Splicing-based Predictive Learning for Individual Chemotherapy Evaluation in Colorectal Cancer

Recruiting now

Conditions studied: Colorectal Cancer, Colorectal Cancer Recurrent, Colorectal Cancer Stage II, Colorectal Cancer Stage III

In brief

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.

Key facts

Study ID

NCT07226115

Run by

City of Hope Medical Center

People needed

200

Starts

2024-06-21

Expected to finish

2028-06-18

Last updated by the study team

2026-07-07

Who can join

Age: 18 and older, up to 80. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• Histologically confirmed stage II-III colorectal cancer (TNM classification, 8th edition)
• Received standard adjuvant chemotherapy after curative resection
• Availability of tumor tissue (FFPE or frozen) before chemotherapy
• Sufficient clinical data for outcome analysis (recurrence, survival)
• Age 18-80 years Stage

You may not qualify if…

• Inflammatory bowel disease
• Inadequate RNA quality or lack of consent

Where it is running

• City of Hope Medical Center — Duarte, California, United States (enrolling)

Full record on ClinicalTrials.gov

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