991 resultados para endometrial cancer


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In this paper, a Bayesian hierarchical model is used to anaylze the female breast cancer mortality rates for the State of Missouri from 1969 through 2001. The logit transformations of the mortality rates are assumed to be linear over the time with additive spatial and age effects as intercepts and slopes. Objective priors of the hierarchical model are explored. The Bayesian estimates are quite robustness in terms change of the hyperparamaters. The spatial correlations are appeared in both intercepts and slopes.

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Introduction Delirium research in palliative care, particularly in the dying phase, is possible but is frequently met with ethical and methodological challenges. This paper describes the challenges faced in a previous delirium screening study. Methods Within 72 hours of admission to an acute inpatient specialist palliative care unit one hundred consecutive patients over 18 years of age with advanced cancer were invited to be screened for delirium using validated screening tools. Results Of the 100 consecutive admissions 49 patients were unable to participate including seven who did not meet the inclusion criteria and nine (six families and three patients) who withheld consent. The remaining 33 patients were more unwell and closer to death than those who were recruited. Reasons for non- participation included being too unwell (ten), unresponsive (nine), died (two) or discharged (three) before recruitment and exceeding the 72hour time limit (nine). Conclusion Gate keeping and physical condition of patients were the main obstacles to recruitment and is consistent with barriers faced in previous studies involving palliative care and dying patients. While it is possible and necessary to conduct studies in palliative care, including the terminal phase, as reflective practitioners we must maintain the balance between the demands for evidence-based practice and our compassion and respect for our most vulnerable of patients.

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Heparan sulfate proteoglycans (HSPGs) are key components of the extracellular matrix that mediate cell proliferation, invasion, and cellular signaling. The biological functions of HSPGs are linked to their co-stimulatory effects on extracellular ligands (e.g., WNTs) and the resulting activation of transcription factors that control mammalian development but also associated with tumorigenesis. We examined the expression profile of HSPG core protein syndecans (SDC1–4) and glypicans (GPC1–6) along with the enzymes that initiate or modify their glycosaminoglycan chains in human breast cancer (HBC) epithelial cells. Gene expression in relation to cell proliferation was examined in the HBC cell lines MCF-7 and MDA-MB-231 following treatment with the HS agonist heparin. Heparin increased gene expression of chain initiation and modification enzymes including EXT1 and NDST1, as well as core proteins SDC2 and GPC6. With HS/Wnt interactions established, we next investigated WNT pathway components and observed that increased proliferation of the more invasive MDA-MB-231 cells is associated with activation of the Wnt signaling pathway. Specifically, there was substantial upregulation (>5-fold) of AXIN1, WNT4A, and MYC in MDA-MB-231 but not in MCF-7 cells. The changes in gene expression observed for HSPG core proteins and related enzymes along with the associated Wnt signaling components suggest coordinated interactions. The influence of HSPGs on cellular proliferation and invasive potential of breast cancer epithelial cells are cell and niche specific. Further studies on the interactions between HSPGs and WNT ligands may yield clinically relevant molecular targets, as well as new biomarkers for characterization of breast cancer progression.

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Breast cancer is the cancer that most commonly affects women worldwide. This type of cancer is genetically complex, but is strongly linked to steroid hormone signalling systems. Because microRNAs act as translational regulators of multiple genes, including the steroid nuclear receptors, single nucleotide polymorphisms (SNPs) in microRNAs genes can have potentially wide-ranging influences on breast cancer development. Thus, this study was conducted to investigate the relationships between six SNPs (rs6977848, rs199981120, rs185641358, rs113054794, rs66461782, and rs12940701) located in four miRNA genes predicted to target the estrogen receptor (miR-148a, miR-221, miR-186, and miR-152) and breast cancer risk in Caucasian Australian women. By using high resolution melt analysis (HRM) and polymerase chain reaction- restriction fragment length polymorphism (PCR-RFLP), 487 samples including 225 controls and 262 cases were genotyped. Analysis of their genotype and allele frequencies indicated that the differences between case and control populations was not significant for rs6977848, rs66461782, and rs12940701 because their p-values are 0.81, 0.93, 0.1 which are all above the threshold value (p=0.05). Our data thus suggests that these SNPs do not affect breast cancer risk in the tested population. In addition, rs199981120, rs185641358, and rs113054794 could not be found in this population, suggesting that these SNPs do not occur in Caucasian Australians.

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Objective To evaluate the effects of Optical Character Recognition (OCR) on the automatic cancer classification of pathology reports. Method Scanned images of pathology reports were converted to electronic free-text using a commercial OCR system. A state-of-the-art cancer classification system, the Medical Text Extraction (MEDTEX) system, was used to automatically classify the OCR reports. Classifications produced by MEDTEX on the OCR versions of the reports were compared with the classification from a human amended version of the OCR reports. Results The employed OCR system was found to recognise scanned pathology reports with up to 99.12% character accuracy and up to 98.95% word accuracy. Errors in the OCR processing were found to minimally impact on the automatic classification of scanned pathology reports into notifiable groups. However, the impact of OCR errors is not negligible when considering the extraction of cancer notification items, such as primary site, histological type, etc. Conclusions The automatic cancer classification system used in this work, MEDTEX, has proven to be robust to errors produced by the acquisition of freetext pathology reports from scanned images through OCR software. However, issues emerge when considering the extraction of cancer notification items.

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Objective: To develop a system for the automatic classification of pathology reports for Cancer Registry notifications. Method: A two pass approach is proposed to classify whether pathology reports are cancer notifiable or not. The first pass queries pathology HL7 messages for known report types that are received by the Queensland Cancer Registry (QCR), while the second pass aims to analyse the free text reports and identify those that are cancer notifiable. Cancer Registry business rules, natural language processing and symbolic reasoning using the SNOMED CT ontology were adopted in the system. Results: The system was developed on a corpus of 500 histology and cytology reports (with 47% notifiable reports) and evaluated on an independent set of 479 reports (with 52% notifiable reports). Results show that the system can reliably classify cancer notifiable reports with a sensitivity, specificity, and positive predicted value (PPV) of 0.99, 0.95, and 0.95, respectively for the development set, and 0.98, 0.96, and 0.96 for the evaluation set. High sensitivity can be achieved at a slight expense in specificity and PPV. Conclusion: The system demonstrates how medical free-text processing enables the classification of cancer notifiable pathology reports with high reliability for potential use by Cancer Registries and pathology laboratories.

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Aims Pathology notification for a Cancer Registry is regarded as the most valid information for the confirmation of a diagnosis of cancer. In view of the importance of pathology data, an automatic medical text analysis system (Medtex) is being developed to perform electronic Cancer Registry data extraction and coding of important clinical information embedded within pathology reports. Methods The system automatically scans HL7 messages received from a Queensland pathology information system and analyses the reports for terms and concepts relevant to a cancer notification. A multitude of data items for cancer notification such as primary site, histological type, stage, and other synoptic data are classified by the system. The underlying extraction and classification technology is based on SNOMED CT1 2. The Queensland Cancer Registry business rules3 and International Classification of Diseases – Oncology – Version 34 have been incorporated. Results The cancer notification services show that the classification of notifiable reports can be achieved with sensitivities of 98% and specificities of 96%5, while the coding of cancer notification items such as basis of diagnosis, histological type and grade, primary site and laterality can be extracted with an overall accuracy of 80%6. In the case of lung cancer staging, the automated stages produced were accurate enough for the purposes of population level research and indicative staging prior to multi-disciplinary team meetings2 7. Medtex also allows for detailed tumour stream synoptic reporting8. Conclusions Medtex demonstrates how medical free-text processing could enable the automation of some Cancer Registry processes. Over 70% of Cancer Registry coding resources are devoted to information acquisition. The development of a clinical decision support system to unlock information from medical free-text could significantly reduce costs arising from duplicated processes and enable improved decision support, enhancing efficiency and timeliness of cancer information for Cancer Registries.

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Modern cancer research requires physiological, three-dimensional (3-D) cell culture platforms, wherein the physical and chemical characteristics of the extracellular matrix (ECM) can be modified. In this study, gelatine methacrylamide (GelMA)-based hydrogels were characterized and established as in vitro and in vivo spheroid-based models for ovarian cancer, reflecting the advanced disease stage of patients, with accumulation of multicellular spheroids in the tumour fluid (ascites). Polymer concentration (2.5-7% w/v) strongly influenced hydrogel stiffness (0.5±0.2kPa to 9.0±1.8kPa) but had little effect on solute diffusion. The diffusion coefficient of 70kDa fluorescein isothiocyanate (FITC)-labelled dextran in 7% GelMA-based hydrogels was only 2.3 times slower compared to water. Hydrogels of medium concentration (5% w/v GelMA) and stiffness (3.4kPa) allowed spheroid formation and high proliferation and metabolic rates. The inhibition of matrix metalloproteinases and consequently ECM degradability reduced spheroid formation and proliferation rates. The incorporation of the ECM components laminin-411 and hyaluronic acid further stimulated spheroid growth within GelMA-based hydrogels. The feasibility of pre-cultured GelMA-based hydrogels as spheroid carriers within an ovarian cancer animal model was proven and led to tumour development and metastasis. These tumours were sensitive to treatment with the anti-cancer drug paclitaxel, but not the integrin antagonist ATN-161. While paclitaxel and its combination with ATN-161 resulted in a treatment response of 33-37.8%, ATN-161 alone had no effect on tumour growth and peritoneal spread. The semi-synthetic biomaterial GelMA combines relevant natural cues with tunable properties, providing an alternative, bioengineered 3-D cancer cell culture in in vitro and in vivo model systems.

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Upon overexpression of integrin αvβ3 and its engagement by vitronectin, we previously showed enhanced adhesion, proliferation, and motility of human ovarian cancer cells. By studying differential expression of genes possibly related to these tumor biological events, we identified the epidermal growth-factor receptor (EGF-R) to be under control of αvβ3 expression levels. Thus in the present study we characterized αvβ3-dependent changes of EGF-R and found significant upregulation of its expression and activity which was reflected by prominent changes of EGF-R promoter activity. Upon disruption of DNA-binding motifs for the transcription factors p53, ETF, the repressor ETR, p50, and c-rel, respectively, we sought to identify DNA elements contributing to αvβ3-mediated EGF-R promoter induction. Both, the p53- and ETF-mutant, while exhibiting considerably lower EGF-R promoter activity than the wild type promoter, retained inducibility by αvβ3. Mutation of the repressor motif ETR, as expected, enhanced EGF-R promoter activity with a further moderate increase upon αvβ3 elevation. The p50-mutant displayed EGF-R promoter activity almost comparable to that of the wild type promoter with no impairment of induction by αvβ3. However, the activity of an EGF-R promoter mutant displaying a disrupted c-rel-binding motif did not only prominently decline, but, moreover, was not longer responsive to enhanced αvβ3, involving this DNA element in αvβ3-dependent EGF-R upregulation. Moreover, αvβ3 did not only increase the EGF-R but, moreover, also led to obvious co-clustering on the cancer cell surface. By studying αvβ3/EGF-R-effects on the focal adhesion kinase (FAK) and the mitogen activated protein kinases (MAPK) p44/42 (erk−1/erk−2), having important functions in synergistic crosstalk between integrins and growth-factor receptors, we found for both significant enhancement of expression and activity upon αvβ3/VN interaction and cell stimulation by EGF. Upregulation of the EGF-R by integrin αvβ3, both receptor molecules with a well-defined role as targets for cancer treatment, might represent an additional mechanism to adapt synergistic receptor signaling and crosstalk in response to an altered tumor cell microenvironment during ovarian cancer progression.

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Cancer-related fatigue is one of the most distressing symptoms experienced by patients with advanced cancer. This doctoral study identified that patients with advanced cancer commonly use a number of self-management strategies in response to fatigue, although these strategies had varying levels of effectiveness in reducing the symptom. The study identified that enhancing self-efficacy and managing depressive symptoms are important factors to consider in the design of future interventions to support fatigue self-management.

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Rapidly developing proteomic tools are improving detection of deregulated kallikrein-related peptidase (KLK) expression, at the protein level, in prostate and ovarian cancer, as well as facilitating the determination of functional consequences downstream. Mass spectrometry (MS)-driven proteomics uniquely allows for the detection, identification and quantification of thousands of proteins in a complex protein pool, and this has served to identify certain KLKs as biomarkers for these diseases. In this review we describe applications of this technology in KLK biomarker discovery, and elucidate MS-based techniques which have been used for unbiased, global screening of KLK substrates within complex protein pools. Although MS-based KLK degradomic studies are limited to date, they helped to discover an array of novel KLK substrates. Substrates identified by MS-based degradomics are reported with improved confidence over those determined by incubating a purified or recombinant substrate and protease of interest, in vitro. We propose that these novel proteomic approaches represent the way forward for KLK research, in order to correlate proteolysis of biological substrates with tissue-related consequences, toward clinical targeting of KLK expression and function for cancer diagnosis, prognosis and therapies.

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This is the protocol for a review and there is no abstract. The objectives are as follows: To assess the effects of education programmes for skin cancer prevention in the general population. Description of the condition Skin cancer is a term that includes both melanoma and keratinocyte cancer. Keratinocyte cancer (also known as nonmelanoma skin cancer) generally refers to basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), although it also includes other rare cutaneous neoplasms (Madan 2010). Skin cancer is the most common cancer in populations of predominantly fair-skinned people (Donaldson 2011; Lomas 2012; Stern 2010), with incidence increasing (Garbe 2009; Leiter 2012). There are variations in annual incidence rates between these populations, with Australia reporting the highest rate of skin cancer in the world (Lomas 2012). In 2012, the estimated age-standardised incidence rate for melanoma was almost 63 per 100,000 people for Australian men, and 40 per 100,000 people for Australian women (AIHW 2012). In Europe, incidence rates range from 10 to 15 per 100,000 people (Garbe 2009; Lasithiotakis 2006), with rates highest amongst men (Stang 2006). In the United States, incidence rates are approximately 18 per 100,000 people (Garbe 2009),with the highest rates reported forwomen (Bradford 2010). Keratinocyte cancer is much more common than melanoma. In 2012, the estimated Australian age-standardised rates for BCCand SCC were 884 and 387 per 100,000 people, respectively (Staples 2006). The cumulative three-year risk of developing a subsequent keratinocyte cancer is 18% for SCC and 44% for BCC (Marcil 2000).