Neoantigen Scoring via Shallow Sequencing and Sample Selection
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Solution Overview
Problem
Tumor heterogenicity poses a challenge in obtaining a biological sample that is representative of the genomic variants present in the whole tumor, leading to excessive costs and time for non-representative sequencing results, and increased risk of infection or surgical complications.
Innovation Solution
Methods for scoring predicted immunogenicity of neoantigens in biological samples involve preparing multiple samples for nucleic acid sequencing, analyzing sequencing parameters, combining initial sequencing results to yield union sequencing results, and selecting a representative sample to score predicted immunogenicity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple biological samples are collected and exhaustively sequenced to ensure representativeness of tumor subclonal populations, then the reliability of genomic analysis and treatment selection is improved, but the cost and time required for sequencing increases significantly
Solution Approach 1:
The patent performs preliminary shallow sequencing on multiple biological samples before final selection. This preliminary action provides initial data to evaluate sample quality and representativeness, enabling informed selection of the best sample for exhaustive sequencing without having to exhaustively sequence all samples first.
Solution Approach 2:
The patent creates a digital copy or proxy representation of the tumor's genomic landscape through shallow sequencing of multiple samples. This proxy data allows identification of the most representative sample, serving as a stand-in for the exhaustive sequencing that would otherwise need to be performed on all samples.
2Measurement precision
If multiple biological samples are collected and exhaustively sequenced to ensure representativeness of tumor subclonal populations, then the accuracy of neoantigen identification is improved, but the data processing requirements and costs increase significantly
Solution Approach 1:
The patent performs preliminary shallow sequencing and analysis on multiple samples to evaluate their quality metrics and representativeness. This preliminary action generates data that guides the selection of the single best sample for exhaustive sequencing, avoiding the need to process exhaustive data from all samples.
Solution Approach 2:
The patent uses shallow sequencing data as a proxy or copy to evaluate sample quality. This proxy assessment allows identification of the most representative sample without requiring complete exhaustive sequencing and processing of all samples, thereby reducing overall data processing complexity.
3Reliability
If additional biological samples are collected through additional procedures to improve representativeness, then the quality of genomic analysis is improved, but the risk of infection or surgical complications increases
Solution Approach 1:
The patent performs preliminary shallow sequencing on multiple samples that have already been collected, eliminating the need for additional invasive procedures. This preliminary analysis of existing samples identifies the most representative one, avoiding further surgical risks while maintaining analysis quality.
Solution Approach 2:
The patent uses computational analysis (shallow sequencing) of existing samples as a proxy to identify the most representative sample. This computational approach replaces the need for additional physical sample collection procedures, thereby avoiding associated surgical risks and infections.
4Reliability
If exhaustive sequencing is performed on multiple candidate samples to identify a representative sample, then the confidence in treatment selection is improved, but the cost increases significantly
Solution Approach 1:
The patent performs preliminary shallow sequencing on multiple candidate samples to assess their quality and representativeness. This preliminary action provides cost-effective evaluation data that guides selection of the single best sample for exhaustive sequencing, avoiding the high cost of exhaustive sequencing on all samples.
Solution Approach 2:
The patent uses shallow sequencing data as a proxy assessment tool to evaluate sample quality. This proxy evaluation allows confident selection of the most representative sample without requiring exhaustive sequencing of all candidates, thereby significantly reducing overall sequencing costs while maintaining confidence in treatment selection.
Data Source
AI summary
Disclosed herein are methods of scoring predicted immunogenicity of neoantigens from biological samples of a subject. Methods can include the steps of preparing biological samples for nucleic acid sequencing; nucleic acid sequencing; evaluating the initial sequencing results by analyzing (e.g., comparing) sequencing parameters of the results; based on an analysis (e.g., a comparison) of sequencing parameters, combining the initial sequencing results to yield union sequencing results or selecting a representative biological sample; and scoring the predicted immunogenicity of neoantigens in the biological samples based on either the union sequencing results or the sequencing results of the representative sample. Methods can further include the step of comparing sequencing parameters of union sequencing results and the initial sequencing results. Methods can further include the steps of generating a neoantigen vaccine that contains or encodes for a neoantigen scored for predicted immunogenicity and administering the neoantigen vaccine to a subject.