CN111424086A - Biomarker for gastric cancer diagnosis and prognosis evaluation, application and detection kit - Google Patents
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Abstract
Compared with the prior art, the cell factor participates in various immune reactions of tumor immune cell infiltration, can realize the staged development stage of gastric cancer risk from the molecular level, quickly and accurately detect and evaluate gastric cancer prognosis, and effectively improve the sensitivity and specificity of prognosis gastric cancer detection and evaluation.
Description
Technical Field
The invention belongs to the field of biomedicine, and particularly relates to a biomarker for gastric cancer diagnosis and prognosis evaluation, a method for evaluating gastric cancer prognosis by using the biomarker and application of a diagnosis kit, in particular to application of a tumor infiltration immune cytokine I L23A as a gastric cancer diagnosis and treatment and prognosis evaluation biomarker and a diagnosis kit.
Background
Gastric Cancer (GC) is one of the most prevalent malignant tumors worldwide, with gastric cancer being the second of the death population due to cancer worldwide. According to data of international cancer research institutions, about 100 ten thousand new gastric cancer cases are newly generated every year in the world, and more than 80 ten thousand death cases exist. With the progress of treatment and diagnosis technology, various treatment and diagnosis methods are continuously available, which greatly improves the clinical diagnosis and treatment of gastric cancer, but due to the heterogeneity and individual difference of cancer, local recurrence or metastasis is easy to occur after primary gastric cancer resection, and almost 50% of patients experience postoperative in situ recurrence, ectopic metastasis and chemotherapy drug-resistant reaction. The 5-year relative survival rate of most advanced gastric cancer patients is still limited to 20%. Therefore, the condition of the gastric cancer patient can be judged in time, the prognosis survival condition of the patient can be known, and the individual treatment scheme can be adopted for different patients. Therefore, the search for simple and effective biomarkers for prognosis diagnosis of gastric cancer patients has very important guiding significance for clinical treatment.
Tumor Microenvironment (TME) is a complex system mainly composed of extracellular matrix, chemokines, cytokines and non-Tumor cells. Tumor Infiltrating Immune Cells (TIIC) are a component of non-Tumor cells in TME, and play a key role in promoting and inhibiting cancer growth. The function and composition of TIIC varies slightly depending on the immune status of the body, and they are independent prognostic factors in various types of cancer. Heterogeneous infiltrates of TIIC have been found in breast cancer and include T cells, dendritic cells, macrophages, neutrophils and mast cells. And the difference of the type, density and position of TIIC in colon cancer tissues is found, so that the method has good prognostic value. Furthermore, Klintrup et al evaluated the relationship between overall inflammatory cell response and different types of TIIC densities in colon cancer patients. The results indicate that a high proportion of mature T cells and dendritic cells, memory T cells in the tiacs subpopulation is generally indicative of a good prognosis, whereas an increase in immunosuppressive regulatory T cells correlates with a poor prognosis of colon cancer.
Interleukin 23A (I L A) is also called I L P19, the gene encodes a α subunit of heterodimeric cytokine interleukin 23(I L023), and the P40 subunit of interleukin 12(I L B) jointly form interleukin 23(I L). I L preferentially acts on memory CD4(+) T cells, can activate the transcription activator STAT4, and stimulate the production of interferon-gamma (IFNG), and has an important role in inhibiting cancer cell spreading in the environment of tumor immune cell infiltration.
There are some patents related to prognostic diagnostic markers of gastric cancer, including patent publication No. 201210549153.2, which describes the use of DACT1 in the preparation of a kit for gastric cancer detection, patent publication No. 201810749863.7, which discloses the diagnosis of early gastric cancer in an individual by detecting the high expression of PD L IM4 gene, etc., but the application of I L23A as a prognostic diagnostic marker of gastric cancer is not reported yet.
The main disadvantages of the prior art are: the clinical method for judging the prognosis of gastric cancer patients is more passive and is not beneficial to the control of the disease condition of the patients by regular postoperative reexamination and telephone follow-up. In order to achieve more precise and individualized clinical treatment, there is a great need to find more biomarkers that can be used for prognosis and evaluation of gastric cancer.
I L23A is an important cytokine I L23 subunit, preferentially acts on memory CD4(+) T cells, can activate a transcription activator STAT4, stimulates the production of interferon-gamma, directly participates in various inflammatory reactions of tumor immune cell infiltration, plays an important role in inhibiting cancer cell diffusion, plays an important role in inhibiting tumor occurrence and development, plays an important role in bridging and pivoting, and can evaluate the state of a patient and judge the prognosis of the patient by detecting the expression condition of I L23A in cancer tissues of a gastric cancer patient.
Disclosure of Invention
The present invention aims to overcome the defects of the prior art and provide a biomarker for gastric cancer diagnosis and prognosis evaluation, an application and a detection kit.
The purpose of the invention can be realized by the following technical scheme that the biomarker for gastric cancer diagnosis and treatment and prognosis evaluation adopts tumor infiltration immune cytokine I L23A as the biomarker for gastric cancer diagnosis and treatment and prognosis evaluation.
The application of the biomarker for gastric cancer diagnosis and prognosis evaluation estimates the prognosis of a patient by detecting the relative expression level of the tumor infiltration immune cytokine I L23A.
The method specifically comprises the following steps:
(1) obtaining total RNA of a gastric cancer tissue sample and a normal tissue sample, and carrying out reverse transcription to obtain cDNA;
(2) designing and synthesizing a qPCR primer of I L23A;
(3) and (3) carrying out qPCR (quantitative polymerase chain reaction) on the cDNA by using the primer synthesized in the step (2), and detecting the relative expression level change of I L23A in the gastric cancer tissue sample by using a relative quantification method.
(4) Analyzing the relation between the expression level and survival time of the gastric cancer patient I L23A, and evaluating the indication effect of the expression level on the prognosis survival time of the gastric cancer patient.
And (2) storing the gastric cancer tissue sample and the normal tissue sample in the step (1) at liquid nitrogen or-80 ℃. The method for obtaining the total RNA of the gastric cancer tissue sample and the normal tissue sample is a conventional method, such as extracting by TRIzol; reverse transcription can be performed using PrimeScriptTMAnd carrying out reverse transcription by using the RT reagent kit.
The qPCR primer in the step (2) is a conventional qPCR primer, and comprises the following qPCR primer sequences:
the relative change of the expression level of I L23A in the gastric cancer tissue sample of step (2) is calculated by the power of the fold change of the expression level of I L23A to 2 (- Δ Δ Δ Ct), wherein Δ Δ Δ Ct is Δ Ct (gastric cancer sample) - Δ Ct (control cancer sample);
Δ Ct (gastric cancer sample) ═ Ct (I L23A in gastric cancer sample) -Ct (reference gene GAPDH in gastric cancer sample);
Δ Ct (control sample) ═ Ct (I L23A in control sample) -Ct (reference gene GAPDH in control sample).
The method for detecting the relative expression level of the tumor infiltration immunocytokine I L23A further comprises a method for detecting the expression level of mRNA of the I L23A gene or a method for specifically detecting the expression level of the I L23A protein in tissues by using an anti-I L23A protein antibody.
The method for detecting the mRNA expression level of the I L23A gene comprises a northern blot analysis method, an in situ hybridization method or a custom chip method;
the method for specifically detecting the expression level of the I L23A protein in the tissue by using the antibody against the I L23A protein comprises an immunohistochemical method or an immunofluorescence method.
A detection kit containing tumor infiltration immune cytokine I L23A.
I L A is an important subunit of cytokine I L, preferentially acts on memory CD4(+) T cells, directly participates in various inflammatory reactions of tumor immune cell infiltration, and has an important role in inhibiting cancer cell diffusion, research shows that the expression level of the cytokine I3923A is remarkably different between clinical human gastric cancer tissues and tissues beside cancer, and a specific high expression phenomenon is shown in the gastric cancer tissues, which prompts that I L A has a marker function 387 in cancer diagnosis, and meanwhile, the prognosis of patients with high expression of I2 23A in the gastric cancer tissues is remarkably superior to that of patients with low expression of I L A, and has statistical difference, which shows that the expression level of I L A can clearly characterize the condition of gastric cancer patients.
By applying the tumor infiltration immune cytokine I L23A, the method can realize the hierarchical stratification of the gastric cancer risk level on the molecular level, accurately and quickly detect and evaluate the prognosis of gastric cancer patients, is convenient for clinically carrying out classified treatment on patients with different prognosis degrees, is favorable for guiding the individualized accurate treatment of the gastric cancer patients, saves the medical cost and has higher clinical application value.
Compared with the prior art, the invention has the following beneficial effects:
1) the invention provides a novel tumor infiltration immune cytokine marker I L23A for evaluating gastric cancer prognosis, which is found to be a specific high-expression phenomenon in gastric cancer tumors relative to normal tissues for the first time, the expression level is closely related to the prognosis survival period of patients, and the tumor infiltration immune cytokine marker I L23A can be used as a gastric cancer prognosis diagnosis marker.
2) The invention provides a primer, a detection method, a prognosis evaluation mode and a diagnosis kit containing the biomarker, and the detection method, the prognosis evaluation mode and the diagnosis kit can quickly, accurately and clearly judge the prognosis condition of a gastric cancer patient by detecting the expression of I L23A of a biopsy sample of the gastric cancer patient, and provide guidance for determining a treatment scheme of the patient.
3) The invention discloses the application of I L23A as a gastric cancer prognosis marker and a detection marker for the first time, wherein the marker is an important factor in gastric cancer tumor infiltration immune cells and directly participates in various immune reactions in a gastric cancer microenvironment.
Drawings
FIG. 1 is a graph showing the difference in expression level of I L23A between a gastric cancer tissue sample and a control normal sample by qPCR.
FIG. 2 is a graph showing the results of tissue chip immunohistochemical staining of 40 pairs of stomach cancer-paracarcinoma tissues, and 4 pairs of exemplified graphs were selected as follows, wherein a-d are graphs showing the results of I L23A expression in stomach cancer tissues, and e-h are graphs showing the results of I L23A expression in paracarcinoma tissues.
FIG. 3 is a graph showing the analysis of the expression level of I L23A in 40 pairs of gastric cancer and paracarcinoma tissues by tissue chip immunohistochemical technique, wherein the dots represent normal tissues and the squares represent gastric cancer tissues.
FIG. 4 is a graph showing the relationship between the expression level and survival time of gastric cancer patients I L23A by using Kaplan-Meier survival curve method.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments.
Example 1: detecting the expression quantity of the collected human gastric cancer tissues and paracancer normal tissues by utilizing a qPCR method
1. RNA extraction
1) Grinding of gastric cancer tissue and tissue adjacent to the cancer
Cleaning a mortar, a grinding pestle, scissors, a scalpel, tweezers and a spoon required for grinding by using ultrapure water, baking for 3 hours in an oven at 60 ℃, wrapping tin foil paper, baking overnight in an oven at 180 ℃, precooling the materials by using liquid nitrogen before grinding tissues, taking out clinical samples stored in the liquid nitrogen, cutting tissue blocks with the size of soybeans, putting the tissue blocks into the precooled mortar, grinding, continuously replenishing liquid nitrogen for a small amount of times, keeping the ultralow temperature state of the mortar until the tissue blocks are ground into powder, wherein the process generally requires 10min-15min, adding 1m L precooled TRIZOI after full grinding, continuously grinding, fully mixing the tissue powder and TRIZOL, transferring the mixture into a marked centrifugal tube of 1.7m L DNase/RNase Free after the TRIZOL is completely melted, extracting RNA, and freezing in a refrigerator at-80 ℃ if the mixture is not used immediately.
2) Extraction and quality inspection of total RNA
The method for separating RNA in the TRIzol specification is adopted to extract the total RNA, and the specific steps are as follows:
placing the centrifuge tube containing TRIzol-lysed tissue at room temperature for 5min, adding chloroform at a ratio of 0.2m L chloroform per ml TRIzol, covering the tube cover, shaking vigorously for 15s, standing for 5min, centrifuging at4 deg.C at 12000 × g for 15min, carefully sucking clear water phase of supernatant, transferring to new 1.7m L DNase/RNase Free centrifuge tube, adding isopropanol at a ratio of 0.5m L isopropanol/m L TRIzol, mixing by turning upside down, standing at room temperature for 10min, centrifuging at4 deg.C at 12000 × g for 10min, and allowing white RNA precipitate to exist at the bottom of the tube, carefully discarding supernatant, adding 75% ethanol at a ratio of 1m L75% ethanol per ml TRIzol for washing precipitate, dissolving at4 deg.C for 7500 g 7500 × g for 5min, centrifuging at4 deg.C, air drying for 5min-10min, adding sterile-80 deg.C, and immediately dissolving RNA in water.
After extraction, total RNA is quantified by using a Nanodrop 2000 ultramicro spectrophotometer, and then the integrity of the RNA is detected by agarose gel electrophoresis, which comprises the following specific steps:
taking 2 mu L extracted total RNA, appropriately diluting the total RNA, quantifying the total RNA by using Nanodrop 2000, using DNase/RNase-Free sterile water as a calibration solution, preparing 0.8% agarose gel, loading the RNA with 500-800ng, performing electrophoresis with 0.5 × TBE and 120V constant voltage for 20min, and observing the electrophoresis buffer on a gel imager, wherein the complete RNA sample should present 3 clear bands in an electrophoresis picture, and the bands respectively represent 28S rRNA, 18S rRNA and 5S rRNA from top to bottom, and the band brightness of the 28S rRNA is twice that of the 18S rRNA.
2. Reverse transcription of total RNA
PrimeScript from Takara was usedTMThe RT reagent kit carries out reverse transcription, comprises two processes of genome DNA removal and reverse transcription, and comprises the following specific steps:
1) the genomic DNA in the total RNA sample is removed, and the system formula is as follows:
| 5×gDNA Eraser Buffer | 2μL |
| gDNA Eraser | 1μL |
| Total RNA | 1μg |
| RNase free water | up to 10μL |
| Total volume | 10μL |
the reaction mixture was placed in a PCR apparatus for reaction at 42 ℃ for 2 min.
2) Reverse transcription reaction
The total RNA samples were equally divided into two pcr tubes, and an mRNA reverse transcription system was configured on ice, the system formulation was as follows:
and (3) after being mixed gently and uniformly, immediately placing the mixture in a PCR instrument for reverse transcription reaction, wherein the reaction conditions are as follows:
45℃ 15min
85℃ 5sec
4℃ 5min
3. qPCR reaction
Taking 0.5 mu L reverse transcription product, adding the reverse transcription product into 19.5 mu L RNase free water, and diluting by 40 times, and configuring a qPCR reaction system as follows:
| 2×SsoAdvanced SYBR Green Supermix | 5μL |
| cDNA (after dilution) | 1μL |
| Forward primer (10. mu.M) | 1μL |
| Reverse primer (10. mu.M) | 1μL |
| Total volume | 10μL |
After mixing, the mixture was immediately centrifuged, and the tube wall was flicked gently to remove air bubbles, and centrifuged again. Then placing the mixture into a StepOne PlusReal-Time PCR System, setting a program and carrying out qPCR reaction, wherein the reaction program is as follows:
4. qPCR data analysis
After the qPCR reaction is completed, the relative expression analysis is carried out on the obtained data, and the specific calculation process is as follows:
Δ Ct (gastric cancer sample) ═ Ct (I L23A in gastric cancer sample) -Ct (reference gene GAPDH in gastric cancer sample)
Δ Ct (control sample) ═ Ct (I L23A in control sample) -Ct (reference gene GAPDH in control sample)
Δ Δ Ct ═ Δ Ct (gastric cancer sample) - Δ Ct (control cancer sample)
The fold change in I L23A expression level is raised to the power of 2 (- Δ Δ Ct).
As shown in FIG. 1, the expression level of I L23A in the gastric cancer tissue sample was significantly higher than that in the control normal sample, and the difference was statistically different (p < 0.01)
The following table shows the qPCR primer sequences used in the experiments:
example 2, detection of expression levels of gastric cancer tissue and paracancer normal tissue by tissue chip immunohistochemistry:
1. frozen section of stomach cancer tissue and tissue beside cancer
The OCT embedding medium (opti-mum cutting temperature compound) is marked on a fixed head, tissues (about 24 × 24 × 3mm without embedding) with proper sizes are placed on the OCT, the surfaces of the tissues are exposed outside the OCT, the tissues are completely embedded by the OCT, the fixed head is placed on a quick cooling table in a freezer, the frozen head is frozen for 10min at about-25 ℃ (the time is slightly different according to the difference of the tissues, the tissues are larger or the fatty tissues can be longer, generally, the time is about 10 min), the frozen head is clamped on a microtome, the angle of a high-speed knife is fixed, the tissues are leveled by fine adjustment to enable the maximum section to be exposed, the fine adjustment scale is adjusted to be 5 mu m, a rolling plate is placed down to start slicing, an operating rod is rotated at a constant speed towards the same direction, the rolling plate is opened after cutting, the tissues are unfolded by a brush pen, the tissues are carefully pasted on a glass slide glass, and are arranged in sequence, and are dried in the air and stored.
2. Immunohistochemical staining of gastric cancer and paracarcinoma tissues
Slides were fixed with 4% paraformaldehyde or 10% formalin for 30 min. After fixation, the plate was washed with PBS for 5min five times. Adding 30% of H2O21 part of the mixture and 50 parts of methanol are mixed, soaked for 30min at room temperature to inactivate endogenous peroxidase, washed for 5 times by distilled water, sealed for 1.5h by 5% BSA in a wet box, the dosage of the BSA is about 300-400 mu L per piece, after the reaction is finished, the liquid is lightly wiped, a primary anti-rabbit monoclonal antibody (Bs-18146r, Bioss) is added into the wet box, diluted by 1% BSA at a dilution ratio of 1:200, reacted for 1-1.5 h at room temperature, washed for 1h by PBS after the reaction is finished, and finally the liquid is lightly wiped, and the wet box is wettedIn the box, a secondary antibody Goat-anti-Rabbit-IgG-HRP is added, diluted by 1% BSA at a dilution ratio of 1:100, and reacted at room temperature for 30 min. After the reaction was finished, the reaction was washed with PBS for about 2h, and finally the liquid was gently wiped off.
Color development: adding DAB for reaction for 2-3 min, placing the sample in tap water for 30s after the sample turns yellow, terminating the reaction, and keeping out of the sun.
Staining, soaking in 0.1-1ug/m L DAPI, staining for 1min, rinsing with PBS three times.
Dehydrating a transparent sealing sheet: 75% ethanol 20s → 85% ethanol 30s → 95% ethanol 1min → absolute ethanol 2min 2 times → xylene 2min 2 times, neutral gum block, appropriate amount of block, and care not to generate bubbles.
3. Tissue chip immunohistochemical scanning and quantitative analysis
The tissue chip is scanned by a tissue chip scanner (panoramic MIDI, 3D HISTECH), and the chip is moved step by step under the lens of the scanner to image while moving, so that all the tissue information on the tissue slice is scanned and imaged to form a file, which contains all the tissue information on the tissue slice, as shown in fig. 2.
The method comprises the steps of entering TMA software of Quant center analysis software after picture scanning is finished, setting the diameter size and the row number of tissue points of a chip, and enabling the software to automatically generate numbers, automatically identifying and setting all dark brown on a tissue section as strong positive, brown yellow as medium positive, light yellow as weak positive and blue cell nucleus as negative by applying densito Quant software in the Quant center, further identifying and analyzing the areas (unit: pixel) of the strong positive, the medium positive, the weak positive and the negative of each tissue point, and the percentage of the positive, and finally grading H-SCORE.
4. Analysis of clinical significance of I L23A expression in cancer tissues in combination with clinical survival information of gastric cancer patients
P <0.05 is considered to be statistically significant, R software (update version 3.5.2) 40 is used for evaluating the expression level of I L A in gastric cancer and tissues beside the gastric cancer in all analyses, as shown in FIG. 3, the expression level of I L A in gastric cancer tissues and tissues beside the gastric cancer is statistically significant (p < 0.01), the expression level of the I in gastric cancer tissues is significantly higher than that of tissues beside the gastric cancer, H-SCORE expression value in the experiments is used as a reference standard, 40 gastric cancer patients are divided into an I L A high expression group and an I L A low expression group according to the median of gene expression, a Kaplan-Meier survival curve is drawn by combining the survival data of the survival period, the analysis result is shown in FIG. 4, I L A high expression gastric cancer patients is longer than that of I L A low expression gastric cancer patients, the difference has statistical significance (p < 0.01), and the analysis result is used as a prognostic marker which can be evaluated as an important diagnosis marker for gastric cancer treatment.
The present invention is not limited to the above-described embodiments, and those skilled in the art should make improvements and modifications within the scope of the present invention based on the disclosure of the present invention.
Claims (10)
1. A biomarker for diagnosis and prognosis evaluation of gastric cancer is characterized in that tumor infiltration immune cytokine I L23A is used as the biomarker for diagnosis and prognosis evaluation of gastric cancer.
2. The use of the biomarker for gastric cancer diagnosis and prognosis evaluation according to claim 1, wherein the prognosis of the patient is evaluated by detecting the relative expression level of the tumor-infiltrating immune cytokine I L23A.
3. The use of the biomarker for diagnosis and prognosis of gastric cancer according to claim 2, wherein the method for detecting the relative expression level of tumor infiltrating immune cytokine I L23A is qPCR method, and comprises the following steps:
(1) obtaining total RNA of a gastric cancer tissue sample and a normal tissue sample, and carrying out reverse transcription to obtain cDNA;
(2) designing and synthesizing a qPCR primer of I L23A;
(3) and (3) carrying out qPCR (quantitative polymerase chain reaction) on the cDNA by using the primer synthesized in the step (2), and detecting the relative expression level change of I L23A in the gastric cancer tissue sample by using a relative quantification method.
4. The use of the biomarker for gastric cancer diagnosis and prognosis evaluation according to claim 3, wherein the gastric cancer tissue sample and the normal tissue sample in step (1) are stored in liquid nitrogen or at-80 ℃.
5. The use of the biomarker for gastric cancer diagnosis and prognosis evaluation according to claim 3, wherein the qPCR primers in step (2) are conventional qPCR primers, comprising the following qPCR primer sequences:
6. the use of the biomarker for gastric cancer diagnosis and prognosis evaluation according to claim 3, wherein the relative expression level change of I L23A in the gastric cancer tissue sample of step (2) is calculated by the power of the fold change of the expression level of I L23A (- Δ Δ Ct) of 2, wherein Δ Δ Ct- Δ Ct (gastric cancer sample) - Δ Ct (control cancer sample);
Δ Ct (gastric cancer sample) ═ Ct (I L23A in gastric cancer sample) -Ct (reference gene GAPDH in gastric cancer sample);
Δ Ct (control sample) ═ Ct (I L23A in control sample) -Ct (reference gene GAPDH in control sample).
7. The use of the biomarker for gastric cancer diagnosis and prognosis evaluation according to claim 2, wherein the method for detecting the relative expression level of tumor infiltrating immunocytokine I L23A further comprises the method for detecting the expression level of I L23A gene mRNA or the expression level of I L23A protein in tissue by using an anti-I L23A protein antibody.
8. The use of the biomarker for gastric cancer diagnosis and prognosis evaluation according to claim 7, wherein the method for detecting the mRNA expression level of I L23A gene comprises northern blot analysis, in situ hybridization or custom chip method;
the method for specifically detecting the expression level of the I L23A protein in the tissue by using the antibody against the I L23A protein comprises an immunohistochemical method or an immunofluorescence method.
9. The use of the biomarker for gastric cancer diagnosis and prognosis evaluation according to claim 2, wherein the relationship between the expression level and survival of I L23A in gastric cancer patients is analyzed to evaluate the effect of the expression level on the prognosis survival of gastric cancer patients.
10. A detection kit containing tumor infiltration immune cytokine I L23A.
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