Plasma metabolism molecular biomarker of colorectal cancer-related polycyclic aromatic hydrocarbon as well as screening method and application of plasma metabolism molecular biomarker

Abstract

The invention discloses a colorectal cancer related polycyclic aromatic hydrocarbon plasma metabolism molecular biomarker as well as a screening method and application thereof, and belongs to the technical field of colorectal cancer. Plasma of a colorectal cancer case and a healthy control group person is detected through gas chromatography-mass spectrometry; the method comprises the following steps: exporting information of a plurality of metabolites detected by a plasma sample, adjusting a batch effect through a ComBat method based on empirical Bayes, and then screening out polycyclic aromatic hydrocarbons with a detection rate of more than 60% in a colorectal cancer case contrast sample; three polycyclic aromatic hydrocarbons are screened out through a random forest method to serve as plasma metabolism molecular biomarkers of colorectal cancer related polycyclic aromatic hydrocarbons, the biomarkers are combined biomarkers of fluorene, anthracene and benzo [k] fluoranthene, the combined AUC of the three polycyclic aromatic hydrocarbons is 0.785, and the prediction accuracy of colorectal cancer is high.

Description

Technical Field

[0001] This invention belongs to the field of colorectal cancer technology, and in particular relates to colorectal cancer-related polycyclic aromatic hydrocarbon plasma metabolism molecular biomarkers, their screening methods, and applications. Background Technology

[0002] Colorectal cancer is one of the most common malignant tumors worldwide and has become a serious public health problem. The occurrence of colorectal cancer is largely influenced by environmental factors. Evidence suggests that exposure to polycyclic aromatic hydrocarbons (PAHs) due to poor diet significantly increases the risk of developing colorectal adenomas and colorectal cancer. Therefore, further exploration of the pathogenic factors and mechanisms of colorectal cancer, and the search for effective environmental exposure biomarkers, are of significant public health importance for the precise prevention and early diagnosis of colorectal cancer. Currently, the diagnosis of colorectal cancer mainly relies on imaging examinations, biochemical tests, and pathological examinations. Among these, colonoscopy is the gold standard for colorectal cancer diagnosis and the most effective screening method for precancerous lesions and the development of cancer; however, its invasiveness and high surgical cost limit its large-scale screening application.

[0003] Given the advancements in metabolomics analysis techniques, multiple studies have demonstrated the feasibility of detecting fecal metabolites for non-invasive diagnosis of colorectal cancer. Using individual samples such as plasma, urine, feces, and tissues, metabolomics can reflect an individual's metabolic status under different physiological and pathological conditions. In existing technologies, researchers have used non-targeted liquid chromatography-mass spectrometry (LC-MS) to detect metabolites in plasma samples, discovering that oleic acid and isocholic acid play antagonistic roles in colorectal cancer and establishing a colorectal cancer diagnostic model with 17 metabolites, demonstrating good diagnostic efficacy. Other researchers have used ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) to identify a group of urinary metabolite markers capable of distinguishing between colorectal cancer patients and healthy controls. Novel tumor markers based on metabolomics are characterized by ease of implementation, high individual compliance, and non-invasiveness, making them widely applicable for screening in the general population.

[0004] However, current research lacks biomarkers to identify colorectal cancer-related changes in polycyclic aromatic hydrocarbon (PAH) metabolism that differentiate the incidence of colorectal cancer caused by PAH exposure. Summary of the Invention

[0005] To overcome the above problems, this invention provides molecular biomarkers for colorectal cancer-related polycyclic aromatic hydrocarbon plasma metabolism, their screening methods, and applications.

[0006] Technical solution:

[0007] In a first aspect, the present invention provides a method for screening molecular biomarkers of polycyclic aromatic hydrocarbon (PAH) plasma metabolism associated with colorectal cancer, specifically:

[0008] Plasma samples from colorectal cancer patients and healthy controls were analyzed using gas chromatography-mass spectrometry.

[0009] Information on multiple metabolites detected in plasma samples was exported, batch effects were adjusted using the ComBat method based on empirical Bayesianism, and then polycyclic aromatic hydrocarbons with a detection rate greater than 60% in colorectal cancer case control samples were screened.

[0010] Three polycyclic aromatic hydrocarbons (PAHs) were screened using a random forest method as molecular biomarkers for PHA plasma metabolism associated with colorectal cancer. The three PAHs screened were fluorene, anthracene, and benzo[k]fluoranthene.

[0011] Secondly, the present invention provides a molecular biomarker for polycyclic aromatic hydrocarbon plasma metabolism associated with colorectal cancer, wherein the biomarker is a combination of fluorene, anthracene, and benzo[k]fluoranthene.

[0012] Thirdly, this invention constructs a colorectal cancer prediction model based on the aforementioned biomarkers. The prediction equation of the colorectal cancer prediction model is as follows:

[0013] Score = 0.035×FI + 0.445×An + 0.628×BkF + 0.019×age - 0.137×sex;

[0014] Wherein: FI is the concentration of fluorene in the plasma sample, in μg / mL; An is the concentration of anthracene in the plasma sample, in μg / mL; BkF is the concentration of benzo[k]fluoranthene in the plasma sample, in μg / mL; age ranges from 19 to 89, based on the subject's actual age; sex is 1 for female subjects and 2 for male subjects; a risk score higher than 1.487 indicates a high risk of colorectal cancer in the subject.

[0015] Beneficial effects:

[0016] 1. This invention utilizes efficient, accurate, and high-throughput GC-MS / MS technology to perform polycyclic aromatic hydrocarbon (PAH) metabolomics analysis on the plasma of colorectal cancer patients and healthy controls, aiming to identify PAH metabolic molecular markers for the early diagnosis of colorectal cancer. The results are of great significance for elucidating the changing patterns of PAH metabolite levels in the plasma of colorectal cancer patients and revealing the role of PAHs in the development and progression of tumors.

[0017] 2. This screening method can be used to obtain efficient biomarkers for the early diagnosis of colorectal cancer. The combined biomarkers of fluorene, anthracene, and benzo[k]fluoranthene can be used to assist in the diagnosis of colorectal cancer. Attached Figure Description

[0018] Figure 1 The detection rate of polycyclic aromatic hydrocarbon levels in the plasma of the sample population in the examples;

[0019] Figure 2 The partial least squares discriminant analysis (PLS-DA) model for colorectal cancer case-control in the examples is shown.

[0020] Figure 3 The ROC curves (FI, An, and BkF) used in the examples to differentiate between colorectal cancer case groups and healthy control groups. Detailed Implementation

[0021] The technical solution of the present invention will be described in detail below through embodiments, but the scope of protection of the present invention is not limited to the embodiments described.

[0022] Example 1

[0023] This embodiment discloses a method for screening plasma metabolic molecules associated with colorectal cancer polycyclic aromatic hydrocarbons (PAHs). The method includes the following steps:

[0024] Step 1: Determine the research subjects and group them.

[0025] Group A, colorectal cancer group, requirements: (1) Han nationality; (2) confirmed by histopathology as colorectal cancer; (3) no other major systemic diseases.

[0026] Group B, healthy control group, requirements: (1) Han nationality; (2) not diagnosed with tumors by physical examination and have no history of tumors; (3) no other major systemic diseases.

[0027] In the healthy control group, sex, age and other demographic characteristics were frequency-matched to those in the colorectal cancer group.

[0028] This study included 185 cases of colorectal cancer and 185 healthy controls, all of whom were Han Chinese. The cases were collected from September 2010 to September 2024 from the Affiliated Hospital of Nanjing Medical University, and all cases were confirmed by histopathology. The controls were healthy individuals who underwent physical examinations at the hospital during the same period and were not found to have tumors. The cases and controls were matched for frequency based on age (±5 years). The demographic information (including age, sex, smoking, and alcohol consumption) and clinical information (including tumor location, tumor grade, and clinical stage) of the subjects were obtained by professionally trained personnel through a standardized questionnaire. All subjects signed informed consent forms and provided 5 mL of venous blood, which was then centrifuged to separate the plasma. This study was approved by the Ethics Committee of Nanjing Medical University.

[0029] Step 2: Screening for molecular markers of polycyclic aromatic hydrocarbon metabolism associated with colorectal cancer using gas chromatography-mass spectrometry.

[0030] 2.1 Sample Pretreatment

[0031] Thaw plasma samples at room temperature. Pipette 200 μL of plasma into a 15 mL glass tube, add 10 μL of internal standard solution (100 ng / mL), mix thoroughly, then add 0.5 mL of hydrochloric acid (6 mol / L), vortex for 2 min, and let stand. Add 0.5 mL of isopropanol, vortex for 2 min, and let stand. Add 3 mL of n-hexane-methyl tert-butyl ether mixed solution, vortex for 2 min, and let stand to separate the layers. Collect the supernatant, repeat the extraction process three times, and collect the supernatant from each extraction into a 15 mL glass tube. Redissolve in 100 μL of n-hexane before analysis.

[0032] 2.2 Instrument Testing

[0033] 2.2.1 Chromatographic parameters

[0034] 1) Column type: DB-5MS capillary column (Agilent, 30 m × 0.25 mm, film thickness 0.25 mm).

[0035] 2) Heating program: Initial temperature 65℃, hold for 30s; increase temperature to 130℃ at a rate of 15℃ / min, hold for 30s; then increase temperature to 220℃ at a rate of 9℃ / min, hold for 60s; then increase temperature to 240℃ at a rate of 7℃ / min, hold for 90s; finally increase temperature to 320℃ at a rate of 15℃ / min, hold for 5min. The total heating time is 31 min 1.2s.

[0036] 3) The injection port temperature is set to 270℃, the injection volume is set to 1μL, the injection is carried out by pulse splitless injection, ammonia is used as the carrier gas, the flow rate is maintained at 1.4mL / min, and the mass spectrometer interface temperature is set to 270℃.

[0037] 2.2.2 Mass Spectrometry Parameters

[0038] The mass spectrometer was equipped with an electron impact ionization (EI) source with an ionization voltage of 70 eV; an ion source temperature of 230 °C; and a solvent delay time of 5 min. All target components were qualitatively analyzed using full scan mode (Scan), with a scan range of 45–350 m / z. After qualitative analysis of all components, quantitative analysis of the target components was performed using selected ion monitoring mode (SIM). The limits of detection (LOD, signal-to-noise ratio S / N = 3) of the analytes were determined by literature review and testing of standard samples. Each target analyte exhibited good linear response within the concentration range (10–1000 ng / mL). 2 (>0.999), the test results show that the determination method used in this experiment can qualitatively and quantitatively analyze all target substances.

[0039] Step 3: Methodological verification.

[0040] 3.1 Limit of Detection and Linear Range of Standard Curve: The limit of detection refers to the lowest concentration at which the analyte can be detected in a sample. The limit of detection is determined by the concentration at which the signal-to-noise ratio is equal to 3. 200 μL of standard solutions of different concentrations were taken and processed according to the above pretreatment method before analysis. Standard curves for polycyclic aromatic hydrocarbons (PAHs) were plotted based on the ratio of the peak area of ​​each PAH to the peak area of ​​the internal standard and the concentrations of the standard solutions. The correlation coefficients (r) of each standard curve were greater than 0.98, and the separation of each PAH was good, meeting the requirements for quantitative detection of actual samples.

[0041] 3.2. Accuracy and precision: The recovery rate was calculated by testing quality control samples with low, medium and high concentrations; the relative standard deviation was calculated by repeatedly measuring the quality control samples.

[0042] By testing quality control samples with low, medium, and high concentrations, the recovery rate was found to be between 80% and 120%. Repeated testing of the quality control samples showed a relative standard deviation (RSD) of less than or equal to 15%, which meets the testing requirements.

[0043] The three concentrations—low, medium, and high—are defined based on the mean ± standard deviation of each polycyclic aromatic hydrocarbon. Low concentration is less than the mean minus the standard deviation, high concentration is greater than the mean plus the standard deviation, and medium concentration is between the two.

[0044] Step 4: Statistical analysis of data and screening of biomarkers.

[0045] Information on multiple metabolites detected in plasma samples was exported. Batch effects were adjusted using the ComBat method based on empirical Bayesianism, and then analytes with a detection rate greater than 60% in plasma samples from colorectal cancer case-control populations were screened. A partial least squares discriminant analysis model was further constructed to determine the differences between colorectal cancer cases and controls. Random forest analysis and receiver operating characteristic (ROC) curves and their areas under the curves were used to evaluate the diagnostic value of plasma polycyclic aromatic hydrocarbon (PAH) levels for colorectal cancer. All statistical analyses were performed using R4.3.1 software. All tests were two-tailed, and P < 0.05 was considered statistically significant.

[0046] Information on multiple metabolites detected in plasma samples was exported, batch effects were adjusted using the ComBat method based on empirical Bayesianism, and then polycyclic aromatic hydrocarbons (PAHs) with a detection rate greater than 60% in colorectal cancer case-control samples were screened. Figure 1 The random forest method was used to screen out three polycyclic aromatic hydrocarbons (PAHs): fluorene (FI), anthracene (An), and benzo[k]fluoranthene (BkF).

[0047] The PLS-DA model showed good differentiation between cases and controls. Figure 2 Meanwhile, receiver operating characteristic (ROC) curves were used to assess the ability of three polycyclic aromatic hydrocarbons (PAHs) to predict colorectal cancer, with fluorene (FI) having an AUC of 0.560, anthracene (An) having an AUC of 0.569, and benzo[k]fluoranthene (BkF) having an AUC of 0.609.

[0048] Table 1. Polycyclic aromatic hydrocarbon levels in colorectal cancer case-control group.

[0049]

[0050] The sample (185 colorectal cancer cases and 185 normal controls) was divided into training and validation sets in a 7:3 ratio. Using 130 pairs of colorectal cancer case-control samples (70%) as the training set, three PAH prediction models were constructed based on the training set using the random forest method. Then, 55 pairs of colorectal cancer case-control samples (30%) were used as the validation set to verify the model effectiveness and predict the risk of colorectal cancer. The results showed that the combined AUC of the three models was 0.785 (…). Figure 3 This suggests that it has a high clinical diagnostic capability for colorectal cancer.

[0051] The construction equations for the three polycyclic aromatic hydrocarbons using the above method are as follows:

[0052] Score = 0.035×FI + 0.445×An + 0.628×BkF + 0.019×age - 0.137×sex.

[0053] The specific value ranges of FI, An, BkF, age, and sex in the formula are shown in Table 2.

[0054] Table 2. Range of values ​​for each variable

[0055]

[0056] The population risk score was calculated using the risk scoring formula, with a range of 0.345-2.676, a mean of 1.161, and a standard deviation of 0.326. Based on the mean ± one standard deviation, the sample was divided into a high-risk group and a low-risk group. The high-risk group had a risk score higher than 1.487 and had a higher risk of colorectal cancer.

[0057] Fluorene (FI), anthracene (An), and benzo[k]fluoranthene (BkF) are three polycyclic aromatic hydrocarbons (PAHs) that are biomarkers of long-term environmental exposure. Elevated levels of these PAHs in patients suggest an association between cumulative exposure and colorectal cancer. Based on this finding, detecting the levels of these three substances in healthy individuals can be used to assess their potential risk of developing colorectal cancer in the future. A healthy person with persistently high levels of these three PAHs is considered to be in a high-risk exposure state. Intervention can be initiated earlier, without waiting for the development of 'early-stage cancer' or even 'late-stage cancer,' such as guiding lifestyle changes, adjusting dietary structure, and recommending closer health monitoring. Therefore, the three biomarkers disclosed in this invention provide a quantifiable risk warning signal before symptoms appear and before cancer develops, preventing the occurrence of 'early lesions' and thus achieving a true 'prevention' approach.

[0058] The above-described embodiments are merely one implementation of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.

Claims

1. A molecular biomarker for plasma metabolism of polycyclic aromatic hydrocarbons associated with colorectal cancer, characterized in that, The biomarker is a combination of fluorene, anthracene, and benzo[k]fluoranthene.

2. The method for screening biomarkers according to claim 1, characterized in that, Includes the following steps: Plasma samples from colorectal cancer patients and healthy controls were analyzed using gas chromatography-mass spectrometry. Information on multiple metabolites detected in plasma samples was exported, batch effects were adjusted using the ComBat method based on empirical Bayesianism, and then polycyclic aromatic hydrocarbons with a detection rate greater than 60% in colorectal cancer case control samples were screened. Three polycyclic aromatic hydrocarbons (PAHs) were screened using a random forest method as molecular biomarkers for PHA plasma metabolism associated with colorectal cancer. The three PAHs screened were fluorene, anthracene, and benzo[k]fluoranthene.

3. The application of the biomarker according to claim 1, characterized in that, A colorectal cancer prediction model was constructed based on the aforementioned biomarkers.

4. The application according to claim 3, characterized in that, The predictive equation for the colorectal cancer prediction model is as follows: Score = 0.035×FI + 0.445×An + 0.628×BkF + 0.019×age -0.137×sex; Wherein, FI is the concentration of fluorene in the plasma sample, in μg / mL; An is the concentration of anthracene in the plasma sample, in μg / mL; BkF is the concentration of benzo[k]fluoranthene in the plasma sample, in μg / mL; age ranges from 19 to 89, based on the subject's actual age; sex is 1 for female subjects and 2 for male subjects; A risk score higher than 1.487 indicates a high risk of colorectal cancer in the subject.

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