AML Mutation Panel for Early Risk Prediction and Therapy Selection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods are inadequate for predicting the risk of acute myeloid leukemia (AML) before its onset and determining the effectiveness of AML therapy, as they do not account for the presence of specific mutations and allele burdens in genes associated with AML.
Innovation Solution
A method for detecting AML-associated mutations in nucleic acid samples using sequencing techniques to identify mutations in genes such as SRSF2, DNMT3A, TET2, IDH2, IDH1, TP53, SF3B1, U2AF1, and JAK2, and predicting AML risk or responsiveness to therapies like chemotherapeutic agents and inhibitors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional diagnostic methods are used to detect AML, then diagnosis can be made after symptoms appear, but early prediction and preventive treatment cannot be achieved
Solution Approach 1:
The patent applies preliminary action by detecting AML-associated mutations in nucleic acid samples before the onset of AML symptoms. The method sequences DNA from blood or bone marrow samples to identify mutations in genes such as IDH1, IDH2, TP53, DNMT3A, TET2, and spliceosome genes, enabling early risk prediction and preventive treatment strategies before the disease fully develops.
2Measurement precision
If mutation detection in multiple genes is performed, then prediction accuracy improves, but testing complexity and cost increase
Solution Approach 1:
The patent applies segmentation by dividing the detection task into specific gene panels. Instead of sequencing the entire genome, the method focuses on sequencing specific genes known to be associated with AML (IDH1, IDH2, TP53, DNMT3A, TET2, and spliceosome genes). This segmented approach maintains high detection accuracy for AML-related mutations while reducing the complexity and cost of the testing system.
3Reliability
If early detection of AML mutations is implemented, then preventive treatment becomes possible, but false positives may lead to unnecessary treatment
Solution Approach 1:
The patent applies local quality by evaluating the specific characteristics and contexts of detected mutations. Not all mutations are treated equally; the method assesses the type, location, and functional impact of each mutation to determine its clinical significance. This localized evaluation approach helps distinguish between benign variants and truly pathogenic mutations, reducing false positives while maintaining high predictive value for AML risk.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables early prediction of AML risk and effective treatment selection by identifying key mutations in nucleic acid samples, allowing for preventive or delaying AML onset through targeted therapies.
Implementation Method 1
sequencing the nucleic acid sample to detect the presence of a mutation in one or more genes selected from the group consisting of SRSF2, U2AF1, and JAK2
Data Source
AI summary
The present technology relates to methods for predicting the risk of acute myeloid leukemia (AML) in a subject prior to the onset of AML symptoms, and whether such a subject will benefit from treatment with an AML therapy. The methods disclosed herein are based on detecting the presence of mutations in the nucleic acid sequences of IDH1/2, TP53, DNMT3A, TET2, and spliceosome genes. Kits for use in practicing the methods are also provided.