[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100610325":3},{"organization":4,"armGroups":7,"interventions":26,"overallOfficials":31,"centralContacts":35,"locations":40,"responsibleParty":56,"collaborators":10,"id":58,"slug":59,"hasResults":60,"nctId":61,"briefTitle":62,"officialTitle":63,"acronym":28,"eligibilityCriteria":64,"healthyVolunteers":60,"sex":65,"minAge":66,"maxAge":67,"enrollmentInfo":68,"targetDuration":10,"studyType":71,"phases":10,"briefSummary":72,"conditions":73,"keywords":78,"overallStatus":42,"whyStopped":10,"lastUpdateSubmitDate":84,"lastUpdatePostDateStruct":85,"startDateStruct":88,"completionDateStruct":90,"leadSponsor":92,"locationsCount":93},{"fullName":5,"class":6},"City of Hope Medical Center","OTHER",[8,14,18,22],{"label":9,"type":10,"description":11,"interventionNames":12},"Non-responders of colorectal cancer (Training Cohort)",null,"Non-responders of colorectal cancer who developed recurrent CRC within 60 months from primary tumor treatment, in the first cohort",[13],"Other: SPLICE",{"label":15,"type":10,"description":16,"interventionNames":17},"Responders of colorectal cancer (Training Cohort)","Responders of colorectal cancer who did not develop recurrent CRC within 60 months from primary tumor treatment, in the first cohort",[13],{"label":19,"type":10,"description":20,"interventionNames":21},"Non-responders of colorectal cancer, with recurrent disease (Validation Cohort)","Non-responders of colorectal cancer who developed recurrent CRC within 60 months from primary tumor treatment, in the second, independent, validation cohort",[13],{"label":23,"type":10,"description":24,"interventionNames":25},"Responders of colorectal cancer (Validation Cohort)","Responders of colorectal cancer who did not develop recurrent CRC within 60 months from primary tumor treatment, in the second, independent, validation cohort",[13],[27],{"type":6,"name":28,"description":29,"armGroupLabels":30,"otherNames":10},"SPLICE","A panel of RNA splicing isoform, whose level is tested in tissue samples derived from the primary tumor.",[9,19,15,23],[32],{"name":33,"affiliation":5,"role":34},"Ajay Goel, PhD","PRINCIPAL_INVESTIGATOR",[36],{"name":33,"role":37,"phone":38,"phoneExt":10,"email":39},"CONTACT","626-218-3452","AJGOEL@COH.ORG",[41],{"facility":5,"status":42,"city":43,"state":44,"zip":45,"country":46,"countryCode":47,"cosmosGeoPoint":48,"geoPoint":53,"contacts":54},"RECRUITING","Duarte","California","91010","United States","US",{"type":49,"coordinates":50},"Point",[51,52],-117.97729,34.13945,{"lat":52,"lon":51},[55],{"name":33,"role":37,"phone":38,"phoneExt":10,"email":39},{"type":57,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR","100610325","splicing-based-predictive-learning-for-individual-chemotherapy-evaluation-in-colorectal-cancer-100610325",false,"NCT07226115","Splicing-based Predictive Learning for Individual Chemotherapy Evaluation in Colorectal Cancer","Splicing-Based Predictive Learning for Individual Chemotherapy Evaluation in Colorectal Cancer (SPLICE)","Inclusion Criteria:\n\n* Histologically confirmed stage II-III colorectal cancer (TNM classification, 8th edition)\n* Received standard adjuvant chemotherapy after curative resection\n* Availability of tumor tissue (FFPE or frozen) before chemotherapy\n* Sufficient clinical data for outcome analysis (recurrence, survival)\n* Age 18-80 years Stage\n\nExclusion Criteria:\n\n* Inflammatory bowel disease\n* Inadequate RNA quality or lack of consent","ALL","18 Years","80 Years",{"count":69,"type":70},200,"ESTIMATED","OBSERVATIONAL","Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide. Although adjuvant chemotherapy improves survival after curative resection, its efficacy varies widely among patients. The absence of reliable predictive biomarkers often leads to overtreatment or undertreatment.\n\nThis study aims to develop a machine learning-based predictive model for adjuvant chemotherapy response using tumor-derived alternative splicing signatures.\n\nBy integrating RNA-seq data, splicing isoform and clinical outcomes, this study seeks to identify molecular predictors of treatment response and recurrence risk after surgery.",[74,75,76,77],"Colorectal Cancer","Colorectal Cancer Recurrent","Colorectal Cancer Stage II","Colorectal Cancer Stage III",[79,80,81,82,83],"Chemotherapy","Adjuvant","Response","Splicing","Prediction","2025-11-05",{"date":86,"type":87},"2025-11-10","ACTUAL",{"date":89,"type":87},"2024-06-21",{"date":91,"type":70},"2026-06-18",{"name":5,"class":6},1]