Genomic Analysis to Identify a Predictive Biomarker for Immunotherapy
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Lung Cancer
- Sponsor
- Se-Hoon Lee
- Enrollment
- 800
- Locations
- 3
- Primary Endpoint
- List of biomarkers
- Status
- Recruiting
- Last Updated
- last year
Overview
Brief Summary
This study is designed to identify the predictive biomarker for immunotherapy using patient samples (tumor tissue, blood, fecal material) who treated with immune checkpoint inhibitor.
Detailed Description
\[Sample acquisition\] * Informed consent is waived for those who agree to donate samples left over from other clinical trials or acquired for other purposes to be used for other research by the sign to master agreement in advance. * The study will be conducted based on the purposes indicated in the master agreement signed by tissue donator \[Clinical data acquisition\] * Baseline demographics: Sex, Birth date, expire date (last follow-up date for the survivals) * Lung cancer treatment history: diagnosed date, treatment history (surgery, radiation therapy, chemotherapy, immunotherapy treatment history, and responses), general performance, metastatic sites * Lung cancer histologic information: pathology, histologic subtype, EGFR mutation profile, ALK-rearrangement result
Investigators
Se-Hoon Lee
Professor
Samsung Medical Center
Eligibility Criteria
Inclusion Criteria
- •aged above or equal to 18
- •Histologically confirmed lung cancer patients
- •Patient treated with immune checkpoint inhibitor
- •Exculsion Criteria:
Exclusion Criteria
- Not provided
Outcomes
Primary Outcomes
List of biomarkers
Time Frame: Baseline
Neoantigen, tumor mutation burden, MHC compatibility, T-cell receptor and associated immune gene signature (IFN-r, interferons such as IL-2 and interleukin family), T-cell subset (T cell surface marker such as CD4+, CD7+, CD8+, CD16, CD34+, CD38+, CD56+, etc.), PD-1/PD-L1 expression, etc.