Whole Exome and Transcriptome RNA-Sequencing Model for the Diagnosis of Prostate Cancer

In our previous study, we developed a genome-wide DNA methylation model for the diagnosis of prostate cancer, and we pointed out that a considerable average error is associated with the current method for the diagnosis of prostate cancer, which is predicated on pathological assessment of biopsied tissue. In this study, we utilized whole exome and transcriptome RNA-sequencing (RNA-seq) data that were derived from 468 tumor samples and 51 normal samples of prostatic tissue, and we analyzed over 20,000 genes per sample. We were able to develop a mathematical model that classified tumor tissue versus normal tissue with a high accuracy. The overall sensitivity was 97.01%, and the overall specificity was 94.12%. The input variables to the model were the mRNA expression values of the following nine genes: ANGPT1, MED21, AOX1, PLP2, HPN, HPN-AS1, EPHA10, NKX2-3, and LRFN1. The model was validated with unknown samples, with a 10-fold cross-validation, and a leave-one-out cross-validation. We present here a genomic model, based on a whole exome and transcriptome RNA-seq analysis of biopsied prostatic tissue, that could be utilized in the diagnosis of prostate cancer.