Purpose: To evaluate associations between pathologic factors and erythroblast transformation-specific (ETS)-related gene (ERG) expression in prostate cancer patients. Using next-generation sequencing, we identified target genes and regulatory networks.
Methods: ERG expression in 60 radical prostatectomies was compared with pathological findings by association rule mining with the Apriori algorithm. Whole-exome and RNA sequencing were performed on three formalin-fixed, paraffin-embedded ERG-positive and negative prostate cancer samples. A network diagram identifying dominant altered genes was constructed using Cytoscape open-source bioinformatics platform and GeneMania plugin.
Results: Pathologic conditions positive for perineural invasion, apical margins, and Gleason score 3 + 4 = 7 were significantly more likely to be ERG-positive than other pathologic conditions (p = 0.0008), suggesting an association between ERG positivity, perineural invasion, apical margins, and Gleason score 3 + 4 = 7 (Firth's logistic regression: OR 42.565, 95% CI 1.670-1084.847, p = 0.0232). Results of whole-exome and RNA sequencing identified 97 somatic mutations containing common mutated genes. Regulatory network analysis identified NOTCH1, MEF2C, STAT3, LCK, CACNA2D3, PCSK7, MEF2A, PDZD2, TAB1, and ASGR1 as pivotal genes. NOTCH1 appears to function as a hub, because it had the highest node degree and betweenness. NOTCH1 staining was found 8 of 60 specimens (13%), with a significant association between ERG and NOTCH1 positivity (p = 0.001).
Conclusions: Evaluating the association between ERG expression and pathologic factors, and identifying the regulatory network and pivotal hub may help to understand the clinical significance of ERG-positive prostate cancer.
Keywords: ERG (ETS-related gene); ETS (erythroblast transformation-specific) gene fusions; Next-generation sequencing; Prostate cancer; TMPRSS2 (transmembrane protease serine 2 gene).