Identification and Validation of Leucine-rich α-2-glycoprotein 1 as a Noninvasive Biomarker for Improved Precision in Prostate Cancer Risk Stratification.

BACKGROUND: More accurate risk assessments are needed to improve prostate cancer management. OBJECTIVE: To identify blood-based protein biomarkers that provided prognostic information for risk stratification. DESIGN SETTING AND PARTICIPANTS: Mass spectrometry was used to identify biomarker candidates from blood, and validation studies were performed in four independent cohorts retrospectively collected between 1988 and 2015. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary outcome objectives were progression-free survival, prostate cancer-specific survival (PCSS), and overall survival. Statistical analyses to assess survival and model performance were performed. RESULTS AND LIMITATION: Serum leucine-rich α-2-glycoprotein 1 (LRG1) was found to be elevated in fatal prostate cancer. LRG1 provided prognostic information independent of metastasis and increased the accuracy in predicting PCSS, particularly in the first 3 yr. A high LRG1 level is associated with an average of two-fold higher risk of disease-progression and mortality in both high-risk and metastatic patients. However, our study design, with a retrospective analysis of samples spanning several decades back, limits the assessment of the clinical utility of LRG1 in today's clinical practice. Thus, independent prospective studies are needed to establish LRG1 as a clinically useful biomarker for patient management. CONCLUSIONS: High blood levels of LRG1 are unfavourable in newly diagnosed high-risk and metastatic prostate cancer, and LRG1 increased the accuracy of risk stratification of prostate cancer patients. PATIENT SUMMARY: High blood levels of leucine-rich α-2-glycoprotein 1 are unfavourable in newly diagnosed high-risk and metastatic prostate cancer

Role of serum response factor expression in prostate cancer biochemical recurrence

BACKGROUND: Up to a third of prostate cancer patients fail curative treatment strategies such as surgery and radiation therapy in the form of biochemical recurrence (BCR) which can be predictive of poor outcome. Recent clinical trials have shown that men experiencing BCR might benefit from earlier intervention post-radical prostatectomy (RP). Therefore, there is an urgent need to identify earlier prognostic biomarkers which will guide clinicians in making accurate diagnosis and timely decisions on the next appropriate treatment. The objective of this study was to evaluate Serum Response Factor (SRF) protein expression following RP and to investigate its association with BCR.MATERIALS AND METHODS: SRF nuclear expression was evaluated by immunohistochemistry (IHC) in TMAs across three international radical prostatectomy cohorts for a total of 615 patients. Log-rank test and Kaplan-Meier analyses were used for BCR comparisons. Stepwise backwards elimination proportional hazard regression analysis was used to explore the significance of SRF in predicting BCR in the context of other clinical pathological variables. Area under the curve (AUC) values were generated by simulating repeated random sub-samples.RESULTS: Analysis of the immunohistochemical staining of benign versus cancer cores showed higher expression of nuclear SRF protein expression in cancer cores compared with benign for all the three TMAs analysed (P < 0.001, n = 615). Kaplan-Meier curves of the three TMAs combined showed that patients with higher SRF nuclear expression had a shorter time to BCR compared with patients with lower SRF expression (P < 0.001, n = 215). Together with pathological T stage T3, SRF was identified as a predictor of BCR using stepwise backwards elimination proportional hazard regression analysis (P = 0.0521). Moreover ROC curves and AUC values showed that SRF was better than T stage in predicting BCR at year 3 and 5 following radical prostatectomy, the combination of SRF and T stage had a higher AUC value than the two taken separately.CONCLUSIONS: SRF assessment by IHC following RP could be useful in guiding clinicians to better identify patients for appropriate follow-up and timely treatment