Methylation detection combined marker based on free DNA in alveolar lavage fluid and application of methylation detection combined marker

Abstract

The invention provides a methylation detection combined marker based on free DNA (cfDNA) in pulmonary alveolar lavage fluid (BAL) and application of the methylation detection combined marker. The methylation combination marker optimizes methylation detection targets in early screening of lung cancer, reduces detection difficulty and cost, and has high diagnosis accuracy, sensitivity and specificity.

Description

Technical Field

[0001] The present invention belongs to the field of biomedical detection technology, and specifically relates to a methylation detection combination marker based on cell-free DNA (cfDNA) in bronchoalveolar lavage fluid (BAL) and its application. Background Art

[0002] As chest CT, especially low-dose spiral CT, becomes increasingly recognized in early lung cancer screening, more and more lung nodules are being discovered clinically. Although imaging features and artificial intelligence technologies provide a valuable basis for differentiating benign from malignant lung nodules, the diagnosis of lung nodules smaller than 2 cm, particularly solid nodules, remains challenging. Finding more efficient diagnostic methods to differentiate between benign and malignant solid nodules is of great clinical significance for the diagnosis of early lung cancer.

[0003] Cell-free DNA (cfDNA) is highly fragmented DNA that exists outside cells. Under certain circumstances, a small amount of cfDNA from "heterogeneous" cells (such as tumor cells or donor cells) can serve as a marker for genetic testing. Currently, "liquid biopsy" technology based on cfDNA testing has garnered significant attention in prenatal diagnosis, cancer screening, early diagnosis, monitoring, and prognostic assessment. Alterations in DNA methylation profiles are characteristic of many tumors and are used in tumor diagnosis and prognostic analysis. In recent years, cfDNA methylation testing has begun to be applied to the diagnosis of various tumors.

[0004] Currently, some studies have reported on the use of cfDNA methylation in the diagnosis of early-stage lung cancer. However, most studies have used peripheral blood samples or resected lung tissue samples for testing, while few have reported on the use of cfDNA methylation testing in bronchoalveolar lavage fluid samples for the diagnosis of peripheral lung nodules. Although peripheral blood samples are simple to obtain, the low amount of tumor-associated DNA input in patients with early-stage lung cancer results in low cfDNA concentrations extracted from peripheral blood samples. This requires a high level of testing depth and technical expertise, and is prone to false negatives.

[0005] In our previous study (Ann Transl Med. 2021;9:1080), we performed routine bronchoscopic cfDNA methylation testing in bronchoalveolar lavage (BAL) fluid (cfDNA) in 48 patients with peripheral pulmonary nodules smaller than 2 cm. The results showed that BAL methylation profiles had an accuracy of 81.3% for distinguishing benign and malignant pulmonary nodules, with a sensitivity and specificity of 81%, both significantly higher than the diagnostic efficiency of plasma. Furthermore, BAL methylation demonstrated a sensitivity of 82.4% in stage I patients. This suggests that cfDNA methylation testing has high clinical value in the diagnosis of peripheral pulmonary nodules. These findings were subsequently confirmed by a research team from West China Hospital, Sichuan University (Clin Epigenetics. 2021;13:185). These studies demonstrate that cfDNA methylation testing in bronchoalveolar lavage fluid (BALF) has promising advantages and application prospects in the diagnosis of early-stage lung cancer.

[0006] Although the inventors' previous studies have confirmed that methylation profile detection of cfDNA in alveolar lavage fluid can be effectively used to distinguish benign from malignant lung nodules, there are still many problems that need further improvement.

[0007] First, the quality control of specimens obtained through alveolar lavage urgently needs to be improved. With conventional bronchoscopy, the distal end of the bronchoscope can only reach the opening of a level 4 bronchus, effectively preventing it from reaching the vicinity of a lung nodule. Consequently, large volumes of fluid (over 100 ml) must be injected during bronchoalveolar lavage. This reduces the reabsorption rate and the concentration and total amount of cfDNA in the alveolar lavage fluid. Furthermore, it can cause localized lung tissue collapse, impairing ventilation and gas exchange. Therefore, the ability to precisely and directly obtain lavage fluid from the local area of ​​a lung nodule, thereby improving specimen quality and, consequently, diagnostic accuracy, is a crucial area requiring optimization.

[0008] Secondly, in previous studies, the inventors examined the methylation profile of cfDNA, revealing 3,421 cancer-related methylation-sensitive regions encompassing 42,176 CpG sites. This significantly increases the difficulty and cost of testing. Optimizing methylation detection targets to reduce the difficulty and cost of testing, while maintaining or even improving test accuracy, is an urgent and crucial issue. Summary of the Invention

[0009] Technical issues

[0010] The present invention is made to solve the problems of low sensitivity and insufficient site combination optimization in the existing technology of cfDNA methylation detection in alveolar lavage fluid.

[0011] Technical Solution

[0012] One object of the present invention is to provide a methylation combination marker, characterized in that the methylation combination marker is composed of the MGC12916 gene, the STAC2 gene, the HECW2 gene, the PPP1R13L gene, the TRIOBP gene and the PITPNM2 gene, wherein the Gene ID of the MGC12916 gene is 84815 (chr17:14212341-14212659), the Gene ID of the STAC2 gene is 342667 (chr17:37381415-37381996), the Gene ID of the HECW2 gene is 57520 (chr2:197457391-197457611), the Gene ID of the PPP1R13L gene is 10848 (chr19:45901589-45901813), and the Gene ID of the TRIOBP gene is 10849 (chr18:45901589-45901814). The ID is 11078 (chr22:38092769-38093209), and the Gene ID of the PITPNM2 gene is 57605 (chr12:123634907-123635137).

[0013] Another object of the present invention is to provide a use of the methylation combination marker in preparing a kit for early screening of lung cancer.

[0014] Furthermore, the kit is used to diagnose benign or malignant peripheral pulmonary nodules.

[0015] Another object of the present invention is to provide a kit for detecting pulmonary nodules, characterized in that the kit comprises a reagent for detecting the methylation level of the above-mentioned methylation combination marker.

[0016] Furthermore, the kit includes sequencing primers for the MGC12916 gene, sequencing primers for the STAC2 gene, sequencing primers for the HECW2 gene, sequencing primers for the PPP1R13L gene, sequencing primers for the TRIOBP gene, and sequencing primers for the PITPNM2 gene.

[0017] Furthermore, the sequencing primers for the MGC12916 gene are: forward primer TGGGTTTTCGCGTATCGACGT, i.e., SEQ ID NO: 1, and reverse primer AGACGAAACCGACGAACTACG, i.e., SEQ ID NO: 2. The sequencing primers for the STAC2 gene are: forward primer TCGGTGGTTCGAGTACGTTCC, i.e., SEQ ID NO: 3, and reverse primer AGACGAAACCGAACTCGAGTAC, i.e., SEQ ID NO: 4. The sequencing primers for the HECW2 gene are: forward primer TCGTTGGTTCGCGTACGTTTC, i.e., SEQ ID NO: 5, and reverse primer AGACGAAACCGACTCGAACTAC, i.e., SEQ ID NO: 6. The sequencing primers for the PPP1R13L gene are: forward primer TCGTTGGTTCGCGTACGTTCG, i.e., SEQ ID NO: 7, and reverse primer AGACGAAACCGACTCGAACTAG, i.e., SEQ ID NO: 8. The sequencing primers for the TRIOBP gene are: forward primer TCGTTGGTTCGCGTACGTTCC, SEQ ID NO: 9, and reverse primer CGAACCCGACTCGAAACGAGT, SEQ ID NO: 10. The sequencing primers for the PITPNM2 gene are: forward primer TCGTTGGTTCGCGTACGTTCG, SEQ ID NO: 11, and reverse primer AGACGAAACCGACTCGAACTAG, SEQ ID NO: 12.

[0018] By using the methylation combination marker, the present invention can construct a six-site cfDNA methylation detection model for the diagnosis of peripheral lung nodules. By using alveolar lavage fluid as the cfDNA methylation detection sample and simultaneously using real-time electromagnetic navigation or virtual electromagnetic navigation technology (ENB or VBN) combined with CBCT for dual guidance and positioning, the quality of the detection sample is improved and the positioning is more accurate.

[0019] In addition, the detection targets of the six-site cfDNA methylation detection model include a combination of the MGC12916 gene, the STAC2 gene, the HECW2 gene, the PPP1R13L gene, the TRIOBP gene, and the PITPNM2 gene. The model can significantly improve detection efficiency and ensure accuracy.

[0020] For patients with clinically implicated pulmonary nodules, where the diagnosis is unclear, this invention uses real-time electromagnetic navigation or virtual electromagnetic navigation (ENB or VBN) combined with CBCT positioning to guide an ultrafine bronchoscope to the bronchioles where the pulmonary nodules are located. After alveolar lavage, cfDNA is extracted from the lavage fluid, and then a six-site methylation test is performed. This six-site methylation detection model is used to differentiate between benign and malignant pulmonary nodules. The specific steps are as follows:

[0021] (1) Combined application of ENB and CBCT: All patients were treated under intravenous combined anesthesia. Thin-slice CT scanning and ENB software import, three-dimensional reconstruction, and navigation path setting and selection were performed before the operation. After ENB or VBN guided the ultra-thin bronchoscope to the target nodule, CBCT was used for precise positioning during the operation.

[0022] (2) Specimen acquisition (lung nodule lavage fluid samples, biopsy specimens): After ENB combined with CBCT reaches the lung nodule, the lung nodule is first lavaged directly with the ENB catheter (40 ml). The lavage fluid is recovered and centrifuged, and the supernatant is stored at -80°C. After lavage, lung biopsy (3-4 pieces) is performed at the lung nodule using biopsy forceps. The biopsy specimens are divided into two parts and sent for histopathology and cryopreserved at -80°C respectively.

[0023] (3) cfDNA extraction: DNA was extracted from pulmonary nodule lavage fluid samples using the QIAamp Circulating Nucleic Acid Kit (Qiagen, Germany). DNA was extracted from lung tissue biopsy specimens using the QIAamp DNA FFPE Tissue Kit (Qiagen, Germany).

[0024] (4) Detection and analysis of methylation profiles: cfDNA was treated with bisulfite to convert all cytosines to uracil. The converted single-stranded DNA molecules were then amplified by PCR for 10 to 14 cycles to form a whole-genome BS-seq library. A custom-designed lung cancer methylation sequencing technology was used for biotinylated RNA enrichment, PCR amplification, target library quantification, and finally sequencing using the NovaSeq 6000. The sequencing primers for each gene are shown in SEQ ID NO: 1 to SEQ ID NO: 12 above.

[0025] Sequencing Data Analysis: Utilizing 3,421 cancer-related methylation-sensitive region markers (containing 42,176 CpG sites) obtained in previous studies, high-throughput sequencing was used to screen six methylation targets highly associated with lung cancer (MGC12916, STAC2, HECW2, PPP1R13L, TRIOBP, and PITPNM2). Principal component analysis (PCA) and heatmap visualization were performed using the R packages "FactoMineR" and "heatmap.plus," respectively. Ultimately, through individual and combined analyses of the six targets, a multi-target methylation diagnostic model was established to determine the benign and malignant nature of lung nodules.

[0026] Beneficial effects

[0027] This invention discloses for the first time a six-site detection model based on cfDNA methylation in alveolar lavage fluid, which has the following effects:

[0028] (1) The quality of test specimens is better. Existing studies have basically used peripheral blood as a specimen for methylation testing. Since the amount of cfDNA in patients with lung nodules is low, the cfDNA content extracted from peripheral blood is not high, and the depth and technical requirements for methylation testing are high, which will result in a certain false negative rate. However, the present invention directly lavages the 7-10 level bronchioles where the target lung nodules are located. The content of cfDNA in the collected alveolar lavage fluid will be higher, and the positive rate will also be correspondingly improved.

[0029] (2) More accurate positioning of lung nodules. Conventional bronchoscopes can generally only reach level 4-5 bronchi for alveolar lavage, requiring a large amount of lavage fluid, resulting in a lower cfDNA concentration. The present invention uses an ultra-fine bronchoscope that can reach level 7-10 bronchioles, getting closer to or directly reaching the site of lung nodules. The required amount of lavage fluid is less, resulting in a higher cfDNA concentration. At the same time, ENB or VBN combined with CBCT is used for dual guidance and positioning, which makes the positioning of target lung nodules more accurate, and the success rate and positive rate are also higher.

[0030] (3) The six-site methylation detection model is simpler and more efficient. Existing methylation detection studies mostly conduct in-depth detection of dozens or hundreds of methylation sites, which requires high technical barriers, is time-consuming, and expensive. The present invention adopts a six-site detection model, which only requires PCR detection of six major methylation sites. It is simple, fast, accurate, significantly improves efficiency, and has stronger clinical feasibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 A diagram showing 2536 regions of 2100 genes detected by the methylation panel of the present invention.

[0032] Figure 2 The heat map results of the six genes of the present invention, MGC12916, STAC2, HECW2, PPP1R13L, TRIOBP, and PITPNM2, are shown.

[0033] Figure 3 The efficacy results of the six methylation genes of the present invention, MGC12916, STAC2, HECW2, PPP1R13L, TRIOBP, and PITPNM2, are shown. DETAILED DESCRIPTION

[0034] The present invention is described below with reference to specific embodiments. It should be noted that the embodiments are merely illustrative and do not limit the present invention in any way.

[0035] Unless otherwise specified, the reagents and equipment used in the present invention can be obtained by purchasing commercial products.

[0036] Example

[0037] 1. Combined application of ENB and CBCT

[0038] For patients with peripheral pulmonary nodules, electromagnetic navigation combined with CBCT is used for localization. Preoperatively, patients undergo a conventional chest CT scan. The scan data is then imported into the electromagnetic navigation device for a virtual navigation simulation to help guide the surgical route. During the procedure, electromagnetic navigation software guides the ultrafine bronchoscope to the pulmonary nodule in real time. A three-dimensional CBCT scan then confirms that the ultrafine bronchoscope has reached the pulmonary nodule. Subsequently, alveolar lavage and pulmonary nodule biopsy are performed.

[0039] 2. Sample Preparation

[0040] After locating the pulmonary nodule under ENB combined with CBCT guidance, 40 ml of room-temperature saline was injected through the operating port of the ultrafine bronchoscope for direct alveolar lavage of the nodule. The lavage fluid was recovered using negative pressure aspiration. Centrifugation was performed within 2 hours (4°C, 1200 bpm, 5 minutes), and the supernatant was stored at -80°C. After lavage, 3-4 lung biopsies were obtained from the nodule using biopsy forceps. The biopsy specimens were divided into two aliquots, which were then sent for histopathology and cryopreserved at -80°C.

[0041] 3. cfDNA Extraction

[0042] DNA was extracted from recovered BALF samples using the QIAamp Circulating Nucleic Acid kit (Qiagen, Germany). The specific steps are as follows:

[0043] Transfer 30µl of Proteinase K to a 2.0ml microcentrifuge tube. Transfer 0.6ml of lavage fluid sample to the microcentrifuge tube containing Proteinase K. Add 0.6ml of Buffer ACL and 5µl of Carrier RNA to the sample and vortex for 15 seconds. Incubate in a 60°C water bath for 15-20 minutes, occasionally inverting the tube to mix thoroughly. Add 0.3ml of isopropanol to the sample and vortex for 15 seconds. Incubate at room temperature for 3 minutes. Place the HiPure Viral Mini Column in a 2ml collection tube. Transfer half the volume (750µl) of the mixture to the column. Centrifuge at 13,000g for 1 minute. Discard the filtrate and return the column to the collection tube. Transfer the remaining mixture to the column. Centrifuge at 13,000g for 1 minute. Discard the filtrate and collection tube. Return the column to a new collection tube. Add 500µl of Buffer GW1 (diluted with ethanol) to the column. Centrifuge at 13,000g for 1 minute. Discard the filtrate and return the column to the collection tube. Add 500µl of Buffer GW2 (diluted with ethanol) to the column. Centrifuge at 13,000g for 1 minute. Discard the filtrate and return the column to the collection tube. Add 500µl of Buffer GW2 (diluted with ethanol) to the column. Centrifuge at 13,000g for 1 minute. Discard the filtrate and return the column to the collection tube. Centrifuge at 13,000g for 2 minutes. Place the column in a new 1.5ml microcentrifuge tube. Dry the column further at 60°C for 5 minutes. Place the column in a new 1.5ml microcentrifuge tube. Add 30-50µl of Buffer AE or sterile water to the center of the column membrane. Let stand for 3 minutes, then centrifuge at 13,000g for 1 minute. Discard the DNA binding column and store the DNA at 2-8°C. For long-term storage, store at -20°C.

[0044] 4. Methylation Detection

[0045] (1) Overview of the experimental process

[0046] The cfDNA of the alveolar lavage fluid obtained above was subjected to bisulfite conversion, DNA purification after conversion, PCR amplification and library construction, high-throughput sequencing, and data analysis.

[0047] (2) Detailed experimental steps

[0048] I. Bisulfite Conversion

[0049] Kit: Burning Rock Sulfite Conversion Reagent (specifically, BR-BS Conversion Reagent)

[0050] Key steps:

[0051] DNA denaturation: Take 5-50 ng cfDNA and add transformation protection solution (containing DNA stabilizer).

[0052] Program: 98°C, 5-10 minutes (to open double-stranded DNA).

[0053] Sulfite treatment: Add sulfite reaction solution (containing sodium bisulfite and free radical scavenger).

[0054] Reaction conditions: 98°C, 45 seconds → 60°C, 60 minutes → multiple cycles (usually 4-6 cycles)

[0055] ·Terminate the reaction: Add binding buffer to terminate the conversion.

[0056] II. Post-transformation DNA purification

[0057] Kit: Burning Stone matching purification magnetic beads (such as BR-BS Purification Beads)

[0058] step:

[0059] Bind the transformed DNA to magnetic beads (under high salt conditions).

[0060] Separate on a magnetic rack and wash twice with 80% ethanol.

[0061] Elution: Elute with low TE buffer or pure water (volume: 10-20 μL).

[0062] Note: Avoid over-drying the beads to avoid DNA breakage.

[0063] III. PCR amplification and library construction

[0064] Kit: Burning Rock Methylation Panel (specifically, a panel targeting methylation sites in specific genes)

[0065] step:

[0066] First round of PCR (target region amplification):

[0067] Primer design: Design corresponding primers based on the gene sequences of the 6 methylation sites.

[0068] MGC12916 (Gene ID: 84815, chr17:14212341-14212659):

[0069] Forward primer TGGGTTTTCGCGTATCGACGT (SEQ ID NO: 1)

[0070] Reverse primer AGACGAAACCGACGAACTACG (SEQ ID NO: 2)

[0071] STAC2 (Gene ID: 342667, chr17:37381415-37381996):

[0072] Forward primer TCGGTGGTTCGAGTACGTTCC (SEQ ID NO: 3)

[0073] Reverse primer AGACGAAACCGAACTCGAGTAC (SEQ ID NO: 4)

[0074] HECW2 (Gene ID: 57520, chr2:197457391-197457611):

[0075] Forward primer TCGTTGGTTCGCGTACGTTTC (SEQ ID NO: 5)

[0076] Reverse primer AGACGAAACCGACTCGAACTAC (SEQ ID NO: 6)

[0077] PPP1R13L (Gene ID: 10848, chr19:45901589-45901813):

[0078] Forward primer TCGTTGGTTCGCGTACGTTCG (SEQ ID NO: 7)

[0079] Reverse primer AGACGAAACCGACTCGAACTAG (SEQ ID NO: 8)

[0080] TRIOBP (Gene ID: 11078, chr22:38092769-38093209):

[0081] Forward primer TCGTTGGTTCGCGTACGTTCC (SEQ ID NO: 9)

[0082] Reverse primer: CGAACCCGACTCGAAACGAGT (SEQ ID NO: 10)

[0083] PITPNM2 (Gene ID:57605, chr12:123634907-123635137):

[0084] Forward primer TCGTTGGTTCGCGTACGTTCG (SEQ ID NO: 11)

[0085] Reverse primer AGACGAAACCGACTCGAACTAG (SEQ ID NO: 12)

[0086] Reaction system: purified DNA (20 μl) + methylated panel primer mix (5 μl) + high-fidelity DNA polymerase (25 μl).

[0087] PCR program: 95°C, 5 min [98°C, 20 s → 60-65°C, 30 s → 72°C, 30 s] × 15-20 cycles, 72°C, 5 min

[0088] Second round of PCR (adding sequencing adapters): Use universal adapter primers with indexes to amplify and construct a complete sequencing library.

[0089] Number of cycles: 6-10 (to avoid bias due to over-amplification).

[0090] Library purification: AMPure XP magnetic beads purification (to remove primer dimers).

[0091] IV. High-throughput sequencing

[0092] Concentration: Qubit quantification.

[0093] Fragment distribution: Agilent 2100 Bioanalyzer (expected peak: 300-500 bp).

[0094] Sequencing platform: Illumina NextSeq 550 / NovaSeq.

[0095] Read length: Paired-end 150 bp (PE150).

[0096] Data volume requirement: Typically ≥10,000× target region coverage depth (to ensure detection of low-frequency methylation signals).

[0097] V. Data Analysis

[0098] UMI error correction: removes PCR duplications and sequencing errors;

[0099] Calculation of methylation levels: Bismark and Bowtie2 were used as alignment tools to calculate the methylation ratio of each CpG site:

[0100] Methylation Level = (number of methylated reads / total number of reads) × 100%

[0101] Report generation: Burning Rock's supporting analysis software (specifically, BR-Report) automatically generates methylation heat maps, differential sites, etc.

[0102] 5. Sequencing Data Analysis

[0103] A total of 2536 regions of 2100 genes were detected by methylation panel. The specific results are as follows Figure 1 shown.

[0104] Subsequently, the six genes with the largest differences were screened out, namely MGC12916, STAC2, HECW2, PPP1R13L, TRIOBP, and PITPNM2. The heat map results of these six genes are as follows Figure 2 shown.

[0105] Experimental example

[0106] The present invention was verified using lavage fluid samples and biopsy samples from 29 cases of pulmonary nodules. Figure 3 As shown, the detection efficiency of the six methylation genes of the present invention are: HECW2 (accuracy 77.9%, sensitivity 46.2%, specificity 100%), MGC12916 (accuracy 80.8%, sensitivity 92.3%, specificity 62.5%), PPP1R13L (accuracy 79.3%, sensitivity 84.6%, specificity 62.5%), STAC2 (accuracy 85.6%, sensitivity 100%, specificity 62.5%), TRIOBP (accuracy 77.4%, sensitivity 84.6%, specificity 75.0%), and PITPNM2 (accuracy 83.2%, sensitivity 75.0%, specificity 84.6%). The efficiency of the six-gene combined detection is: accuracy 95.4%, sensitivity 93.8%, specificity 96.2%.

[0107] Comparative Experimental Example

[0108] Currently, there are only a few studies on the establishment of cfDNA methylation detection models in alveolar lavage fluid.

[0109] (1) Efficacy of the 11-site methylation model of bronchoalveolar lavage fluid (Clin Epigenetics. 2021 Oct 7;13:185): This study established a diagnostic model by detecting 11 methylation sites (CDO1, GSHR, HOXA11, HOXB4-1, HOXB4-2, HOXB4-3, HOXB4-4, LHX9, MIR196A1, PTGER4-1, PTGER4-2), with an area under the curve (AUC) value of 0.82, a specificity of 82%, and a sensitivity of 70%. This study included more methylation sites (11), but the diagnostic sensitivity, specificity, and accuracy were all lower than those of the six-site model of the present invention.

[0110] (2) J Cancer. 2017; 8(17): 3585-91 and Ann Diagn Pathol. 2017; 27: 57-61: These two studies explored the value of RASSF1A and SHOX2 genes in the diagnosis of lung cancer. The results showed that the AUC for methylation of RASSF1A and SHOX2 genes in bronchoalveolar lavage fluid was 0.892, with a sensitivity of 71-81% and a specificity of 90.0%. Although these two studies included fewer methylation sites (2), the sensitivity, specificity, and accuracy of diagnosis were lower than those of the six-site model of the present invention.

[0111] (3) Clin Cancer Res. 2004; 10(7): 2284-8 and MC Cancer. 2010; 10: 600: The AUC for DNA methylation of SHOX2 in bronchial aspirates was 0.86, with a sensitivity of 68% and a specificity of 95%. Another study established a seven-gene model based on PHF11, PDGFRA, TFAP2A, PRR15, HOXA11, TOX2, and TBX15 to diagnose LC patients. The results showed an AUC of 0.87, a sensitivity of 87%, and a specificity of 83.3%. The diagnostic sensitivity, specificity, and accuracy of these two studies were lower than those of the six-locus model of the present invention.

[0112] (4) Detection model of peripheral blood cfDNA (Theranostics. 2019 Apr 6;9:2056-2070): This study screened 9 methylation markers to construct a diagnostic prediction model. The model achieved a sensitivity of 79.5% and a specificity of 85.2% in distinguishing patients with malignant tumors (n = 39) from patients with benign lesions (n ​​= 27). The sensitivity was 75.0% in 20 patients with stage Ia lung cancer and 85.7% in 7 patients with stage Ib lung cancer. The diagnostic sensitivity, specificity, and accuracy of this study were all lower than those of the six-site model of the present invention.

[0113] (5) DNA methylation of CTCs classifies NSCLC subtypes (Transl Lung Cancer Res. 2022;11:224-37): This study found that 5426 differentially methylated CpG sites can distinguish LUAD from lung squamous cell carcinoma (LUSC), 1409 differentially methylated CpG sites can distinguish LUAD from normal tissue, and 2919 differentially methylated CpG sites can distinguish LUSC from normal tissue. The diagnostic accuracy rates were 97.5%, 95.7%, and 100%, respectively. Although the accuracy of this study was higher than that of the six-site model of the present invention, the inclusion of 2919 methylation sites significantly increased the difficulty and cost of detection.

[0114] In summary, the six-site methylation model constructed in the present invention has high diagnostic accuracy, sensitivity and specificity, and only requires the detection of six methylation sites, which has a better cost-effectiveness ratio.

Claims

1. A methylation combination marker for detecting pulmonary nodules, characterized in that: The methylation combination marker consists of MGC12916 gene, STAC2 gene, HECW2 gene, PPP1R13L gene, TRIOBP gene and PITPNM2 gene. Among them, the Gene ID of the MGC12916 gene is 84815, the Gene ID of the STAC2 gene is 342667, the Gene ID of the HECW2 gene is 57520, the Gene ID of the PPP1R13L gene is 10848, the Gene ID of the TRIOBP gene is 11078, and the Gene ID of the PITPNM2 gene is 57605.

2. Use of the methylation combination marker according to claim 1 in preparing a kit for early screening of lung cancer.

3. The use according to claim 2, characterized in that The kit is used for diagnosing benign or malignant peripheral pulmonary nodules.

4. A kit for detecting pulmonary nodules, characterized in that: The kit comprises reagents for detecting the methylation level of the methylation combination marker according to claim 1 .

5. The kit according to claim 4, characterized in that The kit comprises a sequencing primer for the MGC12916 gene, a sequencing primer for the STAC2 gene, a sequencing primer for the HECW2 gene, a sequencing primer for the PPP1R13L gene, a sequencing primer for the TRIOBP gene and a sequencing primer for the PITPNM2 gene.

6. The kit according to claim 5, characterized in that The sequencing primers for the gene are: MGC12916 gene: Forward primer TGGGTTTTCGCGTATCGACGT, i.e. SEQ ID NO: 1, Reverse primer AGACGAAACCGACGAACTACG, i.e. SEQ ID NO: 2, STAC2 gene: Forward primer TCGGTGGTTCGAGTACGTTCC, SEQ ID NO: 3, Reverse primer AGACGAAACCGAACTCGAGTAC, SEQ ID NO: 4, HECW2 gene: Forward primer TCGTTGGTTCGCGTACGTTTC, SEQ ID NO: 5, Reverse primer AGACGAAACCGACTCGAACTAC, ie, SEQ ID NO: 6, PPP1R13L gene: Forward primer TCGTTGGTTCGCGTACGTTCG, ie, SEQ ID NO: 7, Reverse primer AGACGAAACCGACTCGAACTAG, SEQ ID NO: 8, TRIOBP gene: Forward primer TCGTTGGTTCGCGTACGTTCC, ie, SEQ ID NO: 9, Reverse primer CGAACCCGACTCGAAACGAGT, SEQ ID NO: 10, PITPNM2 gene: Forward primer TCGTTGGTTCGCGTACGTTCG, i.e. SEQ ID NO: 11, The reverse primer is AGACGAAACCGACTCGAACTAG, i.e., SEQ ID NO:12.

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