Systems and methods to detect rare mutations and copy number variation

• US 10,683,556 B2
• Filed: 02/15/2019
• Issued: 06/16/2020
• Est. Priority Date: 09/04/2012
• Status: Active Grant

• Current Assignee: Guardant Health Inc.
• Original Assignee: Guardant Health Inc.
• Inventors: Talasaz, AmirAli
• Primary Examiner(s): Priest, Aaron A
• Application Number:
  US16/277,712
• Publication Number:
  US 20190177802A1
• Time in Patent Office: 487 Days
• Field of Search: None
• CPC Class Codes: C12N 15/1065 Preparation or screening of tagged libraries, e.g. tagged microorganisms by STM-mutagenesis, tagged polynucleotides, gene tags
• CPC Class Codes: C12Q 1/6806 Preparing nucleic acids for analysis, e.g. for polymerase chain reaction [PCR] assay C12Q1/6804 takes precedence
• CPC Class Codes: C12Q 1/6869 Methods for sequencing
• CPC Class Codes: C12Q 1/6874 involving nucleic acid arrays, e.g. sequencing by hybridisation
• CPC Class Codes: C12Q 1/6886 for cancer immunoassay for cancer G01N33/574
• CPC Class Codes: C12Q 2537/165 Mathematical modelling, e.g. logarithm, ratio
• CPC Class Codes: C12Q 2545/114 involving a quantitation step
• CPC Class Codes: C12Q 2600/118 Prognosis of disease development
• CPC Class Codes: C12Q 2600/156 Polymorphic or mutational markers
• CPC Class Codes: C12Q 2600/158 Expression markers
• CPC Class Codes: C12Q 2600/16 Primer sets for multiplex assays
• CPC Class Codes: G16B 30/00 ICT specially adapted for sequence analysis involving nucleotides or amino acids
• CPC Class Codes: G16B 30/10 Sequence alignment; Homology search

Abstract

The present disclosure provides a system and method for the detection of rare mutations and copy number variations in cell free polynucleotides. Generally, the systems and methods comprise sample preparation, or the extraction and isolation of cell free polynucleotide sequences from a bodily fluid; subsequent sequencing of cell free polynucleotides by techniques known in the art; and application of bioinformatics tools to detect rare mutations and copy number variations as compared to a reference. The systems and methods also may contain a database or collection of different rare mutations or copy number variation profiles of different diseases, to be used as additional references in aiding detection of rare mutations, copy number variation profiling or general genetic profiling of a disease.

Claims

1. A method of detecting a somatic genetic mutation in double-stranded cell-free deoxyribonucleic acid (cfDNA) from a blood sample for cancer testing in a human subject, comprising:

(a) converting between 100 and 100,000 haploid human genome equivalents of cfDNA derived from the blood sample into non-uniquely tagged parent polynucleotides, wherein the converting comprises ligating the cfDNA with a plurality of molecular barcodes, wherein a given molecular barcode from among the plurality of molecular barcodes is a member of a set of molecular barcodes having between 2 and 1,000 different molecular barcode sequences with a length of at least 5 nucleotides, wherein a molecule of the cfDNA is ligated to a molecular barcode at both ends of the molecule of the cfDNA;

(b) amplifying a plurality of the non-uniquely tagged parent polynucleotides to produce corresponding amplified progeny polynucleotides;

(c) sequencing at least a subset of the amplified progeny polynucleotides to produce sequence reads;

(d) mapping a plurality of the sequence reads to a human reference sequence to produce mapped sequence reads; and

(e) generating a set of consensus sequences from some or all of the mapped sequence reads to detect the somatic genetic mutation, wherein generating a given consensus sequence of the set of consensus sequences is based on information from at least the molecular barcodes, wherein a consensus sequence within the set of consensus sequences corresponds to a unique cfDNA molecule from among the non-uniquely tagged parent polynucleotides, and wherein the somatic genetic mutation comprises a single nucleotide variation (SNV), a copy number variation (CNV), an indel, or a gene fusion.

2. The method of claim 1, wherein the human subject has a cancer or is suspected of having a cancer.

3. The method of claim 1, wherein the cfDNA comprises circulating tumor DNA (ctDNA).

4. The method of claim 1, wherein between 1,000 and 50,000 haploid human genome equivalents of the cfDNA are converted into the non-uniquely tagged parent polynucleotides.

5. The method of claim 1, wherein an expected size distribution of the cfDNA is between 140 and 180 nucleotides.

6. The method of claim 1, wherein a given molecular barcode from among the plurality of molecular barcodes is a member of a set of molecular barcodes having between 5 and 100 different molecular barcodes with a length between 5 and 20 nucleotides.

7. The method of claim 6, wherein the 5 to 20 nucleotides of each of the molecular barcode sequences are pre-determined, non-random sequences.

8. The method of claim 1, wherein the ligating comprises blunt-end ligation or sticky-end ligation.

9. The method of claim 1, wherein each of the plurality of molecular barcodes is part of an adapter sequence.

10. The method of claim 1, further comprising selectively enriching the amplified progeny polynucleotides for target regions associated with cancer prior to sequencing.

11. The method of claim 10, wherein the target regions associated with cancer are selected from a panel of actionable cancer-related genes.

12. The method of claim 1, wherein the sequencing is performed by a sequencer.

13. The method of claim 12, wherein the sequencer is a next-generation sequencer.

14. The method of claim 1, further comprising filtering out sequence reads from among the sequence reads that fail to meet a quality threshold.

15. The method of claim 1, wherein generating the set of consensus sequences comprises assigning a mapped sequence read from among the mapped sequence reads to a family of the mapped sequence reads corresponding to a given consensus sequence from among the set of consensus sequences.

16. The method of claim 15, further comprising collapsing the mapped sequence reads in a plurality of families to generate the set of consensus sequences.

17. The method of claim 15, further comprising generating a base call for at least the family at a genetic locus of a plurality of genetic loci of the human reference sequence.

18. The method of claim 17, further comprising determining a frequency of one or more bases called at the genetic locus from among the plurality of families corresponding to the mapped sequence reads.

19. The method of claim 17, further comprising detecting, at one or more genetic loci, at least one SNV, CNV, indel, or gene fusion.

20. The method of claim 1, further comprising detecting two or more somatic genetic mutations.

21. The method of claim 20, wherein the two or more somatic genetic mutations comprise an SNV and a CNV.

22. The method of claim 16, further comprising identifying a subset of the set of consensus sequences that include a somatic genetic mutation as compared to the human reference sequence at a genetic locus of a plurality of genetic loci of the human reference sequence.

23. The method of claim 22, further comprising calculating a ratio of (a) a number of the set of consensus sequences that include a somatic genetic mutation as compared to the human reference sequence, to (b) a total number of the set of consensus sequences for a genetic locus of a plurality of genetic loci of the human reference sequence.

24. The method of claim 1, wherein the cfDNA comprises between 0.1% and 1% of cfDNA from a cancer genome.

25. The method of claim 24, wherein the cfDNA comprises between 0.1% and 0.5% of cfDNA from the cancer genome.

26. The method of claim 1, wherein generating the given consensus sequence of the set of consensus sequence is further based on using a start base position of a given mapped sequence read from among the mapped sequence reads at which the given mapped sequence read is determined to start mapping to the human reference sequence and a stop base position of the given sequence read at which the given sequence read is determined to stop mapping to the human reference sequence.