976 resultados para Cancer strategy


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The Minister for Health Leo Varadkar has announced that a new National Cancer Strategy is to be developed. This will be the third cancer strategy, covering the period 2016 to 2025. A Cancer Strategy Steering Group has been established to advise the Department on the development of the Strategy. It is anticipated that the work of the Steering Group will be completed by the end of 2015, when it will make recommendations on a draft Strategy to the Minister. The implementation of a new strategy will commence in 2016. (Further information is available at: http://health.gov.ie/blog/press-release/steering-group-to-develop-national-cancer-strategy-2016-2025).

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Review of ‘A Strategy for Cancer Control in Ireland’. The review was led by Professor Pádraig Warde of the Princess Margaret Cancer Centre, Toronto.  The evaluation panel was very impressed with the excellent progress in the cancer control system in Ireland since the publication of “A Strategy for Cancer Control in Ireland” in 2006.   Download the report here.

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Thesis (Ph.D.)--University of Washington, 2016-06

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INTRODUCTION: The treatment of choice for early glottic cancer is still being debated; ultimately it relies on the functional outcome. This paper reports on a novel sparing 4D conformal technique for single vocal cord irradiation (SVCI).

MATERIAL AND METHODS: The records of 164 T1a patients with SCC of the vocal cord, irradiated in the Erasmus MC between 2000 and 2008, were analyzed for local control and overall survival. The quality of life was determined by EORTC H&N35 questionnaires. Also the VHI (voice handicap index), and the TSH (thyroid stimulating hormone) blood levels, were established. On-line image guided SVCI, using cone beam CT or stereotactic radiation therapy (SRT) techniques, were developed.

RESULTS: A LC rate at five-years of 93% and a VHI of 12.7 (0-63) was determined. It appeared feasible to irradiate one vocal cord within 1-2mm accuracy. This way sparing of the contralateral (CL) vocal cord and CL normal tissues, could be achieved.

CONCLUSIONS: Given the accuracy (1-2mm) and small volume disease (CTV limited to one vocal cord), for the use of stereotactic RT techniques SVCI with large fraction sizes is currently being investigated in clinic. It is argued that hypofractionated SVCI can be a competitive alternative to laser surgery.

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BACKGROUND: Aberrant DNA methylation has been implicated as a key survival mechanism in cancer, whereby promoter hypermethylation silences genes essential for many cellular processes including apoptosis. Limited data is available on the methylation profile of apoptotic genes in prostate cancer (CaP). The aim of this study was to profile methylation of apoptotic-related genes in CaP using denaturing high performance liquid chromatography (DHPLC).

METHODS: Based on an in silico selection process, 13 genes were screened for methylation in CaP cell lines using DHPLC. Quantitative methylation specific PCR was employed to determine methylation levels in prostate tissue specimens (n = 135), representing tumor, histologically benign prostate, high-grade prostatic intraepithelial neoplasia and benign prostatic hyperplasia. Gene expression was measured by QRT-PCR in cell lines and tissue specimens.

RESULTS: The promoters of BIK, BNIP3, cFLIP, TMS1, DCR1, DCR2, and CDKN2A appeared fully or partially methylated in a number of malignant cell lines. This is the first report of aberrant methylation of BIK, BNIP3, and cFLIP in CaP. Quantitative methylation analysis in prostate tissues identified 5 genes (BNIP3, CDKN2A, DCR1, DCR2 and TMS1) which were frequently methylated in tumors but were unmethylated in 100% of benign tissues. Furthermore, 69% of tumors were methylated in at least one of the five-gene panel. In the case of all genes, except BNIP3, promoter hypermethylation was associated with concurrent downregulation of gene expression.

CONCLUSION: Future examination of this "CaP apoptotic methylation signature" in a larger cohort of patients is justified to further evaluate its value as a diagnostic and prognostic marker.

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The Association of Cancer Physicians in the United Kingdom has developed a strategy to improve outcomes for cancer patients and identified the goals and commitments of the Association and its members.

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Objective: To explore and define the utility of different strategies for primary prevention (ASA, diet, physical activity) and strategies of screening test (FOBT, sigmoidoscopy, colonoscopy, etc.) for colorectal cancer. Data source: Databases consulted were MEDLINE (1966 to 2006), DARE (1980 to 2006), Cochrane Central Register of Controlled Trials, Cochrane Collaboration’s Registry of Clinical Trials, Cochrane Database of Systematic Reviews and LILACS. Study selection: Studies such clinical trial, cohort and case-control studies of the effectiveness of tests for screening and primary prevention adenoma and colorectal cancer were identified by two reviewers. Data Extraction: The extraction of data and its evaluation is done in most of the process so paired. Limitations: Not strictly complies with the methodology of a systematic review and therefore reproducibility is questionable, the conclusions of this study should be extrapolated with caution. Conclusions: The major strategy of screening on the effectiveness of early detection of premalignant lesions or cancer is colonoscopy every 5 years, however it is necessary to evaluate this measure cost-effectiveness studies. For primary prevention, aspirin and cyclooxygenase-2 inhibitors reduce the incidence of colorectal adenomas. Aspirin can reduce colorectal cancer incidence. However, these medications may be associated with a significant risk of cardiovascular events and gastrointestinal bleeding. The balance between risks and benefits must be evaluated in future studies.

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A sensitive assay to identify volatile organic metabolites (VOMs) as biomarkers that can accurately diagnose the onset of breast cancer using non-invasively collected clinical specimens is ideal for early detection. Therefore the aim of this study was to establish the urinary metabolomic profile of breast cancer patients and healthy individuals (control group) and to explore the VOMs as potential biomarkers in breast cancer diagnosis at early stage. Solid-phase microextraction (SPME) using CAR/PDMS sorbent combined with gas chromatography–mass spectrometry was applied to obtain metabolomic information patterns of 26 breast cancer patients and 21 healthy individuals (controls). A total of seventy-nine VOMs, belonging to distinct chemical classes, were detected and identified in control and breast cancer groups. Ketones and sulfur compounds were the chemical classes with highest contribution for both groups. Results showed that excretion values of 6 VOMs among the total of 79 detected were found to be statistically different (p < 0.05). A significant increase in the peak area of (−)-4-carene, 3-heptanone, 1,2,4-trimethylbenzene, 2-methoxythiophene and phenol, in VOMs of cancer patients relatively to controls was observed. Statiscally significant lower abundances of dimethyl disulfide were found in cancer patients. Bioanalytical data were submitted to multivariate statistics [principal component analysis (PCA)], in order to visualize clusters of cases and to detect the VOMs that are able to differentiate cancer patients from healthy individuals. Very good discrimination within breast cancer and control groups was achieved. Nevertheless, a deep study using a larger number of patients must be carried out to confirm the results.

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With recent advances in mass spectrometry techniques, it is now possible to investigate proteins over a wide range of molecular weights in small biological specimens. This advance has generated data-analytic challenges in proteomics, similar to those created by microarray technologies in genetics, namely, discovery of "signature" protein profiles specific to each pathologic state (e.g., normal vs. cancer) or differential profiles between experimental conditions (e.g., treated by a drug of interest vs. untreated) from high-dimensional data. We propose a data analytic strategy for discovering protein biomarkers based on such high-dimensional mass-spectrometry data. A real biomarker-discovery project on prostate cancer is taken as a concrete example throughout the paper: the project aims to identify proteins in serum that distinguish cancer, benign hyperplasia, and normal states of prostate using the Surface Enhanced Laser Desorption/Ionization (SELDI) technology, a recently developed mass spectrometry technique. Our data analytic strategy takes properties of the SELDI mass-spectrometer into account: the SELDI output of a specimen contains about 48,000 (x, y) points where x is the protein mass divided by the number of charges introduced by ionization and y is the protein intensity of the corresponding mass per charge value, x, in that specimen. Given high coefficients of variation and other characteristics of protein intensity measures (y values), we reduce the measures of protein intensities to a set of binary variables that indicate peaks in the y-axis direction in the nearest neighborhoods of each mass per charge point in the x-axis direction. We then account for a shifting (measurement error) problem of the x-axis in SELDI output. After these pre-analysis processing of data, we combine the binary predictors to generate classification rules for cancer, benign hyperplasia, and normal states of prostate. Our approach is to apply the boosting algorithm to select binary predictors and construct a summary classifier. We empirically evaluate sensitivity and specificity of the resulting summary classifiers with a test dataset that is independent from the training dataset used to construct the summary classifiers. The proposed method performed nearly perfectly in distinguishing cancer and benign hyperplasia from normal. In the classification of cancer vs. benign hyperplasia, however, an appreciable proportion of the benign specimens were classified incorrectly as cancer. We discuss practical issues associated with our proposed approach to the analysis of SELDI output and its application in cancer biomarker discovery.

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Sphingolipids not only function as structural components of cell membranes but also act as signaling molecules to regulate fundamental cellular responses, such as cell death and differentiation, proliferation and certain types of inflammation. Particularly the cellular balance between ceramide and sphingosine 1-phosphate seems to be crucial for a cell's decision to either undergo apoptosis or proliferate, two events which are implicated in tumor development and growth. Whereas ceramide possesses proapoptotic capacity in many cell types, sphingosine 1-phosphate acts as a counterplayer able to induce cell proliferation and protect cells from undergoing apoptosis. Therefore, tipping the balance in favour of ceramide production, i.e. by inhibiting ceramidase or sphingosine kinase activities has potential to support its proapoptotic action and hence represents a promising rational approach to effective cancer therapy. This review highlights most recent data on the regulation of cellular sphingolipid formation and their potential implication in tumor development, and provides perspectives for their use as targets in molecular intervention therapy.

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Histopathologic tumor regression grades (TRGs) after neoadjuvant chemotherapy predict survival in different cancers. In bladder cancer, corresponding studies have not been conducted. Fifty-six patients with advanced invasive urothelial bladder cancer received neoadjuvant chemotherapy before cystectomy and lymphadenectomy. TRGs were defined as follows: TRG1: complete tumor regression; TRG2: >50% tumor regression; TRG3: 50% or less tumor regression. Separate TRGs were assigned for primary tumors and corresponding lymph nodes. The prognostic impact of these 2 TRGs, the highest (dominant) TRG per patient, and competing tumor features reflecting tumor regression (ypT/ypN stage, maximum diameter of the residual tumor) were determined. Tumor characteristics in initial transurethral resection of the bladder specimens were tested for response prediction. The frequency of TRGs 1, 2, and 3 in the primary tumors were n=16, n=19, and n=21; corresponding data from the lymph nodes were n=31, n=9, and n=16. Interobserver agreement in determination of the TRG was strong (κ=0.8). Univariately, all evaluated parameters were significantly (P≤0.001) related to overall survival; however, the segregation of the Kaplan-Meier curves was best for the dominant TRG. In multivariate analysis, only dominant TRG predicted overall survival independently (P=0.035). In transurethral resection specimens of the chemotherapy-naive bladder cancer, the only tumor feature with significant (P<0.03) predictive value for therapy response was a high proliferation rate. In conclusion, among all parameters reflecting tumor regression, the dominant TRG was the only independent risk factor. A favorable chemotherapy response is associated with a high proliferation rate in the initial chemotherapy-naive bladder cancer. This feature might help personalize neoadjuvant chemotherapy.