Transcriptome analysis of neutrophils after endurance exercise reveals novel signaling mechanisms in the immune response to physiological stress

2013 ◽  
Vol 114 (12) ◽  
pp. 1677-1688 ◽  
Author(s):  
Oliver Neubauer ◽  
Surendran Sabapathy ◽  
Ross Lazarus ◽  
Jeremy B. M. Jowett ◽  
Ben Desbrow ◽  
...  
Keyword(s):  
Gene Expression ◽  
Endurance Exercise ◽  
Calcium Binding ◽  
Physiological Stress ◽  
Gene Set Enrichment Analysis ◽  
P Value ◽  
Molecular Signatures ◽  
Proinflammatory Response ◽  
Blood Concentrations ◽  
Signaling Mechanisms

Neutrophils serve as an intriguing model for the study of innate immune cellular activity induced by physiological stress. We measured changes in the transcriptome of circulating neutrophils following an experimental exercise trial (EXTRI) consisting of 1 h of intense cycling immediately followed by 1 h of intense running. Blood samples were taken at baseline, 3 h, 48 h, and 96 h post-EXTRI from eight healthy, endurance-trained, male subjects. RNA was extracted from isolated neutrophils. Differential gene expression was evaluated using Illumina microarrays and validated with quantitative PCR. Gene set enrichment analysis identified enriched molecular signatures chosen from the Molecular Signatures Database. Blood concentrations of muscle damage indexes, neutrophils, interleukin (IL)-6 and IL-10 were increased ( P < 0.05) 3 h post-EXTRI. Upregulated groups of functionally related genes 3 h post-EXTRI included gene sets associated with the recognition of tissue damage, the IL-1 receptor, and Toll-like receptor (TLR) pathways (familywise error rate, P value < 0.05). The core enrichment for these pathways included TLRs, low-affinity immunoglobulin receptors, S100 calcium binding protein A12, and negative regulators of innate immunity, e.g., IL-1 receptor antagonist, and IL-1 receptor associated kinase-3. Plasma myoglobin changes correlated with neutrophil TLR4 gene expression ( r = 0.74; P < 0.05). Neutrophils had returned to their nonactivated state 48 h post-EXTRI, indicating that their initial proinflammatory response was transient and rapidly counterregulated. This study provides novel insight into the signaling mechanisms underlying the neutrophil responses to endurance exercise, suggesting that their transcriptional activity was particularly induced by damage-associated molecule patterns, hypothetically originating from the leakage of muscle components into the circulation.

Time course-dependent changes in the transcriptome of human skeletal muscle during recovery from endurance exercise: from inflammation to adaptive remodeling

2014 ◽  
Vol 116 (3) ◽  
pp. 274-287 ◽  
Author(s):  
Oliver Neubauer ◽  
Surendran Sabapathy ◽  
Kevin J. Ashton ◽  
Ben Desbrow ◽  
Jonathan M. Peake ◽  
...  
Keyword(s):  
Gene Expression ◽  
Skeletal Muscle ◽  
Endurance Exercise ◽  
Time Course ◽  
Acute Stress ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Matrix Remodeling ◽  
Molecular Signatures ◽  
Gene Sets

Reprogramming of gene expression is fundamental for skeletal muscle adaptations in response to endurance exercise. This study investigated the time course-dependent changes in the muscular transcriptome after an endurance exercise trial consisting of 1 h of intense cycling immediately followed by 1 h of intense running. Skeletal muscle samples were taken at baseline, 3 h, 48 h, and 96 h postexercise from eight healthy, endurance-trained men. RNA was extracted from muscle. Differential gene expression was evaluated using Illumina microarrays and validated with qPCR. Gene set enrichment analysis identified enriched molecular signatures chosen from the Molecular Signatures Database. Three hours postexercise, 102 gene sets were upregulated [family wise error rate (FWER), P < 0.05], including groups of genes related with leukocyte migration, immune and chaperone activation, and cyclic AMP responsive element binding protein (CREB) 1 signaling. Forty-eight hours postexercise, among 19 enriched gene sets (FWER, P < 0.05), two gene sets related to actin cytoskeleton remodeling were upregulated. Ninety-six hours postexercise, 83 gene sets were enriched (FWER, P < 0.05), 80 of which were upregulated, including gene groups related to chemokine signaling, cell stress management, and extracellular matrix remodeling. These data provide comprehensive insights into the molecular pathways involved in acute stress, recovery, and adaptive muscular responses to endurance exercise. The novel 96 h postexercise transcriptome indicates substantial transcriptional activity potentially associated with the prolonged presence of leukocytes in the muscles. This suggests that muscular recovery, from a transcriptional perspective, is incomplete 96 h after endurance exercise involving muscle damage.

Gene Expression Profiles Document That Recently- and Previously-Divided CLL Fractions Represent a Continuum but Suggest Differing Modes of Activation for These Fractions in U-CLL and M-CLL

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 317-317
Author(s):  
Xiao J. Yan ◽  
Wentian Li ◽  
Sophia Yancopoulos ◽  
Igor Dozmorov ◽  
Carlo Calissano ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Death ◽  
Cell Signaling ◽  
Lymphoid Tissue ◽  
Research Funding ◽  
Expression Profiles ◽  
Lymphocytic Leukemia ◽  
Gene Set Enrichment Analysis ◽  
P Value ◽  
Gene Sets

Abstract Abstract 317 By using reciprocal densities of surface membrane CXCR4 and CD5, chronic lymphocytic leukemia (CLL) B cells can be divided into 3 fractions indicating time since last division (proliferative, intermediate, and resting). It has been suggested that cells in these fractions represent a continuum from resting to intermediate to proliferative. In this study, we made intraclonal gene expression profile (GEP) comparisons of these fractions from 17 CLL patients to try to confirm this notion and interclonal comparisons between U-CLL and M-CLL patients to determine if pathways involved in the actions of these fractions differed between patient subgroups. PBMCs from 8 U-CLL and 9 M-CLL patients were sorted into 3 fractions (CD19+CD3−CD5hiCXCR4lo, PROLIF), (CD19+CD3−CD5intCXCR4int, INTERM), and (CD19+CD3−CD5loCXCR4hi, REST); RNA was purified from each, and gene expression microarrays using Illumina HumanHT12 beadchips performed. To determine differentially expressed genes in intraclonal comparisons, expression value ratios for fractions from each patient were computed, log-transformed, and Student t-test performed using R (www.r-project.org); for interclonal comparisons, raw GEP data between subpopulations were compared: U-PROLIF and M-PROLIF, and U-REST and M-REST. Sets of significant genes (≥1.5 fold change and P<0.01) were analyzed using Ingenuity Pathway Analysis (IPA) and Gene Set Enrichment Analysis (GSEA). Upon plotting intraclonal average log ratios of PROLIF/INTERM vs INTERM/REST, it was clear that gene expression levels changed in the same direction, i.e. PROLIF>INTERM>REST, or PROLIF<INTERM<REST, consistent with a continuum between the 3 fractions. Within this pattern, 36 genes were significant for both plotted ratios. Of these, 29 were overexpressed, along with CD5; CD68, ITGAX, CCND2, CRIP1 and LGALS1 were the highest. Functional analysis using IPA showed these genes to be related to NFkB signaling and cell trafficking. Seven genes (ADARB1, BACH2, CNTNAP2, HRK, RHPN2, PRPML, and RXPA) were significantly downregulated, along with CXCR4. Next we characterized GEP differences between the PROLIF and REST fractions, identifying 390 genes up-regulated in PROLIF and 244 in REST. The top 5 upregulated PROLIF genes were CD68, LY96, ITGAX, CCND2 and CRIP1, and the top 5 REST genes were BACH2, CXCR4, ADARB1, RHPN2 and HRK. Functionally, the upregulated PROLIF genes were related to BCR signaling, cytokines (IFNa, IL12), NFkB, and Akt, whereas the upregulated REST genes related to BCL2, cell death and cell movement. By GSEA, 813/881 gene sets, defined by expression neighborhoods centered on cancer associated genes, were upregulated in the PROLIF with 436 gene sets significant at a false discovery rate (FDR) <10%; 206 sets were significantly enriched with p value <0.01. For the REST, 68/881 gene sets were upregulated, with none significant even at FDR <25%. Finally, we examined PROLIF and REST fractions from U-CLL vs M-CLL patients. In this interclonal analysis, 93 genes were significantly different between U-PROLIF and M-PROLIF. The top 5 in U-PROLIF were MSI2, TGFBR3, TP53I3, RGCC and IGSF3, and the top 5 in M-PROLIF were MTSS1, BACE2, BRI3BP, AP3B1 and UBE2G2. Similarly, there were 125 genes that were significantly different between U-REST and M-REST. The top 5 in U-REST were DUSP26, CLEC2B, MDK, and EGR2 and in M-REST were NAPSA, RAB24, TARDBP, KCNN4 and ADD3. Interestingly, U-PROLIF and M-PROLIF differed in pathway assignments, with upregulated genes in U-PROLIF contributing to cell signaling and activation, particularly implicating Akt, ERK and P38MAPK. The intraclonal gene GEP analysis on these 3 fractions confirms that CLL clones contain a spectrum of cells that transition in a sequential manner from PROLIF to INTERM to REST fractions. Functional analyses show that genes upregulated in PROLIF correlate with cell signaling and proliferation, while genes upregulated in REST relate to cell death. Thus the PROLIF fraction is enriched in recently divided cells that likely exit from lymphoid tissue and the REST in older, less vital cells that either traffic to lymphoid tissue or die. The interclonal analysis implies that the stimuli and/or the responses of cells in the PROLIF and REST fractions differ between U-CLL and M-CLL. This last novel finding suggests either distinct cells of origin or distinct activation pathways for the IGHV-defined CLL subsets. Disclosures: Barrientos: gilead and pharmacyclics research funding: Research Funding.

A 13-Glycosylation Gene Signature in Multiple Myeloma Can Predicts Survival and Identifies Candidates for Targeted Therapy (GiMM13)

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 4423-4423 ◽  
Author(s):  
Caoilfhionn Connolly ◽  
Alokkumar Jha ◽  
Alessandro Natoni ◽  
Michael E O'Dwyer
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
High Risk ◽  
Research Funding ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Rank Test ◽  
P Value ◽  
Log Rank Test ◽  
Novel Approach

Abstract Introduction Advances in genomics have highlighted the potential for individualized prognostication and therapy in multiple myeloma (MM). Previously developed gene expression signatures have identified patients with high risk (Kuiper et al, Blood 2016) however, they provide few insights into underlying disease biology thereby limiting their use in informing treatment decisions. Glycosylation is deregulated in MM (Glavey et al), and potential consequences include altered cell adhesion, signaling, immune evasion and drug resistance. In this study we have utilized RNA sequencing data from the IA7 CoMMpass cohort to characterize the expression profile of genes involved in glycosylation. This represents a novel approach to identify a distinct molecular pathway related to outcome, which is potentially actionable. Methods A pathway based approach was adopted to evaluate genes implicated in glycosylation, including the generation of selectin ligands. A literature review and KEGG pathway analysis of pathways relating to O-glycans, N-glycans, sialic acid metabolism, glycolipid synthesis and metabolism was completed. RNA Cufflinks-gene level FPKM expression of 458 patients enrolled in the IA7 cohort of the Multiple Myeloma Research Foundation (MMRF) CoMMpass trial (NCT145429) were analysed as derivation cohort. We developed expression cut-offs using a novel approach of adjusted existing linear regression model to define the gene expression cut-off by applying 3rd Quartile data (q1+q2/2-qmin). The analysis of overall survival (OS) was completed using adjusted 'kpas' R-package according to our cut-off model. Association between individual transcripts and OS was analyzed with log-rank test. Genes with p-value <0.2 were used in subsequent prioritization analysis. This cut-off methodology was employed to define the nearest neighbor for a gene for Gene Set Enrichment Analysis (GSEA). As far as 4th neighbor above and below the cut off was used to have centrally driven gene selection method for prioritization. The gene signature was validated in GSE2658 (Shaughnessy et al) dataset. Results Initial analysis yielded 184 prospective genes. 147 were significant on univariate analysis. Following further prioritization of these genes, we identified thirteen genes that had significant impact upon outcomes (GiMM13). Figure 1 reveals that GiMM13 signature has a significant correlation with inferior OS (HR 4.66 p-value 0.022). The prognostic impact of stratifying GiMM13 positive (High risk) or GiMM13 negative (Low risk) by ISS stage was evaluated. In Table 1. Kaplan Meier estimates generated for GiMM13 (High) or GiMM13 (Low) stratified by ISS are compared statistically using the log rank test. The prognostic ability of GiMM13 to synthesize distinct subgroups relative to each ISS stage is shown in Figure 2. ISS1-Low is the the lowest risk group with best prognosis. Hazard ratios relative to the ISS1-Low group were 1.8, p-value 0.029 (ISS2-Low), 2.1, p-value 0.031 (ISS3-Low), 4.3, p-value 0.04 (ISS1-HR), 5.9, p-value 0.039 (ISS2-HR) and 3.1, p-value 0.001 (ISS3-HR). The GiMM13 signature enhances the prognostic ability of ISS to identify patients with inferior or superior outcomes respectively. Conclusion While the therapeutic armamentarium for MM has expanded considerably, the significant molecular heterogeneity in the disease still poses a significant challenge. Our data suggests aberrant transcription of glycosylation genes, involved predominantly in selectin ligand synthesis, is associated with inferior survival outcomes and may help identify patients likely to benefit from treatment with agents targeting aberrant glycosylation, e.g. E-selectin inhibitor. Consistent with recent findings in chemoresistant minimal residual disease (MRD) (Paiva et al, Blood 2016), it would appear that O-glycosylation, rather than N-glycosylation is most significantly implicated in this biological processes conferring inferior outcomes. In conclusion, using a novel pathway-based approach to identify a 13-gene signature (GiMM13), we have developed a robust tool that can refine patient prognosis and inform clinical decision-making. Acknowledgment These data were generated as part of the Multiple Myeloma Research Foundation Personalized Medicine Initiatives (https://research.themmrf.org and www.themmrf.org). Disclosures O'Dwyer: Glycomimetics: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding.

Global Gene Expression Profile of Human Bone Marrow before and after Hydroxyurea Administration in Sickle Cell Anemia.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 3750-3750
Author(s):  
Flavia C. Costa ◽  
Anderson F. Cunha ◽  
Andre Fattori ◽  
Tarcisio S. Peres ◽  
Gustavo G.L. Costa ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bone Marrow ◽  
Sickle Cell ◽  
Calcium Binding ◽  
Human Bone ◽  
Differentially Expressed ◽  
Human Bone Marrow ◽  
P Value ◽  
Clinical Evolution ◽  
New Genes

Abstract The levels of HbF in sickle cell disease (SCD) can be increased by pharmacological agents such as hydroxyurea (HU), which has been shown to reduce the frequency of pain crises, hospitalizations and acute chest events requiring blood transfusions in adults with SCD. However, there is some evidence to suggest that some SCD patients show benefits from HU treatment without increase in their HbF levels. Thus, the molecular mechanism by which HU increases HbF levels and improves the clinical evolution in SCD remains unclear. This study aims to provide the global gene profile of human bone marrow of a homozygous patient three months before beginning treatment and after the initial administration of HU and to investigate groups of differentially expressed genes that could be involved in the pathways by which HU improves the clinical evolution in SCD. Using the Serial Analysis of Gene Expression (SAGE) technique, two libraries, before HU administration (HbS profile) and after HU administration (HbSHU) were performed. A total of 47.192 and 46.697 tags were analyzed for the HbS and HbSHU profiles and represented 15.735 and 15.901 distinct tags, respectively. Among these, 4.151 and 3.817 tags were no match tags that could represent new genes that remain to be identified. When both profiles were compared, 518 transcripts were determined to have statistically significant differential levels of expression (P value < 0.05). The functional annotation of transcripts, according to the Gene Ontology Consortium, showed that the categories of binding and structural molecule activity were up-regulated following HU treatment. For example, genes associated with nucleic acid binding such as Signal Transducer and Activator of Transcription 5 A, v-fos FBJ murine osteosarcoma viral oncogene homolog, Early Growth Response 1 and several ribosomal and zinc finger proteins were induced by HU treatment. Conversely, the transporter activity category was down regulated by HU treatment. Genes associated with oxygen transporter activity and other genes associated with ion binding, like S100 calcium binding protein A8 (calgranulin A) and transferrin were found to be down regulated by HU treatment. Taken together, these results strongly suggest that HU produces a significant change in the expression of bone marrow cells. Future studies of these described genes that are differentially expressed during HU treatment may contribute to further the understanding of the mechanism by which HbF acts in SCD and improves the clinical evolution of the disease. The description of new genes involved in these pathways may also represent a potential tool to identify new targets for the therapy of SCD.

scholarly journals Gene Expression and Epigenetic Analysis in Relapsed/Refractory Diffuse Large B Cell Lymphoma Provides Insights into Evolution of Treatment Resistance to R-CHOP

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 26-26
Author(s):  
Manishkumar S. Patel ◽  
Ellen K. Kendall ◽  
Sarah Ondrejka ◽  
Agrima Mian ◽  
Yazeed Sawalha ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Differentially Expressed Genes ◽  
Research Funding ◽  
B Cell Lymphoma ◽  
Cell Receptor ◽  
B Cell Receptor ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
P Value

Background Diffuse large B cell lymphoma (DLBCL) is curable in ~60-70% of patients using standard chemoimmunotherapy, but the prognosis is poor for relapsed/refractory (R/R) DLBCL. Therefore, understanding the underlying molecular mechanisms will facilitate early prediction and effective management of resistance to therapy. Recent studies of paired diagnostic-relapse biopsies from patients have relied on a single "omics" approach, examining either gene expression or epigenetic evolution. Here we present a combined analysis of gene expression and DNA methylation profiles of paired diagnostic-relapse DLBCL biopsies to identify changes responsible for relapse after R-CHOP. Methods Biopsies from 23 DLBCL patients were obtained at the time of diagnosis and relapse following frontline R-CHOP chemoimmunotherapy. The cohort had 18 (78.3%) male patients with median age of 62 (range, 35-86) years and median IPI of 2.5 (range, 1-5). The median time from diagnosis to relapse was 7 (range, 0-57) months. DNA and RNA were extracted simultaneously from formalin-fixed paraffin embedded (FFPE) biopsy samples. DNA methylation levels were measured through Illumina 850k Methylation Array for 22 pairs of diagnostic-relapse biopsies. RNA from diagnostic-relapse paired biopsies from 6 patients was sequenced using Illumina HiSeq4000. Differentially methylated probes were identified using the DMRcate package, and differentially expressed genes were identified using the DESeq2 package. Gene set enrichment analysis was performed using canonical pathway gene sets from MSigDB. Pearson's correlation with a Bonferroni correction to the p-value was used to calculate the correlation between regularized log transformed gene expression counts and methylation beta values. Results In a pairwise comparison of gene expression between diagnostic and R/R biopsy pairs, we found 14 differentially expressed genes (FDR&lt;0.1 & Log2FC&gt;|1|) consistent across all pairs. Compared to gene expression at diagnosis, five genes (CYP1B1, LGR4, ATXN1, CTSC, ZMAT3) were downregulated, and eight genes (ERBB3, CD19, CARD11, MT-RNR2, IGHG3, CCDC88C, ATP2A3, CENPE, and PCNT) were up-regulated in the R/R samples. Many of these genes have been previously implicated in oncogenesis, such as ERBB3, a member of the epidermal growth receptor family. Importantly, some of these genes have known roles in DLBCL biology, such as CD19, a member of the B-cell receptor complex, and CARD11, a gene in which several oncogenic mutations have been identified in DLBCL as a mediator of NF-KB activation. Gene set enrichment analysis revealed overexpression of immune signatures such as cytokine-cytokine receptor interaction, chemokine receptor-chemokine binding, and the IL-12-STAT4 pathway at diagnosis. At relapse, cell cycle, B-cell receptor, and NOTCH signaling pathways were overexpressed. Interestingly, in a pairwise comparison of methylation between diagnostic and R/R biopsy pairs, there were no differentially methylated probes (FDR&lt;0.05), suggesting no coordinated epigenetic evolution between diagnostic and R/R pairs. For biopsy pairs that had both gene expression and methylation data (5 pairs), we correlated gene expression and methylation values. We found that none of the differentially expressed genes between the diagnostic and R/R biopsies were significantly correlated with methylation status (adjusted p-value&lt;0.05). Conclusions By analyzing paired diagnostic and relapse DLBCL biopsies, we found that at the time of relapse, there are significant transcriptomic changes but no significant epigenetic changes when compared to diagnostic biopsies. Activation of B-cell receptor and NOTCH signaling, as well as the loss of immune signaling at relapse, cannot be attributed to coordinated epigenetic changes in methylation. As the epigenetic profile of the biopsies did not consistently evolve, these data emphasize the need for better understanding of the baseline methylation profiles at the time of diagnosis, as well as acquired somatic mutations that may contribute to the emergence of therapeutic resistance. Future studies are needed to focus on how activation of signaling pathways triggered by genomic alterations can be targeted in relapsed/refractory DLBCL. Disclosures Hsi: Seattle Genetics: Consultancy, Honoraria; Miltenyi: Consultancy, Honoraria; Abbvie: Research Funding; Eli Lilly: Research Funding; CytomX: Consultancy, Honoraria. Hill:Takeda: Research Funding; Genentech: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria, Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding; Beigene: Consultancy, Honoraria, Research Funding; AstraZenica: Consultancy, Honoraria, Research Funding; Kite, a Gilead Company: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Research Funding.

scholarly journals Integrated Genomic-Transcriptomic Study Highlights Accumulation of Genetic Variants and Activation of Inflammatory Pathways

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 4212-4212
Author(s):  
Malathi Kandarpa ◽  
Kristen Pettit ◽  
Tingting Qin ◽  
Yi-Mi Wu ◽  
Dan Robinson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Variants ◽  
Research Funding ◽  
Gene Set Enrichment Analysis ◽  
P Value ◽  
Ras Signaling ◽  
Spleen Size ◽  
Gene Set Enrichment ◽  
Ras Pathway ◽  
Gene Set

INTRODUCTION: The molecular basis of Philadelphia chromosome negative myeloproliferative neoplasms (MPNs) is unclear. So-called "driver" mutations in JAK2, CALR, or MPL are present in the vast majority of cases, but there is no compelling evidence to explain how each mutant gene can lead to phenotypically distinct and/or overlapping disease phenotypes. In an attempt to understand the molecular events that underlay clinical characteristics of MPNs, we studied gene expression profiles and sequenced hematopoietic cells of MPN patients with a focus on myelofibrosis (MF) landscape. METHODS: Patients were consented to MI-ONCOSEQ study approved by the University of Michigan IRB. Peripheral blood or bone marrow aspirates were either enriched for CD34 expressing cells or peripheral blood or bone marrow mononuclear cells (PBMC/BMMC) were analyzed. MI-ONCOSEQ is a Next Generation Sequencing platform to identify genetic aberrations in 1,711 genes and gene expression and fusion analysis of 24,774 capture targets by transcriptome sequencing. Gene expression data was analyzed between various sub-groups of MF based upon clinical (spleen size) or molecular (mutations in Ras pathway genes) characteristics. Gene set enrichment analysis was conducted for the MF cohorts (23 CD34 enriched, 76 PBMC/BMMC) and ET/PV/PrePMF cohort (12 CD34, 35 PBMC/BMMC). RESULTS: We analyzed the genetic landscape of 163 patients with MPNs: 113 with overt MF and 50 with ET (18), PV (23), or prePMF (9). In addition to driver genes, 183 other gene variants were observed. The number of gene variants was higher in older patients (median 4 and 5 variants in those aged 70-80 and >80 yrs respectively) with MF as compared to ET/PV/PrePMF where the median number of variants did not exceed 3. Mutations in ASXL1, TET2, RAS and SRSF2 increased in frequency with age (Fig 1). Gene expression profiles of sub-groups of MF were further analyzed to understand aberrantly regulated molecular pathways. Hierarchical clustering of all MF patients showed that CD34 enriched samples to be distinct from the PBMC/BMMC cohort and therefore these cohorts were analyzed separately. Moreover, hierarchical clustering suggested differences in patients with large spleens. In the comparison of MF to ET/PV/PrePMF within the CD34 population gene enrichment highlights hemopoiesis, leukemia related pathways as well as endoplasmic reticulum and Golgi transport pathways. Previously, we saw that RAS pathway mutations predicted proliferative disease with high WBC counts. Therefore, we focused on RAS pathway mutated cohorts versus RAS wild type cohorts and identified dysregulated pathways by gene set enrichment analysis (Fig 2). The RAS mutated MF cohort (PBMC/BMMC fraction) showed up-regulation of cytokines IL6 (p-value 9.39E-06), IL8 (p-value 1.16E-04), and IL1beta (p-value 5.24E-04) and down-regulation of the TNF superfamily (p-value 9.98E-04). Most notably, there was up regulation of NFkB transport to the nucleus (p-value 8.69E-05) and transcription factor activity. In general, several metabolic pathways were affected and inflammatory pathways were up-regulated. Since spleen size is an indicator of disease severity, progression and response to therapy, gene set enrichment between cohorts of patients with different spleen size (>6cm by physical exam versus <6cm) was analyzed (Fig 3). The data suggest dysregulation of megakaryocyte differentiation (p-value 2.05E-05), cytokine production (p-value 9.09E-05) and signaling, JAK-STAT pathway (p-value 5.10E-05), RAS signaling (p-value 7.67E-05) and NFkB pathway (p-value 1.31E-04) in patients with larger spleens. CONCLUSIONS: Age is a high risk for many hematological malignancies. We analyzed the number of genetic variants by age and determined that accumulation of higher number of mutations might indicate why disease progresses rapidly in older patients. Not only genetic variants, but gene expression changes also contribute to the pathogenesis of MF. Analysis of gene expression changes show enrichment of genes regulating JAK-STAT pathway activity and cytokine production as anticipated, but also implicates epigenetic regulators and the RAS signaling pathway in disease biology. Moreover, enriched pathways in gene expression analysis underscore the dysregulation of NFkB, perhaps as a result of inflammatory response. Thus these pathways are promising candidates for intervention in patients with MF. Disclosures Pettit: Samus Therapeutics: Research Funding. Talpaz:Imago BioSciences: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; CTI BioPharma: Research Funding; Constellation: Research Funding; Incyte: Research Funding; Novartis: Research Funding; Samus Therapeutics: Research Funding.

The Protective Effect of Metformin against Oxandrolone-Induced Infertility in Male Rats

2020 ◽  
Vol 26 ◽  
Author(s):  
Abdulqader Fadhil Abed ◽  
Yazun Bashir Jarrar ◽  
Hamzeh J Al-Ameer ◽  
Wajdy Al-Awaida ◽  
Su-Jun Lee
Keyword(s):  
Gene Expression ◽  
Male Infertility ◽  
Protective Effect ◽  
Histological Examination ◽  
Sperm Count ◽  
Serum Testosterone ◽  
Male Rats ◽  
P Value ◽  
Protective Effects ◽  
Rt Pcr

Background: Oxandrolone is a synthetic testosterone analogue that is widely used among bodybuilders and athletes. However, oxandrolone causes male infertility. Recently, it was found that metformin reduces the risk of infertility associated with diabetes mellitus. Aim: This study aimed to investigate the protective effects of metformin against oxandrolone-induced infertility in male rats. Methods: Rats continuously received one of four treatments (n=7) over 14 days: control DMSO administration, oxandrolone administration, metformin administration, or co-administration of oxandrolone and metformin. Doses were equivalent to those used for human treatment. Subsequently, testicular and blood samples were collected for morphological, biochemical, and histological examination. In addition, gene expression of the testosterone synthesizing enzyme CYP11A1 was analyzed in the testes using RT-PCR. Results: Oxandrolone administration induced male infertility by significantly reducing relative weights of testes by 48%, sperm count by 82%, and serum testosterone levels by 96% (ANOVA, P value < 0.05). In addition, histological examination determined that oxandrolone caused spermatogenic arrest which was associated with 2-fold downregulation of testicular CYP11A1 gene expression. However, co-administration of metformin with oxandrolone significantly ameliorated toxicological alterations induced by oxandrolone exposure (ANOVA, P value < 0.05). Conclusion: Metformin administration protected against oxandrolone-induced infertility in male rats. Further clinical studies are needed to confirm the protective effect of metformin against oxandrolone-induced infertility among athletes.

Utilizing Cancer - Functional Gene Set - Compound Networks to Identify Putative Drugs for Breast Cancer

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 ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Therapy ◽  
Cancer Treatment ◽  
Cancer Survival ◽  
Expression Profiles ◽  
Functional Gene ◽  
Gene Set Enrichment Analysis ◽  
Gene Set ◽  
Gene Sets

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.

scholarly journals Aberrant expression of USF2 in refractory rheumatoid arthritis and its regulation of proinflammatory cytokines in Th17 cells

2020 ◽  
Vol 117 (48) ◽  
pp. 30639-30648
Author(s):  
Dan Hu ◽  
Emily C. Tjon ◽  
Karin M. Andersson ◽  
Gabriela M. Molica ◽  
Minh C. Pham ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gene Expression ◽  
T Cells ◽  
Transcription Factor ◽  
Proinflammatory Cytokines ◽  
Th17 Cells ◽  
Gene Set Enrichment Analysis ◽  
Aberrant Expression ◽  
Signature Genes ◽  
The Impact

IL-17–producing Th17 cells are implicated in the pathogenesis of rheumatoid arthritis (RA) and TNF-α, a proinflammatory cytokine in the rheumatoid joint, facilitates Th17 differentiation. Anti-TNF therapy ameliorates disease in many patients with rheumatoid arthritis (RA). However, a significant proportion of patients do not respond to this therapy. The impact of anti-TNF therapy on Th17 responses in RA is not well understood. We conducted high-throughput gene expression analysis of Th17-enriched CCR6+CXCR3−CD45RA−CD4+T (CCR6+T) cells isolated from anti-TNF–treated RA patients classified as responders or nonresponders to therapy. CCR6+T cells from responders and nonresponders had distinct gene expression profiles. Proinflammatory signaling was elevated in the CCR6+T cells of nonresponders, and pathogenic Th17 signature genes were up-regulated in these cells. Gene set enrichment analysis on these signature genes identified transcription factor USF2 as their upstream regulator, which was also increased in nonresponders. Importantly, short hairpin RNA targetingUSF2in pathogenic Th17 cells led to reduced expression of proinflammatory cytokines IL-17A, IFN-γ, IL-22, and granulocyte-macrophage colony-stimulating factor (GM-CSF) as well as transcription factor T-bet. Together, our results revealed inadequate suppression of Th17 responses by anti-TNF in nonresponders, and direct targeting of the USF2-signaling pathway may be a potential therapeutic approach in the anti-TNF refractory RA.

scholarly journals Anti-Rheumatic Effect of Antisense Oligonucleotide Cytos-11 Targeting TNF-α Expression

2021 ◽  
Vol 22 (3) ◽  
pp. 1022
Author(s):  
Tatyana P. Makalish ◽  
Ilya O. Golovkin ◽  
Volodymyr V. Oberemok ◽  
Kateryna V. Laikova ◽  
Zenure Z. Temirova ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gene Expression ◽  
Rat Model ◽  
Peripheral Blood ◽  
Antisense Oligonucleotide ◽  
Joint Inflammation ◽  
Blood Concentrations ◽  
Tnf Α ◽  
Effective Drugs ◽  
First Time

The urgency of the search for inexpensive and effective drugs with localized action for the treatment of rheumatoid arthritis continues unabated. In this study, for the first time we investigated the Cytos-11 antisense oligonucleotide suppression of TNF-α gene expression in a rat model of rheumatoid arthritis induced by complete Freund’s adjuvant. Cytos-11 has been shown to effectively reduce peripheral blood concentrations of TNF-α, reduce joint inflammation, and reduce pannus development. The results achieved following treatment with the antisense oligonucleotide Cytos-11 were similar to those of adalimumab (Humira®); they also compared favorably with those results, which provides evidence of the promise of drugs based on antisense technologies in the treatment of this disease.

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