SNP (Single Nucleotide Polymorphism) marker and kit for auxiliary diagnosis of lung cancer

Abstract

The invention belongs to the technical field of medical biology, and particularly discloses an SNP (Single Nucleotide Polymorphism) marker for auxiliary diagnosis of lung cancer, and the SNP marker is a combination of 11-94464074, rs3730931, rs28605692, rs769418, rs368770950, rs200543348 and rs3218681. The SNP marker combination can be used for auxiliary diagnosis of the lung cancer, the diagnosis sensitivity of the lung cancer reaches 76.4%, the specificity reaches 70.8%, and the diagnosis sensitivity and the specificity are obviously higher than those of an existing lung cancer screening and diagnosis method; the diagnosis of the lung cancer is more convenient and feasible, and supports are provided for clinicians to quickly and accurately grasp the condition of a patient and timely adopt personalized prevention and treatment schemes.

Description

technical field

[0001] The invention belongs to the technical field of medicine and biology, and in particular relates to a SNP marker and a kit for auxiliary diagnosis of lung cancer. Background technique

[0002] Lung cancer is the main cause of cancer death in my country. In recent years, the incidence and mortality of lung cancer have increased significantly, and due to the diversity of lifestyle and socioeconomic development, there are currently regional and gender differences. A range of attribute risk analyzes showed that smoking, air pollution, and occupational factors were all associated with lung cancer. Behavioral interventions, such as smoking cessation and screening, can be effective in reducing lung cancer incidence and mortality.

[0003] Lung cancer is a multistep, multifactorial disease with multiple histological subtypes and is the deadliest cancer worldwide. Smoking and air pollution are two important risk factors. Other risk factors, such as occupation...

Examples

Embodiment 1

[0027] Example 1: collection of samples and arrangement of sample data

[0028] From April 2019 to December 2020, the inventor collected a large number of blood samples from newly diagnosed lung cancer patients and healthy volunteers of Han nationality from Henan Cancer Hospital. After sorting out the sample data, the inventor selected 180 samples (including 120 patients with lung cancer and 60 healthy controls) underwent whole-exon microarray detection to analyze the single nucleotide variation (single nuclear variants, SNV) of 45 key genes for DNA double-strand break repair.

[0029] Sample selection criteria are as follows:

[0030] (1) Histopathologically confirmed cases of lung cancer in the Chinese Han population, who had not received radiotherapy or chemotherapy before blood collection, and had no previous history of cancer; (2) Healthy controls from the Chinese Han population matched with the age of the cases; and systematically collected these samples Demographic and...

Embodiment 2

[0031] Example 2: Whole Exon Detection of SNP in Peripheral Blood DNA

[0032]Among the 120 eligible Chinese Han population lung cancer patients and 60 Chinese Han population healthy controls screened in Example 1 above, the two groups were age-matched. We selected 45 key genes for double-strand break repair based on literature reports, and used the next-generation sequencing platform (MGI2000 sequencer) developed by Huada BGI Company for the 45 target genes, including all exons and 5kb promoter regions of each gene. Perform sequencing. The specific steps are:

[0033] 1. DNA extraction from peripheral blood

[0034] (1) DNA extraction:

[0035] Extract sample DNA according to the instructions of the QIAGEN Genomic DNA Extraction Kit, the specific steps are as follows:

[0036] 1) Cell thawing: Take the blood sample out of the -80°C refrigerator, and place it in a -20°C low-temperature refrigerator for 24 hours, and then in a 4°C refrigerator for 24 hours;

[0037] 2) R...

Embodiment 3

[0057] Example 3: Analysis of SNP sites and the risk of lung cancer by using the risk score method

[0058] According to the above results, the inventors selected the positively associated SNPs by comparing the genotype distribution frequencies of the two groups of samples ("lung cancer group" and "healthy control group") screened in Example 1, and scanned the individual samples in the whole genome. The SNP regression coefficient was used as the weight, and the risk score was further obtained, and ROC was drawn to evaluate the sensitivity and specificity of prediction, and then the ability of these SNPs to judge the incidence of lung cancer in the Chinese Han population was evaluated.

[0059] The resulting ROC curve is drawn as figure 1 shown. Depend on figure 1 It can be seen that when the combination of the 7 SNP markers screened in Example 1 is used to diagnose and distinguish between lung cancer patients and healthy controls, these 7 SNP sites can distinguish the health...

technical field

[0001] The invention belongs to the technical field of medicine and biology, and in particular relates to a SNP marker and a kit for auxiliary diagnosis of lung cancer. Background technique

[0002] Lung cancer is the main cause of cancer death in my country. In recent years, the incidence and mortality of lung cancer have increased significantly, and due to the diversity of lifestyle and socioeconomic development, there are currently regional and gender differences. A range of attribute risk analyzes showed that smoking, air pollution, and occupational factors were all associated with lung cancer. Behavioral interventions, such as smoking cessation and screening, can be effective in reducing lung cancer incidence and mortality.

[0003] Lung cancer is a multistep, multifactorial disease with multiple histological subtypes and is the deadliest cancer worldwide. Smoking and air pollution are two important risk factors. Other risk factors, such as occupation...

Examples

Embodiment 1

[0027] Example 1: collection of samples and arrangement of sample data

[0028] From April 2019 to December 2020, the inventor collected a large number of blood samples from newly diagnosed lung cancer patients and healthy volunteers of Han nationality from Henan Cancer Hospital. After sorting out the sample data, the inventor selected 180 samples (including 120 patients with lung cancer and 60 healthy controls) underwent whole-exon microarray detection to analyze the single nucleotide variation (single nuclear variants, SNV) of 45 key genes for DNA double-strand break repair.

[0029] Sample selection criteria are as follows:

[0030] (1) Histopathologically confirmed cases of lung cancer in the Chinese Han population, who had not received radiotherapy or chemotherapy before blood collection, and had no previous history of cancer; (2) Healthy controls from the Chinese Han population matched with the age of the cases; and systematically collected these samples Demographic and...

Embodiment 2

[0031] Example 2: Whole Exon Detection of SNP in Peripheral Blood DNA

[0032]Among the 120 eligible Chinese Han population lung cancer patients and 60 Chinese Han population healthy controls screened in Example 1 above, the two groups were age-matched. We selected 45 key genes for double-strand break repair based on literature reports, and used the next-generation sequencing platform (MGI2000 sequencer) developed by Huada BGI Company for the 45 target genes, including all exons and 5kb promoter regions of each gene. Perform sequencing. The specific steps are:

[0033] 1. DNA extraction from peripheral blood

[0034] (1) DNA extraction:

[0035] Extract sample DNA according to the instructions of the QIAGEN Genomic DNA Extraction Kit, the specific steps are as follows:

[0036] 1) Cell thawing: Take the blood sample out of the -80°C refrigerator, and place it in a -20°C low-temperature refrigerator for 24 hours, and then in a 4°C refrigerator for 24 hours;

[0037] 2) R...

Embodiment 3

[0057] Example 3: Analysis of SNP sites and the risk of lung cancer by using the risk score method

[0058] According to the above results, the inventors selected the positively associated SNPs by comparing the genotype distribution frequencies of the two groups of samples ("lung cancer group" and "healthy control group") screened in Example 1, and scanned the individual samples in the whole genome. The SNP regression coefficient was used as the weight, and the risk score was further obtained, and ROC was drawn to evaluate the sensitivity and specificity of prediction, and then the ability of these SNPs to judge the incidence of lung cancer in the Chinese Han population was evaluated.

[0059] The resulting ROC curve is drawn as figure 1 shown. Depend on figure 1 It can be seen that when the combination of the 7 SNP markers screened in Example 1 is used to diagnose and distinguish between lung cancer patients and healthy controls, these 7 SNP sites can distinguish the health...

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