CN112763712B - Tumor diagnosis marker and application thereof - Google Patents

Abstract

The invention relates to a group of tumor diagnosis markers and application thereof. According to the invention, through analyzing immune cells in 288 clinical normal blood samples and blood samples of 186 cancer patients, the CD3 ^‑CD19^‑CD16⁺ NK cell proportion, the CD3 ^‑CD19^‑CD16^‑ NK cell proportion, the TH CM proportion and the TH effector cell proportion are obviously different in a healthy group and a tumor group, and the diagnosis index of the immune cell in the blood samples is used for distinguishing healthy people from tumor patients, and the AUC is more than 0.96. The invention provides a new kit for tumor diagnosis, which can be used for clinical tumor detection, and is particularly suitable for tumor screening in physical examination projects.

Description

Tumor diagnosis marker and application thereof

Technical Field

The invention relates to the field of disease diagnosis, in particular to a group of tumor diagnosis markers and application thereof.

Background

The cellular immune function of the body is closely related to the occurrence and development of tumors.

The role of soluble IL-2R, IL-6 and T cell subsets in diagnosis of benign ovarian malignancies [ J ]. Journal of practical tumors, 2001.) is disclosed in literature (Liu Yan, zhu Meiqi): the ELISA method and the indirect immunofluorescence method are used for measuring the T lymphocyte subpopulation of peripheral blood of patients, and as a result, the peripheral blood CD3 ⁺ and CD8 ⁺ of all patients are not obviously changed, 13 cases of CD4 ⁺ cells in 17 cases of ovarian malignant tumors are obviously reduced, the CD4/CD8 ratio is obviously reduced, and compared with a control group and benign ovarian lesions, the difference is obvious.

Document (Qian Xiaoqin, lin Jianchao, wang Sheliang. Value study of T cell subpopulation detection in assisted diagnosis of malignant patients [ J ]. Zhejiang Utility medicine 2016,21 (3): 170-171.) discloses: peripheral blood T cell subpopulations were detected with a flow cytometer for each of the digestive system tumor (n=130), the hematological tumor (n=88), the lung cancer patient (n=108), and the healthy control group (n=79), and comparisons were made between the groups. As a result, the CD3 ⁺、CD4⁺、CD4⁺/CD8+ of the lung cancer, the digestive system tumor and the blood system tumor patients are obviously lower than that of the healthy control group (P < 0.05), and the CD8 ⁺ and the NK are obviously higher than those of the healthy control group (P < 0.05); comparison between various tumor groups, CD4 ⁺、CD8⁺、CD4⁺/CD8⁺ of the blood tumor group compared with the lung cancer group and the digestive system tumor group, the difference has statistical significance (P < 0.05).

Literature (Su Wen. Detection of immune cell subsets from forty-thousand cancer patients and their clinical significance [ C ]// twelfth national academy of immunology.) discloses: the first 10 patients with high-grade cancers (including lung, stomach, colorectal, cervical, breast, esophagus, thyroid, liver, ovary and lymph) diagnosed in 2012 to 2016 of the hospital were collected for 39,319 cases, and 904 normal physical examination persons were used as non-tumor control groups. All subjects used flow cytometry to detect expression levels of peripheral blood CD4 ⁺T、CD8⁺ T cells, NK cells, and regulatory T cells. Results there was a clear difference in CD4 ⁺T、CD8⁺ T, NK and regulatory T cell levels for each study group (p < 0.05), with the cd4+ T ratio being significantly higher for cervical, breast, thyroid, ovarian cancer patients than for the control group (p < 0.05) and significantly lower for lymphoma patients than for the control group (p < 0.05); the cd8+t ratio was the exact opposite of CD4 ⁺ T in thyroid and lymphoid cancer patients, i.e., the former was lower than control and the latter was higher than control (p < 0.05); for NK cells, the proportion of cells in patients with lung, stomach, colorectal and esophageal cancers is obviously higher than that in the control group (p < 0.05).

However, no report is currently available on the CD3 ^-CD19^-CD16⁺ NK cell fraction, CD3 ^-CD19^-CD16^- NK cell fraction, TH CM fraction or TH effector cell fraction as tumor markers for distinguishing healthy and tumor patients.

Disclosure of Invention

The object of the present invention is to address the deficiencies of the prior art and to provide a set of tumour diagnostic markers and their use.

In a first aspect, the invention provides the use of a reagent for detecting lymphocyte proportion, CD3 ^-CD19^-CD16⁺ NK cell proportion, CD3 ^-CD19^-CD16^- NK cell proportion, TH CM proportion or TH effector cell proportion in the preparation of a tumour diagnostic kit.

In one embodiment of the present invention, the sample to be tested is blood.

As another embodiment of the invention, the kit is used to distinguish whether an individual is a healthy person or a tumor patient.

As another embodiment of the present invention, the tumor patient refers to an individual having a tumor but a tumor type is not yet in an unknown state.

In a second aspect, the invention provides the use of lymphocyte proportion, CD3 ^-CD19^-CD16⁺ NK cell proportion, CD3 ^-CD19^-CD16^- NK cell proportion, TH CM proportion or TH effector cell proportion as biomarkers in the preparation of a tumor diagnostic kit.

In one embodiment of the present invention, the sample to be tested is blood.

As another embodiment of the invention, the kit is used to distinguish whether an individual is a healthy person or a tumor patient.

As another embodiment of the present invention, the tumor patient refers to an individual having a tumor but a tumor type is not yet in an unknown state.

The invention has the advantages that:

1. The invention discovers that the proportion of CD3 ^-CD19^-CD16⁺ NK cells, the proportion of CD3 ^-CD19^-CD16^- NK cells, the proportion of TH CM or the proportion of TH effector cells are different between healthy people and tumor patients for the first time, and the invention has high diagnosis efficiency for distinguishing healthy people from tumor patients through analysis, so that the invention can be used for clinical tumor diagnosis, and particularly can play a good role in the tumor screening of physical examination.

2. Flow cytometry detects cell surface specific markers by measuring individual cells flowing through the instrument. The process begins with the selection of fluorescently labeled antibodies that are specific for cell surface markers that characterize the target cell population. These cell surface markers are often glycoproteins called cluster of differentiation markers, which aid in differentiating cell subsets. Flow cytometry can be performed on a variety of tissues including peripheral blood, bone marrow aspirate, skin biopsy, and tissue culture cell lines. If the cell has a selected label on the surface, binding of the corresponding antibody-fluorophore will absorb the laser energy and then be released as light of a specific wavelength as the cell passes through the laser. The emitted light is detected by an optical system sensitive to various wavelengths, allowing information on multiple surface markings to be read simultaneously and collected by an associated computer. It can analyze tens of thousands of cells at high speed and can measure a plurality of parameters from one cell at the same time. Thus, flow cytometry allows for multi-parameter, rapid quantitative analysis of individual cells or other biological particles, rapid determination of biological properties of individual cells or organelles, and the collection of specific cells or organelles from a population by classification. Flow cytometry is a key tool for analyzing cell subsets and their complex interactions in immune and biological processes. It promotes our insight into the immune system and may play a fundamental role in determining disease prognosis, therapeutic effect, and developing personalized therapeutic agents. The flow cytometry has higher detection speed and large amount of sample analysis capability, a plurality of proteins of single cells can be simultaneously analyzed, the detection accuracy is high, the detection cost is low, however, the requirements on professional technicians for detection are higher, the generated data amount is huge, the flow data analysis can become very complex, and the flow data analysis almost completely depends on the control of analysts, so that the analysis flow is immobilized, and the data is analyzed under the unified standard. The application overcomes the technical difficulty, completes the analysis and data processing of multi-index and comprehensive immune cells, and further screens and obtains the index with great clinical diagnosis significance.

3. The tumor diagnosis method is completed by collecting peripheral blood, is convenient for obtaining materials and has little pain for patients.

Drawings

Fig. 1: B. NK panel detection identifies immune cell subsets and flow of data processing.

Fig. 2: B. NK panel detection identifies immune cell subsets and the main outcome of data processing.

Fig. 3: t panel identifies immune cell subsets and data processing flows.

Fig. 4: t panel identifies the immune cell subpopulation and the main outcome of data processing.

Fig. 5: immune status radar map.

Fig. 6: the detection indexes based on B cells and NK cells can effectively distinguish tumor patients from healthy people.

Fig. 7: the 1 st, 6 th and 7 th items of BNK detection indexes are used for distinguishing tumor patients from healthy people respectively, so that a good prediction effect can be achieved. Items 1,6,7 refer to the predicted effects of lymphocyte proportion, CD3 ^-CD19^-CD16⁺ NK cell proportion and CD3 ^-CD19^-CD16^- NK cell proportion, respectively. The "1,6,7" curve refers to the predicted effect of combining 1,6,7 terms.

Fig. 8: the detection index based on T cells can effectively distinguish tumor patients from healthy people.

Fig. 9: the 11 th and 12 th T cell detection indexes are used for distinguishing tumor patients from healthy people respectively, so that a good prediction effect can be achieved. Items 11, 12 refer to the predicted effect of TH CM proportion or TH effector cell proportion, respectively; the "11, 12" curves are the predicted effects of combining 11, 12 indices.

Detailed Description

The following detailed description of the invention provides specific embodiments with reference to the accompanying drawings.

Example 1

1. Collecting clinical samples

From 5 months 2020 to 8 months 2020, we collected samples from the gold mountain hospital oncology department and clinical laboratory at the university of double denier for a total of 474 cases, including 288 cases of immune normal blood samples and 186 cases of cancer patients.

Age distribution of two sample populations was 18-70 years old; wherein the cancer patients comprise 50 cases of esophagus cancer, 26 cases of gastrointestinal cancer, 60 cases of breast cancer and 50 cases of lung cancer; in this item, the immune normal blood sample is used as a control group, and diseases such as infection, autoimmune diseases, tumor and the like which are clearly likely to influence the immune state are eliminated.

2. Preparation and detection of fresh sample detection marker sample

Fresh anticoagulated whole blood is taken out in a 1.5 ml centrifuge tube, and serum is separated out after centrifugation and stored in a low-temperature refrigerator. Adding erythrocyte lysate with 6 times of cell sediment volume, and performing ice lysis for 15min; after lysis, washing once with 1 XPBS at 1500rpm for 5min, and obtaining cell pellet after centrifugation; 50 μl of antibody mixture (antibody: pbs=1:200) was added to the cell pellet, and the cells were protected from light at room temperature for 15min; after staining, washing with 1 XPBS once at 1500rpm for 5min; after centrifugation to obtain a cell pellet, 500. Mu.l of 1 XPBS was added to resuspend cells into flow-through tubes. Filtering with 300-400 mesh filter screen before on-machine detection, and placing on ice in dark place after filtering to wait for detection. Finally, the cells were analyzed and detected by flow cytometry.

List of experimental reagents:

3. Specific detection content

4. Data processing method

After data are obtained, carrying out data analysis processing by using Flowjo V10 analysis software and GRPHPAD PRISM 8.0.0, and adopting t-test; the difference p <0.05 is statistically significant.

5. Experimental results

According to the experimental data obtained we analyzed the results as follows, T lymphocyte subpopulations, B lymphocytes and NK cells were different between different patient populations, wherein the ratios of helper T cells, killer T cells and regulatory T cells were all different between the normal control group and the fresh tumor sample group, the fresh tumor sample group and the cryopreserved tumor sample group, and B lymphocytes and NK cells were different between the normal sample group and the tumor sample group. We can go through these differences (e.g., as follows) to gain insight into the actual condition of the patient's immune system to aid the clinician's analysis of the disease, pathogenesis, formulation of patient's personalized treatment regimen, and assessment of patient prognosis.

The analytical flow and results of B panel are shown in fig. 1 and 2, which demonstrate the flow of the identification of immune cell subsets by nine-color antibody staining (as demonstrated in B, NK panel above) and the processing of the finishing data, and present the main results. I.e., a B lymphocytes between the normal control group and the cancer group; b dendritic cells; natural killer cells of CD16 ⁺; natural killer cells of d CD16 ^-; e regulatory T lymphocytes; f activating regulatory T lymphocytes; g memory-regulatory T lymphocytes; h differences in naive regulatory T lymphocytes.

The analytical flow and results of T panel are shown in FIGS. 3 and 4, which demonstrate the flow of the identification of immune cell subsets by nine-color antibody staining (as demonstrated in T panel above) and the processing of the finishing data, and which present the main results. I.e., between the normal control group and the cancer group, a inhibits/cytotoxic T lymphocytes; b helper/inducer T lymphocytes; c effector memory-inhibited/cytotoxic T lymphocytes; d central memory inhibiting/cytotoxic T lymphocytes; e effector suppressor/cytotoxic T lymphocytes; f naive suppressor/cytotoxic T lymphocytes; g effector memory helper T lymphocytes; h effector memory helper/inducer T lymphocytes; i effector helper/inducer T lymphocytes; j naive helper/inducer T lymphocytes; k helper T lymphocyte type 1; type 2T helper lymphocytes; m helper T lymphocyte type 17; differences in n regulatory T lymphocytes.

An immune state radar chart is produced, see fig. 5.

Further analysis found that peripheral blood immune cell subpopulation analysis was closely related to disease. At present, no item similar to the (multi-index and comprehensive) immune state assessment of the application exists clinically; through correlation analysis, the key indexes (the proportion of lymphocytes is the proportion of lymphocytes to total peripheral blood white blood cells, the proportion of CD3 ^-CD19^-CD16⁺ NK cells to CD3 ^-CD19^-CD16^- NK cells is the proportion of CD16 ⁺ or CD16 ^- cells in CD3 ^-CD19^- cells, the proportion of TH CM is the proportion of TH CM cells to total CD3 ⁺CD4⁺ helper T lymphocytes), and the proportion of TH effector cells is the proportion of TH effector cells to total CD3 ⁺CD4⁺ helper T lymphocytes) in the project can be used for distinguishing healthy people from tumor patients remarkably (figures 6-9), so that immune states are closely related to diseases (AUC > 0.96); by evaluating the immune status, immune abnormalities in healthy people/patients can be found in time and timely intervention can be given.

The foregoing is merely a preferred embodiment of the present invention, and it should be noted that modifications and additions may be made to those skilled in the art without departing from the method of the present invention, which modifications and additions are also to be considered as within the scope of the present invention.

Claims (4)

1. Use of a reagent for detecting a proportion of CD3 ^-CD19^-CD56⁺CD16⁺ NK cells, a proportion of CD3 ^-CD19^-CD56⁺CD16^- NK cells, a proportion of TH CM or a proportion of TH effector cells in the preparation of a kit for diagnosing a tumor, wherein the proportion of CD3 ^-CD19^-CD56⁺CD16⁺ NK cells to CD3 ^-CD19^-CD56⁺CD16^- NK cells is the proportion of CD16 ⁺ or CD16 ^- cells in CD3 ^-CD19^-CD56⁺ NK cells, the proportion of TH CM is the proportion of TH CM cells to total CD3 ⁺CD4⁺ helper T lymphocytes, the proportion of TH effector cells is the proportion of TH effector cells to total CD3 ⁺CD4⁺ helper T lymphocytes, and the detected sample is blood, the kit for distinguishing whether an individual is a healthy person or a tumor patient.

2. The use according to claim 1, wherein the tumor patient is an individual suffering from a tumor but having a tumor type that is not yet known.

Use of a CD3 ^-CD19^-CD56⁺CD16⁺ NK cell fraction, a CD3 ^-CD19^-CD56⁺CD16^- NK cell fraction, a TH CM fraction or a TH effector cell fraction as biomarker for the preparation of a tumor diagnostic kit, said CD3 ^-CD19^-CD56⁺CD16⁺ NK cell fraction and CD3 ^-CD19^-CD56⁺CD16^- NK cell fraction being the fraction of CD16 ⁺ or CD16 ^- cells in CD3 ^-CD19^-CD56⁺ NK cells, TH CM fraction being the total CD3 ⁺CD4⁺ helper T lymphocyte fraction of TH CM cells, TH effector cell fraction being the total CD3 ⁺CD4⁺ helper T lymphocyte fraction of TH effector cells, the sample being blood, for the detection of a patient, said kit being for the differentiation of healthy or tumor patients.

4. The use according to claim 3, wherein the tumor patient is an individual suffering from a tumor but having a tumor type that is not yet known.