scholarly journals Identification of hub-genes, lncRNAs, and skin cancer inducer genes through meta-analysis of Hidradenitis Suppurativa disease transcriptome data.

2021 ◽  
Author(s):  
Mehrdad Shahbazi ◽  
Nikta Ziaei
Keyword(s):  
Gene Ontology ◽  
Skin Cancer ◽  
Hidradenitis Suppurativa ◽  
Expression Level ◽  
Formyl Peptide Receptor ◽  
Molecular Response ◽  
Transcriptome Data ◽  
Inhibitory Effects ◽  
Hub Genes ◽  
Chemokine Ligand

Abstract This research is aimed to explore the molecular response of the skin cells to Hidradenitis Suppurativa (HS). Microarray transcriptome data for patients with HS, merged and employed to identify the differentially expressed genes (DEGs), gene ontology (GO), and long non-coding RNAs (lncRNAs). A protein-protein interaction network, and consequently, a co-expression network, was constructed for the essential genes. The key genes' clinical relevance was also established by survival analysis, relative expression level, immunohistochemistry, and immune infiltration correlation analysis. Finally, potential herbal ingredients with inhibitory effects on cancer inducer proteins were characterized using the Traditional Chinese Medicine (TCMD) database. The chemokine signaling pathway was the gene ontology of the most significant cluster found by clusterONE. Myocardial Infarction Associated Transcript (MIAT) and RNA Polymerase II Subunit J4, Pseudogene (POLR2J4) are the predicted lncRNAs for up-and down-regulated genes. Interleukin 6 (IL6), Formyl Peptide Receptor 2 (FPR2), C-X-C Motif Chemokine Ligand 10 (CXCL10), C-C Motif Chemokine Receptor 7 (CCR7), and C-C Motif Chemokine Ligand 5 (CCL5) genes were predicted as hub-genes. Tryptophan 2,3-Dioxygenase (TDO2), Serpin Family B Member 4 (SERPINB4), and Matrix Metallopeptidase 3 (MMP3) were demonstrated to be potential cancer inducers due to their high expression level in HS disease. These genes also were positively correlated with dendritic cells, T cell CD4+, monocytes, and neutrophils in the skin cancer microenvironment. Piceatannol, Salicylic acid, and magnolol herbal ingredients were predicted as potential compounds with inhibitory effects on SERPIN B4, MMP3, and TDO2, respectively. The output of the present study will aid in a better understanding of the HS disease and consequent cancer induction mechanism.

scholarly journals Bioinformatics study on genes related to a high-risk postoperative recurrence of lung adenocarcinoma

2021 ◽  
Vol 104 (3) ◽  
pp. 003685042110180
Author(s):  
Xiao Lin ◽  
Meng Zhou ◽  
Zehong Xu ◽  
Yusheng Chen ◽  
Fan Lin
Keyword(s):  
Cell Cycle ◽  
Gene Ontology ◽  
High Risk ◽  
Lung Adenocarcinoma ◽  
Candidate Genes ◽  
Postoperative Recurrence ◽  
High Expression ◽  
Ppi Network ◽  
Hub Genes ◽  
Expression Levels

In this study, we aimed to screen out genes associated with a high risk of postoperative recurrence of lung adenocarcinoma and investigate the possible mechanisms of the involvement of these genes in the recurrence of lung adenocarcinoma. We identify Hub genes and verify the expression levels and prognostic roles of these genes. Datasets of GSE40791, GSE31210, and GSE30219 were obtained from the Gene Expression Omnibus database. Enrichment analysis of gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed for the screened candidate genes using the DAVID database. Then, we performed protein–protein interaction (PPI) network analysis through the database STRING. Hub genes were screened out using Cytoscape software, and their expression levels were determined by the GEPIA database. Finally, we assessed the relationships of Hub genes expression levels and the time of survival. Forty-five candidate genes related to a high-risk of lung adenocarcinoma recurrence were screened out. Gene ontology analysis showed that these genes were enriched in the mitotic spindle assembly checkpoint, mitotic sister chromosome segregation, G2/M-phase transition of the mitotic cell cycle, and ATP binding, etc. KEGG analysis showed that these genes were involved predominantly in the cell cycle, p53 signaling pathway, and oocyte meiosis. We screened out the top ten Hub genes related to high expression of lung adenocarcinoma from the PPI network. The high expression levels of eight genes (TOP2A, HMMR, MELK, MAD2L1, BUB1B, BUB1, RRM2, and CCNA2) were related to short recurrence-free survival and they can be used as biomarkers for high risk of lung adenocarcinoma recurrence. This study screened out eight genes associated with a high risk of lung adenocarcinoma recurrence, which might provide novel insights into researching the recurrence mechanisms of lung adenocarcinoma as well as into the selection of targets in the treatment of the disease.

scholarly journals Comparison of gene expression in the red imported fire ant (Solenopsis invicta) under different temperature conditions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mohammad Vatanparast ◽  
Robert T. Puckett ◽  
Deuk-Soo Choi ◽  
Youngjin Park
Keyword(s):  
Gene Expression ◽  
Gene Ontology ◽  
High Temperature ◽  
Temperature Stress ◽  
Solenopsis Invicta ◽  
Expression Profiles ◽  
Fire Ant ◽  
Molecular Response ◽  
Red Imported Fire Ant ◽  
Imported Fire Ant

AbstractThe red imported fire ant (RIFA), Solenopsis invicta Buren is native to South America and is known as a global problematic invasive species. This study focused on the molecular response of RIFA by comparing gene expression profiles after exposing ants to low (10 °C) and high (40 °C) temperature stress and comparing them to untreated controls (30 °C). A total of 99,085 unigenes (the clustered non-redundant transcripts that are filtered from the longest assembled contigs) were obtained, of which 19,154 were annotated with gene descriptions, gene ontology terms, and metabolic pathways. 86 gene ontology (GO) functional sub-groups and 23 EggNOG terms resulted. Differentially expressed genes (DEGs) with log2FC ≥ 10 were screened and were compared at different temperatures. We found 203, 48, and 66 specific DEGs co-regulated at 10, 20, and 40 °C. Comparing transcriptome profiles for differential gene expression resulted in various DE genes, including cytochrome P450, NADH dehydrogenase subunit 1, cuticle protein and heat shock protein (HSP), which have previously been reported to be involved in cold and high temperature resistance. GO analysis revealed that antioxidant activity is up-regulated under high temperature stress. We verified the RNA-seq data by qPCR on 20 up- and down-regulated DEGs. These findings provide a basis for future understanding of the adaptation mechanisms of RIFA and the molecular mechanisms underlying the response to low and high temperatures.

The Screening and Identification of Key Biomarkers in Adrenocortical Carcinoma: Evidence from a Bioinformatics Analysis

2022 ◽  
Vol 12 (3) ◽  
pp. 523-532
Author(s):  
Xin Yan ◽  
Chunfeng Liang ◽  
Xinghuan Liang ◽  
Li Li ◽  
Zhenxing Huang ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Gene Ontology ◽  
Protein Interaction ◽  
Adrenocortical Carcinoma ◽  
Gene Expression Omnibus ◽  
Heparin Binding ◽  
Ppi Network ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Upregulated Genes

<sec> <title>Objective:</title> This study aimed to identify the potential key genes associated with the progression and prognosis of adrenocortical carcinoma (ACC). </sec> <sec> <title>Methods:</title> Differentially expressed genes (DEGs) in ACC cells and normal adrenocortical cells were assessed by microarray from the Gene Expression Omnibus database. The biological functions of the classified DEGs were examined by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses and a protein–protein interaction (PPI) network was mapped using Cytoscape software. MCODE software was also used for the module analysis and then 4 algorithms of cytohubba software were used to screen hub genes. The overall survival (OS) examination of the hub genes was then performed by the ualcan online tool. </sec> <sec> <title>Results:</title> Two GSEs (GSE12368, GSE33371) were downloaded from GEO including 18 and 43 cases, respectively. One hundred and sixty-nine DEGs were identified, including 57 upregulated genes and 112 downregulated genes. The Gene Ontology (GO) analyses showed that the upregulated genes were significantly enriched in the mitotic cytokines is, nucleus and ATP binding, while the downregulated genes were involved in the positive regulation of cardiac muscle contraction, extracellular space, and heparin-binding (P < 0.05). The Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) pathway examination showed significant pathways including the cell cycle and the complement and coagulation cascades. The protein– protein interaction (PPI) network consisted of 162 nodes and 847 edges, including mitotic nuclear division, cytoplasmic, protein kinase binding, and cell cycle. All 4 identified hub genes (FOXM1, UBE2C, KIF11, and NDC80) were associated with the prognosis of adrenocortical carcinoma (ACC) by survival analysis. </sec> <sec> <title>Conclusions:</title> The present study offered insights into the molecular mechanism of adrenocortical carcinoma (ACC) that may be beneficial in further analyses. </sec>

Morin Exerts Anti-Diabetic Effects in Human HepG2 Cells Via Down-Regulation of miR-29a

2018 ◽  
Vol 127 (09) ◽  
pp. 615-622 ◽  
Author(s):  
Toktam Razavi ◽  
Shideh Montasser Kouhsari ◽  
Khalil Abnous
Keyword(s):  
Insulin Signaling ◽  
High Glucose ◽  
Hepg2 Cells ◽  
Target Genes ◽  
Expression Level ◽  
Inhibitory Effects ◽  
Down Regulation ◽  
Insulin Mimetic ◽  
Important Regulator ◽  
First Time

Abstract Diabetes mellitus is a complex metabolic disease around the world that is characterized by hyperglycemia resulting from impaired insulin secretion, insulin action, or both. MicroRNA-29a is an important regulator of insulin signaling and gluconeogenesis pathways through IRS2, PI3K and PEPCK expressions which up regulates in Diabetes. Morin is a substantial bioflavonoid which has insulin mimetic effect, and interacting with nucleic acids and proteins. In this study HepG2 cells, were exposed to high glucose to induce diabetic condition. We have determined whether high glucose stimulation might promotes miR-29a expression level in HepG2 cells and subsequently evaluated the Morin treatment effects on this state. In HepG2 cells, high glucose increases miR-29a expression level and decreases its target genes, IRS2 and PI3K expression, and increases associated downstream gene in gluconeogenic pathway, PEPCK. Morin treatment down regulates miR-29a expression level and improves insulin signaling and glucose metabolism. To confirm the inhibitory effects of Morin on miR-29a, we have transfected cells with mimic and inhibitor-miR-29a. This study for the first time identifies that Morin improves diabetic condition through down regulation of the miR-29a level, and suggest that this new inhibitor of miR-29a may be a useful biomedicine to treat diabetes.

scholarly journals COL1A1 is a prognostic biomarker and correlated with immune infiltrates in lung cancer

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11145
Author(s):  
Qishun Geng ◽  
Zhibo Shen ◽  
Lifeng Li ◽  
Jie Zhao
Keyword(s):  
Lung Cancer ◽  
T Cells ◽  
Dendritic Cell ◽  
Cd4 T Cells ◽  
Malignant Tumors ◽  
Functional Enrichment ◽  
Expression Level ◽  
Normal Lung ◽  
Hub Genes ◽  
Clinical Prognosis

Objective Lung cancer (LC) is one of the top ten malignant tumors and the first leading cause of cancer-related death among both men and women worldwide. It is imperative to identify immune-related biomarkers for early LC diagnosis and treatment. Methods Three Gene Expression Omnibus (GEO) datasets were selected to acquire the differentially expressed genes(DEGs) between LC and normal lung samples through GEO2R tools of NCBI. To identify hub genes, the DEGs were performed functional enrichment analysis, the protein–protein interaction (PPI) network construction, and Lasso regression. Then, a nomogram was constructed to predict the prognosis of patients with carcinoma based on hub genes. We further evaluated the influence of COL1A1 on clinical prognosis using GSE3141, GSE31210, and TCGA database. Also, the correlations between COL1A1 and cancer immune infiltrates and the B7-CD28 family was investigated via TIMER and GEPIA. Further analysis of immunohistochemistry shown that the COL1A1 expression level is positively correlated with CD276 expression level. Results By difference analysis, there were 340 DEGs between LC and normal lung samples. Then, we picked out seven hub genes, which were identified as components of the risk signature to divide LC into low and high-risk groups. Among them, the expression of COL1A1 is highly correlated with overall survival(OS) and progression-free survival (PFS) (p < 0.05). Importantly, there is a moderate to strong positive relationships between COL1A1 expression level and infiltration level of CD4+ T cells, Macrophage, Neutrophil, and Dendritic cell, as well as CD276 expression level. Conclusion These findings suggest that COL1A1 is correlated with prognosis and immune infiltrating levels, including CD4+ T cells, Macrophage, Neutrophil, and Dendritic cell, as well as CD276 expression level, indicating COL1A1 can be a potential immunity-related biomarker and therapeutic target in LC.

Integrated Gene Expression Profiling Analysis Reveals Potential Molecular Mechanisms and Candidate Biomarkers for Early Risk Stratification and Prediction of STEMI and Post-STEMI Heart Failure Patients

2020 ◽  
Author(s):  
Jing Xu ◽  
Yuejing Yang
Keyword(s):  
Machine Learning ◽  
Gene Ontology ◽  
Risk Stratification ◽  
Molecular Mechanisms ◽  
Interaction Network ◽  
Hub Genes ◽  
Machine Learning Model ◽  
Transcriptomic Signature ◽  
Logistic Regression Algorithm ◽  
Geo Database

Abstract Objective To explore the molecular mechanism and search for the candidate biomarkers with predictive and prognostic potentiality that detectable in the whole blood of STEMI patients and post-STEMI HF patients.Methods In this study, we downloaded GSE60993, GSE61144, GSE66360, and GSE59867 datasets from the NCBI-GEO database. Differentially expressed genes (DEGs) of the datasets were investigated using R. Gene ontology and pathway enrichment were performed via ClueGO, CluePedia, and DAVID database. Protein interaction network was constructed via STRING. Enriched hub genes were analyzed by Cytoscape software. LASSO logistic regression algorithm and ROC analysis were performed to build machine learning models for predicting STEMI. Hub genes for further validated in post-STEMI HF patients from GSE59867.Results We identified 90 up-regulated DEGs and 9 down-regulated DEGs convergence in the three datasets (|log2FC| ≥ 0.8 and adjusted p value < 0.05). They were mainly enriched in Gene Ontology terms relating to cytokine secretion, pattern recognition receptors signaling pathway, and immune cells activation. A cluster of 8 genes including ITGAM, CLEC4D, SLC2A3, BST1, MCEMP1, PLAUR, GPR97, and MMP25 was found to be significant. A machine learning model built by SLC2A3, CLEC4D, GPR97, PLAUR, and BST1 exerted great value for STEMI prediction. Besides, ITGAM and BST1 might be candidate prognostic biomarkers for post-STEMI HF.Conclusions We re-analyzed the integrated transcriptomic signature of STEMI patients showing predictive potentiality and revealed new insights and specific prospective biomarkers for STEMI risk stratification and HF development.

Transcriptome Signatures Reveal Candidate Key Genes in the Peripheral Blood Mononuclear Cells of Patients With Coronary Artery Disease

2020 ◽  
Author(s):  
Vijayakrishna Kolur ◽  
Basavaraj Vastrad ◽  
Chanabasayya Vastrad ◽  
Iranna Kotturshetti ◽  
Anandkumar Tengli
Keyword(s):  
Coronary Artery Disease ◽  
Gene Ontology ◽  
Coronary Artery ◽  
Regulatory Network ◽  
Target Gene ◽  
Enrichment Analysis ◽  
Hub Genes ◽  
Go Enrichment ◽  
Artery Disease ◽  
Go Enrichment Analysis

Abstract BackgroundCoronary artery disease (CAD) is one of the most common disorders in the cardiovascular system. This study aims to explore potential signaling pathways and important biomarkers that drive CAD development. MethodsThe CAD GEO Dataset GSE113079 was featured to screen differentially expressed genes (DEGs). The pathway and Gene Ontology (GO) enrichment analysis of DEGs were analyzed using the ToppGene. We screened hub and target genes from protein-protein interaction (PPI) networks, target gene - miRNA regulatory network and target gene - TF regulatory network, and Cytoscape software. Validations of hub genes were performed to evaluate their potential prognostic and diagnostic value for CAD. Results1,036 DEGs were captured according to screening criteria (525upregulated genes and 511downregulated genes). Pathway and Gene Ontology (GO) enrichment analysis of DEGs revealed that these up and down regulated genes are mainly enriched in thyronamine and iodothyronamine metabolism, cytokine-cytokine receptor interaction, nervous system process, cell cycle and nuclear membrane. Hub genes were validated to find out potential prognostic biomarkers, diagnostic biomarkers and novel therapeutic target for CAD. ConclusionsIn summary, our findings discovered pivotal gene expression signatures and signaling pathways in the progression of CAD. CAPN13, ACTBL2, ERBB3, GATA4, GNB4, NOTCH2, EXOSC10, RNF2, PSMA1 and PRKAA1 might contribute to the progression of CAD, which could have potential as biomarkers or therapeutic targets for CAD.

scholarly journals Bioinformatics analysis reveals novel hub gene pathways associated with IgA nephropathy

2020 ◽  
Vol 25 (1) ◽  
Author(s):  
Xue Jiang ◽  
Zhijie Xu ◽  
Yuanyuan Du ◽  
Hongyu Chen
Keyword(s):  
Gene Ontology ◽  
Inflammatory Response ◽  
Molecular Mechanism ◽  
Bioinformatics Analysis ◽  
Functional Enrichment ◽  
Control Group ◽  
Integrin Subunit ◽  
Ppi Network ◽  
Hub Genes ◽  
Ppi Networks

Abstract Background Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulopathy worldwide. However, the molecular events underlying IgAN remain to be fully elucidated. This study aimed to identify novel biomarkers of IgAN through bioinformatics analysis and elucidate the possible molecular mechanism. Methods Based on the microarray datasets GSE93798 and GSE37460 downloaded from the Gene Expression Omnibus database, the differentially expressed genes (DEGs) between IgAN samples and normal controls were identified. Using the DEGs, we further performed a series of functional enrichment analyses. Protein–protein interaction (PPI) networks of the DEGs were constructed using the STRING online search tool and were visualized using Cytoscape. Next, hub genes were identified and the most important module among the DEGs, Biological Networks Gene Ontology tool (BiNGO), was used to elucidate the molecular mechanism of IgAN. Results In total, 148 DEGs were identified, comprising 53 upregulated genes and 95 downregulated genes. Gene Ontology (GO) analysis indicated that the DEGs for IgAN were mainly enriched in extracellular exosome, region and space, fibroblast growth factor stimulus, inflammatory response, and innate immunity. Module analysis showed that genes in the top 1 significant module of the PPI network were mainly associated with innate immune response, integrin-mediated signaling pathway and inflammatory response. The top 10 hub genes were constructed in the PPI network, which could well distinguish the IgAN and control group in monocyte and tissue samples. We finally identified the integrin subunit beta 2 (ITGB2) and Fc fragment of IgE receptor Ig (FCER1G) genes that may play important roles in the development of IgAN. Conclusions We identified key genes along with the pathways that were most closely related to IgAN initiation and progression. Our results provide a more detailed molecular mechanism for the development of IgAN and novel candidate gene targets of IgAN.

scholarly journals SO004IDENTIFICATION OF HUB GENES, FOCUSED ON CHEMOKINES AND CHEMOKINE RECEPTORS, ASSOCIATED WITH THE DECLINE OF RENAL FUCTION OF DIABETIC KIDNEY DISEASE BY WEIGHTED GENE CO-EXPRESSION NETWORK ANALYSIS

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Songtao Feng ◽  
Bicheng Liu ◽  
Linli Lv ◽  
Gao Yueming ◽  
Di Yin ◽  
...  
Keyword(s):  
Renal Function ◽  
Network Analysis ◽  
Kidney Disease ◽  
T Cell Activation ◽  
Chemokine Receptors ◽  
Diabetic Kidney Disease ◽  
Expression Level ◽  
Hub Genes ◽  
Diabetic Kidney ◽  
Gene Modules

Abstract Background and Aims The fact that activation of the innate immune system and chronic inflammation are closely involved in the pathogenesis of diabetic Kidney disease (DKD). Recent studies have suggested the inflammatory process plays a crucial role in the progression of DKD. Identifying novel inflammatory molecules closely related to the decline of renal function is of significance in diagnosing and predicting the progression of DKD. The weighted gene co-expression network analysis (WGCNA) algorithm represents a novel systems biology method that provide the approach of association between gene modules and clinical traits to find the genes involvement into the certain phenotypic trait. The goal of this study was to identify hub genes and their roles in DKD from the gene sets associated with the decline of renal function by WGCNA. Method The Gene Expression Omnibus (GEO) database and “Nephroseq” website were searched and transcriptome study from DN biopsies with well-established clinical phenotypic data were selected for analysis. Next, we constructed a weighted gene co-expression network and identified modules negatively correlated with eGFR by WGCNA in the data of glomerular tissue. Functional annotations of the genes in modules negatively correlated with eGFR were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Through protein-protein interaction (PPI) analysis and hub gene screening, the hub genes were obtained. Furthermore, we compared the expression level of hub genes between DKD and normal control and drew ROC curves to determine the diagnosis value to DKD of these genes. Results The microarray-based expression datasets GSE30528 were screened out for analysis, which included glomeruli tissue of 9 cases of DKD and 13 cases of control. This microarray platform represented the transcriptome profile of 12411 well-characterized genes. Using WGCNA, a total of 19 gene modules were identified. Then module eigengene were analyzed for correlation with clinical traits of age, sex, ethnicity and eGFR and the “MEhoneydew1” module showed negative associated with eGFR (r=-0.58). GO functional annotation showed that these 551 genes in the “MEhoneydew1” module mainly enriched in the T cell activation. KEGG annotation showed mainly enriched in chemokine signaling pathway. Except for C3, top 10 hub genes, CCR5, CXCR4, CCR7, CCL5, CXCL8, CCR2, CCR1, CX3CR1, C3AR1 and C3, are all members of chemokines or chemokine receptors. Furthermore, we compared the expression level of these 9 genes between DKD and control, and found that all of these 9 genes increased in the DKD group, and the differences of 6 genes, CCR5, CCR7, CCL5, CCR2, CCR1, C3AR1, were of statistical significance. Linear correlation analysis showed that the expression of these 6 genes was negatively correlated with eGFR, and the ROC curve showed that the area under the curve could reach 0.812∼1.0. Conclusion We identified a panel of 6 hub genes focused on chemokines and chemokine receptors critical for decline of renal function of DKD using WGCNA. These genes may serve as biomarkers for diagnosis/prognosis and as putative novel therapeutic targets for DKD.

The Musashi 2 mRNA Expression in the Course of CML.

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 2552-2552
Author(s):  
Sylvie Nadvornikova ◽  
Marketa Zackova ◽  
Tereza Lopotova ◽  
Hana Klamova ◽  
Jana Moravcova
Keyword(s):  
Myeloid Leukemia ◽  
Rna Binding ◽  
Blast Crisis ◽  
Mrna Level ◽  
Mrna Translation ◽  
Transcript Level ◽  
Response To Therapy ◽  
Expression Level ◽  
Molecular Response ◽  
Clinical Prognosis

Abstract Abstract 2552 The Musashi (MSI) gene family members, MSI1 and MSI2, represent an evolutionarily conserved family of RNA-binding proteins that regulate mRNA translation through binding in their N-termini. High levels of MSI2 protein are associated with increased cell proliferation, decreased cell maturation, more aggressive hematologic malignancy diseases and worse clinical prognosis. Recently obtained data pointed to MSI2 playing an important role in acute myeloid leukemia (AML) and in deadly blast crisis of chronic myeloid leukemia (CML) (Ito et al. 2010 Nature 5; 466). In this study we screened the level of MSI2 mRNA in 49 patients in different phases of CML and with different response to therapy – 18 patients at diagnosis (DG), 5 in major molecular response (MMR), 4 in complete molecular response (CMR), 2 after bone marrow transplantation (BMT), 10 in hematology relaps (HR), 6 in accelerrated phase (AP), and 4 in blast crisis (BC), and in 6 healthy donors. The level of MSI2 mRNA was quantified by real-time reverse-transcriptase-polymerase chain reaction using in-house designed specific primers and TaqMan probe and normalized to B2M endogenous control. Expression ratios were calculated by ΔΔCt method, and the differences between groups were statistically evaluated using Mann Whitney test. We detected MSI2 expression in all samples. The median expression of mRNA MSI2 in patients at DG was 1,43 (0,33–3,28), in MMR 0,52 (0,20–0,62), in CMR 0,37 (0,30–0,63), after BMT 1,28 (1,02–1,54), in HR 0,41 (0,16–0,58), in AP 3,78 (1,94–13,69), in BC 15,17 (2,61–28,15). MSI2 expression was statistically up-regulated in patients in advanced phases of CML (AP, BC) when compared with patients in CP (P<0.0001). The difference between patients in DG and remaining patients in CP was also statistically significant (P= 0,0006). No correlation of MSI2 expression level in DG patients with their responsiveness to treatment, BCR-ABL transcript level or survival was found. No significant differences were observed among groups of patients in MMR, CMR, HR, and after BMT. In addition, in order to check whether MSI2 expression level can serve as a marker of CML progression we also retrospectively screened kinetics of MSI2 transcript in 5 CML patients monitored on average 27 months (18–48). During this period, 3 patients developed HR, 1 patient AP and 1 BC. In BC patient the MSI2 transcript level increased with progression of CML in accordance with the increase of leucocytes and BCR-ABL transcript level. In 1 patient with a rising AP BCR-ABL levels remained constant compared to sevenfold increase of the MSI2 transcript level. On the other hand in HR patients we detected a constant or even decreasing level of MSI2 transcript regardless of the increase of leucocytes and BCR-ABL. In summary, our results confirm the association of high MSI2 mRNA level with advanced phases of CML and indicate that increase of MSI2 mRNA level may serve as a valuable marker of advanced phases of CML. In particular for CML patients with constantly high level of BCR-ABL mRNA the monitoring of MSI2 level can be important tool for early recognition of CML progression. Potential contributions of MSI2 to leukemic pathogenesis and its regulation in CML progression remain unknown. Grant support: NT/12392-4 IGA MZ-CR. Disclosures: No relevant conflicts of interest to declare.

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