Meningioma Diagnosis via Specific Gene Mutation Sequencing
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Solution Overview
Problem
Current methods lack effective diagnostic and therapeutic options for meningiomas, particularly in identifying specific mutations associated with neoplasia, which hinders accurate diagnosis, classification, and treatment planning.
Innovation Solution
A method involving the identification of specific mutations in genes such as NF2, TRAF7, AKT1, KLF4, SMO, PIK3CA, PIK3R1, BRCA1, CREBBP, SMARCB1, and PRKAR1A through nucleic acid sequencing and analysis, enabling diagnosis, characterization, classification, and targeted treatment of neoplasia, including meningioma.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If surgical intervention or radiotherapy is used to treat symptomatic meningioma patients, then neurological deficits can be addressed, but there are no established chemotherapeutic targets and treatment options are limited
Solution Approach 1:
The patent identifies specific molecular parameters (mutations in NF2, TRAF7, AKT1, KLF4, SMO, PIK3CA, PIK3R1, BRCA1, CREBBP, SMARCB1, and PRKAR1A genes) that define different meningioma subtypes. By changing from general treatment approaches to targeted therapies based on these molecular parameters, the patent enables personalized treatment strategies that address the lack of chemotherapeutic targets while maintaining effectiveness.
Solution Approach 2:
The patent segments meningiomas into distinct molecular subtypes based on specific gene mutations. This segmentation allows for differentiated treatment approaches for each subtype, transforming the monolithic treatment problem into multiple targeted treatment opportunities, thereby increasing treatment versatility without compromising effectiveness.
2Measurement precision
If genomic analysis is performed to identify mutations, then diagnostic accuracy and treatment targeting improve, but the complexity of analysis and identification of specific mutations increases
Solution Approach 1:
The patent segments the genomic analysis into focused analyses of specific genes known to be associated with meningioma (NF2, TRAF7, AKT1, KLF4, SMO, PIK3CA, PIK3R1, BRCA1, CREBBP, SMARCB1, and PRKAR1A). This segmentation reduces the complexity of whole-genome analysis while maintaining high diagnostic accuracy by concentrating on the most relevant genetic markers.
Solution Approach 2:
The patent performs preliminary identification of mutation hotspots and known association patterns before comprehensive sequencing. By pre-establishing which genes and mutation types are most indicative of meningioma and its subtypes, the patent simplifies the diagnostic workflow and reduces analysis complexity while preserving measurement precision.
3Measurement precision
If comprehensive genetic sequencing is performed to characterize all mutations, then classification accuracy improves, but the time and resources required for analysis increase
Solution Approach 1:
The patent applies partial action by sequencing and analyzing only the specific genes and regions most associated with meningioma pathology rather than performing comprehensive whole-genome sequencing. This partial approach focuses on the essential genetic markers (NF2, TRAF7, AKT1, etc.) that provide sufficient classification accuracy while significantly reducing analysis time and resource requirements.
Solution Approach 2:
The patent performs preliminary characterization of mutation patterns and their associations with meningioma subtypes before full diagnostic workup. By pre-establishing the temporal and functional relationships between specific mutations and tumor characteristics, the patent enables rapid classification without requiring exhaustive genetic analysis, thus reducing time loss while maintaining precision.
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
This approach allows for precise diagnosis, characterization, and treatment of meningiomas by identifying specific mutations, thereby improving diagnostic accuracy and treatment efficacy.
Implementation Method 1
determining the sequence of the nucleic acid comprising the at least one gene, or fragment thereof, associated with neoplasia in the test sample
Implementation Method 2
comparing the sequence of the nucleic acid comprising the at least one gene, or fragment thereof, associated with neoplasia in the test sample with the sequence of at least one mutation of a gene associated with neoplasia, wherein when the sequence of the nucleic acid comprising the at least one gene, or fragment thereof, associated with neoplasia in the test sample is homologous to the sequence of the at least one mutation of the gene associated with neoplasia, the mutation in the gene associated with neoplasia in the subject is identified
Data Source
AI summary
The present invention relates to mutations associated with neoplasia, such as meningioma. Thus, the invention relates to compositions and methods useful for the assessment, characterization, classification and treatment of neoplasia, including meningioma, based upon the presence or absence of mutations that are associated with neoplasia, including meningioma.