Whole Exome Sequencing Identifies Putative Predictors of Recurrent Prostate Cancer with High Accuracy

Abstract

Abstract

Prostate cancer (PCa) is a highly common cancer among men but lacks robust diagnostics that can predict disease recurrence after initial treatment, for example, with radical prostatectomy. Recent advances in genomics and next-generation sequencing heralded the discovery of biomarkers such as the androgen receptor gene (AR) splice events, the TMPRSS2:EGR gene fusion, long noncoding RNA MALAT-1 and SCHLAP1 for PCa prognosis. Still, the question of why some patients experience recurrence, whereas others do not introduce marked uncertainty for both patients and physicians. We report here the whole exome sequencing of 30 recurrent and 44 nonrecurrent PCa patients. We identified 72 and 34 specific somatic single nucleotide variations in the recurrent and the nonrecurrent group, respectively, and developed a classification model to forecast PCa recurrence using a random forest model. The model displayed a sensitivity and specificity of 87.8% and 94.4%, respectively, for identifying the patients with recurrent PCa. These observations warrant further research in independent and larger clinical samples so as to inform future diagnostics innovation for PCa prognosis and recurrence.