Zheng Z, Mao S, Gu Z, et al. - This study was intended to construct a genomic-clinicopathologic nomogram for the prediction of lymph node invasion (LNI) in prostate cancer (PCa). Researchers distinguished differentially expressed genes between LNI and non-LNI PCa samples in the Cancer Genome Atlas database. They performed Univariate Cox regression analysis and minimum redundancy maximum relevance for gene selection. The results of this research revealed that the proposed nomogram combining the 37-gene-based support vector machine model with the Gleason grade had the potential to preoperatively predict LNI in PCa. For functional studies and mechanistic analyses, some of the hub genes should be prioritized.