Gene Expression Panel Predicts Prostate Cancer Recurrence
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Solution Overview
Problem
Current tools for predicting prostate cancer progression have limited predictive accuracy, making it challenging to determine which patients are at risk of recurrence after radical prostatectomy, leading to potential overtreatment or undertreatment.
Innovation Solution
A gene expression panel using a collection of signature genes, including NKX2-1, UPK1A, ADRA2C, ABCC11, MMP11, CPVL, ZYG11A, CLEC4F, OAS2, PGC, UPK3B, PCBP3, ABLIM1, EDARADD, GPR81, MYBPC1, F10, KCNA3, GLDC, KCNQ2, RAPGEF1, TUBB2B, MB, DUOXA1, C2orf43, DUOX1, PCA3, and NPR3, to predict clinical and biochemical recurrence by applying expression levels to a predictive model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current clinical tools (Gleason score, PSA level, clinical stage) are used to predict prostate cancer progression, then the prediction process is simple and easy to apply in the clinic, but the predictive accuracy is limited
Solution Approach 1:
The patent changes the parameters used for prediction from traditional clinical variables (Gleason score, PSA level, clinical stage) to molecular-level parameters (gene expression levels, protein levels, or other biomarker levels) that provide more precise information about cancer progression risk, thereby improving predictive accuracy while accepting increased complexity
Solution Approach 2:
The patent introduces molecular biomarkers (genes, proteins, or other molecules) as intermediary indicators that mediate between the clinical presentation and the actual cancer progression risk, providing a more accurate predictive signal than direct clinical observations alone
2Reliability
If radical prostatectomy is performed on all low-risk patients to ensure adequate treatment, then recurrence risk is reduced, but quality of life is negatively impacted by side effects such as incontinence and impotence
Solution Approach 1:
The patent applies local quality by differentiating treatment approaches based on individual patient risk profiles determined by molecular biomarkers, rather than applying uniform treatment to all low-risk patients, thereby tailoring the intensity of treatment to the specific needs of each patient group
Solution Approach 2:
The patent performs preliminary assessment using molecular biomarkers to identify which patients are truly at risk of recurrence before committing to definitive treatment, allowing for more informed decision-making about whether to proceed with radical prostatectomy or opt for active surveillance
3Object-affected harmful factors
If active surveillance is chosen for low-risk patients to avoid treatment side effects, then quality of life is preserved, but recurrence may go undetected and aggressive disease may progress
Solution Approach 1:
The patent performs preliminary risk stratification using molecular biomarkers before initiating active surveillance, identifying which patients are safe to monitor and which require more aggressive treatment, thereby improving the reliability of disease detection while preserving quality of life for appropriate candidates
Data Source
AI summary
Disclosed is a gene expression panel that can be used to predict prostate cancer (PCa) progression. Some embodiments provide methods for predicting clinical recurrence of PCa. Some embodiments provide a method for treating a patient with prostate cancer, the method comprising: detecting expression levels of a collection of signature genes from a biological sample taken from said patient, wherein said collection of signature genes comprises at least NKX2-1; and correlating expression levels of said collection of signature genes with prostate cancer-related mortality to identify whether the patient is at risk of prostate cancer-related mortality.