Microbial infection, inflammation and epithelial ovarian cancer.
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ABSTRACT:
SUBMITTER: Xie X
PROVIDER: S-EPMC5529868 | biostudies-other | 2017 Aug
REPOSITORIES: biostudies-other
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Project description:BACKGROUND:Factors contributing to chronic inflammation appear to be associated with increased risk of ovarian cancer. The purpose of this study was to assess the association between circulating levels of inflammation mediators and subsequent risk of ovarian cancer. METHODS:We conducted a case-control study of 230 cases and 432 individually matched controls nested within three prospective cohorts to evaluate the association of prediagnostic circulating levels of inflammation-related biomarkers (IL-1?, IL-2, IL-4, IL-5, IL-6, IL-10, IL-12p40, IL-12p70, IL-13, TNF?, IL-1Ra, sIL-1RII, sIL-2Ra, sIL-4R, sIL-6R, sTNF-R1, and sTNF-R2) measured using Luminex xMap technology with risk of ovarian cancer. RESULTS:We observed a trend across quartiles for IL-2 (OR(Q4 vs. Q1): 1.57, 95% CI: 0.98-2.52, P = 0.07), IL-4 (OR(Q4 vs. Q1): 1.50, 95% CI: 0.95-2.38, P = 0.06), IL-6 (OR(Q4 vs. Q1): 1.63, 95% CI: 1.03-2.58, P = 0.03), IL-12p40 (OR(Q4 vs. Q1): 1.60, 95% CI: 1.02-2.51, P = 0.06), and IL-13 (OR(Q4 vs. Q1): 1.42, 95% CI: 0.90-2.26, P = 0.11). Trends were also observed when cytokines were modeled on the continuous scale for IL-4 (P trend = 0.01), IL-6 (P trend = 0.01), IL-12p40 (P trend = 0.01), and IL-13 (P trend = 0.04). ORs were not materially different after excluding cases diagnosed less than 5 years after blood donation or when limited to serous tumors. CONCLUSIONS AND IMPACT:This study provides the first direct evidence that multiple inflammation markers, specifically IL-2, IL-4, IL-6, IL-12, and IL-13, may be associated with risk of epithelial ovarian cancer, and adds to the evidence that inflammation is involved in the development of this disease.
| S-EPMC3089656 | biostudies-literature
Project description:BackgroundEpithelial ovarian cancer (EOC) remains one of the leading causes of cancer-related deaths among women worldwide, despite gains in diagnostics and treatments made over the last three decades. Existing markers of ovarian cancer possess very limited clinical relevance highlighting the emerging need for identification of novel prognostic biomarkers as well as better predictive factors that might allow the stratification of patients who could benefit from a more targeted approach.Patients and methodsA summary of molecular genetics of EOC.ResultsLarge-scale high-throughput genomic technologies appear to be powerful tools for investigations into the genetic abnormalities in ovarian tumors, including studies on dysregulated genes and aberrantly activated signaling pathways. Such technologies can complement well-established clinical histopathology analysis and tumor grading and will hope to result in better, more tailored treatments in the future. Genomic signatures obtained by gene expression profiling of EOC may be able to predict survival outcomes and other important clinical outcomes, such as the success of surgical treatment. Finally, genomic analyses may allow for the identification of novel predictive biomarkers for purposes of treatment planning. These data combined suggest a pathway to progress in the treatment of advanced ovarian cancer and the promise of fulfilling the objective of providing personalized medicine to women with ovarian cancer.ConclusionsThe understanding of basic molecular events in the tumorigenesis and chemoresistance of EOC together with discovery of potential biomarkers may be greatly enhanced through large-scale genomic studies. In order to maximize the impact of these technologies, however, extensive validation studies are required.
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Project description:Cancer stem cells are responsible for sustaining the tumor and giving rise to proliferating and progressively differentiating cells. However, the molecular mechanisms regulating the process of cancer stem cell (CSC) differentiation is not clearly understood. Recently, we reported the isolation of the epithelial ovarian cancer (EOC) stem cells (type I/CD44+). In this study, we show that type I/CD44+ cells are characterized by low levels of both miR-199a and miR-214, whereas mature EOC cells (type II/CD44-) have higher levels of miR-199a and miR-214. Moreover, these two micro RNAs (miRNAs) are regulated as a cluster on pri-miR-199a2 within the human Dnm3os gene (GenBank FJ623959). This study identify Twist1 as a regulator of this unique miRNA cluster responsible for the regulation of the IKKbeta/NF-kappaB and PTEN/AKT pathways and its association of ovarian CSC differentiation. Our data suggest that Twist1 may be an important regulator of 'stemness' in EOC cells. The regulation of MIR199A2/214 expression may be used as a potential therapeutic approach in EOC patients.
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Project description:Epithelial ovarian cancer (OvCa) is associated with high mortality and, as the majority (>75%) of women with OvCa have metastatic disease at the time of diagnosis, rates of survival have not changed appreciably over 30 years. A mechanistic understanding of OvCa initiation and progression is hindered by the complexity of genetic and/or environmental initiating events and lack of clarity regarding the cell(s) or tissue(s) of origin. Metastasis of OvCa involves direct extension or exfoliation of cells and cellular aggregates into the peritoneal cavity, survival of matrix-detached cells in a complex ascites fluid phase and subsequent adhesion to the mesothelium lining covering abdominal organs to establish secondary lesions containing host stromal and inflammatory components. Development of experimental models to recapitulate this unique mechanism of metastasis presents a remarkable scientific challenge, and many approaches used to study other solid tumors (for example, lung, colon and breast) are not transferable to OvCa research given the distinct metastasis pattern and unique tumor microenvironment (TME). This review will discuss recent progress in the development and refinement of experimental models to study OvCa. Novel cellular, three-dimensional organotypic, and ex vivo models are considered and the current in vivo models summarized. The review critically evaluates currently available genetic mouse models of OvCa, the emergence of xenopatients and the utility of the hen model to study OvCa prevention, tumorigenesis, metastasis and chemoresistance. As these new approaches more accurately recapitulate the complex TME, it is predicted that new opportunities for enhanced understanding of disease progression, metastasis and therapeutic response will emerge.
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Project description:Ovarian cancer is the second most common gynecological cancer and the leading cause of death in the United States. In this article we review the diagnosis and current management of epithelial ovarian cancer which accounts for over 95 percent of the ovarian malignancies. We will present various theories about the potential origin of ovarian malignancies. We will discuss the genetic anomalies and syndromes that may cause ovarian cancers with emphasis on Breast cancer type 1/2 mutations. The pathology and pathogenesis of ovarian carcinoma will also be presented. Lastly, we provide a comprehensive overview of treatment strategies and staging of ovarian cancer, conclusions and future directions.
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Project description:Protein biomarkers of early stages of disease are critical for managing the disease and improving outcomes. Unfortunately, discovery of protein biomarkers is hampered by the limited availability of assays for sensitive and reproducible quantification of proteins in complex biological matrices such as blood plasma. In the recent years, Selected Reaction Monitoring (SRM) has emerged as a robust mass spectrometric method, capable of overcoming this limitation. Here, we present a comprehensive SRM-based strategy for developing protein biomarkers for epithelial ovarian cancer, and illustrate the extent to which SRM platform, combined with sound experimental design and statistical analysis, results in robust detection of predictive analytes. First, the biomarker development was guided by a discovery-driven proteomic effort to detect potential N-glycoprotein biomarker candidates in tissue of a genetically stable ovarian cancer mouse model. Next, 65 candidate markers were reproducibly quantified with SRM assays across a large cohort of over 200 plasma samples from ovarian cancer patients and healthy controls. Finally, these measurements were used to derive 5-protein signatures for distinguishing individuals with epithelial ovarian cancer from healthy controls. The sensitivity of the candidate biomarker signature in combination with CA125 ELISA-based measurements currently used in clinic, exceeded that of CA125 ELISA-based measurements alone. The SRM-based strategy in this study is broadly applicable. It can be used in any study that requires accurate and reproducible quantification of selected proteins in a high-throughput and multiplexed fashion.
2019-07-02 | MSV000084048 | MassIVE
Project description:Genomic sequencing analyses of a variety of human cancers have revealed that massive mutations of cancer-relevant genes are the major alterations in cancerous cells, and their mutation frequencies or rates are highly associated with the development, progression, metastasis, and drug resistance of cancers as well as their clinical outcomes and prognosis. One predominant genetic alternation in human epithelial ovarian cancer (EOC) is the mutation of TP53 that encodes the tumor suppressor p53 protein. This essay will review the most recent progress in understanding the role of TP53 mutations in development, progression, and metastasis of EOC, and discuss the potential of TP53 mutations as diagnostic and prognostic biomarkers as well as therapeutic targets for EOC.
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