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Clinical utility of a serum biomarker panel in distinguishing prostate cancer from benign prostate hyperplasia.

ABSTRACT: Prostate-specific antigen (PSA) screening for prostate cancer (PCa) is limited by the lack of specificity but is further complicated in the benign prostatic hyperplasia (BPH) population which also exhibit elevated PSA, representing a clear unmet need to distinguish BPH from PCa. Herein, we evaluated the utility of FLNA IP-MRM, age, and prostate volume to stratify men with BPH from those with PCa. Diagnostic performance of the biomarker panel was better than PSA alone in discriminating patients with negative biopsy from those with PCa, as well as those who have had multiple prior biopsies (AUC 0.75 and 0.87 compared to AUC of PSA alone 0.55 and 0.57 for patients who have had single compared to multiple negative biopsies, respectively). Of interest, in patients with PCa, the panel demonstrated improved performance than PSA alone in those with Gleason scores of 5-7 (AUC 0.76 vs. 0.56) and Gleason scores of 8-10 (AUC 0.74 vs. 0.47). With Gleason scores (8-10), the negative predictive value of the panel is 0.97, indicating potential to limit false negatives in aggressive cancers. Together, these data demonstrate the ability of the biomarker panel to perform better than PSA alone in men with BPH, thus preventing unnecessary biopsies.

SUBMITTER: Kiebish MA

PROVIDER: S-EPMC8302659 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Clinical utility of a serum biomarker panel in distinguishing prostate cancer from benign prostate hyperplasia.

Kiebish Michael A MA Tekumalla Poornima P Ravipaty Shobha S Dobi Albert A Srivastava Shiv S Wu Wenfang W Patil Saurabh S Friss Tracey T Klotz Allison A Srinivasan Alagarsamy A Cullen Jennifer J Rosner Inger L IL Ali Amina A Laszlo Sandra S Petrovic Michele M Fleshner Neil N Garren Jeonifer J Miller Greg G Mahaveer Chand Nischal N Rodrigues Leonardo O LO Granger Elder E Kellogg Mark D MD Luan Shen S Diamandis Eleftherios E Akmaev Viatcheslav R VR Sarangarajan Rangaprasad R Bountra Chas C Freedland Stephen J SJ McLeod David G DG Narain Niven R NR

Scientific reports 20210723 1

Prostate-specific antigen (PSA) screening for prostate cancer (PCa) is limited by the lack of specificity but is further complicated in the benign prostatic hyperplasia (BPH) population which also exhibit elevated PSA, representing a clear unmet need to distinguish BPH from PCa. Herein, we evaluated the utility of FLNA IP-MRM, age, and prostate volume to stratify men with BPH from those with PCa. Diagnostic performance of the biomarker panel was better than PSA alone in discriminating patients w ...[more]

PMID: 34302010

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Project description:BackgroundProstate Cancer (PCa) represents the second leading cause of cancer-related death in men. Prostate-specific antigen (PSA) serum testing, currently used for PCa screening, lacks the necessary sensitivity and specificity. New non-invasive diagnostic tools able to discriminate tumoral from benign conditions and aggressive (AG-PCa) from indolent forms of PCa (NAG-PCa) are required to avoid unnecessary biopsies.MethodsIn this work, 32 formerly N-glycosylated peptides were quantified by PRM (parallel reaction monitoring) in 163 serum samples (79 from PCa patients and 84 from individuals affected by benign prostatic hyperplasia (BPH)) in two technical replicates. These potential biomarker candidates were prioritized through a multi-stage biomarker discovery pipeline articulated in: discovery, LC-PRM assay development and verification phases. Because of the well-established involvement of glycoproteins in cancer development and progression, the proteomic analysis was focused on glycoproteins enriched by TiO2 (titanium dioxide) strategy.ResultsMachine learning algorithms have been applied to the combined matrix comprising proteomic and clinical variables, resulting in a predictive model based on six proteomic variables (RNASE1, LAMP2, LUM, MASP1, NCAM1, GPLD1) and five clinical variables (prostate dimension, proPSA, free-PSA, total-PSA, free/total-PSA) able to distinguish PCa from BPH with an area under the Receiver Operating Characteristic (ROC) curve of 0.93. This model outperformed PSA alone which, on the same sample set, was able to discriminate PCa from BPH with an AUC of 0.79. To improve the clinical managing of PCa patients, an explorative small-scale analysis (79 samples) aimed at distinguishing AG-PCa from NAG-PCa was conducted. A predictor of PCa aggressiveness based on the combination of 7 proteomic variables (FCN3, LGALS3BP, AZU1, C6, LAMB1, CHL1, POSTN) and proPSA was developed (AUC of 0.69).ConclusionsTo address the impelling need of more sensitive and specific serum diagnostic tests, a predictive model combining proteomic and clinical variables was developed. A preliminary evaluation to build a new tool able to discriminate aggressive presentations of PCa from tumors with benign behavior was exploited. This predictor displayed moderate performances, but no conclusions can be drawn due to the limited number of the sample cohort. Data are available via ProteomeXchange with identifier PXD035935.

Project description:BackgroundThe association between benign prostatic hyperplasia (BPH) and prostate cancer (PCa) remains controversial, largely due to a detection bias in traditional observational studies.ObjectiveTo assess the association between BPH and PCa using inherited single nucleotide polymorphisms (SNPs).Design setting and participantsThe participants were White men from the population-based UK Biobank (UKB).Outcome measurements and statistical analysisThe association between BPH and PCa was tested for (1) phenotypic correlation using chi-square, (2) genetic correlation (r g) based on genome-wide SNPs using linkage disequilibrium score regression, and (3) cross-disease genetic associations based on known risk-associated SNPs (15 for BPH and 239 for PCa), individually and cumulatively using genetic risk score (GRS).Results and limitationsAmong 214 717 White men in the UKB, 24 623 (11%) and 14 311 (6.7%) had a diagnosis of BPH and PCa, respectively. Diagnoses of these two diseases were significantly correlated (χ2 = 1862.80, p < 0.001). A significant genetic correlation was found (r g = 0.16; 95% confidence interval 0.03-0.28, p = 0.01). In addition, significant cross-disease genetic associations for established risk-associated SNPs were also found. Among the 250 established genome-wide association study-significant SNPs of PCa or BPH, 49 were significantly associated with the risk of the other disease at p < 0.05, significantly more than expected by chance (N = 12, p < 0.001; χ2 test). Furthermore, significant cross-disease GRS associations were also found; GRSBPH was significantly associated with PCa risk (odds ratio [OR] = 1.26 [1.18-1.36], p < 0.001), and GRSPCa was significantly associated with BPH risk (OR = 1.03 [1.02-1.04], p < 0.001). Moreover, GRSBPH was significantly and inversely associated with lethal PCa risk in a PCa case-case analysis (OR = 0.58 [0.41-0.81], p = 0.002). Only White men were studied.ConclusionsBPH and PCa share common inherited genetics, which suggests that the phenotypic association of these two diseases in observational studies is not entirely caused by the detection bias.Patient summaryFor the first time, we found that benign prostatic hyperplasia and prostate cancer are genetically related. This finding may have implications in disease etiology and risk stratification.

Dataset Information

Clinical utility of a serum biomarker panel in distinguishing prostate cancer from benign prostate hyperplasia.

Publications

Clinical utility of a serum biomarker panel in distinguishing prostate cancer from benign prostate hyperplasia.

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