277 resultados para BREAST-CANCER CELLS


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Background: Breast cancer mortality is declining in many Western countries. If mammography screening contributed to decreases in mortality, then decreases in advanced breast cancer incidence should also be noticeable.
Patients and methods: We assessed incidence trends of advanced breast cancer in areas where mammography screening is practiced for at least 7 years with 60% minimum participation and where population-based registration of advanced breast cancer existed. Through a systematic Medline search, we identified relevant published data for Australia, Italy, Norway, Switzerland, The Netherlands, UK and the USA. Data from cancer registries in Northern Ireland, Scotland, the USA (Surveillance, Epidemiology and End Results (SEER), and Connecticut), and Tasmania (Australia) were available for the study. Criterion for advanced cancer was the tumour size, and if not available, spread to regional/distant sites.
Results: Age-adjusted annual percent changes (APCs) were stable or increasing in ten areas (APCs of -0.5% to 1.7%). In four areas (Firenze, the Netherlands, SEER and Connecticut) there were transient downward trends followed by increases back to pre-screening rates.
Conclusions: In areas with widespread sustained mammographic screening, trends in advanced breast cancer incidence do not support a substantial role for screening in the decrease in mortality.

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The known breast cancer susceptibility polymorphisms in FGFR2, TNRC9/TOX3, MAP3K1, LSP1, and 2q35 confer increased risks of breast cancer for BRCA1 or BRCA2 mutation carriers. We evaluated the associations of 3 additional single nucleotide polymorphisms (SNPs), rs4973768 in SLC4A7/NEK10, rs6504950 in STXBP4/COX11, and rs10941679 at 5p12, and reanalyzed the previous associations using additional carriers in a sample of 12,525 BRCA1 and 7,409 BRCA2 carriers. Additionally, we investigated potential interactions between SNPs and assessed the implications for risk prediction. The minor alleles of rs4973768 and rs10941679 were associated with increased breast cancer risk for BRCA2 carriers (per-allele HR - 1.10, 95% CI: 1.03-1.18, P - 0.006 and HR - 1.09, 95% CI: 1.01-1.19, P = 0.03, respectively). Neither SNP was associated with breast cancer risk for BRCA1 carriers, and rs6504950 was not associated with breast cancer for either BRCA1 or BRCA2 carriers. Of the 9 polymorphisms investigated, 7 were associated with breast cancer for BRCA2 carriers (FGFR2, TOX3, MAP3K1, LSP1, 2q35, SLC4A7, 5p12, P 7 = 10 x (11) - 0.03), but only TOX3 and 2q35 were associated with the risk for BRCA1 carriers (P = 0.0049, 0.03, respectively). All risk-associated polymorphisms appear to interact multiplicatively on breast cancer risk for mutation carriers. Based on the joint genotype distribution of the 7 risk-associated SNPs in BRCA2 mutation carriers, the 5% of BRCA2 carriers at highest risk (i.e., between 95th and 100th percentiles) were predicted to have a probability between 80% and 96% of developing breast cancer by age 80, compared with 42%

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BACKGROUND: In this study we aimed to evaluate the role of a SNP in intron I of the ERCC4 gene (rs744154), previously reported to be associated with a reduced risk of breast cancer in the general population, as a breast cancer risk modifier in BRCA1 and BRCA2 mutation carriers.

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Breast cancer is the most common cause of cancer death in the United Kingdom, with a lifetime risk of one in nine in women. Only 5-10% of all cancers is thought to be due to strongly penetrant inherited predisposing genes, such as BRCA1 and BRCA2. However, other less penetrant genes, including some autosomal recessive genes, are likely to be of etiological importance in other families. This review addresses the current knowledge of breast cancer susceptibility genes and explores the possibilities for future developments. Features of tumor pathology, prognosis, and the scope for targeted treatments in mutation carriers are discussed, and the management of known carriers and those at increased risk for developing breast cancer are evaluated. Genetic testing for cancer susceptibility may become widely available in the future, and has important ethical and management implications. (C) 2004 Wiley-Liss, Inc.

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Aims-An increased concentration of insulin-like growth factor 1 (IGF-1) is an independent risk factor for premenopausal breast cancer. Tamoxifen is thought initially to reduce concentrations of IGF-1 and increase concentrations of the IGF binding proteins. The aim of this study was to compare concentrations of IGF-1, IGF binding protein 1 (IGF-BP1), and IGF-BP3 in patients with breast cancer (n = 14) with those seen in control subjects (n = 23) and to assess the effect of tamoxifen on IGF status in these patients.

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Ligand-induced activation of peroxisome proliferator-activated receptor gamma (PPAIR gamma) inhibits proliferation in cancer cells in vitro and in vivo; however, the downstream targets remain undefined. We report the identification of a peroxisome proliferator response element in the promoter region of the Na+/ H transporter gene NHE1, the overexpression of which has been associated with carcinogenesis. Exposure of breast cancer cells expressing high levels of PPAR gamma to its natural and synthetic agonists resulted in downregulation of NHE1 transcription as well as protein expression. Furthermore, the inhibitory effect of activated PPAR gamma on tumor colony-forming ability was abrogated on overexpression of NHE1, whereas small interfering RNA-mediated gene silencing of NHE1 significantly increased the sensitivity of cancer cells to growth-inhibitory stimuli. Finally, histopathologic analysis of breast cancer biopsies obtained from patients with type II diabetes treated with the synthetic agonist rosiglitazone showed significant repression of NHE1 in the tumor tissue. These data provide evidence for tumor-selective downregulation of NHE1 by activated PPAR gamma in vitro and in pathologic specimens from breast cancer patients and could have potential implications for the judicious use of low doses of PPAR gamma ligands in combination chemotherapy regimens for an effective therapeutic response. [Cancer Res 2009;69(22):8636-44]

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Purpose: The runt-related transcription factor, Runx2 may have an oncogenic role in mediating metastatic events in breast cancer, but whether Runx2 has a role in the early phases of breast cancer development is not clear. We examined the expression of Runx2 and its relationship with oestrogen receptor (ER) and progesterone receptor (PR) in breast cancer cell lines and tissues.

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Background We had previously established that inactivation of RUNX3 occurs by frequent promoter hypermethylation and protein mislocalization in invasive ductal carcinomas (IDC) of breast. Here, we hypothesize that inactivation of RUNX3 occurring in ductal carcinoma in situ (DCIS) represent early event in breast carcinogenesis. Methods The study cohort of 40 patients included 17 pure DCIS cases and 23 cases of DCIS with associated IDC (DCIS-IDC). The DCIS and IDC components of mixed cases were manually microdissected to permit separate evaluation. All the 63 samples including 17 pure DCIS, 23 samples each of DCIS and IDC of DCIS-IDC cases were analyzed for RUNX3 protein expression using R3-6E9 monoclonal antibody as well as promoter methylation status by methylation specific PCR. Results Compared to matched normal breast samples (4 of 40, 10%), DCIS (35 of 40, 88%) and IDC (21 of 23, 91%) exhibited significant RUNX3 inactivation (P

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Proteomic and transcriptomic platforms both play important roles in cancer research, with differing strengths and limitations. Here, we describe a proteo-transcriptomic integrative strategy for discovering novel cancer biomarkers, combining the direct visualization of differentially expressed proteins with the high-throughput scale of gene expression profiling. Using breast cancer as a case example, we generated comprehensive two-dimensional electrophoresis (2DE)/mass spectrometry (MS) proteomic maps of cancer (MCF-7 and HCC-38) and control (CCD-1059Sk) cell lines, identifying 1724 expressed protein spots representing 484 different protein species. The differentially expressed cell-line proteins were then mapped to mRNA transcript databases of cancer cell lines and primary breast tumors to identify candidate biomarkers that were concordantly expressed at the gene expression level. Of the top nine selected biomarker candidates, we reidentified ANX1, a protein previously reported to be differentially expressed in breast cancers and normal tissues, and validated three other novel candidates, CRAB, 6PGL, and CAZ2, as differentially expressed proteins by immunohistochemistry on breast tissue microarrays. In total, close to half (4/9) of our protein biomarker candidates were successfully validated. Our study thus illustrates how the systematic integration of proteomic and transcriptomic data from both cell line and primary tissue samples can prove advantageous for accelerating cancer biomarker discovery.

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The identification of specific oncogenes and tumor suppressor genes in regions of recurrent aneuploidy is a major challenge of molecular cancer research. Using both oligonucleotide single-nucleotide polymorphism and mRNA expression arrays, we integrated genomic and transcriptional information to identify and prioritize candidate cancer genes in regions of increased and decreased chromosomal copy number in a cohort of primary breast cancers. Confirming the validity of this approach, several regions of previously-known copy number (CN) alterations in breast cancer could be successfully reidentified. Focusing on regions of decreased CN, we defined a prioritized list of eighteen candidate genes, which included ARPIN, FBNI, and LZTSI, previously shown to be associated with cancers in breast or other tissue types, and novel genes such as P29, MORF4LI, and TBCID5. One such gene, the RUNX3 transcription factor, was selected for further study. We show that RUNX3 is present at reduced CNs in proportion to the rest of the tumor genome and that RUNX3 CN reductions can also be observed in a breast cancer series from a different center. Using tissue microarrays, we demonstrate in an independent cohort of over 120 breast tissues that RUNX3 protein is expressed in normal breast epithelium but not fat and stromal tissue, and widely down-regulated in the majority of breast cancers (> 85%). In vitro, RUNX3 overexpression suppressed the invasive potential of MDA-MB-231 breast cancer cells in a matrigel assay. Our results demonstrate the utility of integrative genomic approaches to identify novel potential cancer-related genes in primary tumors. This article contains Supplementary Material available at http:// www.interscience.wiley.com/jpages/1045-2257/suppmat. (c) 2006 Wiley-Liss, Inc.

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Tissue microarrays allow high throughput molecular profiling of diagnostic or predictive markers in cancer specimens and rapid validation of novel potential candidates identified from genomic and proteomic analyses in a large number of tumor samples. To validate the use of tissue microarray technology for all the main biomarkers routinely used to decide breast cancer prognostication and postsurgical adjuvant therapy, we constructed a tissue microarray from 97 breast tumors, with a single 0.6 mm core per specimen. Inummostaining; of tissue microarray sections and conventional full sections of each tumor were performed using well-characterized prognostic markers (estrogen receptor ER, progesterone receptor PR and c-erbB2). The full section versus tissue microarray concordance for these stains was 97% for ER, 98% for PR, and 97% for c-erbB2, respectively, with a strong statistical association (kappa value more than 0.90). Fluorescence in situ hybridization analysis for HER-2/neu gene amplification from the single-core tissue microarray was technically successful in about 90% (87/97) of the cases, with a concordance of 95% compared with parallel analyses with the full sections. The correlation with other pathological parameters was not significantly different between full-section and array-based results. It is concluded that the constructed tissue microarray with a single core per specimen ensures full biological representativeness to identify the associations between biomarkers and clinicopathological parameters, with no significant associated sampling bias.