Mesenchymal Stromal Cells From AML Bone Marrow Are Abnormal by Gene Expression Profiling.

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 1055-1055
Author(s):  
Wencai Ma ◽  
R. Eric Davis ◽  
Rodrigo Jacamo ◽  
Marina Konopleva ◽  
Ramiro Garzon ◽  
...  

Abstract Abstract 1055 Cytogenetic and other evidence suggests that the mesenchymal stromal cell (MSC) is abnormal in bone marrow (BM) affected by acute myelogenous leukemia (AML). To gain further insight into molecular and physiologic abnormalities, we used Affymetrix HG-U133 Plus 2 microarrays to compare gene expression between BM-MSCs from 12 AML patients and BM-MSCs from 4 normal donors (ND). BM-MSCs were purified by in vitro culture as adherent cells with a purity of over 95%. Comparison at the single-gene level between AML and ND samples found only one differentially-expressed probe by t tests at a false-discovery rate (FDR) of 0.1. Comparison by the gene set enrichment analysis (GSEA) method of Subramanian et al., which is a more powerful way to find small differences that are significantly enriched within sets of biologically-related genes, first found that many enriched gene sets were predominantly the result of data from one AML sample. After excluding this sample, GSEA at an FDR of 0.25 found 115 downregulated gene sets for AML BM-MSCs from the Gene Ontology-based “C5” category of the mSigDB collection of gene sets. 19 of the 20 most significantly enriched downregulated gene sets were related to cell cycle progression, indicating that BM-MSCs are less proliferative in AML than in normal BM. An upregulated enriched gene set in AML BM-MSCs, from the “C2” category of curated gene sets, was composed of extracellular matrix genes for keratins, collagen, and laminin; while surprising, this is consistent with reports of BM-derived MSCs differentiating into epithelial cells after autografting, and suggest that BM-MSCs in AML may remodel the extracellular matrix. Overall, these results indicate that BM-MSCs in AML patients are substantially different from normal BM-MSCs. These and other differences could have substantial effects on the BM microenvironment and therapy response in AML, and should be studied further. Disclosures: No relevant conflicts of interest to declare.

2021 ◽  
Vol 33 (2) ◽  
pp. 179
Author(s):  
E. Derisoud ◽  
L. Jouneau ◽  
C. Archilla ◽  
N. Daniel ◽  
Y. Jaszczyszyn ◽  
...  

An increased incidence in early embryo loss has been observed in aged mares. Moreover, the first foal born to a mare is lighter than her subsequent foals, with reported impaired placental function at term. Because trophoblast function may be affected from the embryo stage, the aim of this project was to determine the effect of parity in aged mares on gene expression in Day-8.5 embryos. Middle-aged (13.5±2.2 years) nulliparous (never foaled) (ON) or multiparous (1.8±1.6 foals) (OM) Saddlebred, non-nursing mares were inseminated with the semen of one unique stallion. At 8 days post-ovulation (10 days post-hCG), embryos were recovered by uterine flushing and bisected to obtain samples of pure (trophectoderm, TE) or inner cell mass enriched (ICM) trophoblast. Paired end, non-oriented RNA sequencing was performed with Illumina (NextSEqn 500) on 5 and 6 TE and ICM collected from ON and OM, respectively. Differential expression was analysed with DESEqn 2. Embryo size was included in the model and a P<0.05 cutoff was used after false discovery rate correction. Gene set enrichment analysis (GSEA) was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases. Out of the 13 007 and 12 706 genes expressed in ICM and TE, respectively, only 8 in ICM and 6 in TE were differentially expressed, with 2 genes in common. Nevertheless, 19 gene sets were enriched and 6 depleted in the ICM of ON, whereas 2 gene sets were enriched and 8 depleted in the TE of ON compared with OM. Gene sets involved in ribosomal activity and structure, proteasome, integral component of plasma membrane, and immune response were enriched in ICM from ON embryos, and gene sets linked to sphingolipid metabolism, nucleosome, and constituents of the extracellular matrix (ECM) were depleted. In TE from ON mares, enriched gene sets were involved with ribosomes and depleted gene sets were linked to extracellular matrix, focal adhesion, myosin complex, and sequence-specific DNA binding. Overall, 1 enriched (linked to extracellular matrix) and 1 depleted gene set (involved in ribosomal structure) were common to ICM and TE. Thus, embryos from aged nulliparous mares seem to have higher protein turnover and higher immune response compared with those of OM, whereas the depletion of gene sets associated with extracellular matrix and membrane may indicate differences in cellular organisation into lineages. More work is ongoing to study effects on subsequent development.


2018 ◽  
Vol 21 (2) ◽  
pp. 74-83
Author(s):  
Tzu-Hung Hsiao ◽  
Yu-Chiao Chiu ◽  
Yu-Heng Chen ◽  
Yu-Ching Hsu ◽  
Hung-I Harry Chen ◽  
...  

Aim and Objective: The number of anticancer drugs available currently is limited, and some of them have low treatment response rates. Moreover, developing a new drug for cancer therapy is labor intensive and sometimes cost prohibitive. Therefore, “repositioning” of known cancer treatment compounds can speed up the development time and potentially increase the response rate of cancer therapy. This study proposes a systems biology method for identifying new compound candidates for cancer treatment in two separate procedures. Materials and Methods: First, a “gene set–compound” network was constructed by conducting gene set enrichment analysis on the expression profile of responses to a compound. Second, survival analyses were applied to gene expression profiles derived from four breast cancer patient cohorts to identify gene sets that are associated with cancer survival. A “cancer–functional gene set– compound” network was constructed, and candidate anticancer compounds were identified. Through the use of breast cancer as an example, 162 breast cancer survival-associated gene sets and 172 putative compounds were obtained. Results: We demonstrated how to utilize the clinical relevance of previous studies through gene sets and then connect it to candidate compounds by using gene expression data from the Connectivity Map. Specifically, we chose a gene set derived from a stem cell study to demonstrate its association with breast cancer prognosis and discussed six new compounds that can increase the expression of the gene set after the treatment. Conclusion: Our method can effectively identify compounds with a potential to be “repositioned” for cancer treatment according to their active mechanisms and their association with patients’ survival time.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 4095-4095
Author(s):  
Edwin Chen ◽  
Lawrence J Breyfogle ◽  
Rebekka K. Schneider ◽  
Luke Poveromo ◽  
Ross L. Levine ◽  
...  

Abstract TET2 mutations are early somatic events in the pathogenesis of acute myeloid leukemia (AML), myelodysplastic syndrome (MDS) and myeloproliferative neoplasms (MPN) and are one of the most common genetic lesions found in these diseases. In MPN, TET2 mutations are enriched within more advanced disease phenotypes such as myelofibrosis and leukemic transformation and often co-occur with the JAK2V617F mutation, which is present in the majority of MPN patients. We have developed and characterized a Jak2V617F conditional knockin mouse (Jak2VF/+), the phenotype of which closely recapitulates the features of human MPN. To determine the impact of Tet2 loss on Jak2V617F-mediated MPN, we crossed Tet2 conditional knockout mice with Jak2VF/+ knockin and Vav-Cre transgenic mice and backcrossed the compound mutant animals. We then characterized the effects of heterozygous and homozygous loss of Tet2 on the phenotype of Jak2VF/+ mice. We assessed peripheral blood counts, histopathology, hematopoietic differentiation using flow cytometry, colony formation and re-plating capacity. We also evaluated the effects of Tet2 loss on the transcriptome of the HSC compartment using gene expression microarrays and on HSC function using competitive bone marrow transplantation assays. Similar to Jak2VF/+/VavCre+ mice, Tet2+/-/Jak2VF/+/VavCre+ and Tet2-/-/Jak2VF/+/VavCre+ mice develop leukocytosis, elevated hematocrits (HCT) and thrombocytosis. Tet2-/-/Jak2VF/+/VavCre+ mice demonstrate enhanced leukocytosis and splenomegaly compared to the other groups. All groups demonstrate myeloid expansion, erythroid hyperplasia and megakaryocytic abnormalities consistent with MPN in the bone marrow and spleen, while more prominent myeloid expansion and megakaryocytic morphological abnormalities are observed in Tet2-/-/Jak2VF/+/VavCre+ mice as compared to the other groups. Notably, we do not see the development of acute myelogenous leukemia (AML) in Tet2-/-/Jak2VF/+/VavCre+ mice at 6 months. We see enhanced expansion of lineagelowSca1+cKithigh (LSK) cells (enriched for HSC) most prominently in the spleens of Tet2+/-/Jak2VF/+/VavCre+ and Tet2-/-/Jak2VF/+/VavCre+ mice as compared to Jak2VF/+/VavCre+ mice. In colony forming assays, we find that Tet2-/-/Jak2VF/+/VavCre+ LSK cells have enhanced re-plating activity compared to Jak2VF/+/VavCre+ LSK cells and that Tet2-/-/Jak2VF/+/VavCre+ LSK cells form more colonies that Tet2-/-/Jak2+/+/VavCre+ cells. Gene expression analysis demonstrates enrichment of a HSC self-renewal signature inTet2-/-/Jak2VF/+/VavCre+ LSK cells. Concordant with this, we find that Tet2-/-/Jak2VF/+/VavCre+ LSK cells have enhanced competitive repopulation at 16 weeks as compared to Jak2VF/+/VavCre+ and Tet2+/-/Jak2VF/+/VavCre+ LSK cells. In aggregate these findings demonstrate that Tet2 loss promotes disease progression in MPN but is insufficient to drive full leukemic transformation. Disclosures: No relevant conflicts of interest to declare.


2020 ◽  
Author(s):  
Xiaomei Lei ◽  
Zhijun Feng ◽  
Xiaojun Wang ◽  
Xiaodong He

Abstract Background. Exploring alterations in the host transcriptome following SARS-CoV-2 infection is not only highly warranted to help us understand molecular mechanisms of the disease, but also provide new prospective for screening effective antiviral drugs, finding new therapeutic targets, and evaluating the risk of systemic inflammatory response syndrome (SIRS) early.Methods. We downloaded three gene expression matrix files from the Gene Expression Omnibus (GEO) database, and extracted the gene expression data of the SARS-CoV-2 infection and non-infection in human samples and different cell line samples, and then performed gene set enrichment analysis (GSEA), respectively. Thereafter, we integrated the results of GSEA and obtained co-enriched gene sets and co-core genes in three various microarray data. Finally, we also constructed a protein-protein interaction (PPI) network and molecular modules for co-core genes and performed Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis for the genes from modules to clarify their possible biological processes and underlying signaling pathway. Results. A total of 11 co-enriched gene sets were identified from the three various microarray data. Among them, 10 gene sets were activated, and involved in immune response and inflammatory reaction. 1 gene set was suppressed, and participated in cell cycle. The analysis of molecular modules showed that 2 modules might play a vital role in the pathogenic process of SARS-CoV-2 infection. The KEGG enrichment analysis showed that genes from module one enriched in signaling pathways related to inflammation, but genes from module two enriched in signaling of cell cycle and DNA replication. Particularly, necroptosis signaling, a newly identified type of programmed cell death that differed from apoptosis, was also determined in our findings. Additionally, for patients with SARS-CoV-2 infection, genes from module one showed a relatively high-level expression while genes from module two showed low-level. Conclusions. We identified two molecular modules were used to assess severity and predict the prognosis of the patients with SARS-CoV-2 infection. In addition, these results provide a unique opportunity to explore more molecular pathways as new potential targets on therapy in COVID 19.


2021 ◽  
Author(s):  
Yannian Luo ◽  
Juan Xu ◽  
Mingzhen Zhou ◽  
Xiaomei Lei ◽  
Wen Cao ◽  
...  

Abstract Background. Exploring alterations in the host transcriptome following SARS-CoV-2 infection is not only highly warranted to help us understand molecular mechanisms of the disease, but also provide new prospective for screening effective antiviral drugs, finding new therapeutic targets, and evaluating the risk of systemic inflammatory response syndrome (SIRS) early.Methods. We downloaded three gene expression matrix files from the Gene Expression Omnibus (GEO) database, and extracted the gene expression data of the SARS-CoV-2 infection and non-infection in human samples and different cell line samples, and then performed gene set enrichment analysis (GSEA), respectively. Thereafter, we integrated the results of GSEA and obtained co-enriched gene sets and co-core genes in three various microarray data. Finally, we also constructed a protein-protein interaction (PPI) network and molecular modules for co-core genes and performed Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis for the genes from modules to clarify their possible biological processes and underlying signaling pathway. Results. A total of 11 co-enriched gene sets were identified from the three various microarray data. Among them, 10 gene sets were activated, and involved in immune response and inflammatory reaction. 1 gene set was suppressed, and participated in cell cycle. The analysis of molecular modules showed that 2 modules might play a vital role in the pathogenic process of SARS-CoV-2 infection. The KEGG enrichment analysis showed that genes from module one enriched in signaling pathways related to inflammation, but genes from module two enriched in signaling of cell cycle and DNA replication. Particularly, necroptosis signaling, a newly identified type of programmed cell death that differed from apoptosis, was also determined in our findings. Additionally, for patients with SARS-CoV-2 infection, genes from module one showed a relatively high-level expression while genes from module two showed low-level. Conclusions. We identified two molecular modules were used to assess severity and predict the prognosis of the patients with SARS-CoV-2 infection. In addition, these results provide a unique opportunity to explore more molecular pathways as new potential targets on therapy in COVID 19.


Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 4300-4300
Author(s):  
Johann-Christoph Jann ◽  
Maximilian Mossner ◽  
Florian Nolte ◽  
Tobias Boch ◽  
Verena Nowak ◽  
...  

Abstract Introduction: Myelodysplastic Syndrome (MDS) can occur in young people but it is mainly a disease of the elderly with a dramatic increase of incidence in the decades above 60 years. Accordingly, the factor age may be an important gateway to the understanding of the molecular pathogenesis of MDS. Insights into the molecular changes of aging hematopoiesis in healthy organisms have found molecular changes, which often parallel the observations in MDS such as increase of clonality with age, change of epigenetic profiles, skewed lineage commitment toward the myeloid compartment and reduced regenerative capacity after stress. The development of MDS is often suggestive of an accelerated extrapolation of molecular changes, which also occur in normal aging hematopoiesis. Beyond this, increasing evidence is suggesting that MDS hematopoiesis is highly dependent on support of the bone marrow (BM) stroma, which has been shown to display aberrant transcriptomic profiles as compared to healthy BM stroma. To this end, we aimed to test the hypothesis whether the emergence of MDS may be associated with a continuity of molecular changes in BM stroma cells during aging. Therefore, we performed explorative RNA sequencing in a set of MSCs collected from healthy young, healthy old and patients with MDS with a highly standardized pre-analytical work-up algorithm. Methods: We collected BM samples from voluntary healthy young adults (age = 24 - 25 years, female n=3, male n=3), healthy old adults (age 66 - 79 years, female n=3, male n=3) and patients with very low - intermediate risk MDS (age 51 - 87 years, female n=3, male n=3). After isolation of BM mononuclear cells by Ficoll gradient centrifugation, 5x106 mononuclear BM cells were seeded into 25cm² flasks and cultured using StemMACS human MSC Expansion Media (Miltenyi Biotec) with weekly media exchange to select for MSCs. These were expanded and harvested in passage 2. Absence of residual hematopoietic cells was controlled by FACS with anti CD45, CD31, and CD146. Whole transcriptome RNA-sequencing on all samples was carried out from 150ng of high quality RNA using the TruSeq stranded total RNA protocol and 100bp paired end sequencing (Illumina). The bio-informatical pipeline consisted of mapping using hisat2 and cufflinks for calculation of differentially expressed genes. Results: RNA-sequencing generated a mean of 94 million reads per sample. Between the groups "healthy young" and "healthy old" 331 differentially regulated genes were identified. Between "healthy old" and "MDS" 514 genes were differentially regulated (fold change > 1.5, false discovery rate, FDR < 0.05). Among these, 197 genes were differently expressed between all three groups. With these parameters, a total of 17 genes showed a continuous and significant increase of expression from healthy young over healthy old toward MDS. Among these were Kit ligand (KITLG) but also a cluster of membrane based cell adhesion molecules such as Cadherin-6 (CDH6), Laminin Subunit Alpha 2 (LAMA2) and Laminin Subunit Gamma 2 (LAMC2) and others. Conversely, 5 genes showed a continuous and significant decrease of expression from healthy young over healthy old toward MDS, among these Leukocyte-specific protein 1 (LSP1), a gene implicated in regulation of T-cell migration. Gene set enrichment analysis revealed that MDS MSCs exhibited a significant depletion of genes involved in early adipogenic differentiation and enrichment of gene sets associated with extracellular matrix remodeling (FDR < 0.05, normalized enrichment score > 1.7). Although cells were cultured under normoxic conditions, MDS-MSCs displayed marked intrinsic feature of hypoxia. Conclusion: By integrating transcriptomic data from BM stroma cells from healthy individuals during aging and comparison to BM stroma cells from MDS patients we have identified gene sets that are significantly differentially expressed per continuitatem. On the background of the hypothesis that molecular changes in the microenvironment of MDS are an exacerbation of changes also taking place during normal aging in the bone marrow, these genes, which are accumulated in the context of extracellular matrix and cell adhesion are promising candidates to further elucidate a BM stroma based pathogenesis of MDS. Disclosures No relevant conflicts of interest to declare.


Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 1274-1274
Author(s):  
Elisabeth F Heuston ◽  
Bethan Psaila ◽  
Stacie M Anderson ◽  
NISC Comparative Sequencing Program ◽  
David M. Bodine

Abstract The hierarchical model of hematopoiesis posits that hematopoietic stem cells (HSC) give rise to myeloid progenitors (CMP), that can become further restricted to bipotential granulocyte/monocyte progenitors (GMP) or megakaryocyte/erythroid progenitors (MEP). We and others have shown that this model may not accurately depict hematopoiesis. Recent studies have shown that shown that populations of mouse hematopoietic stem and progenitor cells (LSK) have a strong megakaryocyte (Mk) transcriptional profile (Heuston, 2018, Epig. & Chrom.), and single cell studies have identified lineage committed cells in progenitor populations thought to be multipotent. For example, we recently reported that human MEP contain 3 populations: erythroid (Ery) primed, Mk primed, and bipotential (Psaila, 2016; Gen. Bio.). To determine when Mk and Ery cells emerge during mouse hematopoiesis, we performed single cell RNASeq on 10000 LSK, 12000 CMP, 6000 MEP and 8000 GMP cells. Clustering analysis (Satija, 2018, Nat. Biotech.) of all 4 populations identified 33 transcriptionally distinct clusters. In 30 of 33 clusters, 85% of cells were from a single defined population (e.g. MEP). LSK and CMP clusters grouped closely together. We used gene set profiling (Gene Set Enrichment Analysis, GO and KEGG) to correlate transcriptional profiles of clusters with specific hematopoietic lineages and cellular activities. In LSK, the most common transcriptional profiles correlated with active cell cycling. Mk-associated genes (Meis1, Myct1, and Fli1), were co-expressed with lymphoid genes in 56% of all LSK. Consistent with previous studies, we conclude that cells with Mk transcriptional profiles are abundant in LSK. No cells with an Ery RNA signature were observed in LSK. 23% of all CMP cells expressed Mk genes (e.g., Pf4, Itga2b, and Fli1) and were enriched for processes involved in platelet biology (p < 3E-18). 12% of CMP had an Ery RNA signature (low expression of Gata1, Klf1, and Nfe2) and decreased Mk gene expression (e.g., Gata2 and Gfi1b, [p < 3E-18]) compared to other CMP clusters. The high ratio of Gata2/Gata1 expression (1.90) suggests that this cluster contained immature Ery cells. More than 94% of all mouse MEP had Ery RNA signatures. Clusters could be distinguished by gene expression (e.g., Gata1, Klf1, Tfrc) and biological processes (ribosome synthesis and heme-biology processes [p < 4 E-10]). Based on the transcriptional profiles, we determined the most mature erythroid cells in MEP were late BFU-E. To compare the differentiation of Mk and Ery cells, we pooled our LSK, CMP, and MEP data for analysis using the Monocle software package. GMP contained only clusters expressing granulocytic or monocytic genes and were excluded from the analysis. Monocle arranges cells into trajectories based on their transcriptional profiles, with more differentiated cells positioned further from a common node (Xiaojie, 2017, bioRxiv). We found that LSK cells near the node had overlapping lymphoid and Mk transcriptional profiles. Closest to the node, we found 38% of CMP expressed a profile similar to LSK. An additional 45% of CMP formed one trajectory with lymphoid and granulocyte RNA signatures. Another 17% of CMP formed a second trajectory, with cells expressing an Mk signature closest to the node, cells with a mixed Ery/Mk signature further along the trajectory, and MEP cells with Ery-only signatures furthest from the node. To clarify the Mk/Ery divergence, we focused our analysis on the CMP populations expressing Mk RNAs (Figure1). We observed cells in G1/S phase with an immature Mk signature to the left of the node where the trajectories diverge. On the right, cells with immature Mk signatures were nearest the node and cells with a mixed Ery/Mk signature were at the end of the trajectory (upper right; Mk/Ery). Along the second trajectory, rapidly cycling G2/M Mk cells with an early endomitosis-associated RNA signature (e.g., Pf4, Gp1bb, Gp9, and Vwf) were located at the end of the trajectory (lower right; Mk early endomitosis). Our data are consistent with a model in which two waves of Mk differentiation begin in LSK and progresses to CMP. The Mk lineage is divided in CMP, producing cells that begin endomitosis and cells that have an Mk-repressing/Ery-activating cell program that gives rise to the Ery lineage. We conclude that the erythroid lineage is derived from an Mk-like precursor and is the last lineage to be specified in mouse hematopoiesis. Disclosures No relevant conflicts of interest to declare.


Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 2497-2497
Author(s):  
Michael Trus ◽  
Ying Lin ◽  
Gurmit Singh ◽  
Mark D. Minden

Abstract Abstract 2497 Background. High cure rates seen in acute promyelocytic leukemia (APL) result from adding the retinoid all trans retinoic acid (ATRA) to chemotherapy. The addition of ATRA to chemotherapy has not consistently improved survival for other acute myelogenous leukemia (AML) subtypes. This likely reflects differences in the degree ATRA overcomes transcriptional repression imposed by the epigenetic mechanisms of histone acetylation and DNA methylation between AML and APL. Purpose To determine if differences in induction of retinoic acid receptor (RAR) β2 accounts for variations in ATRA-responses between APL and AML cells and to determine the effects epigenetic modifying agents have on the expression of RARβ2 and related gene sets in AML cells. Methods Primary AML samples, NB-4 (APL), and OCI/AML-2 (AML) cell lines were cultured in standard conditions. Treatments included ATRA 1μM, valproic acid (VPA) 0.6 mM, and 5-aza-2`-deoxycytidine (5-aza-2CDR) 400 ng/mL. Gene expression was measured by real-time PCR. Histone-acetylation was measured by chromatin immunoprecipitation (ChIP) and DNA methylation by EpiTYPER. Gene expression profiles were analyzed with Affymetrix U133A arrays followed by Gene Set Enrichment Analysis (GSEA) to identify RARβ2 related gene sets. Results Treatment of APL (NB-4 and primary samples) with ATRA induced expression of RARβ2 and expression remained attenuated in similarly treated AML (OCI/AML-2 and primary samples) cells. Histone deacetylase inhibitors (HDACi) and DNA methyltransferase inhibitors (DNMTi) can potentially reverse epigenetic-mediated transcriptional repression. Treatment of OCI/AML-2 cells with the HDACi VPA and/or the DNMTi 5-aza-2CDR and treatment of primary AML samples with VPA restored ATRA-inducible RARβ2 expression. In accordance, DNA methylation and predominantly deacetylated histones were seen at the OCI/AML-2 RARβ promoter. Treatment of OCI/AML-2 cells with ATRA and VPA (HDACi) in the absence of 5-aza-2CDR (DNMTi) had little effect on DNA methylation at the RARβ promoter, however, 5-aza-2CDR treatments markedly decreased DNA methylation. An unexpected finding was VPA further reduced DNA methylation when added to 5-aza-2CDR treatment. Histone acetylation increased minimally at the RARβ promoter in ATRA-treated OCI/AML-2 cells. However, combining ATRA with VPA (HDACi) and/or 5-aza-2CDR (DNMTi) markedly increased histone acetylation that correlated with gene-induction. The greatest change in histone acetylation and DNA methylation was seen in OCI/AML-2 cells treated with the combination of ATRA + VPA + 5-aza-2CDR that correlated with the largest induction of RARβ2. Heterogeneous levels of DNA methylation were seen at the RARβ promoter in 26 primary AML samples compared to 4 normal bone marrow (NBM) samples. Levels of DNA methylation were similar to NBM in 13 AML samples (50%), decreased in 5 (19%), both increased and decreased in the same sample in 2 (8%), and increased in 6 (23%) primary AML samples. Next, we used Affymetrix gene arrays and GSEA to delineate differences in ATRA-mediated gene regulation between NB-4 (APL) and OCI/AML-2 (AML) cells and to determine whether treatment with VPA (HDACi) and 5-aza-2CDR (DNMTi) restored expression of gene sets that included RARβ2 signaling. ATRA-treatment induced twelve such gene sets in NB-4 cells and six gene sets in OCI/AML-2 cells. Treatment of OCI/AML-2 cells with VPA alone did not induce expression of RARβ2 associated gene sets, whereas treatment of OCI/AML-2 cells with 5-AZA-2CDR modulated expression of a further five gene sets that were modulated in ATRA-treated NB-4 (APL) cells. Treatment of OCI/AML-2 cells with all three agents ATRA + VPA + 5-aza-2CDR was the only treatment combination that modulated the ligand_dependent_nuclear_receptor_activity gene set. This gene set includes many genes regulating retinoid signaling and are engaged as early as 3 hours after ATRA treatment in NB-4 cells. Conclusions RARβ2 is a frequent target for transcriptional repression by epigenetic mechanisms in AML cells. Combinations of HDACi and DNMTi increase ATRA-mediated induction of RARβ2 and epigenetic modifications that favor transcription over individual treatments. This includes a possible demethylating effect of the HDACi VPA. These treatment combinations also restore modulation of a number of RARβ2 related gene sets in AML cells that are similarly regulated in ATRA-treated APL cells. Disclosures: No relevant conflicts of interest to declare.


2018 ◽  
Vol 2018 ◽  
pp. 1-5 ◽  
Author(s):  
Li Liu ◽  
Qianrui Fan ◽  
Feng Zhang ◽  
Xiong Guo ◽  
Xiao Liang ◽  
...  

To identify novel susceptibility genes and gene sets for obesity, we conducted a genomewide expression association analysis of obesity via integrating genomewide association study (GWAS) and expression quantitative trait loci (eQTLs) data. GWAS summary data of body mass index (BMI) and waist-to-hip ratio (WHR) was driven from a published study, totally involving 339,224 individuals. The eQTLs dataset (containing 927,753 eQTLs) was obtained from eQTLs meta-analysis of 5,311 subjects. Integrative analysis of GWAS and eQTLs data was conducted by SMR software. The SMR single gene analysis results were further subjected to gene set enrichment analysis (GSEA) for identifying obesity associated gene sets. A total of 13,311 annotated gene sets were analyzed in this study. SMR single gene analysis identified 20 BMI associated genes (TUFM, SPI1, APOB48R, etc.). Also 3 WHR associated genes were detected (CPEB4, WARS2, and L3MBTL3). The significant association between Chr16p11 and BMI was observed by GSEA (FDR adjusted p value = 0.040). The TGCTGCT, MIR-15A, MIR-16, MIR-15B, MIR-195, MIR-424, and MIR-497 (FDR adjusted p value = 0.049) gene set appeared to be linked with WHR. Our results provide novel clues for the genetic mechanism studies of obesity. This study also illustrated the good performance of SMR for susceptibility gene mapping.


2020 ◽  
Author(s):  
Menglan Cai ◽  
Canh Hao Nguyen ◽  
Hiroshi Mamitsuka ◽  
Limin Li

AbstractGene set enrichment analysis (GSEA) has been widely used to identify gene sets with statistically significant difference between cases and controls against a large gene set. GSEA needs both phenotype labels and expression of genes. However, gene expression are assessed more often for model organisms than minor species. More importantly, gene expression could not be measured under specific conditions for human, due to high healthy risk of direct experiments, such as non-approved treatment or gene knockout, and then often substituted by mouse. Thus predicting enrichment significance (on a phenotype) of a given gene set of a species (target, say human), by using gene expression measured under the same phenotype of the other species (source, say mouse) is a vital and challenging problem, which we call CROSS-species Gene Set Enrichment Problem (XGSEP). For XGSEP, we propose XGSEA (Cross-species Gene Set Enrichment Analysis), with three steps of: 1) running GSEA for a source species to obtain enrichment scores and p-values of source gene sets; 2) representing the relation between source and target gene sets by domain adaptation; and 3) using regression to predict p-values of target gene sets, based on the representation in 2). We extensively validated XGSEA by using four real data sets under various settings, proving that XGSEA significantly outperformed three baseline methods. A case study of identifying important human pathways for T cell dysfunction and reprogramming from mouse ATAC-Seq data further confirmed the reliability of XGSEA. Source code is available through https://github.com/LiminLi-xjtu/XGSEAAuthor summaryGene set enrichment analysis (GSEA) is a powerful tool in the gene sets differential analysis given a ranked gene list. GSEA requires complete data, gene expression with phenotype labels. However, gene expression could not be measured under specific conditions for human, due to high risk of direct experiments, such as non-approved treatment or gene knockout, and then often substituted by mouse. Thus no availability of gene expression leads to more challenging problem, CROSS-species Gene Set Enrichment Problem (XGSEP), in which enrichment significance (on a phenotype) of a given gene set of a species (target, say human) is predicted by using gene expression measured under the same phenotype of the other species (source, say mouse). In this work, we propose XGSEA (Cross-species Gene Set Enrichment Analysis) for XGSEP, with three steps of: 1) GSEA; 2) domain adaptation; and 3) regression. The results of four real data sets and a case study indicate that XGSEA significantly outperformed three baseline methods and confirmed the reliability of XGSEA.


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