63 research outputs found

    Cervical squamous carcinoma cells are resistant to the combined action of tumor necrosis factor-α and histamine whereas normal keratinocytes undergo cytolysis

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    <p>Abstract</p> <p>Background</p> <p>Previous reports showed that mast cells can typically be found in the peritumoral stroma of cervix carcinomas as well as in many other cancers. Both histamine and TNF-α are potent preformed mast cell mediators and they can act simultaneously after release from mast cells. Thus, the effect of TNF-α and histamine on cervical carcinoma cell lines was studied.</p> <p>Methods and results</p> <p>TNF-α alone induced slight growth inhibition and cell cycle arrest at G0/G1 phase in SiHa cells, but increased their migration. Histamine alone had no effect on cells. In addition, TNF-α and histamine in combination showed no additional effect over that by TNF-α alone, although SiHa cells were even pretreated with a protein synthesis inhibitor. Furthermore, TNF-α-sensitive ME-180 carcinoma cells were also resistant to the combination effect of TNF-α and histamine. In comparison, TNF-α or histamine alone induced growth inhibition in a non-cytolytic manner in normal keratinocytes, an effect that was further enhanced to cell cytolysis when both mediators acted in combination. Keratinocytes displayed strong TNF receptor (TNFR) I and II immunoreactivity, whereas SiHa and ME-180 cells did not. Furthermore, cervix carcinoma specimens revealed TNF-α immunoreactivity in peritumoral cells and carcinoma cells. However, the immunoreactivity of both TNFRs was less intense in carcinoma cells than that in epithelial cells in cervical specimens with non-specific inflammatory changes.</p> <p>Conclusion</p> <p>SiHa and ME-180 cells are resistant to the cytolytic effect of TNF-α and histamine whereas normal keratinocytes undergo cytolysis, possibly due to the smaller amount of TNFRs in SiHa and ME-180 cells. In the cervix carcinoma, the malignant cells may resist this endogenous cytolytic action and TNF-α could even enhance carcinoma cell migration.</p

    Two common nonsynonymous paraoxonase 1 (PON1) gene polymorphisms and brain astrocytoma and meningioma

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    <p>Abstract</p> <p>Background</p> <p>Human serum paraoxonase 1 (PON1) plays a major role in the metabolism of several organophosphorus compounds. The enzyme is encoded by the polymorphic gene <it>PON1</it>, located on chromosome 7q21.3. Aiming to identify genetic variations related to the risk of developing brain tumors, we investigated the putative association between common nonsynonymous <it>PON1 </it>polymorphisms and the risk of developing astrocytoma and meningioma.</p> <p>Methods</p> <p>Seventy one consecutive patients with brain tumors (43 with astrocytoma grade II/III and 28 with meningioma) with ages ranging 21 to 76 years, and 220 healthy controls subjects were analyzed for the frequency of the nonsynonymous <it>PON1 </it>genotypes L55M rs854560 and Q192R rs662. All participants were adult Caucasian individuals recruited in the central area of Spain.</p> <p>Results</p> <p>The frequencies of the <it>PON1 </it>genotypes and allelic variants of the polymorphisms <it>PON1 </it>L55M and <it>PON1 </it>Q192R did not differ significantly between patients with astrocytoma and meningioma and controls. The minor allele frequencies were as follows: <it>PON1 </it>55L, 0.398, 0.328 and 0.286 for patients with astrocytoma, meningioma and control individuals, respectively; <it>PON1 </it>192R, 0.341, 0.362 and 0.302 for patients with astrocytoma, meningioma and control individuals, respectively. Correction for age, gender, or education, made no difference in odds ratios and the <it>p </it>values remained non-significant. Haplotype association analyses did not identify any significant association with the risk of developing astrocytoma or meningioma.</p> <p>Conclusions</p> <p>Common nonsynonymous <it>PON1 </it>polymorphisms are not related with the risk of developing astrocytoma and meningioma.</p

    Ovarian cancer

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    Ovarian cancer is not a single disease and can be subdivided into at least five different histological subtypes that have different identifiable risk factors, cells of origin, molecular compositions, clinical features and treatments. Ovarian cancer is a global problem, is typically diagnosed at a late stage and has no effective screening strategy. Standard treatments for newly diagnosed cancer consist of cytoreductive surgery and platinum-based chemotherapy. In recurrent cancer, chemotherapy, anti-angiogenic agents and poly(ADP-ribose) polymerase inhibitors are used, and immunological therapies are currently being tested. High-grade serous carcinoma (HGSC) is the most commonly diagnosed form of ovarian cancer and at diagnosis is typically very responsive to platinum-based chemotherapy. However, in addition to the other histologies, HGSCs frequently relapse and become increasingly resistant to chemotherapy. Consequently, understanding the mechanisms underlying platinum resistance and finding ways to overcome them are active areas of study in ovarian cancer. Substantial progress has been made in identifying genes that are associated with a high risk of ovarian cancer (such as BRCA1 and BRCA2), as well as a precursor lesion of HGSC called serous tubal intraepithelial carcinoma, which holds promise for identifying individuals at high risk of developing the disease and for developing prevention strategies

    Pan-cancer analysis of whole genomes

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    Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

    Metabolic Turnover of Synaptic Proteins: Kinetics, Interdependencies and Implications for Synaptic Maintenance

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    Chemical synapses contain multitudes of proteins, which in common with all proteins, have finite lifetimes and therefore need to be continuously replaced. Given the huge numbers of synaptic connections typical neurons form, the demand to maintain the protein contents of these connections might be expected to place considerable metabolic demands on each neuron. Moreover, synaptic proteostasis might differ according to distance from global protein synthesis sites, the availability of distributed protein synthesis facilities, trafficking rates and synaptic protein dynamics. To date, the turnover kinetics of synaptic proteins have not been studied or analyzed systematically, and thus metabolic demands or the aforementioned relationships remain largely unknown. In the current study we used dynamic Stable Isotope Labeling with Amino acids in Cell culture (SILAC), mass spectrometry (MS), Fluorescent Non-Canonical Amino acid Tagging (FUNCAT), quantitative immunohistochemistry and bioinformatics to systematically measure the metabolic half-lives of hundreds of synaptic proteins, examine how these depend on their pre/postsynaptic affiliation or their association with particular molecular complexes, and assess the metabolic load of synaptic proteostasis. We found that nearly all synaptic proteins identified here exhibited half-lifetimes in the range of 2-5 days. Unexpectedly, metabolic turnover rates were not significantly different for presynaptic and postsynaptic proteins, or for proteins for which mRNAs are consistently found in dendrites. Some functionally or structurally related proteins exhibited very similar turnover rates, indicating that their biogenesis and degradation might be coupled, a possibility further supported by bioinformatics-based analyses. The relatively low turnover rates measured here (∼0.7% of synaptic protein content per hour) are in good agreement with imaging-based studies of synaptic protein trafficking, yet indicate that the metabolic load synaptic protein turnover places on individual neurons is very substantial
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