Genes differentially expressed in medulloblastoma and fetal brain

Michiels, E. M. C., E. Oussoren, M. van Groenigen, E. Pauws, P. M. M. Bossuyt, P. A. Voûte, and F. Baas. Genes differentially expressed in medulloblastoma and fetal brain. Physiol. Genomics 1: 83–91, 1999.—Serial analysis of gene expression (SAGE) was used to identify genes that might be involved in the development or growth of medulloblastoma, a childhood brain tumor. Sequence tags from medulloblastoma (10229) and fetal brain (10692) were determined. The distributions of sequence tags in each population were compared, and for each sequence tag, pairwise χ2 test statistics were calculated. Northern blot was used to confirm some of the results obtained by SAGE. For 16 tags, the χ2 test statistic was associated with a P value < 10−4. Among those transcripts with a higher expression in medulloblastoma were the genes for ZIC1 protein and the OTX2 gene, both of which are expressed in the cerebellar germinal layers. The high expression of these two genes strongly supports the hypothesis that medulloblastoma arises from the germinal layer of the cerebellum. This analysis shows that SAGE can be used as a rapid differential screening procedure.

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An approach to gene-based testing accounting for dependence of tests among nearby genes

10.1101/2021.05.24.445494 ◽

2021 ◽

Author(s):

Ronald J Yurko ◽

Kathryn Roeder ◽

Bernie Devlin ◽

Max G'Sell

Keyword(s):

Multiple Testing ◽

Association Studies ◽

Autism Spectrum ◽

P Value ◽

Genome Wide Association Studies ◽

Strongly Correlated ◽

Test Statistics ◽

Test Statistic ◽

Genome Wide ◽

Insight Into

In genome-wide association studies (GWAS), it has become commonplace to test millions of SNPs for phenotypic association. Gene-based testing can improve power to detect weak signal by reducing multiple testing and pooling signal strength. While such tests account for linkage disequilibrium (LD) structure of SNP alleles within each gene, current approaches do not capture LD of SNPs falling in different nearby genes, which can induce correlation of gene-based test statistics. We introduce an algorithm to account for this correlation. When a gene's test statistic is independent of others, it is assessed separately; when test statistics for nearby genes are strongly correlated, their SNPs are agglomerated and tested as a locus. To provide insight into SNPs and genes driving association within loci, we develop an interactive visualization tool to explore localized signal. We demonstrate our approach in the context of weakly powered GWAS for autism spectrum disorder, which is contrasted to more highly powered GWAS for schizophrenia and educational attainment. To increase power for these analyses, especially those for autism, we use adaptive p-value thresholding (AdaPT), guided by high-dimensional metadata modeled with gradient boosted trees, highlighting when and how it can be most useful. Notably our workflow is based on summary statistics.

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Gene expression panel (TheraPrint) analyzed as predictors of response to neoadjuvant chemotherapy (NCT) in patients (pts) with stage II-III and inflammatory breast cancer (BC).

Journal of Clinical Oncology ◽

10.1200/jco.2012.30.15_suppl.e21013 ◽

2012 ◽

Vol 30 (15_suppl) ◽

pp. e21013-e21013

Author(s):

Femke De Snoo ◽

Justine Peeters ◽

Kim Robinson ◽

Lisette Stork-Sloots ◽

Iris Simon ◽

...

Keyword(s):

Gene Expression ◽

Survival Data ◽

Stage Ii ◽

Differentially Expressed ◽

P Value ◽

Expression Data ◽

Global Test ◽

Patient Cohort ◽

Predictors Of Response ◽

Canonical Pathways

e21013 Background: TheraPrint is a microarray-based gene expression panel of 125 genes identified as potential targets for prognosis and therapeutic response. These genes may hold the key to a greater level of personalized prognosis and therapy for BC pts. The aim of the current study was to assess the clinical relevance of the TheraPrint genes for either predictive and/or prognostic value in 2 patient cohorts treated with NCT. Methods: The 1st patient cohort are 68 Stage II-III BC pts treated with NCT. Expression data from Agilent full genome arrays, containing the MammaPrint, BluePrint and TheraPrint diagnostic profiles/probes (Somlo et al, 2009). Median FU 2.3 years. The 2nd patient cohort are 230 Stage I-III BC pts treated with NCT. Expression data from Affymetrix probe sets was publically available (Iwamoto et al, 2011). Median FU 5.2 years. To identify genes that are differentially expressed between responders (pCR/RCBI) and non-responders, a supervised analysis was performed. The analysis was performed across all pts and also within groups of HER2+ and HER2-. Univariate t-tests were performed, with results filtered by permutation p-value (p<0.05) and fold change of >1.5. Global test was also reported. In addition, survival data analysis was performed across all pts. Results: Overlapping genes between the 2 datasets that were significantly differentially expressed between responders and non-responders include: BCL2 (down-regulated) and CDH3, GRB7, KRT6B, KRT17 (up-regulated). When analysing the HER2- subgroup, 3 genes turned out to be differentially expressed between responders and non-responders in the 2 datasets: FLT1, PIK3R1 (down-regulated) and KRT6B (up-regulated). For the HER2+ subgroup, only one gene overlapped for the 2 datasets: IL2RA (up-regulated). The top canonical pathways for the significant genes have been analyzed, and in addition correlation of the TheraPrint gene expression with survival for these pt groups. Conclusions: This study has identified several genes from a panel of 125 TheraPrint genes with statistically significant correlation between expression and response to NCT.

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Identification of Perturbed Pathways Rendering Susceptibility to Tuberculosis in Type 2 Diabetes Mellitus Patients Using BioNSi Simulation of Integrated Network of Implicated Human Genes

10.21203/rs.3.rs-863821/v1 ◽

2021 ◽

Author(s):

Jyoti Rani ◽

Anasuya Bhargav ◽

Malabika Datta ◽

Urmi Bajpai ◽

Srinivasan Ramachandran

Keyword(s):

Gene Expression ◽

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Mapk Signaling ◽

Differentially Expressed ◽

P Value ◽

Receptor Signaling ◽

Chronic Hyperglycemia

Abstract Adaptive immune response of the Th1 arm is the main defense against tuberculosis (TB). However, in Type 2 Diabetes Mellitus (T2DM) patients, chronic hyperglycemia and inflammation underlie susceptibility to TB and results in poor TB control. The molecular pathways causing susceptibility of diabetics to tuberculosis is not fully understood. Here, an integrative pathway-based approach is used to investigate the perturbed pathways in T2DM patients rendering susceptibility to TB. We obtained 36 genes implicated in the Type 2 diabetes associated tuberculosis (T2DMTB) from literature. Gene expression analysis on T2DM patients’ data (GSE28168) showed that DEFA1 is differentially expressed at Padj < 0.05. The genes CAMP, CD14, CORO1A, LAMP1, TLR4, IL17F and SOCS3 were differentially expressed in T2DM patients at P value < 0.05. 7 microRNAs associated with these T2DMTB genes were obtained from NetworkAnalyst and verified for their literature evidences. The hsa-miR-146a microRNA was differentially expressed at Padj < 0.05. The human host TB susceptibility genes TNFRSF10A, MSRA, GPR148, SLC37A3, PXK, PROK2, REV3L, PGM1, HIST3H2A, PLAC4, LETM2, EMP2 and were also differentially expressed at Padj < 0.05. We included all these genes and added the remaining 28 genes from the T2DMTB set and the rest of differentially expressed genes at Padj < 0.05 in STRING and obtained a well-connected network with high confidence score greater than 0.7. From this network we extracted the KEGG pathways at FDR < 0.05 and retained only Diabetes and TB pathways among the disease pathways. The network was simulated with BioNSi using gene expression data from GSE26168. The Necroptosis pathway showed the maximum perturbations in T2DM patients, followed by NOD-like receptor signaling, Toll-like receptor signaling, NF-kappa-B signaling and MAPK signaling. These pathways likely underlie susceptibility to TB in T2DM patients.

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P135 MAJOR GENE REGULATORS AFFECTED IN COLON AND BLOOD OF DEXTRAN SODIUM SULFATE ACUTE COLITIS MURINE MODEL

Inflammatory Bowel Diseases ◽

10.1093/ibd/zaa010.079 ◽

2020 ◽

Vol 26 (Supplement_1) ◽

pp. S32-S32

Author(s):

Reza Yarani ◽

Oana Palasca ◽

Nadezhda Tsankova Doncheva ◽

Christian Anthon ◽

Bartosz Pilecki ◽

...

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Intestinal Inflammation ◽

Major Gene ◽

Clinical Manifestations ◽

Ease Of Use ◽

Differentially Expressed ◽

In Vivo Studies ◽

P Value ◽

Sequencing Analysis

Abstract Background Dextran sulfate sodium (DSS) ulcerative colitis (UC) murine models have long been used for in vivo studies. DSS is a negatively charged polysaccharide with colitogenic properties. Although the mechanisms by which DSS induces intestinal inflammation are not fully understood, there are several good reasons why the DSS chemical colitis model for investigating the immunopathogenesis mechanism of UC is widely used. These include strong phenotypic clinical manifestations which emulate numerous clinical and histopathological features of human UC, ease of use, low mortality rate and high reproducibility. Here, by using high-throughput RNA sequencing analysis we set to investigate the major predicted gene regulators (GRs) affected by differentially expressed genes in the DSS treated UC model in order to obtain regulatory insights into the pathogenic mechanisms of UC development. Methods A DSS-induced mouse model of UC was established. Total RNA from colon tissue and blood of 3 healthy and 3 DSS-treated mice was extracted and sequenced by Illumina HiSeq 4000. Gene expression levels were obtained by mapping and quantification to the annotated mouse genome. Subsequently, differential gene expression analysis between DSS-treated and control mice both in colon and blood was performed. Ingenuity pathway analysis software (IPA®, Qiagen) was used to predict/identify major GRs affected by significantly differentially expressed genes (SDEGs, FC > |2|, p ≤0.05) in both colon and blood. Results Our analysis revealed how many and which major GRs are affected in DSS-treated mice and also the direction of change as compared to healthy (untreated) mice. In colon, 595 activated and 198 inhibited major GRs (p-value of overlap ≤0.05) in relation to ∼ 3180 SDEGs were identified, while in blood, we identified 205 activated and 62 inhibited GRs (in relation to ∼650 SDEGs). Colon and blood share 181 activated and 41 inhibited GRs. Identified GRs include transcription regulators, cytokines, transmembrane receptors and enzymes that mainly contribute to the development of inflammatory/immune responses. In colon and blood, the top 10 activated and inhibited regulators with the highest positive and negative activation z-score with target molecules as well as expression in the datasets are indicated in Figure 1a and 1b, respectively. Conclusion In this study, we analyzed linkage of GRs to SDEGs through coordinated expression and identified potential major regulators that have significant effect on UC pathogenic-related gene expression. These GRs seem to be the key regulators of transcriptomic changes induced by inflammation. These findings expand our molecular understanding of putative new targets that may be important in the pathophysiology of UC and provide biological insights into the observed expression changes between the UC and healthy controls.

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A BASELINE GENE EXPRESSION-BASED PROGNOSTIC FOR ANTI-TNFα THERAPY RESPONSE IN PATIENTS WITH INFLAMMATORY BOWEL DISEASE

Inflammatory Bowel Diseases ◽

10.1093/ibd/izaa347.019 ◽

2021 ◽

Vol 27 (Supplement_1) ◽

pp. S8-S8

Author(s):

Suraj Sakaram ◽

Yudong He ◽

Timothy Sweeney

Keyword(s):

Gene Expression ◽

Effect Size ◽

Search Algorithm ◽

Geometric Mean ◽

Differentially Expressed ◽

Expression Level ◽

P Value ◽

Predictive Test ◽

Forward Search ◽

Discriminatory Performance

Abstract Background Although anti-TNFα therapies have revolutionized the management and care of IBD, their administration and usage remain suboptimal because 1) over 50% of patients do not have a lasting therapeutic response, 2) they increase risk of infections, liver problems, arthritis, and lymphoma, and 3) they are expensive. With approximately 1.6 million people suffering from IBD in the US and global prevalence of IBD on the rise, a predictive test for anti-TNFα response would greatly improve the efficacy and cost-to-benefit ratio of these biologics. Methods We hypothesized that a multicohort analysis of the publicly available IBD gene expression datasets would yield a robust set of mRNAs for distinguishing anti-TNFα responders vs non-responders in the IBD patient population prior to treatment. We identified 5 datasets (n = 160) where whole-genome transcriptomic data was derived from colonic mucosal biopsies of IBD patients who were then subjected to anti-TNFα therapy and subsequently adjudicated for response. We used the MetaIntegrator framework which leverages a leave-one-study-out cross-validation technique in conjunction with effect size and FDR adjusted p-value to identify significant differentially expressed (DE) genes associated with a patient’s predisposition to a response outcome. DE genes were subjected to a greedy forward search to derive a parsimonious gene signature for a response score (geometric mean of the expression level for all positive mRNAs minus the geometric mean of the expression level of all negative mRNAs, multiplied by the ratio of counts of positive to negative genes). Area under the receiver operating characteristic curve (AUC) was subsequently calculated in a leave-one-study-out manner to assess discriminatory performance. Results We first identified 170 genes that were present in at least 40% of cohorts and significantly differentially expressed between responders and non-responders with effect size > 0.8 and q value < 0.1. A score based on these genes predicts responder vs non-responder across the 5 discovery cohorts with AUC of 0.82. Optimizing the variables with a greedy forward search algorithm allowed us to downselect to 7 genes from the set, and a score based on this parsimonious set of 7 genes improved the discriminatory performance to an AUC of 0.87. Choosing a high sensitivity (90%) for a rule-in scenario, the score had moderate specificity (60%); alternatively choosing a high specificity (90%) for a rule-out scenario, the score still had a good sensitivity (80%). Conclusions These initial findings suggest that there is a strong signal for predicting anti-TNFα response in colonic biopsies. In particular, we showed using the leave-one-study-out approach that a predictive signature using mRNA can be generalizable (works in independent cohorts). These initial results warrant further investigation.

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

Blood ◽

10.1182/blood.v104.11.3750.3750 ◽

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.

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Gene expression in blood reflects smoking exposure among cancer-free women in the Norwegian Women and Cancer (NOWAC) postgenome cohort

Scientific Reports ◽

10.1038/s41598-020-80158-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Nikita Baiju ◽

Torkjel M. Sandanger ◽

Pål Sætrom ◽

Therese H. Nøst

Keyword(s):

Gene Expression ◽

Whole Blood ◽

Smoking Status ◽

Expression Profiles ◽

Differentially Expressed ◽

P Value ◽

Smoking Exposure ◽

Former Smokers ◽

Never Smokers ◽

Free Women

AbstractActive smoking has been linked to modulated gene expression in blood. However, there is a need for a more thorough understanding of how quantitative measures of smoking exposure relate to differentially expressed genes (DEGs) in whole-blood among ever smokers. This study analysed microarray-based gene expression profiles from whole-blood samples according to smoking status and quantitative measures of smoking exposure among cancer-free women (n = 1708) in the Norwegian Women and Cancer postgenome cohort. When compared with never smokers and former smokers, current smokers had 911 and 1082 DEGs, respectively and their biological functions could indicate systemic impacts of smoking. LRRN3 was associated with smoking status with the lowest FDR-adjusted p-value. When never smokers and all former smokers were compared, no DEGs were observed, but LRRN3 was differentially expressed when never smokers were compared with former smokers who quit smoking ≤ 10 years ago. Further, LRRN3 was positively associated with smoking intensity, pack-years, and comprehensive smoking index score among current smokers; and negatively associated with time since cessation among former smokers. Consequently, LRRN3 expression in whole-blood is a molecular signal of smoking exposure that could supplant self-reported smoking data in further research targeting blood-based markers related to the health effects of smoking.

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Sexually Dimorphic Transcriptomic Changes of Developing Fetal Brain Reveal Signaling Pathways and Marker Genes of Brain Cells in Domestic Pigs

Cells ◽

10.3390/cells10092439 ◽

2021 ◽

Vol 10 (9) ◽

pp. 2439

Author(s):

Monica Strawn ◽

Joao G. N. Moraes ◽

Timothy J. Safranski ◽

Susanta K. Behura

Keyword(s):

Gene Expression ◽

Brain Development ◽

Signaling Pathways ◽

Expression Patterns ◽

Fetal Brain ◽

Differentially Expressed ◽

Marker Genes ◽

Pathway Enrichment Analysis ◽

Female Brain ◽

Transcriptomic Changes

In this study, transcriptomic changes of the developing brain of pig fetuses of both sexes were investigated on gestation days (GD) 45, 60 and 90. Pig fetal brain grows rapidly around GD60. Consequently, gene expression of the fetal brain was distinctly different on GD90 compared to that of GD45 and GD60. In addition, varying numbers of differentially expressed genes (DEGs) were identified in the male brain compared to the female brain during development. The sex of adjacent fetuses also influenced gene expression of the fetal brain. Extensive changes in gene expression at the exon-level were observed during brain development. Pathway enrichment analysis showed that the ionotropic glutamate receptor pathway and p53 pathway were enriched in the female brain, whereas specific receptor-mediated signaling pathways were enriched in the male brain. Marker genes of neurons and astrocytes were significantly differentially expressed between male and female brains during development. Furthermore, comparative analysis of gene expression patterns between fetal brain and placenta suggested that genes related to ion transportation may play a key role in the regulation of the brain-placental axis in pig. Collectively, the study suggests potential application of pig models to better understand influence of fetal sex on brain development.

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Abstract TP166: Age-Associated Transcriptomic Alterations in Patients With Ischemic Stroke

Stroke ◽

10.1161/str.51.suppl_1.tp166 ◽

2020 ◽

Vol 51 (Suppl_1) ◽

Author(s):

Gina Sykes ◽

Yusra Batool ◽

Joseph Kamtchum Tatuene ◽

Sarah Zehnder ◽

Glen C Jickling

Keyword(s):

Gene Expression ◽

Functional Analysis ◽

Ischemic Stroke ◽

Immune System ◽

B Cell ◽

Differentially Expressed Genes ◽

Hemorrhagic Transformation ◽

Differentially Expressed ◽

P Value ◽

Humoral Immune

Introduction: Immune system dysregulation occurs with age. This includes an increase in inflammation, and immunosenescence, the inability to efficiently respond to new immune challenges. These changes are evident in various diseases but have yet to be evaluated in a population with ischemic stroke. Age is an important factor in stroke, contributing to stroke risk, outcome and risk of hemorrhagic transformation. This study aimed to assess the changes that occur with age in the leukocyte gene expression of patients with ischemic stroke. Methods: Two cohorts of acute ischemic stroke patients were analyzed; cohort 1 (n=94) and cohort 2 (n=79). RNA was isolated from PAXgene tubes and processed on Affymetrix microarrays. Differentially expressed genes associated with age quartiles were identified by ANCOVA, adjusted for sex and batch. Functional analysis identified age-associated pathways. Differentially expressed genes were compared with previous non-stroke aging studies in whole blood. Results: There were 61 and 442 age-associated genes in cohorts 1 and 2 respectively (FDR-corrected p<0.05, partial correlation coefficient ≥ |0.3|). Nineteen genes, including CR2, CCR6 and CXCR5 , were found in common and decreased with age among both cohorts (max-log10(p value) = 17). Functional analysis of the 61 and 442 genes revealed with advancing age there is a change in the humoral immune system, including antibody production and B cell proliferation. When compared to aging gene expression studies in controls, 52% of age-associated genes in cohort 1 and 31% of cohort 2 age-associated genes overlapped with those found in controls, and 16 of the 19 common genes to both cohorts overlapped in controls (max-log10(p value) = 15). Conclusion: In patients with acute stroke there is a change in leukocyte gene expression with advancing age. Changes included a shift in humoral immune response with a potentially impaired B cell response. While many of the age-associated alterations in gene expression present in stroke are similar to non-stroke controls, these changes warrant further investigation for their impact on stroke outcome and risk.

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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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