Prior studies have noted the importance of gene signatures in the prognosis of PCa. Jin et al demonstrated that an NF-kB-activated recurrence predictor 21 gene signature could predict disease-specific survival and distant metastasis-free survival in patients with PCa, although the study used molecular biological methods. Recently, another study identified a 24-gene signature that was significantly associated with the development of metastasis and prostate cancer-specific mortality after radical prostatectomy. However, the importance of gene signatures in predicting LNI in PCa is not fully understood. In the present study, the predictive accuracy of the 7 genes to distinguish tissues with LNI and those without LNI was measured by ROC curve analysis. In the Cox analysis, gene signature-based risk scores were also the single most powerful predictor of LNI. The 7-gene signature could be of particular use in situations when predictions of the occurrence of LNI are ambiguous or borderline. Additionally, the 7-gene signature in our analysis could promote the initiation of additional therapies to treat LNI and allow for personalized treatment for patients.
The authors would like to acknowledge the help provided by Zebin Zhu (The First Affiliated Hospital, University of Science and Technology of China), Jianming Zeng (CEO of biotrainee.com), and Qiannan Yang (his wife of HMC).
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