A novel 8-gene panel for prediction of early biochemical recurrence in patients with prostate cancer after radical prostatectomy

Approximately 25% of prostate cancer (PCa) cases experience biochemical recurrence (BCR) following radical prostatectomy (RP). The patients with BCR, especially with BCR <= 2 year after RP (early BCR), are more likely to develop clinical metastasis and castration resistance. Now decision-making regarding BCR after RP relies solely on clinical parameters. We thus attempted to establish an early BCR-risk prediction model by combining a molecular signature with clinicopathological features for guiding clinical decision-making. In this study, an 8-gene signature was derived, and these eight genes were SPTBN2, LGI3, TGM3, LENG9, HAS3, SLC25A27, PCDHGA1, and ADPRHL1. The Kaplan-Meier analysis revealed a significantly prolonged BCR-free survival in the patients with low -risk scores compared to those with high-risk scores in both training and validation datasets. Harrell's concordance index and time-dependent receiver operating characteristic analysis demonstrated that this gene signature tended to outperform three commercial panels at early BCR prediction. Moreover, this signature was also proven as an independent predictor of BCR-free survival. A nomogram, incorporating the gene signature and clinicopathologic features, was constructed and excellently predicted 1-, 2-and 3-year BCR-free survival of localized PCa patients after RP. Gene set enrichment analysis, tumor immunity, and mRNA expression profiling analysis showed that the high-risk group was more prone to the immunosuppressive microenvironment and impaired DNA damage response than the low-risk group. Collectively, we successfully developed a novel 8-gene signature as a powerful predictor for early BCR after RP and created a prognostic nomogram, which may help inform the clinical management of PCa.

Automated summary

This study developed a model containing 8-gene signature that can predict the risk of early biochemical recurrence in prostate cancer patients after radical prostatectomy. The model outperformed three commercial panels and may assist in clinical management of PCa.