25 research outputs found

    DNA damage activates a complex transcriptional response in murine lymphocytes that includes both physiological and cancer-predisposition programs

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    BACKGROUND: Double strand (ds) DNA breaks are a form of DNA damage that can be generated from both genotoxic exposures and physiologic processes, can disrupt cellular functions and can be lethal if not repaired properly. Physiologic dsDNA breaks are generated in a variety of normal cellular functions, including the RAG endonuclease-mediated rearrangement of antigen receptor genes during the normal development of lymphocytes. We previously showed that physiologic breaks initiate lymphocyte development-specific transcriptional programs. Here we compare transcriptional responses to physiological DNA breaks with responses to genotoxic DNA damage induced by ionizing radiation. RESULTS: We identified a central lymphocyte-specific transcriptional response common to both physiologic and genotoxic breaks, which includes many lymphocyte developmental processes. Genotoxic damage causes robust alterations to pathways associated with B cell activation and increased proliferation, suggesting that genotoxic damage initiates not only the normal B cell maturation processes but also mimics activated B cell response to antigenic agents. Notably, changes including elevated levels of expression of Kras and mmu-miR-155 and the repression of Socs1 were observed following genotoxic damage, reflecting induction of a cancer-prone phenotype. CONCLUSIONS: Comparing these transcriptional responses provides a greater understanding of the mechanisms cells use in the differentiation between types of DNA damage and the potential consequences of different sources of damage. These results suggest genotoxic damage may induce a unique cancer-prone phenotype and processes mimicking activated B cell response to antigenic agents, as well as the normal B cell maturation processes

    A prognostic signature of Gâ‚‚ checkpoint function in melanoma cell lines

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    As DNA damage checkpoints are barriers to carcinogenesis, G2 checkpoint function was quantified to test for override of this checkpoint during melanomagenesis. Primary melanocytes displayed an effective G2 checkpoint response to ionizing radiation (IR)-induced DNA damage. Thirty-seven percent of melanoma cell lines displayed a significant defect in G2 checkpoint function. Checkpoint function was melanoma subtype-specific with “epithelial-like” melanoma lines, with wild type NRAS and BRAF displaying an effective checkpoint, while lines with mutant NRAS and BRAF displayed defective checkpoint function. Expression of oncogenic B-Raf in a checkpoint-effective melanoma attenuated G2 checkpoint function significantly but modestly. Other alterations must be needed to produce the severe attenuation of G2 checkpoint function seen in some BRAF-mutant melanoma lines. Quantitative trait analysis tools identified mRNA species whose expression was correlated with G2 checkpoint function in the melanoma lines. A 165 gene signature was identified with a high correlation with checkpoint function (p < 0.004) and low false discovery rate (≤ 0.077). The G2 checkpoint gene signature predicted G2 checkpoint function with 77–94% accuracy. The signature was enriched in lysosomal genes and contained numerous genes that are associated with regulation of chromatin structure and cell cycle progression. The core machinery of the cell cycle was not altered in checkpoint-defective lines but rather numerous mediators of core machinery function were. When applied to an independent series of primary melanomas, the predictive G2 checkpoint signature was prognostic of distant metastasis-free survival. These results emphasize the value of expression profiling of primary melanomas for understanding melanoma biology and disease prognosis

    How are compassion fatigue, burnout, and compassion satisfaction affected by quality of working life? Findings from a survey of mental health staff in Italy

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    BACKGROUND: Quality of working life includes elements such as autonomy, trust, ergonomics, participation, job complexity, and work-life balance. The overarching aim of this study was to investigate if and how quality of working life affects Compassion Fatigue, Burnout, and Compassion Satisfaction among mental health practitioners. METHODS: Staff working in three Italian Mental Health Departments completed the Professional Quality of Life Scale, measuring Compassion Fatigue, Burnout, and Compassion Satisfaction, and the Quality of Working Life Questionnaire. The latter was used to collect socio-demographics, occupational characteristics and 13 indicators of quality of working life. Multiple regressions controlling for other variables were undertaken to predict Compassion Fatigue, Burnout, and Compassion Satisfaction. RESULTS: Four hundred questionnaires were completed. In bivariate analyses, experiencing more ergonomic problems, perceiving risks for the future, a higher impact of work on life, and lower levels of trust and of perceived quality of meetings were associated with poorer outcomes. Multivariate analysis showed that (a) ergonomic problems and impact of work on life predicted higher levels of both Compassion Fatigue and Burnout; (b) impact of life on work was associated with Compassion Fatigue and lower levels of trust and perceiving more risks for the future with Burnout only; (c) perceived quality of meetings, need of training, and perceiving no risks for the future predicted higher levels of Compassion Satisfaction. CONCLUSIONS: In order to provide adequate mental health services, service providers need to give their employees adequate ergonomic conditions, giving special attention to time pressures. Building trustful relationships with management and within the teams is also crucial. Training and meetings are other important targets for potential improvement. Additionally, insecurity about the future should be addressed as it can affect both Burnout and Compassion Satisfaction. Finally, strategies to reduce possible work-life conflicts need to be considered

    Genome-Wide Small RNA Sequencing and Gene Expression Analysis Reveals a microRNA Profile of Cancer Susceptibility in ATM-Deficient Human Mammary Epithelial Cells

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    <div><p>Deficiencies in the ATM gene are the underlying cause for ataxia telangiectasia, a syndrome characterized by neurological, motor and immunological defects, and a predisposition to cancer. MicroRNAs (miRNAs) are useful tools for cancer profiling and prediction of therapeutic responses to clinical regimens. We investigated the consequences of ATM deficiency on miRNA expression and associated gene expression in normal human mammary epithelial cells (HME-CCs). We identified 81 significantly differentially expressed miRNAs in ATM-deficient HME-CCs using small RNA sequencing. Many of these have been implicated in tumorigenesis and proliferation and include down-regulated tumor suppressor miRNAs, such as hsa-miR-29c and hsa-miR-16, as well as over-expressed pro-oncogenic miRNAs, such as hsa-miR-93 and hsa-miR-221. MicroRNA changes were integrated with genome wide gene expression profiles to investigate possible miRNA targets. Predicted mRNA targets of the miRNAs significantly regulated after ATM depletion included many genes associated with cancer formation and progression, such as SOCS1 and the proto-oncogene MAF. While a number of miRNAs have been reported as altered in cancerous cells, there is little understanding as to how these small RNAs might be driving cancer formation or how they might be used as biomarkers for cancer susceptibility. This study provides preliminary data for defining miRNA profiles that may be used as prognostic or predictive biomarkers for breast cancer. Our integrated analysis of miRNA and mRNA expression allows us to gain a better understanding of the signaling involved in breast cancer predisposition and suggests a mechanism for the breast cancer-prone phenotype seen in ATM-deficient patients.</p> </div

    Differential expression of 259 present miRNAs in both wild type and ATM-deficient HME-CCs.

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    <p>Differential miRNA expression between wild type and ATM-deficient HME-CCs obtained from three independent replicates of each. The <i>y</i>-axis displays the ATM-deficient to WT expression ratio, the <i>x</i>-axis displays the average expression of each miRNA; both axes are in logarithmic scale. Differentially expressed miRNAs of <i>p</i>-value ≤0.05 and at least 1.5 fold change are blue. Representative significant miRNAs are labelled. Each sample had a separately generated sequencing library and was run in an individual sequencing lane.</p

    Depletion of ATM leads to deregulation of miRNAs important in cancer formation.

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    <p>A) List of 4 known tumor suppressors and 8 oncomirs with significant expression changes after the depletion of ATM. B) Expression levels, tags per million (TpM), of four examples of deregulated miRNAs. Dark gray bars represent wild type expression and light gray bars represent expression in ATM-deficient cells. Error bars are standard error from the expression of 3 independent replicates of each genotype.</p

    Process Map and Summary of Next Gen Sequencing data.

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    <p>A) Small RNA Sequencing pipeline overview. B) Summary statistics of Small RNA sequencing data at different stages of data analysis.</p

    Depletion of ATM in non-cancerous cells reveals effects on miRNAs and target mRNAs that suggest an early event in transformation to cancer.

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    <p>A) Gene Families representing the 202 significantly regulated genes determined using GSEA to give a functional overview of the types of genes affected by changes in miRNA expression. B) Top Functions analysis of ATM-dependent correlated miRNAs and possible mRNA targets by IPA. Only selected significant functional groups are depicted. The dashed line indicates a <i>p</i>-value of 0.01.</p
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