Expression profiles of metamorphosis-related genes during natural transformations in tadpoles of wild Wood Frogs (Lithobates sylvaticus)

2012 ◽  
Vol 90 (9) ◽  
pp. 1059-1071 ◽  
Author(s):  
Laia Navarro-Martín ◽  
Chantal Lanctôt ◽  
Christopher Edge ◽  
Jeff Houlahan ◽  
Vance L. Trudeau
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Rana Sylvatica ◽  
Fold Increase ◽  
Gonadal Development ◽  
Specific Expression ◽  
Wood Frogs ◽  
Lithobates Sylvaticus ◽  
Expression Levels ◽  
Gene Expression Levels

Numerous studies using laboratory-reared tadpoles have shown the importance of thyroid hormones (TH), thyroid receptors (TR), and deiodinase (Dio) enzymes during anuran metamorphosis. Our study focuses on the analysis of thyroid-related genes in tadpoles of wild Wood Frogs ( Lithobates sylvaticus (LeConte, 1825); also known as Rana sylvatica (Cope, 1889)) during metamorphosis. Results showed that, in concordance with laboratory-reared studies, thyroid receptor beta (trb) gene expression profiles presented the most marked changes. At climax and compared with premetamorphic stages, brains, tails, and gonad–mesonephros complex (GMC) tissues increased trb expression levels 5-, 21-, and 41-fold, respectively (p < 0.05). In addition, gene expression levels of brain deiodinase type II and III showed opposite trends, where 3-fold decrease and 10-fold increase were, respectively, found. This finding supports the idea that thyroid hormone, as it has been demonstrated in laboratory-reared tadpoles, is also involved in natural metamorphosis in wild tadpoles. Interestingly, and contrary to our predictions, we observed that whole brain corticotropin-releasing factor (crf) and crf receptor 1 (crfr1) gene expression levels significantly decrease through metamorphosis in wild L. sylvaticus tadpoles. Further analyses are required to determine if a role of TH in the timing of anuran gonadal development exists, as well as the importance of cell-specific and tissue-specific expression of crf and crfr1 to metamorphosis.

scholarly journals Evaluation of TGF-Beta 2 and VEGFα Gene Expression Levels in Epiretinal Membranes and Internal Limiting Membranes in the Course of Retinal Detachments, Proliferative Diabetic Retinopathy, Macular Holes, and Idiopathic Epiretinal Membranes

2018 ◽  
Vol 2018 ◽  
pp. 1-6
Author(s):  
Joanna Stafiej ◽  
Karolina Kaźmierczak ◽  
Katarzyna Linkowska ◽  
Paweł Żuchowski ◽  
Tomasz Grzybowski ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Rna Extraction ◽  
Retinal Diseases ◽  
Epiretinal Membranes ◽  
Expression Levels ◽  
Macular Holes ◽  
Retinal Disorders ◽  
Pars Plana ◽  
Gene Expression Levels

Purpose. To evaluate the expression profiles of the VEGFα and TGFβ in the ERMs and ILMs in retinal disorders. Methods. In this nonrandomized prospective study, 75 patients (34 females and 41 males) referred to pars plana vitrectomy (PPV) due to different retinal diseases were enrolled to the study. The samples of ERMs and ILMs collected during PPV were immediately put in TRIzol® Reagent (Life Technologies, USA) and stored at −70°C until RNA extraction. Gene expression analysis was done with TaqMan® Gene Expression Assays (Applied Biosystems, USA) following the manufacturer’s instructions. Results. The gene expression levels of VEGFα as well as of TGFβ2 were significantly higher in ERMs than in ILMs in all studied groups. The level of TGFβ2 expression exhibits a significantly lower values in iERMs as compared with the RRD group (p=0.043). There were differences in TGFβ2 expression in ILM in groups studied: DR versus RRD, p=0.003; DR versus iERM, p=0,047; and iERM versus RRD, p=0.004. Conclusions. Our results revealed that factors associated with angiogenesis and wound healing processes in eyes with RRD, PDR, iERM, and MH were more upregulated in ERMs than in ILMs. This may indicate that ILM is not responsible for reproliferation and its peeling should be avoided in routine PPV.

Identification of Aberrantly Regulated Genes through Comparison of Genome-Wide Expression Profiles and Karyotype in Hyperdiploid >50 Chromosomes Pediatric Acute Lymphoblastic Leukemia.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 420-420
Author(s):  
Christian Flotho ◽  
Susana C. Raimondi ◽  
James R. Downing
Keyword(s):  
Gene Expression ◽  
Copy Number ◽  
Expression Profiles ◽  
Chromosome 21 ◽  
Small Subset ◽  
Specific Gene ◽  
Expression Levels ◽  
Number Of Genes ◽  
The Mean ◽  
Gene Expression Levels

Abstract We have demonstrated that expression profiling of leukemic blasts can accurately identify the known prognostic subtypes of ALL, including T-ALL, E2A-PBX1, TEL-AML1, MLL rearrangements, BCR-ABL, and hyperdiploid &gt;50 chromosomes (HD&gt;50). Interestingly, almost 70% of the genes that defined HD&gt;50 ALL localized to chromosome 21 or X. To further explore the relationship between gene expression and chromosome dosage, we compared the expression profiles obtained using the Affymetrix U133A&B microarrays of 17 HD&gt;50 ALLs to 78 diploid or pseudodiploid ALLs. Our analysis demonstrated that the average expression level for all genes on a chromosome could be used to predict chromosome copy numbers. Specifically, the copy number for each chromosome calculated by gene expression profiling predicted the numerical chromosomal abnormalities detected by standard cytogenetics. For chromosomes that were trisomic in HD&gt;50 ALL, the mean chromosome-specific gene expression level was increased approximately 1.5-fold compared to that observed in diploid or pseudodiploid ALL cases. Similarly, for chromosome 21 and X, the mean chromosome-specific gene expression levels were increased approximately 2-fold, consistent with a duplication of the active X chromosome and tetrasomy of chromosome 21, a finding verified by standard cytogenetics in &gt;90% of the HD&gt;50 cases. These finding indicate that the aberrant gene expression levels seen in HD&gt;50 ALL primarily reflect gene dosages. Importantly, we did not observe any clustering of aberrantly expressed genes across the duplicated chromosomes, making regional gain or loss of genomic material unlikely. Paradoxically, however, a more detailed analysis revealed a small but statistically significant number of genes on the trisomic/tetrasomic chromosomes whose expression levels were markedly reduced when compared to that seen in diploid or pseudodiploid leukemic samples. Using the Statistical Analysis of Microarrays (SAM) algorithm we identified 20 genes whose expression was reduced &gt;2-fold despite having an increase in copy number. Interestingly, included within this group are several known tumor suppressors, including AKAP12, which is specifically silenced by methylation in fos-transformed cells, and IGF2R and IGFBP7, negative regulators of insulin-like growth factor signaling. In addition to the silencing of a small subset of genes, we also identified 21 genes on these chromosomes whose expression levels were markedly higher (&gt;3-fold) than would be predicted solely based on copy number. Although the mechanism responsible for their increased expression remains unknown, included in this group are four genes involved in signal transduction (IL3RA, IL13RA1, SNX9, and GASP) and a novel cytokine, C17, whose expression is normally limited to CD34+ hematopoietic progenitors. Taken together, these data suggest that aberrant growth in HD&gt;50 ALL is in part driven by increased expression of a large number of genes secondary to chromosome duplications, coupled with a further enhanced expression of a limited number of growth promoting genes, and the specific silencing of a small subset of negative growth regulatory genes. Understanding the mechanisms responsible for the non-dosage related changes in gene expression should provide important insights into the pathology of HD&gt;50 ALL.

scholarly journals The genetic architecture of gene expression levels in wild baboons

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Jenny Tung ◽  
Xiang Zhou ◽  
Susan C Alberts ◽  
Matthew Stephens ◽  
Yoav Gilad
Keyword(s):  
Gene Expression ◽  
Genetic Architecture ◽  
Eqtl Mapping ◽  
Rna Seq ◽  
Specific Expression ◽  
Data Set ◽  
Expression Levels ◽  
Trait Locus ◽  
Eqtl Data ◽  
Gene Expression Levels

Primate evolution has been argued to result, in part, from changes in how genes are regulated. However, we still know little about gene regulation in natural primate populations. We conducted an RNA sequencing (RNA-seq)-based study of baboons from an intensively studied wild population. We performed complementary expression quantitative trait locus (eQTL) mapping and allele-specific expression analyses, discovering substantial evidence for, and surprising power to detect, genetic effects on gene expression levels in the baboons. eQTL were most likely to be identified for lineage-specific, rapidly evolving genes; interestingly, genes with eQTL significantly overlapped between baboons and a comparable human eQTL data set. Our results suggest that genes vary in their tolerance of genetic perturbation, and that this property may be conserved across species. Further, they establish the feasibility of eQTL mapping using RNA-seq data alone, and represent an important step towards understanding the genetic architecture of gene expression in primates.

scholarly journals CellExpress: a comprehensive microarray-based cancer cell line and clinical sample gene expression analysis online system

Database ◽  
2018 ◽  
Vol 2018 ◽  
Author(s):  
Yi-Fang Lee ◽  
Chien-Yueh Lee ◽  
Liang-Chuan Lai ◽  
Mong-Hsun Tsai ◽  
Tzu-Pin Lu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Lines ◽  
Cancer Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Comprehensive Analysis ◽  
Next Generation Sequencing Data ◽  
Clinical Samples ◽  
Expression Levels ◽  
Gene Expression Levels

Abstract With the advancement of high-throughput technologies, gene expression profiles in cell lines and clinical samples are widely available in the public domain for research. However, a challenge arises when trying to perform a systematic and comprehensive analysis across independent datasets. To address this issue, we developed a web-based system, CellExpress, for analyzing the gene expression levels in more than 4000 cancer cell lines and clinical samples obtained from public datasets and user-submitted data. First, a normalization algorithm can be utilized to reduce the systematic biases across independent datasets. Next, a similarity assessment of gene expression profiles can be achieved through a dynamic dot plot, along with a distance matrix obtained from principal component analysis. Subsequently, differentially expressed genes can be visualized using hierarchical clustering. Several statistical tests and analytical algorithms are implemented in the system for dissecting gene expression changes based on the groupings defined by users. Lastly, users are able to upload their own microarray and/or next-generation sequencing data to perform a comparison of their gene expression patterns, which can help classify user data, such as stem cells, into different tissue types. In conclusion, CellExpress is a user-friendly tool that provides a comprehensive analysis of gene expression levels in both cell lines and clinical samples. The website is freely available at http://cellexpress.cgm.ntu.edu.tw/. Source code is available at https://github.com/LeeYiFang/Carkinos under the MIT License. Database URL: http://cellexpress.cgm.ntu.edu.tw/

scholarly journals ERG11 and ABC2 Overexpression but Not ERG11 Gene Mutations Are Involved in the Development of Itraconazole Resistance in Candida Krusei

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 4624-4624 ◽  
Author(s):  
Xiaoyuan He ◽  
Mingfeng Zhao ◽  
Jinyan Chen ◽  
Rimao Wu ◽  
Jianlei Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Fold Increase ◽  
Housekeeping Gene ◽  
Clinical Isolates ◽  
Azole Resistance ◽  
Mrna Levels ◽  
Relative Gene Expression ◽  
Expression Levels ◽  
Relative Gene ◽  
Gene Expression Levels

Abstract Background: Recent years, the incidence and mortality of fungal infection has been on the rise in the patients with hematologic malignancies. This is mainly associated with antifungal resistance and the restricted number of available antifungal drugs. Candida species is one of the most prevalent pathogens in these immunodeficient patients. However, the study of azole resistance mechanisms of Candida has focused on C.albicans, C.glabrata, C.tropicalis. And few studies talked about resistance mechanisms of C.krusei, especially resistant to itraconazole. It was reported that the mutation or overexpression of 14¦Á-demethylases (encoded by ERG11) and upregulation of efflux transporters (encoded by ABC1 and ABC2) may be involved in azole resistance of C.krusei. Here, The purpose of the present study is to preliminarily explore the main molecular mechanisms responsible for Candida krusei clinical isolates to itraconazole, and may provide new sight into fungal infection therapy. Methods: The 14¦Á-demethylases encoded by ERG11 gene in the 16 C.krusei clinical isolates were amplified by polymerase chain reaction (PCR), and their nucleotide sequences were determined to detect point mutations. Meanwhile, ERG11 and efflux transporters (ABC1 and ABC2) genes were determined by quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) for their expression in itraconazole-resistant (R), itraconazole-susceptible dose dependent (SDD) and itraconazole- susceptible (S) C.krusei at the mRNA level. Results: We found 7-point mutations in ERG11 gene of all the C.krusei clinical isolates, including 6 synonymous mutations and 1 missense mutation (C44T). However, the missense mutation was found in the three groups. The mRNA levels of ERG11 gene in itraconazole-resistant isolates showed higher expression compared with itraconazole-susceptible dose dependent and itraconazole- susceptible ones (P=0.015 and P=0.002 respectively). ABC2 gene mRNA levels in itraconazole-resistant group was significantly higher than the other two groups, and the levels of their expression in the isolates appeared to increase with the decrease of susceptibility to itraconazole (P=0.007 in SDD compared with S, P=0.016 in SDD with R, and P<0.001 in S with R respectively). While ABC1 gene presented lower expression in itraconazole resistant strains. However, the mRNA levels of ERG11, ABC1 and ABC2 in a C.krusei (CK10) resistant to both itraconazole and voriconazole were expressed highest in all the itraconazole-resistant isolates. The relative mRNA levels of gene ABC2 and ERG11 can be found in Fig.1 and Fig.2 respectively. Conclusions: There are ERG11 gene polymorphisms in clinical isolates of C.krusei. ERG11 gene mutations were not found to be involved in the development of itraconazole resistance in C.krusei. ERG11 and ABC2 overexpression might be responsible for the acquired itraconazole resistance of these clinical isolates. Therefore, combination of azole and selective efflux transporter inhibitors may help reverse azole resistance and enhance antifungal effect. Figure 1. ABC2 relative gene expression levels in three groups of C.krusei clinical isolates. (A) Relative levels of ABC2 mRNA in all the C.krusei clinical isolates. ABC2 gene expression levels was quantified and normalized relative to the housekeeping gene, ACT1; S, itraconazole-susceptible; SDD, itraconazole-susceptibledose dependent; R, itraconazole-resistant. (B) Log10+3 fold increase of gene expression levels in three groups. (*P<0.05 in R compared with SDD; **P<0.01 in SDD with S; ***P<0.001 in R with S) Figure 1. ABC2 relative gene expression levels in three groups of C.krusei clinical isolates. (A) Relative levels of ABC2 mRNA in all the C.krusei clinical isolates. ABC2 gene expression levels was quantified and normalized relative to the housekeeping gene, ACT1; S, itraconazole-susceptible; SDD, itraconazole-susceptibledose dependent; R, itraconazole-resistant. (B) Log10+3 fold increase of gene expression levels in three groups. (*P<0.05 in R compared with SDD; **P<0.01 in SDD with S; ***P<0.001 in R with S) Figure 2. ERG11 relative gene expression levels in three groups of C.krusei clinical isolates. (A) Relative levels of ERG11 mRNA in all the C.krusei clinical isolates. ERG11 gene expression levels was quantified and normalized relative to the housekeeping gene, ACT1; S, itraconazole-susceptible; SDD, itraconazole-susceptibledose dependent; R, itraconazole-resistant. (B) Log10+3 fold increase of gene expression levels in three groups. (NS, no significance in SDD compared with S; *P<0.05 in R with SDD; **P<0.01 in R with S) Figure 2. ERG11 relative gene expression levels in three groups of C.krusei clinical isolates. (A) Relative levels of ERG11 mRNA in all the C.krusei clinical isolates. ERG11 gene expression levels was quantified and normalized relative to the housekeeping gene, ACT1; S, itraconazole-susceptible; SDD, itraconazole-susceptibledose dependent; R, itraconazole-resistant. (B) Log10+3 fold increase of gene expression levels in three groups. (NS, no significance in SDD compared with S; *P<0.05 in R with SDD; **P<0.01 in R with S) Disclosures No relevant conflicts of interest to declare.

scholarly journals Investigation of RASSF4 gene in head and neck cancers

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Emine H. Karagedik ◽  
Saim Pamuk ◽  
Merve N. Ataş ◽  
Murat Ulusan ◽  
Levent Aydemir ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Family ◽  
Head And Neck ◽  
Fold Increase ◽  
Serum Levels ◽  
Study Groups ◽  
Control Group ◽  
Rt Pcr ◽  
Expression Levels ◽  
Gene Expression Levels

Abstract Objectives RASSF gene family can inhibit the growth of RAS oncogene. This gene family is suggested to have a role in cell cycle control, apoptosis, cell migration, and mitosis control. This study evaluated RASSF4 gene expression levels, SNPs and serum levels in tissues dissected from both healthy individuals and patients diagnosed with head, and neck cancer. Methods RASSF4 gene expression levels were determined using the RT-PCR. Serum levels of RASSF4 were tested using the Enzyme-Linked Immuno Sorbent Assay technique in study groups. RASSF4 rs7896801 and rs884879 genotypes were identified using by the RT-PCR. Results No statistical difference was observed between study groups according to RASSF4 gene expression levels. According to SNP results, rs7896801 revealed a 2.4 fold increase of G-allele presence in patients (p=0.015). The increase in the presence of AA genotype was statistically significant for the control group (p=0.015). Distribution of genotypes and alleles for rs884879 showed a 2.2 fold increase in CC genotype for healthy group (p=0.031) however, the presence of T allele showed a significant increase in the patients (p=0.048). Conclusions We suggest that this study will play a pioneering role for the next studies on RASSF4 gene, especially on SNPs.

scholarly journals Nourin-Associated miRNAs: Novel Inflammatory Monitoring Markers for Cyclocreatine Phosphate Therapy in Heart Failure

2021 ◽  
Vol 22 (7) ◽  
pp. 3575
Author(s):  
Salwa A. Elgebaly ◽  
Robert Todd ◽  
Donald L. Kreutzer ◽  
Robert Christenson ◽  
Nashwa El-Khazragy ◽  
...  
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Myocardial Injury ◽  
Cell Damage ◽  
Expression Profiles ◽  
Preventive Therapy ◽  
Heart Weight ◽  
Serum Samples ◽  
Expression Levels ◽  
Gene Expression Levels

Background: Cyclocreatine phosphate (CCrP) is a potent bioenergetic cardioprotective compound known to preserve high levels of cellular adenosine triphosphate during ischemia. Using the standard Isoproterenol (ISO) rat model of heart failure (HF), we recently demonstrated that the administration of CCrP prevented the development of HF by markedly reducing cardiac remodeling (fibrosis and collagen deposition) and maintaining normal ejection fraction and heart weight, as well as physical activity. The novel inflammatory mediator, Nourin is a 3-KDa formyl peptide rapidly released by ischemic myocardium and is associated with post-ischemic cardiac inflammation. We reported that the Nourin-associated miR-137 (marker of cell damage) and miR-106b-5p (marker of inflammation) are significantly upregulated in unstable angina patients and patients with acute myocardial infarction, but not in healthy subjects. Objectives: To test the hypothesis that Nourin-associated miR-137 and miR-106b-5p are upregulated in ISO-induced “HF rats” and that the administration of CCrP prevents myocardial injury (MI) and reduces Nourin gene expression in “non-HF rats”. Methods: 25 male Wistar rats (180–220 g) were used: ISO/saline (n = 6), ISO/CCrP (0.8 g/kg/day) (n = 5), control/saline (n = 5), and control/CCrP (0.8 g/kg/day) (n = 4). In a limited study, CCrP at a lower dose of 0.4 g/kg/day (n = 3) and a higher dose of 1.2 g/kg/day (n = 2) were also tested. The Rats were injected SC with ISO for two consecutive days at doses of 85 and 170 mg/kg/day, respectively, then allowed to survive for an additional two weeks. CCrP and saline were injected IP (1 mL) 24 h and 1 h before first ISO administration, then daily for two weeks. Serum CK-MB (U/L) was measured 24 h after the second ISO injection to confirm myocardial injury. After 14 days, gene expression levels of miR-137 and miR-106b-5p were measured in serum samples using quantitative real-time PCR (qPCR). Results: While high levels of CK-MB were detected after 24 h in the ISO/saline rats indicative of MI, the ISO/CCrP rats showed normal CK-MB levels, supporting prevention of MI by CCrP. After 14 days, gene expression profiles showed significant upregulation of miR-137 and miR-106b-5p by 8.6-fold and 8.7-fold increase, respectively, in the ISO/saline rats, “HF rats,” compared to the control/saline group. On the contrary, CCrP treatment at 0.8 g/kg/day markedly reduced gene expression of miR-137 by 75% and of miR-106b-5p by 44% in the ISO/CCrP rats, “non-HF rats,” compared to the ISO/Saline rats, “HF rats.” Additionally, healthy rats treated with CCrP for 14 days showed no toxicity in heart, liver, and renal function. Conclusions: Results suggest a role of Nourin-associated miR-137 and miR-106b-5p in the pathogenesis of HF and that CCrP treatment prevented ischemic injury in “non-HF rats” and significantly reduced Nourin gene expression levels in a dose–response manner. The Nourin gene-based mRNAs may, therefore, potentially be used as monitoring markers of drug therapy response in HF, and CCrP—as a novel preventive therapy of HF due to ischemia.

scholarly journals Comparability of reference-based and reference-free transcriptome analysis approaches at the gene expression level

2021 ◽  
Vol 22 (S11) ◽  
Author(s):  
Sung-Gwon Lee ◽  
Dokyun Na ◽  
Chungoo Park
Keyword(s):  
Gene Expression ◽  
De Novo ◽  
Expression Profiles ◽  
Gene Families ◽  
Cell Types ◽  
Model Organisms ◽  
Expression Levels ◽  
Large Gene ◽  
Gene Expression Quantification ◽  
Gene Expression Levels

Abstract Background Lately, high-throughput RNA sequencing has been extensively used to elucidate the transcriptome landscape and dynamics of cell types of different species. In particular, for most non-model organisms lacking complete reference genomes with high-quality annotation of genetic information, reference-free (RF) de novo transcriptome analyses, rather than reference-based (RB) approaches, are widely used, and RF analyses have substantially contributed toward understanding the mechanisms regulating key biological processes and functions. To date, numerous bioinformatics studies have been conducted for assessing the workflow, production rate, and completeness of transcriptome assemblies within and between RF and RB datasets. However, the degree of consistency and variability of results obtained by analyzing gene expression levels through these two different approaches have not been adequately documented. Results In the present study, we evaluated the differences in expression profiles obtained with RF and RB approaches and revealed that the former tends to be satisfactorily replaced by the latter with respect to transcriptome repertoires, as well as from a gene expression quantification perspective. In addition, we urge cautious interpretation of these findings. Several genes that are lowly expressed, have long coding sequences, or belong to large gene families must be validated carefully, whenever gene expression levels are calculated using the RF method. Conclusions Our empirical results indicate important contributions toward addressing transcriptome-related biological questions in non-model organisms.

Targeting FOXM1 Transcription Factor In T-Cell Acute Lymphoblastic Leukemia

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 4974-4974 ◽  
Author(s):  
Özlem Tüfekçi ◽  
Melis Kartal Yandım ◽  
Hale Ören ◽  
Gülersu Irken ◽  
Yusuf Baran
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Cell Proliferation ◽  
Cell Line ◽  
Expression Profiles ◽  
Jurkat Cells ◽  
Pcr Array ◽  
Expression Levels ◽  
Siomycin A ◽  
Gene Expression Levels

Abstract The Forkhead box protein M1(FoxM1) is an important  transcriptional factor that takes play in regulation of cell cyle, proliferation, DNA repair, apoptosis, and angiogenesis. FoxM1 overexpression has been reported to be related with many types of cancer. Since many studies have reported that FOXM1 is an important target for cancer therapy, many researchers are studying on the identification of FOXM1 inhibitors. Siomycin A, a thiazol antibiotic, is known to inhibit FoxM1 transcriptional activity. Dexamethasone is a glucocorticoid  that is very important in treatment of acute lymphoblastic leukemia (ALL) and is known to be more potent compared to other steroids in the treatment of T-cell ALL. In this study, our aims were to determine the gene expression levels of FoxM1 in Jurkat cells (T-ALL cell line), to find out the possible synergistic and apoptotic effects of siomycin A and dexamethasone on this cell line and to investigate the changes in expression profiles of some important genes that have vital roles in cellular processes by targeting FoxM1 with siomycin A and dexamethasone on Jurkat cells. The gene expression levels of FoxM1 were studied with reverse transcriptase polymerase chain reaction (RT-PCR). The cytotoxic effects of siomycin  A and dexamethasone on Jurkat cells were assesed by MTT cell proliferation test.  The possible synergistic, additive, neutral, and antagonistic effect of combination of  dexamethasone and siomycin A was determined with isobologram analysis.  The apoptotic effects of these two agents were evaluated by  Caspase-3 activity, loss of mitochondrial membrane potential and localisation of phosphatidilserine on plasma membrane. For this purpose, Caspase-3 calorimetric assay kit, JC-1 mitochondrial membrane potential assay kit, and Annexin V-FITC apoptosis detection kit were used, respectively. For cell cycle analysis, Jurkat cells treated with siomycin A alone or in combination with dexamethasone were stained by propidium iodide and then analyzed by flow cytometry. Expression profiles of Jurkat cells treated with siomycin A alone or in combination with dexamethasone were determined by Cancer Pathway Finder PCR Array. We found that FoxM1 gene is overexpressed in T-ALL cell line and dexamethasone and siomycin A caused a reduction in gene expression levels of FoxM1 in Jurkat cells. 8% to 13% decrease in proliferation of Jurkat cells were observed when these cells were treated with 1 and 10 µM doses of dexamethasone for 72 hours, respectively. The same doses of dexamethasone combined with siomycin A caused 74% and 75% decrease in proliferation of Jurkat cells. Isobologram analysis revealed very strong synergy between dexamethasone and siomycin A. Apoptotic tests showed no apoptotic activity of dexamethasone and siomycin A on Jurkat cells. Cell cycle analysis demonstrated that, reduction of FOXM1 expression by combination of dexamethasone and siomycin A in Jurkat cells inhibited cell proliferation through induction of G1 phase arrest. PCR Array results showed that apoptotic CASPASE-2, CASPASE-7, and CASPASE-9 genes and XIAP and CYCLIN D3 genes were upregulated in response to the treatment. ETS2 gene, which is known as a protooncogene and shown to be involved in regulation of telomerase, was downregulated in response to siomycin A and dexamethosone alone and in combined treatment. TERF1 gene, which inhibits telomerase activity, was upregulated by the treatment. Combination of Siomycin A and dexamethasone downregulated the MCM-2 gene, which is a key component of the pre-replication complex and involved in the formation of DNA replication fork. Moreover, combined treatment resulted in the downregulation of MKI67 gene encoding a nuclear protein associated with  cellular proliferation. WEE1 gene, which inhibits G2/M phase transition in cell cycle, was also upregulated. These data indicate that FoxM1 gene is strongly overexpressed in T-ALL cell line and targeting FoxM1 by siomycin A and dexamethasone causes a significant decrease in T-ALL cell proliferation through induction of  G1 cell cycle arrest. Importantly, PCR array analyses also showed that siomycin A and dexamethasone treatment affects Jurkat cells via upregulating or downregulating the key genes of cell cycle, apoptosis, cell proliferation, telomere, and telomerase function. All these findings suggest a possible role for FoxM1 in T-ALL pathogenesis and represent FoxM1 as an attractive target for T-ALL therapy. Disclosures: No relevant conflicts of interest to declare.

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