CN112941177A

CN112941177A - Application of CFLAR as diagnosis marker in construction of lung squamous cell carcinoma prognosis prediction model

Info

Publication number: CN112941177A
Application number: CN202110146502.5A
Authority: CN
Inventors: 罗露梦; 乔田奎; 武多娇; 庄喜兵
Original assignee: Jinshan Hospital of Fudan University
Current assignee: Jinshan Hospital of Fudan University
Priority date: 2021-02-03
Filing date: 2021-02-03
Publication date: 2021-06-11

Abstract

The invention relates to the technical field of biomedicine, in particular to application of CFLAR as a diagnosis marker in constructing a lung squamous cell carcinoma prognosis prediction model, the invention combines the biomarker CFLAR and other clinical indexes for use, the invention can assist in making lung squamous carcinoma prognosis detection, and can efficiently and accurately predict the prognosis condition of a patient with lung squamous carcinoma by screening and constructing the lung squamous carcinoma sample based on large-sample anti-tumor immunotherapy after full transcriptome sequencing and machine learning, meanwhile, according to the relevance of the risk of the tumor cell, different immune cell infiltration levels, immune-related pathways, the expression level of a key immune checkpoint inhibitor and the like, the comprehensive evaluation of a tumor immune microenvironment is realized, effective guidance opinions are provided for clinicians on treatment decisions of patients with squamous cell lung carcinoma, and the occurrence of ineffective treatment is reduced, so that the treatment cost and discomfort experience of the patients are reduced.

Description

Application of CFLAR as diagnosis marker in construction of lung squamous cell carcinoma prognosis prediction model

Technical Field

The invention relates to the technical field of biomedicine, in particular to application of CFLAR as a diagnostic marker in constructing a lung squamous cell carcinoma prognosis prediction model.

Background

Lung cancer is the most common cause of cancer-related death in the world today, and 80% of them are non-small cell lung cancers (NSCLC). TNM staging is a currently widely accepted clinical staging system used to predict prognosis and to guide treatment of non-small cell lung cancer patients. However, the current TNM staging system is far from adequate to accurately predict prognosis in non-small cell lung cancer patients. For example, for lung cancer patients, the recurrence rate of lung cancer is as high as 35-50% even in the clinical stage I. In addition, a significant proportion of patients can be cured by surgery alone, and these patients should avoid the extremely strong side effects of adjuvant chemotherapy based on the current TNM system.

Squamous cell carcinoma of lung (also called squamous cell carcinoma of lung), accounts for 40% -51% of primary lung cancer, is commonly seen in middle-aged and elderly men, and has close relation with smoking. Is mainly formed by metaplasia of columnar epithelial cells of bronchial mucosa, including chronic stimulation and damage of bronchial epithelial cells, loss of cilia, squamous metaplasia or typical hyperplasia of basal cells and the like. Squamous cell lung cancer is common in central lung cancer, and tends to grow in the chest cavity, and early squamous cell lung cancer often causes bronchoconstriction or obstructive pulmonary inflammation. Squamous cell lung carcinoma has a large variation in malignancy, and generally, squamous cell carcinoma grows more slowly than other lung cancers, and the tumor grows larger when the squamous cell carcinoma is found.

At present, the main methods and technologies for prognosis prediction of tumor therapy immunotherapy are as follows: detecting markers (such as PD-L1, TMB, dMMR and the like); ② immune function assessment, such as Tumor Infiltrating Lymphocytes (TILs).

The existing lung squamous carcinoma related gene prediction model lacks comprehensive evaluation on different levels of tumor immune microenvironment, such as immune cell infiltration level/immune related pathway/immune molecule and the like. At present, the main technology has low specificity and sensitivity, and the detection method is unstable or has higher price, and has no clear guidance value for clinical tumor treatment. At present, clinical tumor immunity brings long-term benefit hope to partial patients, and the side effect and economic burden of immunotherapy limit clinical application. High specificity and sensitivity techniques are urgently needed in clinic.

Aiming at the defects, the invention provides a novel squamous cell lung carcinoma prognosis prediction model, which can predict the prognosis of patients with squamous cell lung carcinoma and realize the comprehensive evaluation of tumor immune microenvironment according to the correlation between the squamous cell lung carcinoma prognosis model and different immune cell infiltration levels, immune-related pathways, expression levels of key immune checkpoint inhibitors and the like, thereby providing guidance for immunotherapy selection of patients with squamous cell lung carcinoma.

The application of the CFLAR as a diagnostic marker in constructing a lung squamous carcinoma prognosis prediction model is not reported at present.

Disclosure of Invention

The invention aims to provide a lung squamous carcinoma prognosis prediction model and a kit aiming at the defects of the prior art.

In order to achieve the purpose, the invention adopts the technical scheme that:

in a first aspect, the invention provides an application of CFLAR as a diagnostic marker in constructing a lung squamous carcinoma prognosis prediction model.

Preferably, the prediction model further comprises a reagent for detecting the expression level of CFLAR.

Preferably, there is a high risk when the CFLAR expression level is above 12.37775 and a low risk when the CFLAR expression level is below 12.37775.

Preferably, the predictive model further comprises the following reagents: normal human serum and positive control serum.

In a second aspect, the invention provides an application of a reagent for detecting CFLAR expression level in preparing a kit for evaluating the responsiveness of anti-tumor immunotherapy for squamous cell lung carcinoma and survival after prognosis, wherein the detection reagent is used as a unique key component for evaluating the responsiveness of anti-tumor immunotherapy for squamous cell lung carcinoma and survival after prognosis as a kit, and the kit further comprises an instruction book, and the instruction book records the following contents: when the CFLAR expression level is higher than 12.37775, it represents that the immunotherapy responsiveness and prognosis survival is predicted to be a high-risk group, and when the CFLAR expression level is lower than 12.37775, it represents that the immunotherapy responsiveness and prognosis survival is predicted to be a low-risk group.

Preferably, the sample detected using the kit is a fresh tissue tumor sample.

In a third aspect, the invention provides an application of an inhibitor in preparing a medicament for improving lung squamous carcinoma anti-tumor immunotherapy and prognosis survival, wherein the inhibitor is a substance for down-regulating the expression level of CFLAR.

Preferably, the inhibitor is selected from a small molecule compound or a biological macromolecule.

Preferably, the medicament also comprises other medicaments compatible with the inhibitor and pharmaceutically acceptable carriers and/or auxiliary materials.

The invention has the advantages that:

the invention is based on the whole transcriptome sequencing data of the lung squamous carcinoma specimen of the large-sample anti-tumor immunotherapy, screens and constructs by machine learning, can efficiently and accurately predict the response of the lung squamous carcinoma patient to receive the anti-tumor immunotherapy, and the experimental result shows that the model and the diagnostic kit have the advantages of high sensitivity, high specificity and high accuracy when being used clinically. Can provide effective guidance opinions for treatment decisions of the patients with the lung squamous carcinoma for clinicians, and reduce the occurrence of ineffective treatment, thereby reducing the treatment cost and discomfort experience of the patients.

Drawings

FIG. 1 shows the results of OS survival analysis of prognostic-related ARGs in 326 squamous cell lung carcinoma samples. (results showed that the RNA level of the CFLAR gene was significantly negatively correlated with prognosis).

FIG. 2 is the results of correlation analysis of the predicted gene ARGs with the expression levels of three key immune checkpoints (FIG. 2A-FIG. 2C).

Detailed Description

The invention will be further illustrated with reference to specific embodiments. It should be understood that these examples are for illustrative purposes only and are not intended to limit the scope of the present invention. Furthermore, it should be understood that various changes and modifications can be made by those skilled in the art after reading the disclosure of the present invention, and equivalents fall within the scope of the appended claims.

Example 1 model construction and Effect verification

1. Method of producing a composite material

1.1 training set 326 lung squamous carcinoma RNA sequencing data and clinical data from TCGA database, obtaining Autophagy-Related gene (ARGs) expression profiles, verifying and collecting 78 lung squamous carcinoma RNA sequencing data from GTO database, obtaining all RNA expression profiles and Autophagy-Related gene (ARGs) expression profiles.

1.2 screening ARGs related to prognosis through survival analysis, then obtaining the most key ARGs (CFLAR) related to survival by adopting a random forest method, and constructing a risk prediction model based on the gene by adopting a deep machine learning method of random forest. The patients are divided into a low risk group and a high risk group according to the risk obtained by the model. The model is verified to be effective in predicting the prognosis of the squamous cell lung carcinoma patient by ROC analysis of a working characteristic curve of a subject and log-rank test verification of a KM survival curve.

1.3 based on RNA sequencing data, the relationship between high and low risks and immune-related pathways is researched through Gene Set Enrichment Analysis (GSEA), and the high-risk group is found to be related to the up-regulation of immune suppression-related pathways.

1.4 obtaining infiltration levels of 28 tumor infiltrating immune cells by single gene set enrichment analysis (ssGSEA) based on RNA sequencing data, and finding significant correlation with risk by correlation analysis.

1.5 correlation of risk with expression levels of key immune checkpoint molecules PD-1, PD-L1, CTLA4 was found by correlation analysis.

1.6 based on RNA sequencing data, tumor immune scores and stroma scores were obtained by the ESTIMATE algorithm, and correlations between risk and immune scores and mechanism scores were found.

The method for calculating the level of tumor infiltrating immune cells comprises the following steps: (ssGSEA method): immune cells and corresponding gene lists are obtained in the literature, and GSVAenrichment scales are evaluated according to RNA sequencing data and an R language GSVA package.

Correlation analysis method: pearson correlation analysis (correlation analysis methods in this study are all Pearson correlation analysis.

2 results

FIG. 1 is the results of the OS survival analysis of the ARGs with the highest prognosis in the 326 squamous cell lung carcinoma samples. (the results show that the level of gene RNA is significantly negatively correlated with prognosis).

FIGS. 2A-2C are the results of correlation analysis of the expression levels of the predicted genes ARGs with three key immune checkpoints.

Example 2 control test

1. Kit composition

Kit I

Comprises a detection kit instruction, and the detection reagent is a reagent for detecting the expression quantity of the CFLAR.

The description content of the specification is as follows: when the CFLAR expression level is higher than 12.37775, it represents that the immunotherapy responsiveness and prognosis survival is predicted to be a high-risk group, and when the CFLAR expression level is lower than 12.37775, it represents that the immunotherapy responsiveness and prognosis survival is predicted to be a low-risk group.

Reagent kit II

Comprises a detection kit instruction, and the detection reagent is a reagent for detecting the expression quantity of the EGFR.

The description content of the specification is as follows: when the expression level of EGFR is higher than the normal value, it represents that the immunotherapy responsiveness and prognosis survival are predicted to be a high-risk group, and when the expression level of EGFR is lower than the normal value, it represents that the immunotherapy responsiveness and prognosis survival are predicted to be a low-risk group.

2. Method of producing a composite material

2.1 patients with squamous cell lung carcinoma who received anti-tumor immunotherapy at Jinshan Hospital affiliated at the university of Compound Dane, the inclusion and exclusion criteria for the patients were as follows:

(1) patients with squamous cell lung carcinoma receiving immunotherapy with tumors;

(2) complete curative effect information and clinical follow-up information are provided;

(3) having whole transcriptome RNA sequencing data;

(4) patients with unknown tumor immunotherapy results or incomplete survival data were excluded.

2.2 the 100 patients meeting the above criteria were randomly divided into two groups, and the two groups were recorded by the first and second kits according to the instruction.

3. Results

The result shows that the accuracy rate of prediction by using the first kit is 59.3%, and the accuracy rate of prediction by using the second kit is 48.6%.

4. Conclusion

The results show that the marker of the invention has high prognosis prediction accuracy, and the inventor selects the best index based on abundant clinical and research experiences and a large number of cases in hospital for years, and confirms that the marker has excellent evaluation effect, can provide effective guidance for the treatment decision of a clinician on a patient with squamous cell lung carcinoma, reduces the occurrence of ineffective treatment, thereby reducing the treatment cost and discomfort experience of the patient, and has strong practicability.

The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and additions can be made without departing from the principle of the present invention, and these should also be considered as the protection scope of the present invention.

Claims

The application of CFLAR as a diagnostic marker in constructing a lung squamous carcinoma prognosis prediction model.
2. The use of claim 1, wherein the predictive model further comprises a reagent for detecting the amount of CFLAR expression.
3. Use according to claim 2, characterized in that it is at high risk when the CFLAR expression is above 12.37775 and at low risk when the CFLAR expression is below 12.37775.
4. The use of claim 1, wherein the predictive model further comprises the following agents: normal human serum and positive control serum.
5. The application of the reagent for detecting the CFLAR expression quantity in the preparation of the kit for evaluating the lung squamous carcinoma anti-tumor immunotherapy reactivity and the prognosis survival is characterized in that the detection reagent is used as the only key component for realizing the evaluation of the lung squamous carcinoma anti-tumor immunotherapy reactivity and the prognosis survival function by the kit, the kit further comprises an instruction book, and the instruction book records the following contents: when the CFLAR expression level is higher than 12.37775, it represents that the immunotherapy responsiveness and prognosis survival is predicted to be a high-risk group, and when the CFLAR expression level is lower than 12.37775, it represents that the immunotherapy responsiveness and prognosis survival is predicted to be a low-risk group.
6. The use of claim 5, wherein the sample to be tested using the kit is a fresh tissue tumor sample.
7. The application of an inhibitor in preparing a medicament for improving lung squamous carcinoma anti-tumor immunotherapy and prognostic survival is characterized in that the inhibitor is a substance for down-regulating the expression level of CFLAR.
8. The use according to claim 7, wherein the inhibitor is selected from a small molecule compound or a biological macromolecule.
9. The use of claim 7, wherein the medicament further comprises other drugs compatible with the inhibitor and pharmaceutically acceptable carriers and/or excipients.