SNP Panel Authentication for Xenograft Tumor Models
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Solution Overview
Problem
Current methods for authenticating cell lines and tumor models face challenges such as misidentification, contamination, and genetic heterogeneity, particularly in xenograft models, where human and mouse genetic compositions fluctuate, affecting the accuracy of STR and SNP-based authentication methods.
Innovation Solution
A method involving deep next-generation sequencing (NGS) to detect genotypes at multiple human or mouse SNP loci, allowing for precise identification and quantification of contaminants, gender determination, and estimation of mouse content in human-mouse mixtures, using a panel of selected SNPs and statistical models to determine sample authenticity and composition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional STR and SNP-based authentication methods are used for tumor models, then authentication can be performed, but accuracy is reduced due to fluctuating human-mouse genetic compositions in xenograft models
Solution Approach 1:
The patent applies local quality by focusing authentication on specific human tumor cell markers rather than overall genomic composition. By targeting loci specific to human tumor cells (such as human STR markers or human-specific SNPs), the method locally identifies the human component even in the presence of varying mouse stromal content, thereby maintaining authentication accuracy despite compositional fluctuations in xenograft models.
Solution Approach 2:
Instead of attempting to authenticate the entire tumor model composition (which fails due to mixed human-mouse content), the patent inverts the approach by specifically detecting and quantifying only the human tumor cell component. This inversion allows the method to succeed in xenograft models where traditional whole-genome authentication fails.
2Measurement precision
If deep NGS is used to detect genotypes at multiple SNP loci, then sensitivity and accuracy in detecting contamination increase, but cost and complexity increase
Solution Approach 1:
The patent segments the authentication task by selecting and analyzing only specific informative SNP loci rather than performing complete whole-genome sequencing. By focusing on a curated panel of SNPs that are informative for authentication and contamination detection, the method achieves high measurement precision while reducing the complexity and cost associated with comprehensive NGS approaches.
Solution Approach 2:
The patent applies partial action by using a selective panel of SNP loci that provides sufficient information for authentication and contamination detection without requiring exhaustive genomic analysis. This partial approach to NGS maintains high sensitivity and accuracy while significantly reducing the complexity, cost, and data processing requirements compared to full-genome sequencing.
3Measurement precision
If multiple SNP loci are analyzed to identify major and minor components, then ability to quantify contamination improves, but measurement time and processing requirements increase
Solution Approach 1:
The patent applies preliminary action by pre-selecting and optimizing a panel of informative SNP loci before actual authentication testing. This pre-prepared panel is specifically designed to efficiently detect and quantify contaminants, allowing rapid analysis during actual authentication without requiring time-consuming real-time selection of informative markers, thereby reducing processing time while maintaining high quantification accuracy.
Data Source
AI summary
The disclosure provides methods and compositions, e.g., kits, for identifying or authenticating a sample, e.g., a tumor model, based on the genotype of the sample at a group of SNP loci.