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Search: WFRF:(Huhtinen M) > (2020-2022)

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  • Gabriel, M., et al. (author)
  • A relational database to identify differentially expressed genes in the endometrium and endometriosis lesions
  • 2020
  • In: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 7
  • Journal article (peer-reviewed)abstract
    • Endometriosis is a common inflammatory estrogen-dependent gynecological disorder, associated with pelvic pain and reduced fertility in women. Several aspects of this disorder and its cellular and molecular etiology remain unresolved. We have analyzed the global gene expression patterns in the endometrium, peritoneum and in endometriosis lesions of endometriosis patients and in the endometrium and peritoneum of healthy women. In this report, we present the EndometDB, an interactive web-based user interface for browsing the gene expression database of collected samples without the need for computational skills. The EndometDB incorporates the expression data from 115 patients and 53 controls, with over 24000 genes and clinical features, such as their age, disease stages, hormonal medication, menstrual cycle phase, and the different endometriosis lesion types. Using the web-tool, the end-user can easily generate various plot outputs and projections, including boxplots, and heatmaps and the generated outputs can be downloaded in pdf-format.
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  • Jain, S., et al. (author)
  • Diagnostic potential of nanoparticle aided assays for MUC16 and MUC1 glycovariants in ovarian cancer
  • 2022
  • In: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 151:7, s. 1175-1184
  • Journal article (peer-reviewed)abstract
    • Our study reports the discovery and evaluation of nanoparticle aided sensitive assays for glycovariants of MUC16 and MUC1 in a unique collection of paired ovarian cyst fluids and serum samples obtained at or prior to surgery for ovarian carcinoma suspicion. Selected glycovariants and the immunoassays for CA125, CA15-3 and HE4 were compared and validated in 347 cyst fluid and serum samples. Whereas CA125 and CA15-3 performed poorly in cyst fluid to separate carcinoma and controls, four glycovariants including MUC16(MGL), MUC16(STn), MUC1(STn) and MUC1(Tn) provided highly improved separations. In serum, the two STn glycovariants outperformed conventional CA125, CA15-3 and HE4 assays in all subcategories analyzed with main benefits obtained at high specificities and at postmenopausal and early-stage disease. Serum MUC16(STn) performed best at high specificity (90%-99%), but sensitivity was also improved by the other glycovariants and CA15-3. The highly improved specificity, excellent analytical sensitivity and robustness of the nanoparticle assisted glycovariant assays carry great promise for improved identification and early detection of ovarian carcinoma in routine differential diagnostics.
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