Modular Tumor Neoantigen Database for mTSA and aeTSA Detection
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Solution Overview
Problem
Current methods are ineffective in differentiating and identifying tumor neoantigens, hindering early tumor diagnosis and personalized cancer immunotherapy.
Innovation Solution
A method for establishing a tumor neoantigen database that integrates datasets of mutated tumor-specific antigens (mTSAs) and aberrantly expressed tumor-specific antigens (aeTSAs) using DNA/RNA sequencing and LC-MS/MS, predicting binding affinities with MHC molecules, and utilizing HLA genotyping for personalized cancer therapies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current neoantigen identification methods are used, then the process is simple, but the differentiation between mTSAs and aeTSAs is ineffective
Solution Approach 1:
The patent segments the neoantigen identification process into distinct workflows: one for mTSA identification using DNA-seq data and another for aeTSA identification using RNA-seq data. This segmentation allows each workflow to be optimized for its specific target, improving differentiation accuracy while maintaining manageable complexity through modular design
Solution Approach 2:
The patent creates a unified tumor neoantigen database that serves multiple functions: storing mTSA data from DNA-seq, aeTSA data from RNA-seq, and integrating both types of neoantigens for comprehensive tumor diagnosis. This multi-functional database resolves the contradiction by providing accurate differentiation through structured organization while maintaining a single integrated system
2Measurement precision
If comprehensive neoantigen identification is performed, then diagnosis accuracy is improved, but the time required for analysis increases
Solution Approach 1:
The patent divides the comprehensive neoantigen identification into parallel processes: mTSA identification from DNA-seq data and aeTSA identification from RNA-seq data can be performed simultaneously. This segmentation reduces total analysis time while maintaining comprehensive coverage for high accuracy diagnosis
Solution Approach 2:
The patent performs preliminary data processing and filtering steps during the identification processes, such as filtering low-expression peptides and pre-processing sequencing data. These preliminary actions reduce the time required for subsequent analysis while ensuring only high-quality neoantigen candidates are processed, maintaining diagnosis accuracy
3Measurement precision
If multiple data types are integrated, then neoantigen identification accuracy is improved, but the process complexity increases
Solution Approach 1:
The patent segments the data processing into distinct modules: DNA-seq processing for mTSA identification and RNA-seq processing for aeTSA identification. Each module handles its specific data type with dedicated algorithms, improving accuracy while managing complexity through modular architecture that prevents entanglement of processing steps
Solution Approach 2:
The patent introduces standardized data formats and a unified database structure as intermediaries between the different data processing workflows. These intermediaries facilitate smooth integration of mTSA and aeTSA data while abstracting the complexity of data fusion, allowing accurate multi-type integration without proportionally increasing process complexity
Data Source
AI summary
A method for establishing a tumor neoantigen database is and processes for identifying the mutated tumor-specific antigens (mTSAs) and aberrantly expressed tumor-specific antigens (aeTSAs) are disclosed. In particular, the tumor neoantigen database is used for predicting tumor variants of clinical samples.