Genomic Classifiers for HRD Prostate Cancer Prediction
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Solution Overview
Problem
Current methods for diagnosing and treating prostate cancer, particularly homologous recombination deficiency (HRD) prostate cancer, lack effective biomarkers and classifiers to accurately predict patient outcomes and response to therapies like PARP inhibitors, leading to suboptimal treatment strategies.
Innovation Solution
The development of methods, systems, and kits for expression-based analysis using specific biomarkers and genomic classifiers to identify HRD prostate cancer, including probe sets and algorithms for determining nucleic acid expression levels in biological samples, allowing for personalized treatment decisions such as administering PARP inhibitors or other therapies based on HRD status.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard clinical parameters (tumor size, grade, lymph node involvement) are used for diagnosis and treatment stratification, then treatment decisions can be made based on available data, but the ability to accurately predict response to targeted therapies like PARP inhibitors is insufficient
Solution Approach 1:
The patent segments the diagnosis and treatment prediction process by introducing distinct molecular biomarker panels (e.g., HRD-related genes, DNA repair pathway genes) that can be independently analyzed. This segmentation allows for specific prediction of response to targeted therapies like PARP inhibitors, separating the molecular assessment from traditional clinical parameter assessment, thereby improving prediction accuracy without losing molecular information.
2Reliability
If molecular markers are incorporated in clinical practice to define tumor subtypes, then targeted therapy response prediction improves, but the complexity of diagnostic and treatment decision processes increases
Solution Approach 1:
The patent develops universal molecular biomarker panels that can assess multiple aspects of tumor biology simultaneously (e.g., HRD status, DNA repair capacity, therapeutic response prediction). These multi-functional biomarker sets enable a single diagnostic process to provide comprehensive information for targeted therapy decisions, reducing the need for multiple separate tests and simplifying the overall diagnostic workflow while maintaining high reliability.
3Adaptability or versatility
If detailed molecular mechanisms and regulatory pathways are analyzed to improve therapeutic strategy selection, then treatment optimization improves, but the complexity and cost of diagnostic testing increases
Solution Approach 1:
The patent extracts and focuses on specific key molecular biomarkers and pathways that are most relevant for predicting response to targeted therapies. Rather than analyzing all possible molecular mechanisms, the invention selects critical biomarker panels (e.g., specific DNA repair genes, HRD-related markers) that can be tested with simplified, targeted assays. This extraction approach enables effective therapeutic strategy selection while controlling diagnostic complexity and cost.
Data Source
AI summary
The disclosure relates to methods, systems, kits and probe sets for the identification, determination, diagnosis, and/or prognosis of homologous recombination deficiency prostate cancer in a subject. The disclosure also provides biomarkers and clinically useful genomic classifiers for identifying homologous recombination deficiency prostate cancer, bioinformatic methods for determining clinically useful classifiers, and methods of use of each of the foregoing. The methods, systems, kits and probe sets can provide expression-based analysis of biomarkers for purposes of homologous recombination deficiency prostate cancer in a subject. Methods of treating homologous recombination deficiency prostate cancer based on expression analysis are also provided. The methods and classifiers of the present disclosure are also useful for predicting response to anticancer therapy (e.g., PARP inhibitors).