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.
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.
Authors: Amanda Khoo; Lydia Y Liu; Julius O Nyalwidhe; O John Semmes; Danny Vesprini; Michelle R Downes; Paul C Boutros; Stanley K Liu; Thomas Kislinger Journal: Nat Rev Urol Date: 2021-08-27 Impact factor: 14.432
Authors: Miriam Campistol; Juan Morote; Marina Triquell; Lucas Regis; Ana Celma; Inés de Torres; María E Semidey; Richard Mast; Anna Santamaría; Jacques Planas; Enrique Trilla Journal: Cancers (Basel) Date: 2022-05-30 Impact factor: 6.575
Authors: Annalisa Macagno; Alcibiade Athanasiou; Anja Wittig; Ramy Huber; Stephan Weber; Thomas Keller; Martin Rhiel; Bruno Golding; Ralph Schiess Journal: PLoS One Date: 2020-05-18 Impact factor: 3.240
Authors: Helmut Klocker; Bruno Golding; Stephan Weber; Eberhard Steiner; Pierre Tennstedt; Thomas Keller; Ralph Schiess; Silke Gillessen; Wolfgang Horninger; Thomas Steuber Journal: BJUI Compass Date: 2020-03-12
Authors: Juan Morote; Miriam Campistol; Anna Celma; Lucas Regis; Inés de Torres; María E Semidey; Sarai Roche; Richard Mast; Anna Santamaría; Jacques Planas; Enrique Trilla Journal: World J Mens Health Date: 2021-12-27 Impact factor: 5.400