Molecular profiling of human endometrium and endometriosis

Endometriosis is a common hormone-dependent gynecological disease leading to severe menstrual and/or chronic pelvic pain with or without subfertility. The disease is defined by the presence of endometrium-like tissue outside the uterine cavity, primarily on the pelvic peritoneum, ovaries and infiltrating organs of the peritoneal cavity. The current tools for diagnosis and treatment of endometriosis need to be improved to ensure reliable diagnosis and effective treatment. In addition, endometriosis is associated with increased risk of ovarian cancer and, therefore, the differential diagnosis between the benign and malignant ovarian cysts is of importance. The long-term objective of the present study was to support the discovery of novel tools for diagnosis and treatment of endometriosis. This was approached by exploiting genome-wide expression analysis of endometriosis specimens. A novel expression profiling -based classification of endometriosis indicated specific subgroups of lesions partially consistent with the clinical appearance, but partially according to unknown factors. The peritoneum of women with endometriosis appeared to be altered in comparison to that of healthy control subjects, suggesting a novel aspect on the pathogenesis of the disease. The evaluation of action and metabolism of sex hormones in endometrium and endometriosis tissue indicated a novel role of androgens in regulation of the tissues. In addition, an enzyme involved in androgen and neurosteroid metabolism, hydroxysteroid (17beta) dehydrogenase 6, was found to be highly up-regulated in endometriosis tissue as compared to healthy endometrium. The enzyme may have a role in the pathogenesis of endometriosis or in the endometriosis associated pain generation. Finally, a new diagnostic biomarker, HE4, was discovered distinguishing patients with ovarian endometriotic cysts from those with malignant ovarian cancer. The information acquired in this study enables deeper understanding of endometriosis and facilitates the development of improved diagnostic tools and more specific treatments of the diseaseSiirretty Doriast

HE4 in the evaluation of tumor load and prognostic stratification of high grade serous ovarian carcinoma

Objective Human epididymis protein 4 (HE4) is a validated, complementary biomarker to cancer antigen 125 (CA125) for high grade serous ovarian carcinoma (HGSC). Currently, there are insufficient data on the utility of longitudinal HE4 measurement during HGSC treatment and follow up. We set to provide a comprehensive analysis on the kinetics and prognostic performance of HE4 with serial measurements during HGSC treatment and follow up. Methods This prospective study included 143 patients with advanced HGSC (ClinicalTrials.gov identifier: NCT01276574). Serum CA125 and HE4 were measured at baseline, before each cycle of chemotherapy and during follow up until first progression. Baseline biomarker values were compared to the tumor load assessed during surgery and to residual disease. Biomarker nadir values and concentrations at progression were correlated to survival. Results The baseline HE4 concentration distinguished patients with a high tumor load from patients with a low tumor load assessed during surgery (pPeer reviewe

Aggressive and recurrent ovarian cancers upregulate ephrinA5, a non-canonical effector of EphA2 signaling duality

Erythropoietin producing hepatocellular (Eph) receptors and their membrane-bound ligands ephrins are variably expressed in epithelial cancers, with context-dependent implications to both tumor-promoting and-suppressive processes in ways that remain incompletely understood. Using ovarian cancer tissue microarrays and longitudinally collected patient cells, we show here that ephrinA5/EFNA5 is specifically overexpressed in the most aggressive high-grade serous carcinoma (HGSC) subtype, and increased in the HGSC cells upon disease progression. Among all the eight ephrin genes, high EFNA5 expression was most strongly associated with poor overall survival in HGSC patients from multiple independent datasets. In contrast, high EFNA3 predicted improved overall and progression-free survival in The Cancer Genome Atlas HGSC dataset, as expected for a canonical inducer of tumor-suppressive Eph receptor tyrosine kinase signaling. While depletion of either EFNA5 or the more extensively studied, canonically acting EFNA1 in HGSC cells increased the oncogenic EphA2-S897 phosphorylation, EFNA5 depletion left unaltered, or even increased the ligand-dependent EphA2-Y588 phosphorylation. Moreover, treatment with recombinant ephrinA5 led to limited EphA2 tyrosine phosphorylation, internalization and degradation compared to ephrinA1. Altogether, our results suggest a unique function for ephrinA5 in Eph-ephrin signaling and highlight the clinical potential of ephrinA5 as a cell surface biomarker in the most aggressive HGSCs.Peer reviewe

QuantISH : RNA in situ hybridization image analysis framework for quantifying cell type-specific target RNA expression and variability

RNA in situ hybridization (RNA-ISH) is a powerful spatial transcriptomics technology to characterize target RNA abundance and localization in individual cells. This allows analysis of tumor heterogeneity and expression localization, which are not readily obtainable through transcriptomic data analysis. RNA-ISH experiments produce large amounts of data and there is a need for automated analysis methods. Here we present QuantISH, a comprehensive open-source RNA-ISH image analysis pipeline that quantifies marker expressions in individual carcinoma, immune, and stromal cells on chromogenic or fluorescent in situ hybridization images. QuantISH is designed to be modular and can be adapted to various image and sample types and staining protocols. We show that in chromogenic RNA in situ hybridization images of high-grade serous carcinoma (HGSC) QuantISH cancer cell classification has high precision, and signal expression quantification is in line with visual assessment. We further demonstrate the power of QuantISH by showing that CCNE1 average expression and DDIT3 expression variability, as captured by the variability factor developed herein, act as candidate biomarkers in HGSC. Altogether, our results demonstrate that QuantISH can quantify RNA expression levels and their variability in carcinoma cells, and thus paves the way to utilize RNA-ISH technology.Peer reviewe

Interactions between inflammatory signals and the progesterone receptor in regulating gene expression in pregnant human uterine myocytes

The absence of a fall in circulating progesterone levels has led to the concept that human labour is associated with ‘functional progesterone withdrawal’ caused through changes in the expression or function of progesterone receptor (PR). At the time of labour, the human uterus is heavily infiltrated with inflammatory cells, which release cytokines to create a ‘myometrial inflammation’ via NF-κB activation. The negative interaction between NF-κB and PR, may represent a mechanism to account for ‘functional progesterone withdrawal’ at term. Conversely, PR may act to inhibit NF-κB function and so play a role in inhibition of myometrial inflammation during pregnancy. To model this inter-relationship, we have used small interfering (si) RNA-mediated knock-down of PR in human pregnant myocytes and whole genome microarray analysis to identify genes regulated through PR. We then activated myometrial inflammation using IL-1β stimulation to determine the role of PR in myometrial inflammation regulation. Through PR-knock-down, we found that PR regulates gene networks involved in myometrial quiescence and extracellular matrix integrity. Activation of myometrial inflammation was found to antagonize PR-induced gene expression, of genes normally upregulated via PR. We found that PR does not play a role in repression of pro-inflammatory gene networks induced by IL-1β and that only MMP10 was significantly regulated in opposite directions by IL-1β and PR. We conclude that progesterone acting through PR does not generally inhibit myometrial inflammation. Activation of myometrial inflammation does cause ‘functional progesterone withdrawal’ but only in the context of genes normally upregulated via PR

Diagnostic potential of nanoparticle aided assays for MUC16 and MUC1 glycovariants in ovarian cancer

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.Peer reviewe

HE4 in the evaluation of tumor load and prognostic stratification of high grade serous ovarian carcinoma

Objective Human epididymis protein 4 (HE4) is a validated, complementary biomarker to cancer antigen 125 (CA125) for high grade serous ovarian carcinoma (HGSC). Currently, there are insufficient data on the utility of longitudinal HE4 measurement during HGSC treatment and follow up. We set to provide a comprehensive analysis on the kinetics and prognostic performance of HE4 with serial measurements during HGSC treatment and follow up. Methods This prospective study included 143 patients with advanced HGSC (ClinicalTrials.gov identifier: NCT01276574). Serum CA125 and HE4 were measured at baseline, before each cycle of chemotherapy and during follow up until first progression. Baseline biomarker values were compared to the tumor load assessed during surgery and to residual disease. Biomarker nadir values and concentrations at progression were correlated to survival. Results The baseline HE4 concentration distinguished patients with a high tumor load from patients with a low tumor load assessed during surgery (p<.0001). The baseline CA125 level was not associated with tumor load to a similar extent (p=.067). At progression, the HE4 level was an independent predictor of worse survival in the multivariate analysis (p=.002). All patients that were alive 3 years post-progression had a serum HE4 concentration below 199.20 pmol/l at the 1st recurrence. Conclusion HE4 is a feasible biomarker in the treatment monitoring and prognostic stratification of patients with HGSC. Specifically, the serum level of HE4 at first relapse was associated with the survival of patients and it may be a useful complementary tool in the selection of second line treatments. This is to the best of our knowledge the first time this finding has been reported

FUNGI : FUsioN Gene Integration toolset

Motivation: Fusion genes are both useful cancer biomarkers and important drug targets. Finding relevant fusion genes is challenging due to genomic instability resulting in a high number of passenger events. To reveal and prioritize relevant gene fusion events we have developed FUsionN Gene Identification toolset (FUNGI) that uses an ensemble of fusion detection algorithms with prioritization and visualization modules. Results: We applied FUNGI to an ovarian cancer dataset of 107 tumor samples from 36 patients. Ten out of 11 detected and prioritized fusion genes were validated. Many of detected fusion genes affect the PI3K-AKT pathway with potential role in treatment resistance.Peer reviewe

New national and regional biological records for Finland 5. Contributions to agaricoid and ascomycetoid taxa of fungi 4

One genera of agaricoid fungi (Basidiomycota): Romagnesiella and 12 species are reported as new to Finland: Agaricus macrocarpus, Arrhenia obatra, Arrhenia obscurata, Arrhenia rigidipes, Coprinellus brevisetulosus, Coprinus candidatus, Entoloma plebejum, Hydnum vesterholtii, Inocybe phaeocystidiosa, Mycena clavata, Omphalina arctica and Romagnesiella clavus. Two genera of ascomycetoid fungi (Ascomycota): Strossmayeria, Phaeomollisia and 8 species are reported as new to Finland: Arachnopeziza delicatula, Hyaloscypha diabolica, Hyalopeziza cf. tianschanica, Phaeomollisia piceae, Phialina pseudopuberula, Sphaeropezia hepaticarum, Strossmayeria basitricha and Trichopeziza subsulphurea. Information of species recently published elsewhere: Cortinarius angustisporus, C. cacaodiscus, C. caesioarmeniacus, C. centrirufus, C. crassisporus, C. cruentiphyllus, C. davemallochii, C. ferrugineovelatus, C. furvus, C. fuscescens, C. murinascens, C. privignipallens, C. pseudofervidus, C. roseivelatus, C. roseocastaneus, C. subbrunneoideus, C. subexitiosus, C. squamivenetus, C. uraceisporus, Hebeloma eburneum, H. salicicola, Hygrophorus exiguus and Psathyrella fennoscandica is brought here together. New records of little collected and rare taxa Coprinopsis patouillardii, Cuphophyllus cinerellus, Galerina perplexa, Galerina pruinatipes, Gorgoniceps hypothallosa, Inocybe boreocarelica, Marasmius setosus, Psathyrella potteri, Psathyrella tenuicula, Russula adulterina, Russula pyriodora, Scutellinia trechispora, Sowerbyella imperialis and Volvariella murinella are also listed. Corrections of previous information are given on: Cortinarius angulosus (under C. duristipes), Coprinopsis patouillardii and Psathyrella potteri

A relational database to identify differentially expressed genes in the endometrium and endometriosis lesions

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.Peer reviewe