Gastric Cancer Marker Detection and Its Kit Development
NCT ID: NCT05010863
Last Updated: 2021-08-18
Study Results
Results pending
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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Recruitment Status
RECRUITING
Total Enrollment
530 participants
Study Classification
OBSERVATIONAL
Study Start Date
2021-01-01
Study Completion Date
2030-12-30
Brief Summary
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The gastric cancer diagnosis and treatment specifications clearly point out that tumor markers need to be detected in the process of diagnosis, efficacy evaluation and follow-up. However, there is currently a lack of gastric cancer markers with high sensitivity and specificity, and the detection of markers is limited to a single index analysis, which has many shortcomings such as long analysis time, large reagent consumption, and high detection cost. Therefore, this project will use protein chips to detect new types of gastric cancer patient markers and establish a multi-diagnostic model for early screening of gastric cancer. Finally, monoclonal antibodies will be produced against various high-specific tumor markers and a gastric cancer diagnostic kit will be established.
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Detailed Description
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1 Preliminary screening of early gastric cancer markers and antibody verification
(1) Recruitment and sample preparation of patients and healthy people: This project requires four batches of subjects, three batches of healthy people, early gastric cancer and advanced gastric cancer groups, with an average of 30 cases in each group. The other batch (the second batch) is healthy people and 30 cases of chronic atrophic gastritis, early gastric cancer and 30 cases of chronic atrophic gastritis. There were 100 cases in each of the advanced gastric cancer group, and 20 cases in each of liver cancer, colorectal cancer, and breast cancer. Serum and plasma samples obtained from subjects are used to screen potential gastric cancer tumor markers, verify the practicability of established gastric cancer tumor marker diagnostic models and test kits.
1. Recruitment of gastric cancer patients: 30 cases of early gastric cancer patients (T1, T2) and advanced gastric cancer patients (T3, T4) are selected respectively. The staging of gastric cancer is based on the eighth edition of UICC (International Union Against Cancer) TNM staging. Subjects were screened according to the requirements of the informed consent form.
2. Recruitment of healthy people: 30 volunteers without underlying diseases are selected as healthy control group. Subjects were screened according to the requirements of the informed consent form.
3. Sample preparation: intravenous collection to obtain whole blood samples of patients and healthy controls. The sample requirement for each subject is 600ul of serum and plasma.
(2) Antibody chip screening for potential tumor markers of gastric cancer for the first time In order to screen for potential protein markers of gastric cancer, Raybiotech's high-throughput quantitative antibody chip (AAH-BLG-2000) was used to measure 640 in the first batch of subjects (early gastric cancer, advanced gastric cancer, and healthy controls each 30). Kind of human protein. Preliminarily screen out differential proteins, conduct bioinformatics analysis, and finally screen differentially expressed proteins relevant to the research.
2Customized antibody chip to verify gastric cancer tumor markers In order to further verify the candidate tumor markers for the diagnosis of gastric cancer, the differential proteins screened in the previous stage were customized for antibody chips. Use subject serum samples (second batch) for potential biomarker verification. According to the test results, the poorly specific proteins are discarded, and the more specific proteins are retained.
3\. Establishment of diagnostic model Use regression analysis to combine and compare multiple differential proteins, perform quantitative analysis, establish a standard curve, establish a diagnostic model for highly specific differential proteins, and further measure the practicability of the highly specific differential protein diagnostic model.
4 Kit development Monoclonal antibodies were produced as capture antibodies for various high-specific tumor markers, and finally a gastric cancer diagnosis kit was established and promoted in clinical practice.
Establishment and performance measurement of gastric cancer diagnostic kit.
1. Establish gastric cancer diagnostic kits, quality control reference materials and formulate relevant standards on the basis of the above research results.
2. Precision testing: Dilute the self-made quality control reference materials to 3 concentrations of high, medium, and low, each with 3 replicate holes, repeat the test 10 times, and calculate the mean, standard deviation, and test value of each quality control reference product. Coefficient of Variation (CV) value.
3. Sensitivity detection: Take the zero reference standard (specific difference protein) as the sample, and substitute the average value of the fluorescence value measured 20 times plus 2 times the standard deviation into the standard curve equation to calculate the minimum detection volume.
4. Stability test: Divide the self-made kits into two groups and place them in a 4℃ freezer for 6 months and 37℃ for 7 days. The physical appearance of the kit, the linearity of the dose-response curve, accuracy, sensitivity, and minimum detection volume And other indicators are measured, and the specific detection method is the same as the above steps (2) and (3).
5. Comparison with other gastric cancer detection methods: use self-prepared detection kits to detect 30 cases of early gastric cancer serum samples, 30 cases of advanced gastric cancer serum samples, and 30 healthy human serum samples, and analyze the test results.
6. Promotion and optimization of the kit. Random sampling is performed among patients using this kit to observe the diagnosis rate of early clinical gastric cancer and the corresponding prognosis, and analyze the results of the return visit. According to the results of the return visit, continue to conduct corresponding experiments to optimize the performance of the kit, for example: improve its accuracy, sensitivity, and so on.
(1) Recruitment and sample preparation of patients and healthy people: This project requires four batches of subjects, three batches of healthy people, early gastric cancer and advanced gastric cancer groups, with an average of 30 cases in each group. The other batch (the second batch) is healthy people and 30 cases of chronic atrophic gastritis, early gastric cancer and 30 cases of chronic atrophic gastritis. There were 100 cases in each of the advanced gastric cancer group, and 20 cases in each of liver cancer, colorectal cancer, and breast cancer. Serum and plasma samples obtained from subjects are used to screen potential gastric cancer tumor markers, verify the practicability of established gastric cancer tumor marker diagnostic models and test kits.
1. Recruitment of gastric cancer patients: 30 cases of early gastric cancer patients (T1, T2) and advanced gastric cancer patients (T3, T4) are selected respectively. The staging of gastric cancer is based on the eighth edition of UICC (International Union Against Cancer) TNM staging. Subjects were screened according to the requirements of the informed consent form.
2. Recruitment of healthy people: 30 volunteers without underlying diseases are selected as healthy control group. Subjects were screened according to the requirements of the informed consent form.
3. Sample preparation: intravenous collection to obtain whole blood samples of patients and healthy controls. The sample requirement for each subject is 600ul of serum and plasma.
(2) Antibody chip screening for potential tumor markers of gastric cancer for the first time In order to screen for potential protein markers of gastric cancer, Raybiotech's high-throughput quantitative antibody chip (AAH-BLG-2000) was used to measure 640 in the first batch of subjects (early gastric cancer, advanced gastric cancer, and healthy controls each 30). Kind of human protein. Preliminarily screen out differential proteins, conduct bioinformatics analysis, and finally screen differentially expressed proteins relevant to the research.
2Customized antibody chip to verify gastric cancer tumor markers In order to further verify the candidate tumor markers for the diagnosis of gastric cancer, the differential proteins screened in the previous stage were customized for antibody chips. Use subject serum samples (second batch) for potential biomarker verification. According to the test results, the poorly specific proteins are discarded, and the more specific proteins are retained.
3\. Establishment of diagnostic model Use regression analysis to combine and compare multiple differential proteins, perform quantitative analysis, establish a standard curve, establish a diagnostic model for highly specific differential proteins, and further measure the practicability of the highly specific differential protein diagnostic model.
4 Kit development Monoclonal antibodies were produced as capture antibodies for various high-specific tumor markers, and finally a gastric cancer diagnosis kit was established and promoted in clinical practice.
Establishment and performance measurement of gastric cancer diagnostic kit.
1. Establish gastric cancer diagnostic kits, quality control reference materials and formulate relevant standards on the basis of the above research results.
2. Precision testing: Dilute the self-made quality control reference materials to 3 concentrations of high, medium, and low, each with 3 replicate holes, repeat the test 10 times, and calculate the mean, standard deviation, and test value of each quality control reference product. Coefficient of Variation (CV) value.
3. Sensitivity detection: Take the zero reference standard (specific difference protein) as the sample, and substitute the average value of the fluorescence value measured 20 times plus 2 times the standard deviation into the standard curve equation to calculate the minimum detection volume.
4. Stability test: Divide the self-made kits into two groups and place them in a 4℃ freezer for 6 months and 37℃ for 7 days. The physical appearance of the kit, the linearity of the dose-response curve, accuracy, sensitivity, and minimum detection volume And other indicators are measured, and the specific detection method is the same as the above steps (2) and (3).
5. Comparison with other gastric cancer detection methods: use self-prepared detection kits to detect 30 cases of early gastric cancer serum samples, 30 cases of advanced gastric cancer serum samples, and 30 healthy human serum samples, and analyze the test results.
6. Promotion and optimization of the kit. Random sampling is performed among patients using this kit to observe the diagnosis rate of early clinical gastric cancer and the corresponding prognosis, and analyze the results of the return visit. According to the results of the return visit, continue to conduct corresponding experiments to optimize the performance of the kit, for example: improve its accuracy, sensitivity, and so on.
Conditions
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Gastric Cancer
Study Design
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Observational Model Type
COHORT
Study Time Perspective
PROSPECTIVE
Study Groups
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Patients with early gastric cancer
Blood collection
Intervention Type
OTHER
The subject will be drawn a 5ml blood sample
Patients with advanced gastric cancer
Blood collection
Intervention Type
OTHER
The subject will be drawn a 5ml blood sample
healthy person
Blood collection
Intervention Type
OTHER
The subject will be drawn a 5ml blood sample
Patients with colorectal cancer
Blood collection
Intervention Type
OTHER
The subject will be drawn a 5ml blood sample
Liver cancer patients
Blood collection
Intervention Type
OTHER
The subject will be drawn a 5ml blood sample
Breast cancer patient
Blood collection
Intervention Type
OTHER
The subject will be drawn a 5ml blood sample
Patients with atrophic gastritis
Blood collection
Intervention Type
OTHER
The subject will be drawn a 5ml blood sample
Interventions
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Blood collection
The subject will be drawn a 5ml blood sample
Intervention Type
OTHER
Eligibility Criteria
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Inclusion Criteria
patient
1. Age is greater than or equal to 18 years old (including 18 years old);
2. Patients who are diagnosed with cancer after pathological diagnosis;
3. Can provide enough tissue samples;
4. Have not received anti-tumor treatment in the past;
5. Comply with the principle of informed consent and sign the informed consent form.
healthy person:
1. Age is greater than or equal to 18 years old (including 18 years old);
2. No underlying disease;
3. Can provide enough tissue samples;
4. Comply with the principle of informed consent and sign the informed consent form.
1. Age is greater than or equal to 18 years old (including 18 years old);
2. Patients who are diagnosed with cancer after pathological diagnosis;
3. Can provide enough tissue samples;
4. Have not received anti-tumor treatment in the past;
5. Comply with the principle of informed consent and sign the informed consent form.
healthy person:
1. Age is greater than or equal to 18 years old (including 18 years old);
2. No underlying disease;
3. Can provide enough tissue samples;
4. Comply with the principle of informed consent and sign the informed consent form.
Exclusion Criteria
1. The tumor foci cannot be clearly derived from a specific tumor type;
2. Those who have a history of other tumors, autoimmune diseases and allergies;
3. Previously received anti-tumor treatments such as surgery, chemotherapy, radiotherapy, molecular targeted therapy, immunotherapy, biological therapy or Chinese medicines with anti-cancer and anti-tumor effects in the instructions;
4. Participated in any clinical trial within 90 days before the experiment;
5. Received major surgery within 90 days before the experiment;
6. Received bone marrow transplantation 90 days before the experiment;
7. Subjects who may not be able to complete the study due to other reasons or who are determined by the investigator to be unsuitable to participate in this study.
2. Those who have a history of other tumors, autoimmune diseases and allergies;
3. Previously received anti-tumor treatments such as surgery, chemotherapy, radiotherapy, molecular targeted therapy, immunotherapy, biological therapy or Chinese medicines with anti-cancer and anti-tumor effects in the instructions;
4. Participated in any clinical trial within 90 days before the experiment;
5. Received major surgery within 90 days before the experiment;
6. Received bone marrow transplantation 90 days before the experiment;
7. Subjects who may not be able to complete the study due to other reasons or who are determined by the investigator to be unsuitable to participate in this study.
Eligible Sex
ALL
Accepts Healthy Volunteers
Yes
Sponsors
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Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University
OTHER
Sponsor Role
collaborator
First Affiliated Hospital of Wenzhou Medical University
OTHER
Sponsor Role
collaborator
Second Affiliated Hospital of Wenzhou Medical University
OTHER
Sponsor Role
lead
Responsible Party
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Responsibility Role
SPONSOR
Locations
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No. 109, Xueyuan West Road, Lucheng District, Wenzhou City，Zhejiang provincece
Wenzhou, Zhejiang, China
Site Status
RECRUITING
Countries
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China
Central Contacts
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Facility Contacts
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References
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Kim Y, Byeon SJ, Hur J, Lee K, Kim D, Ahn JH, Lee SH, You WK, Kim ST, Park SH, Kang WK, Kim KM, Lee J. High delta-like ligand 4 expression correlates with a poor clinical outcome in gastric cancer. J Cancer. 2019 Jun 2;10(14):3172-3178. doi: 10.7150/jca.30257. eCollection 2019.
Reference Type
BACKGROUND
Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA Cancer J Clin. 2019 Jan;69(1):7-34. doi: 10.3322/caac.21551. Epub 2019 Jan 8.
Reference Type
BACKGROUND
Chen J, Xu M, Zhang Y, Gao C, Sun P. Effects of a stepwise, local patient-specific early oral feeding schedule after gastric cancer surgery: a single-center retrospective study from China. Sci Rep. 2019 Nov 12;9(1):16539. doi: 10.1038/s41598-019-52629-0.
Reference Type
BACKGROUND
Woll E, Thaler J, Keil F, Gruenberger B, Hejna M, Eisterer W, Fridrik MA, Ulmer H, Trommet V, Huemer F, Weiss L, Greil R. Oxaliplatin/Irinotecan/Bevacizumab Followed by Docetaxel/Bevacizumab in Inoperable Locally Advanced or Metastatic Gastric Cancer Patients - AGMT_GASTRIC-3. Anticancer Res. 2017 Oct;37(10):5553-5558. doi: 10.21873/anticanres.11987.
Reference Type
BACKGROUND
Petrovic M, Bukumiric Z, Zdravkovic V, Mitrovic S, Atkinson HD, Jurisic V. The prognostic significance of the circulating neuroendocrine markers chromogranin A, pro-gastrin-releasing peptide, and neuron-specific enolase in patients with small-cell lung cancer. Med Oncol. 2014 Feb;31(2):823. doi: 10.1007/s12032-013-0823-1. Epub 2013 Dec 30.
Reference Type
BACKGROUND
Tsai MM, Wang CS, Tsai CY, Huang HW, Chi HC, Lin YH, Lu PH, Lin KH. Potential Diagnostic, Prognostic and Therapeutic Targets of MicroRNAs in Human Gastric Cancer. Int J Mol Sci. 2016 Jun 16;17(6):945. doi: 10.3390/ijms17060945.
Reference Type
BACKGROUND
Necula L, Matei L, Dragu D, Neagu AI, Mambet C, Nedeianu S, Bleotu C, Diaconu CC, Chivu-Economescu M. Recent advances in gastric cancer early diagnosis. World J Gastroenterol. 2019 May 7;25(17):2029-2044. doi: 10.3748/wjg.v25.i17.2029.
Reference Type
BACKGROUND
Shibutani M, Maeda K, Nagahara H, Ohtani H, Sakurai K, Yamazoe A, Kimura K, Toyokawa T, Amano R, Kubo N, Tanaka H, Muguruma K, Ohira M, Hirakawa K. Significance of Markers of Systemic Inflammation for Predicting Survival and Chemotherapeutic Outcomes and Monitoring Tumor Progression in Patients with Unresectable Metastatic Colorectal Cancer. Anticancer Res. 2015 Sep;35(9):5037-46.
Reference Type
BACKGROUND
Ning S, Wei W, Li J, Hou B, Zhong J, Xie Y, Liu H, Mo X, Chen J, Zhang L. Clinical significance and diagnostic capacity of serum TK1, CEA, CA 19-9 and CA 72-4 levels in gastric and colorectal cancer patients. J Cancer. 2018 Jan 1;9(3):494-501. doi: 10.7150/jca.21562. eCollection 2018.
Reference Type
BACKGROUND
Zhao X, Bian F, Sun L, Cai L, Li L, Zhao Y. Microfluidic Generation of Nanomaterials for Biomedical Applications. Small. 2020 Mar;16(9):e1901943. doi: 10.1002/smll.201901943. Epub 2019 Jul 1.
Reference Type
BACKGROUND
Bigbee WL, Gopalakrishnan V, Weissfeld JL, Wilson DO, Dacic S, Lokshin AE, Siegfried JM. A multiplexed serum biomarker immunoassay panel discriminates clinical lung cancer patients from high-risk individuals found to be cancer-free by CT screening. J Thorac Oncol. 2012 Apr;7(4):698-708. doi: 10.1097/JTO.0b013e31824ab6b0.
Reference Type
BACKGROUND
Bando H, Yoshino T, Shinozaki E, Nishina T, Yamazaki K, Yamaguchi K, Yuki S, Kajiura S, Fujii S, Yamanaka T, Tsuchihara K, Ohtsu A. Simultaneous identification of 36 mutations in KRAS codons 61 and 146, BRAF, NRAS, and PIK3CA in a single reaction by multiplex assay kit. BMC Cancer. 2013 Sep 3;13:405. doi: 10.1186/1471-2407-13-405.
Reference Type
BACKGROUND
Hofmann JN, Yu K, Bagni RK, Lan Q, Rothman N, Purdue MP. Intra-individual variability over time in serum cytokine levels among participants in the prostate, lung, colorectal, and ovarian cancer screening Trial. Cytokine. 2011 Nov;56(2):145-8. doi: 10.1016/j.cyto.2011.06.012. Epub 2011 Jul 20.
Reference Type
BACKGROUND
Nitsch SM, Pries R, Wollenberg B. Head and neck cancer triggers increased IL-6 production of CD34+ stem cells from human cord blood. In Vivo. 2007 May-Jun;21(3):493-8.
Reference Type
BACKGROUND
Zhao Y, Zhao X, Pei X, Hu J, Zhao W, Chen B, Gu Z. Multiplex detection of tumor markers with photonic suspension array. Anal Chim Acta. 2009 Feb 2;633(1):103-8. doi: 10.1016/j.aca.2008.11.035. Epub 2008 Nov 25.
Reference Type
BACKGROUND
Pei X, Chen B, Li L, Gao F, Jiang Z. Multiplex tumor marker detection with new chemiluminescent immunoassay based on silica colloidal crystal beads. Analyst. 2010 Jan;135(1):177-81. doi: 10.1039/b912880h. Epub 2009 Nov 13.
Reference Type
BACKGROUND
Provided Documents
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Document Type: Informed Consent Form
Other Identifiers
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SAHoWMU-CR2021-02-404
Identifier Type: -
Identifier Source: org_study_id
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