Mutation Detection for Hypomethylating Agent Response Prediction
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Solution Overview
Problem
Current treatments for myelodysplastic syndromes (MDS) with hypomethylating agents are not predictive, leading to a lack of identification of responsive patients, resulting in ineffective therapy and potential side effects.
Innovation Solution
Detection of specific mutations in genes such as TET2, ASXL1, and NRAS in nucleic acid samples from patients to predict response to hypomethylating agents like decitabine and azacitidine, using next-generation sequencing and computational analysis to determine allelic frequency and mutational status.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If hypomethylating agents are used to treat MDS patients, then therapy can be administered, but it is impossible to predict which patients will respond and which will not, leading to ineffective therapy and potential side effects
Solution Approach 1:
The patent performs preliminary genetic testing to detect mutations in specific genes (ASXL1, TET2, RUNX1, TP53, SRSF2, DNMT3A, SF3B1, U2AF1, NOTCH2, NRAS, BCOR, NF1, EZH2, MAML1, NOTCH1, IDH2, SCAF11, KDM6B, CBL, ATRX, KDM3A, PRPF8, PTPN11, ZRSR2, IDH1, JAK2, KRAS, NPM1, ETV6, TLR6, WT1, U2AF2, TLR2, GATA2, MYBL2, SF3B3, SUZ12) before administering hypomethylating agents. This preliminary detection of mutational status allows clinicians to predict therapy response in advance and select patients most likely to benefit, avoiding unnecessary treatment in non-responders.
2Reliability
If genetic testing for MDS mutations is performed, then patient selection for therapy can be improved, but the complexity of detecting and measuring multiple gene mutations increases
Solution Approach 1:
The patent segments the complex task of detecting multiple gene mutations into a systematic approach by categorizing mutations into two functional groups: ASXL1 mutations (indicating resistance) and mutations in other genes (indicating potential response). This segmentation allows for a structured testing protocol that can handle multiple genes through a coordinated methodology, making the complex detection process more manageable and interpretable.
3Object-affected harmful factors
If targeted therapy based on mutation detection is implemented, then unnecessary side effects can be avoided, but the device complexity and testing requirements increase
Solution Approach 1:
The patent changes the parameter of patient selection criteria from traditional clinical parameters to genetic mutational status. By detecting specific mutations in DNA and using this genetic information to stratify patients into responder and non-responder categories, the system enables personalized therapy decisions. This parameter change allows for targeted therapy administration that avoids unnecessary side effects in non-responders while maintaining manageable testing complexity through focused gene panels.
Data Source
AI summary
Disclosed are methods for predicting a response of a subject with myelodysplastic syndrome to treatment with a hypomethylating agent, for example using a sample obtained from the subject. The methods can be used to select a subject for treatment with a hypomethylating agent, and/or measure a subject's response to therapy and/or disease progression/regression. The methods include detecting, in a nucleic acid sample obtained from a subject, one or more mutations of any one or more genes selected from Table 3a.