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  • 1.
    Jurcevic, Sanja
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre. Örebro universitet, Institutionen för hälsovetenskap och medicin.
    MicroRNA expression profiling in endometrial adenocarcinoma2015Doctoral thesis, comprehensive summary (Other academic)
  • 2.
    Jurcevic, Sanja
    et al.
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Klinga-Levan, Karin
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Olsson, Björn
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Ejeskär, Katarina
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Verification of microRNA expression in human endometrial adenocarcinoma2016In: BMC Cancer, ISSN 1471-2407, E-ISSN 1471-2407, Vol. 16, no 1, article id 261Article in journal (Refereed)
  • 3.
    Jurcevic, Sanja
    et al.
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Olsson, Björn
    University of Skövde, The Systems Biology Research Centre. University of Skövde, School of Bioscience.
    Klinga-Levan, Karin
    University of Skövde, The Systems Biology Research Centre. University of Skövde, School of Bioscience.
    MicroRNA expression in human endometrial adenocarcinoma2014In: Cancer Cell International, ISSN 1475-2867, E-ISSN 1475-2867, Vol. 14, no 1, article id 88Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: MicroRNAs are small non-coding RNAs that play crucial roles in the pathogenesis of different cancer types. The aim of this study was to identify miRNAs that are differentially expressed in endometrial adenocarcinoma compared to healthy endometrium. These miRNAs can potentially be used to develop a panel for classification and prognosis in order to better predict the progression of the disease and facilitate the choice of treatment strategy.

    METHODS: Formalin fixed paraffin embedded endometrial tissue samples were collected from the Örebro university hospital. QPCR was used to quantify the expression levels of 742 miRNAs in 30 malignant and 20 normal endometrium samples. After normalization of the qPCR data, miRNAs differing significantly in expression between normal and cancer samples were identified, and hierarchical clustering analysis was used to identify groups of miRNAs with coordinated expression profiles.

    RESULTS: In comparisons between endometrial adenocarcinoma and normal endometrium samples 138 miRNAs were found to be significantly differentially expressed (p < 0.001) among which 112 miRNAs have not been previous reported for endometrial adenocarcinoma.

    CONCLUSION: Our study shows that several miRNAs are differentially expressed in endometrial adenocarcinoma. These identified miRNA hold great potential as target for classification and prognosis of this disease. Further analysis of the differentially expressed miRNA and their target genes will help to derive new biomarkers that can be used for classification and prognosis of endometrial adenocarcinoma.

  • 4.
    Jurcevic, Sanja
    et al.
    University of Skövde, School of Life Sciences. University of Skövde, The Systems Biology Research Centre.
    Olsson, Björn
    University of Skövde, School of Life Sciences. University of Skövde, The Systems Biology Research Centre.
    Klinga-Levan, Karin
    University of Skövde, School of Life Sciences. University of Skövde, The Systems Biology Research Centre.
    Validation of Suitable Endogenous Control Genes for Quantitative PCR Analysis of microRNA gene expression in a rat model of endometrial cancer2013In: Cancer Cell International, ISSN 1475-2867, E-ISSN 1475-2867, Vol. 13, article id 45Article in journal (Refereed)
    Abstract [en]

    Background

    MicroRNAs are small RNA molecules that negatively regulate gene expression by translational inhibition or mRNA cleavage. The discovery that abnormal expression of particular miRNAs contributes to human disease, including cancer, has spurred growing interest in analysing expression profiles of these molecules. Quantitative polymerase chain reaction is frequently used for quantification of miRNA expression due to its sensitivity and specificity. To minimize experimental error in this system an appropriate endogenous control gene must be chosen. An ideal endogenous control gene should be expressed at a constant level across all samples and its expression stability should be unaffected by the experimental procedure.

    Results

    The expression and validation of candidate control genes (4.5S RNA(H) A, Y1, 4.5S RNA(H) B, snoRNA, U87 and U6) was examined in 21 rat cell lines to establish the most suitable endogenous control for miRNA analysis in a rat model of cancer. The stability of these genes was analysed using geNorm and NormFinder algorithms. U87 and snoRNA were identified as the most stable control genes, while Y1 was least stable.

    Conclusion

    This study identified the control gene that is most suitable for normalizing the miRNA expression data in rat. That reference gene will be useful when miRNAs expression are analyzed in order to find new miRNA markers for endometrial cancer in rat.

  • 5.
    Ulfenborg, Benjamin
    et al.
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Jurcevic, Sanja
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Lindelöf, Angelica
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Klinga-Levan, Karin
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    Olsson, Björn
    University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre.
    miREC: a database of miRNAs involved in the development of endometrial cancer2015In: BMC Research Notes, ISSN 1756-0500, E-ISSN 1756-0500, Vol. 8, no 1, article id 104Article in journal (Refereed)
    Abstract [en]

    Background

    Endometrial cancer (EC) is the most frequently diagnosed gynecological malignancy and the fourth most common cancer diagnosis overall among women. As with many other forms of cancer, it has been shown that certain miRNAs are differentially expressed in EC and these miRNAs are believed to play important roles as regulators of processes involved in the development of the disease. With the rapidly growing number of studies of miRNA expression in EC, there is a need to organize the data, combine the findings from experimental studies of EC with information from various miRNA databases, and make the integrated information easily accessible for the EC research community.

    Findings

    The miREC database is an organized collection of data and information about miRNAs shown to be differentially expressed in EC. The database can be used to map connections between miRNAs and their target genes in order to identify specific miRNAs that are potentially important for the development of EC. The aim of the miREC database is to integrate all available information about miRNAs and target genes involved in the development of endometrial cancer, and to provide a comprehensive, up-to-date, and easily accessible source of knowledge regarding the role of miRNAs in the development of EC. Database URL: http://www.mirecdb.orgwebcite.

    Conclusions

    Several databases have been published that store information about all miRNA targets that have been predicted or experimentally verified to date. It would be a time-consuming task to navigate between these different data sources and literature to gather information about a specific disease, such as endometrial cancer. The miREC database is a specialized data repository that, in addition to miRNA target information, keeps track of the differential expression of genes and miRNAs potentially involved in endometrial cancer development. By providing flexible search functions it becomes easy to search for EC-associated genes and miRNAs from different starting points, such as differential expression and genomic loci (based on genomic aberrations).

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