integrates hormone and pathogen signals, and thus plays a central role in the balance between growth and immunity in plants. Overall design: Compare the transcriptome of HBI1-Ox and wild type.
Publication Title
The bHLH transcription factor HBI1 mediates the trade-off between growth and pathogen-associated molecular pattern-triggered immunity in Arabidopsis.
Sample Metadata Fields
Subject
View Samples- Rattus norvegicus
- 44 Downloadable Samples
- Affymetrix Rat Genome U34 Array (rgu34a)
Description
We used microarrays to analyze gene expression changes in liver after treatment of rats with two compounds from drug development (R1, R2) to identify potential effects related to hepatotoxicity.
Publication Title
Gene expression-based in vivo and in vitro prediction of liver toxicity allows compound selection at an early stage of drug development.
Sample Metadata Fields
Sex, Specimen part, Treatment
View Samples