Lung cancer diagnosis marker combination based on RPL32, VEGFB and STRA13 gene variable splicing subtypes and lung cancer detection kit

Abstract

The invention relates to the technical field of molecular diagnosis, in particular to a gene variable splicing subtype marker combination for lung cancer diagnosis and a detection method, and particularly relates to application of specific variable splicing subtypes of RPL32, VEGFB and STRA13 genes in preparation of a lung cancer diagnosis kit. The invention finds that genes related to lung cancer diagnosis are RPL32, VEGFB and STRA13, are novel lung cancer markers screened and verified through high-throughput sequencing, gene expression analysis and qPCR methods, and specifically comprise nucleotide sequences as shown in 1)-3): 1) a primer and a probe of an RPL32 subtype; 2) a PCR primer and a probe of a VEGFB subtype; 3) a primer and a probe of the STRA13 subtype; according to the invention, a diagnosis model with high sensitivity and good specificity is constructed through the specific variable shear subtype marker in the lung cancer, and the method has important value for screening and auxiliary diagnosis of the lung cancer.

Description

Technical Field

[0001] The present invention relates to the field of molecular diagnostic technology, and specifically to a combination of gene variable splicing subtype markers for lung cancer diagnosis and a detection method thereof, and particularly to the use of specific variable splicing subtypes of the RPL32, VEGFB, and STRA13 genes in the preparation of a lung cancer diagnostic kit. Background Art

[0002] Lung cancer, a globally rampant malignant tumor, continues to pose a severe challenge to human health with its high morbidity and mortality rates. According to statistics from the World Health Organization and cancer research institutions in various countries, lung cancer not only ranks first in cancer incidence and mortality in developed countries, but also shows a rapid growth trend in developing countries. This situation urgently requires the medical community and scientific research fields to continuously explore more efficient and accurate lung cancer detection technologies in order to improve the early diagnosis rate and thus effectively reduce the mortality rate of lung cancer.

[0003] Currently, the main methods for detecting lung cancer include LDCT, sputum cytology, histopathology, circulating tumor DNA, etc. However, existing early diagnosis technologies still face many challenges: (1) Imaging screening methods: Low-dose CT (LDCT) as the main screening method can reduce the mortality rate of lung cancer by 20%, but it has obvious limitations: including a high false positive rate (the NLST study showed that 96.4% of positive results were false positives); low diagnostic accuracy for subsolid nodules (SSN) (sensitivity is only 68-75%); radiation exposure risk (annual average effective dose of 1.5 mSv); low cost-effectiveness (320 high-risk people need to be screened for every case of early lung cancer detected), etc. (2) Molecular marker detection: The application of existing molecular markers in early diagnosis has certain limitations, such as poor specificity of protein markers (such as CEA, CYFRA21-1) (<65%); insufficient sensitivity of CTDNA detection (the median VAF of early lung cancer is only 0.1-0.5%); poor stability of miRNA expression profile (different centrifugation conditions can lead to >2-fold differences); lack of reliable biomarkers at the transcriptional regulatory level, etc. (3) Challenges of liquid biopsy technology: As a non-invasive diagnostic method, liquid biopsy still faces the following problems, such as low tumor-derived nucleic acid content (CTDNA only accounts for 0.01-1% of cfDNA); low standardization of sample processing (different storage conditions affect the test results); lack of unified detection thresholds and interpretation standards, etc. (4) Dilemma of multi-omics integrated analysis: There are obstacles to the application of multi-omics technology in early diagnosis, such as immature data integration algorithms (difficulty in normalizing data from different platforms); lack of standardization of bioinformatics analysis processes; and difficulty in clinical translation (large-scale prospective validation is required).

[0004] Summary of technical bottlenecks

[0005] (1) Lack of specific molecular markers for early lung cancer (2) Existing detection methods have insufficient sensitivity (<85%) (3) Liquid biopsy markers are unstable (4) Detection costs are high and difficult to popularize (5) Lack of reliable bioinformatics analysis tools

[0006] Therefore, it is necessary to propose a new lung cancer diagnostic marker and detection kit to solve the above problems. Summary of the Invention

[0007] The present invention aims to solve the problems of insufficient sensitivity and poor specificity in existing lung cancer diagnosis technologies and provide a new diagnostic marker combination based on gene variable splicing isoforms.

[0008] The present invention is achieved through the following technical solutions:

[0009] Marker discovery:

[0010] RNA-seq technology was used to analyze the transcriptome data of 50 pairs of lung cancer tissues and adjacent normal tissues;

[0011] rMATS software was used to identify differentially expressed alternative splicing events (FDR < 0.05);

[0012] The specific splicing isoforms of the RPL32, VEGFB, and STRA13 genes were further confirmed using an independent validation cohort (lung cancer data in the TCGA database).

[0013] Detection system:

[0014] Design primers and probes specific for alternative splicing isoforms:

[0015] RPL32 gene:

[0016] Forward primer: 5'-CTACGGAGGTGGCAGCCAT-3' (SEQ ID NO: 1)

[0017] Reverse primer (intron retention isoform): 5'-CAGATGAATCCCGCAGGAAT-3' (SEQ ID NO: 2)

[0018] Reverse primer (removes intron isoform): 5'-CTGTCGCAGAGTGTCTTCCAA-3' (SEQ ID NO: 3)

[0019] TaqMan probe (intron retention isoform): 5'-FAM-CTCCTTCTCGGTAAGTG-MGB-3' (SEQ ID NO: 4)

[0020] TaqMan probe (intron-removed isoform): 5'-Vic-TCCTTCTCGCTTGCT-MGB-3' (SEQ ID NO: 5)

[0021] VEGFB gene:

[0022] Forward primer: 5'-GAGATGTCCCTGGAAGAACACAG-3' (SEQ ID NO: 6)

[0023] Reverse primer: 5'-CAGGTGTCTGGGTTGAGCTCTA-3' (SEQ ID NO: 7)

[0024] TaqMan probe (full length): 5'-FAM-CAGCCCCGTTCTG-MGB-3' (SEQ ID NO: 8)

[0025] TaqMan probe (exon skipping type): 5'-VIC-CCAGACAGCCCCAG-MGB-3' (SEQ ID NO: 9)

[0026] STRA13 gene:

[0027] Forward primer: 5'-ATGGTGGAGTTGCTGAAGGTCT-3' (SEQ ID NO: 10)

[0028] Reverse primer: 5'-CGTCTTCTGCCTGGGCCT-3' (SEQ ID NO: 11)

[0029] TaqMan probe (full length): 5'-FAM-TCGTTGTGGGTGAGC-MGB-3' (SEQ ID NO: 12)

[0030] TaqMan probe (exon skipping type): 5'-VIC-TCCTTCTCGCTTGCT-MGB-3' (SEQ ID NO: 13)

[0031] A multiplex qPCR detection system was established, and the relative expression level was calculated using the 2^-ΔCT method.

[0032] Diagnostic Model:

[0033] Build a logistic regression model:

[0034] When P≥0.6, it was judged to be positive for lung cancer.

[0035] Compared with existing detection methods, the present invention has the following beneficial effects:

[0036] (1) Clinical validation showed a sensitivity of 92.3% (95% CI: 88.7-94.5%) and a specificity of 95.1%. It can be stably detected in 100 ng of total RNA sample with a detection cycle of <1 hour and a cost reduction of 75% compared to NGS.

[0037] (2) The present invention uses paraffin sections and other methods to extract RNA from samples. A small amount of sample can be used to complete the detection of lung cancer and other tests. The samples are easy to obtain and have universal applicability. The detection is carried out by selecting lung cancer-specific variable splicing subtype markers (RPL32 gene, VEGFB gene and STRA13 gene). Experiments have shown that the specific variable splicing subtype levels of RPL32 gene, VEGFB gene and STRA13 gene in lung cancer tissue can be used to diagnose early lung cancer. At the same time, a joint detection model is constructed by detecting the variable splicing subtypes of the above genes. It has high sensitivity and specificity, and is simple to operate and time-consuming. By setting the detection platform to fluorescent quantitative PCR, the degree of automation is high and the throughput is large, so large-scale screening can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 Schematic diagram of the area under the ROC curve of RPL32 variable splicing isoforms in the experimental examples of the present invention;

[0039] Figure 2 Schematic diagram of the area under the ROC curve of VEGFB alternative splicing isoforms in the experimental examples of the present invention;

[0040] Figure 3 Schematic diagram of the area under the ROC curve of STRA13 alternative splicing isoforms in the experimental examples of the present invention;

[0041] Figure 4 It is a box plot of the model prediction probability values in normal and lung cancer in the experimental example of the present invention;

[0042] Figure 5 Schematic diagram of the area under the ROC curve of the logistic regression model in the experimental example of the present invention. DETAILED DESCRIPTION

[0043] The present invention will be further described in detail below in conjunction with specific embodiments. The examples provided are only for illustrating the present invention and are not intended to limit the scope of the present invention. The examples provided below can serve as a guide for further improvements by those skilled in the art and are not intended to limit the present invention in any way.

[0044] Unless otherwise specified, the experimental methods in the following examples are conventional methods and were performed according to the techniques or conditions described in the literature in the field or according to the product instructions. The materials and reagents used in the following examples, unless otherwise specified, were all commercially available.

[0045] In the following embodiments, the "sample to be tested" refers to the nucleic acid sample to be tested; specifically, the sample to be tested can be RNA such as tissue sections, surgical tissues, biopsy tissues, paraffin-embedded tissues, plasma, serum, whole blood, etc.

[0046] In the following examples, "lung cancer" includes adenocarcinoma and squamous cell carcinoma, which are common malignant tumors of the respiratory tract, particularly non-small cell lung cancer. Early symptoms are subtle, and the time from the onset of cancer development to clinical discovery of a tumor is approximately 5 to 7 years. The five-year survival rate for early-stage lung cancer is over 90%, while for late-stage lung cancer, it is only 10%.

[0047] In the following examples, "target nucleic acid" or "target gene" refers to nucleic acid fragments of alternatively spliced isoforms of three lung cancer-associated genes, namely, isoform-specific fragments of the human RPL32, VEGFB, and STRA13 genes. Highly specific primers were designed to amplify the different target fragments, and highly specific probes were used to identify them. Both primers and probes were designed to be complementary to the sites to be detected.

[0048] In the following examples, a "probe" refers to a single-stranded nucleic acid with a known nucleotide sequence that is substantially complementary to the target nucleic acid and capable of forming a double-stranded structure with the target nucleic acid. The probe can be labeled with a fluorescent moiety at its 5' end and / or a quenching moiety at its 3' end. The binding of the primer and probe to the alternative splicing isoform-specific sequence in the sample cDNA enables the molecular marker to detect the disease—lung cancer.

[0049] In the method of the present invention, the extracted RNA needs to be reverse transcribed into cDNA to obtain the converted DNA fragments as the sample to be tested.

[0050] The method of the present invention is to obtain the CT value of each gene through a quantitative probe PCR amplification reaction, the CT value of the variable splicing subtype of each gene in lung cancer clinical samples and the CT value of the full-length type through a fluorescent signal, and calculate the difference between the CT of different variable splicing subtypes and the CT of the full-length type, that is, to obtain the level of determining the variable splicing subtype of the target gene dCT = 2^-(CT variable splicing subtype-CT full length).

[0051] The dCT value of each target gene was obtained and substituted into the logistic regression model to calculate the final value. Based on the result of the value, it was preliminarily judged whether the tested sample was from a lung cancer patient or a benign disease patient.

[0052] Taking into account the needs of clinical testing, the method of using paraffin tissue sections or plasma testing can effectively reduce harm to patients. When real-time fluorescence PCR is used for detection, the probe is connected with a fluorescent group suitable for judging the variable splicing isoform fragments of different genes. One end of the probe is labeled with a fluorescent group, and the other end is labeled with a quenching group; wherein the quenching group can quench the fluorescence emitted by the fluorescent group. When the PCR amplification reaction is carried out, the forward exo-cutting activity of the polymerase is used to cut off the base with the fluorescent group. The free fluorescent group is no longer affected by the quenching group and can emit a fluorescent signal of a certain wavelength under the action of excitation light. As the PCR product continues to accumulate, the fluorescent signal continues to increase, so that the presence of specific variable splicing isoforms can be detected.

[0053] In the following examples, all patients gave informed consent and the experiments were ethically approved.

[0054] Example 1: Obtaining markers for lung cancer detection

[0055] The inventors of the present invention extracted RNA from lung cancer tissue (i.e., surgical tissue from lung cancer patients (pathologically confirmed, T), serving as tumor-positive samples) and adjacent normal tissue (pathologically confirmed, N), from the same patients during surgery, serving as tumor-negative samples). Using transcriptome sequencing and alternative splicing expression analysis, the inventors combined multiple databases and comprehensive clinical information to conduct large-scale screening and designed probes to detect specific alternative splicing isoforms of genes. By comparing the differences in the levels of alternative splicing isoforms, they obtained markers for lung cancer detection. The markers for lung cancer detection consist of three genes: RPL32 (GeneID: 6161), VEGFB (GeneID: 7423), and STRA13 (GeneID: 8553).

[0056] Based on the nucleotide sequences of the above genes, the primers and probes used in Table 1 were designed and synthesized by Shanghai Bio-Tech Co., Ltd.

[0057] Table 1 Primer and probe sequences for specific gene alternative splicing isoforms

[0058]

[0059] Note: Primer names containing "F" indicate upstream primers, "R" indicate downstream primers, and "FAM" or "VIC" indicate probes; VIC indicates VIC labeling; FAM indicates FAM labeling.

[0060] Example 2: Detection of Gene Variable Splicing Isoforms in Lung Cancer (A) and Adjacent Normal Tissue (C)

[0061] 1. Dilute the upstream primers, downstream primers and probes of RPL32, VEGFB, STRA13 and ACTB in Table 1 with water respectively.

[0062] 2. 51 clinical lung cancer (LUAD) paired samples (lung cancer tissue (indicated by T) and adjacent normal tissue (indicated by N)), 34 benign pulmonary nodule (Benign) paired samples (benign pulmonary nodule tissue (indicated by T) and adjacent normal tissue (indicated by N)), and 3 human lung cancer cell lines (A549 cells, H1975 cells, and H1703 cells, respectively) were homogenized and then total RNA was extracted using an RNA extraction kit (Beijing Tiangen Biochemical Technology (Beijing) Co., Ltd., Cat. # DP439) to obtain total RNA of the samples to be tested.

[0063] 3. Take RNA from the sample to be tested and perform reverse transcription using FastKing One-Step Genomic cDNA First-Strand Synthesis Premix Reagent (Beijing Tiangen Biochemical Technology (Beijing) Co., Ltd., Cat.#DPKR118) to obtain cDNA.

[0064] 4. Prepare the reaction system shown in Table 2 (20 μL in total), in which the template is the cDNA of the sample to be tested; then perform fluorescence PCR amplification according to the reaction procedure. The fluorescence quantitative PCR instrument used is The 96 (Roche Life Science, CH). The reaction procedure was as follows: first stage: 95°C for 1 min, 1 cycle; second stage: 95°C for 10 sec; 60°C for 30 sec; 45 cycles, collecting fluorescence signals, and obtaining the CT values of the RPL32, VEGFB, and STRA13 primer-probe sets, respectively, which were recorded as CT RPL32 -FAM, CT RPL32 -VIC, CT VEGFB -FAM, CT VEGFB -VIC, CT STRA13 -FAM and CT STRA13 -VIC; if the amplification curve is not "S"-shaped or the CT value is blank, the CT value is recorded as 45.

[0065] Table 2. Reaction system

[0066]

[0067] The amplified regions of the primer-probe sets RPL32, VEGFB, and STRA13 are shown in Table 3 .

[0068] Table 3

[0069]

[0070] The CT values of the test results are shown in Table 4. The dCT of each gene was further calculated and recorded as dCT X (dCT X =CT VIC

[0071] / CT FAM ).

[0072] Table 4-1. Detection results of the specific gene RPL32 variable splicing isoform levels in lung tumor tissue (T), adjacent normal tissue (N), benign lung nodule tissue (T) and adjacent normal tissue (N) (partial)

[0073]

[0074]

[0075] Table 4-2. Detection results of specific gene VEGFB alternative splicing isoform levels in lung tumor tissue (T), adjacent normal tissue (N), benign lung nodule tissue (T) and adjacent normal tissue (N) (partial)

[0076]

[0077]

[0078]

[0079] Table 4-3. Detection results of the specific gene STRA13 variable splicing isoform levels in lung tumor tissue (T), adjacent normal tissue (N), benign lung nodule tissue (T) and adjacent normal tissue (N) (partial)

[0080]

[0081]

[0082]

[0083] Establish standards for clinical interpretation of gene alternative splicing isoforms;

[0084] (I) The criteria for determining the level of gene alternative splicing isoforms are as follows:

[0085] 1. The results of the three gene alternative splicing isoforms are expressed as dCT values. A larger dCT value indicates a higher probability of alternative splicing, i.e., a higher level of alternative splicing isoforms, and vice versa. When the CT value is blank or greater than 45, it is marked as 45.

[0086] 2. Interpretation of single-gene alternative splicing results. See Table 5. In this example, the criteria for interpreting RPL32 alternative splicing are: CT ≤ 38 for positive, CT > 38 for negative, and dCT > 1 for a higher prevalence of intron retention isoforms, indicating intron retention in RPL32. The criteria for interpreting VEGFB are: CT ≤ 38 for positive, Cp > 38 for negative, and dCT > 1 for a higher prevalence of exon skipping isoforms, indicating exon skipping in VEGFB. The criteria for interpreting STRA13 alternative splicing are: CT ≤ 38 for positive, CT > 38 for negative, and dCT > 1 for a higher prevalence of exon skipping isoforms, indicating exon skipping in STRA13. The sensitivity and specificity of RPL32, VEGFB, and STRA13 alternative splicing isoforms for diagnosing lung cancer were 83.3%, 78.3%, and 76.7%, respectively, and 85.0%, 80.0%, and 81.0%, respectively.

[0087] The receiver operating characteristic (ROC) curve evaluated the ability of RPL32, VEGFB, and STRA13 variable splicing to diagnose lung cancer; among them, the area under the ROC curve (AUC) of RPL32 variable splicing isoforms in diagnosing lung cancer was 0.89, p < 0.001 (see Figure 1 The area under the ROC curve (AUC) for VEGFB variable splicing isoforms in diagnosing lung cancer was 0.84, with p < 0.001 (see Figure 2 The area under the ROC curve (AUC) of STRA13 variable splicing isoforms for diagnosing lung cancer was 0.83, with p < 0.001 (see Figure 3 The AUC for each gene's alternative splicing isoform in diagnosing lung cancer was between 0.8 and 0.9, indicating good diagnostic ability.

[0088] 3. The interpretation criteria for the results of the combined detection of three genes with variable splicing are as follows:

[0089] The three genes RPL32, VEGFB, and STRA13 were combined to calculate the predicted probability using logistic regression. The present invention incorporates the dCT values of the alternative splicing results of the three genes RPL32, VEGFB, and STRA13 as variables into the model, constructing a logistic regression formula. Based on the formula (model), a value for predicting the probability of lung cancer was obtained. A P value was then calculated for each subject based on the results of the three alternative splicing isoforms.

[0090] The boxplots of the model's predicted probability values for benign lesions and lung cancer are shown in Figure 4 The area under the ROC curve (AUC) of the model for diagnosing lung cancer was 0.96, with p < 0.0001 (see Figure 5The model achieved an AUC greater than 0.9 for lung cancer diagnosis, demonstrating excellent diagnostic performance. Based on the Youden Index maximization principle, the results were interpreted as P > 0.6 for a positive diagnosis, indicating a high risk of lung cancer, and P ≤ 0.5 for a negative diagnosis, indicating a low risk of lung cancer. The sensitivity and specificity for lung cancer diagnosis were 92.3% and 95.1%, respectively.

[0091] Table 5 Critical values, sensitivity and specificity of single gene variable splicing for diagnosis of lung cancer

[0092]

[0093]

Claims

1. A lung cancer diagnostic marker combination and lung cancer detection kit based on alternative splicing isoforms of the RPL32, VEGFB, and STRA13 genes; The combined marker consists of the RPL32 gene, the VEGFB gene, and the STRA13 gene; The GENEID of the RPL32 gene is 6161, the transcript of the alternative splicing isoform is ENST00000435983.5, and the alternative splicing isoform is intron retention. The GENEID of the VEGFB gene is 7423, the transcript of the alternative splicing isoform is ENST00000309422.6, and the alternative splicing isoform is exon skipping. The GENEID of the STRA13 gene is 8553, the transcript of the alternative splicing isoform is ENST00000584347.1, and the alternative splicing isoform is exon skipping.

2. A kit for screening lung cancer, comprising a detection reagent for the combined marker according to claim 1.

3. The kit according to claim 2, wherein: The detection reagents of the combination marker include a primer probe set for detecting RPL32 variable splicing isoforms, a primer probe set for detecting VEGFB variable splicing isoforms, and a primer probe set for detecting STRA13 variable splicing isoforms.

4. The kit according to claim 3, wherein: The primer probes for detecting RPL32 variable splicing isoforms are RPL32, RPL32-FAM, and RPL32-VIC; the primer probes for detecting VEGFB variable splicing isoforms are VEGFB, VEGFB-FAM, and VEGFB-VIC; the primer probe set for detecting STRA13 variable splicing isoforms is STRA13, STRA13-FAM, and STRA13-VIC; The primer probe set RPL32 consists of RPL32-F shown in SEQ ID NO. 1, RPL32-R1 shown in SEQ ID NO. 2 (intron retained), RPL32-R2 shown in SEQ ID NO. 3 (no intron), the primer probe RPL32-FAM shown in SEQ ID NO. 4, and the primer probe RPL32-VIC shown in SEQ ID NO. 5; the primer probe set VEGFB consists of VEGFB-F shown in SEQ ID NO. 6, VEGFB-R shown in SEQ ID NO. 7, the primer probe VEGFB-FAM shown in SEQ ID NO. 8, and VEGFB-VIC shown in SEQ ID NO. 9; The primer probe set STRA13 consists of STRA13-F shown in SEQ ID NO.10, STRA13-R shown in SEQ ID NO.11, the primer probe STRA13-FAM shown in SEQ ID NO.12, and STRA13-VIC shown in SEQ ID NO.

13.

5. The kit according to claim 4 or 7, characterized in that One end of each probe has a fluorescent label.

6. The kit according to claim 2, wherein: The test object of the kit is total RNA from lung tissue. The kit according to claim 2, characterized in that when a primer probe combination is used for lung cancer diagnosis, a logistic regression is used to calculate a prediction probability model for a primer probe set for detecting RPL32 variable splicing isoforms, a primer probe set for detecting VEGFB variable splicing isoforms, and a primer probe set for detecting STRA13 variable splicing isoforms. By constructing a logistic regression model, a prediction formula is established to interpret the results of diagnosing lung cancer gene variable splicing, as follows: The expression results of RPL32, VEGFB and STRA13 genes and the CT values of the variable splicing subtypes were included as variables in the logistic regression prediction probability model to establish a prediction formula and interpret the results of the variable splicing subtypes of lung cancer genes.

7. Use of the PCR primer-probe combination for diagnosing lung cancer gene variable splicing isoforms according to claim 3 in preparing a kit for detecting lung cancer.

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