Method and system for determining cancer status

Abstract

Disclosed herein are methods, systems, platforms, non-transitory computer-readable medium, services, and kits for determining a cancer type in an individual. Also described herein include methods, systems, platforms, non-transitory computer-readable medium, and compositions for generating a CpG methylation profile database.

1 .- 26 . (canceled) 
     
     
         27 . A method of diagnosing a cancer in an individual in need thereof, comprising:
 a) processing an extracted genomic DNA with a deaminating agent to generate a treated genomic DNA comprising deaminated nucleotides, wherein the extracted genomic DNA is obtained from a biological sample from the individual;   b) generating a methylation profile of one or more biomarkers selected from Table 58 from the treated genomic DNA; and   c) diagnosing whether the individual has a cancer by comparing the methylation profile to a reference CpG methylation profile obtained from a cancer CpG methylation profile database, wherein a correlation between the methylation profile and the reference CpG methylation profile determines the presence of cancer in the individual.   
     
     
         28 . The method of  claim 27 , wherein the reference CpG methylation profile obtained from the cancer CpG methylation profile database is generated by the steps of:
 a) generating CpG methylation data from a set of biological samples by a sequencing method, wherein the set comprises a first cancerous biological sample, a second cancerous biological sample, a third cancerous biological sample, a first normal biological sample, a second normal biological sample, and a third normal biological sample; wherein the first, second, and third cancerous biological samples are different; and wherein the first, second, and third normal biological samples are different;   b) obtaining a first pair of CpG methylation datasets, with a first processor, generated from the first cancerous biological sample and the first normal biological sample, wherein CpG methylation data generated from the first cancerous biological sample form a first dataset within the first pair of datasets, CpG methylation data generated from the first normal biological sample form a second dataset within the first pair of datasets, and the first cancerous biological sample and the first normal biological sample are from the same biological sample source;   c) obtaining a second pair of CpG methylation datasets, with the first computing device, generated from the second normal biological sample and the third normal biological sample, wherein CpG methylation data generated from the second normal biological sample form a third dataset within the second pair of datasets, CpG methylation data generated from the third normal biological sample form a fourth dataset within the second pair of datasets, and the first, second, and third normal biological samples are different;   d) obtaining a third pair of CpG methylation datasets, with the first computing device, generated from the second cancerous biological sample and the third cancerous biological sample, wherein CpG methylation data generated from the second cancerous biological sample form a fifth dataset within the third pair of datasets, CpG methylation data generated from the third cancerous biological sample form a sixth dataset within the third pair of datasets, and the first, second, and third cancerous biological samples are different;   e) generating a pair-wise methylation difference dataset, with a second processor, from the first, second, and third pair of datasets; and   f) analyzing the pair-wise methylation difference dataset with a control dataset by a machine learning method to generate the cancer CpG methylation profile database, wherein
 (1) the machine learning method comprises: identifying a plurality of makers and a plurality of weights based on a top score, and classifying the samples based on the plurality of markers and the plurality of weights; and 
 (2) the cancer CpG methylation profile database comprises a set of CpG methylation profiles and each CpG methylation profile represents a cancer type. 
   
     
     
         29 . The method of  claim 28 , wherein step e) further comprises
 a) calculating a difference between the first dataset and the second dataset within the first pair of datasets;   b) calculating a difference between the third dataset and the fourth dataset within the second pair of datasets; and   c) calculating a difference between the fifth dataset and the sixth dataset within the third pair of datasets.   
     
     
         30 . The method of  claim 28 , wherein the machine learning method utilizes an algorithm selected from one or more of the following: a principal component analysis, a logistic regression analysis, a nearest neighbor analysis, a support vector machine, and a neural network model. 
     
     
         31 . The method of  claim 28 , wherein the CpG methylation data is generated from an extracted genomic DNA treated with a deaminating agent. 
     
     
         32 . The method of  claim 27 , wherein the comparing further comprises determining the cancer type of the individual. 
     
     
         33 . The method of  claim 32 , wherein the cancer type is a solid cancer type or a hematologic malignant cancer type. 
     
     
         34 . The method of  claim 32 , wherein the cancer type is a metastatic cancer type or a relapsed or refractory cancer type. 
     
     
         35 . The method of  claim 27 , wherein the cancer is lung cancer, colon cancer, breast cancer, or liver cancer. 
     
     
         36 . The method of  claim 28 , wherein the generating further comprises hybridizing each of the one or more biomarkers with a probe, and performing a DNA sequencing reaction to quantify the methylation of each of the one or more biomarkers. 
     
     
         37 . The method of  claim 36 , wherein the probe comprises at least 70%, 80%, 90%, 95%, or 99% sequence identity to a sequence selected from SEQ ID NOs: 1-1775. 
     
     
         38 . The method of  claim 36 , wherein the probe comprises a sequence selected from SEQ ID NOs: 1830-2321. 
     
     
         39 . The method of  claim 27 , wherein the biological samples comprise a circulating tumor DNA sample. 
     
     
         40 . The method of  claim 27 , wherein the biological samples comprise a tissue sample. 
     
     
         41 . The method of  claim 27 , wherein the individual is a human.