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NCT Number: NCT07587229

Alternative Splicing Based Prediction of Chemotherapy Response in Gastric Cancer

This study aims to develop a model to predict response to chemotherapy in gastric cancer using RNA splicing information from tumor tissue.

By analyzing genetic patterns and applying machine learning, the study seeks to identify patients who are less likely to benefit from treatment, helping guide clinical decision-making.

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Key information

Conditions

Gastric Cancer Digestive System Diseases Digestive System Neoplasms Gastrointestinal Diseases Gastrointestinal Neoplasms Neoplasms Neoplasms by Site Stomach Diseases Stomach Neoplasms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

City of Hope Medical Center

Duarte, California, 91016, United States

Location status: Recruiting

About this study

This multicenter observational study aims to develop and validate an alternative splicing (AS)-based model to predict response to 5-FU-based adjuvant chemotherapy in stage II/III gastric cancer.

AS events were identified using TCGA SpliceSeq and UCSC Xena data, and selected candidates were quantified by RT-qPCR.

A predictive model was constructed using Elastic Net-based feature selection and XGBoost, and evaluated in independent training and validation cohorts. An integrated model incorporating clinicopathological factors was also developed.

The primary endpoint is treatment response defined by 3-year recurrence-free survival. Patients with recurrence within 3 years are classified as non-responders, and those without recurrence as responders.

This study aims to establish a clinically applicable biomarker for risk stratification and treatment decision support.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Pathologically confirmed stage II or III gastric cancer
  • Underwent curative surgical resection
  • Received 5-FU-based adjuvant chemotherapy
  • Availability of tumor tissue samples for analysis

Exclusion criteria

  • History of other malignancies
  • Inadequate or poor-quality tissue samples (e.g., contamination)

Treatment and study plan

observational study (no intervention)

Other

This is an observational study without assigned interventions. All patients received standard-of-care 5-FU-based adjuvant chemotherapy, and no experimental intervention was performed.

Primary outcomes

  1. Treatment response based on 3-year recurrence-free survival

    Time frame: 3 years after surgery

    Treatment response was defined based on recurrence-free survival (RFS). Patients who developed recurrence within 3 years after curative surgery were classified as non-responders, whereas those without recurrence were classified as responders.

Secondary outcomes

  1. Diagnostic performance of the predictive model

    Time frame: At model evaluation

    Model performance was assessed using the area under the receiver operating characteristic curve, sensitivity, and specificity in the training and validation cohorts.

  2. Recurrence-free survival stratified by predefined model-derived risk score

    Time frame: Up to 5 years after surgery

    Recurrence-free survival will be evaluated according to the predefined model-derived risk score using Kaplan-Meier survival analysis and Cox proportional hazards models. Recurrence status within 3 years after surgery will be used to define treatment response.

Study contacts

Contact information is provided by the study sponsor or research team.

Ajay Goel

CONTACT

[email protected]

626-256-4673

Sponsors and collaborators

Lead sponsor

City of Hope Medical Center

Other

Registry information

Official study title

A Multicenter Observational Study to Develop and Validate an Alternative Splicing-Based Machine Learning Model for Predicting Response to 5-FU-Based Adjuvant Chemotherapy in Gastric Cancer (VERSA-GC Study)

Important dates

Study start
2026
Primary completion
2027
Study completion
2027
First posted
May 14, 2026
Registry last updated
May 14, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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