Kan lederskap ha påvirkning på sykefravær?

I denne oppgaven skal jeg ta for meg følgende problemstilling; Hvordan kan lederskap påvirke sykefraværet i Norge? Oppgaven tar for seg en studie av IA-avtalens første delmål som handler om å minimere sykefraværet med 10% i forhold til 2018 og lederskap. Den tar for seg hvordan lederens erfaringer og leders stiler kan påvirke mediearbeidene, og ulike faktorer som omhandlet dette. Studie tar for seg ulike perspektiver til hvordan disse kan være en faktor for individets psykiske og fysiske helse. Studiet tar for seg organisasjoner, sett fra medarbeidernes ståsted, og ikke hvilke meninger ledelsene har rundt dette. Min konklusjon etter å ha sett på ulike studier og observasjoner at lederskap kan ha en stor påvirkningsfaktor for sykefraværet i en bedrift. Dette basert de ulike studiene jeg har tatt for meg

Matrix Metalloproteinase 13 Is Induced in Fibroblasts in Polyomavirus Middle T Antigen-Driven Mammary Carcinoma without Influencing Tumor Progression

Matrix metalloproteinase (MMP) 13 (collagenase 3) is an extracellular matrix remodeling enzyme that is induced in myofibroblasts during the earliest invasive stages of human breast carcinoma, suggesting that it is involved in tumor progression. During progression of mammary carcinomas in the polyoma virus middle T oncogene mouse model (MMTV-PyMT), Mmp13 mRNA was strongly upregulated concurrently with the transition to invasive and metastatic carcinomas. As in human tumors, Mmp13 mRNA was found in myofibroblasts of invasive grade II and III carcinomas, but not in benign grade I and II mammary intraepithelial neoplasias. To determine if MMP13 plays a role in tumor progression, we crossed MMTV-PyMT mice with Mmp13 deficient mice. The absence of MMP13 did not influence tumor growth, vascularization, progression to more advanced tumor stages, or metastasis to the lungs, and the absence of MMP13 was not compensated for by expression of other MMPs or tissue inhibitor of metalloproteinases. However, an increased fraction of thin collagen fibrils was identified in MMTV-PyMT;Mmp13−/− compared to MMTV-PyMT;Mmp13+/+ tumors, showing that collagen metabolism was altered in the absence of MMP13. We conclude that the expression pattern of Mmp13 mRNA in myofibroblasts of invasive carcinomas in the MMTV-PyMT breast cancer model recapitulates the expression pattern observed in human breast cancer. Our results suggest that MMP13 is a marker of carcinoma-associated myofibroblasts of invasive carcinoma, even though it does not make a major contribution to tumor progression in the MMTV-PyMT breast cancer model

Regulated expression of a transgene introduced on an oriP/EBNA-1 PAC shuttle vector into human cells

<p>Abstract</p> <p>Background</p> <p>Sequencing of the human genome has led to most genes being available in BAC or PAC vectors. However, limited functional information has been assigned to most of these genes. Techniques for the manipulation and transfer of complete functional units on large DNA fragments into human cells are crucial for the analysis of complete genes in their natural genomic context. One limitation of the functional studies using these vectors is the low transfection frequency.</p> <p>Results</p> <p>We have constructed a shuttle vector, pPAC7, which contains both the <it>EBNA-1 </it>gene and <it>ori</it>P from the Epstein-Barr virus allowing stable maintenance of PAC clones in the nucleus of human cells. The pPAC7 vector also contains the <it>EGFP </it>reporter gene, which allows direct monitoring of the presence of PAC constructs in transfected cells, and the <it>Bsr</it>-cassette that allows highly efficient and rapid selection in mammalian cells by use of blasticidin. Positive selection for recombinant PAC clones is obtained in pPAC7 because the cloning sites are located within the SacBII gene. We show regulated expression of the <it>CDH3 </it>gene carried as a 132 kb genomic insert cloned into pPAC7, demonstrating that the pPAC7 vector can be used for functional studies of genes in their natural genomic context. Furthermore, the results from the transfection of a range of pPAC7 based constructs into two human cell lines suggest that the transfection efficiencies are not only dependent on construct size.</p> <p>Conclusion</p> <p>The shuttle vector pPAC7 can be used to transfer large genomic constructs into human cells. The genes transferred could potentially contain all long-range regulatory elements, including their endogenous regulatory promoters. Introduction of complete genes in PACs into human cells would potentially allow complementation assays to identify or verify the function of genes affecting cellular phenotypes.</p

Visualizing stromal cell dynamics in different tumor microenvironments by spinning disk confocal microscopy

The tumor microenvironment consists of stromal cells and extracellular factors that evolve in parallel with carcinoma cells. To gain insights into the activities of stromal cell populations, we developed and applied multicolor imaging techniques to analyze the behavior of these cells within different tumor microenvironments in the same live mouse. We found that regulatory T-lymphocytes (Tregs) migrated in proximity to blood vessels. Dendriticlike cells, myeloid cells and carcinoma-associated fibroblasts all exhibited higher motility in the microenvironment at the tumor periphery than within the tumor mass. Since oxygen levels differ between tumor microenvironments, we tested if acute hypoxia could account for the differences in cell migration. Direct visualization revealed that Tregs ceased migration under acute systemic hypoxia, whereas myeloid cells continued migrating. In the same mouse and microenvironment, we experimentally subdivided the myeloid cell population and revealed that uptake of fluorescent dextran defined a low-motility subpopulation expressing markers of tumor-promoting, alternatively activated macrophages. In contrast, fluorescent anti-Gr1 antibodies marked myeloid cells patrolling inside tumor vessels and in the stroma. Our techniques allow real-time combinatorial analysis of cell populations based on spatial location, gene expression, behavior and cell surface molecules within intact tumors. The techniques are not limited to investigations in cancer, but could give new insights into cell behavior more broadly in development and disease

DNA ploidy and PTEN as biomarkers for predicting aggressive disease in prostate cancer patients under active surveillance

Background: Current risk stratification tools for prostate cancer patients under active surveillance (AS) may inadequately identify those needing treatment. We investigated DNA ploidy and PTEN as potential biomarkers to predict aggressive disease in AS patients. Methods: We assessed DNA ploidy by image cytometry and PTEN protein expression by immunohistochemistry in 3197 tumour-containing tissue blocks from 558 patients followed in AS at a Norwegian local hospital. The primary endpoint was treatment, with treatment failure (biochemical recurrence or initiation of salvage therapy) as the secondary endpoint. Results: The combined DNA ploidy and PTEN (DPP) status at diagnosis was associated with treatment-free survival in univariable- and multivariable analysis, with a HR for DPP-aberrant vs. DPP-normal tumours of 2.12 (p < 0.0001) and 1.94 (p < 0.0001), respectively. Integration of DNA ploidy and PTEN status with the Cancer of the Prostate Risk Assessment (CAPRA) score improved risk stratification (c-index difference = 0.025; p = 0.0033). Among the treated patients, those with DPP-aberrant tumours exhibited a significantly higher likelihood of treatment failure (HR 2.01; p = 0.027). Conclusions: DNA ploidy and PTEN could serve as additional biomarkers to identify AS patients at increased risk of developing aggressive disease, enabling earlier intervention for nearly 50% of the patients that will eventually receive treatment with current protocol

Deep learning for prediction of colorectal cancer outcome: a discovery and validation study

Background Improved markers of prognosis are needed to stratify patients with early-stage colorectal cancer to refine selection of adjuvant therapy. The aim of the present study was to develop a biomarker of patient outcome after primary colorectal cancer resection by directly analysing scanned conventional haematoxylin and eosin stained sections using deep learning. Methods More than 12 000 000 image tiles from patients with a distinctly good or poor disease outcome from four cohorts were used to train a total of ten convolutional neural networks, purpose-built for classifying supersized heterogeneous images. A prognostic biomarker integrating the ten networks was determined using patients with a non-distinct outcome. The marker was tested on 920 patients with slides prepared in the UK, and then independently validated according to a predefined protocol in 1122 patients treated with single-agent capecitabine using slides prepared in Norway. All cohorts included only patients with resectable tumours, and a formalin-fixed, paraffin-embedded tumour tissue block available for analysis. The primary outcome was cancer-specific survival. Findings 828 patients from four cohorts had a distinct outcome and were used as a training cohort to obtain clear ground truth. 1645 patients had a non-distinct outcome and were used for tuning. The biomarker provided a hazard ratio for poor versus good prognosis of 3·84 (95% CI 2·72–5·43; p<0·0001) in the primary analysis of the validation cohort, and 3·04 (2·07–4·47; p<0·0001) after adjusting for established prognostic markers significant in univariable analyses of the same cohort, which were pN stage, pT stage, lymphatic invasion, and venous vascular invasion. Interpretation A clinically useful prognostic marker was developed using deep learning allied to digital scanning of conventional haematoxylin and eosin stained tumour tissue sections. The assay has been extensively evaluated in large, independent patient populations, correlates with and outperforms established molecular and morphological prognostic markers, and gives consistent results across tumour and nodal stage. The biomarker stratified stage II and III patients into sufficiently distinct prognostic groups that potentially could be used to guide selection of adjuvant treatment by avoiding therapy in very low risk groups and identifying patients who would benefit from more intensive treatment regimes

Chromatin organisation and cancer prognosis: a pan-cancer study

Background: Chromatin organisation affects gene expression and regional mutation frequencies and contributes to carcinogenesis. Aberrant organisation of DNA has been correlated with cancer prognosis in analyses of the chromatin component of tumour cell nuclei using image texture analysis. As yet, the methodology has not been sufficiently validated to permit its clinical application. We aimed to define and validate a novel prognostic biomarker for the automatic detection of heterogeneous chromatin organisation. Methods Machine learning algorithms analysed the chromatin organisation in 461 000 images of tumour cell nuclei stained for DNA from 390 patients (discovery cohort) treated for stage I or II colorectal cancer at the Aker University Hospital (Oslo, Norway). The resulting marker of chromatin heterogeneity, termed Nucleotyping, was subsequently independently validated in six patient cohorts: 442 patients with stage I or II colorectal cancer in the Gloucester Colorectal Cancer Study (UK); 391 patients with stage II colorectal cancer in the QUASAR 2 trial; 246 patients with stage I ovarian carcinoma; 354 patients with uterine sarcoma; 307 patients with prostate carcinoma; and 791 patients with endometrial carcinoma. The primary outcome was cancer-specific survival. Findings: In all patient cohorts, patients with chromatin heterogeneous tumours had worse cancer-specific survival than patients with chromatin homogeneous tumours (univariable analysis hazard ratio [HR] 1·7, 95% CI 1·2–2·5, in the discovery cohort; 1·8, 1·0–3·0, in the Gloucester validation cohort; 2·2, 1·1–4·5, in the QUASAR 2 validation cohort; 3·1, 1·9–5·0, in the ovarian carcinoma cohort; 2·5, 1·8–3·4, in the uterine sarcoma cohort; 2·3, 1·2–4·6, in the prostate carcinoma cohort; and 4·3, 2·8–6·8, in the endometrial carcinoma cohort). After adjusting for established prognostic patient characteristics in multivariable analyses, Nucleotyping was prognostic in all cohorts except for the prostate carcinoma cohort (HR 1·7, 95% CI 1·1–2·5, in the discovery cohort; 1·9, 1·1–3·2, in the Gloucester validation cohort; 2·6, 1·2–5·6, in the QUASAR 2 cohort; 1·8, 1·1–3·0, for ovarian carcinoma; 1·6, 1·0–2·4, for uterine sarcoma; 1·43, 0·68–2·99, for prostate carcinoma; and 1·9, 1·1–3·1, for endometrial carcinoma). Chromatin heterogeneity was a significant predictor of cancer-specific survival in microsatellite unstable (HR 2·9, 95% CI 1·0–8·4) and microsatellite stable (1·8, 1·2–2·7) stage II colorectal cancer, but microsatellite instability was not a significant predictor of outcome in chromatin homogeneous (1·3, 0·7–2·4) or chromatin heterogeneous (0·8, 0·3–2·0) stage II colorectal cancer. Interpretation: The consistent prognostic prediction of Nucleotyping in different biological and technical circumstances suggests that the marker of chromatin heterogeneity can be reliably assessed in routine clinical practice and could be used to objectively assist decision making in a range of clinical settings. An immediate application would be to identify high-risk patients with stage II colorectal cancer who might have greater absolute benefit from adjuvant chemotherapy. Clinical trials are warranted to evaluate the survival benefit and cost-effectiveness of using Nucleotyping to guide treatment decisions in multiple clinical settings

Mutation burden and other molecular markers of prognosis in colorectal cancer treated with curative intent: results from the QUASAR 2 clinical trial and an Australian community-based series

Background Several relatively large studies have assessed molecular indicators of colorectal cancer (CRC) prognosis, but most analyses have been restricted to a handful of markers. Methods In stage II/III CRCs from the QUASAR2 clinical trial and from an Australian community-based series, we assessed gene panels for somatic driver mutations and overall mutation burden. We determined molecular pathways of tumorigenesis, and analysed associations with treatment response and prognosis. Findings In QUASAR2 (N=511), TP53, KRAS, BRAF and GNAS mutations were independently associated with shorter relapse-free survival, whereas total somatic mutation burden was associated with longer survival, even after excluding mismatch repair-deficient (MSI+) and POLE-mutant tumours. We successfully validated these associations in the Australian sample set (N=296). In an extended analysis of 1,752 QUASAR2 and Australian CRCs for which KRAS, BRAF and MSI status was available, we found that KRAS and BRAF mutations were specifically associated with poor prognosis in MSI- cancers. This association was not present in MSI+ cancers, and MSI+ tumours with KRAS or BRAF mutation actually had better prognosis than MSI- cancers that were wildtype for KRAS or BRAF. New rare molecular pathways were also uncovered: mutations in the genes NF1 and NRAS from the MAP kinase pathway co-occurred, mutations in TP53 and ATM appeared to be alternative ways of inactivating the DNA damage response pathway. Interpretation A multi-gene panel has identified two previously unreported prognostic associations in CRC involving both TP53 mutation and total mutation burden, and confirmed associations with KRAS and BRAF. We conclude that even a modest-sized gene panel can provide important information for use in clinical practice and out-perform MSI-based models.</p

In vitro downregulated hypoxia transcriptome is associated with poor prognosis in breast cancer

© The Author(s), 2017. Background Hypoxia is a characteristic of breast tumours indicating poor prognosis. Based on the assumption that those genes which are up-regulated under hypoxia in cell-lines are expected to be predictors of poor prognosis in clinical data, many signatures of poor prognosis were identified. However, it was observed that cell line data do not always concur with clinical data, and therefore conclusions from cell line analysis should be considered with caution. As many transcriptomic cell-line datasets from hypoxia related contexts are available, integrative approaches which investigate these datasets collectively, while not ignoring clinical data, are required. Results We analyse sixteen heterogeneous breast cancer cell-line transcriptomic datasets in hypoxia-related conditions collectively by employing the unique capabilities of the method, UNCLES, which integrates clustering results from multiple datasets and can address questions that cannot be answered by existing methods. This has been demonstrated by comparison with the state-of-the-art iCluster method. From this collection of genome-wide datasets include 15,588 genes, UNCLES identified a relatively high number of genes (>1000 overall) which are consistently co-regulated over all of the datasets, and some of which are still poorly understood and represent new potential HIF targets, such as RSBN1 and KIAA0195. Two main, anti-correlated, clusters were identified; the first is enriched with MYC targets participating in growth and proliferation, while the other is enriched with HIF targets directly participating in the hypoxia response. Surprisingly, in six clinical datasets, some sub-clusters of growth genes are found consistently positively correlated with hypoxia response genes, unlike the observation in cell lines. Moreover, the ability to predict bad prognosis by a combined signature of one sub-cluster of growth genes and one sub-cluster of hypoxia-induced genes appears to be comparable and perhaps greater than that of known hypoxia signatures. Conclusions We present a clustering approach suitable to integrate data from diverse experimental set-ups. Its application to breast cancer cell line datasets reveals new hypoxia-regulated signatures of genes which behave differently when in vitro (cell-line) data is compared with in vivo (clinical) data, and are of a prognostic value comparable or exceeding the state-of-the-art hypoxia signatures.Dr. Abu-Jamous would like to acknowledge the financial assistance from Brunel University London. Professors Buffa and Harris acknowledge support from Cancer Research UK, EU framework 7, and the Oxford NIHR Biomedical Research Centre. Professor Harris acknowledges support from the Breast Cancer Research Foundation. Professor Nandi would like to acknowledge that this work was partly supported by the National Science Foundation of China grant number 61520106006 and the National Science Foundation of Shanghai grant number 16JC1401300. The funding bodies have no role in the design of the study, in the collection, analysis, and interpretation of data, or in writing the manuscript