Saliva Biomarker Panel for Accurate Prostate Cancer Detection
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Solution Overview
Problem
Current diagnostic methods for prostate cancer, such as PSA testing, have low sensitivity and specificity, leading to unnecessary biopsies or underdiagnosis, and there is a lack of molecular-based biomarkers for predicting disease status and therapeutic sensitivity.
Innovation Solution
A method involving the determination and normalization of expression levels of 24 biomarkers (AAMP, CHTOP, EDC4, FYCO1, HNRNPU, HPN, KRT23, MAN2B2, MAX, MRPS25, NDUFS2, PPRC1, RAD23A, REPIN1, SDR39U1, SETBP1, SLC18A2, SMC4, SPARC, SQLE, STRIP1, STX12, UNC45A, XPC) in saliva, followed by an algorithmic analysis to generate a score for diagnosing prostate cancer and assessing disease progression and therapy response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If PSA testing is used for prostate cancer detection, then the diagnostic process can be simplified, but sensitivity and specificity are low leading to unnecessary biopsies or underdiagnosis
Solution Approach 1:
The patent divides the diagnostic approach into two parts: continuing to use PSA testing for its simplicity and ease of operation, while adding a separate molecular biomarker panel (including genes like AR-V7, ERG, and other cancer-specific markers) to improve diagnostic accuracy. This segmentation allows the system to maintain operational simplicity through PSA while enhancing reliability through molecular analysis, resolving the contradiction between ease of operation and diagnostic accuracy.
Solution Approach 2:
The patent creates a composite diagnostic system that combines PSA testing with a panel of molecular biomarkers (including androgen receptor variants, ETS family fusions, and other cancer-specific genes). This composite approach integrates the simplicity of PSA with the high accuracy of molecular markers, achieving both ease of operation and high reliability by synthesizing multiple diagnostic components into a unified system.
2Adaptability or versatility
If molecular genetic information is used to subtype cancers and predict therapy sensitivity, then treatment personalization improves, but current molecular biomarkers are insufficient for predicting therapeutic response
Solution Approach 1:
The patent segments the molecular biomarker analysis into distinct functional categories: androgen receptor variants (AR-V7), ETS family fusions (ERG), and other cancer-specific markers. This segmentation allows comprehensive coverage of different molecular mechanisms while maintaining the ability to personalize treatment based on specific biomarker profiles, addressing the insufficiency of current single-biomarker approaches.
Solution Approach 2:
The patent develops a universal molecular biomarker panel that can simultaneously detect multiple types of prostate cancer molecular features (receptor variants, gene fusions, copy number alterations) and use this information for both cancer subtyping and therapy sensitivity prediction. This multi-functional approach eliminates the loss of information by integrating diverse molecular data into a unified diagnostic framework that supports personalized treatment decisions.
3Reliability
If surveillance through PSA and imaging is used to monitor PCa, then early detection of metastatic disease is possible, but the current biomarker PSA is not unique and may detect prostatitis or BPH
Solution Approach 1:
The patent segments the monitoring approach by separating PSA-based surveillance (which has low specificity) from molecular biomarker monitoring (which provides high specificity). The molecular panel includes prostate cancer-specific markers that do not cross-react with benign conditions like prostatitis or BPH, thereby eliminating false positives while maintaining the ability to detect disease progression and metastasis.
Solution Approach 2:
The patent introduces molecular biomarkers as an intermediary between PSA testing and definitive cancer diagnosis. These molecular markers serve as a mediator that filters out false positives from PSA testing by providing specific confirmation of cancer presence, thereby improving monitoring accuracy without propagating the harmful false positive detections inherent in PSA alone.
Data Source
AI summary
The present disclosure is directed to methods for detecting a prostrate cancer, methods for determining whether a prostrate cancer is stable or progressive, low or high Gleason grade, methods for determining the completeness of surgery, and methods for evaluating the response to a prostrate cancer therapy.