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Prostac: A New Composite Score With Potential Predictive Value in Prostate Cancer.

E O Asante-Asamani¹, Gargi Pal², Leslie Liu³

¹Department of Mathematics, Clarkson University, Potsdam, NY, United States.

Frontiers in Oncology

|April 2, 2021

Summary

A new composite score, Prostac, was developed using three prostate cancer (PCa) biomarkers (PVT1 exons 4A, 4B, and 9) to improve PCa diagnosis. This score accurately classified 100% of PCa cells in validation studies.

Keywords:

PVT1 exons biomarkers composite score mathematical oncology prostate cancer support vector machines

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Area of Science:

Oncology
Biomarkers
Diagnostic Tools

Background:

Prostate cancer (PCa) is a leading cancer diagnosis globally.
Current diagnostic methods like PSA assays have limitations, including low specificity and sensitivity.
Unnecessary biopsies lead to complications, highlighting the need for improved diagnostic accuracy.

Purpose of the Study:

To develop a novel composite score, Prostac, for enhanced prostate cancer diagnosis.
To identify and utilize specific Plasmacytoma Variant Translocation 1 (PVT1) biomarkers for PCa detection.

Main Methods:

Developed a composite score (Prostac) using three PVT1 biomarkers (exons 4A, 4B, and 9).
Employed real-time quantitative polymerase chain reaction (qPCR) for copy number analysis.
Utilized a supervised learning algorithm (support vector machines) to create a classification hyperplane.

Main Results:

PVT1 biomarkers were found to be significantly overexpressed in PCa epithelial cells.
The Prostac score demonstrated linear separability for PCa biomarkers.
Cross-validation showed 100% accurate classification of PCa cells.

Conclusions:

The Prostac score shows significant promise for accurate prostate cancer diagnosis.
This novel biomarker composite score could reduce the need for unnecessary biopsies.
Further clinical trials are warranted to validate Prostac in patient populations.