A pan-cancer blood diagnostic marker and its application

Abstract

The present application discloses a pan-cancer blood diagnostic marker and its application. In the first aspect of the present application, a method for classifying a sample is provided, and the classification method comprises the following steps: obtaining sequencing data of free DNA of the sample; comparing the sequencing data of the free DNA with the position of the nucleosome on the reference genome to obtain the position result of the end of the free DNA relative to the nucleosome distribution; and determining the type of the sample according to the position result. After testing, this method is applicable to many different cancers, and can more sensitively distinguish samples of cancer patients from non-cancer patients, and has low requirements for sequencing depth.

Description

Technical Field

[0001] The present application relates to the technical field of cancer diagnosis, and in particular to a pan-cancer blood diagnostic marker and its application. Background Art

[0002] Circulating cell-free DNA (cfDNA) in peripheral blood is a DNA fragment produced by natural degradation after cell death. Studies have shown that in healthy people, the main sources of cfDNA are blood cells and liver; in cancer patients, dead tumor cells also release cfDNA into the peripheral blood. There are many differences between cfDNA fragments from tumors and cfDNA fragments from non-tumor cells, such as gene mutations, chromosome copy number variations, abnormal methylation levels, and so on. Therefore, cancer diagnosis can be performed by detecting cfDNA signals from tumors in peripheral blood, that is, liquid biopsy technology. Since the collection of peripheral blood is almost non-invasive to the human body and can be sampled repeatedly, cancer diagnosis technology based on peripheral blood cfDNA has a high application value. Related studies have also identified a large number of tumor cfDNA markers and developed a large number of cancer diagnosis technologies, such as high-frequency gene mutation kits, tumor-specific methylation marker kits, and so on.

[0003] In recent years, researchers have discovered that cfDNA is not randomly fragmented when it is produced, and based on this principle, some tumor markers related to cfDNA fragmentation patterns have been discovered, and multiple cancer diagnostic technologies have been developed. For example, based on the positional distribution of the ends of cfDNA fragments on the genome, the preferred sites of specific cancer patients are identified, and these preferred end sites are used to distinguish cancer patients from the control group. However, these preferential sites require the use of complex statistical methods to identify. Moreover, since there is currently no evidence that there are pan-cancer tumor cfDNA preferential sites, it is necessary to identify the corresponding tumor cfDNA preferential sites for each type of cancer, which is costly and has poor universality. In addition, this technology has high requirements for sequencing depth. Usually only a small part of the cfDNA fragment data obtained by sequencing will cover these preferential sites, and most of them are considered useless information and are discarded because they do not cover these sites.

[0004] Therefore, it is necessary to provide a pan-cancer diagnostic marker that has low requirements for sequencing depth and can achieve high sensitivity and low cost. Summary of the invention

[0005] The present application aims to solve at least one of the technical problems existing in the prior art. To this end, the present application proposes a pan-cancer blood diagnostic marker, which can be used to complete the detection at low cost and high sensitivity, and has a low requirement for sequencing depth during the sequencing process.

[0006] In a first aspect of the present application, a method for classifying a sample is provided, the method comprising the following steps:

[0007] Obtain sequencing data of free DNA of the sample;

[0008] Compare the sequencing data of free DNA with the position of nucleosomes on the reference genome to obtain the position results of the ends of the free DNA relative to the nucleosome distribution;

[0009] Based on the location results, determine the type of sample.

[0010] The classification method according to the embodiment of the present application has at least the following beneficial effects:

[0011] Free DNA is mostly produced by chromatin degradation during apoptosis, and its fragmentation pattern is affected by the distribution of nucleosomes: Under normal circumstances (such as healthy controls or other people without cancer), the ends of free DNA tend to fall on the linker DNA between nucleosomes in cells, and fall less inside nucleosomes, which is defined here as the consistency between the ends of free DNA and the nucleosome distribution pattern is high; However, in cancer patients, the tumor-nucleosome distribution pattern is different from that of normal cells, so the consistency of the released DNA and the nucleosome distribution is low, resulting in a significant difference in the overall free DNA fragmentation pattern. In addition, compared with normal tissue, a higher proportion of the free DNA ends released by tumor tissue are inside the nucleosome, thus further reducing its consistency with the nucleosome distribution of normal tissue cells. Based on this principle, the present application quantifies the terminal position distribution of free DNA in the subject, confirms the relative position relationship between the terminal and the nucleosome distribution, and thus diagnoses cancer. After testing, this method is applicable to a variety of different cancers, can more sensitively distinguish samples of cancer patients from non-cancer patients, and has a low requirement for sequencing depth.

[0012] In some embodiments of the present application, the position results of the ends of the free DNA relative to the nucleosome distribution include: the ends of the free DNA fall into the interior of the nucleosome or are located on the connecting DNA.

[0013] In some embodiments of the present application, determining the type of the sample according to the position result includes:

[0014] When the ends of the free DNA fall into the interior of the nucleosome, the sample is determined to be a cancer sample;

[0015] When the ends of the free DNA are located on the linked DNA, the sample is determined to be a non-cancerous sample.

[0016] In some embodiments of the present application, the position results of the free DNA ends relative to the nucleosome distribution include: the proportion of the ends of several free DNAs falling inside the nucleosome, and / or the proportion of the ends of several free DNAs located on the connecting DNA.

[0017] In some embodiments of the present application, determining the type of the sample according to the position result includes:

[0018] When the proportion of the ends of the plurality of free DNAs falling into the interior of the nucleosome is greater than a first threshold, and / or when the proportion of the ends of the plurality of free DNAs located on the connecting DNA is less than a second threshold, the sample is determined to be a cancer sample;

[0019] When the proportion of the ends of a number of free DNAs falling into the interior of the nucleosome is less than or equal to a first threshold, and / or when the proportion of the ends of a number of free DNAs located on the connecting DNA is greater than or equal to a second threshold, the sample is determined to be a non-cancerous sample;

[0020] When the distance between the end of some of the free DNAs and the center of the nucleosome is greater than a third threshold, the sample is determined to be a non-cancerous sample; when the distance between the end of some of the free DNAs and the center of the nucleosome is less than or equal to the third threshold, the sample is determined to be a cancer sample.

[0021] In some embodiments of the present application, the cancer sample is a sample of at least one type of cancer selected from the group consisting of liver cancer, lung cancer, intestinal cancer, pancreatic cancer, bile duct cancer, breast cancer, and ovarian cancer.

[0022] In some embodiments of the present application, the position result is an N-index, satisfying

[0023]

[0024] Among them, N 核小体内部 N is the number of free DNAs whose ends fall into the interior of nucleosomes among a number of free DNAs; 所有 is the total number of free DNA;

[0025] Or, the position result is N′-index, satisfying

[0026]

[0027] Among them, N 连接DNA is the number of linked DNAs whose ends are located in nucleosomes in a number of free DNAs;

[0028] Or, the position result is N″-index, satisfying

[0029]

[0030] Wherein, n is the number of ends in the free DNA, a i is the distance between the ith end and the nucleosome center, b i is the weight of the ith terminal.

[0031] In some embodiments of the present application, determining the type of the sample according to the position result includes:

[0032] When the N-index is greater than the first cutoff value, the sample is determined to be a cancer sample;

[0033] When the N-index is less than or equal to the first cutoff value, the sample is determined to be a non-cancerous sample.

[0034] In some embodiments of the present application, determining the type of the sample according to the position result includes:

[0035] When the N′-index is greater than the second cutoff value, the sample is determined to be a non-cancerous sample;

[0036] When the N′-index is less than or equal to the second cutoff value, the sample is determined to be a cancer sample.

[0037] In some embodiments of the present application, determining the type of the sample according to the position result includes:

[0038] When the N″-index is greater than the third cutoff value, the sample is determined to be a non-cancerous sample;

[0039] When the N″-index is less than or equal to the third cutoff value, the sample is determined to be a cancer sample.

[0040] In some embodiments of the present application, the end of the free DNA includes at least one of an upstream end and a downstream end.

[0041] In some embodiments of the present application, the reference genome includes the entire human genome or a set interval of the entire human genome, and may also be the genome of one or more human individuals (eg, non-cancer patients).

[0042] In some embodiments of the present application, the target genomic interval includes the whole human genome or a set interval of the whole human genome.

[0043] In some embodiments of the present application, the target genomic interval is at least one of chr1, chr2, chr3, chr4, chr5, chr6, chr7, chr8, chr9, chr10, chr11, chr12, chr13, chr14, chr15, chr16, chr17, chr18, chr19, chr20, chr21, chr22, chrX, and chrY in the whole human genome.

[0044] Among them, the reference genome and the target genome interval can be the same or different, but obviously have overlapping parts.

[0045] In some embodiments of the present application, the sample is a blood sample.

[0046] In some embodiments of the present application, the cancer is a solid tumor.

[0047] In some embodiments of the present application, the cancer is selected from at least one of brain cancer, head and neck cancer, lung cancer, liver cancer, breast cancer, stomach cancer, colon cancer, rectal cancer, cervical cancer, ovarian cancer, pancreatic cancer, prostate cancer, thyroid cancer, lymphoma, and skin cancer.

[0048] In some embodiments of the present application, the position of the nucleosome on the reference genome is obtained by at least one of the following methods a) to b):

[0049] a) performing sequencing analysis on cells from non-cancer patients to determine the positions of nucleosomes of the cells on a reference genome;

[0050] b) Analyze the sequencing data of free DNA to establish a nucleosome map on the reference genome and determine the positions of nucleosomes on the reference genome.

[0051] In some embodiments of the present application, the cells from a non-cancer-affected population are optionally autologous cells.

[0052] In some embodiments of the present application, the somatic cells are selected from at least one of endothelial cells, epithelial cells, bone cells, chondrocytes, neural cells, adipocytes, fibroblasts, mesenchymal cells, hepatocytes, pancreatic islet cells, and blood cells.

[0053] In some embodiments of the present application, the cells are blood cells, and the blood cells are white blood cells.

[0054] In some embodiments of the present application, the method for sequencing and analyzing cells of non-cancer populations is selected from at least one of Mnase-seq, ChIP-seq, ATAC-seq, NOME-seq, DNase-seq, FAIRE-seq, and Cut&Tag.

[0055] In some embodiments of the present application, the method further includes obtaining at least one of the copy number variation data of the free DNA of the sample, the methylation data of the free DNA, the length distribution data of the free DNA, the terminal base distribution data of the free DNA, the terminal distribution consistency data of the free DNA, the marker data, and the image data for analysis, and combining the analysis results with the position results to determine the classification of the sample.

[0056] According to a second aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer-executable instructions, wherein the computer-executable instructions are used to enable a computer to execute any of the aforementioned classification methods.

[0057] According to a third aspect of the present application, a device is provided, which includes a processor and a memory, wherein the memory stores a computer program executable on the processor, and the processor implements the aforementioned classification method when executing the computer program.

[0058] In a fourth aspect of the present application, a system for diagnosing cancer is provided, the system comprising:

[0059] An acquisition module, which is used to acquire sequencing data of free DNA from non-cancer patients;

[0060] The comparison module is used to compare the sequencing data of the free DNA with the position of the nucleosomes on the reference genome, obtain the position results of the ends of the free DNA relative to the nucleosome distribution, and determine whether the sample is a cancer sample based on the position results.

[0061] In some embodiments of the present application, the position results of the ends of the free DNA relative to the nucleosome distribution include: the ends of the free DNA fall into the interior of the nucleosome or are located on the connecting DNA.

[0062] In some embodiments of the present application, determining whether a sample is a cancer sample according to the position result includes:

[0063] When the ends of the free DNA fall into the interior of the nucleosome, the sample is determined to be a cancer sample;

[0064] When the ends of the free DNA are located on the linked DNA, the sample is determined to be a non-cancerous sample.

[0065] In some embodiments of the present application, the position results of the free DNA ends relative to the nucleosome distribution include: the proportion of the ends of several free DNAs falling inside the nucleosome, and / or the proportion of the ends of several free DNAs located on the connecting DNA.

[0066] In some embodiments of the present application, determining whether a sample is a cancer sample according to the position result includes:

[0067] When the proportion of the ends of the plurality of free DNAs falling into the interior of the nucleosome is greater than a first threshold, and / or when the proportion of the ends of the plurality of free DNAs located on the connecting DNA is less than a second threshold, the sample is determined to be a cancer sample;

[0068] When the proportion of the ends of a number of free DNAs falling into the interior of the nucleosome is less than or equal to a first threshold, and / or when the proportion of the ends of a number of free DNAs located on the connecting DNA is greater than or equal to a second threshold, the sample is determined to be a non-cancerous sample;

[0069] When the distance between the end of some of the free DNAs and the center of the nucleosome is greater than a third threshold, the sample is determined to be a non-cancerous sample; when the distance between the end of some of the free DNAs and the center of the nucleosome is less than or equal to the third threshold, the sample is determined to be a cancer sample.

[0070] In some embodiments of the present application, the cancer sample is a sample of at least one type of cancer selected from the group consisting of liver cancer, lung cancer, intestinal cancer, pancreatic cancer, bile duct cancer, breast cancer, and ovarian cancer.

[0071] In some embodiments of the present application, the position result is an N-index, satisfying

[0072]

[0073] Among them, N 核小体内部 N is the number of free DNAs whose ends fall into the interior of nucleosomes among a number of free DNAs; 所有 is the total number of free DNA;

[0074] Or, the position result is N′-index, satisfying

[0075]

[0076] Among them, N 连接DNA is the number of linked DNAs whose ends are located in nucleosomes in a number of free DNAs;

[0077] Or, the position result is N″-index, satisfying

[0078]

[0079] Wherein, n is the number of ends in the free DNA, a i is the distance between the ith end and the nucleosome center, b i is the weight of the ith terminal.

[0080] In some embodiments of the present application, determining whether a sample is a cancer sample according to the position result includes:

[0081] When the N-index is greater than the first cutoff value, the sample is determined to be a cancer sample;

[0082] When the N-index is less than or equal to the first cutoff value, the sample is determined to be a non-cancerous sample.

[0083] In some embodiments of the present application, determining whether a sample is a cancer sample according to the position result includes:

[0084] When the N′-index is greater than the second cutoff value, the sample is determined to be a non-cancerous sample;

[0085] When the N′-index is less than or equal to the second cutoff value, the sample is determined to be a cancer sample.

[0086] In some embodiments of the present application, determining whether a sample is a cancer sample according to the position result includes:

[0087] When the N″-index is greater than the third cutoff value, the sample is determined to be a non-cancerous sample;

[0088] When the N″-index is less than or equal to the third cutoff value, the sample is determined to be a cancer sample.

[0089] In some embodiments of the present application, the end of the free DNA includes at least one of an upstream end and a downstream end.

[0090] In some embodiments of the present application, the reference genome includes the entire human genome or a set interval of the entire human genome, and may also include the genome of one or more human individuals.

[0091] In some embodiments of the present application, the target genomic interval includes the whole human genome or a set interval of the whole human genome.

[0092] In some embodiments of the present application, the target genomic interval includes at least one of chr1, chr2, chr3, chr4, chr5, chr6, chr7, chr8, chr9, chr10, chr11, chr12, chr13, chr14, chr15, chr16, chr17, chr18, chr19, chr20, chr21, chr22, chrX, and chrY in the whole human genome.

[0093] Among them, the reference genome and the target genome interval can be the same or different, but obviously have overlapping parts.

[0094] In some embodiments of the present application, the sample is a blood sample.

[0095] In some embodiments of the present application, the cancer is a solid tumor.

[0096] In some embodiments of the present application, the cancer is selected from at least one of brain cancer, head and neck cancer, lung cancer, liver cancer, breast cancer, stomach cancer, colon cancer, rectal cancer, cervical cancer, ovarian cancer, pancreatic cancer, prostate cancer, thyroid cancer, lymphoma, and skin cancer.

[0097] In some embodiments of the present application, the position of the nucleosome on the reference genome is obtained by at least one of the following methods a) to b):

[0098] a) performing sequencing analysis on cells from non-cancer patients to determine the positions of nucleosomes of the cells on a reference genome;

[0099] b) Analyze the sequencing data of free DNA to establish a nucleosome map on the reference genome and determine the positions of nucleosomes on the reference genome.

[0100] In some embodiments of the present application, the cells from a non-cancer-affected population are optionally autologous cells.

[0101] In some embodiments of the present application, the somatic cells are selected from at least one of endothelial cells, epithelial cells, bone cells, chondrocytes, neural cells, adipocytes, fibroblasts, mesenchymal cells, hepatocytes, pancreatic islet cells, and blood cells.

[0102] In some embodiments of the present application, the cells are blood cells, and the blood cells are white blood cells.

[0103] In some embodiments of the present application, the method for sequencing and analyzing cells of non-cancer populations is selected from at least one of Mnase-seq, ChIP-seq, ATAC-seq, NOME-seq, DNase-seq, FAIRE-seq, and Cut&Tag.

[0104] In some embodiments of the present application, the method further includes obtaining at least one of the copy number variation data of the free DNA of the sample, the methylation data of the free DNA, the length distribution data of the free DNA, the terminal base distribution data of the free DNA, the terminal distribution consistency data of the free DNA, the marker data, and the image data for analysis, and combining the analysis results with the position results to determine the classification of the sample.

[0105] In a fifth aspect of the present application, a pan-cancer blood diagnostic marker is provided, wherein the pan-cancer blood diagnostic marker comprises at least one of N-index, N′-index, and N″-index that characterize the consistency between the fragmentation pattern of free DNA and the nucleosome distribution of blood cells, and satisfies

[0106]

[0107] Among them, N 核小体内部 N is the number of free DNAs whose ends fall into the interior of nucleosomes among a number of free DNAs; 所有 is the total number of free DNA;

[0108]

[0109] Among them, N 连接DNA is the number of linked DNAs whose ends are located at the nucleosomes in the free DNAs;

[0110]

[0111] Wherein, n is the number of ends in the free DNA, a i is the distance between the ith end and the nucleosome center, b i is the weight of the ith terminal.

[0112] The sixth aspect of the present application provides the use of the aforementioned pan-cancer blood diagnostic marker or a product for detecting a pan-cancer blood diagnostic marker in the preparation of a cancer diagnostic product.

[0113] The classification of this application can be used for a variety of cancer types, with high universality and a wide range of application scenarios. At the same time, the diagnostic accuracy is high, especially in early-stage cancer patients, which is greatly improved compared with traditional methods. In addition, the data used in this application only requires commonly used whole genome sequencing to obtain, and there are no special requirements for experimental protocols and sequencing platforms. The operation complexity is low, the cost is low, and it is suitable for clinical promotion.

[0114] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0115] Figure 1 It is a flowchart of a sample classification method provided in an embodiment of the present application.

[0116] Figure 2 It is a schematic diagram of the principle of cancer diagnosis in the embodiments of the present application.

[0117] Figure 3 It is the comparison result (A) and ROC curve (B) of the E-index calculated for the samples of data set 1 in Example 1 of the present application.

[0118] Figure 4 It is the comparison result (A) and ROC curve (B) of the E-index calculated for the samples of data set 2 in Example 1 of the present application.

[0119] Figure 5It is the comparison result (A) and ROC curve (B) of the E-index calculated for the samples of data set 3 in Example 1 of the present application.

[0120] Figure 6 It is the comparison result (A) and ROC curve (B) of the E-index calculated for the gastric cancer samples and the control group in the data set 3 in Example 1 of the present application.

[0121] Figure 7 It is the comparison result (A) and ROC curve (B) of the E-index calculated for the samples of data set 4 in Example 1 of the present application.

[0122] Figure 8 It is the classification result of samples in Dataset 1 in Example 2 of the present application using the combined use of N-index and E-index.

[0123] Fig. 9 These are the classification results of samples in Dataset 4 in Example 2 of the present application using N-index and DNA methylation in combination (A) and N-index and E-index in combination (B). DETAILED DESCRIPTION

[0124] The following will clearly and completely describe the concept of the present application and the technical effects produced in combination with the embodiments, so as to fully understand the purpose, features and effects of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of them. Based on the embodiments of the present application, other embodiments obtained by those skilled in the art without creative work are all within the scope of protection of the present application.

[0125] The embodiments of the present application are described in detail below. The described embodiments are exemplary and are only used to explain the present application, and should not be understood as limiting the present application.

[0126] In the description of this application, "several" means more than one, "many" means more than two, "greater than", "less than", "exceed", etc. are understood to exclude the number itself, and "above", "below", "within", etc. are understood to include the number itself. If there is a description of the first and the second, it is only for the purpose of distinguishing the technical features, and it cannot be understood as indicating or implying the relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features. If a logical order is described in the flowchart, in some cases, the steps described or shown can be performed in a different order from that in the flowchart.

[0127] In the description of the present application, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples" or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0128] This application provides a sample classification method, refer to Figure 1 , the method comprises the following steps:

[0129] S110, obtaining sequencing data of free DNA of the sample.

[0130] Among them, free DNA (cfDNA) refers to DNA fragments that are free from cells, usually produced by cell apoptosis or necrosis and released outside the cells. Free DNA exists in various body fluids of organisms, including but not limited to blood, urine, feces, cerebrospinal fluid, saliva, pleural effusion, ascites, etc., so the sample in S110 can be a sample from at least one of the above sources. In some specific embodiments, the sample includes a blood sample from a specific subject, such as whole blood (such as venous whole blood, arterial whole blood, capillary whole blood), plasma, serum, peripheral blood, etc. The sequencing data of free DNA includes the sequence data obtained after sequencing the free DNA.

[0131] S120, aligning the sequencing data of the free DNA with the positions of the nucleosomes on the reference genome to obtain the position results of the ends of the free DNA relative to the nucleosome distribution. S130, determining the type of the sample based on the position results.

[0132] Wherein, nucleosome is the basic structural unit of chromatin formed by DNA and histone, and the core of each nucleosome is formed by DNA winding histone with a certain number of turns (e.g., 1.75 turns), and the nucleosome cores are connected by extended connecting DNA. Therefore, the position of nucleosome on the reference genome can at least be the position of DNA winding histone in nucleosome and / or the connecting DNA between nucleosomes on the reference genome. Therefore, the sequencing data of free DNA is compared with the position of nucleosome on the reference genome, and the position result of the terminal of free DNA relative to the nucleosome distribution finally obtained is actually the relationship reflecting the consistency of the terminal of free DNA and the distribution of nucleosome on the reference genome. In this case, if the terminal of free DNA is more consistent with the distribution of nucleosome on the reference genome, it indicates that free DNA is very likely to come from blood cells; on the contrary, if the terminal of free DNA is more different from the distribution of nucleosome on the reference genome, it indicates that free DNA is very likely to come from other types of biological cells or tissues other than blood cells.

[0133] In some specific embodiments, the position of the nucleosome on the reference genome is obtained by at least one of the following methods a) to b):

[0134] a) performing sequencing analysis on cells of non-cancer patients (or populations) to determine the positions of nucleosomes of the cells on the reference genome;

[0135] b) Analyze the sequencing data of free DNA to establish a nucleosome map on the reference genome and determine the positions of nucleosomes on the reference genome.

[0136] Among them, the cells of the non-cancer population in a) are optionally autologous cells, including but not limited to at least one of endothelial cells, epithelial cells, bone cells, chondrocytes, neural cells, adipocytes, fibroblasts, interstitial cells, hepatocytes, pancreatic islet cells, and blood cells. In some specific embodiments, the cells are blood cells, specifically white blood cells. In some specific embodiments, the method for sequencing and analyzing the cells of the non-cancer population is selected from at least one of Mnase-seq, ChIP-seq, ATAC-seq, NOME-seq, DNase-seq, FAIRE-seq, and Cut&Tag. Therefore, the method a) is actually to obtain the DNA in the tissue cells for library construction and sequencing, so as to obtain the nucleosome distribution in the normal cell tissue of the non-cancer population. And b) is to construct a nucleosome map based on the sequencing data of the obtained free DNA, and then directly determine the position of the nucleosome corresponding to the free DNA in the sample, for example, the method disclosed in Snyder et al. Cell 2016Jan14; 164(1-2): 57-68. It is understandable that obtaining the nucleosome position information on the reference genome can also be directly obtained from some existing data sets, such as an internal data set constructed through other experiments and algorithms that can reflect the nucleosome position information of blood cells of non-cancer people (or healthy people).

[0137] In some specific embodiments, comparing the sequencing data of free DNA with the position of nucleosomes on a reference genome includes: comparing the sequencing data of free DNA with the reference genome, thereby locating the free DNA on the reference genome, and obtaining the positioning site of the end of the free DNA on the reference genome; also includes obtaining the position information of the nucleosome on the reference genome; and then comparing the positioning site of the end of the free DNA on the reference genome with the position of the nucleosome on the reference genome.

[0138] In some specific embodiments, the reference genome is an optional human reference genome, including but not limited to any one of GRCh36 (hg18), GRCh37 (hg19), GRCh38 (hg38), etc. Of course, the reference genome is not limited to this, and can also be a specific interval on the human reference genome, and only a portion of the intervals of interest are compared during the comparison. In addition, the genome of one or more human individuals or a specific interval thereon can also be considered.

[0139] Therefore, in this step, the free DNA is positioned on the reference genome by comparing the sequencing data of the free DNA with the reference genome, and the relative position relationship between the end of the free DNA and the nucleosome distribution on the reference genome is obtained. It can be understood that, depending on the sequencing method, the end of the free DNA may refer to one end or both ends of the free DNA. Specifically, when single-end sequencing is used, only the position of a single end on the reference genome is selected in this step; and when double-end sequencing is used, the end of the free DNA can select any one of the upstream end and the downstream end or the position of both ends on the reference genome. The upstream end and the downstream end refer to the upstream or downstream when cfDNA is sequenced. The end and its position generally refer to the base at the end and the site corresponding to the base on the reference genome.

[0140] In some specific embodiments, the position result of the end of the free DNA relative to the nucleosome distribution refers to the end of the free DNA falling into the interior of the nucleosome or being located on the connecting DNA. In some specific embodiments, when the end of the free DNA falls into the interior of the nucleosome, the sample is a cancer sample; when the end of the free DNA is located on the connecting DNA, the sample is determined to be a non-cancerous sample. In some specific embodiments, there are multiple free DNAs in the sample, for example, more than 10, more than 100, more than 1,000, more than 10,000, more than 100,000, so the position result of the end of the free DNA relative to the nucleosome distribution includes: the proportion of the free DNA ends falling into the interior of the nucleosome, and / or, the proportion of the free DNA ends located on the connecting DNA; the distribution is reflected by the proportion of the total free DNA falling into the interior of the nucleosome or the proportion located on the connecting DNA.

[0141] In some specific embodiments, different bp conditions are set to define falling into the interior of the nucleosome according to the length of the DNA wrapped around histones on the core of the nucleosome. Under normal circumstances, the length of the DNA wrapped around histones in each nucleosome is 146bp, so the middle of the full length of this DNA fragment is used as the center position of the nucleosome, and the 73bp upstream and downstream of the center position of the nucleosome is defined as the interior of the nucleosome. Of course, it is understandable that the position range of the interior of the nucleosome is not fixed, and it can be smaller, such as within 70bp, 65bp, 60bp, 55bp, 50bp; of course, the range can also be larger, such as within 75bp, 80bp, 85bp, 90bp, 95bp, but generally not more than 100bp. In the above case, being located on the connecting DNA is just the opposite, greater than 70bp, 65bp, 60bp, 55bp, 50bp, or greater than 75bp, 80bp, 85bp, 90bp, 95bp, 100bp.

[0142] In some specific embodiments, when the proportion of free DNA whose ends fall into the interior of nucleosomes in the free DNA is greater than a first threshold, and / or when the proportion of free DNA whose ends are located on the connecting DNA is less than a second threshold, the sample is determined to be a cancer sample;

[0143] When the proportion of free DNA whose ends fall into the interior of nucleosomes in the free DNA to the total amount of free DNA is less than or equal to the first threshold, and / or when the proportion of free DNA whose ends are located on the connecting DNA to the total amount of free DNA is greater than or equal to the second threshold, the sample is determined to be a non-cancerous sample;

[0144] When the distance between the end of some free DNA and the center of the nucleosome is greater than a third threshold, the sample is determined to be a non-cancerous sample; when the distance between the end of some free DNA and the center of the nucleosome is less than or equal to the third threshold, the sample is determined to be a cancer sample.

[0145] The first threshold and the second threshold can be set according to actual needs as long as they meet the requirements of being cutoff values, for example, they can be 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, etc. The third threshold is also the same, for example, it can be 50bp, 55bp, 60bp, 65bp, 70bp, 73bp, 75bp, 80bp, 85bp, 90bp, 95bp, 100bp.

[0146] In some specific implementation manners, specific parameters are given for describing the location results.

[0147] In some implementations, this specific parameter is N-index, which satisfies

[0148]

[0149] Among them, N 核小体内部 N is the number of free DNAs whose ends fall into the interior of nucleosomes among a number of free DNAs; 所有 is the total number of free DNA. In some embodiments, when N-index is greater than the first cutoff value, the sample is a cancer sample; when N-index is less than or equal to the first cutoff value, the sample is a non-cancerous sample; the cancer sample is a sample of at least one type of cancer selected from liver cancer, lung cancer, intestinal cancer, pancreatic cancer, bile duct cancer, breast cancer, and ovarian cancer.

[0150] In some specific implementations, this specific parameter is N′-index, which satisfies

[0151]

[0152] Among them, N 连接DNA is the number of linked DNAs whose ends are located at the nucleosomes in the free DNAs. In some embodiments, when N′-index is greater than the second cutoff value, the sample is a non-cancerous sample; when N′-index is less than or equal to the third cutoff value, the sample is determined to be a cancer sample.

[0153] In some specific implementations, this specific parameter is N″-index, which satisfies

[0154]

[0155] Where n is the number of free DNA ends, a i is the distance between the ith end and the nucleosome center, b i is the weight of the ith end. In some embodiments, when N″-index is greater than a third cutoff value, the sample is a non-cancerous sample; when N″-index is less than or equal to the third cutoff value, the sample is determined to be a cancer sample.

[0156] In some embodiments, the N-index or N′-index can be further normalized. It is understood that in this step, in addition to the weighted model, a suitable statistical method can also be used to compare the results to determine the consistency of the two, thereby determining the enrichment of the ends of the cfDNA fragments in the nucleosome region.

[0157] The specific sizes of the first cutoff value and the second cutoff value are similar to the aforementioned threshold values, and can be determined based on actual needs while meeting the requirements for the cutoff values, such as 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.5, 3.0, etc. The third cutoff value is the same, for example, when calculating the weighted mean, it can be 50bp, 55bp, 60bp, 65bp, 70bp, 73bp, 75bp, 80bp, 85bp, 90bp, 95bp, 100bp, etc.

[0158] In some specific embodiments, the free DNA and nucleosomes are free DNA and nucleosomes on the target genome interval. The target genome interval can be the whole human genome, or a set interval in the whole human genome, such as a part of a chromosome, for example, any one or more of chr1-22, chrX, chrY, or one or more custom intervals in the whole human genome. It should be noted that if a set interval in the whole human genome is used, it can be achieved by at least one or more of the following methods, such as using capture or enrichment technology (such as target capture, whole exome sequencing, etc.) during sequencing before acquiring data, or only selecting DNA sequencing reads (sequencing reads) of the set interval when acquiring data. The reference genome and the target genome interval can be the same or different, but obviously the two need to have overlapping parts to complete the construction of the model, and in some cases, the reference genome covers the target genome interval.

[0159] The above-mentioned sample classification method is mainly based on the following concept: most of the free DNA is produced by chromatin degradation during cell apoptosis, and its fragmentation pattern is affected by the distribution of nucleosomes: the ends of free DNA tend to fall on the linker DNA between nucleosomes, while fewer fall inside nucleosomes. In samples from non-cancer patients, cfDNA mostly comes from blood cells, and its fragmentation pattern is highly consistent with the nucleosome distribution of blood cells; however, in patients with solid tumor cancer, tumors and paracancerous tissues do not belong to blood cells, and their nucleosome distribution patterns are different from those of blood cells. Therefore, the released DNA is less consistent with the nucleosome distribution of blood cells, resulting in a decrease in the consistency of the overall peripheral blood free DNA fragmentation pattern with the nucleosome distribution of blood cells. Therefore, the consistency of the peripheral blood free DNA fragmentation pattern with the nucleosome distribution of blood cells can be used as a potential pan-cancer diagnostic marker. Furthermore, this scheme classifies samples by quantifying the consistency of the distribution of cfDNA end positions in the subject's samples with the normal nucleosome distribution pattern, such as the proportion of free DNA ends falling inside the nucleosomes of blood cells.

[0160] It is understandable that in the sample classification method provided in the embodiment of the present application, a variety of different cancers can be distinguished. The specific type of cancer can be at least one selected from solid tumors including brain cancer, head and neck cancer, lung cancer, liver cancer, breast cancer, stomach cancer, colon cancer, rectal cancer, cervical cancer, ovarian cancer, pancreatic cancer, prostate cancer, thyroid cancer, lymphoma, and skin cancer. Among them, brain cancer includes primary brain cancer and secondary brain cancer. Primary brain cancer includes glioma and non-glioma (such as meningioma, medulloblastoma, medullary pituitary adenoma, primary CNS lymphoma and central nervous system germ cell tumor, etc.), secondary brain cancer includes malignant tumors that originate elsewhere but have spread (metastasized) to the brain, such as breast cancer and lung cancer that have metastasized to the brain; head and neck cancer includes oral / oropharyngeal cancer, nasopharyngeal cancer, nasal / sinus cancer, laryngeal cancer / hypopharynx cancer, salivary gland cancer, etc.; lung cancer includes small cell lung cancer, non-small cell lung cancer, etc.; liver cancer includes hepatocellular carcinoma, bile duct cancer, hepatoblastoma, etc.; breast cancer includes carcinoma in situ (such as lobular carcinoma in situ, ductal carcinoma in situ), invasive breast cancer (invasive lobular carcinoma, invasive ductal carcinoma), etc.; gastric cancer includes gastric adenocarcinoma, gastrointestinal stromal tumors, gastrointestinal leiomyosarcoma, gastrointestinal carcinoid, gastrointestinal lymphoma, etc.; cervical cancer includes squamous cell carcinoma and adenocarcinoma, etc.; ovarian cancer includes epithelial tumors, germ cell tumors, stromal tumors, etc.; pancreatic cancer includes pancreatic cancer, cystic tumors, acinar cell carcinoma, sarcoma, ampullary carcinoma, etc.; thyroid cancer includes papillary thyroid carcinoma, follicular thyroid carcinoma, Herxheimer cell carcinoma, etc.; lymphatic cancer includes Hodgkin lymphoma, non-Hodgkin lymphoma, etc.; skin cancer includes non-melanoma skin cancer and melanoma skin cancer, etc.

[0161] In some specific embodiments of the present application, the sample is a blood sample, and the nucleosome is a nucleosome of a blood cell. In some specific embodiments, the blood cell can be one or more types of blood cells, such as at least one of lymphocytes (such as T lymphocytes, B lymphocytes), neutrophils, eosinophils, basophils, monocytes, etc.

[0162] When sampling the technical solution required by this application, the commonly used whole genome shotgun sequencing can be used in the experimental part. The experimental operation is simple and the requirements for initial materials are not high. The diagnostic model can utilize the information of most data, the requirements for sequencing depth are not high, and it is suitable for single-end sequencing, which can further reduce the experimental cost and the diagnostic cost. In addition, it also has the following characteristics:

[0163] 1) Only free DNA sequencing data is required, and there is no need to analyze DNA modifications (such as DNA methylation). However, it can be used in combination with DNA methylation in DNA methylation sequencing data to improve accuracy.

[0164] 2) It can be used in multiple cancer types (i.e., pan-cancer diagnosis can be achieved).

[0165] 3) There are no specific requirements for the chemical reagents and sequencing platforms used in the experiment (strong versatility).

[0166] In addition, it should be noted that in some embodiments, the classification method provided in this application can only exclude some samples as "non-cancerous", but cannot determine the type of cancer. Cancer diagnosis and tumor tracing belong to two different categories and are applicable to different objects. A pan-cancer classification method provided in the embodiments of this application is particularly suitable for people participating in routine physical examinations, and early cancer patients are screened out through cfDNA analysis. After completing the classification provided in this application, it may be necessary to further trace the tumor to determine the specific type of cancer.

[0167] To this end, the classification method may further include a step of confirming the source of the cancer to further classify the sample to complete the tracing of the cancer, or combine this classification method with other classification methods to further improve the accuracy of cancer diagnosis. Specifically, it can be analyzed in combination with other data of free DNA or analyzed in combination with other types of data of the subject. Other data of free DNA include but are not limited to copy number variation data of free DNA, methylation data of free DNA, length distribution data of free DNA, terminal base distribution data of free DNA, and consistency data of terminal distribution of free DNA, etc. Other types of data of the subject may be marker data, imaging data, etc., and analyzed by a model, and the classification of the sample is determined by combining the analysis results with the comparison results. In some specific embodiments, the consistency data of the terminal distribution of free DNA refers to the consistency of the number of times the different sites of the target genomic interval appear as the end of the free DNA of the sample and the number of times the end of the free DNA of the non-cancer population appears. If the consistency is high, the risk of cancer is low; if the consistency is low, there is a greater risk of cancer. For example, it can calculate the consistency of the terminal distribution of free DNA by the consistency E-index:

[0168]

[0169] Where n is the number of sites that appear in the terminal distribution model, x i is the frequency of site i in the terminal distribution model, y i is the frequency of site i at the end of the free DNA of the sample; N 样本 is the total number of cfDNA in the sample; for details, please refer to the prior application 202210496595.9.

[0170] It is understandable that when multiple methods are combined to trace the origin of cancer or improve the accuracy of diagnosis, the combination does not have to completely follow the classification rules under a single method, and a unique rule can also be formed after the combination. It is necessary to specifically judge according to the method used in the actual combination, which will not be repeated here. The classification of the sample can be to classify the subject to which the sample belongs into a cancer population or a non-cancer population, and further can be to classify it into a population with a certain specific cancer, or a population with cancer metastasis, such as lung cancer liver metastasis, etc. Among them, the marker refers to a small molecule (such as amino acids, choline, etc. as metabolic markers), nucleic acid (such as miRNA, mRNA, lncRNA, etc.), protein, flora, etc. associated with one or several specific cancer types. It is understandable that in the embodiments of the present application, the marker data is data of other types of markers that are not related to the copy number variation, methylation, length distribution, terminal base distribution, and terminal distribution of the above-mentioned free DNA, or other quantitative methods of free DNA as markers.

[0171] The present application also provides a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the aforementioned classification method.

[0172] The present application also provides a device, which includes a processor and a memory, wherein the memory stores a computer program that can be executed on the processor, and the processor implements the aforementioned classification method when executing the computer program.

[0173] The memory is a non-transitory computer-readable storage medium that can be used to store non-transitory software programs and non-transitory computer executable programs, such as the aforementioned classification method described in the embodiments of the present application. The processor implements sample classification by running the non-transitory software programs and instructions stored in the memory.

[0174] The memory may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required for at least one function; and the data storage area may store and execute the above-mentioned programs. In addition, the memory may include a high-speed random access memory and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage devices.

[0175] In some embodiments of the present application, the memory may include a memory remotely disposed relative to the processor, and the remote memory may be connected to the processor via a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0176] The non-transitory software program and instructions required to implement the above evaluation are stored in the memory, and when executed by one or more processors, the classification of the above samples is performed.

[0177] The present application also provides a system for diagnosing cancer, the system for diagnosing cancer comprising:

[0178] An acquisition module, which is used to acquire sequencing data of free DNA of a sample;

[0179] The comparison module is used to compare the sequencing data of the free DNA with the position of the nucleosomes on the reference genome, obtain the position results of the ends of the free DNA relative to the nucleosome distribution, and determine whether the sample is a cancer sample based on the position results.

[0180] The specific implementation of the comparison module may refer to the corresponding steps in the aforementioned classification method.

[0181] It is understandable that the system for diagnosing cancer may also include other related modules, or the corresponding acquisition module and comparison module may have multiple functions.

[0182] The above described device or system implementation is only illustrative, and the modules described as separate components may or may not be physically separated, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0183] It is understood that all or some of the steps disclosed above, etc. can be implemented as software, firmware, hardware and appropriate combinations thereof. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, and the computer-readable medium can include a computer storage medium (or a non-transitory medium) and a communication medium (or a temporary medium). It is understood that computer storage media include volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer.

[0184] Additionally, it will be appreciated that communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0185] The present application also provides a pan-cancer blood diagnostic marker, which includes at least one of N-index and N′-index that characterize the consistency between the fragmentation pattern of free DNA and the nucleosome distribution of blood cells, and satisfies

[0186]

[0187] Among them, N 核小体内部 N is the number of free DNAs whose ends fall into the interior of nucleosomes among a number of free DNAs; 所有 is the total number of free DNA;

[0188]

[0189] Among them, N 连接DNA is the number of linked DNAs whose ends are located in nucleosomes in a number of free DNAs;

[0190]

[0191] Where n is the number of free DNA ends, a i is the distance between the ith end and the nucleosome center, b i is the weight of the ith terminal.

[0192] The present application also provides the use of the aforementioned pan-cancer blood diagnostic markers or products for detecting pan-cancer blood diagnostic markers in the preparation of cancer diagnostic products.

[0193] The classification method of the present application is described below in conjunction with specific embodiments.

[0194] Example 1

[0195] 1. Sample source

[0196] 24 volunteers were recruited from the hospital's physical examination population. The physical examination results confirmed that there were no cancer patients. All volunteers signed informed consent forms and underwent ethical review before sample collection.

[0197] 2. Collection and Processing of Peripheral Blood

[0198] Use a blood collection tube containing an anticoagulant (EDTA) to collect peripheral blood (6 ml) from the vein, centrifuge it at 4°C and 1600×g for 15 minutes, aspirate the upper liquid and transfer it to a new centrifuge tube, centrifuge it again at 4°C and 16000×g for 15 minutes, then aspirate the upper liquid (i.e., plasma), transfer it to a freezing tube, and store it in a -80°C refrigerator.

[0199] 3. Extraction and sequencing of cfDNA

[0200] Commercial kits and equipment are used to extract cfDNA from plasma, construct sequencing libraries, and perform high-throughput sequencing (double-end). The sequencing raw data is stripped of sequencing adapters and low-quality cycles, and repetitive sequences, and then aligned to the human genome, removing repetitive sequences and low-quality alignment results to obtain the final alignment results. The positions of both ends of each cfDNA on the genome are extracted, which is the terminal site information of the cfDNA.

[0201] 4. Obtaining blood cell nucleosome distribution data

[0202] In this example, the Mnase-seq experimental data of the GM12878 cell line was used. After obtaining the blood cell nucleosome distribution data, we defined the 73 bp upstream and downstream of the nucleosome center as the nucleosome protection region.

[0203] 5. Calculation method of consistency between cfDNA ends and nucleosome distribution (N-index)

[0204] For each sample to be tested, analyze the number of fragment ends N that fall within the nucleosome protection interval defined in the previous step in the target genomic interval. 核小体内部 , and the number of all cfDNA fragment ends in this interval N 所有 , dividing the two gives the N-index value defined here.

[0205]

[0206] The target genomic region studied here can be the whole genome, or it can be a partial chromosome interval that is manually screened, and similar effects can be achieved. For double-end sequencing data, there can be multiple calculation methods, such as only one end in the nucleosome can be calculated as 1 or 0, and both ends in the nucleosome can be calculated as 1 or 2, but the calculation method should remain fixed in the data set so that the quantitative results (i.e., N-index) can be compared between samples.

[0207] refer to Figure 2As shown in A, there are 6 cfDNAs in the target genomic interval, and there are two nucleosomes. If double-end sequencing is used, there are 12 ends, of which 6 ends fall into the nucleosome protection region; therefore, N 核小体内部 is 6, N 所有 is 12, N-index=6 / 12=1 / 2.

[0208] 6. Cancer diagnosis methods

[0209] First, determine the cancer diagnostic parameters. Construct a set of non-cancer photo samples and a set of cancer patients (can be a single cancer type or multiple cancer types), and calculate the N-index value of each sample cfDNA. Since cancer patients have cfDNA from tumors, overall, the N-index value of cancer patients should be higher than that of non-cancer patients, so a cutoff value can be used to distinguish (i.e., diagnostic parameters) to achieve cancer diagnosis.

[0210] The receiver operating characteristic curve (ROC) can be used to evaluate the accuracy, sensitivity, and specificity of cancer diagnosis using different cutoff values; the AUC (Area Under the Curve) value can be used to evaluate the overall effect of the diagnostic method: the higher the AUC (maximum 1), the better the effect. Finally, the cutoff value is determined according to actual needs. For example, community screening may require specificity > 99%, while high-risk populations may require sensitivity > 95%.

[0211] After determining the cutoff value, for each patient to be tested, the N-index value of the cfDNA is calculated. If it is higher than the cutoff value, the patient is a cancer patient, otherwise it is a non-cancer patient. The N-index value can also be used as a feature value and combined with other information (such as imaging data, cfDNA methylation level, length distribution, etc.) for cancer diagnosis.

[0212] refer to Figure 2 B. When the sample size is sufficient, the difference in the N-index value between the cancer group and the control group has a certain statistical significance. In this case, a specific diagnostic parameter is used as a cutoff value as the distinction between the two groups of samples, and an appropriate cutoff value can be selected according to different specificity, sensitivity and other requirements.

[0213] The samples were classified using data sets from different sources, and the results are as follows:

[0214] (1) Dataset 1 contains sample data of 10 non-cancer patients (control group), 10 liver cancer patients, and 10 lung cancer patients (Dataset 1 source reference Liang et al. Whole-genome sequencing of cell-free DNA yields genome-wide read distribution patterns to track tissue of origin incancer patients. Clin Transl Med. 2020 Oct; 10(6): e177.).

[0215] According to the N-index calculation method provided above, the N-index values ​​of these people are calculated, and the results are as follows Figure 3 As shown in A, the N-index of the two groups of cancer patients is higher than that of non-cancer patients. Figure 3 B. ROC analysis showed that N-index can effectively distinguish cancer patients from non-cancer patients, with an AUC value of 0.82 in liver cancer patients and 0.84 in lung cancer patients, and P values ​​were less than 0.05. When the specificity requirement was 0.8, the sensitivity was 0.8 (lung cancer) and 0.7 (lung cancer), respectively.

[0216] (2) Dataset 2 contains sample data of 4 non-cancer patients, 4 brain tumor patients, 4 colorectal cancer patients, 4 gastric cancer patients, 3 liver cancer patients, 15 lung cancer patients, and 7 pancreatic cancer patients (dataset source reference Song et al. 5-Hydroxymethylcytosine signatures in cell-free DNA provide information about tumor types and stages. Cell Res. 2017 Oct; 27(10): 1231-1242., selected from some cancer samples).

[0217] According to the N-index calculation method provided above, the N-index values ​​of these people are calculated, and the results are as follows Figure 4 As shown in A, among these cancer patients, except for gastric cancer patients, the N-index is higher than that of non-cancer patients. Figure 4B analyzed patients with pancreatic cancer, lung cancer, and combined liver cancer or colorectal cancer (a total of 7 patients). The results showed that when using N-index for cancer diagnosis, the AUCs were 1.0 (liver cancer or colorectal cancer), 0.86 (lung cancer), and 0.97 (pancreatic cancer), and the P values ​​were all less than 0.05; when the specificity requirement was 0.8, the sensitivities were 1.0 (liver cancer or colorectal cancer), 0.86 (lung cancer), and 1.0 (pancreatic cancer).

[0218] (3) Dataset 3 contains sample data of 231 people without cancer, 26 patients with bile duct cancer, 54 patients with breast cancer, 27 patients with colorectal cancer, 27 patients with gastric cancer, 35 patients with pancreatic cancer, 79 patients with lung cancer, and 28 patients with ovarian cancer (the source of the data set is Cristiano et al. Genome-wide cell-free DNA fragmentation in patients with cancer. Nature 2019; 570:(385–389)., and some cancer samples are selected).

[0219] According to the N-index calculation method provided above, the N-index values ​​of these people are calculated, and the results are as follows Figure 5 As shown in A, among these cancer patients, except for ovarian cancer and colorectal cancer, the N-index of other groups is higher than that of the control group of non-cancer patients. The ROC analysis results are shown in Figure 5 B, indicating that the AUC values ​​of N-index for cancer diagnosis in these cancer types are between 0.61 and 0.82, and the P values ​​are all less than 0.05.

[0220] refer to Figure 6 A and B, which are different from the performance of other cancer types, have a downregulation of N-index in gastric cancer patients, which is consistent with the Song dataset. ROC analysis shows that the AUC value is 0.713 and the P value is less than 0.05.

[0221] (4) Dataset 4 contains sample data from 37 people without cancer and 8 patients with liver cancer (dataset source reference Zhang, et al. Hypomethylation in HBV integration regions aids non-invasive surveillance to hepatocellular carcinoma by low-pass genome-wide bisulfite sequencing. BMC Medicine 2020, Aug3; 18(1): 200.).

[0222] According to the N-index calculation method provided above, the N-index values ​​of these people are calculated, and the results are as follows Figure 7 As shown in A, N-index is higher in the liver cancer group than in non-cancer patients. The ROC analysis results are shown in Figure 7 As shown in Figure B, N-index can effectively distinguish liver cancer patients from non-cancer patients, with an AUC value of 0.80 and P values ​​less than 0.05.

[0223] Combined with the above results, it can be seen that the cancer markers provided in the examples of the present application do not require modeling and can be used on data sets from different sources, showing good universality.

[0224] It should also be pointed out that the blood cell nucleosome distribution data in Example 1 uses the Mnase-seq experimental data of the GM12878 cell line, which, as a B lymphocyte cell line, relies on the nucleosome distribution of white blood cells and can only roughly simulate the true source of free DNA in human plasma as a whole.

[0225] Example 2

[0226] This example combines N-index and E-index with DNA methylation data by cutoff value for classification. In terms of performance indicators, the most clinically meaningful indicators are used, namely, sensitivity at 100% specificity (for large-scale screening of asymptomatic patients) or specificity at 100% sensitivity (for accurate diagnosis of symptomatic patients).

[0227] Among them, the method steps of sampling E-index to classify samples are as follows:

[0228] 1. Building a cancer diagnosis model

[0229] 1. Sample source

[0230] Volunteers were recruited from the physical examination population in the hospital. The physical examination results confirmed that there were no cancer patients. All volunteers signed informed consent forms and underwent ethical review before sample collection.

[0231] 2. Collection and Processing of Peripheral Blood

[0232] Use a blood collection tube containing an anticoagulant (EDTA) to collect peripheral blood (6 ml) from the vein, use a centrifuge to centrifuge at 4°C, 1600×g for 15 minutes, aspirate the upper liquid and transfer it to a new centrifuge tube, use a centrifuge to centrifuge again at 4°C, 16000×g for 15 minutes, then aspirate the upper liquid (i.e., plasma), transfer it to a cryopreservation tube, and store it in a -80°C refrigerator.

[0233] 3. Extraction and sequencing of cfDNA

[0234] Commercial kits and equipment are used to extract cfDNA from plasma, construct sequencing libraries, and perform high-throughput sequencing (double-end). The sequencing raw data is stripped of sequencing adapters and low-quality cycles, and repetitive sequences, and then aligned to the human genome, removing repetitive sequences and low-quality alignment results to obtain the final alignment results. The positions of both ends of each cfDNA on the genome are extracted, which is the terminal site information of the cfDNA. Reference Figure 3 , count the number of cfDNA ends located at each site on the reference genome, obtain a statistical table of the number of cfDNA ends for each site in the genome, and construct a site-frequency end distribution model.

[0235] 2. Sample Classification

[0236] 1. Calculation of cfDNA end distribution consistency (E-index)

[0237] For each sample to be tested, the cfDNA end information was extracted according to the method in building a cancer diagnosis model, and the total number of cfDNA fragments in the comparison results (N 样本 ).

[0238] For all sites in the genome, the number of times they are cfDNA ends in the terminal distribution model is used as the weight, and the number of times they are cfDNA ends in the sample to be tested is weighted; then N 样本 The weighted value is normalized as the E-index that characterizes the consistency between the cfDNA terminal distribution of the sample to be tested and the non-cancer population, referring to the following formula:

[0239]

[0240] Where n is the number of sites that appear in the terminal distribution model, x i is the frequency of site i in the terminal distribution model, y i is the frequency of site i at the end of the free DNA of the sample; N 样本 is the total number of cfDNA in the sample.

[0241] The determination of the subsequent cutoff value and the classification of samples refer to Example 1.

[0242] For the method of classifying samples based on DNA methylation data, refer to Chan et al. PNAS 2013 Nov 19; 110(47): 18761-8.

[0243] refer to Figure 8In the liver cancer samples of dataset 1, when N-index is used alone for cancer prediction, the sensitivity is 100% and the specificity is 40%. When N-index is combined with E-index, the sensitivity is 100% and the specificity is increased to 50%.

[0244] refer to Figure 7 In data set 4, N-index, E-index and DNA methylation can effectively distinguish liver cancer patients from non-cancer patients. When N-index is used alone to predict cancer, the sensitivity is 37.5% when the specificity is 100%. Fig. 9 A, when N-index is combined with DNA methylation, when the specificity is 100%, the sensitivity is increased to 75%; when N-index is used alone for cancer prediction, when the sensitivity is 100%, the specificity is 21.62%; Fig. 9 B. When N-index is combined with E-index, the specificity is improved to 91.89% when the sensitivity is 100%.

[0245] Example 3

[0246] This embodiment provides a system for diagnosing cancer, the system comprising:

[0247] An acquisition module is used to obtain sequencing data of free DNA of a sample;

[0248] The comparison module compares the sequencing data of free DNA with the position of nucleosomes on the reference genome to obtain the position results of the ends of the free DNA relative to the nucleosome distribution, and determines whether the sample is a cancer sample based on the position results.

[0249] At the same time, in the comparison module, the N″-index is used for calculation and comparison:

[0250]

[0251] Where n is the number of free DNA ends, a i is the distance between the ith end and the nucleosome center, b i is the weight of the ith end. At the same time, different distances from the nucleosome center are given different weights.

[0252] The system for diagnosing cancer can achieve similar effects of diagnosing cancer in different data sets as in Example 1, and will not be described in detail here.

[0253] Example 4

[0254] This embodiment provides a system for diagnosing cancer. The difference between this system and Embodiment 3 when used is that the positions of nucleosomes are sequenced and analyzed using whole blood samples of healthy people to determine the positions of nucleosomes on the reference genome.

[0255] The system for diagnosing cancer can achieve similar effects of diagnosing cancer in different data sets as in Example 1, and will not be described in detail here.

[0256] Example 5

[0257] This embodiment provides a system for diagnosing cancer. The difference between this system and Embodiment 3 when used is that epithelial tissues of healthy people are used for sequencing analysis when aligning the positions of nucleosomes to determine the positions of nucleosomes in epithelial cells on the reference genome.

[0258] The system for diagnosing cancer can achieve similar effects of diagnosing cancer in different data sets as in Example 1, and will not be described in detail here.

[0259] It can be seen from the above embodiments that the classification method and diagnostic markers provided in this application can be used for a variety of cancer types, with high universality and a wide range of application scenarios. At the same time, the diagnostic accuracy of the above method is relatively high, especially in early cancer patients compared with traditional methods. In addition, the data used to implement the above scheme only need to be obtained by commonly used whole genome sequencing, and there are no special requirements for experimental schemes and sequencing platforms. The operation complexity is low and the cost is low, which is suitable for clinical promotion.

[0260] The present application is described in detail above in conjunction with the embodiments, but the present application is not limited to the above embodiments, and various changes can be made within the knowledge of ordinary technicians in the relevant technical field without departing from the purpose of the present application. In addition, the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

Claims

1. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute a sample classification method; The sample classification method includes the following steps: Obtaining sequencing data of free DNA of the sample; Comparing the sequencing data of the free DNA with the positions of nucleosomes on the reference genome to obtain the position results of the ends of the free DNA relative to the nucleosome distribution; Determine the type of the sample according to the position result; Wherein, the position of nucleosomes on the reference genome is the nucleosome distribution of blood cells on the reference genome, and the blood cells are white blood cells; The position result is N-index, satisfying , N 核小体内部 is the number of free DNAs whose ends fall into the interior of the nucleosome among the free DNAs, N 所有 is the total number of free DNA; or, the position result is N′-index, satisfying , N 核小体内部 is the number of free DNAs whose ends fall into the interior of the nucleosome among the free DNAs, N 连接DNA is the number of connected DNAs whose ends are located in the nucleosomes in the free DNAs; the inside of the nucleosome is within 73 bp upstream and downstream of the center of the nucleosome; Determining the type of the sample according to the position result includes: When the proportion of the ends of the free DNAs falling into the interior of the nucleosome is greater than a first threshold, and / or when the proportion of the ends of the free DNAs located on the connecting DNA is less than a second threshold, the sample is determined to be a cancer sample; When the proportion of the ends of a number of the free DNAs falling into the interior of the nucleosome is less than or equal to a first threshold, and / or when the proportion of the ends of a number of the free DNAs located on the connecting DNA is greater than or equal to a second threshold, the sample is determined to be a non-cancerous sample.

2. The computer-readable storage medium according to claim 1, wherein: The end of the free DNA includes at least one of an upstream end and a downstream end.

3. The computer-readable storage medium according to claim 1, wherein: The reference genome includes the entire human genome or a set interval of the entire human genome.

4. The computer-readable storage medium according to claim 1, wherein: The sample is a blood sample.

5. The computer-readable storage medium according to claim 1, wherein: The cancer is a solid tumor.

6. The computer-readable storage medium according to claim 1, wherein: Determining the type of the sample according to the position result includes: When the N-index is greater than the first cutoff value, the sample is determined to be a cancer sample; When the N-index is less than or equal to the first cutoff value, the sample is determined to be a non-cancerous sample.

7. The computer-readable storage medium according to claim 1, wherein: Determining the type of the sample according to the position result includes: When the N′-index is greater than the second cutoff value, the sample is determined to be a non-cancerous sample; When the N′-index is less than or equal to the second cutoff value, the sample is determined to be a cancer sample.

8. The computer-readable storage medium according to any one of claims 1 to 7, characterized in that: It also includes obtaining at least one of the copy number variation data of the sample's free DNA, methylation data of the free DNA, length distribution data of the free DNA, terminal base distribution data of the free DNA, terminal distribution consistency data of the free DNA, marker data, and image data for analysis, and combining the analysis results with the position results to determine the classification of the sample.

9. The device, characterized in that The method comprises a processor and a memory, wherein the memory stores a computer program that can be run on the processor, and the processor implements a sample classification method when running the computer program; The sample classification method includes the following steps: Obtaining sequencing data of free DNA of the sample; Comparing the sequencing data of the free DNA with the positions of nucleosomes on the reference genome to obtain the position results of the ends of the free DNA relative to the nucleosome distribution; Determine the type of the sample according to the position result; Wherein, the position of nucleosomes on the reference genome is the nucleosome distribution of blood cells on the reference genome, and the blood cells are white blood cells; The position result is N-index, satisfying , N 核小体内部 is the number of free DNAs whose ends fall into the interior of the nucleosome among the free DNAs, N 所有 is the total number of free DNA; or, the position result is N′-index, satisfying , N 核小体内部 is the number of free DNAs whose ends fall into the interior of the nucleosome among the free DNAs, N 连接DNA is the number of connected DNAs whose ends are located in the nucleosomes in the free DNAs; the inside of the nucleosome is within 73 bp upstream and downstream of the center of the nucleosome; The step of determining the type of the sample according to the position result includes: When the proportion of the ends of the free DNAs falling into the interior of the nucleosome is greater than a first threshold, and / or when the proportion of the ends of the free DNAs located on the connecting DNA is less than a second threshold, the sample is determined to be a cancer sample; When the proportion of the ends of a number of the free DNAs falling into the interior of the nucleosome is less than or equal to a first threshold, and / or when the proportion of the ends of a number of the free DNAs located on the connecting DNA is greater than or equal to a second threshold, the sample is determined to be a non-cancerous sample.

10. The device according to claim 9, characterized in that The end of the free DNA includes at least one of an upstream end and a downstream end.

11. The device according to claim 9, characterized in that The reference genome includes the entire human genome or a set interval of the entire human genome.

12. The device according to claim 9, characterized in that The sample is a blood sample.

13. The device according to claim 9, characterized in that The cancer is a solid tumor.

14. The device according to claim 9, characterized in that Determining the type of the sample according to the position result includes: When the N-index is greater than the first cutoff value, the sample is determined to be a cancer sample; When the N-index is less than or equal to the first cutoff value, the sample is determined to be a non-cancerous sample.

15. The device according to claim 9, characterized in that Determining the type of the sample according to the position result includes: When the N′-index is greater than the second cutoff value, the sample is determined to be a non-cancerous sample; When the N′-index is less than or equal to the second cutoff value, the sample is determined to be a cancer sample.

16. The device according to any one of claims 9 to 15, characterized in that It also includes obtaining at least one of the copy number variation data of the sample's free DNA, methylation data of the free DNA, length distribution data of the free DNA, terminal base distribution data of the free DNA, terminal distribution consistency data of the free DNA, marker data, and image data for analysis, and combining the analysis results with the position results to determine the classification of the sample.

17. A system for diagnosing cancer, characterized in that The system comprises: An acquisition module, which is used to acquire sequencing data of free DNA of a sample; A comparison module, wherein the comparison module is used to compare the sequencing data of the free DNA with the positions of nucleosomes on the reference genome to obtain the position results of the ends of the free DNA relative to the nucleosome distribution; and determine whether the sample is a cancer sample based on the position results; Wherein, the position of nucleosomes on the reference genome is the nucleosome distribution of blood cells on the reference genome, and the blood cells are white blood cells; The position result is N-index, satisfying , N 核小体内部 is the number of free DNAs whose ends fall into the interior of the nucleosome among the free DNAs, N 所有 is the total number of free DNA; or, the position result is N′-index, satisfying , N 核小体内部 is the number of free DNAs whose ends fall into the interior of the nucleosome among the free DNAs, N 连接DNA is the number of connected DNAs whose ends are located in the nucleosomes in the free DNAs; the inside of the nucleosome is within 73 bp upstream and downstream of the center of the nucleosome; Determining whether the sample is a cancer sample according to the position result includes: When the proportion of the ends of the free DNAs falling into the interior of the nucleosome is greater than a first threshold, and / or when the proportion of the ends of the free DNAs located on the connecting DNA is less than a second threshold, the sample is determined to be a cancer sample; When the proportion of the ends of a number of the free DNAs falling into the interior of the nucleosome is less than or equal to a first threshold, and / or when the proportion of the ends of a number of the free DNAs located on the connecting DNA is greater than or equal to a second threshold, the sample is determined to be a non-cancerous sample.

18. The system according to claim 17, characterized in that The end of the free DNA includes at least one of an upstream end and a downstream end.

19. The system according to claim 17, characterized in that The reference genome includes the entire human genome or a set interval of the entire human genome.

20. The system according to claim 17, characterized in that The sample is a blood sample.

21. The system according to claim 17, characterized in that The cancer is a solid tumor.

22. The system according to claim 17, characterized in that Determining the type of the sample according to the position result includes: When the N-index is greater than the first cutoff value, the sample is determined to be a cancer sample; When the N-index is less than or equal to the first cutoff value, the sample is determined to be a non-cancerous sample.

23. The system according to claim 17, characterized in that Determining the type of the sample according to the position result includes: When the N′-index is greater than the second cutoff value, the sample is determined to be a non-cancerous sample; When the N′-index is less than or equal to the second cutoff value, the sample is determined to be a cancer sample.

24. The system according to any one of claims 17 to 23, characterized in that It also includes obtaining at least one of the copy number variation data of the sample's free DNA, methylation data of the free DNA, length distribution data of the free DNA, terminal base distribution data of the free DNA, terminal distribution consistency data of the free DNA, marker data, and image data for analysis, and combining the analysis results with the position results to determine the classification of the sample.

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