Identifying gastric cancer patients who may benefit from immunotherapy using tissue biomarkers.
Selecting Patients Who May Benefit From Immunotherapy by Tissue-based Biomarkers
This study is testing a new way to see if certain tissue markers can help doctors find out which gastric cancer patients might benefit from immunotherapy.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 300 (estimated) |
| Ages | 18 Years to 80 Years |
| Sex | All |
| Sponsor | Peking University Academic / other |
| Drugs / interventions | immunotherapy |
| Locations | 1 site (Beijing) |
| Trial ID | NCT05593419 on ClinicalTrials.gov |
What this trial studies
This observational study aims to validate a machine learning model that utilizes a tissue-based immune cell signature to predict which gastric cancer patients are likely to benefit from immunotherapy. The study will enroll 300 patients with unresectable recurrent or metastatic gastric adenocarcinoma to assess the accuracy of this predictive model. Participants must meet specific eligibility criteria, including having measurable disease and a certain performance status. The goal is to enhance patient selection for immunotherapy based on their individual biomarker profiles.
Who should consider this trial
Good fit: Ideal candidates are adults aged 18-80 with histologically confirmed unresectable recurrent or metastatic gastric adenocarcinoma.
Not a fit: Patients who have previously received systemic therapy for metastatic gastric cancer or have had recent surgery may not benefit from this study.
Why it matters
Potential benefit: If successful, this study could lead to more personalized and effective treatment options for gastric cancer patients receiving immunotherapy.
How similar studies have performed: Other studies have shown promise in using biomarker signatures to predict immunotherapy efficacy, suggesting this approach may be viable.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Having signed informed consent * Age:18-80 years old * Histologically confirmed gastric adenocarcinoma * Unresectable recurrent or metastatic gastric cancer * Previous neo-adjuvant or adjuvant treatment for gastric cancer, if applicable, more than 6 months * Measurable disease according to the RECIST criteria * Karnofsky performance status ≥70 * Life expectancy of ≥3 month * No prior radiotherapy except radiotherapy at non-target lesion of the study more than 4 weeks * ALT and AST\<2.5 times ULN (≤5 times ULN in patients with liver metastases) * Serum albumin level ≥3.0g/dL * Serum AKP \< 2.5 times ULN * Serum creatinine \<ULN, and CCr \< 60ml/min * Bilirubin level \< 1.5 ULN * WBC\>3,000/mm3, absolute neutrophil count ≥2000/mm3, platelet\>100,000/mm3, Hb\>9g/dl Exclusion Criteria: * Previous systemic therapy for metastatic gastric cancer * Surgery (excluding diagnostic biopsy) within 4 weeks prior to study entry Contraindications of nuclear magnetic resonance image such as fitment of cardiac pacemaker , nerve stimulator, or aneurysm clip, and metallic foreign body in eye ball and so on. * Allergic constitution or allergic history to protium biologic product or any investigating agents. * Severe heart disease or such history as recorded congestive heart failure, uncontrolled cardiac arrhythmia, angina pectoris needing medication, cardiac valve disease, severe abnormal ECG findings, cardiac infarction , or retractable hypertension. * Pregnancy or lactation period * Other previous malignancy within 5 year, except non-melanoma skin cancer * Legal incapacity
Where this trial is running
Beijing
- Peking University Cancer Hospital — Beijing, China (Recruiting)
Study contacts
- Study coordinator: Yang Chen, MD
- Email: yang_chen@bjcancer.org
- Phone: 010-88196090
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.