The aim of this study was to identify predictor sets of genes whose over- or underexpression in human sporadic adrenocortical tumors would help to identify malignant vs. benign tumors and to predict postsurgical metastatic recurrence. For this, we analyzed the expression of 230 candidate genes using cDNA microarrays in a series of 57 well-characterized human sporadic adrenocortical tumors (33 adenomas and 24 carcinomas). We identified two clusters of genes (the IGF-II cluster containing eight genes, including IGF-II, and the steroidogenesis cluster containing six genes encoding steroidogenic enzymes plus eight other genes) whose combined levels of expression appeared to be good predictors of malignancy. This predictive value was as strong as that of the pathological score of Weiss. The analysis of the population of carcinomas (13 tumors) for genes whose expression would be strongly different between recurring and nonrecurring tumors allowed identification of 14 genes meeting these criteria. Among these genes, there are probably new markers of tumor evolution that will deserve additional validation on a larger scale. Taken together, these results show that the parallel analysis of the expression levels of a selected group of genes on microgram quantities of tumor RNA (a quantity that can be obtained from fine needle aspirations) appears as a complementary method to histopathology for the diagnosis and prognosis of evolution of adrenocortical carcinomas.
Under standard culture conditions, tumor cells are exposed to 20% O(2), whereas the mean tumor oxygen levels within the tumor are much lower. We demonstrate, using low-passaged human tumor cell cultures established from glioma, that a reduction in the oxygen level in these cell cultures dramatically increases the percentage of CD133 expressing cells.
Gliomas such as oligodendrogliomas (ODG) and glioblastomas (GBM) are brain tumours with different clinical outcomes. Histology-based classification of these tumour types is often difficult. Therefore the first aim of this study was to gain microRNA data that can be used as reliable signatures of oligodendrogliomas and glioblastomas. We investigated the levels of 282 microRNAs using membrane-array hybridisation and real-time PCR in ODG, GBM and control brain tissues. In comparison to these control tissues, 26 deregulated microRNAs were identified in tumours and the tissue levels of seven microRNAs (miR-21, miR-128, miR-132, miR-134, miR-155, miR-210 and miR-409-5p) appropriately discriminated oligodendrogliomas from glioblastomas. Genomic, epigenomic and host gene expression studies were conducted to investigate the mechanisms involved in these deregulations. Another aim of this study was to better understand glioma physiopathology looking for targets of deregulated microRNAs. We discovered that some targets of these microRNAs such as STAT3, PTBP1 or SIRT1 are differentially expressed in gliomas consistent with deregulation of microRNA expression. Moreover, MDH1, the target of several deregulated microRNAs, is repressed in glioblastomas, making an intramitochondrial-NAD reduction mediated by the mitochondrial aspartate-malate shuttle unlikely. Understanding the connections between microRNAs and bioenergetic pathways in gliomas may lead to identification of novel therapeutic targets.
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