Cell-free DNA Fragment Size Profiling for Tumor Mutation Burden
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Solution Overview
Problem
Current methods for analyzing cell-free DNA (cfDNA) samples struggle to distinguish between cancer variants and somatic variants originating from hematopoietic cells, leading to false positive mutations that affect clinical decisions due to the majority of cfDNA fragments coming from hematopoietic cells rather than tumor cells.
Innovation Solution
The method involves obtaining a cfDNA sample, extracting and sequencing DNA fragments, performing molecular profiling to determine variant allele frequency, and generating a fragment size distribution profile to differentiate between cancer and hematopoietic cell variants, allowing for the identification and removal of hematopoietic cell variants to accurately determine tumor mutation burden.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cfDNA sequencing is performed to detect cancer variants, then cancer diagnosis and monitoring capability is improved, but false positive mutations from hematopoietic cells increase leading to reduced measurement precision
Solution Approach 1:
The method segments cfDNA fragments by size into distinct categories (e.g., short fragments <100bp vs. long fragments >100bp). Since hematopoietic cells produce predominantly short fragments while tumor cells produce longer fragments, this segmentation allows selective analysis of longer fragments to enrich for true cancer variants and reduce false positives from clonal hematopoiesis.
Solution Approach 2:
The patent applies different analytical criteria to different fragment size categories. Instead of uniform analysis, it uses size-specific thresholds and profiling approaches tailored to each fragment length range, allowing optimized detection parameters for each local region of the cfDNA size distribution to maximize cancer variant identification while filtering hematopoietic artifacts.
2Measurement precision
If variant calling is performed on cfDNA, then tumor mutation burden assessment is improved, but contamination from hematopoietic cell variants leads to inaccurate TMB calculation
Solution Approach 1:
The method extracts and removes hematopoietic cell variants from the total variant list before TMB calculation. By identifying variants associated with clonal hematopoiesis (through size profiling and VAF analysis) and excluding them, the approach isolates true tumor-derived variants for accurate TMB assessment, preventing false inflation of mutation burden.
Solution Approach 2:
Fragment size distribution profiling serves as an intermediary filtering mechanism between raw sequencing data and final variant calling. This intermediate analysis layer identifies and flags variants likely originating from hematopoietic cells, allowing selective removal before downstream TMB calculation, thus mediating between total variant detection and tumor-specific variant identification.
3Reliability
If comprehensive variant analysis is performed, then cancer detection sensitivity is improved, but computational complexity and analysis time increase
Solution Approach 1:
The computational analysis is segmented by fragment size categories, allowing parallel processing of different size ranges. This segmentation enables efficient filtering and profiling of variants within specific size windows rather than uniform analysis of all fragments, reducing overall computational burden while maintaining high sensitivity through targeted deep analysis of cancer-enriched size ranges.
Data Source
AI summary
Methods and systems are provided for differentiating between cancer variants and somatic variants originating from hematopoietic cells in a cell free DNA sample. In some embodiments, the cancer variants can be distinguished from somatic variants originating from hematopoietic cells based on fragment size distribution.