Immune-related early screening marker for predicting and diagnosing radioiodine therapy curative effect response after papillary thyroid carcinoma total resection based on Olink proteomics as well as selection method and application of immune-related early screening marker

Abstract

The invention discloses an immune-related early screening marker for predicting and diagnosing radioiodine treatment effect response after total resection of papillary thyroid carcinoma based on Olink proteomics as well as a selection method and application of the immune-related early screening marker. A serum sample before radioiodine treatment after total resection of a papillary thyroid carcinoma patient is measured; up-regulated protein HGF in a group with poor iodine treatment effect is screened out, the reliability of the up-regulated protein HGF for predicting the radioactive iodine treatment effect is verified on the basis of an independent queue, and it is found that serum psTg and serum HGF are independent predictive factors of disease-free lifetime. The HGF protein screened by the invention can be used for evaluating the curative effect of radioactive iodine treatment and providing a target spot for mechanism research, and meanwhile, the protein can be used for preparing a kit which is poor in iodine treatment effect and is used for screening before radioactive iodine treatment.

Description

Technical Field

[0001] This invention relates to the field of medical technology, specifically to immune-related early screening biomarkers based on Olink proteomics for predicting and diagnosing the response to radioactive iodine therapy after total resection of papillary thyroid carcinoma, as well as their selection methods and applications. Background Technology

[0002] According to the 2020 Global Cancer Incidence and Mortality Database compiled by the International Agency for Research on Cancer (IARC) of the World Health Organization, thyroid cancer is the most common malignant tumor of the endocrine system, ranking ninth in global cancer incidence. Papillary thyroid carcinoma (PTC) is the most important histopathological type, accounting for more than 85% of thyroid cancers. The most common first-line treatment option for PTC patients is radioactive iodine therapy (RAIT) after total thyroidectomy; however, the efficacy of RAIT varies from patient to patient. Different RAIT responses determine different subsequent clinical strategies. The American Thyroid Association recommends long-term active follow-up for PTC patients, especially those at intermediate or high risk, after RAIT. The 2015 American Thyroid Association guidelines state that serological and imaging data 6–12 months after RAIT should be used as indicators to assess the efficacy of RAIT in PTC patients, dividing them into satisfactory response (ER) and non-satisfactory response (NER) groups. Therefore, there is an urgent need for a reliable and convenient method to identify patients with poor RAIT response at an early stage.

[0003] However, almost all existing molecular classifications of PTC rely on tumor tissue removed by puncture or surgery. BRAF V600E Coexistence of TERT promoter mutations in PTC significantly increases tumor invasiveness, recurrence risk, and mortality. High Ki-67 expression is significantly associated with lymph node metastasis, TNM stage progression, and shortened disease-free survival in PTC. (Based on BRAF) V600EA comprehensive scoring system combining mutations, TERT promoter mutations, and the Ki-67 index can effectively differentiate between high-risk and low-risk PTC patients. However, these molecular classifications rely on immunohistochemistry or gene sequencing in clinical practice, and the tumor heterogeneity and limited biopsy depth in PTC also reduce the representativeness of biopsy samples to some extent. Furthermore, when PTC patients undergo surgery and are scheduled for RAIT, the effectiveness of radioiodine therapy cannot be reassessed using biopsy samples. However, blood is a readily available biological sample in clinical practice. The body secretes proteins into serum or plasma, and these proteins can indicate the pathological process of the disease or predict disease prognosis or treatment efficacy by detecting protein abundance. Proteins, as executors of life activities, directly reflect the physiological or pathological state of the body through changes in their abundance and function. Detecting the abundance of various proteins in blood samples before RAIT after thyroid cancer resection using high-throughput sequencing technology can be used to predict the therapeutic response to iodine therapy. Therefore, establishing an early screening model based on proteomics protein biomarkers to identify and monitor protein biomarkers is helpful for the early screening of patients with poor RAIT response.

[0004] Changes in the immune status within the tumor microenvironment (TME) of PTC patients are closely related to tumor progression. However, existing research in the field of PTC immunology mainly focuses on local immune responses within the TME, with little attention paid to the relationship between systemic immunity and RAIT efficacy in PTC patients. Existing classic systemic immune inflammatory markers include neutrophil / lymphocyte ratio, lymphocyte / monocyte ratio, monocyte / lymphocyte ratio, platelet / lymphocyte ratio, and systemic immune inflammatory indices. However, these indicators primarily rely on complete blood counts, while serum immunoproteomics is the ideal indicator of systemic immunity. Therefore, this invention utilizes Olink proteomics detection technology to highly sensitively and specifically target and detect immune response-related proteins, enabling early screening of patients with poor RAIT response. Summary of the Invention

[0005] In view of the problems existing in the prior art, the purpose of this invention is to predict and diagnose immune-related early screening biomarkers for the response to radioactive iodine therapy after total resection of papillary thyroid carcinoma based on Olink proteomics, as well as the selection method and application thereof. By using Olink proteomics technology to identify early screening proteins in patients with poor response to radioactive iodine therapy, this invention effectively addresses the current problem of insufficient attention to systemic immune inflammatory markers, and also solves the problems of time-consuming, insufficient biomarker sensitivity and specificity in current blood sample screening methods.

[0006] To achieve the above objectives, the technical solution of this invention is as follows:

[0007] This invention proposes an immune-related early screening biomarker based on Olink proteomics for predicting and diagnosing the response to radioactive iodine therapy after total resection of papillary thyroid carcinoma, wherein the biomarker is the upregulated protein HGF.

[0008] This invention also discloses a method for selecting immune-related early screening biomarkers based on Olink proteomics to predict and diagnose the response to radioactive iodine therapy after total resection of papillary thyroid carcinoma, comprising the following steps:

[0009] Step 1: Olink proteomics detection and analysis: Serum samples were collected from patients with papillary thyroid carcinoma before radioactive iodine therapy following total resection. 96 inflammation panels* and 96 Immunoassay Panel* measures serum protein levels;

[0010] Step 2: Based on the efficacy evaluation criteria, group the patients from Step 1 into two groups: those satisfied with the efficacy of RAIT and those with poor efficacy.

[0011] Step 3: Based on the protein data obtained in Step 1, differentially expressed proteins are selected as feature variables using three methods: LASSO regression analysis, independent samples t-test, and proteins with the highest single AUC values.

[0012] Step 4: Analyze the differentially expressed proteins obtained in Step 3 and screen for upregulated proteins in the group with poor treatment efficacy;

[0013] Step 5: Perform receiver operating characteristic curve analysis on the upregulated protein and calculate the area under the characteristic curve (AUC).

[0014] Step 6: Collect serum samples from an independent cohort of patients with papillary thyroid carcinoma before radioactive iodine treatment after total resection. Use enzyme-linked immunosorbent assay (ELISA) to detect upregulated proteins in the serum samples from the independent cohort; at the same time, detect the level of thyroglobulin stimulated before radioactive iodine treatment.

[0015] Step 7: Divide the independent cohorts from Step 6 into groups based on the efficacy evaluation criteria, namely those with satisfactory RAIT efficacy and those with poor efficacy; perform receiver operating characteristic (AUC) analysis on the upregulated proteins and psTg from Step 6, and calculate the area under the characteristic curve (AUC).

[0016] Step 8: Combine the upregulated protein described in Step 7 with psTg to establish a Cox proportional hazards regression model to predict disease-free survival.

[0017] Further, in step one, serum samples were extracted from patients with papillary thyroid carcinoma before radioactive iodine therapy following total resection. 96 inflammation panels* and The 96-immune panel* measures serum protein levels, and common proteins from the inflammation and immune panels are removed during statistical analysis.

[0018] Furthermore, the efficacy evaluation criteria in step two were based on the 2015 American Thyroid Association guidelines. Satisfactory efficacy was defined as negative imaging results 6–12 months after total thyroidectomy and radioactive iodine therapy, negative thyroglobulin antibodies, and suppressor thyroglobulin <0.2 ng / ml or stimulatory thyroglobulin <1 ng / ml. The remaining patients were defined as the poor efficacy group.

[0019] This invention proposes the application of an immune-related early screening biomarker based on Olink proteomics to predict and diagnose the response to radioactive iodine therapy after total resection of papillary thyroid carcinoma. The early screening biomarker is used in the preparation of a kit for screening patients with poor response to iodine therapy after total resection of papillary thyroid carcinoma before radioactive iodine therapy.

[0020] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0021] 1) This invention uses Olink proteomics technology to identify early screening proteins in patients who do not respond well to radioactive iodine therapy, effectively solving the problem that there is currently little focus on systemic immune inflammatory markers, and also solving the problems of long time consumption, insufficient sensitivity and specificity of markers in current blood sample screening.

[0022] 2) The Olink proteomics technology utilized in this invention is based on extension of proximity (PEA) analysis, the core of which lies in designing a pair of specific antibodies for each target protein. This not only ensures high specificity of the immune response, but also effectively avoids cross-reactions at the immunological level by labeling each pair of antibodies with complementary DNA single strands, utilizing the specificity of DNA hybridization. This achieves biologically ultrasensitive and unbiased targeted proteomics detection, which is particularly suitable for blood samples that traditional methods cannot handle. Applying this technology to analyze immune-related proteins in the serum of patients with poor response to RAIT, combined with feature selection and dimensionality reduction techniques, it effectively mines useful information from high-throughput data, ultimately screening out a key protein, which is confirmed in an independent cohort.

[0023] 3) Compared with the prior art, the serum samples of the present invention can be easily obtained, causing little harm to patients. The equipment for detecting serum proteins is also widely used in various hospitals, and professional testing personnel are also widely employed. Attached Figure Description

[0024] Figure 1 (a) shows the LASSO coefficient pathway diagram for 141 proteins; (b) shows the cross-validation curves.

[0025] Figure 2(a) shows the abundance expression of the differentially expressed protein FASLG in the two groups with satisfactory (ER) and poor (NER) efficacy before radioactive iodine therapy; (b) shows the abundance expression of the differentially expressed protein CXCL12 in the two groups with ER and NER efficacy before radioactive iodine therapy; (c) shows the abundance expression of the differentially expressed protein HGF in the two groups with ER and NER efficacy before radioactive iodine therapy.

[0026] Figure 3 The middle figure shows the ROC curve for predicting the response to radioactive iodine therapy using the differential protein HGF.

[0027] Figure 4 (a) is a differential expression plot of serum psTg in the ER and NER groups in an independent cohort; (b) is a ROC curve of serum psTg predicting response to radioactive iodine therapy in an independent cohort; (c) is a differential expression plot of serum HGF in the ER and NER groups in an independent cohort; (d) is a ROC curve of serum HGF predicting response to radioactive iodine therapy in an independent cohort.

[0028] Figure 5 (a) Univariate Cox regression survival curves of serum psTg in an independent cohort; (b) Univariate Cox regression survival curves of serum HGF in an independent cohort. Detailed Implementation

[0029] The present invention will be further described below with reference to the accompanying drawings and embodiments, but the scope of protection of the present invention is not limited to the scope described.

[0030] Example 1: Early screening and identification of immune-related biomarkers for poor response to radioactive iodine therapy after thyroid papillary carcinoma resection.

[0031] Twenty-eight participants who visited the Department of Nuclear Medicine at the First Affiliated Hospital of Shanxi Medical University between January and August 2021 were included in this study. All participants underwent RAIT treatment prior to receiving the treatment. 99m TcO4-thyroid imaging and 131 Whole-body scans revealed thyroid tissue contrast in some patients, with no significant difference in the amount of residual thyroid tissue among patients. This study was conducted in accordance with the principles of the Declaration of Helsinki and approved by the Ethics Committee of the First Affiliated Hospital of Shanxi Medical University (2021-K-K176).

[0032] The inclusion criteria were: (1) patients diagnosed with PTC; (2) patients who had undergone thyroidectomy; (3) patients who planned to receive RAIT treatment; and thyroid scans performed before RAIT. 131I. Whole-body scintigraphy; (4) Before RAIT, levothyroxine was discontinued for 4 weeks and serum TSH increased to >30mIU / ml; (5) No glucocorticoid or immunosuppressive drug treatment was received within 4 months; (6) Levothyroxine was administered as replacement therapy after RAIT; (7) Peripheral blood samples were collected completely 1-2 days before RAIT; (8) The patient was willing to participate in this study and signed an informed consent form; (9) The patient promised to voluntarily accept and abide by this experimental protocol.

[0033] Exclusion criteria were: (1) patients with acute inflammatory diseases, autoimmune diseases, chronic inflammatory diseases, or other cancers and other diseases that may cause changes in immunity; and (2) patients who did not have a follow-up visit after RAIT.

[0034] Sixteen patients were in the satisfactory response (ER) group and 12 were in the non-satisfactory response (NER) group. The mean age of the participants was 41 years, and there were no statistically significant differences in age and BMI between the ER and NER groups (P>0.05). Women accounted for 71.43% of all cancer patients, with 87.50% in the ER group and 50.0% in the NER group.

[0035] Based on Olink proteomics, this paper describes the prediction and diagnosis of immune-related early screening biomarkers for the response to radioactive iodine therapy after total resection of papillary thyroid carcinoma, their selection methods, and applications, including the following steps:

[0036] Step 1: Serum samples were collected from the above 28 patients with papillary thyroid carcinoma before radioactive iodine therapy following total resection. Inflammation panel* and The immune panel* measured serum protein levels; proteins shared between the inflammation and immune panels were removed during statistical analysis, resulting in a total of 141 proteins included in the analysis. Specific information on these proteins is shown in the table below:

[0037]

[0038]

[0039]

[0040]

[0041]

[0042]

[0043]

[0044]

[0045]

[0046] Olink proteomics assays utilize a dual-antibody system linked to DNA barcodes. The created double-stranded DNA "barcodes" are unique to the specific antigen and their number is proportional to the initial concentration of the target protein. Immediately after hybridization and extension, PCR amplification is performed, and the amplicon is finally quantified using microfluidic qPCR. Results are presented as log2-scaled normalized protein expression (NPX) values; higher NPX values ​​indicate higher protein abundance.

[0047] Step 2: Based on the efficacy evaluation criteria, group the patients from Step 1 into those who are satisfied with the efficacy of RAIT and those who are not satisfied with the efficacy.

[0048] In step two, the efficacy evaluation criteria were based on the 2015 American Thyroid Association guidelines. Satisfactory efficacy was defined as patients who had negative radiographic imaging, negative thyroglobulin antibody (TgAb), and suppressor thyroglobulin (Tg) <0.2 ng / ml or stimulatory thyroglobulin (Tg)(sTg) <1 ng / ml 6–12 months after total thyroidectomy and radioactive iodine therapy. The remaining patients were defined as the poor efficacy group.

[0049] Step 3: Use three methods to screen differentially expressed proteins from the protein data obtained in Step 1: LASSO regression analysis, independent samples t-test, and protein ranking by single AUC value;

[0050] The specific process of step three is as follows:

[0051] 3.1: The 141 protein data obtained in Step 1 were analyzed using three methods: LASSO regression analysis (using five-fold cross-validation to determine the optimal regularization strength, selecting protein biomarkers with non-zero coefficients under this parameter), independent samples t-test (P<0.05), and validation of the intersection of the results for individual AUC-ranked proteins. This resulted in three differentially expressed proteins being identified as feature variables. Figure 1 It can be seen that the specific process is as follows:

[0052] 3.1.1: Using 141 proteins as independent variables, LASSO regression analysis was performed to generate a penalty function that reduces the number of variables in the regression model by the coefficients. When the standard error λ of the minimum distance is 0.247, three eigenvalues ​​among the 141 independent variables are non-zero: FASLG, CXCL12, and HGF.

[0053] 3.1.2: Independent samples t-test was used to compare differentially expressed proteins between the ER and NER groups before radioactive iodine treatment. Differentially expressed proteins with P < 0.05 were selected as FASLG, CXCL12, and HGF.

[0054] 3.1.3: Calculate the AUC values ​​of 141 proteins and select the top five proteins: FASLG, CXCL12, HGF, IL-10RB, and IL15;

[0055] 3.1.4: Jointly verify the differentially expressed proteins selected by the above three methods and take the intersection to finally determine FASLG, CXCL12 and HGF proteins as feature variables;

[0056] Step 4: Draw a graph showing the differences in the differentially expressed proteins described in Step 3.1 between the ER and NER groups before radioactive iodine treatment;

[0057] Depend on Figure 2 As shown, HGF was upregulated in the NER group before radioactive iodine treatment.

[0058] Step 5: Perform receiver operating characteristic (AUC) analysis on the upregulated protein HGF and calculate the area under the characteristic curve. Figure 3 As shown.

[0059] Step six involves collecting independent cohorts to further validate the reliability of HGF in predicting the efficacy of radioactive iodine therapy.

[0060] 6.1: Sixty participants who visited the Department of Nuclear Medicine at the First Affiliated Hospital of Shanxi Medical University between January and August 2021 were re-enrolled. All participants underwent RAIT treatment prior to receiving the treatment. 99m TcO4-thyroid imaging and 131 Whole-body scans revealed thyroid tissue contrast in some patients, with no significant difference in the amount of residual thyroid tissue among patients. This study was conducted in accordance with the principles of the Declaration of Helsinki and approved by the Ethics Committee of the First Affiliated Hospital of Shanxi Medical University (2021-K-K176). The inclusion and exclusion criteria, as well as the efficacy evaluation criteria, were consistent with those described in Example 1.

[0061] 6.2: The HGF protein in the 60 subjects in step 6.1 was detected by enzyme-linked immunosorbent assay (ELISA), and the psTg level was also detected.

[0062] Step 7: According to the efficacy evaluation criteria, the satisfactory efficacy (ER) group consisted of 30 participants, and the poor efficacy (NER) group consisted of 30 participants; receiver operating characteristic (AUC) curve analysis was performed on the HGF protein and psTg levels of the 60 participants from Step 6.1, and the area under the characteristic curve (AUC) was calculated. Figure 4 As shown.

[0063] Step 8: Combine the HGF protein from Step 7 with psTg to establish a Cox proportional hazards regression model to predict disease-free survival (DFS). The specific steps are as follows:

[0064] We collected disease-free survival time (days) data from 60 patients. Gender, age, HGF protein, and psTg were included in a univariate Cox proportional regression model, while variables with P < 0.05 (i.e., serum HGF protein and serum psTg) were included in a multivariate Cox proportional regression model. We concluded that serum psTg level (P = 0.01) and pre-RAIT serum HGF (P = 0.008) were considered independent predictors of disease-free survival (DFS).

Claims

1. An immune-related early screening biomarker for predicting and diagnosing the response to radioactive iodine therapy after total resection of papillary thyroid carcinoma based on Olink proteomics, characterized in that... The biomarker is the upregulated protein HGF.

2. A method for selecting immune-related early screening biomarkers based on Olink proteomics for predicting and diagnosing the response to radioactive iodine therapy after total resection of papillary thyroid carcinoma, as described in claim 1, characterized in that... Includes the following steps: Step 1: Olink proteomics detection and analysis: Serum samples were collected from patients with papillary thyroid carcinoma before radioactive iodine therapy following total resection. and Measure serum protein levels; Step 2: Based on the efficacy evaluation criteria, the patients from Step 1 were grouped into two groups: those who were satisfied with the efficacy of radioactive iodine therapy and those who were not satisfied with the efficacy. Step 3: Based on the protein data obtained in Step 1, differentially expressed proteins are selected as feature variables using three methods: LASSO regression analysis, independent samples t-test, and proteins with the highest single AUC values. Step 4: Analyze the differentially expressed proteins obtained in Step 3 and screen for upregulated proteins in the group with poor treatment efficacy; Step 5: Perform receiver operating characteristic curve analysis on the upregulated protein and calculate the area under the characteristic curve (AUC). Step Six: Collect serum samples from an independent cohort of patients with papillary thyroid carcinoma before radioactive iodine therapy after total resection. Use enzyme-linked immunosorbent assay (ELISA) to detect upregulated proteins in the serum samples from the independent cohort; at the same time, detect the level of thyroglobulin before radioactive iodine therapy. Step 7: Group the independent cohorts from Step 6 according to the efficacy evaluation criteria, namely, those with satisfactory efficacy and those with poor efficacy of radioactive iodine therapy; perform receiver operating characteristic curve analysis on the upregulated proteins and pre-radioactive iodine-stimulated thyroglobulin from Step 6, and calculate the area under the characteristic curve (AUC). Step 8: Combine the upregulated protein described in Step 7 with the thyroglobulin stimulated before radioactive iodine therapy to establish a Cox proportional hazards regression model to predict disease-free survival.

3. The method for selecting immune-related early screening biomarkers based on Olink proteomics for predicting and diagnosing the response to radioactive iodine therapy after total resection of papillary thyroid carcinoma, as described in claim 2, is characterized in that... In step one, serum samples were collected from patients with papillary thyroid carcinoma before radioactive iodine therapy following total thyroidectomy. and Serum protein levels were measured, and common proteins in the inflammation and immunity panels were removed during statistical analysis.

4. The method for selecting immune-related early screening biomarkers based on Olink proteomics for predicting and diagnosing the response to radioactive iodine therapy after total resection of papillary thyroid carcinoma, as described in claim 2, is characterized in that... In step two, the efficacy evaluation criteria were based on the 2015 American Thyroid Association guidelines. Satisfactory efficacy was defined as negative imaging results, negative thyroglobulin antibodies, and suppressor thyroglobulin < 0.2 ng / ml or stimulatory thyroglobulin < 1 ng / ml 6–12 months after total thyroidectomy and radioactive iodine therapy. The remaining patients were defined as the poor efficacy group.

5. The application of the Olink proteomics-based immune-related early screening biomarker for predicting and diagnosing the response to radioactive iodine therapy after total resection of papillary thyroid carcinoma, as described in claim 1, characterized in that... The kit for screening patients with poor response to iodine therapy after total resection of papillary thyroid carcinoma using the aforementioned early screening biomarkers was prepared before radioactive iodine therapy.

Images