Predictive Marker Analysis for Personalized Cancer Therapy
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Solution Overview
Problem
Current cancer therapies face challenges due to individual patient responses, leading to ineffective and potentially harmful treatments, as existing methods fail to optimize therapy for specific patients, particularly in identifying responsive patients for proteasome inhibition and glucocorticoid therapies.
Innovation Solution
The development of methods and compositions to identify specific predictive markers that determine patient responsiveness to proteasome inhibition and glucocorticoid therapies, allowing for personalized treatment regimens by analyzing marker expression levels in tumors, thereby optimizing therapy and reducing ineffective treatments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If proteasome inhibition therapy and glucocorticoid therapy are used to treat cancer, then treatment efficacy is improved for responsive patients, but harmful effects increase for non-responsive patients due to unnecessary and potentially harmful therapy
Solution Approach 1:
The patent applies preliminary action by determining the expression level of predictive markers (such as PSMB8, PSMB9, PSMB10, and glucocorticoid receptor markers) before initiating proteasome inhibition therapy and glucocorticoid therapy. This allows clinicians to predict patient responsiveness in advance and avoid administering harmful treatments to non-responsive patients, thereby resolving the contradiction between improving treatment efficacy and reducing harmful effects
Solution Approach 2:
The patent uses predictive marker expression levels as an intermediary to mediate between the therapy and patient outcome. By measuring markers like PSMB8, PSMB9, PSMB10, and glucocorticoid receptor expression, the system indirectly assesses patient responsiveness without directly testing the therapy itself, enabling informed treatment decisions that balance efficacy and harm reduction
2Measurement precision
If individualized therapy optimization is implemented, then treatment precision is improved, but device complexity increases due to marker analysis requirements
Solution Approach 1:
The patent extracts specific predictive marker genes (PSMB8, PSMB9, PSMB10, and glucocorticoid receptor markers) from the complex genomic landscape to create a focused assessment panel. By selecting only the most relevant markers rather than analyzing the entire genome, the patent achieves high measurement precision for therapy optimization while minimizing the complexity of the required analysis
Solution Approach 2:
The patent changes the parameter of analysis from broad genomic profiling to specific marker expression levels. By focusing on quantifying the expression of selected predictive markers rather than进行全面 genomic analysis, the patent achieves precise individualized therapy optimization with simplified analytical requirements
Data Source
AI summary
The present invention is directed to the identification of predictive markers that can be used to determine whether patients with cancer are clinically responsive or non-responsive to a therapeutic regimen prior to treatment. In particular, the present invention is directed to the use of certain individual and/or combinations of predictive markers, wherein the expression of the predictive markers correlates with responsiveness or non-responsiveness to a therapeutic regimen. Thus, by examining the expression levels of individual predictive markers and/or predictive markers comprising a marker set, it is possible to determine whether a therapeutic agent, or combination of agents, will be most likely to reduce the growth rate of tumors in a clinical setting.