Gene Expression in CLL Cells Associated with Lymphadenopathy and Chromosome 11q23 Deletion.

Abstract Previously we have demonstrated that peripheral blood samples with B-cell Chronic Lymphocytic Leukemia (CLL) have different gene expression profiles associated with chromosome aberrations detected by fluorescence in situ hybridization (FISH). In particular, the vast majority of differentially expressed genes were related to the presence of the 11q23 deletion. The 11q23 deletion has previously been shown to be correlated with shortened over-all survival and extensive/bulky lymphadenopathy. In this study we sought to identify genes whose expression may play role in the progression of CLL in patients that carry the 11q23 deletion. Gene expression from 10,700 human gene specific 50-mer oligos (MWG Biotech, Ebersberg, Germany) was compared between two groups of peripheral blood CLL samples. The first group consisted of CLL patients with the 11q23 deletion detected by FISH as well as with the presence of abdominal/mediastinal lymphadenopathy. The second group consisted of CLL patients without the 11q23 deletion and without the presence of known abdominal/mediastinal lymphadenopathy. The non-11q deletion group included CLL patients with the 13q14 deletion, trisomy 12, 17p13 deletion, as well as several without any detectable abnormality. Immunoglobulin heavy chain variable region (IgVH) mutational status was compared in CLL samples in both groups to ensure that resulting expression differences were not the result of this known prognostic marker. Median of ratios was compared between the two groups. Eighty-eight (87) genes had a p-value < 0.01. Gene function was classified at the European Molecular Biology Laboratory (EMBL) Bioinformatic Harvester website. Twenty of these differentially expressed genes were cell cycle/cell signaling related genes that were over-expressed in the 11q23 deletion group. Examples include: activating transcription factor 4, rho-associated coiled-coil containing protein kinase 2, fibroblast growth factor 21 precursor, signal transducing adaptor molecule 1, mad2-like 1, interferon receptor 1, pim-2 oncogene, and zw10 interactor. In comparison, using the same peripheral blood CLL samples, 78 genes were differentially expressed (p < 0.01) between those samples that had a mutated IgVH versus those that had an unmutated IgVH. Therefore, the presence of both the 11q23 deletion and bulky abdominal/mediastinal lymphadenopathy significantly alters the gene expression profile of peripheral blood CLL cells, particularly genes related to the cell cycle and cell signaling related processes. Biological roles of some of these genes may help further elucidate the basis of the clinical behavior of CLL patients

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Association Between Gene Expression Profiles and Commonly Mutated Genes In The Hematopoietic Stem Cells Of Patients With Myelodysplastic Syndromes

Blood ◽

10.1182/blood.v122.21.2779.2779 ◽

2013 ◽

Vol 122 (21) ◽

pp. 2779-2779 ◽

Cited By ~ 1

Author(s):

Andrea Pellagatti ◽

Moritz Gerstung ◽

Elli Papaemmanuil ◽

Luca Malcovati ◽

Aristoteles Giagounidis ◽

...

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Gene Expression Data ◽

Expression Profiles ◽

Gene Mutations ◽

Gene Expression Profiles ◽

Differentially Expressed ◽

Expression Data ◽

Common Gene ◽

Mutational Status

Abstract A particular profile of gene expression can reflect an underlying molecular abnormality in malignancy. Distinct gene expression profiles and deregulated gene pathways can be driven by specific gene mutations and may shed light on the biology of the disease and lead to the identification of new therapeutic targets. We selected 143 cases from our large-scale gene expression profiling (GEP) dataset on bone marrow CD34+ cells from patients with myelodysplastic syndromes (MDS), for which matching genotyping data were obtained using next-generation sequencing of a comprehensive list of 111 genes involved in myeloid malignancies (including the spliceosomal genes SF3B1, SRSF2, U2AF1 and ZRSR2, as well as TET2, ASXL1and many other). The GEP data were then correlated with the mutational status to identify significantly differentially expressed genes associated with each of the most common gene mutations found in MDS. The expression levels of the mutated genes analyzed were generally lower in patients carrying a mutation than in patients wild-type for that gene (e.g. SF3B1, ASXL1 and TP53), with the exception of RUNX1 for which patients carrying a mutation showed higher expression levels than patients without mutation. Principal components analysis showed that the main directions of gene expression changes (principal components) tend to coincide with some of the common gene mutations, including SF3B1, SRSF2 and TP53. SF3B1 and STAG2 were the mutated genes showing the highest number of associated significantly differentially expressed genes, including ABCB7 as differentially expressed in association with SF3B1 mutation and SULT2A1 in association with STAG2 mutation. We found distinct differentially expressed genes associated with the four most common splicing gene mutations (SF3B1, SRSF2, U2AF1 and ZRSR2) in MDS, suggesting that different phenotypes associated with these mutations may be driven by different effects on gene expression and that the target gene may be different. We have also evaluated the prognostic impact of the GEP data in comparison with that of the genotype data and importantly we have found a larger contribution of gene expression data in predicting progression free survival compared to mutation-based multivariate survival models. In summary, this analysis correlating gene expression data with genotype data has revealed that the mutational status shapes the gene expression landscape. We have identified deregulated genes associated with the most common gene mutations in MDS and found that the prognostic power of gene expression data is greater than the prognostic power provided by mutation data. AP and MG contributed equally to this work. JB and PJC are co-senior authors. Disclosures: No relevant conflicts of interest to declare.

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A Distinct Expression of Various Gene Subsets in CD34+ Cells Obtained From Patients with Early and Advanced Myelodysplastic Syndrome.

Blood ◽

10.1182/blood.v114.22.3795.3795 ◽

2009 ◽

Vol 114 (22) ◽

pp. 3795-3795

Author(s):

Monika Belickova ◽

Jaroslav Cermak ◽

Alzbeta Vasikova ◽

Eva Budinska

Keyword(s):

Gene Expression ◽

Cell Cycle ◽

Differentially Expressed Genes ◽

Conflicts Of Interest ◽

Expression Profiles ◽

Differentially Expressed ◽

Abnormal Development ◽

Statistical Hypothesis ◽

P Value ◽

Cd34 Cells

Abstract Abstract 3795 Poster Board III-731 Gene expression profiles of CD34+ cells were compared between a cohort of 51 patients with MDS or AML from MDS and 7 healthy controls. The patients were classified according to the WHO criteria as follows: 5q- syndrome (n=7), RA (n=3), RARS (n=2), RCMD (n=10), RAEB-1 (n=7), RAEB-2 (n=15), and AML with MLD (multilineage dysplasia) (n=7). HumanRef-8 v2 Expression Bead Chips (Illumina) were used to generate expression profiles of the samples for >22,000 transcripts. The raw data were normalized data with the R software, lumi package. Normalized data were filtered by detection p-value <0.01, resulting in total number of 9811genes. To identify differentially expressed genes we performed two parallel statistical hypothesis testings: Analysis of Variance (ANOVA) together with Tukey test and empirical bayesian thresholding correction for multiple testing problem; and Significance Analysis of Microarrays (SAM). The results were confirmed by real-time quantitative PCR for six genes (TaqMan Gene Expression Assays). Hierarchical clustering of significantly differentially expressed genes clearly separated patients and controls, 5q-syndrome and RAEB-1 as a separate entities confirming usefulness of WHO classification subgroups. The most up-regulated genes in all patients included HBG2, HBG1, CYBRD1, HSPA1B, ANGPT1, and MYC. We assume that expression changes in globin genes, both fetal and adult globins (HBG2, HBG1 and HBA1, HBB) may play role not only in dysregulation of erythropoiesis but also in the disease progression or leukemic transformation of MDS. Among the most down-regulated genes, 13 genes related to B-lymphopoiesis (e.g. POU2AF1, VPREB1, VPREB3, CD79A, EBF1, LEF1, BCL3, IRF8 & IRF4) were detected, suggesting the abnormal development of B-cell progenitors in all MDS patients. Some of these genes (e.g. VPREB3, LEF1) showed decreasing trend in expression level from early to advanced MDS with the lowest expression in AML with MLD. Patients with advanced MDS had significantly decreased expression of genes involved in in the mitotic cell cycle, DNA replication, and chromosome segregation compared to early MDS where these gene subsets were up-regulated. The DAVID database also identified de-regulation in the cell cycle pathway through its 7 genes (CDC25C, CDC7, CDC20, ORC1L, CCNB2, BUB1, & CCNA2). On the other hand, advanced MDS patients showed significant up-regulation of proto-oncogenes (BMI1, MERTK) and genes related to angiogenesis (ANGPT1), anti-apoptosis (VNN1). The results confirm on molecular basis that increased cell proliferation and resistance to apoptosis together with a loss of cell cycle control, damaged DNA repair and altered immune response may play an important role in the expansion of malignant clone in MDS patients. The study was supported by Grant NR-9235 obtained from the Ministry of Health, Czech Republic. Disclosures: No relevant conflicts of interest to declare.

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HIV-1 Infection Transcriptomics: Meta-Analysis of CD4+ T Cells Gene Expression Profiles

Viruses ◽

10.3390/v13020244 ◽

2021 ◽

Vol 13 (2) ◽

pp. 244 ◽

Cited By ~ 1

Author(s):

Antonio Victor Campos Coelho ◽

Rossella Gratton ◽

João Paulo Britto de Melo ◽

José Leandro Andrade-Santos ◽

Rafael Lima Guimarães ◽

...

Keyword(s):

Gene Expression ◽

T Cells ◽

Differentially Expressed Genes ◽

Cd4 T Cells ◽

Expression Profiles ◽

Meta Analysis ◽

Differentially Expressed ◽

Rna Seq ◽

Infected Cells ◽

Hiv 1

HIV-1 infection elicits a complex dynamic of the expression various host genes. High throughput sequencing added an expressive amount of information regarding HIV-1 infections and pathogenesis. RNA sequencing (RNA-Seq) is currently the tool of choice to investigate gene expression in a several range of experimental setting. This study aims at performing a meta-analysis of RNA-Seq expression profiles in samples of HIV-1 infected CD4+ T cells compared to uninfected cells to assess consistently differentially expressed genes in the context of HIV-1 infection. We selected two studies (22 samples: 15 experimentally infected and 7 mock-infected). We found 208 differentially expressed genes in infected cells when compared to uninfected/mock-infected cells. This result had moderate overlap when compared to previous studies of HIV-1 infection transcriptomics, but we identified 64 genes already known to interact with HIV-1 according to the HIV-1 Human Interaction Database. A gene ontology (GO) analysis revealed enrichment of several pathways involved in immune response, cell adhesion, cell migration, inflammation, apoptosis, Wnt, Notch and ERK/MAPK signaling.

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Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Hashimoto’s Thyroiditis

10.21203/rs.3.rs-1023446/v1 ◽

2021 ◽

Author(s):

Li Guoquan ◽

Du Junwei ◽

He Qi ◽

Fu Xinghao ◽

Ji Feihong ◽

...

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Inflammatory Responses ◽

Expression Profiles ◽

Treatment Options ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Chronic Lymphocytic Thyroiditis ◽

Hub Genes

Abstract BackgroundHashimoto's thyroiditis (HT), also known as chronic lymphocytic thyroiditis, is a common autoimmune disease, which mainly occurs in women. The early manifestation was hyperthyroidism, however, hypothyroidism may occur if HT was not controlled for a long time. Numerous studies have shown that multiple factors, including genetic, environmental, and autoimmune factors, were involved in the pathogenesis of the disease, but the exact mechanisms were not yet clear. The aim of this study was to identify differentially expressed genes (DEGs) by comprehensive analysis and to provide specific insights into HT. MethodsTwo gene expression profiles (GSE6339, GSE138198) about HT were downloaded from the Gene Expression Omnibus (GEO) database. The DEGs were assessed between the HT and normal groups using the GEO2R. The DEGs were then sent to the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The hub genes were discovered using Cytoscape and CytoHubba. Finally, NetworkAnalyst was utilized to create the hub genes' targeted microRNAs (miRNAs). ResultsA total of 62 DEGs were discovered, including 60 up-regulated and 2 down-regulated DEGs. The signaling pathways were mainly engaged in cytokine interaction and cytotoxicity, and the DEGs were mostly enriched in immunological and inflammatory responses. IL2RA, CXCL9, IL10RA, CCL3, CCL4, CCL2, STAT1, CD4, CSF1R, and ITGAX were chosen as hub genes based on the results of the protein-protein interaction (PPI) network and CytoHubba. Five miRNAs, including mir-24-3p, mir-223-3p, mir-155-5p, mir-34a-5p, mir-26b-5p, and mir-6499-3p, were suggested as likely important miRNAs in HT. ConclusionsThese hub genes, pathways and miRNAs contribute to a better understanding of the pathophysiology of HT and offer potential treatment options for HT.

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Insight into Molecular Profile Changes after Skeletal Muscle Contusion Using Microarray and Bioinformatics Analyses

10.21203/rs.3.rs-85830/v1 ◽

2020 ◽

Author(s):

Na Li ◽

Ru-feng Bai ◽

Chun Li ◽

Li-hong Dang ◽

Qiu-xiang Du ◽

...

Keyword(s):

Gene Expression ◽

Network Analysis ◽

Differentially Expressed Genes ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Healing Process ◽

Differentially Expressed ◽

Molecular Profile ◽

Wound Age ◽

Functional Modules

Abstract Background: Muscle trauma frequently occurs in daily life. However, the molecular mechanisms of muscle healing, which partly depend on the extent of the damage, are not well understood. This study aimed to investigate gene expression profiles following mild and severe muscle contusion, and to provide more information about the molecular mechanisms underlying the repair process.Methods: A total of 33 rats were divided randomly into control (n = 3), mild contusion (n = 15), and severe contusion (n = 15) groups; the contusion groups were further divided into five subgroups (1, 3, 24, 48, and 168 h post-injury; n = 3 per subgroup). Then full genome microarray of RNA isolated from muscle tissue was performed to access the gene expression changes during healing process.Results: A total of 2,844 and 2,298 differentially expressed genes were identified in the mild and severe contusion groups, respectively. The analysis of the overlapping differentially expressed genes showed that there are common mechanisms of transcriptomic repair of mild and severe contusion within 48 h post-contusion. This was supported by the results of principal component analysis, hierarchical clustering, and weighted gene co‐expression network analysis of the 1,620 coexpressed genes in mildly and severely contused muscle. From these analyses, we discovered that the gene profiles in functional modules and temporal clusters were similar between the mild and severe contusion groups; moreover, the genes showed time-dependent patterns of expression, which allowed us to identify useful markers of wound age. We then performed an analysis of the functions of genes (including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway annotation, and protein–protein interaction network analysis) in the functional modules and temporal clusters, and the hub genes in each module–cluster pair were identified. Interestingly, we found that genes downregulated within 24−48 h of the healing process were largely associated with metabolic processes, especially oxidative phosphorylation of reduced nicotinamide adenine dinucleotide phosphate, which has been rarely reported. Conclusions: These results improve our understanding of the molecular mechanisms underlying muscle repair, and provide a basis for further studies of wound age estimation.

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Gene Expression Profiles of Papillary Thyroid Microcarcinoma

International Surgery ◽

10.9738/intsurg-d-17-00049.1 ◽

2017 ◽

Vol 102 (1-2) ◽

pp. 39-46 ◽

Cited By ~ 1

Author(s):

Woo Young Kim ◽

Jae Bok Lee ◽

Seung Pil Jung ◽

Hoon Yub Kim ◽

Sang Uk Woo ◽

...

Keyword(s):

Gene Expression ◽

Gene Expression Profile ◽

Differentially Expressed Genes ◽

Expression Profile ◽

Expression Profiles ◽

Differentially Expressed ◽

Papillary Thyroid Microcarcinoma ◽

Papillary Thyroid ◽

Normal Thyroid ◽

Thyroid Microcarcinoma

The objective was to identify gene expression profile of papillary thyroid microcarcinoma. To help improve diagnosis of papillary thyroid microcarcinoma, we performed gene expression profiling and compared it to pair normal thyroid tissues. We performed microarray analysis with 6 papillary thyroid microcarcinoma and 6 pair normal thyroid tissues. Differentially expressed genes were selected using paired t test, linear models for microarray data, and significance analysis of microarrays. Real-time quantitative reverse transcription–polymerase chain reaction was used to validate the representative 10 genes (MET, TIMP1, QPCT, PROS1, LRP4, SDC4, CITED1, DPP4, LRRK2, RUNX2). We identified 91 differentially expressed genes (84 upregulated and 7 downregulated) in the gene expression profile and validated 10 genes of the profile. We identified a significant genetic difference between papillary thyroid microcarcinoma and normal tissue by 10 upregulated genes greater than 2-fold (P < 0.05).

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Integrated Transcriptomic Analysis of Necrosis-related Gene in Diffuse Gliomas

Journal of Neurological Surgery Part A Central European Neurosurgery ◽

10.1055/s-0039-1683448 ◽

2019 ◽

Vol 80 (04) ◽

pp. 240-249

Author(s):

Jiajia Wang ◽

Jie Ma

Keyword(s):

Gene Expression ◽

High Risk ◽

Differentially Expressed Genes ◽

Expression Profiles ◽

Prognostic Index ◽

Gene Expression Profiles ◽

Risk Groups ◽

Low Risk ◽

Differentially Expressed ◽

Low Grade

Glioblastoma multiforme (GBM), an aggressive brain tumor, is characterized histologically by the presence of a necrotic center surrounded by so-called pseudopalisading cells. Pseudopalisading necrosis has long been used as a prognostic feature. However, the underlying molecular mechanism regulating the progression of GBMs remains unclear. We hypothesized that the gene expression profiles of individual cancers, specifically necrosis-related genes, would provide objective information that would allow for the creation of a prognostic index. Gene expression profiles of necrotic and nonnecrotic areas were obtained from the Ivy Glioblastoma Atlas Project (IVY GAP) database to explore the differentially expressed genes.A robust signature of seven genes was identified as a predictor for glioblastoma and low-grade glioma (GBM/LGG) in patients from The Cancer Genome Atlas (TCGA) cohort. This set of genes was able to stratify GBM/LGG and GBM patients into high-risk and low-risk groups in the training set as well as the validation set. The TCGA, Repository for Molecular Brain Neoplasia Data (Rembrandt), and GSE16011 databases were then used to validate the expression level of these seven genes in GBMs and LGGs. Finally, the differentially expressed genes (DEGs) in the high-risk and low-risk groups were subjected to gene ontology enrichment, Kyoto Encyclopedia of Genes and Genomes pathway, and gene set enrichment analyses, and they revealed that these DEGs were associated with immune and inflammatory responses. In conclusion, our study identified a novel seven-gene signature that may guide the prognostic prediction and development of therapeutic applications.

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Genomewide Expression Profile Analysis of the Candida glabrata Pdr1 Regulon

Eukaryotic Cell ◽

10.1128/ec.00073-10 ◽

2010 ◽

Vol 10 (3) ◽

pp. 373-383 ◽

Cited By ~ 48

Author(s):

Kelly E. Caudle ◽

Katherine S. Barker ◽

Nathan P. Wiederhold ◽

Lijing Xu ◽

Ramin Homayouni ◽

...

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Candida Glabrata ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Differentially Expressed ◽

Resistant Isolate ◽

Content Type ◽

Activating Mutations ◽

Zinc Cluster

ABSTRACTThe ABC transportersCandida glabrataCdr1 (CgCdr1), CgPdh1, and CgSnq2 are known to mediate azole resistance in the pathogenic fungusC. glabrata. Activating mutations inCgPDR1, a zinc cluster transcription factor, result in constitutive upregulation of these ABC transporter genes but to various degrees. We examined the genomewide gene expression profiles of two matched azole-susceptible and -resistantC. glabrataclinical isolate pairs. Of the differentially expressed genes identified in the gene expression profiles for these two matched pairs, there were 28 genes commonly upregulated withCgCDR1in both isolate sets includingYOR1,LCB5,RTA1,POG1,HFD1, and several members of theFLOgene family of flocculation genes. We then sequencedCgPDR1from each susceptible and resistant isolate and found two novel activating mutations that conferred increased resistance when they were expressed in a common background strain in whichCgPDR1had been disrupted. Microarray analysis comparing these reengineered strains to their respective parent strains identified a set of commonly differentially expressed genes, includingCgCDR1,YOR1, andYIM1, as well as genes uniquely regulated by specific mutations. Our results demonstrate that while CgPdr1 activates a broad repertoire of genes, specific activating mutations result in the activation of discrete subsets of this repertoire.

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Microarray Analysis of Peripheral Blood Monocytes in Sickle Cell Anemia Patients with Cerebrovascular Stenosis.

Blood ◽

10.1182/blood.v104.11.3570.3570 ◽

2004 ◽

Vol 104 (11) ◽

pp. 3570-3570

Author(s):

M. Catherine Driscoll ◽

Remi Adenika ◽

Ronald L. Nagel ◽

Eric P. Hoffman

Keyword(s):

Gene Expression ◽

Cell Signaling ◽

Differentially Expressed Genes ◽

Sickle Cell ◽

Sickle Cell Anemia ◽

Peripheral Blood ◽

Blood Monocytes ◽

Peripheral Blood Monocytes ◽

Lymphocyte Antigen ◽

Antigen Complex

Abstract Cerebrovascular disease (CVD) of both large and small cerebral vessels occurs in one-third of patients with sickle cell anemia (SCA) by age 20 years. Large vessel stenosis (LVS) occurs in ~10% of patients and is associated with overt stroke and/or (+) transcranial Doppler (TCD). Epistatic genetic modifiers are postulated to account for the significant phenotypic heterogeneity of SCA and likely contribute to CVD. Potential genetic modifers of CVD may be found in pathways for inflammation, adhesion, stress/immune reactions, angiogenesis, thrombosis, and oxidant generation. Peripheral blood monocytes are activated in SCA and contribute to inflammation and endothelial activation. The goal of this study is to determine if there is a difference in gene expression profiles of monocytes in patients with SCA and LVS, compared to SCA controls without CVD, and to normal African American (AA) controls. The study group consisted of 1) SCA patients with LVS [n = 6, (moyamoya = 3, no moyamoya =3)], 2) SCA patients without CVD and nornal TCD (n = 3), and 3) normal AA controls (n = 3). The 6 SCA-LVS patients were on chronic transfusion programs to maintain Hb S <30%. Monocytes were isolated by negative selection (RosetteSep Antibody) and total RNA extracted, converted to cRNA and hybridized to Affymetrix U133A GeneChip. Gene profiles were analyzed using dChip version 1.3 and gene lists were created for genes with a 2-fold or greater increase or decrease in expression with a Welch t-test p-values of 0.05 or less. Results: 1) SCA controls without CVD compared to AA controls revealed 50 differentially expressed genes (p<0.05), 16 with 2-fold or greater change. Differential gene expression was observed in pathways for angiogenesis (PD-ECGF, 5.1 fold, p = 0.025), cell signaling (lymphocyte antigen complex 6, 10.4 fold, p = 0.032, STAT1, 5.1 fold, p = 0.039), and inflammation (MARCO, 3.1 fold, p = 0.042). 2) SCA patients with LVS compared to SCA controls revealed 47 differentially expressed genes (p = <0.05) but only 6 genes with 2-fold or greater change. These included angiogenesis (PD-ECFG, -3.59 fold, p = 0.02), cell signaling (lymphocyte antigen complex 6, −4.61 fold, p = 0.02), adhesion (junction plakoglobin, −7.73 fold, p = 0.03), inflammation (LTA4H, 2.57 fold, p =0.009). These data suggest that patients with SCA and LVS overexpress leukotriene A4 hydrolase (LTA4H), an enzyme that catalyzes the final step in the leukotriene B4 (LTB4) pathway. LTB4 is a chemoattractant which triggers adhesion and aggregation of leukocytes to the endothelium. Five-lipoxygenase-activating protein (FLAP), a leukotriene pathway protein has recently been identified as a candidate gene for stroke and AMI risk in an Icelandic population. Also of interest, the SCA-LVS patients showed decreased expression of PD-ECFG and lymphocyte antigen complex 6, both genes being significantly overexpressed in SCA controls. Since the SCA-LVS patients are on chronic transfusion, underexpression could be due to the ameliorating effects of transfusion therapy. Validation studies of these findings are currently underway.

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Changes in Gene Expression Profiles in Patients with 5q- Syndrome Caused by Lenalidomide Treatment

Blood ◽

10.1182/blood.v118.21.5023.5023 ◽

2011 ◽

Vol 118 (21) ◽

pp. 5023-5023

Author(s):

Monika Belickova ◽

Jaroslav Cermak ◽

Jitka Vesela ◽

Eliska Cechova ◽

Zuzana Zemanova ◽

...

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Conflicts Of Interest ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Differentially Expressed ◽

Aurora A ◽

Genes Expression ◽

Marrow Stroma ◽

Cell Niche

Abstract Abstract 5023 A direct effects of lenalidomide on gene expression in 5q- patients was studied using HumanRef-8 v2 Expression BeadChips (Illumina). Expression profiles of 6 patients (before treatment and at the time of the first erytroid response) and 6 healthy controls were investigated from CD14+ monocytes of peripheral blood. Differentially expressed genes were identified by Significance Analysis of Microarrays (SAM). Simultaneously, selected genes (TNF, JUN, IL1) were monitored in the course of treatment using Real-Time PCR with Taqman Gene Expression Assays. A comparison of gene expression levels before and during lenalidomide treatment revealed 97 differentially expressed genes (FC >2; p<0.05) related to following biological processes: immune response (16 genes), inflammatory response (11 genes), response to bacteria (8 genes), anti-apoptosis (7 genes), regulation of MAP kinase activity (5 genes), oxygen transport (4 genes), and regulation of cell proliferation (11 genes). An overexpression of a number of cytokines (e.g. TNF, IL8, IL1B, CCL3L, CXCL2, and TNFAIP3) was detected in patients before treatment, after lenalidomide administration expression of the majority of the up-regulated cytokine genes decreased to the control baseline level. Detected overproduction of the cytokines in 5q- syndrome may lead to an increased apoptosis of hematopoietic progenitor cells and together with excessive oxidative stress may contribute to the damage the hematopoietic niche. In the same manner, untreated patients showed suppressed expression of two genes (CXCR4, CRTAP) which play an important role in the stem cell niche. After treatment, we detected increased expression of these genes. Both the observations might explain favorable effects of lenalidomide on the bone marrow stroma defect seen in 5q- syndrome. On the other hand, a substantial increase of the ARPC1B gene (an activator and a substrate of Aurora A) expression was detected after lenalidomide treatment. Since overexpression of Aurora A leads to polyploidy and chromosomal instability, ARPC1B might play a role in the disease progression observed in some patients treated with lenalidomide. To conclude, described changes in genes expression may contribute to identification of the pathways affected by lenalidomide and to the explanation of some effects of this drug that have not been fully understood yet. Supported by grants NS/9634 MZCR, UHKT2005 00023736, MSM0021620808 and COST EUGESMA Disclosures: No relevant conflicts of interest to declare.

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