Enhanced Gene Expression of EZH2 In Patients with Primary Myelofibrosis

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 4118-4118
Author(s):  
Vibe Skov ◽  
Thomas Stauffer Larsen ◽  
Mads Thomassen ◽  
Caroline Riley ◽  
Morten Krogh Jensen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Myeloproliferative Neoplasms ◽  
Primary Myelofibrosis ◽  
Fold Change ◽  
Differentially Expressed ◽  
Altered Expression ◽  
Core Proteins ◽  
Enhancer Of Zeste

Abstract Abstract 4118 Introduction: The polycomb repressive complex (PRC) 2 contains 3 core proteins, EZH2 (enhancer of zeste homolog 2), SUZ12, and EED, in which the SET (suppressor of vaegation-enhancer of zeste-trithorax) domain of EZH2 mediates the histone methyltransferase activity. This induces trimethylation of lysine 27 on histone H3, regulates the expression of HOX genes, and promotes proliferation and aggressiveness of neoplastic cells. EZH2, a known repressor of gene transcription, has been reported to be overexpressed in many cancers and correlates with poor prognosis. EZH2 may also be involved in disease progression in patients with the classical Philadelphia-negative chronic myeloproliferative neoplasms (CMPNs) encompassing essential thrombocythemia (ET), polycythemia vera (PV), and primary myelofibrosis (PMF). Since the potential oncogenic role of EZH2 in CMPNs has never been investigated, we have assessed gene expression of EZH2 in a cohort of patients with CMPNs. Patients and Methods: Using Affymetrix HG-U133 2.0 Plus microarrays, recognizing 54675 probe sets (38500 genes), gene expression profiling has been performed on control subjects (n=21) and patients with ET (n =19), PV (n=41), and PMF (n=9). All patients were diagnosed according to the WHO criteria of a CMPN. Total RNA was purified from whole blood and amplified to biotin-labeled RNA and hybridized to microarray chips. Results: We identified 20439, 25307, 17417, and 25421 probe sets which were differentially expressed between controls and patients with ET, PV, PMF, and CPMNs as a whole, respectively (false discovery rate (FDR) adjusted p values < 0.05). These genes included EZH2, which was highly significantly upregulated in patients with PMF as compared to controls (2.3 fold upregulated; uncorrected p-value=1.09×10-8 and FDR=1.75×10-6, and between PMF and non-PMF patients (fold change=2.0, FDR < 0.0005). No significant differences in EZH2 gene expression were recorded between controls and ET patients, controls and PV patients, or controls and the CMPN group as a whole. Within patients, the EZH2 gene was also differentially expressed with the highest levels being recorded in patients with PMF compared to PV patients (fold change=2.4, FDR < 7.5 ×10-6). Discussion and Conclusions: Using global gene expression profiling we have found the EZH2 gene to be significantly upregulated in CMPN patients, with the highest expression levels being found in PMF. We hypothesize that an altered expression of EZH2 may be involved in the transformation of ET and PV into myelofibrosis. It remains to be clarified if deregulation of EZH2 occurs consequent to mutations in the EZH2-gene. Enhanced EZH2 expression may also be associated with silencing of differentiation genes during myelofibrotic and leukemic transformation. An increased expression of EZH2 may provide a proliferative advantage of the malignant clone through interaction with the pathways of key elements controlling cell growth arrest and differentiation, (e.g. nuclear factor kappa beta and - the proteasome pathway). Studies are in progress to elucidate if genomic loss of distinct microRNAs (microRNA 101 leads to overexpression of EZH2 in cancer is associated with overexpression of EZH2 in CMPNs. Highly expressed EZH2 may be a new marker of an aggressive clinical phenotype which might imply EZH2 as a novel biomarker for predicting prognosis. If so, EZH2-blockade might be a novel approach to be incorporated in the strategies for developing epigenetic therapies in patients with CMPNs. Disclosures: No relevant conflicts of interest to declare.

Comprehensive gene expression analysis of IDH1/2 mutant biliary cancers (BC).

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 4598-4598
Author(s):  
Francesca Battaglin ◽  
Joanne Xiu ◽  
Yasmine Baca ◽  
Jia Zeng ◽  
Anthony Frank Shields ◽  
...  
Keyword(s):  
Gene Expression ◽  
Inflammatory Response ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Molecular Profile ◽  
Specific Gene ◽  
Altered Expression ◽  
Idh Mutations

4598 Background: Isocitrate dehydrogenases (IDH) mutations (mut) identify a distinct subtype of BC that has yet to be fully characterized. We recently showed that IDH1/2 mutant (mIDH) BC harbor specific gene alterations involving chromatin remodeling and DNA repair, and a differential immune markers profile compared to other mIDH GI tumors. Here we aim to further dissect the molecular profile of mIDH BC through a comprehensive gene expression profiling analysis. Methods: 524 BC samples (303 intrahepatic cholangiocarcinoma, IHCC, 67 extrahepatic cholangiocarcinoma, EHCC, 141 gallbladder, 13 unspecified) collected between February to December of 2019 were included. Samples were analyzed using NextGen DNA sequencing (NextSeq, 592 gene panel), whole transcriptome RNA sequencing (NovaSeq) and immunohistochemistry (Caris Life Sciences, Phoenix, AZ). EBseq was used to identify differentially expressed genes in mIDH vs wild type (WT) tumors with control for FDR ( Q < 0.2). Pathway and functional enrichment analysis was performed using g:Profiler and Enrichr. Results: mIDH frequency in our cohort was 11.4% (60/524), with higher prevalence of IDH1 mut (8.8%). IHCC showed the highest mut prevalence: IDH1 13.5%, IDH2 4.6%. mIDH was more common in females ( P = 0.0036). A total of 774 genes were significantly differentially expressed between mIDH and WT: 582 underexpressed (Fold change, FC: 0.025~0.699); 192 overexpressed (FC: 1.43~3.3). Pathway enrichment showed a significant decrease of gene expression in cytokine-cytokine receptor interaction ( Q = 0.002) and inflammatory response genes ( Q = 0.005) in mIDH. Interferon-γ- and PD1 signaling-related genes expression was significantly lower in mIDH vs WT ( Q = 0.02) including IFNG (FC 0.32), NKG7 (FC 0.36), CD8B (FC 0.37), BATF (FC 0.40), PD1 (FC 0.53), SLAMF6 (FC 0.55) and PD-L2 (FC 0.60). Wnt and cadherin signaling were also enriched for altered expression in several genes in mIDH BC ( Q = 3.86e-7 and < 0.00001, respectively). Conclusions: To our knowledge, this is the largest and most extensive gene expression profiling study focused on mIDH BC. Our data show for the first time a distinct gene expression profile characterizing mIDH tumors which display significant downregulation of inflammatory response pathways and immune-related genes. These findings contribute to further the understanding of mIDH BC and may inform the future development of rational combination therapies.

scholarly journals Transcriptome analysis reveals that exogenous ethylene activates immune and defense responses in a high late blight resistant potato genotype

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Xiaohui Yang ◽  
Li Chen ◽  
Yu Yang ◽  
Xiao Guo ◽  
Guangxia Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Late Blight ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Defense Responses ◽  
Differentially Expressed ◽  
Metabolic Pathway Analysis ◽  
Transcriptional Responses ◽  
Signaling Transduction Pathway ◽  
Potato Genotype

AbstractEthylene (ET) is one of the many important signaling hormones that functions in regulating defense responses in plants. Gene expression profiling was conducted under exogenous ET application in the high late blight resistant potato genotype SD20 and the specific transcriptional responses to exogenous ET in SD20 were revealed. Analysis of differentially expressed genes (DEGs) generated a total of 1226 ET-specific DEGs, among which transcription factors, kinases, defense enzymes and disease resistance-related genes were significantly differentially expressed. GO enrichment and KEGG metabolic pathway analysis also revealed that numerous defense regulation-related genes and defense pathways were significantly enriched. These results were consistent with the interaction of SD20 and Phytophthora infestans in our previous study, indicating that exogenous ET stimulated the defense response and initiated a similar defense pathway compared to pathogen infection in SD20. Moreover, multiple signaling pathways including ET, salicylic acid, jasmonic acid, abscisic acid, auxin, cytokinin and gibberellin were involved in the response to exogenous ET, which indicates that many plant hormones work together to form a complex network to resist external stimuli in SD20. ET-induced gene expression profiling provides insights into the ET signaling transduction pathway and its potential mechanisms in disease defense systems in potato.

scholarly journals Digital Gene Expression Profiling Analysis of Aged Mice under Moxibustion Treatment

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Nan Liu ◽  
Yunyao Jiang ◽  
Min Xing ◽  
Baixiao Zhao ◽  
Jincai Hou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Ontology ◽  
Gene Expression Profiling ◽  
Differentially Expressed Genes ◽  
Pathway Analysis ◽  
Expression Profiling ◽  
Digital Gene Expression ◽  
Differentially Expressed ◽  
Aged Mice ◽  
Digital Gene Expression Profiling

Aging is closely connected with death, progressive physiological decline, and increased risk of diseases, such as cancer, arteriosclerosis, heart disease, hypertension, and neurodegenerative diseases. It is reported that moxibustion can treat more than 300 kinds of diseases including aging related problems and can improve immune function and physiological functions. The digital gene expression profiling of aged mice with or without moxibustion treatment was investigated and the mechanisms of moxibustion in aged mice were speculated by gene ontology and pathway analysis in the study. Almost 145 million raw reads were obtained by digital gene expression analysis and about 140 million (96.55%) were clean reads. Five differentially expressed genes with an adjusted P value < 0.05 and |log⁡2(fold  change)| > 1 were identified between the control and moxibustion groups. They were Gm6563, Gm8116, Rps26-ps1, Nat8f4, and Igkv3-12. Gene ontology analysis was carried out by the GOseq R package and functional annotations of the differentially expressed genes related to translation, mRNA export from nucleus, mRNA transport, nuclear body, acetyltransferase activity, and so on. Kyoto Encyclopedia of Genes and Genomes database was used for pathway analysis and ribosome was the most significantly enriched pathway term.

A New Molecular Classification of Multiple Myeloma Using Gene Expression Profiling and Fluorescence In Situ Hybridisation as Predictor for Event Free Survival.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 73-73 ◽  
Author(s):  
Dirk Hose ◽  
Jean-Francois Rossi ◽  
Carina Ittrich ◽  
John deVos ◽  
Axel Benner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Molecular Classification ◽  
Differentially Expressed ◽  
Event Free Survival ◽  
Free Survival ◽  
Cytogenetic Aberrations

Abstract AIM was to establish a new molecular classification of Multiple Myeloma (MM) based on changes in global gene expression attributable to cytogenetic aberrations detected by interphase FISH (iFISH) in order to (i) predict event free survival (EFS) and (ii) investigate differentially expressed genes as basis for a group specific and risk adapted therapy. PATIENTS AND METHODS. Bone marrow aspirates of 105 newly diagnosed MM-patients (65 trial (TG) / 40 independent validation group (VG)) and 7 normal donors (ND) were CD138-purified by magnetic activated cell sorting. RNA was in-vitro transcribed and hybridised to Affymetrix HG U133 A+B GeneChip (TG) and HG U133 2.0 plus arrays (VG). CCND1 and CCND2 expression was verified by real time RT-PCR. iFISH was performed on purified MM-cells using probes for chromosomes 11q23, 11q13, 13q14, 17p13 and the IgH-translocations t(4;14) and t(11;14). Expression data were normalised (Bioconductor package gcrma) and nearest shrunken centroids (NSC) applied to calculate and cross validate a predictor on 40 patients of the TG with a comprehensive iFISH panel available combined with CCND overexpression. Differentially expressed genes were identified using empirical Bayes statistics for pairwise comparison. RESULTS. Overexpression of a D-type cyclin (D1 or D2) was found in 61/65 patients with MM compared to ND. CCND3 overexpression only appeared concomitantly with CCND2 overexpression. Four groups could be distinguished: (1.1) CCND1 (11q13) overexpression and trisomy 11q13, (1.2) CCND1 overexpression and translocations involving 11q13 i.e. t(11;14), (2.1) CCND2 overexpression without 11q13+, t(11;14), t(4;14), (2.2) CCND2 overexpression with t(4;14) and FGFR3 upregulation. A predictor of 6 to 566 genes correctly classifies all 40 patients of the TG (estimated cross validated error rate 0%). An independent VG of 40 patients was used. Genes with highest scores in NSC are: (1.1) CCND1, ribosomal proteins (e.g. RPL 28, 29), GPX1, CCRL2, (1.2) CCND1, TGIF, and NCAM (non-overexpression), (2.1) CCND2, (2.2) FGFR3, WHSC1, CCND2, IRTA2, SELL, and MAGED4. Distribution of clinical parameters (i.e. β2M, Durie Salmon stages, ISS) was not significantly different between the groups. The distribution of del(13)(q14q14) was (1.1) 31.5%, (1.2) 37.5%, (2.1) 37.5% and (2.2) 100%. (p<0.01). I.e. HGF, DKK1, VCAM, CD163 are differentially expressed between all 4 groups and ND (adjusted p<0.001). The groups defined by the predictor show a significantly different EFS after autologous stem cell transplantation according to the GMMG-HD3 protocol (median: (1.1) 18 / (1.2) not reached (no event) / (2.1) 22 / (2.2) 6 months; log-rank-test: p=0.004). CONCLUSION. CCND1 or CCND2 overexpression is nearly ubiquitous in MM and attributable to defined cytogenetic aberrations. Gene expression and iFISH allow a molecular classification of MM which can be predicted by gene expression profiling alone. Groups in the classification show a distinctive pattern in gene expression as well as a different EFS interpretable as risk stratification and indicator of therapeutic targets.

Gene Expression Profiling of Isolated Mesenchymal and Osteoblastic Cells Exhibits a Different Pattern of Expression in Multiple Myeloma Patients as Compared to Healthy Subjects: Potential Relationship with the Presence of Bone Lesions.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 3513-3513
Author(s):  
Nicola Giuliani ◽  
Katia Todoerti ◽  
Gina Lisignoli ◽  
Sara Tagliaferri ◽  
Luca Agnelli ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Cell Proliferation ◽  
Osteogenic Differentiation ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Differentially Expressed ◽  
Bone Lesions ◽  
Bone Status ◽  
Probe Set

Abstract Gene expression alterations occurring in the bone microenvironment cells and their potential relationships with the occurrence of bone lesions in multiple myeloma (MM) patients have never been investigated. In this study, we have isolated both mesenchymal (MSC) and osteoblastic (OB) cells, without in vitro differentiation, from bone biopsies obtained by iliac crest of 24 MM patients, 7 MGUS subjects and 8 healthy donors (N) who underwent orthopedics surgery. Bone status was evaluated in all MM patients by total X rays scan and MRI for the spine. Firstly, we evaluated cell proliferation in relationship with growth substrate (bone and glass) and cell phenotype by flow cytometry and immunohistochemistry. We found that both MSC and OB cells have higher cell doubling rate in MM patients as compared to N. Higher expression of alkaline phosphatase and Runx2 was observed in OB as compared to MSC cells in both N and MM patients without osteolytic lesions, but not in osteolytic ones. We performed a gene expression profiling analysis of isolated MSC and OB cells using GeneChip® Affymetrix HG-U133A oligonucleotide arrays. An unsupervised analysis of the most variable genes across the dataset generated a hierarchical clustering with the two major branches containing respectively MSC and OB samples. A multiclass analysis of N, MGUS and MM patients identified 33 differentially expressed probe-set (specific for 27 genes) in MSC cells, and 19 differentially expressed probe-set (13 genes) in OB, and the identified transcripts mainly characterized N versus MM and MGUS samples. A supervised analysis between N and MM samples identified 65 probes (56 genes: 17 up-regulated and 39 down-regulated) differentially expressed in MSC and 35 probes (29 genes, 12 up-regulated and 17 down-regulated) in OB. Notably, genes encoding the Homeobox class proteins, such as HOXB2-6-7, were up-regulated in both MSC and OB of MM patients as compared to N. As regards the bone status, a total of 60 probe-sets (3 up-regulated and 57 down-regulated genes) were found differentially expressed in MSC from osteolytic vs. non-osteolytic MM patients, whereas MGUS-MSC exhibited an intermediate transcriptional profile between osteolytic and non-osteolytic MM patients. A distinct pattern of gene expression profiling was also observed in MSC versus OB when osteolytic and non-osteolytic MM patients were compared (26 vs. 94 differentially expressed probe-sets, respectively), including transcription factors related to MSC osteogenic differentiation belonging to Runx2 pathway (HEY1) or Wnt and BMP signaling On the other hand, few genes were found differentially expressed in OB cells in relationship with the presence of bone lesions. In conclusion, we identified a distinctive transcriptional fingerprint in isolated MSC and OB cells of MM patients as compared to N subjects, which mainly correlated with cell proliferation. Moreover, a different gene expression profile was observed in MSC cells of MM patients according to the presence/absence of bone lesions, highlighting the critical role of the block of the osteogenic differentiation.

Blood-based gene expression profiling to reveal potential response biomarkers for immunotherapy in advanced lung cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15155-e15155
Author(s):  
Jie Wu ◽  
Weihua Huang ◽  
Changhong Yin ◽  
Yee Him Cheung ◽  
Debra Abrams ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Time Course ◽  
Γδ T Cells ◽  
Principal Component ◽  
Genetic Mutation ◽  
Differentially Expressed ◽  
Advanced Lung Cancer

e15155 Background: Novel immunotherapies are becoming a viable option for advanced lung cancer treatment. High-throughput gene expression profiling (GEP) has enabled better understanding of patient responsiveness to targeted immunotherapy. However, non-invasive blood-based signatures are needed to monitor and predict response. Methods: To evaluate the predictive and prognostic role of blood-based GEP, we designed a longitudinal study by enrolling 15 patients with advanced lung cancers. A total of 65 samples were collected for RNA sequencing, ~4 blood specimens per patient, before and during anti-PD-1 treatment. We used multiple analyses, including time-course differential gene expression, principal component, lymphocyte compartment deconvolution, and genetic mutation, to search for and assess potential predictive and prognostic aspects. Results: Of 15 patients, 11 were classified as Responders (partial responders) and four were Non-Responders (one stable and three progressive diseases). Our analyses demonstrated: 1) By comparing baseline GEPs from Responders vs. Non-Responders before the first treatment, we identified potential markers (e.g., LY6E is significantly lower expressed in Responders, with Log2 Fold change = -3.44 and p = 1.83E-04) that can be used as predictors of responsiveness of the patients; 2) Immunoglobulin subunits- and T cell receptor complex-related genes were differentially expressed in Responders (DAVID analysis, p = 6.7E-3 and 2.1E-2, respectively), but not in Non-responders; 3) γδ T cells in the lymphocyte compartment were relatively increased in Responders; 4) Despite a different set of genes differentially expressed at different time points, the biggest GEP changes were at ~ week 6, after the second treatment. Additionally, we observed certain genes consistently up- or down-regulated through the whole course of treatment. Furthermore, after the first treatment, genes in the immune response pathway were regulated to different directions in Responders and Non-Responders. For example, interleukin receptor genes, such as IL18R1 and IL18RAP, and CD24 were down-regulated in Responders, but up-regulated in Non-Responders (p = 0.042, 0.023 and 0.044 respectively, t-test for the differential expression in these two groups). Conclusions: The utility of blood GEP to identify predictive and prognostic factors for precision immunotherapy is encouraging. Nevertheless, these results, predictive of the anti-PD-1 clinical response, are preliminary and need to be validated in a larger cohort.

scholarly journals Gene expression profiling in whole blood of patients with coronary artery disease

2010 ◽  
Vol 119 (8) ◽  
pp. 335-343 ◽  
Author(s):  
Chiara Taurino ◽  
William H. Miller ◽  
Martin W. McBride ◽  
John D. McClure ◽  
Raya Khanin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Gene Expression Profiling ◽  
Whole Blood ◽  
Expression Profiling ◽  
Gene Expression Analysis ◽  
Differentially Expressed ◽  
Differentially Expressed Mirnas ◽  
Artery Disease

Owing to the dynamic nature of the transcriptome, gene expression profiling is a promising tool for discovery of disease-related genes and biological pathways. In the present study, we examined gene expression in whole blood of 12 patients with CAD (coronary artery disease) and 12 healthy control subjects. Furthermore, ten patients with CAD underwent whole-blood gene expression analysis before and after the completion of a cardiac rehabilitation programme following surgical coronary revascularization. mRNA and miRNA (microRNA) were isolated for expression profiling. Gene expression analysis identified 365 differentially expressed genes in patients with CAD compared with healthy controls (175 up- and 190 down-regulated in CAD), and 645 in CAD rehabilitation patients (196 up- and 449 down-regulated post-rehabilitation). Biological pathway analysis identified a number of canonical pathways, including oxidative phosphorylation and mitochondrial function, as being significantly and consistently modulated across the groups. Analysis of miRNA expression revealed a number of differentially expressed miRNAs, including hsa-miR-140-3p (control compared with CAD, P=0.017), hsa-miR-182 (control compared with CAD, P=0.093), hsa-miR-92a and hsa-miR-92b (post- compared with pre-exercise, P<0.01). Global analysis of predicted miRNA targets found significantly reduced expression of genes with target regions compared with those without: hsa-miR-140-3p (P=0.002), hsa-miR-182 (P=0.001), hsa-miR-92a and hsa-miR-92b (P=2.2×10−16). In conclusion, using whole blood as a ‘surrogate tissue’ in patients with CAD, we have identified differentially expressed miRNAs, differentially regulated genes and modulated pathways which warrant further investigation in the setting of cardiovascular function. This approach may represent a novel non-invasive strategy to unravel potentially modifiable pathways and possible therapeutic targets in cardiovascular disease.

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