TP53 Mutation Score for WEE1 Inhibitor Patient Selection
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Solution Overview
Problem
There is a need for biomarkers to predict which patients are likely to respond to treatment with WEE1 inhibitors, particularly for those who are non-responsive or may become refractive to first-line therapies, as current treatments often target DNA indiscriminately and can lead to resistance in cancer cells.
Innovation Solution
The identification of TP53 gene mutations, specifically using a 'p53 filter' to assign point values based on mutation types, allows for the classification of patients likely to respond to WEE1 inhibitor treatment by calculating a TP53 mutation score, enabling targeted therapy with WEE1 inhibitors such as WEE1-1.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If WEE1 inhibitors are used to treat cancer, then treatment efficacy is improved for p53-defective tumors, but patient selection becomes more complex requiring biomarker analysis
Solution Approach 1:
The patent applies preliminary action by performing TP53 mutation status analysis and calculating mutation scores before initiating WEE1 inhibitor treatment. This pre-screening process identifies patients with p53-defective tumors who are most likely to respond to WEE1 inhibition, ensuring that the complex patient selection criteria are established beforehand rather than during treatment decision-making
Solution Approach 2:
The patent introduces an intermediary biomarker system (TP53 mutation score calculation based on specific mutation types) that mediates between the complex molecular characteristics of tumors and the clinical decision to use WEE1 inhibitors. This intermediary scoring system simplifies the translation of genetic data into treatment recommendations
2Measurement precision
If TP53 mutation scoring system is implemented, then patient response prediction is improved, but diagnostic complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the TP53 gene into specific mutable regions (exons 2-11) and further segmenting mutations into weighted categories (nonsense, frameshift, splice site, missense mutations). Each segment type is assigned a specific point value, transforming a complex genetic analysis into a structured, quantifiable scoring system that improves prediction accuracy while maintaining diagnostic feasibility
Solution Approach 2:
The patent changes the parameter of mutation assessment from a qualitative description to a quantitative scoring system. By assigning numerical values to different mutation types (e.g., nonsense mutations = 3 points, frameshift = 2 points) and calculating cumulative scores, the system transforms complex genetic data into a simple threshold-based prediction tool
Data Source
AI summary
The present invention relates generally to the use of gene mutations, whose presence or absence are useful for predicting a patient's response to treatment with an anti-proliferative agent, in particular a WEE1 inhibitor. The presence or absence of a mutation to the TP53 gene, can be used to predict response to treatment with a WEE1 inhibitor in a patient presenting with a cancerous condition.