Here, we performed a systematic analysis to discover new biomarkers of overall survival and tumor progression in ovarian cancer patients. More specifically, we determined whether nuclear-encoded mitochondrial genes related to mitochondrial biogenesis and function are effective in predicting clinical outcome in ovarian cancer. As a consequence, we are able to provide in silico validation of the prognostic value of these mitochondrial markers, in a well-defined population of ovarian cancer patients. Towards this end, we used a group of N=111 ovarian cancer patients (serous type; stage III), with optimal de-bulking. Importantly, in this group of cancer patients, CA125 and PCNA (conventional markers) were associated with poor overall survival, as would be expected. Using this approach, we identified >100 new individual mitochondrial gene probes that effectively predicted significantly reduced overall survival, with hazard-ratios (HR) of up to 3.68 (p < 9.8e-05). These mitochondrial mRNA transcripts included membrane proteins, chaperones, anti-oxidant enzymes, as well as mitochondrial ribosomal proteins (MRPs) and key members of the OXPHOS (I-V) complexes. Based on this bioinformatics analysis and in silico validation, we conclude that mitochondrial biogenesis and OXPHOS should both be considered as new therapeutic targets, for the more effective treatment of human ovarian cancers. The mitochondrial biomarkers that we have identified could also be employed as new companion diagnostics to assist oncologists in: i) more accurately predicting clinical outcomes and ii) improving the response to therapy, in ovarian cancer patients.
Keywords: mitochondrial biomarkers; ovarian cancer; recurrence; relapse; treatment failure.