CN-116479126-B - Marker for predicting curative effect of lung cancer immunotherapy and construction method of scoring system

Abstract

The invention provides a marker for predicting curative effect of lung cancer immunotherapy and a construction method of a scoring system, and relates to the technical field of biology. The inventor researches find that mRNA of CypB, RNA transcribed from FAM83H-AS1 gene and LNCRNA VPS D1-AS1 are related to prognosis of lung cancer, and immune cell infiltration condition around lung cancer focus is related to treatment of lung cancer patients, therefore, the invention takes mRNA of CypB, RNA transcribed from FAM83H-AS1 gene, LNCRNA VPS D1-AS1, panCK, CD3, CD4, CD8 and Foxp3 AS marks, provides a method for constructing a scoring system for predicting curative effect of lung cancer immunotherapy, and the scoring system constructed by the method can comprehensively evaluate the states of tumors and microenvironments thereof, accurately predict the progression risk and prognosis condition of lung cancer and better guide clinical medication.

Inventors

• TAN JINJING
• YANG LEI
• GU MENG
• Peng Yanjing

Assignees

• 首都医科大学附属北京胸科医院
• 北京市结核病胸部肿瘤研究所

Dates

Publication Date

20260508

Application Date

20230329

Claims (5)

1. 1. The construction method of the scoring system for predicting the curative effect of the lung cancer immunotherapy is characterized by comprising the following steps: a. taking lung cancer tissues of a patient AS samples, detecting mRNA of CypB, RNA transcribed from FAM83H-AS1 gene and LNCRNA VPS D1-AS1 in the samples, and obtaining expression level scores of the mRNA of CypB, the RNA transcribed from FAM83H-AS1 gene and VPS9D1-AS1 VPS9D1-AS 1; b. detecting panCK, CD3, CD4, CD8 and Foxp3 in the sample in the step a, distinguishing tumor cells, killer T cells, helper T cells and regulatory T cells according to detection results, and obtaining counts of the killer T cells, the helper T cells and the regulatory T cells in a tumor cell area and a tumor interstitial area; c. construction of scoring System formula immune score=a 1 Expression level score of mRNA of CypB+a 2 Expression level score +a of FAM83H-AS1 Gene transcribed RNA 3 LNCRNA VPS9 expression level score +b of D1-AS1 1 Number of killer T cells in tumor cell area/number of helper T cells in tumor cell area +b 2 Number of killer T cells in tumor cell area/number of regulatory T cells in tumor cell area +b 3 Number of killer T cells in tumor cell region/number of killer T cells in tumor interstitial region+b 4 Number of T helper cells in tumor cell region/number of T helper cells in tumor interstitial region; The a 1 、a 2 、a 3 、b 1 、b 2 、b 3 and b 4 are coefficients; the values of coefficients a 1 、a 2 、a 3 、b 1 、b 2 、b 3 and b 4 are determined by a mathematical modeling method by taking the expression level score of CypB mRNA, the expression level score of RNA transcribed from FAM83H-AS1 gene, the expression level score of LNCRNA VPS D1-AS1, the number of killer T cells in the tumor cell area/the number of helper T cells in the tumor cell area, the number of killer T cells in the tumor cell area/the number of regulatory T cells in the tumor cell area, the number of killer T cells in the tumor cell area/the number of killer T cells in the tumor interstitial area, the number of helper T cells in the tumor cell area/the number of helper T cells in the tumor interstitial area AS independent variables and the outcome data after the immunotherapy of patients AS dependent variables.
2. 2. The method according to claim 1, wherein in step a, the detection method of CypB mRNA, FAM83H-AS1 gene transcribed RNA and LNCRNA VPS D1-AS1 in the sample comprises an RNA scope method.
3. 3. The method of claim 1, wherein in step b, the detection methods of panCK, CD3, CD4, CD8 and Foxp3 in the sample comprise Opal polychromatic fluorescent labeling.
4. 4. The method of claim 1, wherein in step b, the sample is subjected to nuclear staining to identify each individual cell.
5. 5. The method of claim 1, wherein the mathematical modeling method comprises at least one of lasso regression, support vector machines, random forests, or decision trees.

Description

Marker for predicting curative effect of lung cancer immunotherapy and construction method of scoring system Technical Field The invention relates to the technical field of biology, in particular to a marker for predicting curative effect of lung cancer immunotherapy and a construction method of a scoring system. Background Cancer is a serious disease that is seriously threatening the life and health of humans. Wherein the incidence and mortality of lung cancer predominate in the first place of cancer. For tumor patient treatment, targeting treatment aiming at specific driving gene mutation and recently emerging immunotherapy aiming at body immune system regulation have good effects, but the two treatment schemes have indications, and more than 60% of patients still have no definite gene mutation as a drug target, do not express PD-L1, only try different chemotherapeutics continuously, and decide to continue treatment or change drugs after observing the curative effect. However, currently there is no clinically effective prognostic marker for tumor patients. For patients in the middle of treatment, imaging evaluation was mainly performed to evaluate the change in tumor size, and for patients with a change of more than 15%, progress was defined. However, small changes in tumor volume, as well as molecular changes within the tumor, do not allow information to be obtained from the effects. Moreover, with respect to prognostic markers for tumor patients, a significant portion of the current studies have focused on serum markers for tumors. However, serum samples are derived from distant tumor lesions, and several studies have reported that local cytokine levels in tumors are significantly different from those in serum. Thus serum may not reflect the status of the tumor in situ. In addition, the evaluation of single markers is far less than the comprehensive evaluation of multiple markers and multiple latitudes. For these reasons, a proportion of patients with lung cancer who develop more rapidly may delay treatment because of the lack of timely use of effective treatment, and thus may not be able to stop the rapid progression of the tumor. Therefore, there is an urgent need for a molecular marker that can determine patient prognosis in early cancer, screen out patients with worse prognosis and faster progression, discover minor progression of tumors during treatment, assist in the selection of protocols and timely intervention during patient treatment, which is of great importance in saving patient lives. In view of this, the present invention has been made. Disclosure of Invention A first object of the present invention is to provide a marker for predicting the efficacy of immunotherapy of lung cancer, to solve at least one of the above problems. The second object of the invention is to provide the application of the marker in preparing a product for predicting the curative effect of lung cancer immunotherapy. The third object of the invention is to provide a kit for predicting the curative effect of lung cancer immunotherapy. The fourth object of the invention is to provide a method for constructing a scoring system for predicting the curative effect of lung cancer immunotherapy. In a first aspect, the present invention provides a marker for predicting the efficacy of immunotherapy of lung cancer, said marker comprising RNA and a cell surface marker protein; The RNA comprises mRNA of CypB, RNA transcribed from FAM83H-AS1 gene and LNCRNAVPS D1-AS1; the cell surface marker proteins include panCK, CD3, CD4, CD8 and Foxp3. In a second aspect, the invention provides the use of the above marker in the manufacture of a product for predicting the efficacy of immunotherapy for lung cancer. In a third aspect, the invention provides a kit for predicting the efficacy of immunotherapy of lung cancer, said kit comprising probes for detecting RNA transcribed from the CypB, FAM83H-AS1 genes and LNCRNA VPS D1-AS1, and biological macromolecules for detecting panCK, CD3, CD4, CD8 and Foxp 3. As a further embodiment, the biological macromolecule comprises an antibody or an antibody functional fragment. In a fourth aspect, the present invention provides a method for constructing a scoring system for predicting the efficacy of immunotherapy of lung cancer, comprising the steps of: a. Taking lung cancer tissues of a patient AS a sample, detecting mRNA of CypB, RNA transcribed from FAM83H-AS1 gene and LNCRNAVPS D1-AS1 in the sample, and obtaining expression level scores of the mRNA of CypB, the RNA transcribed from FAM83H-AS1 gene and LNCRNA VPS D1-AS 1; b. Detecting panCK, CD3, CD4, CD8 and Foxp3 in the sample in the step a, distinguishing tumor cells, killer T cells, helper T cells and regulatory T cells according to detection results, and obtaining counts of the killer T cells, the helper T cells and the regulatory T cells in a tumor cell area and a tumor interstitial area; c. Constructing a scoring system formula, wherein immune