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

City of Hope

Status: Enrolling

Conditions: Colorectal Cancer Stage III; Colorectal Cancer Recurrent; Colorectal Cancer Stage II; Colorectal Cancer

Treatments: Other: SPLICE

Study type: Observational

Funder types: Other

Identifiers

NCT07226115

23228/SPLICE

Details and patient eligibility

About

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.

Full description

Colorectal cancer (CRC) remains a major global health burden, with adjuvant chemotherapy representing the standard of care after curative resection. However, patient responses to therapy vary widely, and no validated molecular model currently guides adjuvant treatment selection.

Recent studies suggest that aberrant alternative splicing-rather than gene-level expression alone-plays a crucial role in shaping chemotherapy sensitivity and tumor recurrence. Yet, these complex transcriptomic variations are often missed by standard differential expression analyses.

The ASPAIRE framework (Alternative Splicing and Predictive mAchIne learnIng for Response Evaluation) applies advanced computational modeling to capture multidimensional splicing features from RNA-seq data and transform them into clinically actionable predictions.

In this research effort, the investigators will leverage machine learning to predict adjuvant chemotherapy response for CRC. The research plan will employ three phases:

1. Identification of alternative splicing patterns associated with adjuvant chemotherapy response through RNA sequencing and computational feature extraction.
2. The investigators will then develop an assay based on reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and train a machine-learning model to predict chemotherapy response.
3. The investigators will independently validate the assay. This assay is provisionally termed " SPLICE " (Splicing-based Predictive Learning for Individual Chemotherapy Evaluation in Colorectal Cancer) and will be tested for disease free survival up to five years after treatment.

At the end of this study, this assay will have been developed and validated to help clinical decision-making by predicting both disease free survival.

Enrollment: 200 estimated patients

Sex: All

Ages: 18 to 80 years old

Volunteers: No Healthy Volunteers

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

Trial design

200 participants in 4 patient groups

Non-responders of colorectal cancer (Training Cohort)

Description:

Non-responders of colorectal cancer who developed recurrent CRC within 60 months from primary tumor treatment, in the first cohort

Treatment:

Other: SPLICE

Responders of colorectal cancer (Training Cohort)

Description:

Responders of colorectal cancer who did not develop recurrent CRC within 60 months from primary tumor treatment, in the first cohort

Treatment:

Other: SPLICE

Non-responders of colorectal cancer, with recurrent disease (Validation Cohort)

Description:

Non-responders of colorectal cancer who developed recurrent CRC within 60 months from primary tumor treatment, in the second, independent, validation cohort

Treatment:

Other: SPLICE

Responders of colorectal cancer (Validation Cohort)

Description:

Responders of colorectal cancer who did not develop recurrent CRC within 60 months from primary tumor treatment, in the second, independent, validation cohort

Treatment:

Other: SPLICE