This SuperSeries is composed of the SubSeries listed below.
Compensatory RNA polymerase 2 loading determines the efficacy and transcriptional selectivity of JQ1 in Myc-driven tumors.
Specimen part, Treatment
View SamplesWe here use B-cell tumors as a model to address the mechanism of action of JQ1, a widely used BET inhibitor.
Compensatory RNA polymerase 2 loading determines the efficacy and transcriptional selectivity of JQ1 in Myc-driven tumors.
Treatment
View SamplesThe tumor suppressor p53 is a transcription factor that controls the response to stress. Here, we dissected the transcriptional programs triggered upon restoration of p53 in Myc-driven lymphomas, based on the integrated analysis of p53 genomic occupancy and gene regulation. p53 binding sites were identified at promoters and enhancers, both characterized by the pre-existence of active chromatin marks. p53 recruitment at these sites was mainly mediated through protein-protein or protein-chromatin interactions and, only for a small fraction, through recognition of the 20 base-pair p53 consensus motif. At promoters, p53 binding to the consensus motif was associated with gene induction, but not repression, indicating that the latter was most likely indirect. p53 also targeted unmarked distal sites devoid of activation marks, at which binding was prevalently driven by recognition of the consensus motif. At all sites, our data highlighted a functional role for the canonical, unsplit consensus element, but did not provide evidence for p53 recruitment by split motifs. Altogether, our data highlight key features of genome recognition by p53 and provide unprecedented insight into the pathways associated with p53 re-activation and tumor regression. Overall design: Total RNA profiling of gene expression in Eµ-myc lymphomas following p53 restoration by Illumina sequencing
Genome-wide analysis of p53-regulated transcription in Myc-driven lymphomas.
Specimen part, Cell line, Subject
View SamplesOver-expression of the Myc transcription factor causes its widespread interaction with regulatory domains in the genome, but leads to the up- and down-regulation of discrete sets of genes. The molecular determinants of these selective transcriptional responses remain elusive. Here, we present an integrated time-course analysis of transcription and mRNA dynamics following Myc activation in proliferating mouse fibroblasts, based on chromatin immunoprecipitation, metabolic labeling of newly synthesized RNA, extensive sequencing and mathematical modeling. Transcriptional activation correlated with the highest increases in Myc binding at promoters. Repression followed a reciprocal scenario, with the lowest gains in Myc binding. Altogether, the relative abundance (henceforth, “share”) of Myc at promoters was the strongest predictor of transcriptional responses in diverse cell types, predominating over Myc's association with the co-repressor Miz1. Myc activation elicited immediate loading of RNAPII at activated promoters, followed by increases in pause-release5, while repressed promoters showed opposite effects. Gains and losses in RNAPII loading were proportional to the changes in the Myc share, suggesting that repression by Myc may be largely indirect, owing - at least in part - to competition for limiting amounts of RNAPII. Secondary to the changes in RNAPII loading, the dynamics of elongation and pre-mRNA processing were also rapidly altered at Myc regulated genes, leading to the transient accumulation of partially or aberrantly processed mRNAs. Altogether, our results shed light on how over-expressed Myc alters the various phases of the RNAPII cycle and the resulting transcriptional response. Overall design: Time course profiling of 4sU-labeled and total RNA upon Myc activation in 3T9-MycER mouse fibroblasts
Integrative analysis of RNA polymerase II and transcriptional dynamics upon MYC activation.
Specimen part, Subject
View SamplesRNAseq analysis of YAP and Myc induced in quiescent and confluent 3T9 fibroblasts Overall design: RNAseq analysis of YAP and Myc induced in quiescent and confluent 3T9 fibroblasts
Transcriptional integration of mitogenic and mechanical signals by Myc and YAP.
Specimen part, Cell line, Subject
View SamplesTyrosine kinase inhibitors (TKI) are highly effective in treatment of chronic myeloid leukemia (CML) but do not eliminate leukemia stem cells (LSC), which remain a potential source of relapse. TKI treatment effectively inhibits BCR-ABL kinase activity in CML LSC, suggesting that additional kinase-independent mechanisms contribute to LSC preservation. We investigated whether signals from the bone marrow (BM) microenvironment protect CML LSC from TKI treatment. Coculture with human BM mesenchymal stromal cells (MSC) significantly inhibited apoptosis and preserved CML stem/progenitor cells following TKI exposure, maintaining colony forming ability and engraftment potential in immunodeficient mice. We found that the N-Cadherin receptor plays an important role in MSC-mediated protection of CML progenitors from TKI. N-Cadherin-mediated adhesion to MSC was associated with increased cytoplasmic N-Cadherin--catenin complex formation, as well as enhanced -catenin nuclear translocation and transcriptional activity. Increased exogenous Wnt-mediated -catenin signaling played an important role in MSC-mediated protection of CML progenitors from TKI treatment. Our results reveal a close interplay between N-Cadherin and the Wnt--catenin pathway in protecting CML LSC during TKI treatment. Importantly, these results reveal novel mechanisms of resistance of CML LSC to TKI treatment, and suggest new targets for treatment designed to eradicate residual LSC in CML patients.
Microenvironmental protection of CML stem and progenitor cells from tyrosine kinase inhibitors through N-cadherin and Wnt-β-catenin signaling.
Specimen part
View SamplesTranscriptional profiling of NKAES-derived NK cells after 7 days of culture compared to primary human NK cells and NK cells stimulated by low or high dose IL2 after 7 days of culture.
Expansion of highly cytotoxic human natural killer cells for cancer cell therapy.
Specimen part
View SamplesTo identify new markers for minimal residual disease (MRD) detection in acute lymphoblastic leukemia (ALL), we compared genome-wide gene expression of lymphoblasts from 270 patients with newly diagnosed childhood ALL to that of normal CD19 CD10 B-cell progenitors (n=4). Expression of 30 genes differentially expressed by > 3-fold in at least 25% of cases of ALL (or 40% of ALL subtypes) was tested by flow cytometry in 200 B-lineage ALL and 61 nonleukemic BM samples, including samples containing hematogones. Of the 30 markers, 22 (CD44, BCL2, HSPB1, CD73, CD24, CD123, CD72, CD86, CD200, CD79b, CD164, CD304, CD97, CD102, CD99, CD300a, CD130, PBX1, CTNNA1, ITGB7, CD69, CD49f) were differentially expressed in up to 81.4% of ALL cases; expression of some markers was associated with the presence of genetic abnormalities. Results of MRD detection by flow cytometry with these markers correlated well with those of molecular testing (52 follow-up samples from 18 patients); sequential studies during treatment and diagnosis-relapse comparisons documented their stability. When incorporated in 6-marker combinations, the new markers afforded the detection of 1 leukemic cell among 105 BM cells. These new markers should allow MRD studies in all B-lineage ALL patients, and substantially improve their sensitivity.
New markers for minimal residual disease detection in acute lymphoblastic leukemia.
Specimen part
View SamplesMixed-lineage leukemias represent about 3-5% of acute leukemias occurring in patients of all ages and comprise several different subtypes (biphenotypic, bilineal, and lineage switch). The optimal therapeutic approach to these cases, especially in pediatric patients, has not been defined. We used microarrays to detail the gene expression of pediatric patients with biophenotypic leukemia.
Acute mixed lineage leukemia in children: the experience of St Jude Children's Research Hospital.
No sample metadata fields
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Genome-scale analysis of DNA methylation in lung adenocarcinoma and integration with mRNA expression.
Sex, Age, Specimen part, Race, Subject
View Samples