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

Splicing-Based Predictive Learning for Individual Chemotherapy Evaluation in Colorectal Cancer (SPLICE)

Who can join

Ages 18 to 80 · All sexes

Inclusion Criteria:

* 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

Exclusion Criteria:

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

About the study

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.

What is being tested

• SPLICE (other)

Sponsor: City of Hope Medical Center · Participants: 200 · Started: Jun 21, 2024

Contact the study team

• Ajay Goel, PhD · Phone: 626-218-3452

Official record on ClinicalTrials.gov — NCT07226115

Locations in the U.S.

Conditions

• Colorectal Cancer

From ClinicalTrials.gov, data retrieved Sep 30, 2026. Each study sets its own eligibility; the study team decides who can join.