Ignite Creation Date:
2025-12-24 @ 5:31 PM
Ignite Modification Date:
2025-12-25 @ 3:04 PM
Study NCT ID:
NCT05498168
Status:
UNKNOWN
Last Update Posted:
2022-08-11
First Post:
2022-08-09
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Computational Prediction and Experimental Validation of Esophageal Cancer Associated Neoantigens
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D004938', 'term': 'Esophageal Neoplasms'}], 'ancestors': [{'id': 'D005770', 'term': 'Gastrointestinal Neoplasms'}, {'id': 'D004067', 'term': 'Digestive System Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D006258', 'term': 'Head and Neck Neoplasms'}, {'id': 'D004066', 'term': 'Digestive System Diseases'}, {'id': 'D004935', 'term': 'Esophageal Diseases'}, {'id': 'D005767', 'term': 'Gastrointestinal 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': '2022-09-01', '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 esophageal cancer', 'timeFrame': '3 months from the begining of study', 'description': 'The analysis of tumor DNA and RNA sequencing data will provide the mutational distribution of patients with esophageal cancer, which could give rise to neoantigens. Of those, neoantigens derived from hotspot mutations in Vietnamese esophageal cancer patients will be identified.'}, {'measure': 'The ratio of predicted neoantigens being presented by HLA-I', 'timeFrame': '6 months from the begining of 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 begining of 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': ['Esophageal Cancer', 'Neoantigen']}, 'descriptionModule': {'briefSummary': 'This study is to develop computational pipelines and experimental validation assays for improving the identification of neoantigens from patients with esophageal cancer.', 'detailedDescription': 'Esophageal cancer (EC) is the common malignant tumor with poor survival. The long-term surival rate of patients with advanced EC stages has not been improved with multidisciplinary treatments including surgery and chemotherapy and radiation. Recently, immunotherapy approaches using checkpoint inhibitors (CPI), cancer vaccine, and adoptive T cell therapy have improved survival outcomes of EC patients. The clinical outcomes are associated with expression levels as well as the immunogenicity of neoantigens which arise from soma mutations. Therefore, the identification of immunogenic neoantigens is essential for achieving effective therapies. Recent data published by the Tumor Neoantigen Selection Alliance (TESLA) show that the majority (98%) of predicted neoantigens are lack of immunogenicity and ineffective in activating antitumor immune responses. In our study, we aim to develop a pipeline with both computational prediction tools and experimental validation assays to enhance the accuracy of neoantigen identification.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT', 'OLDER_ADULT'], 'maximumAge': '90 Years', 'minimumAge': '15 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'All the patients who were diagnosed with adavanced esophageal cancer and underwent surgical resection', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n1. Male or Female patients aged 18 years and older\n2. Diagnosed with advanced esophageal cancer\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': 'NCT05498168', 'briefTitle': 'Computational Prediction and Experimental Validation of Esophageal Cancer Associated Neoantigens', 'organization': {'class': 'OTHER', 'fullName': 'University Medical Center Ho Chi Minh City (UMC)'}, 'officialTitle': 'Computational Prediction and Experimental Validation of Esophageal Cancer Associated Neoantigens', 'orgStudyIdInfo': {'id': '61/GCN-HDDD'}}, 'armsInterventionsModule': {'interventions': [{'name': 'ratio of predicted neoantigens', 'type': 'GENETIC', '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, PhD', 'role': 'CONTACT', 'email': 'long.vd@umc.edu.vn', 'phone': '+84.8.39525656'}, {'name': 'Thong Dang Quang', 'role': 'CONTACT', 'email': 'thong.dq@umc.edu.vn'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University Medical Center Ho Chi Minh City (UMC)', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}