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.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2021
Historique:
received: 28 05 2021
accepted: 12 10 2021
entrez: 12 11 2021
pubmed: 13 11 2021
medline: 31 12 2021
Statut: epublish

Résumé

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.

Identifiants

pubmed: 34767586
doi: 10.1371/journal.pone.0259093
pii: PONE-D-21-17494
pmc: PMC8589165
doi:

Substances chimiques

Antigens, Neoplasm 0
Biomarkers, Tumor 0
LGALS3BP protein, human 0
Prostate-Specific Antigen EC 3.4.21.77

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0259093

Déclaration de conflit d'intérêts

The authors have read the journal’s policy and the authors of this manuscript have the following competing interests: AA, AW, RH, OS, and RS are paid employees of Proteomedix AG. TS is a scientific advisor to Proteomedix. RS has founder shares of Proteomedix. AA, AW, RH, and RS are named as inventors on a patent application for the biomarkers described in this publication (CH 00752/21). This does not alter our adherence to PLOS ONE policies on sharing data and materials.

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Auteurs

Alcibiade Athanasiou (A)

Proteomedix AG, Zurich-Schlieren, Switzerland.

Pierre Tennstedt (P)

Martini-Klinik, University Hospital Hamburg-Eppendorf, Hamburg, Germany.

Anja Wittig (A)

Proteomedix AG, Zurich-Schlieren, Switzerland.

Ramy Huber (R)

Proteomedix AG, Zurich-Schlieren, Switzerland.

Oliver Straub (O)

Proteomedix AG, Zurich-Schlieren, Switzerland.

Ralph Schiess (R)

Proteomedix AG, Zurich-Schlieren, Switzerland.

Thomas Steuber (T)

Martini-Klinik, University Hospital Hamburg-Eppendorf, Hamburg, Germany.

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Classifications MeSH