Tumor Clone Sequencing with Molecular Barcodes and Read Pooling
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Solution Overview
Problem
Traditional methods for sequencing cancerous tumors are error-prone, slow, and expensive, and fail to detect minor sub-clones that drive tumor growth and resistance, due to limited sequencing reads from single cells and low detection limits.
Innovation Solution
A method involving molecular barcode sequencing of genetic material from tumor cells, which includes attaching a unique barcode to nucleic acids, assembling sequence reads into tumor cell sequences, clustering self-similar cells, and pooling reads to identify and characterize dominant and minor tumor sub-clones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional single-cell sequencing methods are used, then each tumor cell can be sequenced individually, but the sequencing is error-prone, slow, and expensive with insufficient sequencing reads
Solution Approach 1:
The patent combines multiple single-cell sequencing results into a pooled analysis approach. By merging reads from multiple cells and using consensus algorithms, the method achieves higher sequencing accuracy while maintaining high throughput. The combination of reads from multiple cells compensates for individual cell sequencing errors and increases the effective sequencing depth.
2Measurement precision
If traditional sequencing methods are used, then sequencing can be performed on available samples, but minor sub-clones present at low frequencies are often below the detection limit
Solution Approach 1:
The patent pools sequencing reads from multiple tumor cells to achieve sufficient read depth for detecting minor sub-clones. By combining reads across multiple cells and using consensus algorithms, the method increases detection sensitivity for low-frequency variants that would be undetectable in single-cell sequencing.
Solution Approach 2:
The patent performs preliminary clustering of tumor cells based on sequencing data before final variant calling. This preliminary grouping allows the method to accumulate reads from cells with similar profiles, thereby increasing the effective read depth for detecting minor sub-clones while reducing computational complexity.
3Loss of information
If traditional methods are used to profile tumor heterogeneity, then the clonal makeup can be assessed, but the process is slow and expensive
Solution Approach 1:
The patent performs preliminary clustering of tumor cells based on initial sequencing data to identify potential sub-clones. This preliminary organization of data by clonal similarity enables more efficient downstream analysis and reduces the time required for complete tumor heterogeneity profiling while maintaining comprehensive information capture.
Solution Approach 2:
The patent combines sequencing data from multiple cells and integrates it with clustering algorithms to efficiently reconstruct tumor clonal architecture. By merging information across multiple cells and using consensus approaches, the method achieves comprehensive tumor heterogeneity assessment at reduced time and cost compared to traditional single-cell sequencing.
Data Source
AI summary
Disclosed herein are methods for profiling a cancerous tumor using a high-throughput sequencing technique.