TsRNA biomarker for predicting curative effect of lung cancer immunotherapy and application of tsRNA biomarker

Abstract

The invention discloses a tsRNA biomarker for lung cancer immunotherapy curative effect prediction and application thereof, the marker is used for preparing a product for lung adenocarcinoma neoadjuvant immunotherapy combined chemotherapy curative effect prediction, the marker is 3 'tiRNA-AlaCGC, the product is a qPCR kit, and the qPCR kit comprises a primer pair for detecting the marker in a focus. The method comprises the following steps: screening high-expression tsRNA in tissues of a lung adenocarcinoma neoadjuvant immunotherapy combined chemotherapy patient through high-throughput sequencing, verifying differential expression of the tsRNA through lung cancer and normal bronchial epithelial cell lines, and determining that the expression level of the tsRNA is related to prognosis of the lung cancer patient through a tissue chip. Through verification, the marker has relatively good sensitivity and specificity on lung adenocarcinoma immunotherapy curative effect prediction, is easy to popularize and apply by adopting classic real-time quantitative fluorescent PCR detection, and has important clinical application value.

Description

Technical Field

[0001] The present invention belongs to the field of medical and health technology, and specifically relates to a tsRNA biomarker for predicting the efficacy of lung cancer immunotherapy and an application thereof. Background Art

[0002] Lung cancer ranks first among the causes of cancer-related deaths. Lung adenocarcinoma is the main pathological subtype of lung cancer, accounting for about 40%-60%. The emergence of immunotherapy has profoundly changed the treatment of patients with driver gene-negative lung adenocarcinoma. Neoadjuvant immunotherapy can significantly improve the overall survival of lung cancer patients. However, due to the heterogeneity of the tumor microenvironment, neoadjuvant immunotherapy combined with chemotherapy only benefits some patients with lung adenocarcinoma. How to screen these patients has become an urgent problem to be solved.

[0003] Transfer RNA-derived small RNA (tsRNA) is one of the most abundant non-coding RNAs in cells. It is a product produced by precise regulation and shearing of tRNA. In recent years, a large number of studies have shown that tsRNA can affect the stability of mRNA and protein translation in tumors, thereby affecting the occurrence and development of tumors. Due to its high abundance, tsRNA has the potential to become a diagnostic marker.

[0004] Therefore, if a tsRNA biomarker that can be used to predict the efficacy of immunotherapy for lung adenocarcinoma can be discovered, it will be able to quickly screen treatment-sensitive and drug-resistant populations in the neoadjuvant chemotherapy combined with immunotherapy cohort for lung adenocarcinoma, which will have important clinical application value. Summary of the invention

[0005] The main purpose of the present invention is to provide a tsRNA biomarker for predicting the efficacy of immunotherapy for lung adenocarcinoma. Through high-throughput small RNA chip detection, the treatment-sensitive population and the drug-resistant population in the neoadjuvant chemotherapy combined with immunotherapy cohort for lung adenocarcinoma are detected, and the tsRNA highly expressed in the drug-resistant group is screened out.

[0006] Another object of the present invention is to provide the use of the tsRNA biomarker in the preparation of a product for diagnosing the efficacy of immunotherapy for lung adenocarcinoma.

[0007] In order to achieve the above invention objectives, this application adopts the following technical solutions:

[0008] In a first aspect, the present application provides a tsRNA biomarker, wherein the tsRNA biomarker is a 3' tiRNA isoform.

[0009] Furthermore, the tsRNA biomarker is 3'tiRNA-AlaCGC.

[0010] In a second aspect, the present application provides the use of the tsRNA biomarker in the preparation of a product for predicting the efficacy of lung cancer immunotherapy.

[0011] Preferably, the lung cancer immunotherapy efficacy prediction product is a real-time quantitative fluorescence PCR detection kit.

[0012] In a third aspect, the present application provides a reagent for predicting the efficacy of immunotherapy for lung cancer, comprising a primer pair for detecting 3'tiRNA-AlaCGC, wherein the primer pair has a sequence as shown in SEQ ID NO: 1-2.

[0013] More preferably, the reagent detects the expression level of 3'tiRNA-AlaCGC in the subject's lung adenocarcinoma lesions. When the expression level of 3'tiRNA-AlaCGC in the subject's lung adenocarcinoma lesions is high, it indicates that the subject is likely to have a poor immunotherapy effect.

[0014] In a fourth aspect, the present application provides a kit for predicting the efficacy of immunotherapy for lung cancer, comprising the reagent described in the third aspect.

[0015] More preferably, the kit is a real-time quantitative fluorescent PCR detection kit, comprising a primer pair for detecting 3'tiRNA-AlaCGC in lesions of lung adenocarcinoma patients.

[0016] Further, the PCR primer sequence for detecting tsRNA3'tiRNA-AlaCGC is:

[0017] F:5'-ACGATCTTCGCATGTACGAGG-3';

[0018] R:5'-CGATCTTGGTGGAGGAGCC-3'.

[0019] The present invention first screens the tsRNA highly expressed in the tissues of patients after immunotherapy for lung adenocarcinoma through high-throughput sequencing, and then obtains the tsRNA with diagnostic value through population verification. It has been verified that 3'tiRNA-AlaCGC has good sensitivity and specificity for the evaluation of the efficacy of immunotherapy for lung adenocarcinoma and the prognosis diagnosis. It adopts the classic real-time quantitative fluorescence PCR detection, which is easy to promote and apply, and has important clinical application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 .Use high-throughput small RNA sequencing to screen the differential expression of tsRNA in the drug-resistant group and the treatment-sensitive group of lung adenocarcinoma patients treated with neoadjuvant immunotherapy combined with chemotherapy;

[0021] Figure 2.Real-time fluorescence quantitative PCR detected that the expression of tsRNA3'tiRNA-AlaCGC in lung adenocarcinoma cell lines was higher than that in normal bronchial epithelial cell lines;

[0022] Figure 3 .RNA in situ hybridization showed that patients with lung adenocarcinoma with high expression of tsRNA3'tiRNA-AlaCGC had a poor prognosis;

[0023] Figure 4 .Receiver operating characteristic curve for using tsRNA3'tiRNA-AlaCGC to predict whether a cell is sensitive or resistant to neoadjuvant immunotherapy combined with chemotherapy. DETAILED DESCRIPTION

[0024] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several variations and improvements may be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0025] Example 1: High-throughput small RNA screening of differentially expressed tsRNAs

[0026] Patient samples were collected. The patient type was lung adenocarcinoma patients confirmed by pathological biopsy and received neoadjuvant immunotherapy combined with chemotherapy before surgical treatment. After the treatment cycle, the treatment efficacy was evaluated by 2 radiologists according to the RECIST 1.1 standard. The patients with partial remission or complete remission were classified as the treatment sensitive group, and the patients with tumor progression or no remission were classified as the drug resistant group.

[0027] Arraystar small RNA microarray high-throughput small RNA sequencing was used to analyze the differential expression of tsRNA in the neoadjuvant immunotherapy combined with chemotherapy resistant group and the treatment sensitive group. This part of the experiment was completed by Spectrum (Shanghai) Biotechnology Co., Ltd. Based on the differential expression fold ≥ 2 and p value < 0.05, the tsRNA with significant abnormal expression was screened, and the most significant tsRNA was screened as 3'tiRNA-AlaCGC. ( Figure 1 )

[0028] Example 2: Detection of the difference of tsRNA3'tiRNA-AlaCGC in normal bronchial epithelial cell line and lung adenocarcinoma cell line by real-time fluorescence quantitative PCR

[0029] The normal bronchial epithelial cell line is BEAS-2B, and the lung adenocarcinoma cell lines are A549, H1299, H23, H1975, and PC9 cell lines. The above cell lines were purchased from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). All cells were stored in a suitable culture environment (5% CO2, 37°C) and cultured in high-glucose DMEM (supplemented with 10% FBS). Total RNA was extracted from the cells using Trizol reagent (LifeTechnologies, USA) according to the instructions. The extracted tsRNA was reverse transcribed into cDNA using PrimeScript RT Reagent Kit (TAKARA, Japan) according to the instructions. SYBR Premix Ex Taq (TAKARA, Japan) was used to detect the PCR primer sequence of tsRNA3'tiRNA-AlaCGC,

[0030] F: 5'-ACGATCTTCGCATGTACGAGG-3' (SEQ ID NO: 1);

[0031] R: 5'-CGATCTTGGTGGAGGAGCC-3' (SEQ ID NO: 2).

[0032] Real-time fluorescence quantitative PCR was performed in ABI7500 QPCR instrument according to the instructions to analyze the difference of tsRNA 3'tiRNA-AlaCGC in normal bronchial epithelial cell line and lung adenocarcinoma cell line ( Figure 2 ), confirming that tsRNA 3'tiRNA-AlaCGC was highly expressed in lung adenocarcinoma cell lines.

[0033] Example 3: RNA in situ hybridization suggests that tsRNA3'tiRNA-AlaCGC is associated with poor prognosis in patients with lung adenocarcinoma

[0034] Tissue microarrays containing 178 lung adenocarcinoma specimens collected in the Department of Thoracic Surgery affiliated to Fudan University were used for in situ hybridization of tsRNA3'tiRNA-AlaCGC. The probes were purchased from Wuhan Boster Biotechnology Co., Ltd., and this part of the experiment was completed by Wuhan Boster Biotechnology Co., Ltd. The expression of 3'tiRNA-AlaCGC was quantified by two independent pathology experts according to the degree of staining. The staining intensity is divided into four levels: 0, negative; 1, weak; 2, moderate; 3, strong. The percentage of positive cells is divided into 0, negative; 1, ≥25%; 2, 25-50%; 3, 50-75%; 4, >75%. The percentage of positive cells was multiplied by the staining level to calculate the weighted staining score. Finally, all samples were divided into two levels according to the score: <3, low expression; ≥3, high expression. According to the high and low expression, the 178 lung adenocarcinoma patients were divided into a high expression group (103 people) and a low expression group (75 people), and the Kaplan-Meier method was used to draw the survival curve according to the disease-free survival and overall survival ( Figure 3 ), the survival information suggested that the disease-free survival and overall survival of lung adenocarcinoma patients with high expression of tsRNA3'tiRNA-AlaCGC were shorter than those with low expression, and the prognosis was poor.

[0035] Example 4: Comparison of 3'tiRNA-AlaCGC content in lesions between the treatment-sensitive group and the drug-resistant group of patients receiving neoadjuvant immunotherapy combined with chemotherapy

[0036] Lesions in the treatment-sensitive and drug-resistant groups of patients receiving neoadjuvant immunotherapy combined with chemotherapy were collected, and total RNA was extracted from the tissues using Trizol reagent (Life Technologies, USA) according to the instructions. The extracted tsRNA was reverse transcribed into cDNA using PrimeScript RTReagent Kit (TAKARA, Japan) according to the instructions. SYBR Premix Ex Taq (TAKARA, Japan) was used to detect the PCR primer sequence of tsRNA3'tiRNA-AlaCGC.

[0037] F: 5'-ACGATCTTCGCATGTACGAGG-3' (SEQ ID NO: 1);

[0038] R: 5'-CGATCTTGGTGGAGGAGCC-3' (SEQ ID NO: 2).

[0039] Real-time fluorescence quantitative PCR was performed in ABI7500 QPCR instrument according to the instructions to analyze the difference between tsRNA 3'tiRNA-AlaCGC in the sensitive group and the resistant group. Figure 4) to obtain the optimal threshold point, that is, the cutoff value, which is 5.700. All samples were divided into two groups according to the cutoff value. Those above the cutoff value were classified as having a high probability of resistance to neoadjuvant immunotherapy combined with chemotherapy, and those below the cutoff value were classified as having a high probability of sensitivity to neoadjuvant immunotherapy combined with chemotherapy.

[0040] The experimental results show that the prediction model has a specificity of 93.33% and a sensitivity of 52.94%.

[0041] The above is only a preferred embodiment of the present invention. It should be pointed out that ordinary technicians in this technical field can make several improvements and supplements without departing from the principle of the present invention. These improvements and supplements should also be regarded as the scope of protection of the present invention.

Claims

1. A tsRNA biomarker, characterized in that The tsRNA biomarker is 3'tiRNA-AlaCGC.

2. Use of the tsRNA biomarker according to claim 1 in the preparation of a product for predicting the efficacy of lung cancer immunotherapy.

3. The use according to claim 2, characterized in that: The lung cancer immunotherapy efficacy prediction product is a real-time quantitative fluorescence PCR detection kit.

4. A reagent for predicting the efficacy of immunotherapy for lung cancer, characterized in that: The invention comprises a primer pair for detecting 3'tiRNA-AlaCGC, wherein the primer pair has the sequences shown in SEQ ID NO: 1-2.

5. A kit for predicting the efficacy of immunotherapy for lung cancer, characterized in that: Comprising the reagent described in claim 4.

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