Izadi, Pantea;Noruzinia, Mehrdad;Fereidooni, Foruzandeh;Nateghi, Mohammad Reza
Asian Pacific Journal of Cancer Prevention
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v.13
no.8
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pp.4113-4117
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2012
Breast cancer is a prevalent heterogeneous malignant disease. Gene expression profiling by DNA microarray can classify breast tumors into five different molecular subtypes: luminal A, luminal B, HER-2, basal and normal-like which have differing prognosis. Recently it has been shown that immunohistochemistry (IHC) markers including estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (Her2), can divide tumors to main subtypes: luminal A (ER+; PR+/-; HER-2-), luminal B (ER+;PR+/-; HER-2+), basal-like (ER-;PR-;HER2-) and Her2+ (ER-; PR-; HER-2+). Some subtypes such as basal-like subtype have been characterized by poor prognosis and reduced overall survival. Due to the importance of the ER signaling pathway in mammary cell proliferation; it appears that epigenetic changes in the $ER{\alpha}$ gene as a central component of this pathway, may contribute to prognostic prediction. Thus this study aimed to clarify the correlation of different IHC-based subtypes of breast tumors with $ER{\alpha}$ methylation in Iranian breast cancer patients. For this purpose one hundred fresh breast tumors obtained by surgical resection underwent DNA extraction for assessment of their ER methylation status by methylation specific PCR (MSP). These tumors were classified into main subtypes according to IHC markers and data were collected on pathological features of the patients. $ER{\alpha}$ methylation was found in 25 of 28 (89.3%) basal tumors, 21 of 24 (87.5%) Her2+ tumors, 18 of 34 (52.9%) luminal A tumors and 7 of 14 (50%) luminal B tumors. A strong correlation was found between $ER{\alpha}$ methylation and poor prognosis tumor subtypes (basal and Her2+) in patients (P<0.001). Our findings show that $ER{\alpha}$ methylation is correlated with poor prognosis subtypes of breast tumors in Iranian patients and may play an important role in pathogenesis of the more aggressive breast tumors.
Objectives: MicroRNAs (miRNAs) are important regulators of many physiological and pathological processes, including tumorigenesis and metastasis. In this study, we sought to determine the underlying molecular mechanisms of metastatic cervical carcinoma by performing miRNA profiling. Methods: Tissue samples were collected from ten cervical squamous cancer patients who underwent hysterectomy and pelvic lymph node (PLN) dissection in our hospital, including four PLN-positive (metastatic) cases and six PLN-negative (non-metastatic) cases. A miRNA microarray platform with 1223 probes was used to determine the miRNA expression profiles of these two tissue types and case groups. MiRNAs having at least 4-fold differential expression between PLN-positive and PLN-negative cervical cancer tissues were bioinformatically analyzed for target gene prediction. MiRNAs with tumor-associated target genes were validated by quantitative reverse transcription-polymerase chain reaction (RT-PCR). Results: Thirty-nine miRNAs were differentially expressed (>4-fold) between the PLN-positive and PLN-negative groups, of which, 22 were up-regulated and 17 were down-regulated. Sixty-nine percent of the miRNAs (27/39) had tumor-associated target genes, and the expression levels of six of those (miR-126, miR-96, miR-144, miR-657, miR-490-5p, and miR-323-3p) were confirmed by quantitative (q)RT-PCR. Conclusions: Six MiRNAs with predicted tumor-associated target genes encoding proteins that are known to be involved in cell adhesion, cytoskeletal remodeling, cell proliferation, cell migration, and apoptosis were identified. These findings suggest that a panel of miRNAs may regulate multiple and various steps of the metastasis cascade by targeting metastasis-associated genes. Since these six miRNAs are predicted to target tumor-associated genes, it is likely that they contribute to the metastatic potential of cervical cancer and may aid in prognosis or molecular therapy.
Journal of the Korea Society of Computer and Information
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v.15
no.11
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pp.215-224
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2010
Most chronic diseases are complex diseases which are caused by interactions of several genes. Studies on finding SNPs and gene-gene interactions involved in the development of complex diseases can contribute to prevention and treatment of the diseases. Previous studies mostly concentrate on finding only the set of SNPs involved. In this study we suggest a way to see how these SNPs interact using boolean expressions. The proposed method consists of two stages. In the first stage we find the set of SNPs involved in the development of diseases using mutual information based on entropy. In the second stage we find the highest accuracy boolean expression that consists of the SNP set obtained in the first stage. We experimented with clinical data to demonstrate the effectiveness of the proposed method. We also compared the differences between our method and the previous results on the SNP associations studies.
Aim: To evaluate the association of glutathione S-transferases gene polymorphisms with the risk of gastric cancer, with reference to smoking and Helicobacter pylori infection. Methods: We conducted a 1:1 matched case-control study with 410 gastric cancer cases and 410 cancer-free controls. Polymorphisms of GSTM1, GSTT1 and GSTP1 were determined using PCR-CTPP. Results: The GSTM1 and GSTT1 null genotypes were significantly associated with the risk of gastric cancer after adjusting for potential confounding factors (OR=1.68, 95% CI=1.32-2.23 for null GSTM1, OR=1.73; 95% CI=1.24-2.13 for null GSTT1). The combination of null GSTM1 and null GSTT1 conferred an elevated risk (OR=2.54, 95% CI=1.55-3.39). However, no association was found for GSTP1 polymorphism The smoking modified the association of GSTM1 and GSTT1 null genotypes with the risk of gastric cancer. Conclusion: GSTM1 and GSTT1 null genotypes are associated with increased risk of gastric cancer, and smoking modifies the association.
Objective: An experiment was conducted to study the association between the single nucleotide polymorphisms (SNPs) in 5'-untranslated regions (5'-UTR) of equine chorionic gonadotropin (eCG) genes and the serum eCG levels. Methods: SNPs in 5'-UTR of eCG genes were screened across 10 horse breeds, including 7 Chinese indigenous breeds and 3 imported breeds using iPLEX chemistry, and the association between the serum eCG levels of 174 pregnant Da'an mares and their serum eCG levels (determined with ELISA) was analyzed. Results: Four SNPs were identified in the 5'-UTR of the $eCG{\alpha}$ gene, and one of them was unique in the indigenous breeds. There were 2 SNPs detected at the 5' end of the $eCG{\beta}$ subunit gene, and one of them was only found in the Chinese breeds. The SNP g.39948246T>C at the 5'-UTR of $eCG{\alpha}$ was associated significantly with eCG levels of 75-day pregnant mare serum (p<0.05) in Da'an mares. Prediction analysis on binding sites of transcription factors showed that the g.39948246T>C mutation causes appearance of the specific binding site of hepatocyte nuclear factor 3 forkhead homolog 2 (HFH-2), which is a transcriptional repressor belonging to the forkhead protein family of transcription factors. Conclusion: The SNP g.39948246T>C at the 5'-UTR of $eCG{\alpha}$ is associated with eCG levels of 75-day pregnant mare serum (p<0.05).
Identification of fusion gene is of prominent importance in cancer research field because of their potential as carcinogenic drivers. RNA sequencing (RNA-Seq) data have been the most useful source for identification of fusion transcripts. Although a number of algorithms have been developed thus far, most programs produce too many false-positives, thus making experimental confirmation almost impossible. We still lack a reliable program that achieves high precision with reasonable recall rate. Here, we present FusionScan, a highly optimized tool for predicting fusion transcripts from RNA-Seq data. We specifically search for split reads composed of intact exons at the fusion boundaries. Using 269 known fusion cases as the reference, we have implemented various mapping and filtering strategies to remove false-positives without discarding genuine fusions. In the performance test using three cell line datasets with validated fusion cases (NCI-H660, K562, and MCF-7), FusionScan outperformed other existing programs by a considerable margin, achieving the precision and recall rates of 60% and 79%, respectively. Simulation test also demonstrated that FusionScan recovered most of true positives without producing an overwhelming number of false-positives regardless of sequencing depth and read length. The computation time was comparable to other leading tools. We also provide several curative means to help users investigate the details of fusion candidates easily. We believe that FusionScan would be a reliable, efficient and convenient program for detecting fusion transcripts that meet the requirements in the clinical and experimental community. FusionScan is freely available at http://fusionscan.ewha.ac.kr/.
Objectives : In this study, we investigated the SNP (single-nucleotide polymorphism) of IL10 in patients with stroke. The present study was undertaken to see if specific genotypic and allelic variations are associated with stroke in the Korean population. Methods : Blood samples from all subjects were obtained for DNA extraction and collected in EDTA tube. Genomic DNA was extracted using DNA isolation kit for Mammalian Blood (Boehringer Mannheim, IN, USA). The extracted DNA was amplified by polymerase chain reaction (PCR). Pyrosequencing was performed according to manufacturer's standard protocol. Results : There was no statistically significant genotypic distribution difference between control and stroke group. The frequencies of A/A homozygotes and A/C heterozygotes among control subjects were 91 (87.5%) and 13 (12.5%). The frequencies of A/A and A/C among the stroke patients were 85 (89.5%) and 10 (10.5%). There was not statistically significant allelic frequency difference between control and stroke group. The allelic frequency of A and C was 195 (93.8%) and 13 (6.2%) among the control subjects and 180 (94.7%) and 10 (5.3%) in stroke patients, respectively. Conclusion : The cytokine IL10 may not be pathogenetic factors in stroke. But further studies including different cytokine gene can be a useful for predicting stroke. Establishment of more systemic approach and high quality of prospective cohorts will be necessary for the good prediction of genetic markers.
Lee kyung-Hun;Park Se-Won;Kim In-Ho;Yoon Sung-Soo;Park Seon-Yang;Kim Byoung-Kook
Genomics & Informatics
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v.4
no.3
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pp.97-102
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2006
In acute leukemia patients, several successful methods of expression profiling have been used for various purposes, i.e., to identify new disease class, to select a therapeutic target, or to predict chemo-sensitivity and clinical outcome. In the present study, we tested the peripheral blood of 47 acute leukemia patients in an attempt to identify differentially expressed genes in AML and ALL using a Korean-made 10K oligo-nucleotide microarray. Methods: Total RNA was prepared from peripheral blood and amplified for microarray experimentation. SAM (significant analysis of microarray) and PAM (prediction analysis of microarray) were used to select significant genes. The selected genes were tested for in a test group, independently of the training group. Results: We identified 345 differentially expressed genes that differentiated AML and ALL patients (FWER<0.05). Genes were selected using the training group (n=35) and tested for in the test group (n=12). Both training group and test group discriminated AML and ALL patients accurately. Genes that showed relatively high expression in AML patients were deoxynucleotidyl transferase, pre-B lymphocyte gene 3, B-cell linker, CD9 antigen, lymphoid enhancer-binding factor 1, CD79B antigen, and early B-cell factor. Genes highly expressed in ALL patients were annexin A 1, amyloid beta (A4) precursor protein, amyloid beta (A4) precursor-like protein 2, cathepsin C, lysozyme (renal amyloidosis), myeloperoxidase, and hematopoietic prostaglandin D2 synthase. Conclusion: This study provided genome wide molecular signatures of Korean acute leukemia patients, which clearly identify AML and ALL. Given with other reported signatures, these molecular signatures provide a means of achieving a molecular diagnosis in Korean acute leukemia patents.
Jang, Hee Yeon;Lim, Seung Mook;Lee, Hyun Jung;Hong, Joon-Seok;Kim, Gi Jin
Clinical and Experimental Reproductive Medicine
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v.47
no.1
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pp.42-53
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2020
Objective: Recently, microRNA (miRNA) has been identified both as a powerful regulator involved in various biological processes through the regulation of numerous genes and as an effective biomarker for the prediction and diagnosis of various disease states. The objective of this study was to identify and validate miRNAs and their target genes involved in inflammation in placental tissue. Methods: Microarrays were utilized to obtain miRNA and gene expression profiles from placentas with or without inflammation obtained from nine normal pregnant women and 10 preterm labor patients. Quantitative real-time polymerase chain reaction and Western blots were performed to validate the miRNAs and differentially-expressed genes in the placentas with inflammation. Correlations between miRNA and target gene expression were confirmed by luciferase assays in HTR-8/SVneo cells. Results: We identified and validated miRNAs and their target genes that were differentially expressed in placentas with inflammation. We also demonstrated that several miRNAs (miR-371a-5p, miR-3065-3p, miR-519b-3p, and miR-373-3p) directly targeted their target genes (LEF1, LOX, ITGB4, and CD44). However, some miRNAs and their direct target genes showed no correlation in tissue samples. Interestingly, miR-373-3p and miR-3065-3p were markedly regulated by lipopolysaccharide (LPS) treatment, although the expression of their direct targets CD44 and LOX was not altered by LPS treatment. Conclusion: These results provide candidate miRNAs and their target genes that could be used as placental biomarkers of inflammation. These candidates may be useful for further miRNA-based biomarker development.
Memarzadeh, Armin;Shahmansouri, Amir Ali;Poologanathan, Keerthan
Steel and Composite Structures
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v.44
no.3
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pp.309-324
/
2022
The post-fire elastic stiffness and performance of concrete-filled steel tube (CFST) columns containing recycled aggregate concrete (RAC) has rarely been addressed, particularly in terms of material properties. This study was conducted with the aim of assessing the modulus of elasticity of recycled aggregate concrete-filled steel tube (RACFST) stub columns following thermal loading. The test data were employed to model and assess the elastic modulus of circular RACFST stub columns subjected to axial loading after exposure to elevated temperatures. The length/diameter ratio of the specimens was less than three to prevent the sensitivity of overall buckling for the stub columns. The gene expression programming (GEP) method was employed for the model development. The GEP model was derived based on a comprehensive experimental database of heated and non-heated RACFST stub columns that have been properly gathered from the open literature. In this study, by using specifications of 149 specimens, the variables were the steel section ratio, applied temperature, yielding strength of steel, compressive strength of plain concrete, and elastic modulus of steel tube and concrete core (RAC). Moreover, parametric and sensitivity analyses were also performed to determine the contribution of different effective parameters to the post-fire elastic modulus. Additionally, comparisons and verification of the effectiveness of the proposed model were made between the values obtained from the GEP model and the formulas proposed by different researchers. Through the analyses and comparisons of the developed model against formulas available in the literature, the acceptable accuracy of the model for predicting the post-fire modulus of elasticity of circular RACFST stub columns was seen.
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