Ignite Creation Date:
2025-12-25 @ 1:44 AM
Ignite Modification Date:
2025-12-26 @ 12:01 AM
Study NCT ID:
NCT05498194
Status:
UNKNOWN
Last Update Posted:
2022-08-11
First Post:
2022-08-09
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Computational Prediction and Experimental Validation of Gastric Cancer Associated Neoantigens
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D013274', 'term': 'Stomach Neoplasms'}], 'ancestors': [{'id': 'D005770', 'term': 'Gastrointestinal Neoplasms'}, {'id': 'D004067', 'term': 'Digestive System Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D004066', 'term': 'Digestive System Diseases'}, {'id': 'D005767', 'term': 'Gastrointestinal Diseases'}, {'id': 'D013272', 'term': 'Stomach Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 50}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2022-08-15', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2022-08', 'completionDateStruct': {'date': '2023-12-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2022-08-09', 'studyFirstSubmitDate': '2022-08-09', 'studyFirstSubmitQcDate': '2022-08-09', 'lastUpdatePostDateStruct': {'date': '2022-08-11', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2022-08-11', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2023-12-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'The neoantigen landscape of patients with gastric cancer', 'timeFrame': '3 months from the beginning of the study', 'description': 'The analysis of tumor DNA and RNA sequencing data will provide the mutational distribution of patients with gastric cancer, which could give rise to neoantigens. Of those, neoantigens derived from hotspot mutations in Vietnamese gastric cancer patients will be identified.'}], 'secondaryOutcomes': [{'measure': 'The ratio of predicted neoantigens being presented by HLA-I', 'timeFrame': '6 months from the beginning of the study', 'description': 'Computational pipelines will be employed to predict the pairing of neoantigens and HLA molecules. Subsequently, the ratio of those predicted neoantigens will be validated by co-immunoprecipitation with anti-HLA antibodies and mass spectrometry analysis for their binding to corresponding HLA molecules.'}, {'measure': 'The ratio of predicted neoantigens being immunogenic.', 'timeFrame': '12 months from the beginning of the study', 'description': 'Immunoassays will be employed to identify neoantigens that could activate CD4 and CD8 T cells to kill tumor cells and serve as putative candidates for immunotherapy.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Gastric Cancer', 'Neoantigens']}, 'descriptionModule': {'briefSummary': 'This study is to develop methods for identification of neoantigens from patients with gastric cancer.', 'detailedDescription': 'Gastric cancer (GC) is the fourth most common cancer type and one of the leading causes of cancer-related death in Vietnam. Immunotherapy using checkpoint inhibitors (CPI) in combination with certain types of chemotherapy has been clinically shown to offer survival benefits for patients diagnosed with advanced stomach cancer. However, clinical outcomes of CPI are associated with the quantity as well as the quality of neoantigens which arise due to mutations in coding regions of cancer associated genes. Such neoantigens can be presentable by cancer cells to the host adaptive immune system and activate antitumor responses. Hence, the identification of neoantigens would be of significance for immunotherapeutic approaches. Recent data published by the Tumor Neoantigen Selection Alliance (TESLA) indicate that a large proportion (98%) of predicted neoantigens are not immunogenic and ineffective in activating anti-tumor responses. In the present study, we aim to develop a comprehensive pipeline incorporating both computational prediction tools and experimental validation assays to enhance the accuracy of neoantigen identification.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT'], 'maximumAge': '18 Years', 'minimumAge': '15 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'All the patients who were diagnosed with adavanced gastric cancer and underwent surgical resection', 'eligibilityCriteria': 'Inclusion Criteria:\n\n1. Male or Female patients aged 15 years and older\n2. Diagnosed with advanced gastric cancer (T2-4b/N0-3/M0-1 stage, according to the eighth edition of the American Joint Committee on Cancer TNM (AJCC TNM) system)\n3. Treatment-Naive\n4. Not known for other concomitant cancers\n5. Provide written informed consent\n\nExclusion Criteria:\n\n1. Insufficient tumor tissues (less than 1 cm3)\n2. Unable to sign informed consent\n3. Underwent treatment'}, 'identificationModule': {'nctId': 'NCT05498194', 'briefTitle': 'Computational Prediction and Experimental Validation of Gastric Cancer Associated Neoantigens', 'organization': {'class': 'OTHER', 'fullName': 'University Medical Center Ho Chi Minh City (UMC)'}, 'officialTitle': 'Computational Prediction and Experimental Validation of Gastric Cancer Associated Neoantigens', 'orgStudyIdInfo': {'id': '62/GCN-HDDD'}}, 'armsInterventionsModule': {'interventions': [{'name': 'ratio of predicted neoantigens', 'type': 'DIAGNOSTIC_TEST', 'description': '10 ml of whole blood is collected from each patient prior surgery Fresh tumor tissue samples (\\~ 1cm3 ) are collected during surgery'}]}, 'contactsLocationsModule': {'locations': [{'zip': '700000', 'city': 'Ho Chi Minh City', 'country': 'Vietnam', 'facility': 'University Medical Center Ho Chi Minh City', 'geoPoint': {'lat': 10.82302, 'lon': 106.62965}}], 'centralContacts': [{'name': 'Long Vo Duy', 'role': 'CONTACT', 'email': 'long.vd@umc.edu.vn', 'phone': '+84.918133915'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University Medical Center Ho Chi Minh City (UMC)', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}