6 resultados para oncogenesis

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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BACKGROUND: Cancer initiation and progression might be driven by small populations of cells endowed with stem cell-like properties. Here we comparatively addressed the expression of genes encoding putative stemness regulators including c-Myc, Klf4, Nanog, Oct4A and Sox2 genes in benign prostatic hyperplasia (BPH) and prostate cancer (PCA). METHODS: Fifty-eight PCA and thirty-nine BPH tissues samples were used for gene expression analysis, as evaluated by quantitative real-time polymerase chain reaction (qRT-PCR). The expression of specific Klf4 isoforms was tested by conventional PCR. Klf4 specific antibodies were used for protein detection in a tissue microarray including 404 prostate samples. RESULTS: Nanog, Oct4A and Sox2 genes were comparably expressed in BPH and PCA samples, whereas c-Myc and Klf4 genes were expressed to significantly higher extents in PCA than in BPH specimens. Immunohistochemical studies revealed that Klf4 protein is detectable in a large majority of epithelial prostatic cells, irrespective of malignant transformation. However, in PCA, a predominantly cytoplasmic location was observed, consistent with the expression of a differentially spliced Klf4α isoform. CONCLUSION: Klf4 is highly expressed at gene and protein level in BPH and PCA tissues but a cytoplasmic location of the specific gene product is predominantly detectable in malignant cells. Klf4 location might be of critical relevance to steer its functions during oncogenesis.

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Background Levels of differentiation among populations depend both on demographic and selective factors: genetic drift and local adaptation increase population differentiation, which is eroded by gene flow and balancing selection. We describe here the genomic distribution and the properties of genomic regions with unusually high and low levels of population differentiation in humans to assess the influence of selective and neutral processes on human genetic structure. Methods Individual SNPs of the Human Genome Diversity Panel (HGDP) showing significantly high or low levels of population differentiation were detected under a hierarchical-island model (HIM). A Hidden Markov Model allowed us to detect genomic regions or islands of high or low population differentiation. Results Under the HIM, only 1.5% of all SNPs are significant at the 1% level, but their genomic spatial distribution is significantly non-random. We find evidence that local adaptation shaped high-differentiation islands, as they are enriched for non-synonymous SNPs and overlap with previously identified candidate regions for positive selection. Moreover there is a negative relationship between the size of islands and recombination rate, which is stronger for islands overlapping with genes. Gene ontology analysis supports the role of diet as a major selective pressure in those highly differentiated islands. Low-differentiation islands are also enriched for non-synonymous SNPs, and contain an overly high proportion of genes belonging to the 'Oncogenesis' biological process. Conclusions Even though selection seems to be acting in shaping islands of high population differentiation, neutral demographic processes might have promoted the appearance of some genomic islands since i) as much as 20% of islands are in non-genic regions ii) these non-genic islands are on average two times shorter than genic islands, suggesting a more rapid erosion by recombination, and iii) most loci are strongly differentiated between Africans and non-Africans, a result consistent with known human demographic history.

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MET, also known as hepatocyte growth factor receptor (HGFR), is a receptor tyrosine kinase with an important role, both in normal cellular function as well as in oncogenesis. In many cancer types, abnormal activation of MET is related to poor prognosis and various strategies to inhibit its function, including small molecule inhibitors, are currently in preclinical and clinical evaluation. Autophagy, a self-digesting recycling mechanism with cytoprotective functions, is induced by cellular stress. This process is also induced upon cytotoxic drug treatment of cancer cells and partially allows these cells to escape cell death. Thus, since autophagy protects different tumor cells from chemotherapy-induced cell death, current clinical trials aim at combining autophagy inhibitors with different cancer treatments. We found that in a gastric adenocarcinoma cell line GTL-16, where MET activity is deregulated due to receptor overexpression, two different MET inhibitors PHA665752 and EMD1214063 lead to cell death paralleled by the induction of autophagy. A combined treatment of MET inhibitors together with the autophagy inhibitor 3-MA or genetically impairing autophagy by knocking down the key autophagy gene ATG7 further decreased cell viability of gastric cancer cells. In general, we observed the induction of cytoprotective autophagy in MET expressing cells upon MET inhibition and a combination of MET and autophagy inhibition resulted in significantly decreased cell viability in gastric cancer cells.

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Autophagy plays a key role in the maintenance of cellular homeostasis. In healthy cells, such a homeostatic activity constitutes a robust barrier against malignant transformation. Accordingly, many oncoproteins inhibit, and several oncosuppressor proteins promote, autophagy. Moreover, autophagy is required for optimal anticancer immunosurveillance. In neoplastic cells, however, autophagic responses constitute a means to cope with intracellular and environmental stress, thus favoring tumor progression. This implies that at least in some cases, oncogenesis proceeds along with a temporary inhibition of autophagy or a gain of molecular functions that antagonize its oncosuppressive activity. Here, we discuss the differential impact of autophagy on distinct phases of tumorigenesis and the implications of this concept for the use of autophagy modulators in cancer therapy.

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Canine transmissible venereal tumor (CTVT) is a parasitic cancer clone that has propagated for thousands of years via sexual transfer of malignant cells. Little is understood about the mechanisms that converted an ancient tumor into the world's oldest known continuously propagating somatic cell lineage. We created the largest existing catalog of canine genome-wide variation and compared it against two CTVT genome sequences, thereby separating alleles derived from the founder's genome from somatic drivers of clonal transmissibility. We show that CTVT has undergone continuous adaptation to its transmissible allograft niche, with overlapping mutations at every step of immunosurveillance, particularly self-antigen presentation and apoptosis. We also identified chronologically early somatic mutations in oncogenesis- and immune-related genes that may represent key initiators of clonal transmissibility. Thus, we provide the first insights into the specific genomic aberrations that underlie CTVT's dogged perseverance in canids around the world.

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Several improvements in ovarian cancer treatment have been achieved in recent years, both in surgery and in combination chemotherapy with targeting. However, ovarian tumors remain the women's cancers with highest mortality rates. In this scenario, a pivotal role has been endorsed to the immunological environment and to the immunological mechanisms involved in ovarian cancer behavior. Recent evidence suggests a loss of the critical balance between immune-activating and immune-suppressing mechanisms when oncogenesis and cancer progression occur. Ovarian cancer generates a mechanism to escape the immune system by producing a highly suppressive environment. Immune-activated tumor infiltrating lymphocytes (TILs) in ovarian tumor tissue testify that the immune system is the trigger in this neoplasm. The TIL mileau has been demonstrated to be associated with better prognosis, more chemosensitivity, and more cases of optimal residual tumor achieved during primary cytoreduction. Nowadays, scientists are focusing attention on new immunologically effective tumor biomarkers in order to optimize selection of patients for recruitment in clinical trials and to identify relationships of these biomarkers with responses to immunotherapeutics. Assessing this point of view, TILs might be considered as a potent predictive immunotherapy biomarker.