Version 1
: Received: 30 September 2024 / Approved: 1 October 2024 / Online: 1 October 2024 (14:32:50 CEST)
How to cite:
Žvirblė, M.; Vaicekauskaitė, I.; Survila, Ž.; Bosas, P.; Dobrovolskienė, N.; Mlynska, A.; Sabaliauskaitė, R.; Pašukonienė, V. Soluble PD-L1 and PD-1 Significantly Improve the Accuracy of a Diagnostic Model of mRNA Transcripts in the Diagnosis of Prostate Cancer. Preprints2024, 2024100035. https://doi.org/10.20944/preprints202410.0035.v1
Žvirblė, M.; Vaicekauskaitė, I.; Survila, Ž.; Bosas, P.; Dobrovolskienė, N.; Mlynska, A.; Sabaliauskaitė, R.; Pašukonienė, V. Soluble PD-L1 and PD-1 Significantly Improve the Accuracy of a Diagnostic Model of mRNA Transcripts in the Diagnosis of Prostate Cancer. Preprints 2024, 2024100035. https://doi.org/10.20944/preprints202410.0035.v1
Žvirblė, M.; Vaicekauskaitė, I.; Survila, Ž.; Bosas, P.; Dobrovolskienė, N.; Mlynska, A.; Sabaliauskaitė, R.; Pašukonienė, V. Soluble PD-L1 and PD-1 Significantly Improve the Accuracy of a Diagnostic Model of mRNA Transcripts in the Diagnosis of Prostate Cancer. Preprints2024, 2024100035. https://doi.org/10.20944/preprints202410.0035.v1
APA Style
Žvirblė, M., Vaicekauskaitė, I., Survila, Ž., Bosas, P., Dobrovolskienė, N., Mlynska, A., Sabaliauskaitė, R., & Pašukonienė, V. (2024). Soluble PD-L1 and PD-1 Significantly Improve the Accuracy of a Diagnostic Model of mRNA Transcripts in the Diagnosis of Prostate Cancer. Preprints. https://doi.org/10.20944/preprints202410.0035.v1
Chicago/Turabian Style
Žvirblė, M., Rasa Sabaliauskaitė and Vita Pašukonienė. 2024 "Soluble PD-L1 and PD-1 Significantly Improve the Accuracy of a Diagnostic Model of mRNA Transcripts in the Diagnosis of Prostate Cancer" Preprints. https://doi.org/10.20944/preprints202410.0035.v1
Abstract
Objectives: To assess the role of soluble PD-L1 and PD-1 in combination with mRNA transcripts of PCA3, PSMA, AR genes in diagnostics of clinically significant prostate cancer (PCa). Methods: For 68 PCa patients, plasma sPD-L1 and sPD-1 were measured by ELISA method and the urinary PSMA, PCA3 and AR were tested using RT-qPCR. Results: PSMA and AR were iden-tified as the most reliable biomarkers for predicting clinically significant prostate cancer, with AUCs of 0.81 and 0.78, respectively. Additionally, the expression levels of PSMA and PCA3 were associated with the pT3 stage. Despite the diagnostic potential of mRNA transcripts alone, the ad-dition of sPD-L1 and sPD-1 significantly enhanced diagnostic accuracy. Combination doubled the specificity of PCA3 from 44.1% to 88.0%, compared to PCA3 alone. sPD-L1, sPD-1 and AR resulted in the best distinction between clinically significant and insignificant prostate cancer, achieving an AUC of 0.97, an accuracy of 0.95, a sensitivity of 100%, a specificity of 95%, revealing the potential of AR in distinguishing clinically significant PCa, more effectively than PSMA and PCA3. Our find-ings highlight the significant potential of sPD-1 in enhancing diagnostic accuracy when added to a triple gene panel, achieving an AUC of 0.90 compared to an AUC of 0.78 without sPD-1. This un-derscores the value of sPD-1, which has been less explored than sPD-L1 in cancer diagnostics. Con-clusions: sPD-L1 and sPD-1 has a potential to significantly enhance the accuracy of PCa diagnostics when added to the diagnostic panel, alongside PSMA, PCA3, and AR mRNA transcripts.
Medicine and Pharmacology, Oncology and Oncogenics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
