Application of plasma specific piRNA marker in preparation of reagent for detecting non-small cell lung cancer caused by tobacco exposure

Abstract

The invention relates to application of a plasma specific piRNA marker in preparation of a reagent for detecting non-small cell lung cancer caused by tobacco exposure, and belongs to the technical field of biomedicine. According to the application of the piRNA in the preparation of the detection reagent for the plasma specific piRNA marker of the non-small cell lung cancer caused by tobacco exposure, at least one of piR-2850767, piR-372947, piR-726712, piR-720636 and piR-157618 is used in the preparation of the detection reagent for the plasma specific piRNA marker of the non-small cell lung cancer caused by tobacco exposure. By detecting the plasma expression level of each piRNA in the piRNA combination, the piRNA marker is screened out in non-small cell lung cancer patients and healthy control and in the healthy control, the expression levels of smokers and non-smokers have significant statistical differences in plasma, and an intermediary effect exists between the smoking state and the non-small cell lung cancer. The piRNA marker provided by the invention has high sensitivity and high specificity in non-small cell lung cancer diagnosis.

Description

Technical Field

[0001] The present application relates to the field of biomedical technology, and more specifically, to the use of plasma-specific piRNA markers in the preparation of reagents for detecting non-small cell lung cancer caused by tobacco exposure. Background Art

[0002] Lung cancer is a common malignant tumor worldwide. Its early hidden nature means that most patients are already in the middle or late stages when diagnosed, and the prognosis is extremely poor. The five-year survival rate of patients with early lung cancer can reach over 90%, reflecting the importance of early diagnosis. However, the existing diagnostic methods such as chest imaging, bronchoscopy and sputum examination are not ideal. Although the widely used imaging technology (LDCT) can be used for early screening, the false positive rate is high, which affects the accuracy of diagnosis. Therefore, it is difficult to accurately capture early lung cancer by relying solely on imaging. There is an urgent need to develop new strategies that combine efficient biomarkers with LDCT to enhance diagnostic specificity, provide opportunities for early screening and diagnosis of lung cancer patients, and improve the quality of life of patients.

[0003] PIWI-interacting RNAs (piRNAs) are small, non-coding RNAs (23-31 nucleotides in length). As a novel epigenetic marker, they can exert epigenetic regulatory effects through transposon silencing, regulating DNA methylation, and controlling mRNA transcription and translation, influencing gene expression and thus participating in the development and progression of various diseases. Previous studies have shown that piRNAs are expressed in a tissue-specific manner in humans, and their abnormal expression may be involved in multiple signaling pathways, such as inflammation, apoptosis, and the cell cycle, thereby participating in the development and progression of lung cancer. This suggests that piRNAs may be promising biomarkers for the early diagnosis of lung cancer.

[0004] However, existing piRNA-based lung cancer diagnostic technologies have numerous drawbacks and shortcomings. Specifically, most current methods used to predict and detect lung cancer are invasive, insensitive, and involve radiation exposure. Their ability to identify early-stage lung cancer is limited, making them unsuitable for routine lung cancer screening. Furthermore, piRNA-based lung cancer diagnostic technology is still immature, and changes in the expression levels of certain piRNA molecules in lung cancer may not be significant enough, resulting in insufficient diagnostic sensitivity. Summary of the Invention

[0005] In response to the above-mentioned deficiencies in the existing technology, the present application provides a set of specific plasma piRNA markers for the diagnosis of non-small cell lung cancer, as well as their screening methods and uses. Based on the detection of the plasma expression levels of five piRNAs, piRNA markers have good predictive value for the occurrence of lung cancer and can be used as specific diagnostic markers for non-small cell lung cancer.

[0006] According to a first aspect of the present invention, there is provided a use of a plasma-specific piRNA marker in the preparation of a reagent for detecting non-small cell lung cancer caused by tobacco exposure, wherein the plasma-specific piRNA comprises at least one of piR-2850767, piR-372947, piR-726712, piR-720636, and piR-157618;

[0007] The nucleotide sequence of the piR-2850767 is shown in SEQ ID NO: 1, the nucleotide sequence of the piR-372947 is shown in SEQ ID NO: 2, the nucleotide sequence of the piR-726712 is shown in SEQ ID NO: 3, the nucleotide sequence of the piR-720636 is shown in SEQ ID NO: 4, and the nucleotide sequence of the piR-157618 is shown in SEQ ID NO: 5.

[0008] According to another aspect of the present invention, there is provided a use of a plasma-specific piRNA marker in the preparation of a kit for detecting non-small cell lung cancer caused by tobacco exposure, wherein the plasma-specific piRNA comprises at least one of piR-2850767, piR-372947, piR-726712, piR-720636, and piR-157618;

[0009] The nucleotide sequence of the piR-2850767 is shown in SEQ ID NO: 1, the nucleotide sequence of the piR-372947 is shown in SEQ ID NO: 2, the nucleotide sequence of the piR-726712 is shown in SEQ ID NO: 3, the nucleotide sequence of the piR-720636 is shown in SEQ ID NO: 4, and the nucleotide sequence of the piR-157618 is shown in SEQ ID NO: 5.

[0010] According to another aspect of the present invention, a kit for detecting non-small cell lung cancer caused by tobacco exposure is provided, the kit comprising plasma-specific piRNA markers, wherein the plasma-specific piRNA markers comprise any one of piR-2850767, piR-372947, piR-726712, piR-720636, and piR-157618;

[0011] The nucleotide sequence of the piR-2850767 is shown in SEQ ID NO: 1, the nucleotide sequence of the piR-372947 is shown in SEQ ID NO: 2, the nucleotide sequence of the piR-726712 is shown in SEQ ID NO: 3, the nucleotide sequence of the piR-720636 is shown in SEQ ID NO: 4, and the nucleotide sequence of the piR-157618 is shown in SEQ ID NO: 5.

[0012] According to another aspect of the present invention, a method for screening plasma-specific piRNA markers for non-small cell lung cancer caused by tobacco exposure is provided, comprising the following steps:

[0013] (1) RNA sequencing was used to detect and compare the plasma piRNA counts in peripheral blood samples of tobacco-exposed NSCLC patients and healthy controls;

[0014] (2) normalizing the piRNA count values ​​obtained in step (1) and using a logistic model to screen piRNAs associated with non-small cell lung cancer across the entire genome;

[0015] (3) Unmatched differential expression analysis was performed using the whole genome differential expression analysis method to screen out plasma piRNAs associated with tobacco exposure in healthy controls based on the criteria of a fold difference > 1 and a multiplicity-corrected FDR value less than 0.05;

[0016] (4) Venn analysis was used to intersect the two types of plasma piRNAs screened in step (2) and step (3), and differentially expressed plasma piRNAs associated with both lung cancer and tobacco exposure were obtained as candidate piRNAs;

[0017] (5) evaluating the mediating effect of the candidate piRNA obtained in step (4) on the correlation between smoking and tobacco exposure by a mediation effect analysis method, and determining the plasma-specific piRNA markers of non-small cell lung cancer caused by tobacco exposure, wherein the plasma-specific piRNA markers of non-small cell lung cancer caused by tobacco exposure are piR-2850767, piR-372947, piR-726712, piR-720636, and piR-157618;

[0018] The nucleotide sequence of the piR-2850767 is shown in SEQ ID NO: 1, the nucleotide sequence of the piR-372947 is shown in SEQ ID NO: 2, the nucleotide sequence of the piR-726712 is shown in SEQ ID NO: 3, the nucleotide sequence of the piR-720636 is shown in SEQ ID NO: 4, and the nucleotide sequence of the piR-157618 is shown in SEQ ID NO: 5.

[0019] According to another aspect of the present invention, a screening system for plasma-specific piRNA markers of non-small cell lung cancer caused by tobacco exposure is provided, comprising:

[0020] Plasma piRNA count value acquisition module: used to detect and compare the plasma piRNA count values ​​in peripheral blood samples of tobacco-exposed non-small cell lung cancer patients and healthy controls using RNA sequencing methods;

[0021] Non-small cell lung cancer-related piRNA screening module: used to standardize the obtained piRNA count values ​​and use the logistic model to screen piRNAs related to non-small cell lung cancer on a genome-wide scale;

[0022] Tobacco exposure-related plasma piRNA screening module: used to perform unmatched differential analysis using the whole-genome differential expression analysis method, and screened plasma piRNAs associated with tobacco exposure in healthy controls based on the criteria of a fold difference > 1 and a multiple-corrected FDR value less than 0.05;

[0023] Candidate piRNA screening module: used to use Venn analysis to intersect the two types of plasma piRNAs screened in step (2) and step (3), and obtain differentially expressed plasma piRNAs that are simultaneously related to lung cancer and tobacco exposure as candidate piRNAs;

[0024] Analysis module for plasma-specific piRNA markers of non-small cell lung cancer caused by tobacco exposure: used to evaluate the mediating effect of candidate piRNAs in the correlation between smoking and tobacco exposure through a mediation effect analysis method, and to determine plasma-specific piRNA markers of non-small cell lung cancer caused by tobacco exposure. The plasma-specific piRNA markers of non-small cell lung cancer caused by tobacco exposure are piR-2850767, piR-372947, piR-726712, piR-720636, and piR-157618;

[0025] The nucleotide sequence of the piR-2850767 is shown in SEQ ID NO: 1, the nucleotide sequence of the piR-372947 is shown in SEQ ID NO: 2, the nucleotide sequence of the piR-726712 is shown in SEQ ID NO: 3, the nucleotide sequence of the piR-720636 is shown in SEQ ID NO: 4, and the nucleotide sequence of the piR-157618 is shown in SEQ ID NO: 5.

[0026] In general, the above technical solutions conceived by the present invention have the following technical advantages compared with the existing technology:

[0027] The plasma piRNA markers screened by the present invention, starting from the whole genome level, after the discovery and validation phase, revealed for the first time that the expression of piR-2850767, piR-372947, piR-726712, piR-720636, and piR-157618 in the plasma of patients with non-small cell lung cancer and healthy controls, and in the plasma of smokers and never-smokers in healthy controls, showed statistically significant differences, and there was a mediating effect between smoking status and non-small cell lung cancer. The piRNA markers have high sensitivity and high specificity in non-small cell lung cancer risk assessment, have good predictive value, and can be easily detected in peripheral blood samples, showing good application prospects. Therefore, the piRNA markers of the present invention can be used as specific diagnostic markers for non-small cell lung cancer. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 Figure 1 is a volcano plot of plasma piRNA screening for genome-wide association analysis of non-small cell lung cancer and the corresponding screening process (a) and a volcano plot of plasma piRNA screening for smokers vs. non-smokers in healthy control populations and the corresponding screening process (b).

[0029] Figure 2 Venn intersection analysis of differentially expressed plasma piRNAs associated with lung cancer and smoking status.

[0030] Figure 3 The expression levels of piR-2850767 (a), piR-372947 (b), piR-726712 (c), piR-720636 (d) and piR-157618 (e) in the plasma of cancer tissues vs. adjacent tissues.

[0031] Figure 4 The expression levels of piR-2850767 (a), piR-372947 (b), piR-726712 (c), piR-720636 (d) and piR-157618 (e) in plasma before and after surgery. DETAILED DESCRIPTION

[0032] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

[0033] The present invention provides a method for using the piRNA as a plasma-specific piRNA marker for non-small cell lung cancer, wherein the piRNA comprises any one of piR-2850767, piR-372947, piR-726712, piR-720636, and piR-157618.

[0034] The nucleotide sequence of piR-2850767 is shown in SEQ ID NO: 1 (5'-GCUGGGAAGGCCCGGCGGGGAAGGGG-3'), the nucleotide sequence of piR-372947 is shown in SEQ ID NO: 2 (5'-CGGCUGGGAAGGCCCGGCGGGGAAGGGGGCU-3'), the nucleotide sequence of piR-726712 is shown in SEQ ID NO: 3 (5'-GCUGGGAAGGCCCGGCGGGGAAGGGGGCU-3'), the nucleotide sequence of piR-720636 is shown in SEQ ID NO: 4 (5'-ACGCGGGAGACCGGGGUUCGUUUCCCCG-3'), and the nucleotide sequence of piR-157618 is shown in SEQ ID NO: 5 (5'-AGUUGGUCUGAGUGUUGUGGGUUAUUGUUAAG-3').

[0035] The present invention provides a method for screening specific plasma piRNA markers for non-small cell lung cancer, comprising the following steps:

[0036] Step 1: Design and establish a population of 136 pairs of non-small cell lung cancer case controls with age ± 2 years and sex-matched controls; collect relevant information such as the patients' smoking history, obtain peripheral blood from lung cancer patients and healthy controls, and collect peripheral blood from 21 non-small cell lung cancer patients who have undergone lung cancer resection surgery before and one week after surgery, and separate plasma and blood cells from the peripheral blood; use Total RNA was extracted from plasma using the LS lysis buffer pretreatment method combined with miRNeasy Serum / Plasma Kit (catalog no. 217184). 5 μl of plasma total RNA was used as the starting RNA template. Plasma small RNA libraries were constructed according to the instructions for the miRNA Library Kit (QIAGEN, Germany). The small RNA libraries were sequenced on an Illumina second-generation sequencer. The massive data generated by the second-generation sequencer were further analyzed using the CLC Genomics Workbench, and piRNA counts were quantitatively compared to the piRbase v3.0 library.

[0037] Step 2: piRNAs with a count per million (CPM) ≥ 1 in 20% of both lung cancer plasma and healthy control plasma were included in the analysis. The variance stabilizing transformation (VST) method in the DESeq2 software package was used to normalize the plasma piRNA count data from NSCLC patients and healthy controls.

[0038] Step 3: Plasma piRNA count data from lung cancer patients and healthy controls were normalized by VST, and piRNAs associated with lung cancer were screened genome-wide using a logistic model. The screening criterion was that the Bonferroni multi-corrected P value was less than 6.92 × 10 -6 ;

[0039] Step 4: In the healthy control population, unmatched differential analysis was performed using the DESeq2 software package. Based on the criteria of a fold difference > 1 and a multiplicity-corrected FDR value less than 0.05, plasma piRNAs with significant differential expression in smokers (ex-smokers and current smokers) compared with never-smokers were screened to verify the smoking-related plasma piRNAs.

[0040] Step 5: Venn intersection analysis was used to screen the plasma piRNAs obtained in the above steps (2) and (3), and differentially expressed plasma piRNAs that were associated with both lung cancer and smoking status were obtained as candidate piRNAs;

[0041] Step 6: Use the mediation analysis model to evaluate the mediating effect of the screened plasma candidate piRNAs in the association between smoking and lung cancer.

[0042] In step 3, the vst-normalized piRNA data were used as the independent variable, and lung cancer status was used as the dependent variable, with correction for age, sex, body mass index, smoking status, and drinking status.

[0043] In step 6, smoking status was used as the independent variable, lung cancer status was used as the dependent variable, and the vst-standardized piRNA data was used as the mediating factor to adjust for age, sex, body mass index, and drinking status.

[0044] The following are specific embodiments

[0045] Example 1: This example provides a method for screening smoking-related specific plasma piRNA markers for the diagnosis of non-small cell lung cancer

[0046] 1. Experimental Methods

[0047] A total of 136 pairs of non-small cell lung cancer case-control groups were designed and established using age ± 2 years and sex-matched controls. Relevant information such as the patients' smoking history was collected, and peripheral blood was obtained from lung cancer patients and healthy controls. In addition, peripheral blood was collected from 21 non-small cell lung cancer patients who had undergone lung cancer resection surgery before and one week after surgery, and plasma and blood cells were separated from the peripheral blood. Total RNA was extracted from plasma using the LS lysis buffer pretreatment method combined with miRNeasy Serum / Plasma Kit (catalog no. 217184). 5 μl of plasma total RNA was used as the starting RNA template. A plasma small RNA library was constructed according to the instructions for the miRNALibrary Kit (QIAGEN, Germany). The small RNA library was sequenced on an Illumina second-generation sequencer. The massive data generated by the second-generation sequencer were further analyzed using the CLC Genomics Workbench, and piRNA counts were quantitatively compared (piRbase v3.0 library).

[0048] 2. Screening of plasma piRNAs associated with both lung cancer and smoking

[0049] (1) piRNAs with a count per million (CPM) ≥ 1 in 20% of the samples in lung cancer plasma and healthy control plasma were included in the analysis, and the variance stabilizing transformation (VST) method in the DESeq2 software package was used to standardize the plasma piRNA count data of non-small cell lung cancer patients and healthy controls.

[0050] Specifically, the steps for the vst normalization described above are as follows: First, install and load the DESeq2 package, then load the DESeq2 package into your R environment: library(DESeq2). Input data: Two data sets are input: a piRNAcount matrix containing sample IDs and corresponding piRNAcount values, and a data frame containing sample IDs and sample group information (lung cancer status: NSCLC patients or healthy controls). Create a DESeqDataSet object: Use the DESeqDataSetFromMatrix function to create a DESeqDataSet object from the input data. This object will contain all the information needed for subsequent analysis.

[0051] dds<-DESeqDataSetFromMatrix(countData=count_matrix,

[0052] colData=design_table,

[0053] design=~condition)

[0054] Among them, count_matrix is ​​the piRNAcount data matrix, design_table is a data frame containing sample grouping information, and condition is the conditional variable for comparison.

[0055] Perform vst standardization: Use the vst function to perform vst standardization on the DESeqDataSet object:

[0056] vst_dds<-vst(dds,blind=TRUE)

[0057] vst_dds contains the piRNAcount data after vst normalization, which can be used for subsequent differential expression analysis or other statistical tests.

[0058] More specifically, through the above steps, the vst method in the DESeq2 software package can be used to perform vst normalization on the plasma piRNAcount data of non-small cell lung cancer patients and healthy controls, which will help reduce the variability between samples and make subsequent differential expression analysis more accurate and reliable.

[0059] (2) After VST normalization of plasma piRNA count data from lung cancer patients and healthy controls, a logistic model was used to screen piRNAs associated with lung cancer on a genome-wide scale. The screening criterion was that the Bonferroni multi-corrected P value was less than 6.92×10 -6 .

[0060] (3) In the healthy control population, the DESeq2 software package was used to perform unmatched differential analysis. Based on the criteria of difference fold > 1 and multiple correction FDR value less than 0.05, the plasma piRNAs with significant differential expression in smokers (quit smoking + current smoking) compared with never smokers were screened, thereby verifying the plasma piRNAs related to smoking.

[0061] (4) Venn intersection analysis was used to screen the plasma piRNAs obtained in the above steps (2) and (3), and differentially expressed plasma piRNAs that were simultaneously associated with lung cancer and smoking status were obtained as candidate piRNAs.

[0062] (5) A mediation analysis model was used to evaluate the mediating effect of the screened plasma candidate piRNAs in the association between smoking and lung cancer.

[0063] Specifically, a mediation analysis model was used to evaluate the mediating effect of the selected plasma candidate piRNAs on the association between smoking and lung cancer. The specific steps are as follows: First, install and load the mediation package, then load the mediation package into your R environment: library(mediation). Input data: The input data is a data frame containing the sample name and the corresponding confounding variable, lung cancer status, smoking status, and vst-normalized piRNA counts. Mediation effect model construction: A regression model was constructed that included smoking status, lung cancer status, and candidate piRNAs, with smoking status as the independent variable, lung cancer status as the dependent variable, and the candidate piRNA as the mediating variable.

[0064] modelM<-lm(M~X+Covariates,data=DATA)

[0065] modelY<-glm(Y~X+M+Covariates,data=DATA,

[0066] family=binomial("logit")

[0067] model<-mediate(modelM,modelY,treat="X",mediator="M",

[0068] sims = 1000, robustSE = TRUE)

[0069] Among them, DATA is a data frame, M is the mediating variable, X is the independent variable, Y is the dependent variable, and Covariates is the covariate, including age, gender, body mass index, and drinking status.

[0070] Interpretation and verification of results: Based on the results of the mediation effect test, explain the mediating role of the candidate piRNA in the association between smoking and lung cancer. If the mediation effect is significant, it means that the candidate piRNA plays a mediating role in the association between smoking and lung cancer.

[0071] Through the above steps, the mediating effect of the screened plasma candidate piRNAs in the association between smoking and lung cancer can be evaluated, providing new ideas and methods for a deeper understanding of the mechanism of the impact of smoking on lung cancer.

[0072] 3. Experimental Results

[0073] like Figure 1 As shown in a, in the lung cancer case-control population, there were 116 piRNAs with increased expression in the plasma of lung cancer patients compared with the control population (OR>1 and P<6.92×10 -6 ), and 29 genes showed decreased expression (OR < 1 and P < 6.92 × 10 -6 ).like Figure 1 As shown in (b), in the control population, compared with never-smokers, smokers (quit smoking + current smoking) had 10 piRNAs with increased expression in plasma (difference fold > 1 and FDR < 0.05), and 14 piRNAs with decreased expression (difference fold < 1 and FDR < 0.05).

[0074] like Figure 2 As shown in the figure, Venn intersection analysis of the piRNAs discovered above revealed that there were five piRNAs with increased expression in the plasma of lung cancer patients and smokers in the control group (piR-2850767, piR-110504, piR-726712, piR-372947, and piR-88647), and three piRNAs with decreased expression (piR-720636, piR-157618, and piR-143510).

[0075] As shown in Table 1, the above 8 piRNAs were subjected to mediation analysis. The results showed that piR-2850767, piR-372947, and piR-726712 were risk factors for smoking-induced lung cancer, exerting a mediating effect of 28.16% to 35.87%; piR-720636 and piR-157618 were protective factors, exerting a mediating effect of 31.26% and 25.43% respectively.

[0076] Table 1 The mediating effect of plasma candidate piRNAs in the association between smoking and lung cancer

[0077]

[0078] Note: The mediation analysis model was adjusted for age, sex, body mass index, and drinking status, and the mediating factor was the piRNA counts value based on VST standardization.

[0079] Example 2: Evaluation of the predictive ability of piR-2850767, piR-372947, piR-726712, piR-720636 or piR-157618 combined with traditional predictive factors for non-small cell lung cancer

[0080] 1. Experimental Methods

[0081] A logistic prediction model was constructed using the plasma piRNA data extracted from 2-(1) of Example 1 and converted to VST in 136 lung cancer patients and 129 healthy controls. GraphPad Prism (version 8.2.1) was used to plot receiver operating characteristic (ROC) curves. The predictive efficacy of lung cancer was analyzed using traditional predictive factors (age, sex, body mass index, smoking status, and drinking status), piR-2850767, piR-372947, piR-726712, piR-720636, or piR-157618, and the predictive efficacy of individual piRNAs or piRNA combinations combined with traditional predictive factors (additional inclusion of these individual piRNAs or piRNA combinations in the model). In addition, the expression levels of plasma piR-2850767, piR-372947, piR-726712, piR-720636, and piR-157618 were compared before and after surgery in 21 patients with non-small cell lung cancer who underwent lung cancer resection.

[0082] 2. Experimental Results

[0083] As shown in Table 2, compared with traditional predictive factors (age, sex, body mass index, smoking and drinking), the addition of any one or combination of the five piRNA biomarkers significantly increased the ability to predict the risk of non-small cell lung cancer. Among them, the combination of traditional predictive factors with piR-2850767 increased the AUC from 0.649 to 0.886, the combination with piR-372947 increased the AUC to 0.871, the combination with piR-726712 increased the AUC to 0.875, the combination with piR-720636 increased the AUC to 0.786, and the combination with piR-157618 increased the AUC from 0.649 to 0.834. At the same time, the combination with the piRNA combination increased the AUC from 0.649 to 0.926. The plasma expression levels of piR-2850767, piR-372947 and piR-726712 were higher in lung cancer patients than in controls ( Figure 3 ac in the middle), and its plasma expression level was significantly reduced after lung cancer resection ( Figure 4Compared with controls, the expression levels of piR-720636 and piR-157618 in the plasma of lung cancer patients were lower ( Figure 3 d, e), and the expression level of piR-157618 increased after surgery ( Figure 4 In addition, the expression level of plasma piR-720636 did not change significantly between preoperative and postoperative periods, but the median expression level of plasma piR-720636 after surgery was higher than that before surgery ( Figure 4 These results suggest that the expression levels of plasma piR-2850767, piR-372947, piR-726712, piR-720636, and piR-157618 are potential non-small cell lung cancer-specific diagnostic markers that can be conveniently detected in peripheral blood samples and have promising application prospects.

[0084] Table 2 Predictive efficacy of plasma piRNA markers combined with traditional predictive factors for lung cancer

[0085]

[0086]

[0087] It will be easily understood by those skilled in the art that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. Use of plasma-specific piRNA markers in the preparation of reagents for detecting non-small cell lung cancer caused by tobacco exposure, wherein the plasma-specific piRNA comprises at least one of piR-2850767, piR-372947, piR-726712, piR-720636 and piR-157618; The nucleotide sequence of the piR-2850767 is shown in SEQ ID NO: 1, the nucleotide sequence of the piR-372947 is shown in SEQ ID NO: 2, the nucleotide sequence of the piR-726712 is shown in SEQ ID NO: 3, the nucleotide sequence of the piR-720636 is shown in SEQ ID NO: 4, and the nucleotide sequence of the piR-157618 is shown in SEQ ID NO:

5.

2. Use of plasma-specific piRNA markers in the preparation of a kit for detecting non-small cell lung cancer caused by tobacco exposure, wherein the plasma-specific piRNA includes at least one of piR-2850767, piR-372947, piR-726712, piR-720636 and piR-157618; The nucleotide sequence of the piR-2850767 is shown in SEQ ID NO: 1, the nucleotide sequence of the piR-372947 is shown in SEQ ID NO: 2, the nucleotide sequence of the piR-726712 is shown in SEQ ID NO: 3, the nucleotide sequence of the piR-720636 is shown in SEQ ID NO: 4, and the nucleotide sequence of the piR-157618 is shown in SEQ ID NO:

5.

3. A detection kit for non-small cell lung cancer caused by tobacco exposure, characterized in that: The kit includes a plasma-specific piRNA marker, and the plasma-specific piRNA marker includes any one of piR-2850767, piR-372947, piR-726712, piR-720636, and piR-157618; The nucleotide sequence of the piR-2850767 is shown in SEQ ID NO: 1, the nucleotide sequence of the piR-372947 is shown in SEQ ID NO: 2, the nucleotide sequence of the piR-726712 is shown in SEQ ID NO: 3, the nucleotide sequence of the piR-720636 is shown in SEQ ID NO: 4, and the nucleotide sequence of the piR-157618 is shown in SEQ ID NO:

5.

4. A method for screening plasma-specific piRNA markers for non-small cell lung cancer caused by tobacco exposure, characterized in that: The following steps are involved: (1) RNA sequencing was used to detect and compare the count values ​​of plasma piRNA in peripheral blood samples of patients with tobacco-induced non-small cell lung cancer and healthy controls; (2) normalizing the piRNA count values ​​obtained in step (1) and using a logistic model to screen piRNAs associated with non-small cell lung cancer across the entire genome; (3) Unmatched differential analysis was performed using the whole genome differential expression analysis method to screen out plasma piRNAs associated with tobacco exposure in healthy controls based on the criteria of a multiple difference > 1 and a multiple-corrected FDR value less than 0.05; (4) Venn analysis was used to intersect the two types of plasma piRNAs screened in step (2) and step (3), and differentially expressed plasma piRNAs that were simultaneously associated with lung cancer and tobacco exposure were obtained as candidate piRNAs; (5) evaluating the mediation effect of the candidate piRNA obtained in step (4) in the correlation between smoking and tobacco exposure by a mediation effect analysis method, and determining the plasma-specific piRNA markers of non-small cell lung cancer caused by tobacco exposure, wherein the plasma-specific piRNA markers of non-small cell lung cancer caused by tobacco exposure are piR-2850767, piR-372947, piR-726712, piR-720636 and piR-157618; The nucleotide sequence of the piR-2850767 is shown in SEQ ID NO: 1, the nucleotide sequence of the piR-372947 is shown in SEQ ID NO: 2, the nucleotide sequence of the piR-726712 is shown in SEQ ID NO: 3, the nucleotide sequence of the piR-720636 is shown in SEQ ID NO: 4, and the nucleotide sequence of the piR-157618 is shown in SEQ ID NO:

5.

5. A screening system for plasma-specific piRNA markers of non-small cell lung cancer caused by tobacco exposure, characterized in that: include: Plasma piRNA count value acquisition module: used to detect and compare the count values ​​of plasma piRNA in peripheral blood samples of patients with non-small cell lung cancer caused by tobacco exposure and healthy controls using RNA sequencing methods; Non-small cell lung cancer related piRNA screening module: used to standardize the obtained piRNA count values ​​and use the logistic model to screen piRNAs related to non-small cell lung cancer in the whole genome; Tobacco exposure-related plasma piRNA screening module: used to perform unmatched differential analysis using the whole genome differential expression analysis method, and screen out plasma piRNAs associated with tobacco exposure in healthy controls based on the criteria of differential multiple > 1 and multiple corrected FDR value less than 0.05; Candidate piRNA screening module: used to use Venn analysis to intersect the two types of plasma piRNAs screened in step (2) and step (3), and obtain differentially expressed plasma piRNAs that are simultaneously related to lung cancer and tobacco exposure as candidate piRNAs; Analysis module for plasma-specific piRNA markers of non-small cell lung cancer caused by tobacco exposure: used to evaluate the mediation effect of the candidate piRNAs obtained in the correlation between smoking and tobacco exposure through the mediation effect analysis method, and determine the plasma-specific piRNA markers of non-small cell lung cancer caused by tobacco exposure, wherein the plasma-specific piRNA markers of non-small cell lung cancer caused by tobacco exposure are piR-2850767, piR-372947, piR-726712, piR-720636 and piR-157618; The nucleotide sequence of the piR-2850767 is shown in SEQ ID NO: 1, the nucleotide sequence of the piR-372947 is shown in SEQ ID NO: 2, the nucleotide sequence of the piR-726712 is shown in SEQ ID NO: 3, the nucleotide sequence of the piR-720636 is shown in SEQ ID NO: 4, and the nucleotide sequence of the piR-157618 is shown in SEQ ID NO: 5.

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