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  • RNA-seq profiling of a radi...
    Young, Arabella; Berry, Rachael; Holloway, Adele F; Blackburn, Nicholas B; Dickinson, Joanne L; Skala, Marketa; Phillips, Jessica L; Brettingham-Moore, Kate H

    BMC cancer, 11/2014, Letnik: 14, Številka: 1
    Journal Article

    Radiotherapy is a chosen treatment option for prostate cancer patients and while some tumours respond well, up to 50% of patients may experience tumour recurrence. Identification of functionally relevant predictive biomarkers for radioresponse in prostate cancer would enable radioresistant patients to be directed to more appropriate treatment options, avoiding the side-effects of radiotherapy. Using an in vitro model to screen for novel biomarkers of radioresistance, transcriptome analysis of a radioresistant (PC-3) and radiosensitive (LNCaP) prostate cancer cell line was performed. Following pathway analysis candidate genes were validated using qRT-PCR. The DNA repair pathway in radioresistant PC-3 cells was then targeted for radiation sensitization using the PARP inhibitor, niacinimide. Opposing regulation of a DNA repair and replication pathway was observed between PC-3 and LNCaP cells from RNA-seq analysis. Candidate genes BRCA1, RAD51, FANCG, MCM7, CDC6 and ORC1 were identified as being significantly differentially regulated post-irradiation. qRT-PCR validation confirmed BRCA1, RAD51 and FANCG as being significantly differentially regulated at 24 hours post radiotherapy (p-value =0.003, 0.045 and 0.003 respectively). While the radiosensitive LNCaP cells down-regulated BRCA1, FANCG and RAD51, the radioresistant PC-3 cell line up-regulated these candidates to promote cell survival post-radiotherapy and a similar trend was observed for MCM7, CDC6 and ORC1. Inhibition of DNA repair using niacinamide sensitised the radioresistant cells to irradiation, reducing cell survival at 2 Gy from 66% to 44.3% (p-value =0.02). These findings suggest that the DNA repair candidates identified via RNA-seq hold potential as both targets for radiation sensitization and predictive biomarkers in prostate cancer.