Splicing-based Predictive Learning for Individual Chemotherapy Evaluation in Colorectal Cancer
Splicing-Based Predictive Learning for Individual Chemotherapy Evaluation in Colorectal Cancer (SPLICE)
City of Hope Medical Center
200 participants
Jun 21, 2024
OBSERVATIONAL
Conditions
Summary
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. This study aims to develop a machine learning-based predictive model for adjuvant chemotherapy response using tumor-derived alternative splicing signatures. By integrating RNA-seq data, splicing isoform and clinical outcomes, this study seeks to identify molecular predictors of treatment response and recurrence risk after surgery.
Eligibility
Plain Language Summary
Simplified for easier understanding
This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.
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Interventions
A panel of RNA splicing isoform, whose level is tested in tissue samples derived from the primary tumor.
Locations(1)
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NCT07226115