WO2023050909A1 - Cga基因作为靶点在制备用于诊断和治疗耐药实体瘤药物的应用 - Google Patents

Cga基因作为靶点在制备用于诊断和治疗耐药实体瘤药物的应用 Download PDF

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WO2023050909A1
WO2023050909A1 PCT/CN2022/100014 CN2022100014W WO2023050909A1 WO 2023050909 A1 WO2023050909 A1 WO 2023050909A1 CN 2022100014 W CN2022100014 W CN 2022100014W WO 2023050909 A1 WO2023050909 A1 WO 2023050909A1
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cga
drug
sgc7901
protein
cells
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赵晓迪
聂勇战
曹田宇
卢媛媛
樊代明
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中国人民解放军空军军医大学
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Definitions

  • the present invention relates to solid tumor drug resistance diagnosis and prognosis evaluation technology, in particular to the new discovery based on the high expression of glycoprotein hormone alpha polypeptide (CGA, namely glycoprotein hormones, alpha polypeptide) in solid tumor tissue and lead to solid tumor drug resistance, the gene Or/and proteins are used as targets for the diagnosis and prognosis evaluation of solid tumor drug resistance.
  • CGA glycoprotein hormone alpha polypeptide
  • Chemotherapy plays an important role in the treatment of solid tumors.
  • most patients undergo chemotherapy drug resistance, leading to treatment failure.
  • tumors develop resistance to one drug (single-drug resistance) during chemotherapy, and at the same time, cross-resistance to other drugs that have not been used and have different chemical structures and mechanisms of action. This phenomenon is called multidrug resistance.
  • the study of the mechanism of drug resistance in solid tumors and the development of drugs that reverse drug resistance are important research areas in the prevention and treatment of cancer.
  • In order to reverse the drug resistance of solid tumors improve the efficacy of solid tumor chemotherapy, reduce the risk of drug resistance and prolong the survival rate, there is an urgent need in this field to study the mechanism and key gene targets of drug resistance in solid tumors through various methods.
  • one aspect of the present invention provides the application of the CGA gene or its encoded protein as a target in the preparation of reagents or kits for drug resistance diagnosis and/or prognosis assessment of solid tumors.
  • the solution of the present invention is the application of the detection reagent of CGA gene or its encoded protein in the preparation of reagents or kits for the diagnosis of drug resistance and/or prognosis evaluation of solid tumors.
  • reagents or kits are tested by RT-PCR, real-time quantitative PCR, digital PCR, fluorescent dye method, resonance light scattering method, sequencing or biological mass spectrometry, in situ hybridization, Northern blotting, chip, high-throughput sequencing platform, immunoassay Histochemical or enzyme-linked immunosorbent assay to detect the messenger RNA of CGA gene transcription or the protein encoded by CGA gene.
  • the reagent or kit contains specific primers for amplifying CGA genes, probes hybridizing with CGA gene nucleotide sequences, or antibodies or antibody fragments specifically binding to CGA proteins.
  • the antibody is a monoclonal antibody or a polyclonal antibody.
  • the detection sample of the reagent or kit is serum, plasma, cells, cell culture supernatant, urine, tissue or tissue lysate.
  • the present invention also provides the application of the CGA gene or its encoded protein as a target in the preparation of drugs for treating drug-resistant solid tumors.
  • the solution of the present invention is the application of CGA gene expression inhibitors or protein expression inhibitors for the preparation of drugs for the treatment of drug-resistant solid tumors.
  • the CGA gene expression inhibitor is selected from CRISPR gene editing therapeutic drugs, antisense nucleic acid drugs, siRNA drugs or miRNA drugs that block the normal transcription or post-transcriptional translation of the CGA gene by CRISPR/Cas9 gene editing technology or RNA interference technology .
  • the CGA protein expression inhibitor is selected from protein glycosylation inhibitors, protein phosphorylation inhibitors or protein phosphorylation inhibitors that affect the post-translational modification process of CGA protein or affect the stability of CGA protein, and affect the expression level, activity or function of CGA protein. and antibodies.
  • the present invention also provides a method for constructing a drug-resistant solid tumor cell research model, for which the method provided by the present invention includes: knocking out the CGA gene in the solid tumor cell.
  • solid tumor cells are cultured in a medium containing one or more chemotherapeutic drugs to construct initial drug-resistant solid tumor cells, and then the CGA gene in the initial drug-resistant solid tumor cells is knocked out to obtain drug-resistant solid tumor cells.
  • CRISPR/Cas9 technology was used to knock out the CGA gene in the initial drug-resistant solid tumor cells to obtain drug-resistant solid tumor cells.
  • the present invention also provides a method for constructing a drug-resistant solid tumor animal model.
  • the method provided by the present invention includes: injecting the drug-resistant solid tumor cells constructed by the above method into the animal model to construct a drug-resistant solid tumor animal model.
  • Fig. 1 is a graph showing the results of CGA mRNA expression between gastric cancer drug-resistant cell lines SGC7901 ADR and SGC7901 VCR and control cell line SGC7901 in Example 1.
  • Fig. 2 is a graph showing the results of CGA protein expression in cells and culture supernatants between gastric cancer drug-resistant cell lines SGC7901 ADR and SGC7901 VCR and control cell line SGC7901 in Example 2.
  • Fig. 3 is an immunofluorescence staining diagram of CGA protein expression between gastric cancer drug-resistant cell lines SGC7901 ADR and SGC7901 VCR and control cell line SGC7901 in Example 3.
  • Fig. 4 is the expression change of CGAmRNA under the sublethal dose of chemotherapeutic drug induction condition of chemotherapy drug-sensitive gastric cancer cell SGC7901 and NCI-N87 in embodiment 4;
  • Fig. 4 A is SGC7901 and NCI-N87 cell cultured in fluorouracil (1 ⁇ g/ml)
  • Fig. 4B is the first day of SGC7901 and NCI-N87 cells under the culture condition of doxorubicin (0.5 ⁇ g/ml). Comparison of CGAmRNA expression levels after 1, 3, 5, and 7 days with that of untreated control cells.
  • Figure 5A is the IHC staining micrograph of CGA protein in the post-chemotherapy gastric cancer tissue (Post) and its paired pre-chemotherapy gastric cancer tissue (Pre) of 6 representative cases of gastric cancer patients with stable or progressive disease after chemotherapy in Example 5
  • Fig. 5B is the IHC score statistical chart of CGA expression in gastric cancer tissues of 31 patients with stable or progressive disease after chemotherapy and their paired gastric cancer tissues before chemotherapy; Micrographs of IHC staining of CGA protein in post-chemotherapy gastric cancer tissues of gastric cancer patients and their paired pre-chemotherapy gastric cancer tissues.
  • FIG. 6A is the IHC staining of CGA protein in xenograft tissues of mice treated with control group (Saline) or chemotherapeutic drug treatment group (Fluorouracil) based on 4 cases of gastric cancer patient-derived xenograft (Patient derived xenograft, PDX) model Micrographs;
  • FIG. 6B is a graph showing the growth curves of the tumor volumes of 4 groups of PDX mice receiving chemotherapy and their control group.
  • Figure 7A shows the detection of enzyme-linked immunosorbent assay (Enzyme-linked immunosorbent assay, ELISA) from the normal control group (Normal), gastric cancer non-chemotherapy group (Non-chemo), gastric cancer neoadjuvant chemotherapy group (Neoadjuvant chemotherapy) and gastric cancer palliative chemotherapy Statistical graph of the CGA protein content in plasma samples of the group (Palliativechemo);
  • Figure 7B shows that patients in the neoadjuvant chemotherapy group for gastric cancer were divided into stable disease (SD) and partial remission (PR) groups according to their chemotherapy efficacy evaluation, and the two groups of patients Statistical chart of CGA protein content in plasma;
  • Figure 7C is a statistical chart of CGA protein content in plasma samples of patients in the neoadjuvant chemotherapy group for gastric cancer before and after surgery; - Statistical graph of CGA protein content in paired plasma samples after 6 cycles of chemotherapy;
  • Figure 7E shows that patients in the gastric cancer pal
  • Figure 7F shows 64 gastric cancer patients who received chemotherapy and were followed up, divided into CGA low expression and CGA high expression according to the median plasma CGA concentration (304.7pg/ml) , The survival curves of the two groups of patients.
  • Figure 8A shows the results of Oncomine data analysis, and there is no statistical difference in the expression of CGA between gastric cancer tissues and normal gastric mucosal tissues
  • Figure 8B shows the results of GEPIA data analysis, and there is no statistical difference in the expression of CGA between gastric cancer tissues and normal gastric mucosal tissues.
  • Figure 9A is a schematic diagram of the CGA gene knockout site in SGC7901 ADR and SGC7901 VCR cells and a map of DNA sequencing results;
  • Figure 9B is Western blotting (Westernblotting, WB) verification of two single clones of CGA gene knockout in SGC7901 ADR and SGC7901 VCR cells CGA protein expression in cell lines (KO-1 and KO-2).
  • Figure 10A is the fitting curve of cell survival rate and drug concentration of SSGC7901 ADR cells of CGA gene WT and KO under different concentrations of fluorouracil and doxorubicin;
  • Figure 10B is the fitting curve of SGC7901 VCR cells of CGA gene WT and KO at different concentrations The fitting curves of cell viability and drug concentration under the treatment of fluorouracil and paclitaxel.
  • Figure 11A is a statistical graph of the number of apoptosis in SGC7901 ADR cells of CGA gene WT and KO after treatment with fluorouracil and doxorubicin;
  • Figure 11B is a statistics of the number of apoptosis in SGC7901 VCR cells of CGA gene WT and KO after treatment with fluorouracil and paclitaxel picture.
  • Figure 12A is the cell growth curve of SGC7901 ADR cells with CGA gene WT and KO treated with fluorouracil and doxorubicin
  • Figure 12B is the cell growth curve of SGC7901 VCR cells with CGA gene WT and KO treated with fluorouracil and paclitaxel.
  • Figure 13A and 13B are the tumor growth curves of SGC7901 ADR and SGC7901 VCR cells of CGA gene WT and KO in nude mice under the treatment conditions of fluorouracil, doxorubicin and paclitaxel;
  • Figure 13C and 13D are the SGC7901 ADR of CGA gene WT and KO and SGC7901 VCR cells in nude mice under the treatment conditions of fluorouracil, doxorubicin and paclitaxel;
  • Figure 13E and 13F are CGA gene WT and KO SGC7901 ADR and SGC7901 VCR cells in nude mice treated with fluorouracil, doxorubicin and paclitaxel Representative micrographs of Ki-67 and cleaved Caspase-3 protein IHC staining of tumors treated with mycin and paclitaxel.
  • Figure 14A is a schematic diagram of the screening strategy for specific miRNAs targeting CGA
  • Figure 14B is the expression of miR-17-3p, miR-630, miR-708-3p, miR-761 in gastric cancer drug-resistant cells SGC7901 ADR and SGC7901 VCR and their parents Expression in SGC7901 cells
  • Figure 14C is WB detection of cells after transfection of miR-17-3p, miR-630, miR-708-3p, and miR-761 mimetics in gastric cancer drug-resistant cells SGC7901 ADR and SGC7901 VCR Changes in the expression of CGA protein.
  • Figure 15A is the SGC7901 ADR cells transfected with miR-708-3p and miR-761 mimics, the cell survival rate under the treatment of fluorouracil and doxorubicin;
  • Figure 15B is the transfection of miR-708-3p and miR-761 mimics The cell viability of SGC7901 VCR cells treated with fluorouracil and paclitaxel.
  • Figure 16A is the tumor growth curve of SGC7901 ADR cells under 6 different treatment conditions after tumor formation
  • Figure 16B is the tumor pictures of SGC7901 ADR cells under 6 different treatment conditions after tumor formation
  • Figure 16C is the tumor growth curve of SGC7901 ADR cells after tumor formation
  • Figure 16D is a representative micrograph of SGC7901 ADR cells after tumor formation under 6 groups of different treatment conditions, after IHC staining of Ki-67 and cleaved Caspase-3 protein .
  • Figure 17A is the cell survival rate of SGC7901 ADR cells with CGA gene knockout after adding CGA recombinant protein (recombinant CGA, rCGA), under the treatment of fluorouracil and doxorubicin;
  • Figure 17B is the SGC7901 ADR cells with CGA gene knockout After transfection with CGA expression plasmids of WT, N52Q, N78Q or DM, the cell survival rate under the treatment of fluorouracil and doxorubicin.
  • Glycoprotein hormone alpha polypeptide is the common alpha subunit of four glycoprotein hormones (human chorionic gonadotropin, follicle stimulating hormone, luteinizing hormone and thyroid stimulating hormone) in the human body. Under normal physiological conditions, human chorionic gonadotropin is mainly secreted by placental trophoblast cells, and follicle-stimulating hormone, luteinizing hormone, and thyroid-stimulating hormone are mainly secreted by pituitary cells.
  • the four glycoprotein hormones are composed of ⁇ and ⁇ subunits, of which the ⁇ subunits are encoded by different genes, and the ⁇ subunits are all encoded by the CGA gene.
  • the CGA gene exists on human chromosome 6, and the sequence region is 9.6 long. kbp, there are 2 transcripts, encoding 2 protein isoforms respectively.
  • the mRNA generated by the transcription of the CGA gene of the present invention (abbreviated as CGA mRNA) is expected to include its full-length ribonucleotide sequence, or a naturally occurring variant, or a fragment of the full-length sequence and the variant, especially can be detected and determined specifically A fragment of the sequence, more preferably a fragment that can be distinguished from other RNA sequences in solid tumor tissue.
  • a fragment that can be distinguished from other RNA sequences in solid tumor tissue Preferably at least 7, 8, 9, 10, 11, 12, 15 or 20 contiguous ribonucleotides of said full-length ribonucleotide sequence are comprised.
  • the protein encoded by the CGA gene of the present invention is intended to include naturally occurring variants of said protein as well as fragments of said protein or said variant, particularly immunologically detectable fragments.
  • An immunologically detectable fragment preferably comprises at least 5, 6, 7, 8, 9, 10, 11, 12, 15 or 20 contiguous amino acids of said marker polypeptide.
  • the expression "protein encoded by CGA gene” includes the complete protein sequence of CGA, and the marker polypeptide defined above.
  • the term "drug resistance of solid tumors” means that solid tumor patients or solid tumor cells or tissues isolated in vitro are resistant to a single chemotherapeutic drug or multiple chemotherapeutic drugs.
  • Sensitivity refers to the IC50 (half-inhibitory concentration) of a certain chemotherapeutic drug after induction or other treatment compared with the parental cells whose growth inhibition rate of a certain chemotherapeutic drug reaches more than 60% at its normal blood concentration. , which refers to the drug concentration required when the number of surviving cells is reduced by half after administration) is increased by more than 2 times.
  • the present invention relates to the application of CGA mRNA or protein detection reagents in the preparation of reagents or kits for the diagnosis and/or prognosis evaluation of solid tumor drug resistance, wherein the increased expression of CGA mRNA or protein is an indication of solid tumor drug resistance indication and/or an indication of poor prognosis in gastric cancer.
  • detection reagent for CGA mRNA in the present invention should not only be understood as a detection reagent for CGA mRNA, but should include other detection reagents known to those skilled in the art that can reflect the expression level of CGA mRNA.
  • the expression level of CGA mRNA can be indirectly detected by quantitatively detecting the cDNA obtained by reverse transcription of CGA mRNA.
  • the "detection reagent for CGA mRNA” can be selected from reagents known to those skilled in the art, such as nucleic acid that can hybridize with the RNA and is labeled with a fluorescent marker; in common cases, the detection reagent for RNA can be selected from primers for RT-PCR, And the product that is used to amplify RT-PCR---the primer of cDNA; In some embodiments, the detection reagent of described CGA mRNA comprises the reagent that is applicable to following at least one method: real-time fluorescent quantitative PCR, digital PCR, fluorescent dye methods, resonance light scattering, sequencing or biological mass spectrometry.
  • the quantitative detection agent of CGAmRNA is a probe or primer capable of specifically binding to CGAmRNA or CGA cDNA.
  • the present invention also relates to qRT-PCR primers of CGA mRNA, its upstream primer is shown in SEQ ID NO: 1, and the downstream primer is shown in SEQ ID NO: 2.
  • the primer can be used for the diagnosis and/or prognosis evaluation of human gastric cancer drug resistance.
  • antibody includes polyclonal antibodies as well as monoclonal antibodies, and the term “antibody fragment” includes antigenic compound binding fragments of these antibodies, including Fab, F(ab') 2 , Fd, Fv, scFv, bispecific antibodies and antibody The smallest recognition unit, and single-chain derivatives of these antibodies and fragments, such as scFv-Fc, etc.
  • the type of antibody can choose IgG1, IgG2, IgG3, IgG4, IgA, IgM, IgE, IgD.
  • antibody includes naturally occurring antibodies as well as non-naturally occurring antibodies, including, for example, chimeric, bifunctional, humanized, and human antibodies, as well as related synthetic antibodies. isoforms.
  • antibody is used interchangeably with "immunoglobulin”.
  • the measurement sample includes blood (whole blood), serum, plasma, cell culture supernatant, urine, tissue or tissue lysate.
  • the CGA gene expression inhibitors in the present invention refer to reagents, preparations or drugs that block the normal transcription or post-transcriptional translation of CGA genes based on CRISPR/Cas9 gene editing technology or RNA interference technology, such as CRISPR gene editing therapeutic drugs, anti- Sense nucleic acid drugs, siRNA drugs, miRNA drugs, etc.
  • the CGA protein expression inhibitors in the present invention refer to agents, preparations or drugs that affect the post-translational modification process of CGA protein or affect the stability of CGA protein, and affect the expression level, activity or function of CGA protein, such as protein glycosylation inhibitors, Protein phosphorylation inhibitors, neutralizing antibodies, etc.
  • Gastric cancer is a cancer that occurs in the gastric mucosa, and the vast majority of gastric cancers are adenocarcinomas. In the following examples, all gastric cancers that are not specified are gastric adenocarcinoma. However, the research results of the present invention are not limited to gastric cancer. According to the conventional understanding of those skilled in the art, related applications can be applied to solid tumors including lung cancer, breast cancer, colorectal cancer, liver cancer, ovarian cancer and prostate cancer.
  • the cell lines SGC7901, SGC7901 ADR and SGC7901 VCR used in the examples are all preserved in the State Key Laboratory of Tumor Biology, Air Force Military Medical University.
  • Example 1 Real-time quantitative PCR (Real-time qualitative PCR, RT-qPCR) detection of CGAmRNA expression differences between gastric cancer drug-resistant cell lines SGC7901 ADR and SGC7901 VCR and control cell line SGC7901
  • Gastric adenocarcinoma cell line SGC7901 is derived from the Academy of Military Medical Sciences and preserved by the State Key Laboratory of Tumor Biology, Air Force Military Medical University;
  • SGC7901 cells were cultured in DMEM medium containing 10% (v/v) fetal bovine serum;
  • the drug-resistant gastric cancer cells SGC7901 ADR and SGC7901 VCR were established by intermittent induction method. The method was to expose the parental cells of SGC7901 to lethal doses of doxorubicin and vincristine medium for a short period of time, respectively, and induced them generation by generation, in which doxorubicin The concentration was 2.5 ⁇ g/ml, and the concentration of vincristine was gradually increased from 1 ⁇ g/ml to 5 ⁇ g/ml; specifically, SGC7901 ADR cells were cultured in DMEM medium containing 0.05 ⁇ g/ml doxorubicin and 10% fetal bovine serum The long-term culture of SGC7901 VCR cells adopts DMEM medium containing 0.5 ⁇ g/ml vincristine and 10% fetal bovine serum, all at 37°C and containing 5% (v/v) CO 2 conditions, and the cells are cultivated until After several growth periods, the IC50 of the cultured cells increased by more than 2 times
  • RT-qPCR was used to detect the expression level of CGA gene in SGC7901 ADR and SGC7901 VCR and SGC7901 cells, the specific steps are as follows:
  • RNA isolation reagent TRIzol RNA isolation reagent
  • Figure 1 is the result graph of CGAmRNA expression between the gastric cancer drug-resistant cell line SGC7901 ADR and SGC7901 VCR and the control group cell line SGC7901; it can be seen from Figure 1 that the expression of CGA mRNA in the gastric cancer drug-resistant cell line SGC7901 ADR and SGC7901 VCR is higher than that of the control group The increase of SGC7901 in the cell line of the group was significant (P ⁇ 0.05), indicating that the expression level of CGAmRNA was related to the multidrug resistance of gastric cancer.
  • Example 2 WB detection of CGA protein expression differences between gastric cancer drug-resistant cell lines SGC7901 ADR and SGC7901 VCR and control cell line SGC7901
  • the culture of gastric cancer drug-resistant cell lines SGC7901 ADR and SGC7901 VCR and the control cell line SGC7901 was the same as in Example 1.
  • Millipore ultrafiltration tube to centrifuge at 4°C and 4000 ⁇ g for 1 h to collect the secreted protein in the culture supernatant, use the RIPA cell lysate to extract the total cell protein, and determine the concentration and quality of the supernatant and cell sample protein by BCA method;
  • Electrophoresis was performed using Bio-Rad's standard electrophoresis device, and the membrane was transferred using Bio-Rad's fast membrane transfer device; after the PVDF membrane was blocked, the primary antibody (rabbit anti-human CGA monoclonal antibody, Abcam, 1:1000; mouse anti-human ⁇ -Tubulin monoclonal antibody, Sigma-Aldrich, 1:2000) and incubated overnight at 4°C.
  • the primary antibody rabbit anti-human CGA monoclonal antibody, Abcam, 1:1000
  • mouse anti-human ⁇ -Tubulin monoclonal antibody Sigma-Aldrich, 1:2000
  • Fig. 2 is the result graph of CGA protein expression in the cell and in the culture supernatant between gastric cancer drug-resistant cell lines SGC7901 ADR and SGC7901 VCR and the control cell line SGC7901 ;
  • the CGA protein in SGC7901 VCR cells and secreted into the culture supernatant was higher than that of the control cell line SGC7901, indicating that the expression level of CGA protein was related to the multidrug resistance of gastric cancer.
  • Example 3 Immunofluorescence (IF) detection of differences in expression and subcellular localization of CGA protein between gastric cancer drug-resistant cell lines SGC7901 ADR and SGC7901 VCR and control cell line SGC7901
  • the culture of gastric cancer drug-resistant cell lines SGC7901 ADR and SGC7901 VCR and the control cell line SGC7901 was the same as in Example 1.
  • Figure 3 is the immunofluorescence results of CGA protein expression between the gastric cancer drug-resistant cell line SGC7901 ADR and SGC7901 VCR and the control cell line SGC7901; it can be seen from Figure 3 that the expression of CGA protein in the gastric cancer drug-resistant cell line SGC7901 ADR and SGC7901 VCR cells The amount was higher than that of the control cell line SGC7901, and it was mainly expressed in the cytoplasm and cell membrane of SGC7901 ADR and SGC7901 VCR cells, indicating that CGA protein was highly expressed in gastric cancer multidrug resistant cells.
  • Example 4 RT-qPCR detection of expression changes of CGAmRNA in gastric cancer cell line SGC7901 and NCI-N87 cells under sublethal dose chemotherapy drug-induced conditions
  • gastric adenocarcinoma cell SGC7901 was the same as in Example 1; gastric adenocarcinoma cell NCI-N87 was purchased from the American type culture collection (ATCC), and the culture conditions were the same as those of SGC7901 cells; and doxorubicin sensitive;
  • the chemotherapeutic environment of the tumor in vivo is simulated by giving sublethal doses of chemotherapeutic drugs (drug concentration at which the cells maintain 50% mortality after 24 hours of drug treatment), and the expression changes of CGA genes are observed.
  • RT-qPCR was used to detect the expression of CGA gene in SGC7901 and NCI-N87 cells after receiving sublethal doses of fluorouracil (1 ⁇ g/ml) and doxorubicin (0.5 ⁇ g/ml) on days 1, 3, 5, and 7.
  • fluorouracil 1 ⁇ g/ml
  • doxorubicin 0.5 ⁇ g/ml
  • Figure 4 shows the expression changes of CGAmRNA in gastric cancer cells SGC7901 and NCI-N87, which are sensitive to chemotherapy drugs, under sublethal doses of chemotherapy drugs; After 3, 5, and 7 days, the expression of CGAmRNA was compared with the expression of CGAmRNA in untreated control cells.
  • Fig. 4B is the 1st, 3rd, and 5th days of SGC7901 and NCI-N87 cells under the culture condition of doxorubicin (0.5 ⁇ g/ml). 1. Comparison of the expression level of CGAmRNA after 7 days with the expression level of CGAmRNA in untreated control cells. It can be seen from Figure 4 that chemotherapy drugs can induce CGA gene expression, and the increase is more obvious in cells that survive longer under chemotherapy conditions, indicating that the expression level of CGA can reflect the drug resistance status of gastric cancer cells.
  • Example 5 Immunohistochemistry (IHC) detection of CGA protein expression in gastric cancer tissues before and after chemotherapy in gastric cancer patients receiving chemotherapy
  • the paraffin-embedded tissue samples of gastric cancer tissues from 37 gastric cancer patients receiving neoadjuvant chemotherapy before and after chemotherapy were collected; the samples before chemotherapy were taken from endoscopic biopsy, and the samples after chemotherapy were taken from gastric cancer surgery. treat.
  • the paraffin-embedded tissue samples used in this example were all from the tissue sample bank of the State Key Laboratory of Tumor Biology, Air Force Military Medical University; according to the system stipulated by the ethics review committee, each patient signed an informed consent form before sampling.
  • the general situation and pathological information of 37 gastric cancer patients were collected in Table 2, among which 31 cases were chemotherapy-resistant and 6 cases were chemotherapy-sensitive.
  • Chemotherapy regimen FOLFOX, fluorouracil, calcium folinate, oxaliplatin; EOX, epirubicin, oxaliplatin, capecitabine; DCF, docetaxel, cisplatin, fluorouracil; ECF, epirubicin Mycin, cisplatin, fluorouracil; XELOX, capecitabine, oxaliplatin; SOX, S-1, oxaliplatin; FOLFIRI, fluorouracil, leucovorin, irinotecan; FOLT, fluorouracil, leucovorin , oxaliplatin, docetaxel.
  • Chemosensitive According to Response Evaluation Criteria in Solid Tumors-RECIST (Response Evaluation Criteria in Solid Tumors-RECIST) version 1.1, patients with gastric cancer are evaluated as complete remission (CR) or PR in response to neoadjuvant chemotherapy before surgery.
  • Chemotherapy resistance According to RECIST version 1.1, gastric cancer patients are evaluated as SD or PD in response to neoadjuvant chemotherapy regimens before surgery.
  • IHC was used to detect the expression level of CGA protein in gastric cancer tissues of 37 gastric cancer patients before and after chemotherapy, and the specific steps were as follows:
  • tissue slices were baked in a constant temperature oven at 60°C for about 1 hour, dewaxed in xylene for 10 minutes, repeated 3 times, and then dehydrated in 99.9%, 96% and 70% ethanol for 5 minutes, repeated 3 times;
  • the immunohistochemical reaction was scored semi-quantitatively by the immunoreaction integral method, and the staining intensity was divided into 4 grades: no positive cells were scored as 0 points, weak positive cells were scored as 1 point, moderate positive cells were scored as 2 points, and strong positive cells were scored as 3 points.
  • IHC score ⁇ (staining intensity ⁇ percentage of positive cells).
  • Fig. 5A is the IHC staining micrograph of CGA protein in post-chemotherapy cancer tissue (Post) and its paired pre-chemotherapy cancer tissue (Pre) in 6 representative cases of chemotherapy-resistant gastric cancer patients (Patient1-6).
  • the results show that CGA protein is negatively or weakly positively expressed in gastric cancer tissues before chemotherapy, while CGA protein is positively or strongly positively expressed in gastric cancer tissues after chemotherapy.
  • Figure 5B is the IHC scoring chart of CGA expression in gastric cancer tissues of 31 chemotherapy-resistant gastric cancer patients after chemotherapy and before chemotherapy.
  • FIG. 5C is a micrograph of IHC staining of CGA protein in gastric cancer tissues of 6 chemotherapy-sensitive gastric cancer patients (Patient 7-12) after chemotherapy and before chemotherapy, and the results show the expression of CGA protein in gastric cancer tissues before and after chemotherapy No significant difference, all negative.
  • Example 6 IHC detection of expression of CGA protein in tumor tissue of gastric cancer patient-derived xenograft (Patient derived xenograft, PDX) model receiving chemotherapy or control treatment
  • Gastric cancer tissues were collected from gastric cancer patients who underwent gastric cancer resection in the First affiliated Hospital of Air Force Military Medical University; according to the system stipulated by the ethics review committee, all patients signed informed consent before sampling; gastric cancer tissues were immediately placed in Hank's balance Transport in liquid;
  • the PDX model was performed within 4 hours after the gastric cancer tissue was isolated, and the specific steps were as follows:
  • Table 3 The general situation and pathological information of 4 patients with gastric cancer
  • P2-P4 gastric cancer PDX mice from the same patient tissue were divided into experimental group and control group (3-5 mice in each group). 3 times a week), the control group received an intraperitoneal injection of an equal volume of normal saline (3 times a week), and the tumor volumes of the experimental group and the control group were recorded. After 3-4 weeks, the mice were killed according to the requirements of the experimental animal theory, and the tumor tissues were fixed, embedded, and sectioned for IHC staining to observe the expression of CGA protein. The specific steps of IHC are the same as in Example 5.
  • Fig. 6A is the IHC staining micrograph of CGA protein in transplanted tumor tissues of mice corresponding to PDX1-4 and the control group, indicating that after the gastric cancer tissues were treated with chemotherapeutic drugs, the expression levels of CGA protein in each group were higher than those in the control group. Organizations have different degrees of elevation.
  • Figure 6B is a graph of the tumor volume of the 4 groups of PDX mice receiving chemotherapy and the control group, reflecting the response of the patient-derived tumor tissue to chemotherapy drugs: the tumor growth in the PDX1 experimental group was slow after treatment, indicating that it is sensitive to fluorouracil ; The tumor volume of the PDX2-4 experimental group still increased after treatment, indicating that it was resistant to fluorouracil.
  • Example 7 ELISA detection of CGA protein content in the serum of different populations and analysis of the diagnostic value of CGA for gastric cancer drug resistance 1.
  • the chemotherapy regimens of the patients in the neoadjuvant chemotherapy group and the palliative chemotherapy group included fluorouracil, paclitaxel, cisplatin, and doxorubicin alone or in combination.
  • the serum of normal people is the serum of healthy people who have been diagnosed as upper digestive tumors through gastroscopy and biopsy cases. According to the system stipulated by the ethics review committee, each patient signed an informed consent form before sampling.
  • the general conditions of the collected 139 patients with gastric cancer are shown in Table 4-6.
  • Table 4 The general situation and pathological information of 41 patients with gastric cancer receiving neoadjuvant chemotherapy
  • Chemotherapy regimen DS, docetaxel, S-1; DF, cisplatin, fluorouracil; DOX, docetaxel, oxaliplatin, capecitabine.
  • Table 5 The general situation and pathological information of 56 patients with gastric cancer receiving palliative chemotherapy
  • Chemotherapy regimen SP, S-1, cisplatin; XELIRI, capecitabine, irinotecan; EOX, epirubicin, oxaliplatin, capecitabine.
  • Table 6 The general situation and pathological information of 42 patients with gastric cancer without chemotherapy
  • ELISA was used to detect the content of CGA protein in the plasma samples of the gastric cancer chemotherapy group, non-chemotherapy group and normal control group, using the CGAELISA kit (Cat. No.: NBP2-75262) from Novus Biologicals, USA. The specific steps were as follows:
  • Dissolve 5000pg protein standard in 1ml sample diluent and prepare the standard into 5000, 2500, 1250, 625, 312.5, 156.25, 78.13, 0pg/ml concentration gradients by doubling dilution method; Dilute at a ratio of 1:2; add standard products of each concentration gradient and diluted plasma samples into the spotting wells of a 96-well microtiter plate with a sample volume of 100 ⁇ l/well, and incubate at 37°C for 90 minutes after the membrane is blocked.
  • ELISA technology was used to detect the content of CGA protein in plasma samples of gastric cancer chemotherapy group, non-chemotherapy group and normal control group.
  • the results are shown in Figure 7A : The expression of CGA in neoadjuvant chemotherapy group (Neoadjuvant chemotherapy) and palliative chemotherapy group (Palliativechemo) was higher than that in non-chemotherapy group (Non-chemo) and normal control group (Normal), and the difference was significant (P ⁇ 0.05 ); there was no significant difference in the average concentration of plasma CGA between the non-chemotherapy group and the normal control group; as shown in Figure 7B, among the patients in the neoadjuvant chemotherapy group, the plasma CGA level of the patients whose curative effect was evaluated as SD was higher than that of the patients whose curative effect was evaluated as PR , the difference was significant (P ⁇ 0.01); as shown in Figure 7C, in the
  • Embodiment 8 is a diagrammatic representation of Embodiment 8
  • the inventors further analyzed the expression of the CGA gene in gastric cancer and normal tissues according to the relevant data in the Oncomine and GEPIA databases
  • the Oncomine database is currently the world's largest cancer gene chip database and integrated data mining platform, which integrates RNA from sources such as the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and published literature. and DNA-seq data, which can be used to analyze gene expression differences.
  • the Gene Expression Profiling Interactive Analysis (GEPIA) database is a visual cancer big data analysis platform established on the basis of the two major transcriptome databases, TCGA and the genotype-tissue expression (GTEx). . The inventors mined the relevant information in Oncomine and GEPIA databases, and analyzed the expression difference of CGA gene in gastric cancer and adjacent normal tissues, so as to further clarify whether CGA can be used as a specific marker of gastric cancer drug resistance.
  • Figure 8A is the data analysis results of CGA mRNA expression in gastric cancer tissue samples and normal gastric mucosal tissue samples in 6 DNA or RNA-seq data sets from different sources in the Oncomine database, indicating that the expression of CGA gene in the 6 data sets is different in gastric cancer and normal gastric mucosal tissue samples. There was no statistical difference in gastric mucosal tissue.
  • Figure 8B is a dot plot of CGA mRNA expression in 408 cases of gastric cancer tissues and 211 cases of normal gastric mucosal tissues in the GEPIA database, indicating that there is no statistical difference in the expression of CGA gene between gastric cancer tissues and adjacent normal tissues. It can be seen from FIG. 8 that there is no difference in the expression of CGA gene between normal gastric tissue and gastric cancer tissue. In combination with other embodiments of the present invention, it is shown that CGA is a specific marker of gastric cancer drug resistance, not a marker of gastric cancer.
  • Example 9 Construction of a cell line that stably knocks out the CGA gene
  • the culture of drug-resistant gastric cancer cells SGC7901 ADR and SGC7901 VCR cells was the same as in Example 1.
  • the sgRNA that can target the CGA gene was designed and selected through the sgRNA design website (https://crispr.dbcls.jp), and the non-targeting sgRNA sequence was used as a control.
  • the nucleotide sequence is shown in Table 7;
  • the QuickChangePCR reaction system is: 10 ⁇ PCR Buffer for KOD-Plus-Neo 5 ⁇ l, 2mMdNTPs 5 ⁇ l, 25mM MgSO 4 3 ⁇ l, upstream and downstream primers (10 ⁇ M) each 1.5 ⁇ l, gRNA_GFP-T1 plasmid template 50ng, KOD-Plus-Neo 1 ⁇ l, ddH 2 O to supplement the reaction volume to 50 ⁇ l; QuickChangePCR reaction conditions are: 94°C for 2min; 98°C for 10s, 68°C for 2min, 22 cycles ;
  • Use WB to detect the expression of CGA protein in SGC7901 ADR and SGC7901 VCR knockout CGA gene cells the specific steps are as follows: use RIPA cell lysate to extract total cell protein, BCA method to determine the protein concentration of cell samples; use Bio-Rad standard electrophoresis The device was subjected to electrophoresis, and the membrane was transferred using a Bio-Rad rapid membrane transfer instrument; after the PVDF membrane was blocked, the primary antibody (rabbit anti-human CGA monoclonal antibody, purchased from Abcam, 1:1000; mouse anti-human ⁇ -Tubulin monoclonal antibody, purchased from Sigma-Aldrich, 1:2000) and incubated overnight at 4°C.
  • Figure 9A is a schematic diagram of the CGA gene knockout site and DNA sequencing results in SGC7901 ADR and SGC7901 VCR cells, indicating that in the exon 3 region of the CGA gene, sgRNA induces Cas9 protein cleavage and proceeds in a non-homologous recombination manner Repair, resulting in CGA gene defect.
  • Figure 9B is the WB verification of CGA protein expression in two monoclonal cell lines (KO-1 and KO-2) in which the CGA gene was knocked out in SGC7901 ADR and SGC7901 VCR cells, indicating that sgRNA successfully induced CGA gene cleavage and defect repair, Resulting in loss of CGA protein expression. The results identified the optimal target for screening: sgRNA#1 had the highest target activity.
  • Example 10 Effect of Knockout of CGA Gene on Cell Survival Rate of Drug-resistant Gastric Cancer Cell Lines SGC7901 ADR and SGC7901 VCR Under Different Chemotherapeutic Drug Treatments
  • KO-1 and KO-2 Two monoclonal cell lines (KO-1 and KO-2) that successfully constructed the drug-resistant gastric cancer cell lines SGC7901 ADR and SGC7901 VCR knocked out of the CGA gene in Example 9 were used for cell proliferation-toxicity experiments.
  • Fig. 10A is the fitting curve of cell survival rate and drug concentration of SGC7901 ADR cells of CGA gene WT and KO under different concentrations of fluorouracil and doxorubicin treatment, indicating that after knockout of CGA gene, gastric cancer drug-resistant cell line SGC7901 ADR has The IC50 of fluorouracil and doxorubicin decreased significantly.
  • Figure 10B is the fitting curve of cell survival rate and drug concentration of SGC7901 VCR cells of CGA gene WT and KO treated with different concentrations of fluorouracil and paclitaxel, indicating that after the knockout of CGA gene, gastric cancer drug-resistant cell line SGC7901 VCR is resistant to fluorouracil and paclitaxel. The IC50 of paclitaxel decreased significantly. It can be seen from Fig. 10 that the knockout of CGA gene can lead to a significant reduction in the drug resistance of gastric cancer drug-resistant cells.
  • Example 11 Effect of Knockout of CGA Gene on Apoptosis of Drug-resistant Gastric Cancer Cell Lines SGC7901 ADR and SGC7901 VCR Under Chemotherapeutic Drug Treatment
  • KO-1 and KO-2 Two monoclonal cell lines, KO-1 and KO-2, in which the gastric cancer drug-resistant cell lines SGC7901 ADR and SGC7901 VCR knocked out the CGA gene were successfully constructed using Example 9, and cell apoptosis was detected under a certain concentration of chemotherapeutic drugs.
  • the multidrug-resistant WTSGC7901 ADR and SGC7901 VCR cells without CGA gene knockout were used as controls.
  • the SGC7901 ADR and SGC7901 VCR cells with CGA genes WT, KO-1, and KO-2 were expanded and cultured until the cells were in good condition, and each cell was digested with trypsin to prepare a single cell suspension, which was inoculated into a 6-well plate, and the number of cells per well was about 2 ⁇ 105 cells; after the cells adhered to the wall, add fluorouracil, doxorubicin or paclitaxel at a concentration of 10 ⁇ g/ml to treat the cells of each group; after the drug treatment, the cells were prepared into a single cell suspension; After washing with PBS at 4°C, resuspend the cells in 200 ⁇ l of binding buffer (10 mM HEPES/NaOH, pH 7.4; 140 mM NaCl; 2.5 mM CaCl 2 ), add 10 ⁇ l of Annexin V-FITC and 5 ⁇ l of PI staining solution, mix well and incubate at 37°C Incubat
  • Figure 11A is a statistical graph of apoptosis data of SGC7901 ADR cells treated with fluorouracil and doxorubicin in CGA gene WT and KO, indicating that fluorouracil and doxorubicin are more likely to induce apoptosis of SGC7901 ADR cells after CGA gene knockout.
  • Figure 11B is a statistical graph of the apoptosis data of SGC7901 VCR cells treated with fluorouracil and paclitaxel of CGA gene WT and KO, indicating that fluorouracil and paclitaxel are more likely to induce apoptosis of SGC7901 VCR cells after CGA gene knockout. It can be seen from Fig. 11 that the knockout of CGA gene can lead to the obvious reduction of the drug resistance of gastric cancer drug-resistant cells, and the cells are prone to apoptosis induced by chemotherapeutic drugs.
  • Example 12 Effect of Knockout of CGA Gene on Cell Proliferation Ability of Drug-resistant Gastric Cancer Cell Lines SGC7901 ADR and SGC7901 VCR Under Chemotherapeutic Drug Treatment
  • KO-1 and KO-2 Two monoclonal cell lines, KO-1 and KO-2, in which the gastric cancer drug-resistant cell lines SGC7901 ADR and SGC7901 VCR knocked out the CGA gene were successfully constructed in Example 9, and the cell proliferation ability was tested under a certain concentration of chemotherapeutic drugs to determine Multidrug-resistant WT SGC7901 ADR and SGC7901 VCR cells served as controls.
  • the SGC7901 ADR and SGC7901 VCR cells with CGA genes WT, KO-1, and KO-2 were expanded and cultured until the cells were in good condition, each cell was digested with trypsin, and the concentration of each cell was adjusted to 5 ⁇ 10 4 cells/ml with complete medium.
  • Figure 12A is the cell growth curve of SGC7901 ADR cells of CGA gene WT and KO under the treatment of fluorouracil and doxorubicin, indicating that after the knockout of the CGA gene, the proliferation of gastric cancer drug-resistant cell line SGC7901 ADR under the treatment conditions of fluorouracil and doxorubicin The ability was significantly weakened;
  • Figure 12B is the cell growth curve of the CGA gene WT and KO SGC7901 VCR cells under the treatment of fluorouracil and paclitaxel, indicating that after the CGA gene knockout, the proliferation of gastric cancer drug-resistant cell line SGC7901 VCR under the treatment conditions of fluorouracil and paclitaxel The ability was significantly weakened; as can be seen from Figure 12, CGA gene knockout can lead to a significant reduction in the proliferation ability of gastric cancer drug-resistant cells in the environment of chemotherapeutic drugs.
  • Example 9 to construct the successful gastric cancer drug-resistant cell line SGC7901 ADR and SGC7901 VCR knockout CGA gene monoclonal cell line (KO-1), with multidrug-resistant WT SGC7901 ADR and SGC7901 VCR cells as controls; experimental animals Select 6-8 week-old female thymus-deficient nude mice (purchased from Beijing Weitong Lihua Experimental Animal Technology Co., Ltd.), and raise them in a constant temperature and humidity SPF environment.
  • SGC7901 ADR and SGC7901 VCR cells with CGA gene WT or KO were used for subcutaneous tumor formation experiments in nude mice, and the effect of chemotherapy drugs on tumor growth (tumor volume and weight) was observed by intraperitoneal injection of chemotherapy drugs.
  • IHC staining was performed to observe the expressions of cell proliferation-related protein Ki-67 and cell apoptosis-related protein cleaved Caspase-3.
  • the specific steps of IHC are as follows: the tissue slices were baked in a constant temperature oven at 60°C for about 1 hour, dewaxed in xylene for 10 minutes, repeated 3 times, and then dehydrated in 99.9%, 96% and 70% ethanol for 5 minutes , repeated 3 times; boil the slices in sodium citrate antigen retrieval solution for 15 min, put the slices in 3% H 2 O 2 for 15 min, add blocking solution dropwise and incubate at room temperature for 30 min; primary antibody (rabbit anti-human Ki-67 monoclonal Abcam, 1:200; rabbit anti-human cleaved Caspase-3 monoclonal antibody, Abcam, 1:200) were incubated overnight at 4°C.
  • Washing with PBS was repeated 3 times for 5 min, and the secondary antibody (biotin-labeled goat anti-rabbit IgG polymer, Zhongshan Jinqiao) was incubated at room temperature for 1 h. Wash with PBS, develop color with DAB, stain cell nuclei with hematoxylin; differentiate with 1% hydrochloric acid alcohol, turn blue with 0.1% ammonia water, dehydrate the sections in 70%, 96% and 99.9% ethanol in turn, and seal with neutral gum .
  • the secondary antibody biotin-labeled goat anti-rabbit IgG polymer, Zhongshan Jinqiao
  • 13A and 13B are the tumor growth curves of SGC7901 ADR and SGC7901 VCR cells of CGA gene WT and KO in nude mice treated with fluorouracil, doxorubicin and paclitaxel.
  • 13C and 13D are pictures of tumors and tumor weight statistics of SGC7901 ADR and SGC7901 VCR cells of CGA gene WT and KO in nude mice treated with fluorouracil, doxorubicin and paclitaxel.
  • Figures 13A-D show that after CGA gene knockout, the growth of gastric cancer drug-resistant cell lines SGC7901 ADR and SGC7901 VCR in vivo resistant to chemotherapy drugs was significantly slowed down.
  • Figure 13E and 13F are the tumors of SGC7901 ADR and SGC7901 VCR cells of CGA gene WT and KO in nude mice under the treatment conditions of fluorouracil, doxorubicin and paclitaxel, and are representative after IHC staining of Ki-67 and cleaved Caspase-3 protein
  • the micrographs showed that after knockout of CGA gene, gastric cancer drug-resistant cell lines SGC7901 ADR and SGC7901 VCR were treated with chemotherapeutic drugs in vivo, the proliferation ability was significantly weakened, and the apoptosis was significantly increased. It can be seen from FIG. 13 that knockout of the CGA gene can significantly reduce the ability of gastric cancer drug-resistant cells to resist chemotherapy drugs in vivo.
  • Example 14 Interfering with the expression of the CGA gene by microRNA (miRNA) in gastric cancer cells
  • the culture of gastric cancer drug-resistant cell lines SGC7901 ADR and SGC7901 VCR is the same as in Example 1; miRNA is a small non-coding RNA with a length of about 18-25 nucleotides in eukaryotic cells, which usually negatively regulates gene expression at the post-transcriptional level .
  • the chemically synthesized miRNA mimics in the present invention were purchased from Guangzhou Ruibo Biotechnology Co., Ltd.
  • the miRNAs that can specifically target the CGA gene were predicted by the online miRNA prediction algorithm website miRWalk (http://mirwalk.umm.uni-heidelberg.de) and TargetScan (http://www.targetscan.org/vert_72/), respectively, A total of 36 miRNAs specifically targeting the CGA gene were obtained by taking the intersection of the two (Table 8). Through Pubmed (https://pubmed.ncbi.nlm.nih.gov), the functions of these 36 miRNAs in cancer drug resistance were verified one by one, and 4 miRNAs (miR-17 -3p, miR-630, miR-708-3p, miR-761) for follow-up research.
  • RT-qPCR was used to detect the expression difference of four miRNAs between gastric cancer drug-resistant cell lines SGC7901 ADR and SGC7901 VCR and their parental chemotherapy-sensitive SGC7901 cells.
  • the total RNA was extracted from the cells of the strain, and the concentration and quality of the RNA were measured by a spectrophotometer; the RNA was reverse-transcribed into cDNA using the Takara reverse transcription kit, and the reverse transcription system: RNA 3.75 ⁇ l, 2 ⁇ mRQ Buffer 5 ⁇ l, mRQ Enzyme 1.25 ⁇ l; Reverse transcription reaction conditions: incubate at 37°C for 60 minutes, incubate at 85°C for 5 minutes, and maintain at 4°C; use Takara SYBR Premix Ex Taq II to use the reverse rate product as a template, and perform RT-qPCR detection by chimeric fluorescence method, reaction system: 2 ⁇ SYBR Premix Ex Taq II 10 ⁇ l, upstream primer 1 ⁇ l, downstream primer 1 ⁇
  • the four miRNA mimetics were transfected into gastric cancer drug-resistant cell lines SGC7901 ADR and SGC7901 VCR by liposome method, and the specific steps were as follows: culture SGC7901 ADR and SGC7901 VCR cells to logarithmic growth phase, and digest each cell with trypsin , inoculated into a 6-well plate, the number of cells per well was about 2 ⁇ 105 ; when the growth confluence of the cells in the 6-well plate reached about 30%, the medium was replaced with Opti-MEM medium; use sterile Microcentrifuge tubes, respectively mix Opti-MEM (purchased from Gibco) with miR-17-3p, miR-630, miR-708-3p, miR-761 analogs and negative controls in corresponding proportions; Take a microcentrifuge tube, mix Opti-MEM and Lipofectamine RNAiMAX (purchased from Invitrogen) according to the corresponding proportion; after incubating the two tubes at room temperature for 5 min, mix well,
  • Fig. 14A is a schematic diagram of a screening strategy for specific miRNAs targeting CGA genes.
  • Figure 14B shows the expression of miR-17-3p, miR-630, miR-708-3p, and miR-761 in gastric cancer drug-resistant cells SGC7901 ADR and SGC7901 VCR and their parental SGC7901 cells, indicating that these 4 miRNAs are expressed in drug-resistant cells The expression of all miRNAs was decreased, which is a prerequisite for the upregulation of these miRNAs for targeted inhibition of CGA.
  • Figure 14C shows the changes in the expression of CGA protein in the cells detected by WB after transfection of miR-17-3p, miR-630, miR-708-3p, and miR-761 mimetics in gastric cancer drug-resistant cells SGC7901 ADR and SGC7901 VCR , indicating that miR-708-3p and miR-761 can significantly inhibit the expression of CGA protein, and play a role in targeting and inhibiting CGA. It can be seen from FIG. 14 that miRNAs can interfere with the expression of CGA genes in gastric cancer cells, and miR-708-3p and miR-761 are miRNAs that effectively inhibit CGA.
  • Example 15 Effect of miRNA interference with CGA gene on the cell survival rate of gastric cancer drug-resistant cell lines SGC7901 ADR and SGC7901 VCR treated with different chemotherapeutic drugs
  • gastric cancer drug-resistant cell lines SGC7901 ADR and SGC7901 VCR was the same as in Example 1.
  • Chemically synthesized miR-708-3p and miR-761 mimics were purchased from Guangzhou Ruibo Biotechnology Co., Ltd.
  • Figure 15A is the SGC7901 ADR cells transfected with miR-708-3p and miR-761 mimics, the cell survival rate under fluorouracil and doxorubicin treatment, indicating transfection of miR-708-3p and miR-761 mimics After interfering with CGA gene expression, the survival ability of gastric cancer drug-resistant cell line SGC7901 ADR under the treatment conditions of fluorouracil and doxorubicin was significantly weakened.
  • Figure 15B is the cell survival rate of SGC7901 VCR cells transfected with miR-708-3p and miR-761 mimics under the treatment of fluorouracil and paclitaxel, indicating that transfection of miR-708-3p and miR-761 mimics interferes with CGA After gene expression, the survival ability of gastric cancer drug-resistant cell line SGC7901 VCR under the treatment conditions of fluorouracil and doxorubicin was significantly weakened. It can be seen from FIG. 15 that interference with CGA gene expression by miRNA can significantly reduce the survival ability of gastric cancer drug-resistant cells in the environment of chemotherapeutic drugs.
  • Example 16 Effect of miRNA interference CGA gene on drug-resistant gastric cancer cell line SGC7901 ADR in mice on chemotherapeutic drug treatment
  • gastric cancer drug-resistant cell line SGC7901 ADR is the same as that in Example 1.
  • the source and feeding of the experimental animals are the same as in Example 13.
  • MiR-708-3p and miR-761 mimics for in vivo injection were purchased from Xi'an Rongqingchang Biotechnology Co., Ltd.
  • the gastric cancer drug-resistant cell SGC7901 ADR was used to carry out the subcutaneous tumor formation experiment in nude mice, and the specific implementation steps were as follows: 5 ⁇ 10 6 cells were subcutaneously injected into the right flank of each nude mouse. After 2-3 weeks of tumor cell injection, when the tumor grew to about 100 mm, the nude mice were randomly divided into 6 groups, with 8 nude mice in each group; the first group was injected with miRNA control drug ( prodrugctrl) and intraperitoneal injection of normal saline; the second group was injected with miRNA control drug and intraperitoneal injection of fluorouracil (20 mg/kg) every 3 days; the third group was injected with miR-708-3p mimic drug (miR) every 3 days -708-3p prodrug) and intraperitoneal injection of normal saline; group 4 intratumoral injection of miR-708-3p mimic drug and intraperitoneal injection of fluorouracil every 3 days; group 5 intratumoral injection of miR-761 mimic every 3
  • the mice were sacrificed according to the requirements of the experimental animal theory, and the tumors were weighed. After the tumor tissue was fixed, embedded and sectioned, IHC staining was performed to observe the expressions of the cell proliferation-related protein Ki-67 and the cell apoptosis-related protein cleaved Caspase-3. The specific steps were the same as in Example 5.
  • Figure 16A is the tumor growth curve of SGC7901 ADR cells under 6 different treatment conditions after tumor formation
  • Figure 15B is the tumor pictures of SGC7901 ADR cells under 6 different treatment conditions after tumor formation
  • Figure 16C is the tumor growth curve of SGC7901 ADR cells after tumor formation
  • the tumor weight statistical graph under 6 groups of different treatment conditions Figure 16A-C shows that after injection of miR-708-3p and miR-761 mimics to interfere with CGA gene expression, gastric cancer drug-resistant cell line SGC7901 ADR resists chemotherapy drugs in vivo
  • the growth of SGC7901 ADR cells was significantly slowed down
  • Figure 16D is a representative micrograph of Ki-67 and cleaved Caspase-3 protein IHC staining after SGC7901 ADR cell tumor formation under 6 different treatment conditions, indicating that the injection of miR-708 After -3p and miR-761 mimetics interfered with the expression of CGA gene, the proliferation ability of gastric cancer drug-resistant cell line SGC7901 ADR was
  • Example 17 Effect of interference with CGA protein glycosylation on cell survival rate of gastric cancer drug-resistant cell line SGC7901 ADR treated with chemotherapy drugs
  • Glycosylation is an important post-translational modification process after protein synthesis. Interfering with the glycosylation process of proteins can affect the stability of proteins and further interfere with their expression in cells.
  • the purpose of this example is to prove that interfering with the glycosylation modification of CGA protein can reduce the resistance of cells to chemotherapy drugs.
  • the gastric cancer drug-resistant cell line SGC7901 ADR knockout CGA gene KO-1 monoclonal cell line successfully constructed in Example 9 was used, and rCGA treated with different conditions or transfected with glycosylation modification sites were added to the medium After the point mutation of the CGA plasmid, the cell viability was detected under the condition of chemotherapy drug treatment.
  • PNGase F Use peptide N-glycosidase F (PNGase F, purchased from Suzhou Ruian Biological Co., Ltd.) to incubate the rCGA solution (purchased from Beijing Yiqiao Shenzhou Co., Ltd.), and react at 37°C for 4 hours to remove N-linked glycans on the rCGA protein peptide chain. .
  • Figure 17A is the cell survival rate of SGC7901 ADR cells with CGA gene knockout after adding rCGA, under the treatment of fluorouracil and doxorubicin .
  • the survival ability under the treatment condition of doxorubicin was significantly enhanced; but after adding rCGA treated with PNGase F, the survival ability of SGC7901 ADR with knockout of CGA gene had no significant difference to the treatment condition of fluorouracil or doxorubicin.
  • Figure 17B is the cell survival rate under the treatment of fluorouracil and doxorubicin after the CGA expression plasmids of WT, N52Q, N78Q or DM were transfected in SGC7901 ADR cells with CGA gene knockout, indicating that after the CGA expression plasmids of WT were transfected.
  • the survival ability of the CGA gene knockout SGC7901 ADR to fluorouracil or doxorubicin treatment was significantly enhanced, but after transfection of N52Q, N78Q or DM CGA expression plasmids, the CGA gene knockout SGC7901 ADR did not respond to fluorouracil or doxorubicin treatment. There was no significant difference in viability under the conditions. It can be seen from FIG. 17 that interfering with CGA protein glycosylation can significantly reduce the survival ability of gastric cancer drug-resistant cells in the environment of chemotherapy drugs, which can be used as a method to reduce drug resistance of tumor cells.

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Abstract

本发明公开了CGA基因作为靶点在制备用于诊断和治疗耐药实体瘤药物的应用，具体公开了基于CGA在实体瘤组织中高表达并导致实体瘤耐药的新发现，将该基因或/和蛋白作为靶点用于对耐药实体瘤进行诊断和治疗。

Description

CGA基因作为靶点在制备用于诊断和治疗耐药实体瘤药物的应用 技术领域
本发明涉及实体瘤耐药诊断和预后评估技术，具体涉及基于糖蛋白激素α多肽(CGA，即glycoprotein hormones,alpha polypeptide)在实体瘤组织中高表达并导致实体瘤耐药的新发现，将该基因或/和蛋白作为靶点用于对实体瘤耐药进行诊断和预后进行评估。
背景技术
实体瘤的常规治疗手段包括外科手术、化学治疗和放射治疗。化学治疗(化疗)在实体瘤治疗中发挥着重要作用，然而绝大多数患者在接受化疗过程中发生化疗药物耐受导致治疗失败。更重要的是，在化疗中肿瘤发生对一种药物耐药(单一药物耐药)，同时对其它未曾使用且在化学结构及作用机制均不相同的多种药物也产生交叉耐药性，这一现象称为多药耐药。对实体瘤耐药发生机制的研究和寻找开发逆转耐药的药物是当前肿瘤防治中的重要研究领域。为了逆转实体瘤耐药，提高实体瘤化疗的疗效，降低耐药风险及延长生存率，本领域迫切需要通过多种方式研究实体瘤耐药发生的机制和关键基因靶点。
发明内容
基于本发明的研究发现，本发明一方面提供CGA基因或其编码蛋白作为靶点在制备用于实体瘤耐药诊断和/或预后评估的试剂或试剂盒中的应用。
进一步，本发明的方案是CGA基因或其编码蛋白的检测试剂在制备用于实体瘤耐药诊断和/或预后评估的试剂或试剂盒中的应用。
进一步，上述试剂或试剂盒通过RT-PCR、实时定量PCR、数字PCR、荧光染料法、共振光散射法、测序或生物质谱法、原位杂交、Northern blotting、芯片、高通量测序平台、免疫组织化学或酶联免疫吸附法检测CGA基因转录的信使RNA或CGA基因编码蛋白。
进一步，所述试剂或试剂盒中含有扩增CGA基因的特异性引物、与CGA基因核苷酸序列杂交的探针或与CGA蛋白特异性结合的抗体或抗体片段。
进一步，所述抗体为单克隆抗体或多克隆抗体。
进一步，所述试剂或试剂盒的检测样本为血清、血浆、细胞、细胞培养上清、尿液、组织或组织裂解液。
本发明还提供了CGA基因或其编码蛋白的作为靶点在制备用于治疗耐药实体瘤药物的应用。
进一步，本发明的方案是CGA基因表达抑制剂或蛋白表达的抑制剂制备用于治疗耐药实体瘤药物的应用。
进一步，所述CGA基因表达抑制剂选自通过CRISPR/Cas9基因编辑技术或RNA干扰技术阻断CGA基因正常转录或转录后翻译过程的CRISPR基因编辑治疗药物、反义核酸药物、siRNA药物或miRNA药物。
进一步，所述CGA蛋白表达抑制剂选自影响CGA蛋白翻译后修饰过程或影响CGA蛋白稳定性、以及影响CGA蛋白表达水平、活性或功能的蛋白糖基化抑制剂、蛋白磷酸化抑制剂或中和抗体。
本发明同时还提供了一种耐药实体瘤细胞研究模型的构建方法，为此，本发明所提供的方法包括：敲除实体瘤细胞中的CGA基因。
进一步的方案中，在含有一种或多种化疗药物的培养基中培养实体瘤细胞构建初始耐药实体瘤细胞，之后敲除初始耐药实体瘤细胞中的CGA基因得到耐药实体瘤细胞。
进一步，采用CRISPR/Cas9技术敲除初始耐药实体瘤细胞中的CGA基因得到耐药实体瘤细胞。
本发明又提供了一种耐药实体瘤动物模型的构建方法，为此，本发明所提供得方法包括：将上述方法构建的耐药实体瘤细胞注射入动物模型构建耐药实体瘤动物模型。
附图说明
图1为实施例1中胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR与对照组细胞株SGC7901之间CGAmRNA表达量的结果图。
图2为实施例2中胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR与对照组细胞株SGC7901之间在细胞内和培养上清中CGA蛋白表达量的结果图。
图3为实施例3中胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR与对照组细胞株SGC7901之间CGA蛋白表达的免疫荧光染色图。
图4为实施例4中化疗药物敏感的胃癌细胞SGC7901和NCI-N87在亚致死剂量的化疗药物诱导条件下CGAmRNA的表达变化；图4A是SGC7901和NCI-N87细胞在氟尿嘧啶(1μg/ml)培养条件下第1、3、5、7天后CGAmRNA的表达量与未处理对照细胞的CGAmRNA表达量的比较，图4B是SGC7901和NCI-N87细胞在阿霉素(0.5μg/ml)培养条件下第 1、3、5、7天后CGAmRNA的表达量与未处理对照细胞的CGAmRNA表达量的比较。
图5A为实施例5中具有代表性的6例接受化疗后疾病稳定或进展的胃癌患者的化疗后胃癌组织(Post)及其配对的化疗前胃癌组织(Pre)中CGA蛋白的IHC染色显微图；图5B为31例接受化疗后疾病稳定或进展的胃癌患者的化疗后胃癌组织及其配对的化疗前胃癌组织中CGA表达的IHC评分统计图；图5C为6例接受化疗后部分缓解的胃癌患者的化疗后胃癌组织及其配对的化疗前胃癌组织中CGA蛋白的IHC染色显微图。
图6A为基于4例胃癌患者来源的异种移植(Patient derived xenograft，PDX)模型的小鼠在接受对照组(Saline)或化疗药治疗组(Fluorouracil)处理后的移植瘤组织中CGA蛋白的IHC染色显微图；图6B为4组PDX小鼠接受化疗及其对照组的肿瘤体积的生长曲线图。
图7A为酶联免疫吸附试验(Enzyme-linked immunosorbent assay，ELISA)检测来源于正常对照组(Normal)、胃癌未化疗组(Non-chemo)、胃癌新辅助化疗组(Neoadjuvant chemo)和胃癌姑息化疗组(Palliativechemo)的人群血浆样本中CGA蛋白含量的结果统计图；图7B为胃癌新辅助化疗组患者按其化疗疗效评估分为疾病稳定(SD)和部分缓解(PR)两组，两组患者血浆的CGA蛋白含量的结果统计图；图7C为胃癌新辅助化疗组患者手术前与手术后配对的血浆样本中CGA蛋白含量的结果统计图；图7D为胃癌姑息化疗组患者在化疗前和4-6个化疗周期后的配对的血浆样本中CGA蛋白含量的结果统计图；图7E为胃癌姑息化疗组患者按其化疗疗效评估分为疾病进展(PD)和疾病稳定(SD)两组，两组患者血浆的CGA蛋白含量的结果统计图；图7F为64名接受化疗并进行随访的胃癌患者，按血浆CGA浓度的中位数(304.7pg/ml)划分为CGA低表达和CGA高表达后，两组患者的生存曲线图。
图8A为Oncomine数据分析结果，CGA在胃癌组织和正常胃粘膜组织表达无统计学差异；图8B为GEPIA数据分析结果，CGA在胃癌组织和正常胃粘膜组织表达无统计学差异。
图9A为SGC7901 ADR和SGC7901 VCR细胞中CGA基因敲除位点示意及DNA测序结果图；图9B为蛋白印迹(Westernblotting，WB)验证SGC7901 ADR和SGC7901 VCR细胞中CGA基因敲除的两个单克隆细胞株(KO-1和KO-2)中CGA蛋白表达。
图10A为CGA基因WT和KO的SSGC7901 ADR细胞在不同浓度的氟尿嘧啶和阿霉素处理下的细胞存活率与药物浓度的拟合曲线；图10B为CGA基因WT和KO的SGC7901 VCR细胞在不同浓度的氟尿嘧啶和紫杉醇处理下的细胞存活率与药物浓度的拟合曲线。
图11A为CGA基因WT和KO的SGC7901 ADR细胞氟尿嘧啶和阿霉素处理后的细胞凋亡数量统计图；图11B为CGA基因WT和KO的SGC7901 VCR细胞氟尿嘧啶和紫杉醇处理后的细胞凋亡数量统计图。
图12A为CGA基因WT和KO的SGC7901 ADR细胞在氟尿嘧啶和阿霉素处理下的细胞生长曲线；图12B为CGA基因WT和KO的SGC7901 VCR细胞在氟尿嘧啶和紫杉醇处理下的细胞生长曲线。
图13A和13B为CGA基因WT和KO的SGC7901 ADR和SGC7901 VCR细胞在裸鼠体内在氟尿嘧啶、阿霉素和紫杉醇治疗条件下的肿瘤生长曲线；图13C和13D为CGA基因WT和KO的SGC7901 ADR和SGC7901 VCR细胞在裸鼠体内在氟尿嘧啶、阿霉素和紫杉醇治疗条件下的肿瘤重量统计图；图13E和13F为CGA基因WT和KO的SGC7901 ADR和SGC7901 VCR细胞在裸鼠体内在氟尿嘧啶、阿霉素和紫杉醇治疗条件下的肿瘤进行Ki-67和cleaved Caspase-3蛋白IHC染色后具有代表性的显微图。
图14A为靶向CGA的特异性miRNA的筛选策略示意图；图14B为miR-17-3p、miR-630、miR-708-3p、miR-761在胃癌耐药细胞SGC7901 ADR和SGC7901 VCR及其亲本SGC7901细胞中的表达；图14C为在胃癌耐药细胞SGC7901 ADR和SGC7901 VCR中转染miR-17-3p、miR-630、miR-708-3p、miR-761的拟似物后，WB检测细胞中CGA蛋白的表达变化。
图15A为转染miR-708-3p和miR-761拟似物的SGC7901 ADR细胞，在氟尿嘧啶和阿霉素处理下的细胞存活率；图15B为转染miR-708-3p和miR-761拟似物的SGC7901 VCR细胞，在氟尿嘧啶和紫杉醇处理下的细胞存活率。
图16A为SGC7901 ADR细胞成瘤后在6组不同处理条件下的肿瘤生长曲线，图16B为SGC7901 ADR细胞成瘤后在6组不同处理条件下的肿瘤图片，图16C为SGC7901 ADR细胞成瘤后在6组不同处理条件下的肿瘤重量统计图；图16D为SGC7901 ADR细胞成瘤后在6组不同处理条件下，进行Ki-67和cleaved Caspase-3蛋白IHC染色后具有代表性的显微图。
图17A为CGA基因敲除的SGC7901 ADR细胞在添加CGA重组蛋白(recombinant CGA，rCGA)后，在氟尿嘧啶和阿霉素处理下的细胞存活率；图17B为CGA基因敲除的SGC7901 ADR细胞在转染WT、N52Q、N78Q或DM的CGA表达质粒后，在氟尿嘧啶和阿霉素处理下的细胞存活率。
具体实施方式
除非另有说明，本文中的术语或方法根据相关领域普通技术人员的认识理解或采用 已有方法实现。
糖蛋白激素α多肽(glycoprotein hormones,alpha polypeptide,CGA)是人体内4种糖蛋白激素(人绒毛膜促性腺激素、卵泡刺激素、黄体生成素和促甲状腺激素)的共同α亚基。在正常生理条件下，人绒毛膜促性腺激素主要由胎盘的滋养层细胞分泌，卵泡刺激素、黄体生成素和促甲状腺激素主要由腺垂体细胞分泌。4种糖蛋白激素均由α和β两个亚基组成，其中β亚基为不同基因编码，α亚基均为CGA基因编码,CGA基因存在于人的6号染色体上，该序列区域长9.6kbp，有2个转录本，分别编码2个蛋白亚型。
本发明的CGA基因转录生成的mRNA(简称CGA mRNA)预期包括其全长核糖核苷酸序列，或天然存在的变体，或全长序列及变体的片段，特别是可被检测并确定具体序列的片段，更优选为能够在实体瘤组织中与其他RNA序列相区分的片段。优选地包含所述全长核糖核苷酸序列的至少7、8、9、10、11、12、15或20个连续的核糖核苷酸。
本发明的CGA基因编码蛋白预期包括所述蛋白的天然存在的变体以及所述蛋白或所述变体的片段，特别是免疫学上可检测的片段。免疫学上可检测的片段优选地包含所述标志物多肽的至少5、6、7、8、9、10、11、12、15或20个连续氨基酸。“CGA基因编码蛋白”的表述包括CGA的完整蛋白序列，及上述所定义的所述标志物多肽。
在本申请中，术语“实体瘤耐药”是指实体瘤患者或体外分离的实体瘤细胞或组织对单一化疗药物或多种化疗药物产生耐药性，具体是指与对化疗药物敏感(化疗敏感是指某种化疗药物在其正常血药浓度下对细胞生长的抑制率达到60％以上)的亲本细胞相比，经诱导或其他方法处理后，细胞对该化疗药物的IC50(半抑制浓度，指在用药后存活的细胞数量减少一半时所需的药物浓度)升高2倍以上。对于临床实体瘤患者：依据《实体肿瘤的疗效评价标准1.1版(Response Evaluation Criteria in Solid Tumors RECIST Version 1.1)》，新辅助化疗患者接受治疗后，判定为疾病进展(Progression Diseased，PD)和疾病稳定(StableDisease，SD)；姑息化疗患者接受治疗后，判定为疾病进展(Progression Diseased，PD)。
本发明涉及CGA mRNA或蛋白的检测试剂在制备用于实体瘤耐药诊断和/或预后评估的试剂或试剂盒中的应用，其中升高的CGA mRNA或蛋白的表达量是实体瘤耐药的指征和/或胃癌预后不良的指征。
术语“CGA mRNA的检测试剂”在本发明中不应仅仅理解为对CGA mRNA的检测剂，而应包括被本领域技术人员所知的其余可反映CGA mRNA表达水平的检测试剂。例如可通 过定量检测CGA mRNA反转录所得的cDNA对CGA mRNA的表达量进行间接检测。
“CGA mRNA的检测试剂”可选用本领域技术人员所公知的试剂，例如能够与该RNA杂交，且标记有荧光标记的核酸等；常见情况下RNA的检测剂可以选自RT-PCR的引物，以及用于扩增RT-PCR的产物——cDNA的引物；在一些实施方式中，所述CGA mRNA的检测试剂包括适用于如下至少一种方法的试剂：实时荧光定量PCR、数字PCR、荧光染料法、共振光散射法、测序或生物质谱法。
在一些实施方式中，所述CGAmRNA的定量检测剂为能够特异性结合CGAmRNA或CGA cDNA的探针或引物。
根据本发明的一方面，本发明还涉及CGA mRNA的qRT-PCR引物，其上游引物如SEQ ID NO：1所示，下游引物如SEQ ID NO：2所示。该引物可用于人胃癌耐药的诊断和/或预后评估。
“抗体”此用语包括多克隆抗体及单克隆抗体，“抗体片段”此用语包括这些抗体的抗原化合物结合片段，包括Fab、F(ab’) 2、Fd、Fv、scFv、双特异抗体和抗体最小识别单位，以及这些抗体和片段的单链衍生物，例如scFv-Fc等。抗体的类型可以选择IgG1、IgG2、IgG3、IgG4、IgA、IgM、IgE、IgD。此外，“抗体”此用语包括天然发生的抗体以及非天然发生的抗体，包括例如嵌合型(chimeric)、双功能型(bifunctional)、人源化(humanized)抗体以及人抗体，以及相关的合成异构形式(isoforms)。“抗体”此用语可和“免疫球蛋白”互换使用。
在一些实施方式中，所述测量样品包括血液(全血)、血清、血浆、细胞培养上清、尿液、组织或组织裂解液。
本发明所述CGA基因表达抑制剂是指基于通过CRISPR/Cas9基因编辑技术或RNA干扰技术，阻断CGA基因正常转录或转录后翻译过程的试剂、制剂或药物，例如CRISPR基因编辑治疗药物、反义核酸药物、siRNA药物、miRNA药物等。
本发明所述CGA蛋白表达抑制剂是指影响CGA蛋白翻译后修饰过程或影响CGA蛋白稳定性、以及影响CGA蛋白表达水平、活性或功能的试剂、制剂或药物，例如蛋白糖基化抑制剂、蛋白磷酸化抑制剂、中和抗体等。
下面将结合实施例对本发明的实施方案进行详细描述，但是本领域技术人员将会理解，下列实施例仅用于说明本发明，而不应视为限制本发明的范围。
胃癌是发生在胃部黏膜的癌症，绝大多数胃癌属于腺癌。在以下实施例中，非特殊说明的胃癌均为胃腺癌。但本发明的研究成果不限于胃癌，根据本领域技术人员的常规 认识，相关应用可及与包括肺癌、乳腺癌、结直肠癌、肝癌、卵巢癌和前列腺等实体瘤。
以下实施例中未注明具体条件者，按照常规条件或制造商建议的条件进行。所用试剂或仪器未注明生产厂商者，均为可以通过市购获得的常规产品。
其中，实施例中所使用细胞系SGC7901、SGC7901 ADR和SGC7901 VCR均保存于空军军医大学肿瘤生物学国家重点实验室。
SPSS 18.0软件用于数据统计和分析；P<0.05代表统计结果有意义。
实施例1：实时定量PCR(Real-time qualitative PCR，RT-qPCR)检测CGAmRNA在胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR与对照组细胞株SGC7901之间的表达差异
1.研究对象
胃腺癌细胞株SGC7901来源于自军事医学科学院，由空军军医大学肿瘤生物学国家重点实验室保藏；
SGC7901细胞培养于含10％(v/v)胎牛血清的DMEM培养基；
耐药胃癌细胞SGC7901 ADR和SGC7901 VCR细胞采用间歇诱导法建立，方法是分别将SGC7901亲本细胞短时间暴露于致死剂量的阿霉素和长春新碱培养基中逐代诱导而成，其中阿霉素浓度为2.5μg/ml，长春新碱浓度由1μg/ml逐渐增加至5μg/ml；具体的，SGC7901 ADR细胞长期培养时采用含0.05μg/ml阿霉素、10％胎牛血清的DMEM培养基SGC7901 VCR细胞长期培养时采用含0.5μg/ml长春新碱、10％胎牛血清的DMEM培养基，均于37℃、含5％(v/v)CO 2的条件下培养，细胞培养至对数生长期后，相对于化疗敏感细胞(即亲本细胞)相比，所培养细胞IC50升高2倍以上，收集细胞得到耐药胃癌细胞SGC7901 ADR和SGC7901 VCR，进行后续实验。所建立的SGC7901 ADR和SGC7901 VCR细胞对氟尿嘧啶、阿霉素、紫杉醇等化疗药交叉耐药。
2.实验方法
采用RT-qPCR检测CGA基因在SGC7901 ADR和SGC7901 VCR和SGC7901细胞的表达水平，具体步骤如下：
各细胞培养24h后，使用RNA分离试剂TRIzol从细胞中提取总RNA，并用紫外分光光度计测定RNA的浓度和质量；
使用Applied Biological Materials Inc.5×All-In-One RT MasterMix逆转录RNA获取cDNA，逆转录体系：RNA 1μg，5×All-In-One RT MasterMix 4μl，ddH 2O补充反应体积至20μl；反应条件：25℃孵育10min，42℃孵育15min，85℃酶灭活5min；
使用TaKaRa TB GreenPremix Ex Taq TM(TliRNaseH Plus),Bulk以逆转率产物为模版，通过TB Green嵌合荧光法进行RT-qPCR检测，反应体系：TB Green Premix Ex Taq(2×)(TliRNaseH Plus)，Bulk 12.5μl，上游引物1μl，下游引物1μl，cDNA 1μl，ddH 2O补充反应体积至25μl；反应条件：95℃反应30s，40个循环于95℃，5s；60℃，30s；在60℃时采集荧光；溶解曲线，从60℃升至95℃过程中，每个循环增加0.5℃；各PCR反应引物序列见表1；采用2 -△△CT法计算定量结果，对各细胞株内各mRNA表达量进行统计分析。
表1.RT-qPCR引物序列
Figure PCTCN2022100014-appb-000001
3.实验结论
图1为胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR与对照组细胞株SGC7901之间CGAmRNA表达量的结果图；由图1可知，CGAmRNA在胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR中的表达较对照组细胞株SGC7901升高，差异具有显著性(P<0.05)，说明CGAmRNA表达水平与胃癌多药耐药相关。
实施例2：WB检测CGA蛋白在胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR与对照组细胞株SGC7901之间的表达差异
1.研究对象
胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR与对照组细胞株SGC7901的培养同实施例1。
2.实验方法
采用WB检测CGA蛋白在SGC7901 ADR和SGC7901 VCR和SGC7901细胞的表达水平，具体步骤如下：
各细胞正常培养24h后，更换无胎牛血清的DMEM培养基继续培养24h，分别收集培养上清和细胞；
使用Millipore超滤管于4℃、4000×g离心1h以收集培养上清的分泌蛋白，使用RIPA细胞裂解液提取细胞总蛋白，BCA法测定上清和细胞样品蛋白的浓度和质量；
使用Bio-Rad的标准电泳装置进行电泳，使用Bio-Rad快速转膜仪转膜；将PVDF膜封闭后，一抗(兔抗人CGA单抗，Abcam，1：1000；鼠抗人α-Tubulin单抗，Sigma-Aldrich， 1：2000)孵育4℃过夜。PBS洗涤5min，重复3次，二抗(HRP标记驴抗兔、羊抗鼠IgG，GE Healthcare Life Sciences，1：5000)室温孵育1h；PBS洗涤5min，重复3次，使用ECL化学发光液，使用Bio-Rad ChemiDox XRS凝胶成像系统测定蛋白条带的灰度值。
3.实验结论
图2为胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR与对照组细胞株SGC7901之间在细胞内和培养上清中CGA蛋白表达量的结果图；由图2可知，胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR细胞内以及分泌到培养上清中CGA蛋白较对照组细胞株SGC7901升高，说明CGA蛋白表达水平与胃癌多药耐药相关。
实施例3：免疫荧光(Immunofluorescence，IF)检测CGA蛋白在胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR与对照组细胞株SGC7901之间的表达及亚细胞水平定位的差异
1.研究对象
胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR与对照组细胞株SGC7901的培养同实施例1。
2.实验方法
采用IF检测CGA蛋白在SGC7901 ADR、SGC7901 VCR和SGC7901细胞的表达和定位，具体步骤如下：
各细胞接种至腔室载玻片常规培养24h后，加入4％多聚甲醛以固定细胞，加入0.5％Triton，室温静置15min使细胞通透化；滴加山羊血清封闭液，室温静置30min；一抗(兔抗人CGA单抗，Abcam，1：1000)孵育4℃过夜。PBS洗涤5min，洗涤3次，二抗(Alexa Fluor Plus 594标记驴抗兔IgG，Thermo Fisher Scientific，1：200)室温避光孵育1h。PBS洗涤5min，重复3次，DAPI非特异性染细胞核15min；封片后使用Nikon A1共聚焦显微镜观察荧光表达。
3.实验结论
图3为胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR与对照组细胞株SGC7901之间CGA蛋白表达的免疫荧光结果图；由图3可知，胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR细胞中CGA蛋白的量较对照组细胞株SGC7901升高，且主要表达在SGC7901 ADR和SGC7901 VCR细胞的细胞质和细胞膜，说明CGA蛋白在胃癌多药耐药细胞中高表达。
实施例4：RT-qPCR检测胃癌细胞株SGC7901和NCI-N87细胞在亚致死剂量化疗药物诱 导条件下CGAmRNA的表达变化
1.研究对象
胃腺癌细胞SGC7901的培养同实施例1；胃腺癌细胞NCI-N87购自美国模式培养物集存库(American type culture collection，ATCC)，培养条件同SGC7901细胞；上述两株细胞均对化疗药氟尿嘧啶和阿霉素敏感；
2.实验方法
通过给予亚致死剂量(药物处理24h后细胞保持50％死亡率的药物浓度)的化疗药物处理，模拟肿瘤在体内的化疗环境，观察CGA基因的表达变化。
具体采用RT-qPCR检测CGA基因在SGC7901和NCI-N87细胞在接受亚致死剂量的氟尿嘧啶(1μg/ml)和阿霉素(0.5μg/ml)处理后第1、3、5、7天的表达水平，具体步骤同实施例1。
3.实验结论
图4为化疗药物敏感的胃癌细胞SGC7901和NCI-N87在亚致死剂量化疗药物诱导条件下CGAmRNA的表达变化；图4A是SGC7901和NCI-N87细胞在氟尿嘧啶(1μg/ml)培养条件下第1、3、5、7天后CGAmRNA的表达量与未处理对照细胞的CGAmRNA表达量的比较，图4B是SGC7901和NCI-N87细胞在阿霉素(0.5μg/ml)培养条件下第1、3、5、7天后CGAmRNA的表达量与未处理对照细胞的CGAmRNA表达量的比较。由图4可知，化疗药物可诱导CGA基因表达，且在化疗条件下存活时间越长的细胞中升高更为明显，说明CGA的表达量可反映胃癌细胞的耐药状态。
实施例5：免疫组织化学(Immunohistochemistry，IHC)检测CGA蛋白在接受化疗的胃癌患者的化疗前后配对的胃癌组织中的表达情况
1.研究对象
收集37例接受新辅助化疗胃癌患者在化疗前后的胃癌组织的石蜡包埋组织样本；化疗前样本取自胃镜活检，化疗后样本取自胃癌手术，患者在活检或手术前均未进行放疗和其他治疗。该实施例所使用的石蜡包埋组织样本均来自空军军医大学肿瘤生物学国家重点实验室组织样本库；按照伦理审查委员会规定的制度，每位患者在取样前均签署了知情同意书。收集37例胃癌患者的一般情况及病理信息见表2，其中31例为化疗耐药，6例为化疗敏感。
表237例胃癌患者的一般情况及病理信息
Figure PCTCN2022100014-appb-000002
Figure PCTCN2022100014-appb-000003
1化疗方案：FOLFOX，氟尿嘧啶、亚叶酸钙、奥沙利铂；EOX，表阿霉素、奥沙利铂、卡培他滨；DCF，多西他赛、顺铂、氟尿嘧啶；ECF，表阿霉素、顺铂、氟尿嘧啶；XELOX，卡培他滨、奥沙利铂；SOX，替吉奥、奥沙利铂；FOLFIRI，氟尿嘧啶、亚叶酸钙、伊立替康；FOLT，氟尿嘧啶、亚叶酸钙、奥沙利铂、多西他赛。
2疗效评价：PR，部分缓解；SD，疾病稳定；PD，疾病进展。
2.研究中对胃癌患者化疗敏感、化疗耐药等相关指标的定义
化疗敏感：指依据实体瘤疗效评价标准(Response Evaluation Criteria in Solid Tumors-RECIST)1.1版，胃癌患者在接受手术前对新辅助化疗方案的疗效评价为完全缓解(completeremission，CR)或PR的。
化疗耐药：指依据RECIST 1.1版，胃癌患者在接受手术前对新辅助化疗方案的疗效评价为SD或PD的。
3.实验方法
采用IHC检测37例胃癌患者化疗前后的胃癌组织中CGA蛋白的表达水平，具体步骤如下：
将组织切片置于60℃恒温箱中烘烤约1h后，在二甲苯中10min脱蜡，重复3次，再依次置于99.9％、96％和70％的乙醇中5min脱水，重复3次；
将切片置于柠檬酸钠抗原修复液中煮沸15min，将切片置于3％H 2O 2中15min，滴加封闭液室温孵育30min；一抗(兔抗人CGA单抗，Abcam，1：200)孵育4℃过夜；PBS洗涤5min，重复3次，二抗(生物素标记山羊抗兔IgG聚合物，中杉金桥)室温孵育1h；PBS洗涤，DAB显色，苏木精染细胞核。1％盐酸酒精分化，0.1％氨水返蓝后，将切片依次置于70％、96％和99.9％的乙醇中脱水，使用中性树胶封片；
采用免疫反应积分法对免疫组织化学反应进行半定量评分，染色强度分为4级：未 见阳性细胞计0分，弱阳性计1分，中等阳性计2分，强阳性计3分。IHC评分数＝Σ(染色强度×阳性细胞百分比)。
4.实验结论
图5A为在具有代表性的6例化疗耐药的胃癌患者中(Patient1-6)，CGA蛋白在胃癌化疗后癌组织(Post)及其配对的化疗前癌组织(Pre)的IHC染色显微图，结果表明CGA蛋白在化疗前胃癌组织阴性或弱阳性表达，而CGA蛋白在化疗后胃癌组织阳性或强阳性表达。图5B为31例化疗耐药的胃癌患者的化疗后和化疗前胃癌组织中CGA表达的IHC评分统计图，结果表明在31例化疗后胃癌组织样本中，有70.96％(22/31)的样本为CGA阳性染色；进一步采用非参数秩和检验进行统计学分析，发现CGA蛋白在胃癌化疗后癌组织较其配对的化疗前癌组织中表达水平升高，差异具有显著性差异(P<0.05)。图5C为6例化疗敏感的胃癌患者(Patient 7-12)的化疗后和化疗前胃癌组织中的CGA蛋白的IHC染色显微图，结果表明CGA蛋白在化疗前和化疗后胃癌组织中的表达无显著差异，均为阴性。由图5可知，CGA蛋白在化疗耐药胃癌患者的化疗后胃癌组织中显著升高且在化疗前后的胃癌组织中存在显著表达差异，而在化疗敏感胃癌患者的化疗前后组织中均为阴性表达，说明CGA蛋白与胃癌耐药的发生具有显著相关性。
实施例6：IHC检测CGA蛋白在接受化疗或对照处理的胃癌患者来源的异种移植(Patient derived xenograft，PDX)模型的肿瘤组织中的表达情况
1.研究对象
胃癌组织取材于空军军医大学第一附属医院接受胃癌切除术的胃癌患者；按照伦理审查委员会规定的制度，患者在取样前均签署了知情同意书；术中切除胃癌组织后，立即放入Hank’s平衡液中转运；
PDX模型在胃癌组织离体后4h内进行，具体步骤如下：
选择肿瘤活力较好的无菌胃癌组织，将组织剪切成约3mm 3的小块并与Matrigel混匀，每块分别接种至3-5只雄性NOD-Prkdc em1IDMO-Il2rg em2IDMO(NPI)小鼠，术后于无特定病原体(Specific pathogen free，SPF)环境中继续饲养，记为P0代PDX；每周测量小鼠体重，成瘤后每周测量肿瘤的长短径并计算肿瘤体积(肿瘤体积＝0.52×长径×短径 2)；当P0代PDX的肿瘤生长至500mm 3时进行传代移植，移植方法同前，成瘤后记为P1代PDX。以此方法依次获得的P2、P3、P4代具有稳定遗传特性的PDX小鼠可用于后续实验。收集4例胃癌患者的一般情况及病理信息见表3。
表3 4例胃癌患者的一般情况及病理信息
Figure PCTCN2022100014-appb-000004
2.实验方法
将同一患者组织来源的P2-P4代胃癌PDX小鼠分为实验组和对照组(每组3-5只)，实验组接受抗代谢类化疗药氟尿嘧啶(Fluorouracil，60mg/kg)腹腔注射(每周3次)，对照组接受等体积生理盐水腹腔注射(每周3次)，记录实验组和对照组肿瘤体积。3-4周后，按实验动物理论要求处死小鼠，对肿瘤组织固定、包埋、切片后进行IHC染色，观察CGA蛋白的表达。IHC具体步骤同实施例5。
3.实验结论
图6A为PDX1-4所对应治疗组和对照组小鼠移植瘤组织中CGA蛋白的IHC染色显微图,表明胃癌组织在接受化疗药物治疗后，各组的CGA蛋白表达水平较对照处理组的组织有不同程度的升高。图6B为4组PDX小鼠接受化疗及其对照组肿瘤体积的曲线图，反映了患者来源的肿瘤组织对化疗药的反应性：PDX1的实验组接受治疗后肿瘤生长缓慢，表明其对氟尿嘧啶敏感；PDX2-4实验组接受治疗后肿瘤体积依然升高，表明其对氟尿嘧啶耐药。将图6A中CGA蛋白的表达可与图6B肿瘤生长曲线对应分析可知：在接受化疗后，CGA蛋白表达升高不明显的肿瘤对化疗药物敏感，而CGA蛋白表达升高明显的肿瘤对化疗药物耐药。上述结果说明CGA蛋白的表达水平变化与胃癌耐药的发生具有显著相关性。
实施例7：ELISA检测不同人群血清中CGA蛋白含量并分析CGA对胃癌耐药的诊断价值1.研究对象
收集来自空军军医大学肿瘤生物学国家重点实验室组织样本库中的41例接受新辅助化疗的胃癌患者(新辅助化疗组Neoadjuvant chemo)、56例接受姑息化疗的胃癌患者(姑息化疗组Palliativechemo)、42例未接受化疗的胃癌患者(未化疗组Non-chemo)和57例正常人(正常对照组Normal)的血浆样品。其中，新辅助化疗组和姑息化疗组患者的化疗方案包括单独或联合使用氟尿嘧啶、紫杉醇、顺铂以及阿霉素，未化疗组患 者的血浆均是在患者最初诊断为胃癌并未接受任何放化疗时收集，正常人血清是经胃镜检查并经活检病例确诊为无上消化肿瘤的健康人的血清。按照伦理审查委员会规定的制度，每位患者在取样前均签署了知情同意书。收集139例胃癌患者的一般情况见表4-6。
表4 41例接受新辅助化疗胃癌患者的一般情况及病理信息
Figure PCTCN2022100014-appb-000005
Figure PCTCN2022100014-appb-000006
1化疗方案：DS，多西他赛、替吉奥；DF，顺铂、氟尿嘧啶；DOX，多西他赛、奥沙利铂、卡培他滨。
2患者生存时间截止至本研究随访结束时。
表5 56例接受姑息化疗胃癌患者的一般情况及病理信息
Figure PCTCN2022100014-appb-000007
Figure PCTCN2022100014-appb-000008
Figure PCTCN2022100014-appb-000009
1化疗方案：SP，替吉奥、顺铂；XELIRI，卡培他滨、伊立替康；EOX，表阿霉素、奥沙利铂、卡培他滨。
表6 42例未化疗胃癌患者的一般情况及病理信息
Figure PCTCN2022100014-appb-000010
Figure PCTCN2022100014-appb-000011
2.实验方法
采用ELISA检测胃癌化疗组、未化疗组和正常对照组血浆样品中CGA蛋白的含量，使用美国Novus Biologicals公司CGAELISA试剂盒(货号：NBP2-75262)，具体步骤如下：
将5000pg蛋白标准品溶解于1ml样本稀释液中，通过倍比稀释法，将标准品配制成5000、2500、1250、625、312.5、156.25、78.13、0pg/ml浓度梯度；将血浆与样本稀释液按1：2比例稀释；将各浓度梯度的标准品和稀释后的血浆样品加入96孔酶标板的点样孔中，加样量为100μl/孔，薄膜封闭后置于37℃孵育90min，弃去96孔板中液体，加入100μl生物素标记的CGA抗体稀释液(稀释比1：1000)，薄膜封闭后置于37℃孵育60min，弃去96孔板中液体，用洗涤液洗涤3次。每孔加入100μl辣根过氧化物工作液，薄膜封闭后置于37℃孵育30min，弃去96孔板中液体，用洗涤液洗涤3次。加入90μl底物工作液，薄膜封闭后置于37℃孵育15min，加入50μl终止工作液，使用酶标仪检测450nm的吸光度(OD值)；将不同浓度梯度标准品与对应的OD 值进行线性回归分析，拟合出函数方程式，将血浆样品对应的OD值代入该方程式，计算出样本中CGA的浓度。
3.实验结论
在血液中检测肿瘤标志物目前是肿瘤临床早期诊断最常用的方法，本实施例利用ELISA技术检测胃癌化疗组、未化疗组和正常对照组血浆样本中CGA蛋白的含量，结果如图7A所示：CGA在胃癌新辅助化疗组(Neoadjuvant chemo)和姑息化疗组(Palliativechemo)中的表达量高于未化疗组(Non-chemo)和正常对照组(Normal)，其差异具有显著性(P<0.05)；未接受化疗组与正常对照组的血浆CGA平均浓度无显著差异；如图7B所示，在新辅助化疗组患者中，疗效评估为SD的患者血浆CGA水平高于疗效评估为PR的患者，其差异具有显著性(P<0.01)；如图7C所示，在15例接受新辅助化疗组患者术前和术后配对的血浆中，CGA蛋白含量在术后低于术前，其差异具有显著性(P<0.05)。如图7D所示，在46名接受姑息化疗患者术前和术后配对的血浆中，CGA蛋白含量在化疗后低于接受化疗前，其差异具有显著性(P<0.01)；如图7E所示，在接受姑息性化疗患者中，疗效评估为PD的患者血浆CGA蛋白含量高于疗效评估为SD的患者，其差异具有显著性(P<0.05)；如图7F所示，根据血浆中CGA蛋白含量的中位数(304.7pg/ml)将64例接受化疗并进行随访的患者分为两组：CGA高表达组(CGAHigh)和CGA低表达组(CGALow)；通过Log-rank检验表明，血浆CGA高表达的患者生存期短于CGA低表达的患者。上述结果说明，血浆中CGA蛋白含量的可以反映胃癌患者对化疗的反应性，并可作为预判患者在接受化疗后生存时间的指标。
实施例8：
基于上述实施例的研究发现，发明人进一步根据Oncomine和GEPIA数据库中的相关数据，分析CGA基因在胃癌和正常组织中的表达情况
1.研究对象
Oncomine数据库是目前全球最大的癌基因芯片数据库和整合数据挖掘平台，整合了基因表达数据库(Gene Expression Omnibus，GEO)、肿瘤基因组图谱(The Cancer Genome Atlas，TCGA)和已发表的文献等来源的RNA和DNA-seq数据，可用于分析基因表达差异。基因表达谱数据交互分析(Gene Expression Profiling Interactive Analysis，GEPIA)数据库是在TCGA与基因型-组织表达(the genotype-tissue expression，GTEx)这两大转录组数据库基础上建立的可视化癌症大数据分析平台。发明人通过挖掘Oncomine 与GEPIA两大数据库中相关信息，分析CGA基因在胃癌与癌旁正常组织中的表达差异，以进一步明确CGA是否可作为胃癌耐药的特异性标志物。
2.分析方法
在Oncomine数据库(https://www.oncomine.org/)中，将胃癌组织与正常胃粘膜组织的多个数据集进行比较，分析各数据集中CGA基因的表达水平。为降低错误率，以P<0.0001、Fold Change>2和基因排名前10％作为筛选阈值对结果进一步分析。在GEPIA数据库(http://gepia.cancer-pku.cn/)中，以“CGA”和“STAD”为关键词检索CGA在胃癌和正常胃粘膜组织中的差异表达数据。
3.分析结论
图8A是Oncomine数据库中6个不同来源的DNA或RNA-seq数据集中胃癌组织样本和正常胃粘膜组织样本中CGA mRNA表达的数据分析结果，表明在6份数据中CGA基因的表达在胃癌和正常胃粘膜组织中均无统计学差异。图8B是GEPIA数据库中408例胃癌组织和211例正常胃粘膜组织中CGAmRNA表达的点状图，表明CGA基因的表达在胃癌组织和癌旁正常组织中无统计学差异。由图8可知，CGA基因在正常胃组织和胃癌组织中的表达无差异，结合本发明其他实施例，表明CGA是胃癌耐药的特异性标志物，而不是胃癌发生的标志物。
实施例9：构建稳定敲除CGA基因的细胞系
1.研究对象
耐药胃癌细胞SGC7901 ADR和SGC7901 VCR细胞的培养同实施例1。
2.实验方法
分别以胃癌耐药细胞SGC7901 ADR和SGC7901 VCR作为目标细胞，采用CRISPR/Cas9技术构建稳定敲除CGA基因的细胞系。具体实验步骤如下：
(1)设计合成sgRNA。通过sgRNA设计网站(https://crispr.dbcls.jp)设计并选择能够靶向CGA基因的sgRNA，以非靶向sgRNA序列为对照，核苷酸序列如表7所示；
(2)构建Cas9单载体质粒。将人类密码子优化过的Cas9和表达识别GFP的sgRNA载体gRNA_GFP-T1(购于Addgene，货号41819)，采用TOYOBO高保真高效率高速PCR酶KOD-Plus-Neo试剂盒(货号KOD-401)，将识别CGA基因的sgRNA 19bpDNA通过使用QuickChangePCR的方法插入sgRNA表达载体中；QuickChangePCR反应体系为：10×PCR Buffer for KOD-Plus-Neo 5μl，2mMdNTPs 5μl，25mM MgSO 4 3μl，上下游引 物(10μM)各1.5μl，gRNA_GFP-T1质粒模板50ng，KOD-Plus-Neo 1μl，ddH 2O补充反应体积至50μl；QuickChangePCR反应条件为：94℃反应2min；98℃反应10s，68℃反应2min，反应22个循；
(3)转染目的细胞：将1μg sgRNA表达质粒、3μg Cas9表达质粒和1μg EGFP(p-EGFP-C1)表达质粒同时转染SGC7901 ADR和SGC7901 VCR细胞，3天后使用流式细胞仪分选GFP表达阳性的单细胞，培养单细胞使之克隆化生长，通过PCR扩增后DNA测序和WB验证基因敲除是否成功。
采用WB检测CGA蛋白在SGC7901 ADR和SGC7901 VCR敲除CGA基因的细胞中的表达，具体步骤如下：使用RIPA细胞裂解液提取细胞总蛋白，BCA法测定细胞样品蛋白浓度；使用Bio-Rad的标准电泳装置进行电泳，使用Bio-Rad快速转膜仪转膜；将PVDF膜封闭后，一抗(兔抗人CGA单抗，购自Abcam，1：1000；鼠抗人α-Tubulin单抗，购自Sigma-Aldrich，1：2000)孵育4℃过夜。PBS洗涤5min，重复3次，二抗(HRP标记驴抗兔、羊抗鼠IgG，购自GE Healthcare Life Sciences，1：5000)室温孵育1h；PBS洗涤5min，重复3次，使用ECL化学发光液，通过Bio-Rad ChemiDox XRS凝胶成像系统测定蛋白条带的灰度值。
表7.靶向CGA基因的sgRNA序列
Figure PCTCN2022100014-appb-000012
3.实验结论
图9A为SGC7901 ADR和SGC7901 VCR细胞中CGA基因敲除位点示意及DNA测序结果图，表明在CGA基因的第3号外显子区域，sgRNA诱导Cas9蛋白发生切割后以非同源重组的方式进行修复，导致CGA基因缺损。图9B为WB验证SGC7901 ADR和SGC7901 VCR细胞中CGA基因敲除的两个单克隆细胞株(KO-1和KO-2)中CGA蛋白表达，表明sgRNA成功诱导了CGA基因切割和缺损性修复，导致CGA蛋白表达缺失。经结果鉴定，筛选最优靶点：sgRNA#1靶点活性最高。
实施例10：敲除CGA基因对胃癌耐药细胞系SGC7901 ADR和SGC7901 VCR在不同化疗药物处理下的细胞存活率的影响
1.研究对象
采用实施例9构建成功的胃癌耐药细胞系SGC7901 ADR和SGC7901 VCR敲除CGA基因的两个单克隆细胞株(KO-1和KO-2)进行细胞增殖-毒性实验，以未进行CGA基因敲除的多药耐药SGC7901 ADR和SGC7901 VCR细胞(WT)作为对照。
2.实验方法
将CGA基因WT、KO-1、KO-2的SGC7901 ADR和SGC7901 VCR细胞扩大培养至细胞状态良好，用胰酶消化各细胞，采用完全培养基调整各细胞浓度为5×10 4个/ml，将细胞悬液均匀的加入96孔板中，每孔100μl，37℃培养过夜；待细胞贴壁后，各孔置换为相应以梯度稀释的分别含有不同浓度氟尿嘧啶(Fluorouracil)、阿霉素(Adriamycin)或紫杉醇(Paclitaxel)的完全培养基，每孔100μl；并在无细胞的孔中加入相应不同浓度的含药培养基，作为空白对照；药物处理结束后，每孔加入10μl CCK-8溶液，在37℃继续培养2h，450nm测定吸光度，实验结果以细胞存活率表示：细胞存活率(％)＝(药物处理组-空白对照)/(未药物处理组-空白对照)×100％。
3.实验结论
图10A为CGA基因WT和KO的SGC7901 ADR细胞在不同浓度的氟尿嘧啶和阿霉素处理下的细胞存活率与药物浓度的拟合曲线，表明CGA基因敲除后，胃癌耐药细胞株SGC7901 ADR对氟尿嘧啶和阿霉素的IC50显著降低。图10B为CGA基因WT和KO的SGC7901 VCR细胞在不同浓度的氟尿嘧啶和紫杉醇处理下的细胞存活率与药物浓度的拟合曲线，表明CGA基因敲除后，胃癌耐药细胞株SGC7901 VCR对氟尿嘧啶和紫杉醇的IC50显著降低。由图10可知，CGA基因敲除可导致胃癌耐药细胞的耐药性明显降低。
实施例11：敲除CGA基因对胃癌耐药细胞系SGC7901 ADR和SGC7901 VCR在化疗药物处理下细胞凋亡的影响
1.研究对象
采用实施例9构建成功的胃癌耐药细胞系SGC7901 ADR和SGC7901 VCR敲除CGA基因的KO-1和KO-2两个单克隆细胞株，在一定化疗药物浓度条件下进行细胞凋亡检测，以未敲除CGA基因多药耐药的WTSGC7901 ADR和SGC7901 VCR细胞作为对照。
2.实验方法
将CGA基因WT、KO-1、KO-2的SGC7901 ADR和SGC7901 VCR细胞扩大培养至细胞状态良好，用胰酶消化各细胞，制备单细胞悬液，接种至6孔板，每孔细胞数约为2×10 5个；待细胞贴壁后，添加浓度为10μg/ml的氟尿嘧啶、阿霉素或紫杉醇处理各组细胞；药物处理结束后，将细胞制备成单细胞悬液；用预冷至4℃的PBS洗涤后，将细胞重悬于200μl结合缓冲液(10mMHEPES/NaOH，pH 7.4；140mMNaCl；2.5mM CaCl 2)，加入10μl Annexin V-FITC和5μl PI染色液，混匀后37℃避光孵育30min。加入300μl结合缓冲液，使用流式细胞仪在515nm激发光波波长下检测FITC荧光，用大于560nm激发光波波长检测PI荧光。
3.实验结论
图11A为CGA基因WT和KO的SGC7901 ADR细胞氟尿嘧啶和阿霉素处理后的细胞凋亡数据统计图，表明氟尿嘧啶和阿霉素更容易诱导CGA基因敲除后SGC7901 ADR的细胞凋亡。图11B为CGA基因WT和KO的SGC7901 VCR细胞氟尿嘧啶和紫杉醇处理后的细胞凋亡数据统计图，表明氟尿嘧啶和紫杉醇更容易诱导CGA基因敲除后SGC7901 VCR的细胞凋亡。由图11可知，CGA基因敲除可导致胃癌耐药细胞的耐药性明显降低，细胞易于发生化疗药诱导的细胞凋亡现象。
实施例12：敲除CGA基因对胃癌耐药细胞系SGC7901 ADR和SGC7901 VCR在化疗药物处理下细胞增殖能力的影响
1.研究对象
采用实施例9构建成功的胃癌耐药细胞系SGC7901 ADR和SGC7901 VCR敲除CGA基因的KO-1和KO-2两个单克隆细胞株，在一定化疗药物浓度条件下进行细胞增殖能力检测，以多药耐药的WT SGC7901 ADR和SGC7901 VCR细胞作为对照。
2.实验方法
将CGA基因WT、KO-1、KO-2的SGC7901 ADR和SGC7901 VCR细胞扩大培养至细胞状态良好，用胰酶消化各细胞，采用完全培养基调整各细胞浓度为5×10 4个/ml，将细胞悬液均匀的加入96孔板中，每孔100μl，37℃培养过夜；待细胞贴壁后，各孔置换为分别含有10μg/ml的氟尿嘧啶、阿霉素或紫杉醇的完全培养基，每孔100μl；在无细胞的孔中加入相应不同浓度的含药培养基，作为空白对照；药物处理结束后，每孔加入10μl CCK-8溶液，在37℃继续培养2h，450nm测定吸光度，实验结果以细胞存活率表 示：细胞存活率(％)＝(药物处理组-空白对照)/(未药物处理组-空白对照)×100％。
3.实验结论
图12A为CGA基因WT和KO的SGC7901 ADR细胞在氟尿嘧啶和阿霉素处理下的细胞生长曲线，表明CGA基因敲除后，胃癌耐药细胞株SGC7901 ADR对氟尿嘧啶和阿霉素处理条件下的增殖能力明显减弱；图12B为CGA基因WT和KO的SGC7901 VCR细胞在氟尿嘧啶和紫杉醇处理下的细胞生长曲线，表明CGA基因敲除后，胃癌耐药细胞株SGC7901 VCR对氟尿嘧啶和紫杉醇处理条件下的增殖能力明显减弱；由图12可知，CGA基因敲除可导致胃癌耐药细胞的在化疗药物环境中的增殖能力明显降低。
实施例13：敲除CGA基因对胃癌耐药细胞系SGC7901 ADR和SGC7901 VCR在小鼠体内对化疗药物治疗的影响
1.研究对象
采用实施例9构建成功的胃癌耐药细胞系SGC7901 ADR和SGC7901 VCR敲除CGA基因的单克隆细胞株(KO-1)，以多药耐药的WT SGC7901 ADR和SGC7901 VCR细胞作为对照；实验动物选取6-8周龄雌性胸腺缺失裸鼠(购自北京维通利华实验动物技术有限公司)，饲养于恒温恒湿SPF环境中。
2.实验方法
采用CGA基因WT或KO的SGC7901 ADR和SGC7901 VCR细胞进行裸鼠皮下成瘤实验，并通过腹腔注射化疗药物来观察其对肿瘤生长(肿瘤体积和重量)的影响。具体实验方法如下：随机将裸鼠分为对照组(注射CGA基因WT的SGC7901 ADR和SGC7901 VCR细胞)和实验组(注射CGA基因KO的SGC7901 ADR和SGC7901 VCR细胞)，每组各5只裸鼠，在每只裸鼠右侧胁腹部皮下各注射5×10 6个细胞；在注射肿瘤细胞成瘤2-3周后，待肿瘤生长至约100mm 3时，分别给予对照组和实验组裸鼠腹腔每3天注射生理盐水、氟尿嘧啶(20mg/kg)、阿霉素(8mg/kg)或紫杉醇(3mg/kg)，并观察和测量所形成肿瘤的大小(肿瘤体积＝0.52×长径×短径 2)。实验终止当日，按实验动物理论要求处死小鼠并取肿瘤称重。
对肿瘤组织固定、包埋、切片后进行IHC染色，观察细胞增殖相关蛋白Ki-67和细胞凋亡相关蛋白cleaved Caspase-3表达。IHC具体步骤如下：将组织切片置于60℃恒温箱中烘烤约1h后，在二甲苯中10min脱蜡，重复3次，再依次置于99.9％、96％和70％的乙醇中5min脱水，重复3次；将切片置于柠檬酸钠抗原修复液中煮沸15min，将切片置于3％H 2O 2中15min，滴加封闭液室温孵育30min；一抗(兔抗人Ki-67单抗， Abcam，1：200；兔抗人cleaved Caspase-3单抗，Abcam，1：200)孵育4℃过夜。PBS洗涤5min，重复3次，二抗(生物素标记山羊抗兔IgG聚合物，中杉金桥)室温孵育1h。PBS洗涤，DAB显色，苏木精染细胞核；1％盐酸酒精分化，0.1％氨水返蓝后，将切片依次置于70％、96％和99.9％的乙醇中脱水，使用中性树胶封片。
3.实验结论
图13A和13B为CGA基因WT和KO的SGC7901 ADR和SGC7901 VCR细胞在裸鼠体内对氟尿嘧啶、阿霉素和紫杉醇治疗条件下的肿瘤生长曲线。图13C和13D为CGA基因WT和KO的SGC7901 ADR和SGC7901 VCR细胞在裸鼠体内对氟尿嘧啶、阿霉素和紫杉醇治疗条件下的肿瘤图片和肿瘤重量统计图。图13A-D表明CGA基因敲除后，胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR在体内抵抗化疗药物的生长明显减慢。图13E和13F为CGA基因WT和KO的SGC7901 ADR和SGC7901 VCR细胞在裸鼠体内对氟尿嘧啶、阿霉素和紫杉醇治疗条件下的肿瘤，对Ki-67和cleaved Caspase-3蛋白IHC染色后具有代表性的显微图，表明CGA基因敲除后，胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR在体内经化疗药物治疗后，增殖能力显著减弱，细胞凋亡明显增加。由图13可知，CGA基因敲除可导致胃癌耐药细胞的在体内抵抗化疗药物的能力明显降低。
实施例14：在胃癌细胞中通过微小核糖核酸(microRNA，miRNA)干扰CGA基因的表达
1.研究对象
胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR的培养同实施例1；miRNA是真核生物细胞内长约18-25个核苷酸的非编码小分子RNA，通常在转录后水平负性调控基因表达。本发明中化学合成的miRNA拟似物购自广州锐博生物技术有限公司。
2.实验方法
通过在线miRNA预测算法网站miRWalk(http://mirwalk.umm.uni-heidelberg.de)和TargetScan(http://www.targetscan.org/vert_72/)分别预测能够特异性靶向CGA基因的miRNA，取二者的交集共获得36个特异性靶向CGA基因的miRNA(表8)。通过Pubmed(https://pubmed.ncbi.nlm.nih.gov)逐一查证这36个miRNA在癌症耐药中的功能，选择其中4个在胃癌耐药中功能未被报道的miRNA(miR-17-3p、miR-630、miR-708-3p、miR-761)进行后续研究。
采用RT-qPCR检测4个miRNA在胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR与其亲本化疗敏感SGC7901细胞之间的表达差异，具体步骤如下：各细胞培养24h后，使用QIAGEN  RNA提取试剂盒分别从三株细胞中提取总RNA，并用分光光度计测定RNA的浓度和质量；使用Takara逆转录试剂盒将RNA逆转录为cDNA，逆转录体系：RNA 3.75μl，2×mRQ Buffer 5μl，mRQ Enzyme 1.25μl；逆转录反应条件：37℃孵育60min，85℃孵育5min，4℃维持；使用Takara SYBR Premix Ex Taq II以逆转率产物为模版，通过嵌合荧光法进行RT-qPCR检测，反应体系：2×SYBR Premix Ex Taq II 10μl，上游引物1μl，下游引物1μl，cDNA 2μl，ddH 2O补充反应体积至20μl；反应条件：95℃反应30s，95℃反应5s，60℃反应30s(45个循环)，在60℃时采集荧光；各miRNA的PCR反应引物购自广州锐博生物技术有限公司。采用2 -△△CT法计算定量结果，对各细胞株内各mRNA表达量进行统计分析，CT为荧光信号达到阈值所需的循环次数。
采用脂质体法将4种miRNA的拟似物转染胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR，具体步骤如下：将SGC7901 ADR和SGC7901 VCR细胞培养至对数生长期，用胰酶消化各细胞，接种至6孔板，每孔细胞数约为2×10 5个；待细胞在6孔板中的生长融合度至约30％时，将培养基更换为Opti-MEM培养基；使用无菌的微量离心管，按相应比例将Opti-MEM(购自Gibco公司)分别与miR-17-3p、miR-630、miR-708-3p、miR-761的拟似物及阴性对照混匀；另取一只微量离心管，按相应比例将Opti-MEM与Lipofectamine RNAiMAX(购自Invitrogen公司)混匀；两管室温孵育5min后，混合均匀，室温孵育20min；将上述混合液缓慢加入相应6孔板中，48h后换为相应正常培养基；采用WB检测SGC7901 ADR和SGC7901 VCR转染4种miRNA拟似物的细胞中CGA蛋白的表达，具体步骤同实施例2。
3.实验结果
图14A为靶向CGA基因的特异性miRNA的筛选策略示意图。图14B为miR-17-3p、miR-630、miR-708-3p、miR-761在胃癌耐药细胞SGC7901 ADR和SGC7901 VCR及其亲本SGC7901细胞中的表达，表明这4个miRNA在耐药细胞中的表达均下降，这是上调这些miRNA进行靶向抑制CGA的前提条件。图14C为在胃癌耐药细胞SGC7901 ADR和SGC7901 VCR中转染miR-17-3p、miR-630、miR-708-3p、miR-761的拟似物后，WB检测细胞中CGA蛋白的表达变化，表明miR-708-3p和miR-761能够明显抑制CGA蛋白的表达，发挥了靶向抑制CGA的作用。由图14可知，miRNA能够干扰胃癌细胞中CGA基因的表达，其中miR-708-3p和miR-761是有效抑制CGA的miRNA。
表8miRWalk和TargetScan数据库共同预测可靶向CGA的miRNA
Figure PCTCN2022100014-appb-000013
Figure PCTCN2022100014-appb-000014
Figure PCTCN2022100014-appb-000015
实施例15：miRNA干扰CGA基因对胃癌耐药细胞系SGC7901 ADR和SGC7901 VCR在不同化疗药物处理下的细胞存活率的影响
1.研究对象
胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR的培养同实施例1。化学合成的miR-708-3p和miR-761拟似物购自广州锐博生物技术有限公司。
2.实验方法
采用脂质体法将miR-708-3p和miR-761拟似物转染胃癌耐药细胞株SGC7901 ADR和SGC7901 VCR，具体步骤同实施例9；在氟尿嘧啶、阿霉素、紫杉醇的IC50浓度处理下进行细胞存活率检测，以转染阴性对照miRNA拟似物的SGC7901 ADR和SGC7901 VCR细胞作为对照，具体步骤同实施例10。
3.实验结论
图15A为转染miR-708-3p和miR-761拟似物的SGC7901 ADR细胞，在氟尿嘧啶和阿霉素处理下的细胞存活率，表明转染miR-708-3p和miR-761拟似物干扰CGA基因表达后，胃癌耐药细胞株SGC7901 ADR对氟尿嘧啶和阿霉素处理条件下的存活能力明显减弱。图15B为转染miR-708-3p和miR-761拟似物的SGC7901 VCR细胞，在氟尿嘧啶和紫杉醇处理下的细胞存活率，表明转染miR-708-3p和miR-761拟似物干扰CGA基因表达后，胃癌耐药细胞株SGC7901 VCR对氟尿嘧啶和阿霉素处理条件下的存活能力明显减弱。由图15可知，通过miRNA干扰CGA基因表达可导致胃癌耐药细胞的在化疗药物环境中的存活能力明显降低。
实施例16：miRNA干扰CGA基因对胃癌耐药细胞系SGC7901 ADR在小鼠体内对化疗药物治疗的影响
1.研究对象
胃癌耐药细胞株SGC7901 ADR的培养同实施例1。实验动物的来源与饲养同实施例13。体内注射用miR-708-3p和miR-761拟似物购自西安荣清畅生物科技有限公司。
2.实验方法
采用胃癌耐药细胞SGC7901 ADR进行裸鼠皮下成瘤实验，具体实施步骤如下：在每只裸鼠右侧胁腹部皮下各注射5×10 6个细胞。在注射肿瘤细胞成瘤2-3周后，待肿瘤生长至约100mm 3时，随机将裸鼠分为6组，每组8只裸鼠；第1组每3天瘤内注射miRNA对照药物(prodrugctrl)和腹腔注射生理盐水；第2组每3天瘤内注射miRNA对照药物和腹腔注射氟尿嘧啶(20mg/kg)；第3组每3天瘤内注射miR-708-3p拟似物药物(miR-708-3p prodrug)和腹腔注射生理盐水；第4组每3天瘤内注射miR-708-3p拟似物药物和腹腔注射氟尿嘧啶；第5组每3天瘤内注射miR-761拟似物药物(miR-761prodrug)和腹腔注射生理盐水；第6组每3天瘤内注射miR-761拟似物药物和腹腔注射氟尿嘧啶。观察和测量每组所形成肿瘤的大小(肿瘤体积＝0.52×长径×短径 2)。实验终止当日，按实验动物理论要求处死小鼠并取肿瘤称重。对肿瘤组织固定、包埋、切片后进行IHC染色，观察细胞增殖相关蛋白Ki-67和细胞凋亡相关蛋白cleaved Caspase-3表达，具体步骤同实施例5。
3.实验结论
图16A为SGC7901 ADR细胞成瘤后在6组不同处理条件下的肿瘤生长曲线，图15B为SGC7901 ADR细胞成瘤后在6组不同处理条件下的肿瘤图片，图16C为SGC7901 ADR细胞成瘤后在6组不同处理条件下的肿瘤重量统计图，图16A-C表明在注射miR-708-3p和miR-761拟似物干扰CGA基因表达后，胃癌耐药细胞株SGC7901 ADR在体内抵抗化疗药物的生长明显减慢；图16D为SGC7901 ADR细胞成瘤后在6组不同处理条件下，对Ki-67和cleaved Caspase-3蛋白IHC染色后具有代表性的显微图，表明在注射miR-708-3p和miR-761拟似物干扰CGA基因表达后，胃癌耐药细胞株SGC7901 ADR在体内经化疗药物治疗后的增殖能力显著减弱，细胞凋亡明显增加。由图16可知，miRNA干扰CGA基因表达可导致胃癌耐药细胞的在体内抵抗化疗药物的能力明显降低。
实施例17：干扰CGA蛋白糖基化对胃癌耐药细胞系SGC7901 ADR在化疗药物处理下细胞存活率的影响
糖基化是蛋白合成后重要的翻译后修饰过程，干扰蛋白的糖基化过程可影响蛋白的稳定性，进而干扰其在细胞内的表达。本实施例的目的在于证明干扰CGA蛋白的糖基化 修饰可减少细胞对化疗药物的耐药性。
1.研究对象
本实施例采用实施例9构建成功的胃癌耐药细胞系SGC7901 ADR敲除CGA基因的KO-1单克隆细胞株，在培养基中添加经不同条件处理后的rCGA或转染糖基化修饰位点突变的CGA质粒后，在化疗药物处理的条件下进行细胞存活率检测。
2.实验方法
采用肽N-糖苷酶F(PNGase F，购自苏州瑞安生物公司)孵育rCGA溶液(购自北京义翘神州公司)，37℃条件下反应4h，去除rCGA蛋白肽链上的N-连聚糖。
采用QuickChangePCR方法，将野生型(WT)的人CGA表达质粒(购自上海吉凯公司)上的两个N-糖基化位点(第52和第78位天冬氨酸)分别或同时突变为谷氨酸(突变第52位天冬氨酸命名为N52Q，突变第78位天冬氨酸命名为N78Q，同时突变第52位和第78位天冬氨酸命名为DM)，QuickChangePCR具体步骤同实施例9。
在CGA基因敲除的SGC7901 ADR细胞的培养基中，添加经过或未经过PNGase F处理后的rCGA(20μg/ml)；或通过脂质体法将WT、N52Q、N78Q或DM的人CGA表达质粒转染CGA基因敲除的SGC7901 ADR细胞，具体步骤同实施例9；经上述处理后，细胞在氟尿嘧啶和阿霉素的IC50浓度处理下进行存活率检测，具体步骤同实施例10。
3.实验结论
图17A为CGA基因敲除的SGC7901 ADR细胞在添加rCGA后，在氟尿嘧啶和阿霉素处理下的细胞存活率，表明添加未经PNGase F处理的rCGA后，CGA基因敲除的SGC7901 ADR对氟尿嘧啶或阿霉素处理条件下的存活能力明显增强；但添加经过PNGase F处理的rCGA后，CGA基因敲除的SGC7901 ADR对氟尿嘧啶或阿霉素处理条件下的存活能力无显著差异。图17B为CGA基因敲除的SGC7901 ADR细胞在转染WT、N52Q、N78Q或DM的CGA表达质粒后，在氟尿嘧啶和阿霉素处理下的细胞存活率，表明转染WT的CGA表达质粒后，CGA基因敲除的SGC7901 ADR对氟尿嘧啶或阿霉素处理条件下的存活能力明显增强，但转染N52Q、N78Q或DM的CGA表达质粒后，CGA基因敲除的SGC7901 ADR对氟尿嘧啶或阿霉素处理条件下的存活能力无显著差异。由图17可知，干扰CGA蛋白糖基化可导致胃癌耐药细胞的在化疗药物环境中的存活能力明显降低，可作为减少肿瘤细胞耐药性的方法。

Claims (14)

  1. CGA基因或其编码蛋白作为靶点在制备用于实体瘤耐药诊断和/或预后评估的试剂或试剂盒中的应用。
  2. CGA基因或其编码蛋白的检测试剂在制备用于实体瘤耐药诊断和/或预后评估的试剂或试剂盒中的应用。
  3. 根据权利要求1所述的应用，其特征在于，所述试剂或试剂盒通过RT-PCR、实时定量PCR、数字PCR、荧光染料法、共振光散射法、测序或生物质谱法、原位杂交、Northern blotting、芯片、高通量测序平台、免疫组织化学或酶联免疫吸附法检测CGA基因转录的信使RNA或CGA基因编码蛋白。
  4. 根据权利要求1所述的应用，其特征在于，所述试剂或试剂盒中含有扩增CGA基因的特异性引物、与CGA基因核苷酸序列杂交的探针或与CGA蛋白特异性结合的抗体或抗体片段。
  5. 根据权利要求4所述的应用，其特征在于，所述抗体为单克隆抗体或多克隆抗体。
  6. 根据权利要求1～5任一权利要求所述的应用，其特征在于，所述试剂或试剂盒的检测样本为血清、血浆、细胞、细胞培养上清、尿液、组织或组织裂解液。
  7. CGA基因或其编码蛋白的作为靶点在制备用于治疗耐药实体瘤药物的应用。
  8. CGA基因表达抑制剂或蛋白表达的抑制剂制备用于治疗耐药实体瘤药物的应用。
  9. 如权利要求8所述的应用，其特征在于，所述CGA基因表达抑制剂选自通过CRISPR/Cas9基因编辑技术或RNA干扰技术阻断CGA基因正常转录或转录后翻译过程的CRISPR基因编辑治疗药物、反义核酸药物、siRNA药物或miRNA药物。
  10. 如权利要求8所述的应用，其特征在于，所述CGA蛋白表达抑制剂选自影响CGA蛋白翻译后修饰过程或影响CGA蛋白稳定性、以及影响CGA蛋白表达水平、活性或功能的蛋白糖基化抑制剂、蛋白磷酸化抑制剂或中和抗体。
  11. 一种耐药实体瘤细胞研究模型的构建方法，其特征在于，方法包括：敲除实体瘤细胞中的CGA基因。
  12. 如权利要求11所述的耐药实体瘤细胞研究模型的构建方法，其特征在于，在含有一种或多种化疗药物的培养基中培养实体瘤细胞构建初始耐药实体瘤细胞，之后敲除初始耐药实体瘤细胞中的CGA基因得到耐药实体瘤细胞。
  13. 如权利要求12所述的耐药实体瘤细胞研究模型的构建方法，其特征在于，采用CRISPR/Cas9技术敲除初始耐药实体瘤细胞中的CGA基因得到耐药实体瘤细胞。
  14. 一种耐药实体瘤动物模型的构建方法，其特征在于，方法包括：将权利要求12或13所述方法构建的耐药实体瘤细胞注射入动物模型构建耐药实体瘤动物模型。
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