Gastric Cancer
Conditions
Brief summary
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.
Detailed description
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.
Interventions
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.
Sponsors
City of Hope Medical Center
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
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)
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Treatment response based on 3-year recurrence-free survival | 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
| Measure | Time frame | Description |
|---|---|---|
| Diagnostic performance of the predictive model | 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. |
| Recurrence-free survival stratified by predefined model-derived risk score | 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. |
Countries
United States
Contacts
CONTACTAjay Goel
Outcome results
None listed