Cancer detection and classification using methylome analysis

Abstract

There is described herein a method of detecting the presence of DNA from cancer cells in a subject comprising: providing a sample of cell-free DNA from a subject; subjecting the sample to library preparation to permit subsequent sequencing of the cell-free methylated DNA; adding a first amount of filler DNA to the sample, wherein at least a portion of the filler DNA is methylated, then optionally denaturing the sample; capturing cell-free methylated DNA using a binder selective for methylated polynucleotides; sequencing the captured cell-free methylated DNA; comparing the sequences of the captured cell-free methylated DNA to control cell-free methylated DNAs sequences from healthy and cancerous individuals and from individuals with distinct cancer types and subtypes; identifying the presence of DNA from cancer cells if there is a statistically significant similarity between one or more sequences of the captured cell-free methylated DNA and cell-free methylated DNAs sequences from cancerous individuals.

1 . A method, comprising:
 (a) subjecting a plurality of nucleic acid molecules generated from a cell-free deoxynucleic acid (cfDNA) sample of said subject to sequencing to yield a plurality of sequencing reads;   (b) computer processing said plurality of sequencing reads to generate a methylation profile for said plurality of nucleic acid molecules; and   (c) computer processing said methylation profile to determine that said subject has or is at risk of having said cancer at an area under the receiver operating characteristic curve (AUROC) of at least about 94%.   
     
     
         2 . The method of  claim 1 , wherein said cancer is selected from the group consisting of lung cancer, breast cancer, colorectal cancer, acute myelogenous leukemia, and glioblastoma multiform. 
     
     
         3 . The method of  claim 2 , wherein said cancer is acute myelogenous leukemia. 
     
     
         4 . The method of  claim 3 , wherein said AUROC is at least about 99%. 
     
     
         5 . The method of  claim 1 , wherein said determining said subject has or is at risk of having a type of cancer comprises determining a tissue of origin of said cfDNA. 
     
     
         6 . The method of  claim 1 , further comprising determining said subject has or is at risk of having a subtype of cancer. 
     
     
         7 . The method of  claim 2 , when said subject has or is at risk of breast cancer, further comprising determining a subtype of breast cancer, wherein said subtype comprises ER positive, ER negative, HER2 positive, HER2 negative, or triple-negative breast cancer (TNBC). 
     
     
         8 . The method of  claim 2 , when said subject has or is at risk of acute myelogenous leukemia, further comprising determining a subtype of acute myelogenous leukemia, wherein said subtype comprises FLT3 negative or FLT3 positive. 
     
     
         9 . The method of  claim 2 , when said subject has or is at risk of glioblastoma multiform, further comprising determining a subtype of glioblastoma multiform, wherein said subtype comprises IDH mutation positive or IDH mutation negative. 
     
     
         10 . The method of  claim 2 , when said subject has or is at risk of lung cancer, further comprising determining a subtype of lung cancer, wherein said subtype comprises adenocarcinoma, squamous carcinoma, or small cell carcinoma. 
     
     
         11 . The method of  claim 1 , further comprising generating a report that said subject does or does not have said cancer or is or is not at risk or having said cancer. 
     
     
         12 . A method, comprising:
 (a) subjecting a plurality of nucleic acid molecules generated from a cell-free deoxynucleic acid (cfDNA) sample of said subject to sequencing to yield a plurality of sequencing reads;   (b) computer processing said plurality of sequencing reads to generate a methylation profile for said plurality of nucleic acid molecules; and   (c) computer processing said methylation profile to determine that said subject has or is at risk of having said specific stage of said cancer at an area under the receiver operating characteristic curve (AUROC) of at least about 93%.   
     
     
         13 . The method of  claim 12 , wherein said cancer is lung cancer. 
     
     
         14 . The method of  claim 13 , wherein said specific stage is an early stage of lung cancer. 
     
     
         15 . The method of  claim 14 , wherein said AUROC is at least about 95%. 
     
     
         16 . The method of  claim 13 , wherein said specific stage is a late stage of lung cancer. 
     
     
         17 . The method of  claim 12 , wherein said methylation profile comprises methylation levels of a plurality of differentially methylated region (DMR) of said plurality of nucleic acid molecules. 
     
     
         18 . The method of  claim 17 , wherein said DMR comprises hypermethylation or hypomethylation. 
     
     
         19 . The method of  claim 12 , further comprising mixing said cfDNA sample with an amount of filler DNA to generate a DNA mixture sample. 
     
     
         20 . The method of  claim 19 , wherein said DNA mixture sample comprises at least an amount of total DNA that is at least about 50 nanograms (ng). 
     
     
         21 . The method of  claim 20 , wherein said filler DNA is at least partially methylated and comprises a length of about 50 bp to 800 bp. 
     
     
         22 . The method of either  claim 12 , further comprising incubating said DNA mixture to increase a rate of enrichment of at least one or more methylated regions of said plurality of nucleic acid molecules of said cfDNA sample. 
     
     
         23 . The method of  claim 22 , further comprising incubating said DNA mixture with a binder that is configured to bind methylated nucleotides, wherein said binder comprises a protein comprising a methyl-CpG-binding domain. 
     
     
         24 . The method of  claim 23 , further comprising incubating said DNA mixture with a binder that is configured to bind methylated nucleotides, wherein said binder comprises an antibody. 
     
     
         25 . The method of either  claim 12 , wherein computer processing said methylation profile comprises comparing to a methylation profile of a healthy subject or using a trained machine learning algorithm. 
     
     
         26 . The method of  claim 25 , wherein said trained machine learning algorithm comprises a linear regression. 
     
     
         27 . The method of  claim 26 , wherein said comparing comprises comparing said methylation profile to said methylation profile of said healthy subject with respect to FANTOM5 enhancers, CpG islands, CpG shores, CpG shelves, or any combination thereof.