Marker for lung cancer immunotherapy prognosis

Abstract

The invention belongs to the technical field of biology, and particularly relates to a marker for lung cancer immunotherapy prognosis. The invention finds that the expression levels of serum metabolites tert-butyl 3-hydroxybutyrate and isocamphoric acid of patients with effective ICIs immunotherapy and patients with ineffective ICIs immunotherapy are significantly different. The two metabolites are used as markers for immunotherapy prognosis of lung cancer patients, and have high sensitivity and specificity; diagnosis efficiency is high and operation is simple; stable existence in serum and accurate result are realized.

Description

Technical Field

[0001] The invention belongs to the field of biotechnology, and specifically relates to a marker for the prognosis of lung cancer immunotherapy. Background Art

[0002] Lung cancer is a serious malignant tumor that originates mainly from cells in the bronchi and alveoli. According to the World Health Organization, lung cancer is one of the leading causes of cancer death worldwide. It is mainly divided into two categories: non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC).

[0003] Treatments for lung cancer include surgery, radiotherapy, chemotherapy, targeted therapy, and immunotherapy (Ma Yunfei, Yu Mingwei, Li Guangda, et al. Research progress in traditional Chinese and Western medicine on hypercoagulable state of lung cancer [J]. Journal of Modern Integrated Traditional Chinese and Western Medicine, 2020.). The treatment of advanced lung cancer mainly relies on systemic treatments such as chemotherapy, radiotherapy, and targeted therapy (Liu Yaoyao, Miao Jianlong. Research progress in immunotherapy combined with radiotherapy for non-small cell lung cancer [J]. Journal of Clinical Pulmonary Medicine, 2023.)

[0004] Immune checkpoint inhibitors (ICIs) are a new type of cancer treatment method that blocks the binding of immune checkpoints to their ligands, relieves the inhibition of tumor cells on the immune system, and thus enhances the body's anti-tumor immune response (Zhang Wenxin, Guo Hongjie, Pan Xiaohui, et al. Research progress of immune checkpoint inhibitors [J]. Pharmaceutical Progress, 2022.). Immune checkpoint inhibitors (ICIs) mainly include antibody inhibitors targeting programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1). These drugs play an important role in the treatment of various cancers by blocking inhibitors of T cell activation and function and enhancing the immune system's ability to attack tumor cells (Douglas B. Johnson, S. Chandra et al. "Immune Checkpoint Inhibitor Toxicity in 2018." JAMA (2018).). Immunotherapy represented by immune checkpoint inhibitors (ICIs) has been widely used in the treatment of lung cancer, showing good efficacy and significantly improving the survival rate of patients.

[0005] At present, PD-L1 immunohistochemical detection is the only clinically accepted predictive marker for the efficacy of anti-PD-1 treatment, but its predictive accuracy is relatively weak. There are certain deficiencies in the detection of PD-L1 as a marker for predicting the efficacy of immunotherapy. The main reasons are that there is still no consensus on the interpretation criteria of immunohistochemical detection results and the PD-L1 reporting specifications, and the results of different test kits may be inconsistent. There are certain challenges in PD-L1 immunohistochemical detection, including the differences between different detection methods and antibody clones that may lead to inconsistent results. In addition, PD-L1 expression may be heterogeneous within the tumor, which requires obtaining tissue samples from multiple tumor areas to reduce the risk of false negative results (Hyojin Kim, H. Kwon et al. "PD-L1 immunohistochemical assays for assessment of therapeutic strategies involving immune checkpoint inhibitors in non-small cell lung cancer: a comparative study." Oncotarget (2017).). As a result, the detection results of PD-L1 cannot fully reflect the true situation of PD-L1 expression. Therefore, PD-L1 expression is not a sufficiently comprehensive independent biomarker for clinical treatment decisions.

[0006] In recent years, tumor mutation burden (TMB), microsatellite instability (MSI) and mismatch repair gene deletion, tumor infiltrating lymphocytes, human leukocyte antigen (HLA), peripheral blood neutrophil-to-lymphocyte ratio, circulating tumor cells, etc. have shown promise as optional predictive biomarkers for the efficacy of anti-PD-1 therapy. However, these markers currently have certain limitations and controversies in predicting the efficacy of immunotherapy for lung cancer. Therefore, finding effective and reliable efficacy prediction biomarkers is very necessary for achieving precision immunotherapy for lung cancer. At present, there is an urgent need to discover markers that can be used to predict the efficacy of immunotherapy for lung cancer.

[0007] Blood biomarkers have shown broad application prospects in the diagnosis and treatment of various diseases due to their easy access, low cost and non-invasive characteristics. They are an ideal method for evaluating the efficacy of ICIs immunotherapy for lung cancer. The detection of serum metabolites can be used to analyze the differences in the expression of small molecule metabolites in different organisms under the same disease state, so as to discover markers that can be used to evaluate the efficacy of disease treatment. High-pressure liquid chromatography-mass spectrometry (LC-MS) is currently a common technical method for detecting serum metabolites. The application of LC-MS technology to detect small molecule metabolites has the advantages of high throughput, high resolution, high sensitivity and good specificity. Different organisms with lung cancer will cause abnormal expression of small molecule metabolites. Therefore, LC-MS technology can be used to detect the expression of serum metabolites in lung cancer patients before treatment, and screen out serum metabolite spectra that can be used to predict the efficacy of ICIs immunotherapy for lung cancer, so as to further achieve more accurate ICIs immunotherapy and improve the benefit rate of immunotherapy for lung cancer patients. Summary of the invention

[0008] The present invention found that the expression levels of serum metabolites tert-butyl 3-hydroxybutyrate and isocamphoric acid were significantly different between patients who were effective in ICIs immunotherapy and patients who were ineffective in ICIs immunotherapy. Based on this, the present invention was completed.

[0009] In a first aspect, the present invention provides a marker for the prognosis of lung cancer immunotherapy, wherein the marker is tert-butyl 3-hydroxybutyrate or isoketocamphoric acid.

[0010] Furthermore, when the expression level of tert-butyl 3-hydroxybutyrate in the biological sample of the lung cancer patient is ≤25410 charge number (Z) or the expression level of isocamphoric acid in the biological sample of the lung cancer patient is ≤9161 (Z), the lung cancer patient has a good prognosis after immunotherapy.

[0011] Furthermore, the biological sample of the subject is selected from blood and / or urine.

[0012] Preferably, the blood sample of the subject is at least one of peripheral blood, plasma and / or serum.

[0013] In a second aspect, the present invention provides use of the marker described in the first aspect in preparing a reagent for predicting the prognosis of lung cancer immunotherapy.

[0014] Furthermore, when the expression level of tert-butyl 3-hydroxybutyrate in the biological sample of the lung cancer patient is ≤25410(Z) or the expression level of isocamphoric acid in the biological sample of the lung cancer patient is ≤9161(Z), the lung cancer patient has a good prognosis after immunotherapy.

[0015] Furthermore, the biological sample of the subject is selected from blood and / or urine.

[0016] Preferably, the blood sample of the subject is at least one of peripheral blood, plasma and / or serum.

[0017] In a third aspect, the present invention provides a kit for predicting the prognosis of lung cancer immunotherapy, wherein the kit contains a reagent for detecting the expression level of the marker described in the first aspect.

[0018] Furthermore, when the expression level of tert-butyl 3-hydroxybutyrate in the biological sample of the lung cancer patient is ≤25410(Z) or the expression level of isocamphoric acid in the biological sample of the lung cancer patient is ≤9161(Z), the lung cancer patient has a good prognosis after immunotherapy.

[0019] Furthermore, the biological sample of the subject is selected from blood and / or urine.

[0020] Preferably, the blood sample of the subject is at least one of peripheral blood, plasma and / or serum.

[0021] Furthermore, the kit may be an ELISA detection kit and / or a colloidal gold detection kit.

[0022] Furthermore, the diagnostic method of the kit includes a direct method, an indirect method, a double antibody sandwich method and / or a competitive method.

[0023] Beneficial Effects

[0024] Compared with the prior art, the advantages of the marker for prognosis of lung cancer patients with immunotherapy and its application provided by the present invention are:

[0025] (1) High sensitivity and specificity;

[0026] (2) High diagnostic efficiency and simple operation;

[0027] (3) It is stable in serum and the results are accurate;

[0028] (4) It has clinical application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 The expression levels of serum metabolite 3-hydroxybutyrate tert-butyl ester in the effective group and the ineffective group.

[0030] Figure 2 The expression levels of serum metabolite isocamphoric acid in the effective group and the ineffective group.

[0031] Figure 3 Effect of serum metabolites in the experimental group on predicting the efficacy of immunotherapy for lung cancer.

[0032] Figure 4 The expression levels of serum metabolite 3-hydroxybutyrate tert-butyl ester in the validation group were compared between the effective group and the ineffective group.

[0033] Figure 5 The expression levels of serum metabolite isocamphoric acid in the validation group in the effective group and the ineffective group.

[0034] Figure 6 Validation group serum metabolites in predicting the efficacy of immunotherapy for lung cancer. DETAILED DESCRIPTION

[0035] The specific embodiments of the present invention are further described below. It should be noted that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation of the present invention. In addition, the technical features involved in the embodiments described below can be combined with each other as long as they do not conflict with each other.

[0036] The experimental methods in the following examples are conventional methods unless otherwise specified, and the experimental materials used in the following examples are commercially available unless otherwise specified.

[0037] Explanation of terms

[0038] Solid tumor efficacy evaluation method: It is a crucial link in the field of tumor treatment. It is not only related to the selection and adjustment of treatment plans, but also directly affects the patient's prognosis and quality of life. The WHO standard is one of the earliest standards used to evaluate the efficacy of solid tumors, but due to its lack of quantitative indicators, the efficacy evaluation is not accurate enough. In order to overcome this defect, the International Union Against Cancer (UICC) and the National Cancer Institute (NCI) of the United States and other institutions jointly developed the RECIST (Response Evaluation Criteria in Solid Tumors) standard, which evaluates the efficacy by quantifying the changes in tumor size and has become an internationally accepted solid tumor efficacy evaluation standard.

[0039] Example 1: Standards for elimination

[0040] A. Inclusion Criteria

[0041] (1) All patients with lung cancer were pathologically confirmed;

[0042] (2) No surgery, radiotherapy, chemotherapy, or targeted therapy before immunotherapy;

[0043] (3) The medical records of lung cancer patients are complete.

[0044] B. Exclusion criteria

[0045] (1) Combined with hypertension, diabetes, and heart disease;

[0046] (2) Combined with benign lung diseases (such as pneumonia, tuberculosis, emphysema, chronic obstructive pulmonary disease, etc.);

[0047] (3) Combined with malignant tumors of other tissues and organs (such as liver cancer, gastric cancer, breast cancer, etc.).

[0048] C. Experimental Group

[0049] A total of 20 patients with lung cancer who had never been treated for ICIs were admitted to Beijing Chest Hospital affiliated to Capital Medical University and received ICIs immunotherapy, including 16 males and 4 females, aged 43-80 years old. All lung cancer patients were diagnosed by pathological histology.

[0050] D. Validation Group

[0051] A total of 30 patients with lung cancer who were initially treated with ICIs were admitted to Beijing Chest Hospital affiliated to Capital Medical University. Among them, 26 were male and 4 were female, aged 44-82 years. All lung cancer patients were diagnosed by pathological histology.

[0052] Example 2 ICIs immunotherapy

[0053] A. First-line ICIs immunotherapy

[0054] Monotherapy: pembrolizumab or atezolizumab;

[0055] Dual immunotherapy combination: nivolumab combined with ipilimumab.

[0056] B. Second-line ICIs immunotherapy

[0057] Nivolumab monotherapy;

[0058] Pembrolizumab monotherapy;

[0059] Atezolizumab monotherapy.

[0060] C. Evaluation of the efficacy of ICIs immunotherapy

[0061] After at least 2 cycles of immunotherapy, the solid tumor efficacy evaluation method is used to assess the efficacy of ICIs immunotherapy in lung cancer patients. The evaluation results are divided into: CR (complete remission), PR (partial remission), SD (stable disease) and PD (progressive disease).

[0062] Patients with PR and SD as the evaluation results were included in the effective treatment group;

[0063] Patients with PD as the evaluation result were included in the ineffective treatment group.

[0064] Example 3 Test group serum metabolites

[0065] A. Specimen Collection and Processing

[0066] (1) Collect 4 ml of fasting venous blood from lung cancer patients, centrifuge and separate serum, and store at ultra-low temperature;

[0067] (2) Take 100 μL of the sample in (1), add 400 μL of protein precipitant, and shake to mix;

[0068] (3) Ultrasonic extraction of the system in (2) and standing at low temperature;

[0069] (4) Centrifuging the system of (3), aspirating the supernatant, filtering, transferring to an LC injection bottle, and storing at ultra-low temperature;

[0070] (5) All sample extracts were mixed in equal volumes to prepare quality control samples (QC);

[0071] (6) Load samples for liquid chromatography-mass spectrometry and analyze data.

[0072] B. Data Analysis

[0073] The metabolomics data were statistically analyzed using SPSS 17.0 software, and the data were expressed as mean ± standard deviation. The concentration levels between groups were compared using t-test, and the rates between groups were compared using χ2 test. 2 The difference was statistically significant when P < 0.05. The receiver operating characteristic curve (ROC) was used to analyze the value of serum metabolites in predicting the efficacy of immunotherapy for lung cancer.

[0074] C. Test Results

[0075] As shown in Table 1, there were 14 samples in the effective immunotherapy group and 6 samples in the ineffective immunotherapy group. The results of serum metabolite detection in the experimental group showed that tert-butyl 3-hydroxybutyrate and isocamphoric acid were differential metabolites of the two.

[0076] like Figure 1 and Figure 2 As shown in the figure, the expression levels of serum metabolites tert-butyl 3-hydroxybutyrate and isocamphoric acid in the ICIs immunotherapy ineffective group were significantly higher than those in the treatment effective group, and the difference was statistically significant (P < 0.05).

[0077] Table 1. Results of serum metabolites in the pre-test group (mean ± standard deviation)

[0078]

[0079] As shown in Table 2, the positive rate of serum metabolite tert-butyl 3-hydroxybutyrate in the ineffective immunotherapy group was higher, reaching 50.0%, while the positive rate in the effective immunotherapy group was lower, only 11.7%, and the difference was statistically significant (P < 0.05). The positive rate of serum metabolite isocamphoric acid was higher in the ineffective group (50.0%), while the positive rate in the effective group was lower (12.0%), and the difference was statistically significant (P < 0.05).

[0080] like Figure 3 As shown in the ROC curve, the area under the curve (AUC) of tert-butyl 3-hydroxybutyrate was 0.816, and the AUC of isocamphoric acid was 0.772, indicating that serum metabolites tert-butyl 3-hydroxybutyrate and isocamphoric acid have clinical application value in predicting the efficacy of immunotherapy for lung cancer.

[0081] Table 2. Positive rate of serum metabolites in the pre-test group in patients with lung cancer immunotherapy

[0082]

[0083] Example 4 Validation Group Serum Metabolites

[0084] A. Specimen Collection and Processing

[0085] (1) Collect 4 ml of fasting venous blood from lung cancer patients, centrifuge and separate serum, and store at ultra-low temperature;

[0086] (2) Take 100 μL of the sample in (1), add 400 μL of protein precipitant, and shake to mix;

[0087] (3) Ultrasonic extraction of the system in (2) and standing at low temperature;

[0088] (4) Centrifuging the system of (3), aspirating the supernatant, filtering, transferring to an LC injection bottle, and storing at ultra-low temperature;

[0089] (5) All sample extracts were mixed in equal volumes to prepare quality control samples (QC);

[0090] (6) Load samples for liquid chromatography-mass spectrometry and analyze data.

[0091] B. Data Analysis

[0092] The metabolomics data were statistically analyzed using SPSS 17.0 software, and the data were expressed as mean ± standard deviation. The concentration levels between groups were compared using t-test, and the rates between groups were compared using χ2 test. 2 The difference was statistically significant when P < 0.05. The receiver operating characteristic curve (ROC) was used to analyze the value of serum metabolites in predicting the efficacy of immunotherapy for lung cancer.

[0093] C. Test Results

[0094] As shown in Table 3, there were 24 samples in the effective immunotherapy group and 6 samples in the ineffective immunotherapy group. The results of serum metabolite detection in the experimental group showed that tert-butyl 3-hydroxybutyrate and isocamphoric acid were differential metabolites of the two.

[0095] like Figure 4 and Figure 5 As shown in the figure, the expression levels of serum metabolites tert-butyl 3-hydroxybutyrate and isocamphoric acid in the ICIs immunotherapy ineffective group were significantly higher than those in the treatment effective group, and the difference was statistically significant (P < 0.05).

[0096] Table 3. Serum metabolite detection results of the validation group (mean ± standard deviation)

[0097]

[0098] As shown in Table 4, the positive rate of serum metabolite tert-butyl 3-hydroxybutyrate in the ineffective immunotherapy group was higher, reaching 50.0%, while the positive rate in the effective immunotherapy group was lower, only 14.2%, and the difference was statistically significant (P < 0.05). The positive rate of serum metabolite isocamphoric acid was higher in the ineffective group (50.0%), while the positive rate in the effective group was lower (13.3%), and the difference was statistically significant (P < 0.05).

[0099] like Figure 6 As shown in the ROC curve, the area under the curve (AUC) of tert-butyl 3-hydroxybutyrate was 0.855, and the AUC of isocamphoric acid was 0.759, indicating that serum metabolites tert-butyl 3-hydroxybutyrate and isocamphoric acid have clinical application value in predicting the efficacy of immunotherapy for lung cancer.

[0100] Table 4. Positive rate of serum metabolites in validation group in patients undergoing immunotherapy for lung cancer

[0101]

Claims

1. A marker for the prognosis of lung cancer immunotherapy, wherein the marker is tert-butyl 3-hydroxybutyrate or isoketocamphoric acid; when the expression level of tert-butyl 3-hydroxybutyrate in a biological sample of a lung cancer patient is ≤25410 charge number (Z) or the expression level of isoketocamphoric acid in a biological sample of a lung cancer patient is ≤9161 (Z), the lung cancer patient has a good prognosis after immunotherapy.

2. Use of the marker as claimed in claim 1 in the preparation of a reagent for predicting the prognosis of lung cancer immunotherapy.

3. A kit for predicting the prognosis of lung cancer immunotherapy, the kit comprising a reagent for detecting the expression level of the marker according to claim 1.

4. The biological sample of the subject according to any one of claims 1 to 3 is selected from blood and / or urine.

5. The blood sample of the subject as claimed in claim 4 is at least one of peripheral blood, plasma and / or serum.

6. The kit as claimed in claim 3 can be an ELISA detection kit and / or a colloidal gold detection kit.

7. The diagnostic method of the kit as claimed in claim 6 comprises direct method, indirect method, double antibody sandwich method and / or competitive method.

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