Project description:Transcriptional profiling by array of CML CD34+ cells to understand the response of chronic myeloid leukaemia stem cells to an EZH2 inhibitor, GSK343.
Project description:Transcriptional profiling of four cell populations to understanding chronic myeloid leukaemia in humans. The populations are normal haematopoietic stem cells (HSC), normal progenitor cells (HPC), CML stem cells (LSC) and CML progenitor cells (LPC).
Project description:Imatinib therapy is first-line treatment for chronic myeloid leukemia (CML), and its failure to target CML progenitor/stem cells may lead to an increased risk of relapse. We report here that fenretinide, a well-tolerated vitamin A derivative, is capable of eradicating primitive CML progenitor/stem cells and significantly enhances the efficacy of imatinib at physiologically achievable concentrations. As tested by colony forming cell assays, formation of various colonies derived primitive CML CD34+ cells was significantly suppressed by fenretinide, particularly with respect to the formation of colonies derived from erythroid progenitors and more primitive CML progenitor/stem cells. Also, fenretinide significantly enhanced the ability of imatinib to suppress the formation of the colonies. Moreover, fenretinide was able to induce apoptosis in primitive CML CD34+ cells while sparing the normal counterparts. In particular, primitive CML CD34+CD38- cells appeared to be most sensitive to fenretinide induced apoptosis. Through transcriptome analysis and molecular validation, we further showed that fenretinide induced apoptosis in CML CD34+ cells was probably mediated by a series of stress responsive events which were likely triggered by elevated levels of intracellular reactive oxygen species. Accordingly, the combination of fenretinide and imatinib may provide a potential solution for overcoming relapse and resistance in CML. Experiment Overall Design: Transcriptome profiles of CML CD34+ cells with and without fenretinide treatment were analyzed using whole genome expression arrays (Affymetrix HG-U133 Plus 2.0) in four CML patients (CML32, CML33, CML34 and CML35, see Table 1). To minimize potential data biases, both treated and untreated cell samples were maintained in culture for 48 hours before hybridization.
Project description:We screened TKI-treated-CML-samples in different-phases based on < or >10% copies of BCR-ABL, undetected and control-samples for generating transcriptomics-profile. Transcriptionally, three clusters were identified which showed correlation with BCR-ABL transcript-levels i.e. <10% copies (I-cluster) , undetectable (II-cluster) and >10% copies (III-cluster). CML-new cases as well as Tyrosiine kinase treated-different phases of CML
Project description:Tyrosine 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-M-NM-2-catenin complex formation, as well as enhanced M-NM-2-catenin nuclear translocation and transcriptional activity. Increased exogenous Wnt-mediated M-NM-2-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-M-NM-2-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. RNA was obtained from CML CD34+ cells treated with or without IM (5M-NM-<M) and MSC for 96 hours, amplified, labeled and hybridized to GeneChip 1.0 arrays (Affymetrix, Santa Clara, CA). Microarray data analysis was performed using R (version 2.9) with genomic analysis packages from Bioconductor (version 2.4). The 33297 probes represented on the microarray were filtered by cross-sample mean, and for standard deviation of greater than the 25% quantile, yielding 18624 probes representing 12553 genes. Linear regression was used to model the gene expression with the consideration of a 2x2 factorial design and matched samples. Differentially expressed genes were identified by calculating empirical Bayes moderated t-statistic, and p-values were adjusted by FDR using the M-bM-^@M-^\LIMMAM-bM-^@M-^] package. Gene Set Enrichment Analysis (GSEA) was performed using GSEA software version 2.04 to detect enrichment of predetermined gene sets using t-scores from all genes for 1263 gene sets in the C2 (curated gene sets) category from the Molecular Signature Database (MsigDB).
Project description:This study used snATAC-seq to profile Chromatin accessibility in 26 day-old iPSC-derived kidney organoids, treated with TGFB1, the EzH2 inhibitor GSK343, a combination of both or a vehicle control for 48 hours (days 24-26) before harvesting. 2 organoids per condition were pooled and dissociated using a cold-active protease. Nuclei were extracted and profiled using the 10X Genomics Single-cell ATAC reagent kit v1.1. Libraries were sequenced using paired-end reads on an Illumina NovaSeq 6000. Initial processing was performed using CellRanger ATAC v1.2.0 (10X Genomics).
Project description:Transcriptional profiling comparing the genes upregulated or downregulated by active hGR-Xebf3 by treating hormone DEX to those by non-active hGR-Xebf3 in Xenopus animal caps. Three experimental conditions, Noggin and hGR-Xebf3 without DEX treatment (1), Noggin and hGR-Xebf3 with DEX treatment (2), and Noggin and hGR with DEX treatment (3). Comparison, 1 vs.2 and 1 vs. 3. Biological replicates, 4 times
Project description:This study used scRNA-seq to characterise the transcriptome in 26 day-old iPSC-derived kidney organoids, treated with TGFB1, the EzH2 inhibitor GSK343, a combination of both or a vehicle control for 48 hours (days 24-26) before harvesting. 2 organoids per condition were pooled and dissociated using a cold-active protease. Nuclei were extracted and profiled using the 10X Genomics Single-cell 3' V3 kits. Libraries were sequenced using paired-end reads on an Illumina NextSeq 500. Initial processing was performed using CellRanger v3.1.0 (10X Genomics).
Project description:Analysis of lin-CD34+CD45+ (iCD34+) cell population from two normal bone marrow-derived (BM1K and BM9) iPSCs and two CML (CML15 and CML17) iPSCs . CML iCD34+ cells have characteristics similar to primary CML leukemia stem cell in patients. Results provide insight into molecular profile characterized CML iCD34 and mechanism of its maintenance and drug resistance. iCD34+ cell samples obtained from two control BM1K and BM9 iPSCs (both for the same normal donor) and CML15 and CML17 iPSCs (both from the same patient in chronic phase of CML). Each group was treated with DMSO (control) or 5 μM imatinib. The complete phenotype for iCD34+ cells: lin-CD34+CD45+CD90+CD117+CD45RA-. This population also inclyde Rhodaminelow and ALDKhigh cells.
Project description:Purpose:The purpose of this study is to detect activated or silenced genes during LPS-induced dendritic cell maturation. Gene expression differences between two samples could be found using transcriptome profiling (RNA-seq) analysis. Methods:Mouse dendritic cells were generated from bone marrow cells in RPMI-1640 medium with recombinant mouse GM-CSF and IL-4, mature DCs were obtained after LPS induced maturation. Immature DCs and mature DCs were sorted respectively based on maturation marker CD86 and Iab(MHCII) using flowcytrometer. DC mRNA profiles were generated by deep sequencing,using Illumina Results: We mapped about 10 million sequence reads per sample to the mouse genome, identified 1,300 upregulated genes and 1,475 dow regulated genes during dendritic cell maturation. DC mRNA profiles immature and mature moouse BMDCs were generated by deep sequencing