Application of serum exosome lncRNA in preparation of detection product for immune checkpoint inhibitor associated pneumonia

Abstract

The invention provides an application of a serum exosome lncRNA in preparation of a detection product for immune checkpoint inhibitor associated pneumonia, and the serum exosome lncRNA is TTC9-DT, or TTC9-DT and ITGA2-AS1. The invention also provides an application of the serum exosome lncRNA in preparation of a detection product for immune checkpoint inhibitor associated pneumonia. By using the serum exosome lncRNA disclosed by the invention, the sensitivity, the specificity and the accuracy of immune checkpoint inhibitor-related pneumonia diagnosis can be remarkably improved, and compared with a clinical conventional non-specific blood index, the serum exosome lncRNA disclosed by the invention has a better diagnosis effect. In addition, detection can be carried out in a liquid biopsy mode, the method has the advantages of being minimally invasive, capable of achieving real-time monitoring and the like, a detection reagent is low in cost and high in universality, efficient clinical diagnosis and identification can be carried out, the early diagnosis rate is increased, and the method has high clinical application value and wide application prospects.

Description

Technical Field

[0001] This invention relates to the field of molecular detection technology, and more specifically, to the application of serum exosomal lncRNA in the preparation of detection products for immune checkpoint inhibitor-associated pneumonia. Background Technology

[0002] Immune checkpoint inhibitors (ICIs), such as anti-programmed cell death 1 (PD-1) and anti-programmed cell death ligand 1 (PD-L1) antibodies, can enhance the body's immune system to produce anti-tumor therapeutic effects. However, they can also lead to unexpected immune-related adverse events (irAEs), among which immune checkpoint inhibitor-associated pneumonia (CIP) is one of the most serious and potentially life-threatening complications. CIP occurs in up to 19% of patients and accounts for 35% of deaths in patients receiving anti-PD-1 / PD-L1 inhibitor therapy. Early diagnosis and timely treatment can effectively reverse CIP progression and significantly reduce mortality, but the lack of specific diagnostic methods makes accurate diagnosis and timely intervention a major challenge.

[0003] Diagnosing CIP is complex and typically requires multidisciplinary collaboration, including clinical assessment, imaging studies, and sometimes pathological examination. However, both computed tomography (CT) and pathological examination lack specific features, making differential diagnosis challenging. Furthermore, CT scans are often difficult to perform in critically ill patients or in areas with insufficient medical facilities. Therefore, easily implemented, non-invasive, and specific diagnostic tools, such as peripheral blood biomarkers, are crucial for CIP diagnosis. Currently, routine clinical biomarkers such as C-reactive protein (CRP), neutrophil count (NEU), lymphocyte count (LYM), neutrophil-to-lymphocyte ratio (NLR), and interleukin-6 (IL-6) lack specificity and sensitivity in CIP diagnosis. Therefore, early detection and accurate diagnosis of CIP are essential for effective management.

[0004] Exosomes (EVs) are small vesicles carrying proteins, lipids, and nucleic acids (including long non-coding RNAs, lncRNAs) and are involved in immune regulation and cancer. Therefore, exosomes released under pathological conditions tend to carry disease-specific content, making them valuable biomarkers. Studies have shown that EV-derived lncRNAs have the potential to be diagnostic and prognostic biomarkers in a variety of diseases and cancers. Specific EV-derived lncRNAs, such as LINC00265, LINC00467, and UCA1, have been identified as potential biomarkers for the diagnosis and treatment monitoring of acute myeloid leukemia. Similarly, EV-derived lncRNAs have shown value in the diagnosis of gastric cancer, and EVs also play an important role in lung diseases such as asthma, chronic obstructive pulmonary disease (COPD), and idiopathic lung disease.

[0005] However, the application of serum EV-derived lncRNAs in the diagnosis of CIP remains underexplored. Given the urgent need for early and accurate biomarkers for the management of CIP, it is crucial to investigate the potential of serum EV-derived lncRNAs as diagnostic and prognostic biomarkers. Summary of the Invention

[0006] To overcome the aforementioned defects and shortcomings in the existing technology, this invention provides the application of serum exosomal lncRNA in the preparation of detection products for immune checkpoint inhibitor-associated pneumonia.

[0007] The first objective of this invention is to provide the application of a detection reagent for serum exosomal lncRNA TTC9-DT in the preparation of a detection product for immune checkpoint inhibitor-associated pneumonia.

[0008] A second objective of this invention is to provide a kit for detecting immune checkpoint inhibitor-associated pneumonia.

[0009] A third objective of this invention is to provide a system for the diagnosis of immune checkpoint inhibitor-associated pneumonia.

[0010] This invention claims protection for the following: Application of serum exosomal lncRNA TTC9-DT detection reagent in the preparation of detection products for immune checkpoint inhibitor-associated pneumonia; The detection product is used to distinguish between patients with immune checkpoint inhibitor-associated pneumonia and patients with infectious pneumonia. The detection product also contains reagents for detecting blood indicators, including lymphocyte count and / or lactate dehydrogenase. The detection product is used to diagnose patients with immune checkpoint inhibitor-associated pneumonia after immune checkpoint inhibitor therapy. The detection product also contains a reagent for detecting serum exosome lncRNA ITGA2-AS1 and a reagent for detecting blood parameters, including neutrophil count.

[0011] The gene ID of the serum exosome lncRNA TTC9-DT is ENSG00000245466, and the gene ID of the serum exosome ITGA2-AS1 is ENSG00000249899.

[0012] A kit for detecting immune checkpoint inhibitor-associated pneumonia, the kit containing reagents for detecting serum exosomal lncRNA TTC9-DT; The kit also contains reagents for detecting serum exosomal lncRNA ITGA2-AS1.

[0013] As one feasible method, the reagent for detecting serum exosome lncRNA TTC9-DT is a primer with a nucleotide sequence as shown in SEQ ID NO: 1-2.

[0014] As one feasible method, the reagent for detecting serum exosomal lncRNA ITGA2-AS1 is a primer with a nucleotide sequence as shown in SEQ ID NO: 3-4.

[0015] Preferably, the kit further comprises serum exosome RNA extraction reagent, reverse transcription reagent and / or real-time quantitative PCR detection reagent.

[0016] A method for detecting immune checkpoint inhibitor-associated pneumonia, the method comprising the following steps: S1. Obtain the relative expression levels of serum exosomal lncRNA TTC9-DT, or the relative expression levels of serum exosomal lncRNA TTC9-DT and serum exosomal lncRNA ITGA2-AS1; S2. In distinguishing between patients with immune checkpoint inhibitor-associated pneumonia and patients with infectious pneumonia, the relative expression level of serum exosomal lncRNA TTC9-DT was compared with the threshold of 2.39. If the relative expression level of serum exosomal lncRNA TTC9-DT was greater than 2.39, the subject was a patient with immune checkpoint inhibitor-associated pneumonia. In diagnosing patients with immune checkpoint inhibitor-associated pneumonia after treatment with immune checkpoint inhibitors, the relative expression levels of serum exosomal lncRNA TTC9-DT and serum exosomal lncRNA ITGA2-AS1 were calculated using the formula: Logit(PCILnc) = -5.734 + 2.103×TTC9-DT + 1.152×ITGA2-AS1. The calculated value was compared with a threshold of 0.275. If the calculated value was greater than 0.275, the subject was considered to have immune checkpoint inhibitor-associated pneumonia.

[0017] A system for diagnosing immune checkpoint inhibitor-associated pneumonia includes a data input module, a database storage module, a disease prediction module, and an output module; The data input module is used to input the subject's characteristic parameters, which include the relative expression levels of serum exosomal lncRNA TTC9-DT and serum exosomal lncRNA ITGA2-AS1. The database storage module is used to store characteristic parameters of the population sample, including relative expression data of serum exosomal lncRNA TTC9-DT, or relative expression data of serum exosomal lncRNA TTC9-DT and serum exosomal lncRNA ITGA2-AS1. The population sample includes samples from subjects with non-immune checkpoint inhibitor-associated pneumonia and samples from patients with immune checkpoint inhibitor-associated pneumonia. The non-immune checkpoint inhibitor-associated pneumonia subject samples include subject samples with infectious pneumonia or subject samples without immune checkpoint inhibitor-associated pneumonia after immune checkpoint inhibitor treatment. The disease prediction module is connected to the data input module and the database storage module respectively, and is used to construct a prediction model using the feature parameters of the population sample, and to obtain the disease outcome of the subject based on the feature parameters of the subject obtained from the data input module. The output module is used to output the disease outcome of the subject obtained by the disease prediction module.

[0018] Preferably, the characteristic parameters also include lymphocyte count, lactate dehydrogenase and / or neutrophil count data obtained from the clinical testing system.

[0019] Compared with the prior art, the present invention has the following beneficial effects: This invention provides the application of serum exosomal lncRNA in the preparation of detection products for immune checkpoint inhibitor-associated pneumonia (IUI). Using the serum exosomal lncRNA of this invention significantly improves the sensitivity, specificity, and accuracy of diagnosing IUI. Compared with conventional non-specific blood indicators used in clinical practice, the serum exosomal lncRNA of this invention has better diagnostic efficacy. Furthermore, this invention can be performed via liquid biopsy, offering advantages such as minimally invasive procedures and real-time monitoring. The detection reagents are low-cost and widely available, enabling highly efficient clinical diagnosis and differentiation, improving early diagnosis rates, and possessing high clinical application value and broad application prospects. Attached Figure Description

[0020] Figure 1 This is a flowchart of a method for CIP diagnosis using the kit from Example 2.

[0021] Figure 2 ROC curve of the diagnostic model for CIP constructed using serum EV lncRNA TTC9-DT and ITGA2-AS1.

[0022] Figure 3 ROC curve of a diagnostic model for differentiating CIP and infectious pneumonia constructed using serum EV lncRNA TTC9-DT.

[0023] Figure 4 ROC curves for comparing and jointly analyzing the diagnostic efficacy of the diagnostic model based on serum EV lncRNA TTC9-DT and ITGA2-AS1 with that of NEU.

[0024] Figure 5 ROC curves for comparing and combining the diagnostic efficacy of the model constructed based on serum EV lncRNA TTC9-DT with LYM and LDH. Detailed Implementation

[0025] The present invention will be further illustrated below with reference to specific embodiments, but the embodiments do not limit the present invention in any way. Unless otherwise specified, the reagents, methods, and equipment used in the present invention are conventional reagents, methods, and equipment in this technical field.

[0026] Unless otherwise specified, all reagents and materials used in the following examples are commercially available.

[0027] Example 1 Primer Design I. Experimental Methods 1. Obtaining the nucleotide sequence of the target gene Log in to the Ensembl website (https: / / www.ensembl.org / index.html?redirect=no) to obtain the nucleotide sequences of long non-coding RNAs (lncRNAs) TTC9-DT and ITGA2-AS1.

[0028] For the nucleotide sequence of TTC9-DT (ENSG00000245466), please see: https: / / www.ensembl.org / Homo_sapiens / Gene / Sequence?db=core;g=ENSG00000245466;r=14:70608798-70641298;t=ENST00000500016; For the detailed nucleotide sequence of ITGA2-AS1 (ENSG00000249899), please see: https: / / www.ensembl.org / Homo_sapiens / Gene / Sequence?db=core;g=ENSG00000249899;r=5:52930606-52990278.

[0029] 2. Specific primer design (1) Based on the exon structure of lncRNA shown on the Ensembl website, design primer pairs that span at least one exon linker region (the forward primer is located at the 3' end of the upstream exon, and the reverse primer is located at the 5' end of the downstream exon). (2) NCBI Primer-BLAST verification showed no cross-gene matching. The parameters were set as follows: maximum non-specific matching length ≤ 8 bp; amplicon length: 80-200 bp, excluding primers with ≥ 12 bp continuous matching with other transcripts (including antisense strands).

[0030] II. Experimental Results The specific primer sequences for lncRNAs TTC9-DT and ITGA2-AS1 are shown in Table 1.

[0031] Table 1 Specific primer sequences

[0032] Example 2: Construction of a kit for detecting immune checkpoint inhibitor-associated pneumonia (CIP) I. Composition (1) The specific primers shown in Table 1 of Example 1; (2) ddH2O; (3) SYBR ® Premix Ex Taq™; (4) Evo M-MLV reverse transcription reagent from Accurate Biology.

[0033] II. Usage Method Figure 1 The specific steps for using the reagent kit of this invention are as follows: 1. Extraction of serum exosomes (1) Separation of serum 5 mL of peripheral blood was drawn from the patient using a non-treated blood collection tube. The sample was centrifuged at 3500 rpm and 4°C for 15 min. The supernatant was collected as serum, aliquoted, and stored at -80°C for later use or immediate use.

[0034] (2) Isolation and extraction of serum exosomes Exosomes in serum samples were separated using differential ultracentrifugation. The specific steps are as follows: ① Centrifuge the serum sample at 300×g for 10 min and collect the supernatant to remove cells from the sample; ② Centrifuge the supernatant obtained in step ① at 2000×g for 10 min and collect the supernatant to remove cell debris from the sample; ③ Centrifuge the supernatant obtained in step ② at 10000×g for 30 min, collect the supernatant, and process it with a 0.22 μm diameter filter to remove large particles such as apoptotic bodies from the supernatant; ④ Use an ultra-fast refrigerated centrifuge to centrifuge at 120,000×g for 90 min, remove the supernatant, resuspend the precipitate with sterile PBS, collect serum exosomes, obtain serum exosome samples, and store at -80℃ for later use or use immediately.

[0035] 2. Extraction of serum exosomal RNA (1) Add Trizol to the serum exosome sample to make up to 1 mL; keep at 15-30℃ and let stand for 5 min; (2) Add 200 μL of chloroform, vortex to mix for 15 s, let stand at room temperature for 5 min, and then centrifuge at 12000×g for 15 min at 4℃. After centrifugation, separate into 3 layers, and collect the upper colorless and transparent RNA layer for later use; (3) Transfer the RNA layer to a new RNase-free EP tube, add isopropanol to precipitate the RNA molecules, and the volume of isopropanol is the same as the volume of the RNA layer in step (2). Let it stand at 15-30℃ for 5 min, and then centrifuge at 12000×g at 4℃ for 10 min. A gel-like precipitate appears at the bottom of the centrifuge tube. (4) Discard the supernatant, add 1 mL of anhydrous ethanol solution for washing, vortex shake, and centrifuge at 12000×g for 5 min at 4℃; repeat the washing once, and then invert the EP tube on filter paper until the ethanol evaporates completely. (5) Add 15 μL of DEPC water to dissolve the RNA precipitate, pipette the precipitate, and let it stand at 55-60℃ for 10 min to promote RNA dissolution. Use a Nano Drop2000 ultra-micro spectrophotometer to determine the RNA quality and concentration, and thus obtain serum exosome RNA.

[0036] 3. Reverse transcription of serum exosomal RNA Following the instructions for the Evo M-MLV reverse transcription kit from Accurate Biology, the extracted serum exosomal RNA was reverse transcribed to synthesize the required cDNA.

[0037] 4. Detection of serum exosomal lncRNA expression levels The RT-qPCR reaction system is shown in Table 2.

[0038] Table 2 RT-qPCR reaction system

[0039] The RT-qPCR amplification program is shown in Table 3.

[0040] Table 3 RT-qPCR amplification program

[0041] 5. Analysis of amplification products Three replicates were set up for each sample, and the Ct value of each sample was read. The data was then analyzed using a 2-diode array. -ΔΔCt Calculate the relative expression levels of lncRNAs TTC9-DT and ITGA2-AS1 in the samples.

[0042] 6. Statistical analysis to select diagnostic cutoff values. Using MedCalc 19.6.0 statistical analysis software, the data were analyzed and processed through 2... -ΔΔCT The relative expression levels of lncRNAs TTC9-DT and ITGA2-AS1 were calculated. A multivariate model CILnc for the diagnosis of CIP was constructed using logistic regression with serum exosomal lncRNAs TTC9-DT and ITGA2-AS1. The model formula is: Logit(PCILnc) = -5.734 + 2.103 × TTC9-DT + 1.152 × ITGA2-AS1. Receiver operating characteristic (ROC) curves were plotted, and 0.275 was determined as the optimal cutoff value by finding the highest Youden index. That is, when the relative expression level of the constructed model is greater than 0.275, the patient can be diagnosed with CIP.

[0043] The relative expression level of TTC9-DT was used alone to differentiate between CIP and infectious pneumonia. ROC curves were plotted and the highest Youden index was used to determine that 2.39 was the optimal cutoff value. That is, when the relative expression level of the constructed model is greater than 2.39, the patient can be diagnosed with CIP rather than infectious pneumonia.

[0044] Example 3: Diagnostic efficacy of serum exosomal lncRNAs TTC9-DT and ITGA2-AS1 in recognizing immune checkpoint inhibitor-associated pneumonia I. Experimental Methods Serum samples were collected from 44 patients treated with immune checkpoint inhibitors but who did not develop CIP, 28 patients with infectious pneumonia, and 31 patients with CIP. The serum samples were tested using the kit described in Example 2.

[0045] II. Experimental Results Figure 2The ROC curve for the combined diagnosis of CIP using serum exosomal lncRNA TTC9-DT and ITGA2-AS1 was used to evaluate its diagnostic efficacy. Results showed that the area under the receiver operating characteristic (AUC) for the combined diagnosis of CIP using serum exosomal lncRNA TTC9-DT and ITGA2-AS1 was 0.945, with a 95% confidence interval (95% CI) of 0.883–1.000, a standard error of 0.032, and P < 0.001. At a cutoff value of 0.275, the sensitivity was 95.2% and the specificity was 80.0%.

[0046] Figure 3 The ROC curve for serum exosome TTC9-DT in differentiating CIP and infectious pneumonia can be used to evaluate the diagnostic efficacy of serum exosome TTC9-DT in this differential diagnosis. Results showed that the AUC of serum exosome TTC9-DT in differentiating CIP and infectious pneumonia was 0.704, with a 95% CI of 0.551–0.857, a standard error of 0.078, and P = 0.019. When the cutoff value was 2.39, the sensitivity was 62.5% and the specificity was 71.4%.

[0047] Example 4: Comparison and combination of lncRNA detection efficacy and commonly used clinical biomarker diagnostic efficacy I. Experimental Methods Peripheral blood samples were obtained from patients using peripheral venous puncture. NEU and LYM levels were detected using a fully automated hematology analyzer, LDH levels were detected using a biochemical analyzer, and serum exosome lncRNA levels of TTC9-DT and ITGA2-AS1 were detected using the kit from Example 2.

[0048] ROC curves were used to compare the diagnostic efficacy of the CILnc model, NEU, and the combination of CILnc model and NEU in diagnosing CIP. ROC curves were also used to compare the diagnostic efficacy of TTC9-DT, LYM, LDH, TTC9-DT combined with LYM, TTC9-DT combined with LDH, and TTC9-DT combined with LYM and LDH in differentiating CIP from infectious pneumonia.

[0049] The specific steps for joint analysis are as follows: SPSS software was used to perform receiver operating characteristic (ROC) curve analysis for the combined diagnosis of multiple indicators.

[0050] Step 1: Define variables and create a table: For example, the first column (testa) is the value of NEU, which is a numerical variable; the second column (testb) is the value of the CILnc model, which is a numerical variable; disease is the disease state, 0 is no disease, and 1 is disease, that is, having CIP.

[0051] Step 2: Import the data into Medcalc.

[0052] Step 3: Logistic Regression Click Statistics -> Regression -> Logistic Regression. In the Logistic Regression dialog box, select Disease in the Dependent Variable box, and select testa and testb in the first and second rows of the Independent Variable box, respectively. In the Logistic Regression results dialog box, click Save predicted probabilities to save the probabilities to the dataset.

[0053] Step 4: At this point, a new value LOGREGR_Pred1 appears in the data frame. This value represents the predicted probability values ​​of testa and testb generated by logistic regression. It comprehensively reflects the diagnostic capabilities of testa and testb. The receiver operating characteristic curve plotted using LOGREGR_Pred1 is the combined diagnosis of the two values.

[0054] II. Experimental Results like Figure 4 The results in Table 4 show that the CILnc model has a higher diagnostic efficacy for CIP in patients after immunotherapy compared to commonly used clinical biomarkers. The area under the curve for multi-indicator combined diagnosis indicates that CILnc combined with NEU has a better diagnostic effect.

[0055] Table 4. Diagnostic efficacy of CIP

[0056] like Figure 5 The results in Table 5 show that, in the differential diagnosis of CIP and infectious pneumonia, the area under the curve of the multi-indicator combined diagnosis of serum exosomal lncRNA TTC9-DT with LYM and LDH has a better diagnostic effect than that of single indicators and other combined schemes.

[0057] Table 5 Diagnostic efficacy of CIP and infectious pneumonia

[0058] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. Use of a detection reagent for serum exosome lncRNA TTC9-DT in the preparation of a detection product for immune checkpoint inhibitor associated pneumonia.

2. Use according to claim 1, characterized in that, The detection product is used to distinguish immune checkpoint inhibitor associated pneumonia patients from infectious pneumonia patients, and the detection product further contains a detection reagent for a blood index comprising lymphocyte count and / or lactate dehydrogenase.

3. Use according to claim 1, characterized in that, The detection product is used to diagnose immune checkpoint inhibitor associated pneumonia patients after immune checkpoint inhibitor treatment, and the detection product further contains a detection reagent for serum exosome lncRNA ITGA2-AS1.

4. Use according to claim 3, characterized in that, The detection product further contains a detection reagent for a blood index comprising neutrophil count.

5. A kit for detecting immune checkpoint inhibitor associated pneumonitis, characterized in that, The kit contains a reagent for detecting serum exosome lncRNA TTC9-DT.

6. The kit of claim 5, wherein The reagent for detecting serum exosome lncRNA TTC9-DT is a primer with a nucleotide sequence as shown in SEQ ID NO: 1-2.

7. The kit of claim 5, wherein The kit further contains a reagent for detecting serum exosome lncRNA ITGA2-AS1.

8. The kit of claim 7, wherein The reagent for detecting serum exosome lncRNA ITGA2-AS1 is a primer with a nucleotide sequence as shown in SEQ ID NO: 3-4.

9. A system for immune checkpoint inhibitor associated pneumonia diagnosis, characterized in that, The system comprises a data input module, a database storage module, a disease prediction module and an output module. The data input module is used to input characteristic parameters of a subject, and the characteristic parameters comprise relative expression data of serum exosome lncRNA TTC9-DT, or relative expression data of serum exosome lncRNA TTC9-DT and serum exosome lncRNA ITGA2-AS1. The database storage module is used to store characteristic parameters of population samples, and the characteristic parameters comprise relative expression data of serum exosome lncRNA TTC9-DT, or relative expression data of serum exosome lncRNA TTC9-DT and serum exosome lncRNA ITGA2-AS1, and the population samples comprise non-immune checkpoint inhibitor associated pneumonia subject samples and immune checkpoint inhibitor associated pneumonia patient samples. The non-immune checkpoint inhibitor associated pneumonia subject samples comprise infectious pneumonia subject samples or immune checkpoint inhibitor treatment without immune checkpoint inhibitor associated pneumonia subject samples. The disease prediction module is connected to the data input module and the database storage module, respectively, and is used to construct a prediction model using the characteristic parameters of the population samples, and obtain a disease result of a subject based on the characteristic parameters of the subject obtained from the data input module. The output module is used to output the disease result of the subject obtained by the disease prediction module.

10. The system of claim 9, wherein, The characteristic parameters further comprise lymphocyte count, lactate dehydrogenase and / or neutrophil count data obtained by a clinical test system.

Images