Displaying publications 1 - 20 of 62 in total

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  1. Construction of a microRNA-mRNA Regulatory Network in De Novo Cytogenetically Normal Acute Myeloid Leukemia Patients
    Esa E, Hashim AK, Mohamed EHM, Zakaria Z, Abu Hassan AN, Mat Yusoff Y, et al.
    Genet Test Mol Biomarkers, 2021 Mar;25(3):199-210.
    PMID: 33734890 DOI: 10.1089/gtmb.2020.0182
    Background: The association between dysregulated microRNAs (miRNAs) and acute myeloid leukemia (AML) is well known. However, our understanding of the regulatory role of miRNAs in the cytogenetically normal AML (CN-AML) subtype pathway is still poor. The current study integrated miRNA and mRNA profiles to explore novel miRNA-mRNA interactions that affect the regulatory patterns of de novo CN-AML. Methods: We utilized a multiplexed nanoString nCounter platform to profile both miRNAs and mRNAs using similar sets of patient samples (n = 24). Correlations were assessed, and an miRNA-mRNA network was constructed. The underlying biological functions of the mRNAs were predicted by gene enrichment. Finally, the interacting pairs were assessed using TargetScan and microT-CDS. We identified 637 significant negative correlations (false discovery rate <0.05). Results: Network analysis revealed a cluster of 12 miRNAs representing the majority of mRNA targets. Within the cluster, five miRNAs (miR-495-3p, miR-185-5p, let-7i-5p, miR-409-3p, and miR-127-3p) were posited to play a pivotal role in the regulation of CN-AML, as they are associated with the negative regulation of myeloid leukocyte differentiation, negative regulation of myeloid cell differentiation, and positive regulation of hematopoiesis. Conclusion: Three novel interactions in CN-AML were predicted as let-7i-5p:HOXA9, miR-495-3p:PIK3R1, and miR-495-3p:CDK6 may be responsible for regulating myeloid cell differentiation in CN-AML.
    Matched MeSH terms: Gene Expression Profiling/methods
  2. A modified binary particle swarm optimization for selecting the small subset of informative genes from gene expression data
    Mohamad MS, Omatu S, Deris S, Yoshioka M
    IEEE Trans Inf Technol Biomed, 2011 Nov;15(6):813-22.
    PMID: 21914573 DOI: 10.1109/TITB.2011.2167756
    Gene expression data are expected to be of significant help in the development of efficient cancer diagnoses and classification platforms. In order to select a small subset of informative genes from the data for cancer classification, recently, many researchers are analyzing gene expression data using various computational intelligence methods. However, due to the small number of samples compared to the huge number of genes (high dimension), irrelevant genes, and noisy genes, many of the computational methods face difficulties to select the small subset. Thus, we propose an improved (modified) binary particle swarm optimization to select the small subset of informative genes that is relevant for the cancer classification. In this proposed method, we introduce particles' speed for giving the rate at which a particle changes its position, and we propose a rule for updating particle's positions. By performing experiments on ten different gene expression datasets, we have found that the performance of the proposed method is superior to other previous related works, including the conventional version of binary particle swarm optimization (BPSO) in terms of classification accuracy and the number of selected genes. The proposed method also produces lower running times compared to BPSO.
    Matched MeSH terms: Gene Expression Profiling/methods*
  3. Fulltext Identification of Reference Genes in Chicken Intraepithelial Lymphocyte Natural Killer Cells Infected with Very-virulent Infectious Bursal Disease Virus
    Boo SY, Tan SW, Alitheen NB, Ho CL, Omar AR, Yeap SK
    Sci Rep, 2020 05 22;10(1):8561.
    PMID: 32444639 DOI: 10.1038/s41598-020-65474-3
    Due to the limitations in the range of antibodies recognising avian viruses, quantitative real-time PCR (RT-qPCR) is still the most widely used method to evaluate the expression of immunologically related genes in avian viruses. The objective of this study was to identify suitable reference genes for mRNA expression analysis in chicken intraepithelial lymphocyte natural killer (IEL-NK) cells after infection with very-virulent infectious bursal disease virus (vvIBDV). Fifteen potential reference genes were selected based on the references available. The coefficient of variation percentage (CV%) and average count of these 15 genes were determined by NanoString technology for control and infected samples. The M and V values for shortlisted reference genes (ACTB, GAPDH, HMBS, HPRT1, SDHA, TUBB1 and YWHAZ) were calculated using geNorm and NormFinder. GAPDH, YWHAZ and HMBS were the most stably expressed genes. The expression levels of three innate immune response related target genes, CASP8, IL22 and TLR3, agreed in the NanoString and RNA sequencing (RNA-Seq) results using one or two reference genes for normalisation (not HMBS). In conclusion, GAPDH and YWHAZ could be used as reference genes for the normalisation of chicken IEL-NK cell gene responses to infection with vvIBDV.
    Matched MeSH terms: Gene Expression Profiling/methods
  4. Fulltext Flexible model-based clustering of mixed binary and continuous data: application to genetic regulation and cancer
    Zainul Abidin FN, Westhead DR
    Nucleic Acids Res, 2017 04 20;45(7):e53.
    PMID: 27994031 DOI: 10.1093/nar/gkw1270
    Clustering is used widely in 'omics' studies and is often tackled with standard methods, e.g. hierarchical clustering. However, the increasing need for integration of multiple data sets leads to a requirement for clustering methods applicable to mixed data types, where the straightforward application of standard methods is not necessarily the best approach. A particularly common problem involves clustering entities characterized by a mixture of binary data (e.g. presence/absence of mutations, binding, motifs and epigenetic marks) and continuous data (e.g. gene expression, protein abundance, metabolite levels). Here, we present a generic method based on a probabilistic model for clustering this type of data, and illustrate its application to genetic regulation and the clustering of cancer samples. We show that the resulting clusters lead to useful hypotheses: in the case of genetic regulation these concern regulation of groups of genes by specific sets of transcription factors and in the case of cancer samples combinations of gene mutations are related to patterns of gene expression. The clusters have potential mechanistic significance and in the latter case are significantly linked to survival. The method is available as a stand-alone software package (GNU General Public Licence) from http://github.com/BioToolsLeeds/FlexiCoClusteringPackage.git.
    Matched MeSH terms: Gene Expression Profiling/methods*
  5. Fulltext Endogenous HIF2A reporter systems for high-throughput functional screening
    Zaini MN, Patel SA, Syafruddin SE, Rodrigues P, Vanharanta S
    Sci Rep, 2018 08 13;8(1):12063.
    PMID: 30104738 DOI: 10.1038/s41598-018-30499-2
    Tissue-specific transcriptional programs control most biological phenotypes, including disease states such as cancer. However, the molecular details underlying transcriptional specificity is largely unknown, hindering the development of therapeutic approaches. Here, we describe novel experimental reporter systems that allow interrogation of the endogenous expression of HIF2A, a critical driver of renal oncogenesis. Using a focused CRISPR-Cas9 library targeting chromatin regulators, we provide evidence that these reporter systems are compatible with high-throughput screening. Our data also suggests redundancy in the control of cancer type-specific transcriptional traits. Reporter systems such as those described here could facilitate large-scale mechanistic dissection of transcriptional programmes underlying cancer phenotypes, thus paving the way for novel therapeutic approaches.
    Matched MeSH terms: Gene Expression Profiling/methods*
  6. RNA-Seq transcriptomic analysis of the Morus alba L. leaves exposed to high-level UVB with or without dark treatment
    Guan Q, Yu J, Zhu W, Yang B, Li Y, Zhang L, et al.
    Gene, 2018 Mar 01;645:60-68.
    PMID: 29274907 DOI: 10.1016/j.gene.2017.12.045
    Ultraviolet-B (UVB) irradiation induces oxidative stress in plant cells due to the generation of excessive reactive oxygen species. Morus alba L. (M. abla) is an important medicinal plant used for the treatment of human diseases. Also, its leaves are widely used as food for silkworms. In our previous research, we found that a high level of UVB irradiation with dark incubation led to the accumulation of secondary metabolites in M. abla leaf. The aim of the present study was to describe and compare M. alba leaf transcriptomics with different treatments (control, UVB, UVB+dark). Leaf transcripts from M. alba were sequenced using an Illumina Hiseq 2000 system, which produced 14.27Gb of data including 153,204,462 paired-end reads among the three libraries. We de novo assembled 133,002 transcripts with an average length of 1270bp and filtered 69,728 non-redundant unigenes. A similarity search was performed against the non-redundant National Center of Biotechnology Information (NCBI) protein database, which returned 41.08% hits. Among the 20,040 unigenes annotated in UniProtKB/SwissProt database, 16,683 unigenes were assigned 102,232 gene ontology terms and 6667 unigenes were identified in 287 known metabolic pathways. Results of differential gene expression analysis together with real-time quantitative PCR tests indicated that UVB irradiation with dark incubation enhanced the flavonoid biosynthesis in M. alba leaf. Our findings provided a valuable proof for a better understanding of the metabolic mechanism under abiotic stresses in M. alba leaf.
    Matched MeSH terms: Gene Expression Profiling/methods*
  7. Biofilm-Related Diseases and Omics: Global Transcriptional Profiling of Enterococcus faecium Reveals Different Gene Expression Patterns in the Biofilm and Planktonic Cells
    Lim SY, Teh CSJ, Thong KL
    OMICS, 2017 10;21(10):592-602.
    PMID: 29049010 DOI: 10.1089/omi.2017.0119
    Enterococcus faecium is an opportunistic pathogen with a remarkable ability to acquire resistance toward multiple antibiotics, including those of last-resort drugs such as vancomycin and daptomycin. The occurrence of vancomycin-resistant E. faecium is on the rise and there is a need to understand the virulence of this organism. One of the factors that contributes to the virulence is the ability to form biofilms. Since bacteria in biofilm state are more resistant to antibiotics and host immune response, understanding the molecular mechanism of biofilm development is important to control biofilm-related diseases. The aim of this study was to determine the global gene expression profiles of an E. faecium strain, VREr5, during the early event of sessile growth compared with its planktonic phase through RNA-sequencing approach. The results clearly illustrated distinct expression profiles of the planktonic and biofilm cells. A total of 177 genes were overexpressed in the biofilm cells. Most of them encode for proteins involved in adherence, such as the ebpABCfm locus. Genes associated with plasmid replication, gene exchange, and protein synthesis were also upregulated during the early event of biofilm development. Furthermore, the transcriptome analysis also identified genes such as fsrB, luxS, and spx that might suppress biofilm formation in VREr5. The putative biofilm-related bee locus was found to be downregulated. These new findings could provide caveats for future studies on the regulation and maintenance of biofilm and development of biomarkers for biofilm-related diseases.
    Matched MeSH terms: Gene Expression Profiling/methods
  8. RNomic identification and evaluation of npcTB_6715, a non-protein-coding RNA gene as a potential biomarker for the detection of Mycobacterium tuberculosis
    Kanniappan P, Ahmed SA, Rajasekaram G, Marimuthu C, Ch'ng ES, Lee LP, et al.
    J Cell Mol Med, 2017 10;21(10):2276-2283.
    PMID: 28756649 DOI: 10.1111/jcmm.13148
    Technological advances in RNA biology greatly improved transcriptome profiling during the last two decades. Besides the discovery of many small RNAs (sRNA) that are involved in the physiological and pathophysiological regulation of various cellular circuits, it becomes evident that the corresponding RNA genes might also serve as potential biomarkers to monitor the progression of disease and treatment. sRNA gene candidate npcTB_6715 was previously identified via experimental RNomic (unpublished data), and we report its application as potential biomarker for the detection of Mycobacterium tuberculosis (MTB) in patient samples. For proof of principle, we developed a multiplex PCR assay and report its validation with 500 clinical cultures, positive for Mycobacteria. The analysis revealed 98.9% sensitivity, 96.1% specificity, positive and negative predictive values of 98.6% and 96.8%, respectively. These results underscore the diagnostic value of the sRNA gene as diagnostic marker for the specific detection of MTB in clinical samples. Its successful application and the general ease of PCR-based detection compared to standard bacterial culture techniques might be the first step towards 'point-of-care' diagnostics of Mycobacteria. To the best of our knowledge, this is the first time for the design of diagnostic applications based on sRNA genes, in Mycobacteria.
    Matched MeSH terms: Gene Expression Profiling/methods
  9. Relative quantification of human β‑defensins gene expression in pterygium and normal conjunctiva samples
    Abubakar SA, Isa MM, Omar N, Tan SW
    Mol Med Rep, 2020 Dec;22(6):4931-4937.
    PMID: 33174018 DOI: 10.3892/mmr.2020.11560
    The human ocular surface produces highly conserved cationic peptides. Human β‑defensins (HBDs) serve an important role in innate and adaptive immunity. They are primarily expressed in epithelial cells in response to infection and provide the first line of defence against invading microbes. Defensin β1 (DEFB1) is constitutively expressed and regulated by inflammatory mediators including interferon‑γ, lipopolysaccharide and peptidoglycans. DEFB4A is locally induced in response to microbial infection while DEFB109 is induced via Toll‑like receptor 2. The present study examined the expression of the HBD DEFB1, DEFB4A and DEFB109 genes in pterygium. The pterygium tissues and normal conjunctiva samples were obtained from 18 patients undergoing pterygium surgery. The reverse transcription‑quantitative polymerase chain reaction method was employed to determine the expression of DEFB1, DEFB4A and DEFB109 genes. The results revealed that the expression of DEFB1 and DEFB4A was significantly higher and upregulated in pterygium samples when compared with normal conjunctiva samples from each patient (P<0.05), while the expression of DEFB109 was observed to be lower in pterygium samples when compared with normal samples from the same patient. Previous studies have revealed that DEFB1 and DEFB4A genes are present in low concentrations inside the human eye, and they are upregulated during the maturation of keratinocytes, suggesting a possible role in cell differentiation. The DEFB109 gene is present in higher concentrations inside the human eye, though it is newly discovered. It has also been reported that DEFB1 may be involved in carcinogenesis epithelial tumours. Collectively, the current data suggests that HBDs may serve a crucial role in the pathogenesis and development of pterygia, and thus may be considered as novel molecular targets in understanding pterygia development.
    Matched MeSH terms: Gene Expression Profiling/methods
  10. High-Throughput RT-qPCR for the Analysis of Circulating MicroRNAs
    Tan GW, Tan LP
    Methods Mol Biol, 2017;1580:7-19.
    PMID: 28439823 DOI: 10.1007/978-1-4939-6866-4_2
    Reverse transcription followed by real-time or quantitative polymerase chain reaction (RT-qPCR) is the gold standard for validation of results from transcriptomic profiling studies such as microarray and RNA sequencing. The current need for most studies, especially biomarker studies, is to evaluate the expression levels or fold changes of many transcripts in a large number of samples. With conventional low to medium throughput qPCR platforms, many qPCR plates would have to be run and a significant amount of RNA input per sample will be required to complete the experiments. This is particularly challenging when the size of study material (small biopsy, laser capture microdissected cells, biofluid, etc.), time, and resources are limited. A sensitive and high-throughput qPCR platform is therefore optimal for the evaluation of many transcripts in a large number of samples because the time needed to complete the entire experiment is shortened and the usage of lab consumables as well as RNA input per sample are low. Here, the methods of high-throughput RT-qPCR for the analysis of circulating microRNAs are described. Two distinctive qPCR chemistries (probe-based and intercalating dye-based) can be applied using the methods described here.
    Matched MeSH terms: Gene Expression Profiling/methods
  11. Fulltext A novel and non-invasive approach utilising nasal washings for the detection of nasopharyngeal carcinoma
    Tan GW, Sivanesan VM, Abdul Rahman FI, Hassan F, Hasbullah HH, Ng CC, et al.
    Int J Cancer, 2019 Oct 15;145(8):2260-2266.
    PMID: 30698824 DOI: 10.1002/ijc.32173
    Nasopharyngeal carcinoma (NPC) is an epithelial cancer of the nasopharynx which is highly associated with Epstein-Barr virus (EBV). Worldwide, most of the top 20 countries with the highest incidence and mortality rates of NPC are low- and middle-income countries. Many studies had demonstrated that EBV could be detected in the tissue, serum and plasma of NPC patients. In this study, we explored the potential of assays based on non-invasive nasal washings (NW) as a diagnostic and prognostic tool for NPC. A total of 128 patients were evaluated for NW EBV DNA loads and a subset of these samples were also tested for 27 EBV and human miRNAs shortlisted from literature. EBV DNA and seven miRNAs showed area under the receiver operating characteristic curve (AUC) values of more than 0.7, suggestive of their potential utility to detect NPC. Logistic regression analyses suggested that combination of two NW assays that test for EBNA-1 and hsa-miR-21 had the best performance in detecting NPC. The trend of NW EBV DNA load matched with clinical outcome of 71.4% (10 out of 14) NPC patients being followed-up. In summary, the non-invasive NW testing panel may be particularly useful for NPC screening in remote areas where healthcare facilities and otolaryngologists are lacking, and may encourage frequent testing of individuals in the high risk groups who are reluctant to have their blood tested. However, further validation in an independent cohort is required to strengthen the utility of this testing panel as a non-invasive detection tool for NPC.
    Matched MeSH terms: Gene Expression Profiling/methods
  12. Fulltext Comparative transcriptome analysis to identify candidate genes involved in 2-methoxy-1,4-naphthoquinone (MNQ) biosynthesis in Impatiens balsamina L
    Foong LC, Chai JY, Ho ASH, Yeo BPH, Lim YM, Tam SM
    Sci Rep, 2020 09 30;10(1):16123.
    PMID: 32999341 DOI: 10.1038/s41598-020-72997-2
    Impatiens balsamina L. is a tropical ornamental and traditional medicinal herb rich in natural compounds, especially 2-methoxy-1,4-naphthoquinone (MNQ) which is a bioactive compound with tested anticancer activities. Characterization of key genes involved in the shikimate and 1,4-dihydroxy-2-naphthoate (DHNA) pathways responsible for MNQ biosynthesis and their expression profiles in I. balsamina will facilitate adoption of genetic/metabolic engineering or synthetic biology approaches to further increase production for pre-commercialization. In this study, HPLC analysis showed that MNQ was present in significantly higher quantities in the capsule pericarps throughout three developmental stages (early-, mature- and postbreaker stages) whilst its immediate precursor, 2-hydroxy-1,4-naphthoquinone (lawsone) was mainly detected in mature leaves. Transcriptomes of I. balsamina derived from leaf, flower, and three capsule developmental stages were generated, totalling 59.643 Gb of raw reads that were assembled into 94,659 unigenes (595,828 transcripts). A total of 73.96% of unigenes were functionally annotated against seven public databases and 50,786 differentially expressed genes (DEGs) were identified. Expression profiles of 20 selected genes from four major secondary metabolism pathways were studied and validated using qRT-PCR method. Majority of the DHNA pathway genes were found to be significantly upregulated in early stage capsule compared to flower and leaf, suggesting tissue-specific synthesis of MNQ. Correlation analysis identified 11 candidate unigenes related to three enzymes (NADH-quinone oxidoreductase, UDP-glycosyltransferases and S-adenosylmethionine-dependent O-methyltransferase) important in the final steps of MNQ biosynthesis based on genes expression profiles consistent with MNQ content. This study provides the first molecular insight into the dynamics of MNQ biosynthesis and accumulation across different tissues of I. balsamina and serves as a valuable resource to facilitate further manipulation to increase production of MNQ.
    Matched MeSH terms: Gene Expression Profiling/methods
  13. Fulltext Preliminary study on the expression of endothelial cell biology related genes in the liver of dengue virus infected mice treated with Carica papaya leaf juice
    Mohd Abd Razak MR, Norahmad NA, Md Jelas NH, Jusoh B, Muhammad A, Mohmad Misnan N, et al.
    BMC Res Notes, 2019 Apr 03;12(1):206.
    PMID: 30944031 DOI: 10.1186/s13104-019-4242-z
    OBJECTIVE: The purpose of this study was to profile and identify the endothelial cell biology related genes that are affected by dengue virus infection in the liver tissue of AG129 mice, with and without Carica papaya leaf juice treatment.

    RESULTS: The dengue fever mouse model was established by intraperitoneal inoculation of dengue virus, New Guinea C strain at 2 × 106 PFU. Daily oral administration of 1000 mg/kg freeze-dried C. papaya leaf juice (FCPLJ) was done starting from day 1 to day 3 post infection. The RNA was extracted from liver tissues harvested on day 4 post infection. The expression levels of 84 genes related to mouse endothelial cell biology were determined by qRT-PCR technique. Dengue virus infection upregulated 15 genes and downregulated two genes in the liver of AG129 mice. The FCPLJ treatment upregulated monocyte chemoattractant protein 1 and downregulated intercellular adhesion molecule 1, integrin beta 3 and fibronectin 1 genes during dengue virus infection. The data showed the potential effect of FCPLJ treatment on the expression profile of endothelial cell biology related genes in the liver of dengue virus infected-AG129 mice. Further proteomic studies are needed to determine the functional roles of the genes affected by FCPLJ treatment.

    Matched MeSH terms: Gene Expression Profiling/methods
  14. Metabolomics and its role in understanding cellular responses in plants
    Bhalla R, Narasimhan K, Swarup S
    Plant Cell Rep, 2005 Dec;24(10):562-71.
    PMID: 16220342
    A natural shift is taking place in the approaches being adopted by plant scientists in response to the accessibility of systems-based technology platforms. Metabolomics is one such field, which involves a comprehensive non-biased analysis of metabolites in a given cell at a specific time. This review briefly introduces the emerging field and a range of analytical techniques that are most useful in metabolomics when combined with computational approaches in data analyses. Using cases from Arabidopsis and other selected plant systems, this review highlights how information can be integrated from metabolomics and other functional genomics platforms to obtain a global picture of plant cellular responses. We discuss how metabolomics is enabling large-scale and parallel interrogation of cell states under different stages of development and defined environmental conditions to uncover novel interactions among various pathways. Finally, we discuss selected applications of metabolomics.
    Matched MeSH terms: Gene Expression Profiling/methods
  15. Fulltext A review of feature extraction software for microarray gene expression data
    Tan CS, Ting WS, Mohamad MS, Chan WH, Deris S, Shah ZA
    Biomed Res Int, 2014;2014:213656.
    PMID: 25250315 DOI: 10.1155/2014/213656
    When gene expression data are too large to be processed, they are transformed into a reduced representation set of genes. Transforming large-scale gene expression data into a set of genes is called feature extraction. If the genes extracted are carefully chosen, this gene set can extract the relevant information from the large-scale gene expression data, allowing further analysis by using this reduced representation instead of the full size data. In this paper, we review numerous software applications that can be used for feature extraction. The software reviewed is mainly for Principal Component Analysis (PCA), Independent Component Analysis (ICA), Partial Least Squares (PLS), and Local Linear Embedding (LLE). A summary and sources of the software are provided in the last section for each feature extraction method.
    Matched MeSH terms: Gene Expression Profiling/methods*
  16. Feasibility of the salivary transcriptome as a novel biomarker in determining disease susceptibility
    Hidayat MFH, Milne T, Cullinan MP, Seymour GJ
    J Periodontal Res, 2018 Jun;53(3):369-377.
    PMID: 29280135 DOI: 10.1111/jre.12522
    BACKGROUND AND OBJECTIVE: The salivary transcriptome may present as a readily available and non-invasive source of potential biomarkers. The development of chronic periodontitis is determined by individual patient susceptibility; hence, the aim of this study was to determine the potential of the salivary transcriptome as a biomarker of disease susceptibility using chronic periodontitis as an example.

    MATERIAL AND METHODS: Using an Oragene® RNA kit, the total RNA was purified from the saliva of 10 patients with chronic periodontitis and 10 patients without chronic periodontitis. The quantity and quality of the total RNA was determined, and a measure of gene expression via cDNA was undertaken using the Affymetrix microarray system. The microarray profiling result was further validated by real-time quantitative polymerase chain reaction.

    RESULTS: Spectrophotometric analysis showed the total RNA purified from each participant ranged from 0.92 μg/500 μL to 62.85 μg/500 μL. There was great variability in the quantity of total RNA obtained from the 2 groups in the study with a mean of 10.21 ± 12.71 μg/500 μL for the periodontitis group and 15.97 ± 23.47 μg/500 μL for the control group. Further the RNA purity (based on the A260 /A280 ratio) for the majority of participants (9 periodontitis and 6 controls) were within the acceptable limits for downstream analysis (2.0 ± 0.1). The study samples, showed 2 distinct bands at 23S (3800 bp) and 16S (1500 bp) characteristic of bacterial rRNA. Preliminary microarray analysis was performed for 4 samples (P2, P6, H5 and H9). The percentage of genes present in each of the 4 samples was not consistent with about 1.8%-18.7% of genes being detected. Quantitative real-time polymerase chain reaction confirmed that the total RNA purified from each sample was mainly bacterial RNA (Uni 16S) with minimal human mRNA.

    CONCLUSION: This study showed that minimal amounts of human RNA were able to be isolated from the saliva of patients with periodontitis as well as controls. Further work is required to enhance the extraction process of human mRNA from saliva if the salivary transcriptome is to be used in determining individual patient susceptibility.

    Matched MeSH terms: Gene Expression Profiling/methods*
  17. Fulltext Interferon-stimulated gene of 20 kDa protein (ISG20) degrades RNA of hepatitis B virus to impede the replication of HBV in vitro and in vivo
    Leong CR, Funami K, Oshiumi H, Mengao D, Takaki H, Matsumoto M, et al.
    Oncotarget, 2016 10 18;7(42):68179-68193.
    PMID: 27626689 DOI: 10.18632/oncotarget.11907
    Hepatitis B virus (HBV) barely induces host interferon (IFN)-stimulated genes (ISGs), which allows efficient HBV replication in the immortalized mouse hepatocytes as per human hepatocytes. Here we found that transfection of Isg20 plasmid robustly inhibits the HBV replication in HBV-infected hepatocytes irrespective of IRF3 or IFN promoter activation. Transfection of Isg20 is thus effective to eradicate HBV in the infected hepatocytes. Transfection of HBV genome or ε-stem of HBV pgRNA (active pgRNA moiety) failed to induce Isg20 in the hepatocytes, while control polyI:C (a viral dsRNA analogue mimic) activated MAVS pathway leading to production of type I IFN and then ISGsg20 via the IFN-α/β receptor (IFNAR). Consistently, addition of IFN-α induced Isg20 and partially suppressed HBV replication in hepatocytes. Chasing HBV RNA, DNA and proteins by blotting indicated that ISG20 expression decreased HBV RNA and replicative DNA in HBV-transfected cells, which resulted in low HBs antigen production and virus titer. The exonuclease domains of ISG20 mainly participated in HBV-RNA decay. In vivo hydrodynamic injection, ISG20 was crucial for suppressing HBV replication without degrading host RNA in the liver. Taken together, ISG20 acts as an innate anti-HBV effector that selectively degrades HBV RNA and blocks replication of infectious HBV particles. ISG20 would be a critical effector for ameliorating chronic HBV infection in the IFN therapy.
    Matched MeSH terms: Gene Expression Profiling/methods
  18. Using fuzzy association rule mining in cancer classification
    Mahmoodian H, Hamiruce Marhaban M, Abdulrahim R, Rosli R, Saripan I
    Australas Phys Eng Sci Med, 2011 Apr;34(1):41-54.
    PMID: 21327594 DOI: 10.1007/s13246-011-0054-8
    The classification of the cancer tumors based on gene expression profiles has been extensively studied in numbers of studies. A wide variety of cancer datasets have been implemented by the various methods of gene selection and classification to identify the behavior of the genes in tumors and find the relationships between them and outcome of diseases. Interpretability of the model, which is developed by fuzzy rules and linguistic variables in this study, has been rarely considered. In addition, creating a fuzzy classifier with high performance in classification that uses a subset of significant genes which have been selected by different types of gene selection methods is another goal of this study. A new algorithm has been developed to identify the fuzzy rules and significant genes based on fuzzy association rule mining. At first, different subset of genes which have been selected by different methods, were used to generate primary fuzzy classifiers separately and then proposed algorithm was implemented to mix the genes which have been associated in the primary classifiers and generate a new classifier. The results show that fuzzy classifier can classify the tumors with high performance while presenting the relationships between the genes by linguistic variables.
    Matched MeSH terms: Gene Expression Profiling/methods*
  19. Fulltext Biases in small RNA deep sequencing data
    Raabe CA, Tang TH, Brosius J, Rozhdestvensky TS
    Nucleic Acids Res, 2014 Feb;42(3):1414-26.
    PMID: 24198247 DOI: 10.1093/nar/gkt1021
    High-throughput RNA sequencing (RNA-seq) is considered a powerful tool for novel gene discovery and fine-tuned transcriptional profiling. The digital nature of RNA-seq is also believed to simplify meta-analysis and to reduce background noise associated with hybridization-based approaches. The development of multiplex sequencing enables efficient and economic parallel analysis of gene expression. In addition, RNA-seq is of particular value when low RNA expression or modest changes between samples are monitored. However, recent data uncovered severe bias in the sequencing of small non-protein coding RNA (small RNA-seq or sRNA-seq), such that the expression levels of some RNAs appeared to be artificially enhanced and others diminished or even undetectable. The use of different adapters and barcodes during ligation as well as complex RNA structures and modifications drastically influence cDNA synthesis efficacies and exemplify sources of bias in deep sequencing. In addition, variable specific RNA G/C-content is associated with unequal polymerase chain reaction amplification efficiencies. Given the central importance of RNA-seq to molecular biology and personalized medicine, we review recent findings that challenge small non-protein coding RNA-seq data and suggest approaches and precautions to overcome or minimize bias.
    Matched MeSH terms: Gene Expression Profiling/methods*
  20. Fulltext Predicting the clinical outcome of oral potentially malignant disorders using transcriptomic-based molecular pathology
    Sathasivam HP, Kist R, Sloan P, Thomson P, Nugent M, Alexander J, et al.
    Br J Cancer, 2021 Aug;125(3):413-421.
    PMID: 33972745 DOI: 10.1038/s41416-021-01411-z
    BACKGROUND: This study was undertaken to develop and validate a gene expression signature that characterises oral potentially malignant disorders (OPMD) with a high risk of undergoing malignant transformation.

    METHODS: Patients with oral epithelial dysplasia at one hospital were selected as the 'training set' (n = 56) whilst those at another hospital were selected for the 'test set' (n = 66). RNA was extracted from formalin-fixed paraffin-embedded (FFPE) diagnostic biopsies and analysed using the NanoString nCounter platform. A targeted panel of 42 genes selected on their association with oral carcinogenesis was used to develop a prognostic gene signature. Following data normalisation, uni- and multivariable analysis, as well as prognostic modelling, were employed to develop and validate the gene signature.

    RESULTS: A prognostic classifier composed of 11 genes was developed using the training set. The multivariable prognostic model was used to predict patient risk scores in the test set. The prognostic gene signature was an independent predictor of malignant transformation when assessed in the test set, with the high-risk group showing worse prognosis [Hazard ratio = 12.65, p = 0.0003].

    CONCLUSIONS: This study demonstrates proof of principle that RNA extracted from FFPE diagnostic biopsies of OPMD, when analysed on the NanoString nCounter platform, can be used to generate a molecular classifier that stratifies the risk of malignant transformation with promising clinical utility.

    Matched MeSH terms: Gene Expression Profiling/methods*
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