Platelet marker for detecting lung cancer and detection kit

Abstract

The invention belongs to the field of lung cancer detection, and particularly relates to a platelet marker for detecting lung cancer and a detection kit. The method comprises the following steps: firstly, carrying out transcriptome sequencing on platelets of a healthy (HC) individual and a lung cancer (Lung) individual, then, carrying out differential expression analysis to identify genes which are specifically and differentially expressed in the platelets of a lung cancer patient for the first time, and screening out ZYX, GMPR, RPL9 and RPL11 genes. A logistic regression model is constructed based on mRNA expression levels of the four genes, and in subject working characteristic curve analysis of a training set, the area under a curve is up to 0.97. The application of mRNA expression levels of platelet genes ZYX, GMPR, RPL9 and RPL11 in diagnosis of lung cancer is defined mainly in a liquid biopsy mode, the marker is used for predicting occurrence of the lung cancer, and the invention aims to identify a new marker of the lung cancer and prepare a lung cancer diagnosis kit based on the marker.

Description

Technical Field

[0001] The present invention belongs to the field of lung cancer detection, and in particular relates to a platelet marker and a detection kit for detecting lung cancer. Background Art

[0002] Lung cancer (LC) is one of the malignant tumors with the highest morbidity and mortality rates worldwide. It is divided into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). According to the latest statistics, there will be approximately 2.481 million new cases of lung cancer in the world in 2022, with a mortality rate of approximately 1.817 million, accounting for 18.7% of all cancer deaths. In my country, there will be approximately 1.061 million new lung cancer patients and approximately 715,000 deaths in 2022, ranking first in both morbidity and mortality. The 5-year survival rate of lung cancer is relatively low, at approximately 19.7%. At present, the main treatment methods include surgical resection, radiotherapy and chemotherapy, targeted therapy, and immunotherapy, but Chinese lung cancer patients are mainly in the middle and late stages when diagnosed, resulting in a sharp increase in the mortality rate in my country. Therefore, improving the early diagnosis rate is the main way to fundamentally improve the 5-year survival rate of lung cancer. There are existing lung cancer markers, such as tumor mutation burden (TMB) and tumor infiltrating lymphocytes (TILs), but there is no unified detection standard and there is heterogeneity. Due to the limitations of existing biomarkers, there is an urgent need to develop more sensitive and specific detection methods to achieve early diagnosis and personalized treatment of lung cancer and improve patient survival.

[0003] In recent years, liquid biopsy as a non-invasive detection method has provided an important tool for early diagnosis, prognosis assessment and treatment monitoring of cancer. It is highly stable, comes from peripheral blood, is easy to collect, is non-invasive and repeatable, and can integrate a variety of tumor signals to reflect the dynamic progression of the tumor. In addition, platelets can protect CTCs from attacks by the immune system, while promoting their adhesion to the vascular endothelium and enhancing their metastatic ability. They can also actively absorb RNA molecules (such as miRNA, mRNA) released by tumors, or obtain tumor-specific RNA through direct contact with tumor cells, which can be used to distinguish tumor patients from healthy individuals. Therefore, platelets have unique advantages in liquid biopsy and can be used for early diagnosis, typing, treatment monitoring and prognosis assessment of tumors, and are currently receiving widespread attention.

[0004] The inability to effectively detect cancer at an early stage is a major challenge for lung cancer markers. Based on the above problems, it is particularly important to find new, more convenient and efficient lung cancer tumor markers.

[0005] Therefore, based on this, the technical solution of the present invention is proposed. Summary of the invention

[0006] In order to solve the problems existing in the prior art, the present invention provides a platelet marker for detecting lung cancer, wherein the platelet marker includes ZYX, GMPR, RPL9 and RPL11.

[0007] Based on the same technical concept, another embodiment of the present invention is to provide a use of a platelet marker in preparing a kit for detecting lung cancer, wherein the platelet marker includes ZYX, GMPR, RPL9 and RPL11.

[0008] Based on the same technical concept, another embodiment of the present invention is to provide a detection kit for lung cancer, wherein the detection kit comprises detection reagents for detecting platelet markers, and the platelet markers include ZYX, GMPR, RPL9 and RPL11.

[0009] Preferably, the detection reagent is a primer, and the primer is used to detect the expression level of ZYX, GMPR, RPL9 and RPL11.

[0010] Preferably, the detection kit also includes cDNA of the sample to be tested, DNA polymerase, four deoxynucleotide triphosphates, SYBR Green I, Mg 2+ , buffer, enzyme-free water, EDTA reagent, Trizol reagent and primers of internal reference genes GAPDH and β-actin.

[0011] Preferably, the sample to be tested is a human blood sample.

[0012] In the present invention, the combination of ZYX, GMPR, RPL9 and RPL11 genes is used as a new target for lung cancer diagnosis by the following method:

[0013] (1) Collect, separate and extract platelet samples from patients;

[0014] (2) Extraction and quality control of platelet RNA;

[0015] (3) Construction of RNA-seq library of platelet samples and sequencing analysis of ZYX, GMPR, RPL9 and RPL11 gene expression;

[0016] (4) The expression levels of ZYX, GMPR, RPL9 and RPL11 genes were measured in additional healthy subjects and lung cancer patients.

[0017] The beneficial effects of the present invention are:

[0018] By analyzing the platelet transcriptomes of healthy (HC) individuals and lung cancer (Lung) individuals, it was found that the ZYX, GMPR, RPL9 and RPL11 genes were significantly different in cancer patients, and the diagnostic model constructed by the above four genes showed excellent performance. This model not only showed high sensitivity and specificity in distinguishing HC individuals from Lung individuals, but also achieved an accuracy of more than 95% in independent training sets, showing its great potential in clinical applications. The present invention mainly detects the expression of platelet ZYX, GMPR, RPL9 and RPL11 genes in the patient's peripheral blood to determine the occurrence of lung cancer in order to achieve the purpose of early screening. Moreover, the molecular mechanisms of these genes in the study of the occurrence of lung cancer mechanisms have not been fully revealed, and have not yet been applied in the development of diagnostic reagents. The combination of these genes is expected to provide a new strategy for the diagnosis of lung cancer.

[0019] That is, the present invention has constructed a lung cancer diagnosis application based on a group of genes including platelet ZYX, GMPR, RPL9 and RPL11 through large-sample clinical research, which overcomes many limitations of current lung cancer markers, opens up a new model for early diagnosis and exploration of lung cancer, and provides the possibility to fundamentally improve the difficulties in early diagnosis of lung cancer and the prognosis of lung cancer patients, which is conducive to clinical promotion and application. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 This is the result diagram of genes that are significantly differentially expressed in platelets between HC individuals and Lung individuals, screened out through differential expression analysis.

[0022] Figure 2 This is the result of univariate logistic regression analysis of differentially expressed genes.

[0023] Figure 3 This is the result of the multi-factor Lasso regression screening model analysis of the four genes with the largest odds ratio among the differentially expressed genes.

[0024] Figure 4 This is the result diagram of genes that are significantly differentially expressed in platelets between HC individuals and Lung individuals, screened out through differential expression analysis.

[0025] Figure 5This is a graph showing the differential expression of ZYX in platelets of HC individuals (n=55) and Lung individuals (n=59) obtained by transcriptome sequencing (Wilcoxon rank sum test was used for statistics, ****P<0.0001).

[0026] Figure 6 This is a graph showing the difference in expression of GMPR in platelets of HC individuals (n=55) and Lung individuals (n=59) obtained by transcriptome sequencing (Wilcoxon rank sum test was used for statistics, ****P<0.0001).

[0027] Figure 7 This is a graph showing the differential expression of RPL9 in platelets of HC individuals (n=55) and Lung individuals (n=59) obtained by transcriptome sequencing (Wilcoxon rank sum test was used for statistics, ****P<0.0001).

[0028] Figure 8 This is a graph showing the differential expression of RPL11 in platelets of HC individuals (n=55) and Lung individuals (n=59) obtained by transcriptome sequencing (Wilcoxon rank sum test was used for statistics, ****P<0.0001).

[0029] Fig. 9 The expression level of ZYX in platelets of HC individuals (n=15) and Lung individuals (n=15) obtained by RT-qPCR (Wilcoxon rank sum test was used for statistics; ****P<0.0001).

[0030] Fig.10 The expression level of GMPR in platelets of HC individuals (n=15) and Lung individuals (n=15) obtained by RT-qPCR (Wilcoxon rank sum test was used for statistics; ****P<0.0001).

[0031] Fig.11 The expression level of RPL9 in platelets of HC individuals (n=15) and Lung individuals (n=15) obtained by RT-qPCR (Wilcoxon rank sum test was used for statistics; ****P<0.0001).

[0032] Fig.12 The expression level of RPL11 in platelets of HC individuals (n=15) and Lung individuals (n=15) obtained by RT-qPCR (Wilcoxon rank sum test was used for statistics; ****P<0.0001).

[0033] Fig.13It is the ROC curve of the multi-factor logistic regression model constructed by integrating the expression levels of the two genes GMPR and RPL11 in the training set (the X-axis represents the true negative rate, that is, specificity %; the Y-axis represents the true positive rate, that is, sensitivity %).

[0034] Fig.14 It is the ROC curve of the multi-factor logistic regression model constructed by integrating the expression levels of the two genes ZYX and RPL9 in the training set (the X-axis represents the true negative rate, that is, specificity %; the Y-axis represents the true positive rate, that is, sensitivity %). DETAILED DESCRIPTION

[0035] To make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other implementation methods obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0036] Note: Unless otherwise specified, the materials and reagents used in this example can be obtained from commercial sources.

[0037] In addition, in order to screen new highly specific markers that can diagnose lung cancer, the present invention studied the peripheral whole blood of 114 patients (55 HC individuals and 59 Lung individuals) collected from West China Hospital of Sichuan University. The collected whole blood was stored in a 10 ml EDTA-coated BD vacuum blood collection tube containing the anticoagulant EDTA. EDTA inhibits the immediate activation and aggregation of platelets through calcium chelation, thereby blocking the coagulation cascade reaction. In order to minimize the degradation of platelet RNA, whole blood stored in vacuum tubes needs to be separated within 6 hours at room temperature or 4°C.

[0038] 1. Collection and storage of platelets

[0039] The venous blood of the subjects was collected in a 10 mL anticoagulant tube and centrifuged to separate platelets within 2 hours at room temperature. First, centrifuge at 120g for 20 minutes at room temperature to separate into two layers. The upper platelet-rich plasma was transferred to a new EP tube (note that part of the plasma should be retained when aspirating, not all), and then centrifuged at 360g for 20 minutes. The precipitate is the platelet, which was washed twice with PBS and RNA was extracted after adding 300 μL of DEPC water.

[0040] (II) Platelet RNA extraction (blood total RNA rapid extraction kit, BioTeKe)

[0041] (1) Add 900 μL of lysis buffer to the platelet suspension and lyse by pipetting;

[0042] (2) Centrifuge at 12,000 rpm for 10 min at 4°C and transfer the supernatant to a new enzyme-free EP tube;

[0043] (3) Add 180 μL of chloroform, vortex for 15 seconds, and incubate at room temperature for 10 minutes;

[0044] (4) Centrifuge at 12000 rpm for 10 min at 4°C and collect the upper aqueous phase;

[0045] (5) Add an equal volume of 70% ethanol, invert to mix, and transfer to adsorption column RA;

[0046] (6) Centrifuge at 1000 rpm for 3 min and discard the waste liquid;

[0047] (7) Add 500 μL of deproteinized solution RE, centrifuge at 12000 rpm for 3 min, and discard the waste liquid;

[0048] (8) Add 700 μL of RE rinse solution, centrifuge at 12000 rpm for 3 min, and discard the waste liquid;

[0049] (9) Add 500 μL of RE rinse solution for a second rinse, centrifuge at 12000 rpm for 3 min, and discard the waste liquid;

[0050] (10) Centrifuge at 12000 rpm for 5 min and discard the remaining liquid;

[0051] (11) Place the adsorption column RA into a new enzyme-free EP tube, add 30 μL of RNase free water that has been heated to 56°C, and centrifuge at 12,000 rpm for 3 min to collect platelet RNA;

[0052] (12) RNA quality control testing was performed using Agilent 2100. Only samples with a RIN > 7 and a total amount ≥ 10 pg were defined as qualified quality control specimens and could be used for subsequent sequencing.

[0053] (III) Platelet sample RNA-seq library construction and sequencing

[0054] Sequencing strategy: Hiseqxten, PE151 sequencing; Library construction process: Transcriptome library construction, firstly, the qualified samples were digested with DNase I, then the mRNA was separated with oligo(dT) magnetic beads, the mRNA was broken into certain fragments by ultrasound, cDNA was synthesized, and then the DNA fragment ends were repaired, "A" was added to the 3' end of the fragment, and then the library adapter was connected, PCR was performed, and the hybridization library was constructed.

[0055] (IV) Platelet RNA-seq raw data processing

[0056] First, the raw data images obtained by sequencing were converted into standard Fastq format sequence information with double-end 150 base pair pairing using Illumina's bcl2fastq software. Then, the raw RNA sequencing reads data were strictly quality controlled using TrimGalore (v0.6.7) software, including the removal of low-quality data and trimming and shearing of adapter sequences to improve data quality. Subsequently, the cleaned reads were accurately aligned to the human reference genome (GRCh38) using HISAT2 (v2.2.1). Finally, featureCounts (v2.0.0) software was used in combination with the NCBI gene annotation gtf file GRCh38.84 version to calculate the number of reads mapped on genomic features (such as genes, exons, promoters, etc.).

[0057] (V) Data Analysis

[0058] The present invention uses edgeR (v3.40.2) to perform statistical tests between HC individual platelets and Lung individual platelets. The present invention sets the threshold of logFC (log-fold change) to 1 to ensure the significance of gene expression changes; at the same time, the threshold of logCPM (log-counts per million) is set to 3 to exclude the interference of low-expression genes. In addition, the present invention uses FDR (false discovery rate) correction and sets the threshold to 0.05 to control the false positive rate caused by multiple comparisons. The present invention also excludes genes located on the Y chromosome and limits the analysis objects to protein-coding genes to ensure the biological significance and clinical relevance of the research results. After this series of screening conditions, we finally identified a series of genes that were significantly upregulated or downregulated in lung cancer platelets (such as Figure 1 ), and a univariate regression analysis was performed (as shown in Figure 2 This provides a new perspective for the diagnosis of lung cancer.

[0059] In order to evaluate the relationship between the mRNA expression level of a single gene and the binary dependent variable (lung cancer and health), this example performed a single factor Lasso regression screening analysis on the genes that were significantly upregulated or downregulated in lung cancer. Among these genes, ZYX, GMPR, RPL9 and RPL11 genes showed an odds ratio that was significantly better than other genes (such as Figure 3This indicates that the expression levels of ZYX and GMPR genes in HC individuals are significantly increased compared with those in Lung individuals, and the expression levels of RPL9 and RPL11 genes in HC individuals are significantly decreased compared with those in Lung individuals, and their expression changes have a strong predictive ability for the occurrence of lung cancer. The differential expression of the four genes in different individuals can also be intuitively observed through the heat map (as shown in Figure 2). Figure 4 shown).

[0060] In this example, the above platelet transcriptome data were used to normalize the gene expression values ​​with the platelets of HC individuals as the control, and the expression levels of ZYX, GMPR, RPL9 and RPL11 in HC individuals and lung individuals were calculated (the results are shown in Figures 5 to 8 ZYX and GMPR were significantly upregulated in platelets from HC individuals, whereas RPL9 and RPL11 were significantly downregulated in platelets from Lung individuals.

[0061] (VI) Verification of the expression levels of ZYX, GMPR, RPL9 and RPL11 in platelets of clinical samples

[0062] In the present invention, according to the above-mentioned platelet separation method, additional platelet samples from 15 HC individuals and 15 Lung individuals were collected. Furthermore, in this example, the expression levels of ZYX, GMPR, RPL9 and RPL11 in these samples were detected using RT-qPCR technology. Table 1 below shows the primers used.

[0063] Table 1

[0064]

[0065] The results are as follows Figures 9 to 12 As shown, the mRNA expression levels of ZYX and GMPR in platelets of Lung individuals were increased, while the mRNA expression levels of RPL9 and RPL11 were significantly decreased compared with those of HC individuals.

[0066] (VII) ROC performance test

[0067] The differences in the mRNA expression levels of ZYX, GMPR, RPL9 and RPL11 in platelets between HC individuals and lung individuals were evaluated by using the receiver operating characteristic curve (ROC) and its area under the curve (AUC), and the test efficiency was further evaluated.

[0068] First, the transcriptome data of platelets in 114 patients were used as training sets, and a univariate logistic regression model was constructed based on the expression levels of GMPR and RPL11 to predict the occurrence of lung cancer. In the training set, these univariate regression models performed well, with AUC values ​​reaching above 0.97 (e.g. Fig.13 In addition, a univariate logistic regression model was constructed based on the expression levels of ZYX and RPL9 to predict the occurrence of lung cancer. In the training set, these univariate regression models performed well, with AUC values ​​exceeding 0.97 (as shown in Figure 2). Fig.14 These results fully confirm the strong ability and stability of platelet genes ZYX, GMPR, RPL9 and RPL11 in lung cancer prediction.

[0069] (VIII) Conclusion

[0070] The present invention has found through research that ZYX and GMPR genes are lowly expressed in platelets in HC individuals and highly expressed in lung individuals; while RPL9 and RPL11 genes are highly expressed in platelets in HC individuals and lowly expressed in lung individuals. The mRNA expression levels of ZYX, GMPR, RPL9 and RPL11 were detected in HC individuals and lung individuals using real-time quantitative polymerase chain reaction (RT-qPCR) technology. Then, a logistic regression model was constructed based on the expression levels of ZYX, GMPR, RPL9 and RPL11 genes. The model was subjected to ROC analysis in the training set, and the results showed that the AUC value was as high as 0.97.

[0071] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A platelet marker for detecting lung cancer, characterized in that: The platelet markers include ZYX, GMPR, RPL9 and RPL11.

2. Use of platelet markers in the preparation of a kit for detecting lung cancer, characterized in that: The platelet markers include ZYX, GMPR, RPL9 and RPL11.

3. A detection kit for lung cancer, characterized in that: The detection kit includes detection reagents for detecting platelet markers, and the platelet markers include ZYX, GMPR, RPL9 and RPL11.

4. The detection kit according to claim 3, characterized in that The detection reagent is a primer, and the primer is used to detect the expression levels of ZYX, GMPR, RPL9 and RPL11.

5. The detection kit according to claim 3, characterized in that The detection kit also includes a sample cDNA to be tested, DNA polymerase, four deoxynucleotide triphosphates, SYBR Green I, Mg 2+ , buffer, enzyme-free water, EDTA reagent, Trizol reagent and primers of internal reference genes GAPDH and β-actin.

6. The detection kit according to claim 5, characterized in that The sample to be tested is a human blood sample.

Images