Ignite Creation Date:
2025-12-24 @ 4:48 PM
Ignite Modification Date:
2025-12-29 @ 5:03 AM
Study NCT ID:
NCT07224750
Status:
RECRUITING
Last Update Posted:
2025-11-26
First Post:
2025-11-03
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
A Noninvasive and Screening miRNA Signature for Gastrointestinal Cancer
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D006528', 'term': 'Carcinoma, Hepatocellular'}, {'id': 'D018281', 'term': 'Cholangiocarcinoma'}, {'id': 'D000077277', 'term': 'Esophageal Squamous Cell Carcinoma'}, {'id': 'D013274', 'term': 'Stomach Neoplasms'}, {'id': 'D005770', 'term': 'Gastrointestinal Neoplasms'}], 'ancestors': [{'id': 'D000230', 'term': 'Adenocarcinoma'}, {'id': 'D002277', 'term': 'Carcinoma'}, {'id': 'D009375', 'term': 'Neoplasms, Glandular and Epithelial'}, {'id': 'D009370', 'term': 'Neoplasms by Histologic Type'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D008113', 'term': 'Liver Neoplasms'}, {'id': 'D004067', 'term': 'Digestive System Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D004066', 'term': 'Digestive System Diseases'}, {'id': 'D008107', 'term': 'Liver Diseases'}, {'id': 'D002294', 'term': 'Carcinoma, Squamous Cell'}, {'id': 'D018307', 'term': 'Neoplasms, Squamous Cell'}, {'id': 'D004938', 'term': 'Esophageal Neoplasms'}, {'id': 'D006258', 'term': 'Head and Neck Neoplasms'}, {'id': 'D004935', 'term': 'Esophageal Diseases'}, {'id': 'D005767', 'term': 'Gastrointestinal Diseases'}, {'id': 'D013272', 'term': 'Stomach Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 1000}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2024-06-21', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-11', 'completionDateStruct': {'date': '2026-06-18', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-11-24', 'studyFirstSubmitDate': '2025-11-03', 'studyFirstSubmitQcDate': '2025-11-03', 'lastUpdatePostDateStruct': {'date': '2025-11-26', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2025-11-05', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2026-06-18', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Diagnostic Accuracy of miRNA Panel', 'timeFrame': 'At baseline (pre-treatment blood sample).', 'description': 'Sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) for distinguishing GI cancer patients from non-cancer controls.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Noninvasive screening', 'Circulating miRNA', 'Machine learning', 'Gastrointestinal cancer', 'Blood-based cancer detection'], 'conditions': ['Hepatocellular Carcinoma (HCC)', 'Cholangiocarcinoma', 'Pancreatic Ductal Adenocarcinoma (PDAC)', 'Esophageal Squamous Cell Carcinoma (ESCC)', 'Gastric Cancer (GC)', 'Colorectal Cancer Screening']}, 'referencesModule': {'references': [{'pmid': '39636625', 'type': 'BACKGROUND', 'citation': 'Goddard KAB, Feuer EJ, Mandelblatt JS, Meza R, Holford TR, Jeon J, Lansdorp-Vogelaar I, Gulati R, Stout NK, Howlader N, Knudsen AB, Miller D, Caswell-Jin JL, Schechter CB, Etzioni R, Trentham-Dietz A, Kurian AW, Plevritis SK, Hampton JM, Stein S, Sun LP, Umar A, Castle PE. Estimation of Cancer Deaths Averted From Prevention, Screening, and Treatment Efforts, 1975-2020. JAMA Oncol. 2025 Feb 1;11(2):162-167. doi: 10.1001/jamaoncol.2024.5381.'}, {'pmid': '38572751', 'type': 'BACKGROUND', 'citation': 'Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, Jemal A. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024 May-Jun;74(3):229-263. doi: 10.3322/caac.21834. Epub 2024 Apr 4.'}]}, 'descriptionModule': {'briefSummary': 'Gastrointestinal (GI) cancers remain a major global health burden, largely due to the lack of effective and accessible early screening strategies. Current diagnostic approaches-including endoscopy, computed tomography (CT), and magnetic resonance imaging (MRI)-are either invasive, resource-intensive, or insufficiently sensitive for detecting early-stage disease, and are therefore not suitable for population-wide screening or for simultaneously identifying multiple GI tumor types. As a result, many patients are diagnosed at advanced stages, when therapeutic options are limited and prognosis is poor.\n\nCirculating microRNAs (miRNAs) offer a promising alternative, as they are stable in peripheral blood and reflect tumor-related molecular alterations. In this study, the investigators aim to develop and validate a robust, noninvasive miRNA-based signature capable of distinguishing GI cancers from non-malignant controls. By integrating multi-cohort datasets and applying machine learning-based feature selection and predictive modeling, the investigators will construct a screening panel optimized for reproducibility, scalability, and early-stage detection. This noninvasive miRNA signature has the potential to support accessible, cost-effective, and clinically practical population-level screening for GI cancers, ultimately facilitating earlier diagnosis and improving outcomes for participants.', 'detailedDescription': "This study will establish a comprehensive, retrospective, international multi-center cohort consisting of peripheral blood samples from participants with major gastrointestinal cancers-including hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA), pancreatic ductal adenocarcinoma (PDAC), esophageal squamous cell carcinoma (ESCC), gastric cancer (GC), and colorectal cancer (CRC)-as well as non-malignant controls. Small RNA sequencing will be performed to generate high-resolution circulating miRNA expression profiles.\n\nDuring the discovery phase, the investigators will conduct rigorous preprocessing, normalization, batch effect correction, and differential expression analyses to identify circulating miRNAs associated with malignant transformation across GI cancer types. Machine learning-based feature selection (e.g., LASSO, mRMR, ensemble methods) and classifier development (e.g., SVM, Random Forest, XGBoost) will then be used to derive a minimal yet robust miRNA panel capable of optimally distinguishing cancer from non-cancer.\n\nDuring the modeling and evaluation phase, the identified miRNA signature will undergo multi-center training and validation across international cohorts to ensure robustness across geographic regions, sequencing platforms, and clinical demographics. Beyond binary classification, the investigators will assess the panel's ability to discriminate among specific GI cancer subtypes, thereby supporting differential diagnosis and tumor-origin inference. Model performance will be evaluated using AUROC, sensitivity at clinically meaningful specificity thresholds, early-stage detection capability, and calibration in independent validation cohorts.\n\nThrough this sequential discovery → modeling → multi-center validation framework, the investigators aim to develop a noninvasive circulating miRNA panel that (1) accurately distinguishes cancer from non-cancer individuals and (2) differentiates among multiple gastrointestinal cancer types, thereby providing a clinically scalable solution for early cancer detection and population-level screening."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Adult participants (≥18 years) from international multi-center cohorts, including patients with GI cancers (HCC, CCA, PDAC, ESCC, GC, CRC) and non-cancer controls. Blood samples and de-identified clinical data are available for discovery, training, and validation of a circulating miRNA biomarker panel.', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n1. Adults aged 18 years or older at the time of blood sample collection.\n2. Patients with a confirmed diagnosis of one of the following gastrointestinal cancers: Hepatocellular carcinoma (HCC), Cholangiocarcinoma (CCA), Pancreatic ductal adenocarcinoma (PDAC), Esophageal squamous cell carcinoma (ESCC), Gastric cancer (GC), Colorectal cancer (CRC), Non-cancer control participants, including healthy volunteers or patients with benign gastrointestinal conditions.\n3. Availability of retrospective blood samples collected according to institutional protocols.\n4. Willingness to allow use of de-identified clinical and demographic data for research purposes.\n\nExclusion Criteria:\n\n* other active malignancies; insufficient sample quality/volume; recent chemotherapy/radiotherapy/surgery; any condition preventing reliable participation.'}, 'identificationModule': {'nctId': 'NCT07224750', 'acronym': 'MiGIC', 'briefTitle': 'A Noninvasive and Screening miRNA Signature for Gastrointestinal Cancer', 'organization': {'class': 'OTHER', 'fullName': 'City of Hope Medical Center'}, 'officialTitle': 'A Noninvasive and Screening miRNA Signature for Gastrointestinal Cancer', 'orgStudyIdInfo': {'id': '23228/MiGIC'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Hepatocellular Carcinoma cohort', 'description': 'Patients diagnosed with hepatocellular carcinoma (HCC) confirmed by clinical, imaging, and/or histopathological criteria. Blood samples collected retrospectively from multiple international centers.'}, {'label': 'Cholangiocarcinoma cohort', 'description': 'Patients diagnosed with cholangiocarcinoma (CCA), including intrahepatic and extrahepatic subtypes, confirmed clinically and/or histopathologically. Blood samples collected retrospectively from multiple international centers.'}, {'label': 'Pancreatic Ductal Adenocarcinoma cohort', 'description': 'Patients diagnosed with pancreatic ductal adenocarcinoma (PDAC), confirmed by standard diagnostic criteria. Samples collected from multiple international centers.'}, {'label': 'Esophageal Squamous Cell Carcinoma cohort', 'description': 'Patients diagnosed with esophageal squamous cell carcinoma (ESCC). Blood samples collected retrospectively from international collaborating centers.'}, {'label': 'Gastric Cancer cohort', 'description': 'Patients diagnosed with gastric cancer (GC), confirmed clinically and/or histopathologically. Samples collected from multiple international centers.'}, {'label': 'Colorectal Cancer cohort', 'description': 'Patients diagnosed with colorectal cancer (CRC), confirmed by standard diagnostic methods. Blood samples collected retrospectively from multiple international centers.'}, {'label': 'Non-cancer / Healthy control group', 'description': 'Non-cancer individuals, including healthy volunteers and patients with benign gastrointestinal conditions. Blood samples collected from international centers and matched for age and sex where possible.'}]}, 'contactsLocationsModule': {'locations': [{'zip': '91010', 'city': 'Duarte', 'state': 'California', 'status': 'RECRUITING', 'country': 'United States', 'contacts': [{'name': 'Ajay Goel, PhD', 'role': 'CONTACT', 'email': 'ajgoel@coh.org', 'phone': '626-359-8111'}], 'facility': 'City of Hope Nat Medical Ctr', 'geoPoint': {'lat': 34.13945, 'lon': -117.97729}}], 'centralContacts': [{'name': 'Junyong Weng, PhD', 'role': 'CONTACT', 'email': 'juweng@coh.org', 'phone': '06263151444'}], 'overallOfficials': [{'name': 'Ajay Goel, PhD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'City of Hope Medical Center'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'City of Hope Medical Center', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}