Systems and methods to detect rare mutations and copy number variation

What is this patent about?

’152 is related to the field of molecular diagnostics and bioinformatics, specifically focusing on the high-sensitivity detection of genetic aberrations in cell-free DNA (cfDNA). The technology addresses the challenge of identifying rare somatic mutations and copy number variations that are often masked by the inherent noise and distortion found in standard next-generation sequencing workflows. By analyzing extracellular polynucleotides isolated from bodily fluids like blood, the system provides a non-invasive means to monitor disease states such as cancer.

The underlying idea behind ’152 is to maximize the conversion of limited starting genetic material into a digital library where individual parent molecules can be accurately tracked and reconstructed. By using a high molar excess of molecular barcodes to tag both ends of cfDNA fragments, the invention ensures that even a small amount of input DNA (1–100 ng) is represented with high fidelity. This approach allows the system to distinguish between true biological variants and artifacts introduced during PCR amplification or sequencing by grouping reads into families derived from the same original molecule.

The claims of ’152 focus on a method for detecting somatic genetic variants by contacting a specific mass of cfDNA with at least an 80× molar excess of molecular barcodes to ensure a conversion efficiency of at least 20%. The process involves attaching barcodes to both ends of the cfDNA fragments, amplifying these tagged molecules, and then sequencing the resulting progeny. The independent claims specifically highlight the use of these barcodes to group sequence reads into families, which are then used to identify single nucleotide variations, indels, copy number variations, or gene fusions with high sensitivity.

In practice, the invention functions by implementing a high-diversity library preparation that captures a vast majority of the starting molecules, which is critical when only a few mutated fragments may exist in a 10 mL blood sample. After sequencing, the bioinformatics pipeline collapses the raw reads into consensus sequences based on the unique or non-unique barcode combinations and the genomic coordinates of the fragments. This collapsing mechanism effectively filters out random sequencing errors, as a true mutation will appear across multiple progeny in a family, whereas an error will typically appear in only one.

This method differs from prior approaches by significantly improving the conversion efficiency of the library preparation and utilizing a dual-tagging strategy to overcome the limitations of low-abundance templates. While traditional sequencing often loses rare signals due to inefficient ligation or high background noise, this system uses digital sequencing to provide a near-perfect representation of the original sample. By normalizing read counts and variant frequencies across predefined genomic regions, the technology enables the detection of cancer-related changes at frequencies as low as 0.1%, providing a robust tool for serial monitoring of tumor burden and treatment response.