Use of CYP1b1 gene SNP site in prognosis prediction of lung cancer

Abstract

The present invention relates to use of a CYP1B1 gene SNP site in the prognosis prediction of lung cancer, and belongs to the technical field of biomedicine. Provided is a biomarker for evaluating the prognosis of a lung cancer patient. The biomarker is a CYP1B1 gene rs9341266 site polymorphism. Among lung cancer patients, those with G > A at the CYP1B1 gene rs9341266 site have a poor prognosis. Provided is use of a marker in the preparation of a detection reagent for evaluating the prognosis of a lung cancer patient. Provided are a genotyping detection reagent, diagnostic kit, and prognosis detection system for evaluating the prognosis of a lung cancer patient. Predicting the prognosis of lung cancer patients, especially smokers, the elderly, patients with stage III + IV lung cancer, and patients having a family history of malignant tumors and / or an SCLC subtype among lung cancer patients, and formulating a treatment strategy and an intervention measure based on these predictions are of great significance for prolonging the survival time of patients.

Description

Application of CYP1B1 gene SNP sites in lung cancer prognosis prediction Technical Field

[0001] This invention relates to the application of CYP1B1 gene SNP sites in lung cancer prognosis prediction, and belongs to the field of biomedical technology. Background Technology

[0002] According to statistics released by the National Cancer Center of China in 2022, the predicted number of new cases and deaths from lung cancer was 870,982 and 766,898, respectively. Despite significant advancements in early diagnosis and new treatment options for lung cancer in recent years, the average 5-year survival rates for non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) in the United States are only 28% and 7%, respectively. Therefore, reliably predicting lung cancer prognosis remains challenging in this field, and establishing an accurate prognostic indicator to effectively improve the treatment and survival rates of lung cancer patients is imperative. Among the causes of poor prognosis in lung cancer patients, the TNM staging system is widely used, especially for advanced lung cancer (stage III or IV). In addition, several other factors significantly reduce survival rates, including advanced age, male sex, smoking history, and small cell lung cancer.

[0003] The most significant risk factor for lung cancer development is tobacco smoke, which is statistically significantly associated with lung cancer risk. Smokers are 20 times more likely to be diagnosed with lung cancer than non-smokers. Data shows that those who quit smoking after a lung cancer diagnosis have a lower risk of developing secondary cancers and a better prognosis. However, some people without the aforementioned risk factors also develop lung cancer, indicating that lung cancer is not a self-inflicted disease, and genetic influences are almost negligible in prognosis. The cytochrome P4501B1 (CYP1B1) gene is located on chromosome 2, consisting of 3 exons and 2 introns, encoding an enzyme protein composed of 543 amino acids. The CYP1B1 gene spans a region on Chr2p22-p21. Approximately 180 single nucleotide polymorphisms (SNPs) of the CYP1B1 gene have been reported in the dbSNP database. This gene is involved not only in the proliferation and development of normal cells but also in the progression and migration of tumor cells. This invention aims to explore the application of CYP1B1 gene SNP sites in predicting the prognosis of lung cancer. Summary of the Invention

[0004] The purpose of this invention is to solve the technical problem of the application of CYP1B1 gene SNP sites in lung cancer prognosis prediction.

[0005] To achieve the objectives of this invention, this invention provides a biomarker for assessing the prognosis of lung cancer patients, wherein the biomarker is the CYP1B1 gene rs9341266 site polymorphism; lung cancer patients with G>A at the CYP1B1 gene rs9341266 site have a poor prognosis.

[0006] This invention provides the application of the CYP1B1 gene rs9341266 site polymorphism as a prognostic biomarker for lung cancer patients, wherein lung cancer patients with G>A at the CYP1B1 gene rs9341266 site have a poor prognosis.

[0007] This invention provides the application of the CYP1B1 gene rs9341266 site polymorphism in the preparation of a diagnostic kit for assessing the prognosis of lung cancer patients, wherein lung cancer patients with G>A at the CYP1B1 gene rs9341266 site have a poor prognosis.

[0008] Preferably, the lung cancer patient is a smoker, an elderly person, a patient with stage III+IV lung cancer, a patient with a family history of malignant tumors, and / or a patient with SCLC (small cell lung cancer) subtype.

[0009] This invention provides the application of a biomarker in the preparation of a diagnostic reagent for assessing the prognosis of lung cancer patients. The biomarker is the genotype of the CYP1B1 gene rs9341266 locus. Lung cancer patients with G>A at the CYP1B1 gene rs9341266 locus have a poor prognosis.

[0010] This invention provides a genotyping test reagent for assessing the prognosis of lung cancer patients. The genotyping test reagent is used to perform genotyping on lung cancer patients. The genotyping test detects the genotype at the rs9341266 locus of the CYP1B1 gene. Lung cancer patients with G>A at the rs9341266 locus of the CYP1B1 gene have a poor prognosis.

[0011] This invention provides the application of a genotyping detection reagent in the preparation of a diagnostic kit for predicting the prognosis and survival status of lung cancer patients. The genotyping detection reagent is used to perform genotyping detection on lung cancer patients. The genotyping detection is to detect the genotype of the CYP1B1 gene rs9341266 locus in lung cancer patients. Lung cancer patients with G>A at the CYP1B1 gene rs9341266 locus have a poor prognosis.

[0012] This invention provides a prognostic detection system for lung cancer patients, including detecting the genotype of the CYP1B1 gene rs9341266 locus in lung cancer patients; lung cancer patients with G>A at the CYP1B1 gene rs9341266 locus have a poor prognosis.

[0013] Preferably, the system includes a data processing device and a substance for detecting biomarkers; the data processing device includes a data input module, a data recording module, a data comparison module, and a conclusion output module; the data input module is configured to input the category value of the biomarker of the sample to be tested; the data recording module is configured to store the category value of the biomarker of the sample to be tested and the judgment criteria; the data comparison module is configured to receive the category value of the biomarker of the sample to be tested sent by the data input module, and retrieve the judgment criteria from the data recording module and compare them with the biomarker of the sample to be tested; the conclusion output module is configured to receive the comparison result sent by the data comparison module, and judge the comparison result according to predetermined judgment conditions; determine the genotype of the tested person and its prognosis; the biomarker includes the genotype of the CYP1B1 gene rs9341266 locus of the patient.

[0014] Compared with the prior art, the present invention has the following beneficial effects:

[0015] This invention can predict the prognosis of lung cancer patients, especially smokers, the elderly, patients with stage III+IV lung cancer, patients with a family history of malignant tumors and / or SCLC subtypes, and can be used to formulate treatment strategies and interventions, which is of great significance for prolonging the survival time of patients. Attached Figure Description

[0016] Figure 1 shows the process of analyzing the demographic and clinical characteristics of the patients.

[0017] Figure 2. Schematic diagram of the regulatory role of CYP1B1 in lung cancer progression through different pathways;

[0018] Figure 3 shows the relationship between the CYP1B1 gene polymorphism rs9341266 and the survival and prognosis of lung cancer patients.

[0019] Figure 3A is an enlarged view of Figure A in Figure 3;

[0020] Figure 3B is an enlarged view of Figure B in Figure 3;

[0021] Figure 3C is an enlarged view of Figure C in Figure 3;

[0022] Figure 3D is an enlarged view of Figure 3D;

[0023] Figure 3E is an enlarged view of Figure E in Figure 3;

[0024] Figure 3F is an enlarged view of Figure 3F;

[0025] Figure 3G is an enlarged view of Figure G in Figure 3;

[0026] Figure 3H is an enlarged view of Figure 3H;

[0027] Figure 3I is an enlarged view of Figure 3I. Detailed Implementation

[0028] To make the present invention more apparent and understandable, preferred embodiments are described in detail below with reference to the accompanying drawings:

[0029] This invention provides a biomarker for assessing the prognosis of lung cancer patients, wherein the biomarker is the CYP1B1 gene rs9341266 site polymorphism; lung cancer patients with G>A at the CYP1B1 gene rs9341266 site have a poor prognosis.

[0030] This invention provides the application of the CYP1B1 gene rs9341266 site polymorphism as a prognostic biomarker for lung cancer patients, wherein lung cancer patients with G>A at the CYP1B1 gene rs9341266 site have a poor prognosis.

[0031] This invention provides the application of the CYP1B1 gene rs9341266 site polymorphism in the preparation of a diagnostic kit for assessing the prognosis of lung cancer patients, wherein lung cancer patients with G>A at the CYP1B1 gene rs9341266 site have a poor prognosis.

[0032] The lung cancer patients referred to are smokers, elderly people, patients with stage III+IV lung cancer, patients with a family history of malignant tumors and / or patients with SCLC subtypes.

[0033] This invention provides the application of a biomarker in the preparation of a diagnostic reagent for assessing the prognosis of lung cancer patients. The biomarker is the genotype of the CYP1B1 gene rs9341266 locus. Lung cancer patients with G>A at the CYP1B1 gene rs9341266 locus have a poor prognosis.

[0034] This invention provides a genotyping test reagent for assessing the prognosis of lung cancer patients. The genotyping test reagent is used to perform genotyping on lung cancer patients. The genotyping test detects the genotype at the rs9341266 locus of the CYP1B1 gene. Lung cancer patients with G>A at the rs9341266 locus of the CYP1B1 gene have a poor prognosis.

[0035] This invention provides the application of a genotyping detection reagent in the preparation of a diagnostic kit for predicting the prognosis and survival status of lung cancer patients. The genotyping detection reagent is used to perform genotyping detection on lung cancer patients. The genotyping detection is to detect the genotype of the CYP1B1 gene rs9341266 locus in lung cancer patients. Lung cancer patients with G>A at the CYP1B1 gene rs9341266 locus have a poor prognosis.

[0036] This invention provides a prognostic detection system for lung cancer patients, including detecting the genotype of the CYP1B1 gene rs9341266 locus in lung cancer patients; lung cancer patients with G>A at the CYP1B1 gene rs9341266 locus have a poor prognosis.

[0037] The system includes a data processing device and a substance for detecting biomarkers; the data processing device includes a data input module, a data recording module, a data comparison module, and a conclusion output module; the data input module is configured to input the category values ​​of the biomarkers in the sample to be tested; the data recording module is configured to store the category values ​​of the biomarkers in the sample to be tested and the judgment criteria; the data comparison module is configured to receive the category values ​​of the biomarkers in the sample to be tested sent by the data input module, and retrieve the judgment criteria from the data recording module and compare them with the biomarkers in the sample to be tested; the conclusion output module is configured to receive the comparison results sent by the data comparison module, and judge the comparison results according to predetermined judgment conditions; determine the genotype and prognosis of the tested subject; the biomarker includes the genotype of the CYP1B1 gene rs9341266 locus in the patient.

[0038] Example

[0039] I. Sample Collection and Methods:

[0040] 1) Research Group & Data Collection:

[0041] Starting in January 2009, patients with primary lung cancer were recruited for an 11-month period. Among the patients, 536 were from Changhai Hospital affiliated with Naval Medical University, and 352 were from the Taizhou Institute of Health Sciences, Fudan University. Inclusion criteria included patients diagnosed with primary lung cancer by histopathology who had no prior history of malignant tumors in other organs; there were no restrictions on gender or age. Clinical statistics were then collected from the patients' medical records, and follow-up statistics were obtained through telephone interviews.

[0042] 2) SNP genotyping:

[0043] Prior to treatment, 5 ml of blood was collected from all enrolled patients. Genomic DNA was extracted using the Qiagen Blood DNA Extraction kit (Qiagen, Hilden, Germany), and genotyping was performed using the SNPscan™ kit (Genesky Biotechnology, Shanghai, China). Detailed procedures were applied to assess the quality of the genotyping, including the Hardy-Weinberg equilibrium (HWE) test, a success rate of >95%, internal positive control samples, and repeated genotyping. Personal clinical data was kept confidential by staff performing genotyping tests in the laboratory.

[0044] The SNPscan™ kit is a kit developed by Shanghai Tianhao Biotechnology Co., Ltd. for multiplex SNP genotyping.

[0045] 3) Statistical analysis:

[0046] Prior to the association study using the Pearson chi-square test, the HWE test was performed on the CYP1B1 gene rs9341266 locus in the target population. We recorded overall survival from sample collection to the date of death from any cause or the last follow-up. Median survival was recorded using the Kaplan-Meier method, and differences between groups were validated using the Log-rank test. Univariate and multivariate Cox regression analyses were used to estimate 95% confidence intervals and hazard ratios, adjusted for sex and age. Cox regression analysis of SNPs was performed using four SNP genetic models (genotype, allele, recessive, and dominant), stratified by sex, age, family history of malignancy and smoking status, TNM stage, and lung cancer histological classification. All tests were two-sided. A p-value less than 0.05 was considered statistically significant. All statistical analyses were performed using R version 3.6.0 (Federation for R Statistical Computation, Vienna, Austria).

[0047] II. Experimental Design and Results:

[0048] 1) Demographic, clinical characteristics, and prognostic analysis of lung cancer patients:

[0049] This study enrolled 888 lung cancer patients and recorded their clinical characteristics during the follow-up phase. The study sample was uniformly Han Chinese. 49 patients (5.52%) were unable to complete follow-up. Multivariate Cox regression analysis was used to assess the correlation between clinical characteristics and prognosis in lung cancer patients. The results are shown in Table 1. The median survival time for all patients was 36.73 months. Among the patients, 610 were male (72.7%) and 524 were elderly (over 60 years old). 582 patients (69.4%) were heavily exposed to tobacco smoke. Furthermore, 625 patients (74.5%) were diagnosed with advanced cancer. Among all patients, women, patients under 60 years of age, and non-smokers had significantly longer median survival times (MST) than men, patients over 60 years of age, and smokers. In addition, patients with advanced TNM had significantly shorter MSTs than those with stage I and II TNM disease (Table 1).

[0050] Table 1. Characteristics and prognostic analysis of cancer patients (n=839)

[0051] Other carcinomas listed with * include adenosquamous carcinoma, large cell carcinoma, carcinosarcoma, and mucoepidermoid carcinoma; early stage refers to TNM stages I and II; late stage refers to TNM stages III and IV.

[0052] 2) Correlation between CYP1B1 rs9341266 and prognosis in lung cancer patients:

[0053] CYP1B1 rs9341266 revealed 727 GG, 102 GA, and 10 AA genotypes. Furthermore, there were 156 G alleles and 122 A alleles at the CYP1B1 rs9341266 locus. In deceased patients, the frequencies of the G and A alleles were 92.37% (1234 out of 1336) and 7.63% (102 out of 1336), respectively, while in surviving patients they were 94.15% (322 out of 342) and 5.85% (20 out of 342), respectively. In univariate Cox regression analysis, patients with the A allele had a higher risk of death (HR = 1.27; 95% CI: 1.04–1.55; P = 0.021). Multivariate Cox regression analysis showed that, after adjusting for age, sex, and smoking status, the mortality rate of patients with the dominant GA+AA genotype was significantly higher than that of patients with the GG genotype (adjusted HR = 1.25; 95% CI: 1.00–1.56; P = 0.045) (as shown in Table 3) (Figure 3A).

[0054] 3) Correlation between CYP1B1 polymorphism stratified by patient clinical condition and lung cancer prognosis:

[0055] We performed a stratified analysis to understand the association between CYP1B1 rs9341266 and lung cancer prognosis. Male patients with genotype AA had a higher risk of death than those with genotype GG (adjusted HR = 2.37, 95% CI: 1.17–4.79, adjusted P = 0.016) (see Table 3); in the sex-stratified analysis, the dominant genotype AA was also present relative to genotypes AA+GA (adjusted HR = 1.36, 95% CI: 1.06–1.74, adjusted P = 0.015) (see Table 3) (Figures 3B and 3C). In patients aged 60 years and older, the risk of death was higher for patients with the A allele than for those with the G allele (adjusted hazard ratio = 1.48, 95% CI: 1.16–1.89, adjusted P = 0.001), as were the risks for the AA genotype compared to the GG genotype (adjusted HR = 2.86, 95% CI: 1.41–5.80, adjusted P = 0.004) (Tables 2 and 3), the GA genotype compared to the GG genotype (adjusted HR = 1.34, 95% CI: 1.01–1.77, adjusted P = 0.042) (Tables 2 and 3), and the GA+AA dominant genotype compared to the GG genotype (adjusted HR = 1.43, 95% CI: 1.10–1.86, adjusted P = 0.008) (Table 3) (Figures 3D, 3E, 3F, 3G). In smokers, the risk of death was higher with allele A than with allele G (adjusted HR = 1.29, 95% confidence interval: 1.03–1.63, adjusted P = 0.027) (see Tables 2 and 3). In patients with a family history of malignancy, allele rs9341266A was associated with a higher predicted risk of death compared to allele G (adjusted HR = 1.49, 95% CI: 1.08–2.06, adjusted P = 0.016) (see Tables 2 and 3), as was the case with genotype AA compared to genotype GG (adjusted HR = 3.83, 95% CI: 1.68–8.73, adjusted P = 0.001) (see Tables 2 and 3) and recessive AA compared to GG+GA (adjusted HR = 3.75, 95% CI: 1.65–8.53, adjusted P = 0.002) (see Tables 2 and 3).In patients with small cell lung cancer, the rs9341266 polymorphism A allele increased the prognostic risk of death compared to the G allele (adjusted HR = 2.54, 95% CI: 1.26–5.11, adjusted P = 0.008) (see Tables 2 and 3), as did the AA genotype compared to the GG genotype (adjusted HR = 4.97, 95% CI: 1.16–21.34, adjusted P = 0.031) (see Table 3), the dominant GA+AA genotype compared to the GG genotype (adjusted hazard ratio = 2.34, 95% CI: 1.02–5.36, adjusted P = 0.044) (see Table 3), and the recessive AA genotype compared to the GG+GA genotype (adjusted HR = 4.72, 95% CI: 1.10–20.21, adjusted P = 0.037) (see Table 3). For patients diagnosed with advanced lung cancer, the risk of death was higher in patients with the rs9341266 genotype AA than in those with the genotype GG (adjusted HR = 2.11, 95% CI: 1.08–4.10, adjusted P = 0.028) (as shown in Table 3), and the same was true for the recessive AA genotype compared to GG+GA (adjusted HR = 2.08, 95% CI: 1.07–4.05, adjusted P = 0.030) (as shown in Table 3) (Figures 3H and 3I).

[0056] In summary, the above studies demonstrate a strong correlation between G>A at the rs9341266 site of the CYP1B1 gene and poor prognosis in lung cancer patients, particularly in smokers, the elderly, patients with stage III+IV lung cancer, those with a family history of malignant tumors, and those with SCLC subtypes. These studies play a crucial role in predicting the potential prognostic opportunities for lung cancer patients, thus providing a reference for developing new treatment strategies.

[0057] Figure 1 illustrates the research process of this invention, including patient demographics and clinical characteristics. Lung cancer patients were assessed using clinical characteristics and analytical strategies. For 839 patients with primary lung cancer (49 patients were excluded due to lack of medical information), clinical characteristics, including tobacco status, histology, and TNM staging, were evaluated. Demographic and statistical analyses were performed on clinical characteristics, SNPs, stratification analysis, and prognosis.

[0058] Figure 2 illustrates the regulatory role of CYP1B1 in lung cancer progression through different pathways. CYP1B1 initiates Sp1 by increasing the expression of 4-hydroxyestradiol (4-OHE2). Sp1 can trigger two pathways. On one hand, it increases E-cadherin transcriptional repressors such as ZEB1 and TWIST1, subsequently promoting EMT. On the other hand, Sp1 increases β-catenin levels, thereby triggering the activation of Wnt signaling. Both pathways can promote cell proliferation and development.

[0059] Figure 3 shows the impact of the CYP1B1 gene polymorphism rs9341266 on the survival and prognosis of lung cancer patients. These patients are male in the genotype model (Figure 3B), male in the dominant model (Figure 3C), elderly (>60 years old) in the genotype model (Figure 3D, Figure 3E), elderly (>60 years old) in the dominant model (Figure 3F), elderly (>60 years old) in the recessive model (Figure 3G), stage III+IV disease in the genotype model (Figure 3H), and stage III+IV disease in the recessive model (Figure 3I).

[0060] Table 2. Correlation between CYP1B1-rs9341266 polymorphism and prognosis of Chinese cancer patients in allele models.

[0061] HR: Hazard ratio; CI: Confidence interval; ref: Control group; *: Adjusted for gender and age

[0062] Table 3. Relationship between CYP1B1-rs9341266 and prognosis in Chinese cancer patients using different models.

[0063] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any form or substance. It should be noted that those skilled in the art can make various improvements and additions without departing from the present invention, and these improvements and additions should also be considered within the scope of protection of the present invention. Any modifications, alterations, and equivalent changes made by those skilled in the art based on the above-disclosed technical content without departing from the spirit and scope of the present invention are equivalent embodiments of the present invention. Furthermore, any modifications, alterations, and evolutions made to the above embodiments based on the essential technology of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A biomarker for assessing the prognosis of lung cancer patients, characterized in that, The biomarker is the CYP1B1 gene rs9341266 site polymorphism; lung cancer patients with G>A at the CYP1B1 gene rs9341266 site have a poor prognosis.

2. The application of the CYP1B1 gene rs9341266 polymorphism as a prognostic biomarker for lung cancer patients, characterized in that... Lung cancer patients with G>A at the rs9341266 locus of the CYP1B1 gene have a poor prognosis.

3. The application of the CYP1B1 gene rs9341266 polymorphism in the preparation of a diagnostic kit for assessing the prognosis of lung cancer patients, characterized in that... Lung cancer patients with G>A at the rs9341266 locus of the CYP1B1 gene have a poor prognosis.

4. The application according to claim 3, characterized in that, The lung cancer patients referred to are smokers, elderly people, patients with stage III+IV lung cancer, patients with a family history of malignant tumors and / or patients with SCLC subtypes.

5. The application of a biomarker in the preparation of a diagnostic reagent for assessing the prognosis of lung cancer patients, characterized in that, The biomarker is the genotype at the rs9341266 locus of the CYP1B1 gene; lung cancer patients with G>A at the rs9341266 locus of the CYP1B1 gene have a poor prognosis.

6. A genotyping test reagent for assessing the prognosis of lung cancer patients, characterized in that, The genotyping reagent is used to perform genotyping on lung cancer patients. The genotyping test detects the genotype at the rs9341266 locus of the CYP1B1 gene. Lung cancer patients with G>A at the rs9341266 locus of the CYP1B1 gene have a poor prognosis.

7. The application of a genotyping detection reagent in the preparation of a diagnostic kit for predicting the prognostic survival status of lung cancer patients, characterized in that, The genotyping test reagent is used to perform genotyping on lung cancer patients. The genotyping test is to detect the genotype of the CYP1B1 gene rs9341266 locus in lung cancer patients. Lung cancer patients with G>A at the CYP1B1 gene rs9341266 locus have a poor prognosis.

8. A prognostic detection system for lung cancer patients, characterized in that, This includes detecting the genotype of the CYP1B1 gene rs9341266 locus in lung cancer patients; lung cancer patients with G>A at the CYP1B1 gene rs9341266 locus have a poor prognosis.

9. A prognostic detection system for lung cancer patients according to claim 8, characterized in that, The system includes a data processing device and a substance for detecting biomarkers; the data processing device includes a data input module, a data recording module, a data comparison module, and a conclusion output module; the data input module is configured to input the category values ​​of the biomarkers in the sample to be tested; the data recording module is configured to store the category values ​​of the biomarkers in the sample to be tested and the judgment criteria; the data comparison module is configured to receive the category values ​​of the biomarkers in the sample to be tested sent by the data input module, and retrieve the judgment criteria from the data recording module and compare them with the biomarkers in the sample to be tested; the conclusion output module is configured to receive the comparison results sent by the data comparison module, and judge the comparison results according to predetermined judgment conditions; determine the genotype and prognosis of the tested subject; the biomarker includes the genotype of the CYP1B1 gene rs9341266 locus in the patient.

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