Prostate cancer biomarkers: a practical review based on different clinical scenarios

References

• Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424.
   PubMed Web of Science ®Google Scholar
• Kasivisvanathan V, Rannikko AS, Borghi M, et al. MRI-Targeted or standard biopsy for Prostate-Cancer diagnosis. N Engl J Med. 2018;378(19):1767–1777.
   PubMed Web of Science ®Google Scholar
• Rouvière O, Puech P, Renard-Penna R, et al. Use of prostate systematic and targeted biopsy on the basis of multiparametric MRI in biopsy-naive patients (MRI-FIRST): a prospective, multicentre, paired diagnostic study. Lancet Oncol. 2019;20(1):100–109.
   PubMed Web of Science ®Google Scholar
• Martini A, Cumarasamy S, Gupta A, et al. Clinical implications of prostatic capsular abutment or bulging on multiparametric magnetic resonance imaging. Minerva Urol Nefrol. 2019;71(5):502–507.
   PubMed Web of Science ®Google Scholar
• Cumarasamy S, Martini A, Falagario UG, et al. Development of a model to predict prostate cancer at the apex (PCAP model) in patients undergoing robot-assisted radical prostatectomy. World J Urol. 2020;38(4):813–819.
   PubMed Web of Science ®Google Scholar
• Gradishar WJ, Anderson BO, Balassanian R, et al. NCCN guidelines insights: breast cancer, version 1.2017. J Natl Compr Canc Netw. 2017;15(4):433–451.
   PubMed Web of Science ®Google Scholar
• Kumar SK, Callander NS, Alsina M, et al. Multiple myeloma, version 3.2017, NCCN clinical practice guidelines in oncology. J Natl Compr Canc Netw. 2017;15(2):230–269.
   PubMed Web of Science ®Google Scholar
• Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Making. 2006;26(6):565–574.
   PubMed Web of Science ®Google Scholar
• Cucchiara V, Cooperberg MR, Dall'Era M, et al. Genomic markers in prostate cancer decision making. Eur Urol. 2018;73(4):572–582.
   PubMed Web of Science ®Google Scholar
• Mottet N, van den Bergh RCN, Briers E, et al. EAU – ESTRO – ESUR – SIOG guidelines on prostate cancer 2020. European Association of Urology Guidelines. 2020 Edition. Vol. presented at the EAU Annual Congress Amsterdam 2020. Arnhem (The Netherlands): European Association of Urology Guidelines Office; 2020.
   Google Scholar
• NCCN. Prostate Cancer (Version 4.2019). 2019. [cited 2019 Nov 1]. Available from: https://www.nccn.org/professionals/physician_gls/pdf/prostate_blocks.pdf.
   Google Scholar
• Sanda MG, Cadeddu JA, Kirkby E, et al. Clinically localized prostate cancer: AUA/ASTRO/SUO guideline. Part I: risk stratification, shared decision making, and care options. J Urol. 2018;199(3):683–690.
   PubMed Web of Science ®Google Scholar
• Loeb S, Vellekoop A, Ahmed HU, et al. Systematic review of complications of prostate biopsy. Eur Urol. 2013;64(6):876–892.
   PubMed Web of Science ®Google Scholar
• Avgeris M, Mavridis K, Scorilas A. Kallikrein-related peptidases in prostate, breast, and ovarian cancers: from pathobiology to clinical relevance. Biol Chem. 2012;393(5):301–317.
   PubMed Web of Science ®Google Scholar
• Lilja H, Ulmert D, Vickers AJ. Prostate-specific antigen and prostate cancer: prediction, detection and monitoring. Nat Rev Cancer. 2008;8(4):268–278.
   PubMed Web of Science ®Google Scholar
• Catalona WJ, Partin AW, Slawin KM, et al. Use of the percentage of free prostate-specific antigen to enhance differentiation of prostate cancer from benign prostatic disease: a prospective multicenter clinical trial. JAMA. 1998;279(19):1542–1547.
   PubMed Web of Science ®Google Scholar
• Bruno SM, Falagario UG, d'Altilia N, et al. PSA density help to identify patients with elevated PSA due to prostate cancer rather than intraprostatic inflammation: a prospective single center study. Front Oncol. 2021;11:693684.
   PubMed Web of Science ®Google Scholar
• Cormio L, Lucarelli G, Selvaggio O, et al. Absence of bladder outlet obstruction is an independent risk factor for prostate cancer in men undergoing prostate biopsy. Medicine. 2016;95(7):e2551.
   PubMed Web of Science ®Google Scholar
• Cicione A, Cormio L, Cantiello F, et al. Presence and severity of lower urinary tract symptoms are inversely correlated with the risk of prostate cancer on prostate biopsy. Minerva Urol Nefrol. 2017;69(5):486–492.
   PubMed Web of Science ®Google Scholar
• Cormio L, Lucarelli G, Netti GS, et al. Post-void residual urinary volume is an independent predictor of biopsy results in men at risk for prostate cancer. Anticancer Res. 2015;35(4):2175–2182.
   PubMed Web of Science ®Google Scholar
• Cormio L, Cindolo L, Troiano F, et al. Development and internal validation of novel nomograms based on benign prostatic obstruction-related parameters to predict the risk of prostate cancer at first prostate biopsy. Front Oncol. 2018;8:438.
   PubMed Web of Science ®Google Scholar
• Bazinet M, Meshref AW, Trudel C, et al. Prospective evaluation of prostate-specific antigen density and systematic biopsies for early detection of prostatic carcinoma. Urology. 1994;43(1):44–51; discussion 51.
   PubMed Web of Science ®Google Scholar
• Nordstrom T, Akre O, Aly M, et al. Prostate-specific antigen (PSA) density in the diagnostic algorithm of prostate cancer. Prostate Cancer Prostatic Dis. 2018;21(1):57–63.
   PubMed Web of Science ®Google Scholar
• Falagario UG, Jambor I, Lantz A, et al. Combined use of prostate-specific antigen density and magnetic resonance imaging for prostate biopsy decision planning: a retrospective multi-institutional study using the prostate magnetic resonance imaging outcome database (PROMOD). Eur Urol Oncol. 2021;4(6):971–979.
   PubMedGoogle Scholar
• Jambor I, Falagario U, Ratnani P, et al. Prediction of biochemical recurrence in prostate cancer patients who underwent prostatectomy using routine clinical prostate multiparametric MRI and decipher genomic score. J Magn Reson Imaging. 2020;51(4):1075–1085.
   PubMed Web of Science ®Google Scholar
• Lantz A, Falagario UG, Ratnani P, et al. Expanding active surveillance inclusion criteria: a novel nomogram including preoperative clinical parameters and magnetic resonance imaging findings. Eur Urol Oncol. 2020;S2588-9311(20)30125-5. DOI:https://doi.org/10.1016/j.euo.2020.08.001.
   Google Scholar
• Ramirez ML, Nelson EC, Devere White RW, et al. Current applications for prostate-specific antigen doubling time. Eur Urol. 2008;54(2):291–300.
   PubMed Web of Science ®Google Scholar
• McDunn JE, Stirdivant SM, Ford LA, et al. Metabolomics and its application to the development of clinical laboratory tests for prostate cancer. EJIFCC. 2015;26(2):92–104.
   PubMedGoogle Scholar
• Parekh DJ, Punnen S, Sjoberg DD, et al. A multi-institutional prospective trial in the USA confirms that the 4Kscore accurately identifies men with high-grade prostate cancer. Eur Urol. 2015;68(3):464–470.
   PubMed Web of Science ®Google Scholar
• Vickers AJ, Cronin AM, Aus G, et al. A panel of kallikrein markers can reduce unnecessary biopsy for prostate cancer: data from the European randomized study of prostate cancer screening in Göteborg, Sweden. BMC Med. 2008;6:19.
   PubMed Web of Science ®Google Scholar
• Vickers A, Cronin A, Roobol M, et al. Reducing unnecessary biopsy during prostate cancer screening using a four-kallikrein panel: an independent replication. J Clin Oncol. 2010;28(15):2493–2498.
   PubMed Web of Science ®Google Scholar
• Carlsson S, Maschino A, Schroder F, et al. Predictive value of four kallikrein markers for pathologically insignificant compared with aggressive prostate cancer in radical prostatectomy specimens: results from the European randomized study of screening for prostate cancer section Rotterdam. Eur Urol. 2013;64(5):693–699.
   PubMed Web of Science ®Google Scholar
• Falagario UG, Martini A, Wajswol E, et al. Avoiding unnecessary magnetic resonance imaging (MRI) and biopsies: negative and positive predictive value of MRI according to prostate-specific antigen density, 4Kscore and risk calculators. European Urology Oncology. 2020;3(5):700–704.
   PubMed Web of Science ®Google Scholar
• Falagario UG, Lantz A, Jambor I, et al. Using biomarkers in patients with positive multiparametric magnetic resonance imaging: 4Kscore predicts the presence of cancer outside the index lesion. Int J Urol. 2021;28(1):47–52.
   Web of Science ®Google Scholar
• de la Calle C, Patil D, Wei JT, et al. Multicenter evaluation of the prostate health index to detect aggressive prostate cancer in biopsy naive men. J Urol. 2015;194(1):65–72.
   PubMed Web of Science ®Google Scholar
• Loeb S, Catalona WJ. The prostate health index: a new test for the detection of prostate cancer. Ther Adv Urol. 2014;6(2):74–77.
   PubMedGoogle Scholar
• Bryant RJ, Sjoberg DD, Vickers AJ, et al. Predicting high-grade cancer at ten-core prostate biopsy using four kallikrein markers measured in blood in the ProtecT study. J Natl Cancer Inst. 2015;107(7):djv095.
   PubMedGoogle Scholar
• de Kok JB, Verhaegh GW, Roelofs RW, et al. DD3(PCA3), a very sensitive and specific marker to detect prostate tumors. Cancer Res. 2002;62(9):2695–2698.
   PubMed Web of Science ®Google Scholar
• Salami SS, Schmidt F, Laxman B, et al. Combining urinary detection of TMPRSS2:ERG and PCA3 with serum PSA to predict diagnosis of prostate cancer. Urol Oncol. 2013;31(5):566–571.
   PubMed Web of Science ®Google Scholar
• Leyten GH, Hessels D, Jannink SA, et al. Prospective multicentre evaluation of PCA3 and TMPRSS2-ERG gene fusions as diagnostic and prognostic urinary biomarkers for prostate cancer. Eur Urol. 2014;65(3):534–542.
   PubMed Web of Science ®Google Scholar
• Sanguedolce F, Cormio A, Brunelli M, et al. Urine TMPRSS2: ERG fusion transcript as a biomarker for prostate cancer: literature review. Clin Genitourin Cancer. 2016;14(2):117–121.
   PubMed Web of Science ®Google Scholar
• Tomlins SA, Day JR, Lonigro RJ, et al. Urine TMPRSS2:ERG plus PCA3 for individualized prostate cancer risk assessment. Eur Urol. 2016;70(1):45–53. Jul
   PubMed Web of Science ®Google Scholar
• Leyten GH, Hessels D, Smit FP, et al. Identification of a candidate gene panel for the early diagnosis of prostate cancer. Clin Cancer Res. 2015;21(13):3061–3070.
   PubMed Web of Science ®Google Scholar
• Van Neste L, Hendriks RJ, Dijkstra S, et al. Detection of high-grade prostate cancer using a urinary molecular Biomarker-Based risk score. Eur Urol. 2016;70(5):740–748.
   PubMed Web of Science ®Google Scholar
• Busetto GM, Del Giudice F, Maggi M, et al. Prospective assessment of two-gene urinary test with multiparametric magnetic resonance imaging of the prostate for men undergoing primary prostate biopsy. World J Urol. 2021;39(6):1869–1877.
   PubMed Web of Science ®Google Scholar
• Maggi M, Del Giudice F, Falagario UG, et al. SelectMDx and multiparametric magnetic resonance imaging of the prostate for men undergoing primary prostate biopsy: a prospective assessment in a Multi-Institutional study. Cancers. 2021;13(9):2047.
   PubMed Web of Science ®Google Scholar
• McKiernan J, Donovan MJ, O'Neill V, et al. A novel urine exosome gene expression assay to predict high-grade prostate cancer at initial biopsy. JAMA Oncol. 2016;2(7):882–889.
   PubMed Web of Science ®Google Scholar
• McKiernan J, Donovan MJ, Margolis E, et al. A prospective adaptive utility trial to validate performance of a novel urine exosome gene expression assay to predict high-grade prostate cancer in patients with prostate-specific antigen 2-10ng/ml at initial biopsy. Eur Urol. 2018;74(6):731–738.
   PubMed Web of Science ®Google Scholar
• Lepore S, Milillo L, Trotta T, et al. Adhesion and growth of osteoblast-like cells on laser-engineered porous titanium surface: expression and localization of N-cadherin and beta-catenin. J Biol Regul Homeost Agents. 2013;27(2):531–541.
   PubMed Web of Science ®Google Scholar
• Sreekumar A, Poisson LM, Rajendiran TM, et al. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature. 2009;457(7231):910–914.
   PubMed Web of Science ®Google Scholar
• Wojno KJ, Costa FJ, Cornell RJ, et al. Reduced rate of repeated prostate biopsies observed in ConfirmMDx clinical utility field study. Am Health Drug Benefits. 2014;7(3):129–134.
   PubMedGoogle Scholar
• Partin AW, Van Neste L, Klein EA, et al. Clinical validation of an epigenetic assay to predict negative histopathological results in repeat prostate biopsies. J Urol. 2014;192(4):1081–1087.
   PubMed Web of Science ®Google Scholar
• Stewart GD, Van Neste L, Delvenne P, et al. Clinical utility of an epigenetic assay to detect occult prostate cancer in histopathologically negative biopsies: results of the MATLOC study. J Urol. 2013;189(3):1110–1116.
   PubMed Web of Science ®Google Scholar
• Parr RL, Mills J, Harbottle A, et al. Mitochondria, prostate cancer, and biopsy sampling error. Discov Med. 2013;15(83):213–220.
   PubMed Web of Science ®Google Scholar
• Verschoor ML, Ungard R, Harbottle A, et al. Mitochondria and cancer: past, present, and future. Biomed Res Int. 2013;2013:612369.
   PubMed Web of Science ®Google Scholar
• Robinson K, Creed J, Reguly B, et al. Accurate prediction of repeat prostate biopsy outcomes by a mitochondrial DNA deletion assay. Prostate Cancer Prostatic Dis. 2010;13(2):126–131.
   PubMed Web of Science ®Google Scholar
• Knezevic D, Goddard AD, Natraj N, et al. Analytical validation of the oncotype DX prostate cancer assay - a clinical RT-PCR assay optimized for prostate needle biopsies. BMC Genomics. 2013;14(1):690.
   PubMedGoogle Scholar
• Klein EA, Cooperberg MR, Magi-Galluzzi C, et al. A 17-gene assay to predict prostate cancer aggressiveness in the context of Gleason grade heterogeneity, tumor multifocality, and biopsy undersampling. Eur Urol. 2014;66(3):550–560.
   PubMed Web of Science ®Google Scholar
• Cullen J, Rosner IL, Brand TC, et al. A biopsy-based 17-gene genomic prostate score predicts recurrence after radical prostatectomy and adverse surgical pathology in a racially diverse population of men with clinically low- and intermediate-risk prostate cancer. Eur Urol. 2015;68(1):123–131.
   PubMed Web of Science ®Google Scholar
• Eggener S, Karsh LI, Richardson T, et al. A 17-gene panel for prediction of adverse prostate cancer pathologic features: prospective clinical validation and utility. Urology. 2019;126:76–82.
   PubMed Web of Science ®Google Scholar
• Eggener SE, Rumble RB, Armstrong AJ, et al. Molecular biomarkers in localized prostate cancer: ASCO guideline. J Clin Oncol. 2020;38(13):1474–1494.
   PubMed Web of Science ®Google Scholar
• Cuzick J, Swanson GP, Fisher G, et al. Prognostic value of an RNA expression signature derived from cell cycle proliferation genes in patients with prostate cancer: a retrospective study. Lancet Oncol. 2011;12(3):245–255.
   PubMed Web of Science ®Google Scholar
• Cooperberg MR, Simko JP, Cowan JE, et al. Validation of a cell-cycle progression gene panel to improve risk stratification in a contemporary prostatectomy cohort. J Clin Oncol. 2013;31(11):1428–1434.
   PubMed Web of Science ®Google Scholar
• Shore N, Concepcion R, Saltzstein D, et al. Clinical utility of a biopsy-based cell cycle gene expression assay in localized prostate cancer. Curr Med Res Opin. 2014;30(4):547–553.
   PubMed Web of Science ®Google Scholar
• Cuzick J, Berney DM, Fisher G, et al. Prognostic value of a cell cycle progression signature for prostate cancer death in a conservatively managed needle biopsy cohort. Br J Cancer. 2012;106(6):1095–1099.
   PubMed Web of Science ®Google Scholar
• Shipitsin M, Small C, Choudhury S, et al. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error. Br J Cancer. 2014;111(6):1201–1212.
   PubMed Web of Science ®Google Scholar
• Dietrich D, Hasinger O, Banez LL, et al. Development and clinical validation of a real-time PCR assay for PITX2 DNA methylation to predict prostate-specific antigen recurrence in prostate cancer patients following radical prostatectomy. J Mol Diagn. 2013;15(2):270–279.
   PubMed Web of Science ®Google Scholar
• Blume-Jensen P, Berman DM, Rimm DL, et al. Development and clinical validation of an in situ biopsy-based multimarker assay for risk stratification in prostate cancer. Clin Cancer Res. 2015;21(11):2591–2600.
   PubMed Web of Science ®Google Scholar
• Pound CR, Partin AW, Eisenberger MA, et al. Natural history of progression after PSA elevation following radical prostatectomy. JAMA. 1999;281(17):1591–1597.
   PubMed Web of Science ®Google Scholar
• Erho N, Crisan A, Vergara IA, et al. Discovery and validation of a prostate cancer genomic classifier that predicts early metastasis following radical prostatectomy. PLoS One. 2013;8(6):e66855.
   PubMed Web of Science ®Google Scholar
• Spratt DE, Yousefi K, Deheshi S, et al. Individual patient-level meta-analysis of the performance of the decipher genomic classifier in high-risk men after prostatectomy to predict development of metastatic disease. J Clin Oncol. 2017;35(18):1991–1998.
   PubMed Web of Science ®Google Scholar
• Ross AE, Johnson MH, Yousefi K, et al. Tissue-based genomics augments post-prostatectomy risk stratification in a natural history cohort of intermediate- and High-Risk men. Eur Urol. 2016;69(1):157–165.
   PubMed Web of Science ®Google Scholar
• Gore JL, Du Plessis M, Santiago-Jimenez M, et al. Decipher test impacts decision making among patients considering adjuvant and salvage treatment after radical prostatectomy: interim results from the multicenter prospective PRO-IMPACT study. Cancer. 2017;123(15):2850–2859.
   PubMed Web of Science ®Google Scholar
• Dalela D, Santiago-Jimenez M, Yousefi K, et al. Genomic classifier augments the role of pathological features in identifying optimal candidates for adjuvant radiation therapy in patients with prostate cancer: development and internal validation of a multivariable prognostic model. J Clin Oncol. 2017;35(18):1982–1990.
   PubMed Web of Science ®Google Scholar
• Falagario UG, Beksac AT, Martini A, et al. Defining prostate cancer at favorable intermediate risk: the potential utility of magnetic resonance imaging and genomic tests. J Urol. 2019;202(1):102–107.
   PubMed Web of Science ®Google Scholar
• Beksac AT, Cumarasamy S, Falagario U, et al. Multiparametric magnetic resonance imaging features identify aggressive prostate cancer at the phenotypic and transcriptomic level. J Urol. 2018;200(6):1241–1249.
   PubMed Web of Science ®Google Scholar
• Silecchia G, Falagario U, Sanguedolce F, et al. Multiparametric magnetic resonance imaging/transrectal ultrasound fusion-guided prostate biopsy: a comparison with systematic transrectal ultrasound-guided prostate biopsy. J Gerontol Geriatr. 2018;2018(4):200–204.
   Google Scholar
• Beksac AT, Sobotka S, Xu P, et al. Downgrading of grade group after radical prostatectomy: comparison of multiparametric magnetic resonance imaging guided fusion biopsy and standard 12-core biopsy. Urology. 2019;127:80–85.
   PubMed Web of Science ®Google Scholar
• Stallone G, Cormio L, Netti GS, et al. Pentraxin 3: a novel biomarker for predicting progression from prostatic inflammation to prostate cancer. Cancer Res. 2014;74(16):4230–4238.
   PubMed Web of Science ®Google Scholar
• Falagario UG, Busetto GM, Netti GS, et al. Prospective validation of pentraxin-3 as a novel serum biomarker to predict the risk of prostate cancer in patients scheduled for prostate biopsy. Cancers. 2021;13(7):1611.
   PubMed Web of Science ®Google Scholar
• Strom P, Nordstrom T, Aly M, et al. The Stockholm-3 model for prostate cancer detection: algorithm update, biomarker contribution, and reflex test potential. Eur Urol. 2018;74(2):204–210.
   PubMed Web of Science ®Google Scholar
• Moller A, Olsson H, Gronberg H, et al. The Stockholm3 blood-test predicts clinically-significant cancer on biopsy: independent validation in a multi-center community cohort. Prostate Cancer Prostatic Dis. 2019;22(1):137–142.
   PubMed Web of Science ®Google Scholar
• Conese M, Castellani S, Lepore S, et al. Evaluation of genome-wide expression profiles of blood and sputum neutrophils in cystic fibrosis patients before and after antibiotic therapy. PLoS One. 2014;9(8):e104080.
   PubMed Web of Science ®Google Scholar
• Salami SS, Singhal U, Spratt DE, et al. Circulating tumor cells as a predictor of treatment response in clinically localized prostate cancer. J Clin Oncol Precis Oncol. 2019;3(3):1–9.
   Google Scholar
• Tătaru OS, Vartolomei MD, Rassweiler JJ, et al. Artificial intelligence and machine learning in prostate cancer patient management-current trends and future perspectives. Diagnostics. 2021;11(2):354.
   Web of Science ®Google Scholar