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Liquid biopsy based on next-generation sequencing (NGS) method has become an increasingly powerful detection tool for clinical research and practice. As a companion diagnostic panel, circulating tumor DNA (ctDNA) assay has the considerable potential to detect the blood tumor mutation burden (bTMB), and bTMB calculated by ctDNA assay is regarded as a novel and promising biomarker for immunotherapy nowadays. Though immune checkpoint inhibitors (ICIs) in immunotherapy are highly effective but can induce severe immune-related adverse events (irAEs), which cannot be better predicted in advance. Meanwhile adoptive transfer of T cells transgenic for tumor-reactive T-cell receptors (TCR) is an attractive immunotherapeutic approach. However, clinical translation is so far limited due to challenges in the identification of suitable target antigens as well as TCRs that are concurrent safe and efficient. Definition of key characteristics relevant for effective and specific tumor rejection is essential to improve current TCR-based immunotherapy. This research is to characterize in-depth TCRs derived from HLA-mismatched allogeneic repertoire targeting different myeloperoxidase (MPO)-derived peptides presented by the same HLA-restriction element. Overall the purpose of this trial is to investigate the combined predictive biomarkers (including bTMB and HLA) related to the immunotherapy effects and the biomarker (TCR) associated with adverse reactions during immunotherapy and hold a predictive role, thus further benefit patients receiving immunotherapy, especially in the advanced stage lung cancer patients where tissue samples are unavailable.
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Blood samples including the plasma and PBMC (peripheral blood mononuclear cell) from immunotherapy-naive lung cancer patients will be analyzed by CGP panel (OrigiMed, Inc.) for multiple molecular biomarkers including mutations with sensitivity/resistance to targeted therapies, bTMB, HLA, etc. Treatment methods and outcomes will be followed-up to inspect the clinical benefit and safety with CGP-panel analysis.
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Xiaomin Niu
Data sourced from clinicaltrials.gov
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