A novel serum biomarker quintet reveals added prognostic value when combined with standard clinical parameters in prostate cancer patients by predicting biochemical recurrence and adverse pathology.

The objective was to determine the prognostic utility of a new biomarker combination in prostate cancer (PCa) patients undergoing Radical Prostatectomy (RP). Serum samples and clinical data of 557 men who underwent RP for PCa with pathological stage (pT) <3 at Martini Clinic (Hamburg, Germany) were used for analysis. Clinical Grade Group and clinical stage was determined using biopsy samples while tumor marker concentrations were measured in serum using immunoassays. The prognostic utility of the proposed marker combination was assessed using Cox proportional hazard regression and Kaplan-Meier analysis. The performance was compared to the Cancer of the Prostate Risk Assessment (CAPRA) score in the overall cohort and in a low-risk patient subset. A multivariable model comprising fibronectin 1, galectin-3-binding protein, lumican, matrix metalloprotease 9, thrombospondin-1 and PSA together with clinical Grade Group (GG) and clinical stage (cT) was created. The proposed model was a significant predictor of biochemical recurrence (BCR) (HR 1.29 per 5 units score, 95%CI 1.20-1.38, p<0.001). The Kaplan-Meier analysis showed that the proposed model had a better prediction for low-risk disease after RP compared to CAPRA (respectively 5.0% vs. 9.1% chance of BCR). In a pre-defined low risk population subset, the risk of BCR using the proposed model was below 5.2% and thus lower when compared to CAPRA = 0-2 (9%), GG<2 (7%) and NCCN = low-risk (6%) subsets. Additionally, the proposed model could significantly (p<0.001) discriminate patients with adverse pathology (AP) events at RP from those without. In conclusion, the proposed model is superior to CAPRA for the prediction of BCR after RP in the overall cohort as well as a in a pre-defined low risk patient population subset. It is also significantly associated with AP at RP.

Analytical performance of thrombospondin-1 and cathepsin D immunoassays part of a novel CE-IVD marked test as an aid in the diagnosis of prostate cancer.

The Prostate Specific Antigen (PSA) test suffers from low specificity for the diagnosis of Prostate Cancer (PCa). We originally discovered two cancer-related proteins thrombospondin-1 (THBS1) and cathepsin D (CTSD) using a mass-spectrometry-based proteomics approach. The two serum proteins were shown to improve the diagnosis of high-grade PCa. Thus, we developed quantitative ELISAs for the determination of their concentration in human serum. Here we report their analytical performance in terms of limit of detection, specificity, precision, linearity and interferences, which were determined based on CLSI guidelines. Further, we investigated the influence of pre-analytical factors on concentration measurements. For this, blood from 4-6 donors was collected in different tubes and stored at room temperature for different times prior to centrifugation at different centrifugal forces and temperatures. Stability of THBS1 and CTSD under different storage temperatures was also evaluated. Our results show that the assays are specific, linear and sensitive enough to allow measurement of clinical samples. Precision in terms of repeatability and total within-laboratory coefficient of variation (CV) are 5.5% and 8.1% for THBS1 and 4.3% and 7.2% for CTSD, respectively. Relative laboratory-to-laboratory differences were -6.3% for THBS1 and -3% for CTSD. Both THBS1 and CTSD were stable in serum samples, with 80-120% recoveries of concentrations across donors, sample preparation and storage. In conclusion, the ELISAs as part of the novel commercial in vitro diagnostic test Proclarix are suitable for the use in clinical practice. THBS1 and CTSD can be accurately measured for their intended use independent of the lot and laboratory when conditions consistent with routine practice for PSA sampling and storage are used.

Thrombospondin 1 and cathepsin D improve prostate cancer diagnosis by avoiding potentially unnecessary prostate biopsies.

OBJECTIVES: To investigate and further validate if two novel cancer-related glycoproteins, discovered by a genetic-guided proteomics approach, can distinguish benign disease from prostate cancer (PCa) in men with enlarged prostates. PATIENTS AND METHODS: A retrospective study was performed that included men with a total prostate-specific antigen (PSA) concentration of 2.0-10 ng/mL, negative digital rectal examination and enlarged prostate (volume ≥35 mL). Serum samples were collected between 2011 and 2016 at a single centre from 474 men before they underwent prostate biopsy. Serum concentrations of thrombospondin 1 (THBS1) and cathepsin D (CTSD) glycoproteins were combined with the percentage of free PSA to total PSA ratio (%fPSA) to predict any or significant cancer at biopsy. RESULTS: The multivariable logistic regression model including THBS1, CTSD and %fPSA discriminated among biopsy-positive and biopsy-negative patients in the validation set with an area under the curve (AUC) of 0.86 (P < 0.001, 95% confidence interval (CI) 0.82-0.91), while %fPSA alone showed an AUC of 0.64 (P < 0.001, 95% CI 0.57-0.71). At 90% sensitivity for PCa, the specificity of the model was 62%, while %fPSA had a specificity of 23%. For high grade (Gleason score ≥ 7 in prostatectomy specimen) PCa, the specificity was 48% at 90% sensitivity, with an AUC of 0.83, (P < 0.001, 95% CI 0.77 to 0.88). Limitations of the study include the retrospective set-up and single-centre cohort. CONCLUSIONS: A model combining two cancer-related glycoproteins (THBS1 and CTSD) and %fPSA can improve PCa diagnosis and may reduce the number of unnecessary prostate biopsies because of its improved specificity for PCa when compared to %fPSA alone.