Systems and methods to detect rare mutations and copy number variation

What is this patent about?

’731 is related to the field of genetic diagnostics and bioinformatics, specifically focusing on the high-sensitivity detection of rare mutations and copy number variations within cell-free polynucleotides. The technology addresses the inherent challenges of analyzing circulating tumor DNA (ctDNA), where disease-related genetic signals are often buried under significant background noise from healthy germline DNA and artifacts introduced during the sequencing process.

The underlying idea behind ’731 is to treat the sequencing process as a communication channel prone to noise and distortion, which can be overcome by a sophisticated molecular tagging and collapsing strategy. By attaching identifiers to individual DNA fragments before amplification, the system can distinguish between true biological variants and errors introduced by PCR or the sequencer itself, effectively creating a high-fidelity digital representation of the original sample.

The claims of ’731 focus on a method for quantifying single nucleotide variant tumor markers by utilizing a specific non-unique tagging architecture on at least 10 ng of cell-free DNA. The process involves grouping sequence reads into families based on a combination of barcode sequences and the physical properties of the fragment—such as start/stop positions and length—to derive a consensus sequence for each original parent molecule.

In practice, the invention works by converting fragmented cell-free DNA into a library where each molecule is labeled with a barcode of at least five nucleotides. After these molecules are amplified and sequenced, the system uses the consensus sequences to filter out random errors; if a mutation appears in only one read of a family, it is discarded as noise, whereas mutations present across the family are retained as high-confidence calls. This allows for the detection of rare variants at frequencies as low as 0.1%, which is often below the raw error rate of standard sequencing platforms.

This approach differentiates itself from prior methods by maximizing conversion efficiency and utilizing a hybrid identification strategy that does not require billions of unique barcodes to track individual molecules. By combining relatively small sets of barcodes with the natural diversity of fragment endpoints, the technology achieves the sensitivity required for early cancer detection and longitudinal monitoring of treatment efficacy without the prohibitive costs or technical overhead of traditional molecular counting techniques.