Aquaglyceroporin-3's Expression and Cellular Localization Is Differentially Modulated by Hypoxia in Prostate Cancer Cell Lines.
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ABSTRACT:
SUBMITTER: de Almeida A
PROVIDER: S-EPMC8068192 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundHistone deacetylase inhibitors (HDACis) like vorinostat are promising radiosensitisers in prostate cancer, but their effect under hypoxia is not known. We investigated gene expression associated with radiosensitisation of normoxic and hypoxic prostate cancer cells by vorinostat.MethodsCells were exposed to vorinostat under normoxia or hypoxia and subjected to gene expression profiling before irradiation and clonogenic survival analysis.ResultsPretreatment with vorinostat led to radiosensitisation of the intrinsically radioresistant DU 145 cells, but not the radiosensitive PC-3 and 22Rv1 cells, and was independent of hypoxia status. Knockdown experiments showed that the sensitisation was not caused by repression of hypoxia-inducible factor HIF1 or tumour protein TP53. Global deregulation of DNA repair and chromatin organisation genes was associated with radiosensitisation under both normoxia and hypoxia. A radiosensitisation signature with expression changes of 56 genes was generated and valid for both conditions. For eight signature genes, baseline expression also correlated with sensitisation, showing potential as pretreatment biomarker. The hypoxia independence of the signature was confirmed in a clinical data set.ConclusionsPretreatment with HDACi may overcome radioresistance of hypoxic prostate tumours by similar mechanisms as under normoxia. We propose a gene signature to predict radiosensitising effects independent of hypoxia status.
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Project description:Gene dynamic analysis is essential in identifying target genes involved pathogenesis of various diseases, including cancer. Cancer prognosis is often influenced by hypoxia. We apply a multi-step pipeline to study dynamic gene expressions in response to hypoxia in three cancer cell lines: prostate (DU145), colon (HT29), and breast (MCF7) cancers. We identified 26 distinct temporal expression patterns for prostate cell line, and 29 patterns for colon and breast cell lines. The module-based dynamic networks have been developed for all three cell lines. Our analyses improve the existing results in multiple ways. It exploits the time-dependence nature of gene expression values in identifying the dynamically significant genes; hence, more key significant genes and transcription factors have been identified. Our gene network returns significant information regarding biologically important modules of genes. Furthermore, the network has potential in learning the regulatory path between transcription factors and the downstream genes. In addition, our findings suggest that changes in genes BMP6 and ARSJ expression might have a key role in the time-dependent response to hypoxia in breast cancer.
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