Status
Conditions
About
This is a prospective observational clinical study designed to predict the therapeutic efficacy of first-line treatment with tislelizumab combined with standard chemotherapy in patients with ES-SCLC using TCR repertoire technology. The study plans to enroll 40 treatment-naive patients with ES-SCLC.
Full description
The advancement of Next-Generation Sequencing (NGS) technology has facilitated the detection of T-cell immune repertoires across various solid tumor types, and a growing body of research indicates that T-cell immune repertoires hold potential as biomarkers for immunotherapy; in the field of non-small cell lung cancer (NSCLC), previous studies have suggested that the characteristics of the baseline T-cell receptor (TCR) repertoire and changes in the TCR repertoire before and after immunotherapy are associated with immunotherapeutic efficacy, while such exploration remains lacking in the field of small cell lung cancer (SCLC). Due to limitations in cost and experimental methods, the currently available TCR databases contain limited information, encompassing only a small fraction of antigen-TCR binding pairs, and furthermore, these binding pair data fail to cover all antigens that any given TCR might potentially bind to; to address this issue, the research community has explored the use of machine learning models to predict the antigen specificity of unknown and experimentally unvalidated TCRs, which has shown feasibility. This study, as a prospective observational clinical study designed to predict the therapeutic efficacy of first-line treatment with tislelizumab combined with standard chemotherapy in patients with extensive-stage small cell lung cancer (ES-SCLC) using TCR repertoire technology, plans to enroll 40 treatment-naive patients with ES-SCLC, and aims to predict the neoantigen-specific TCR repertoire by analyzing tumor neoantigens, integrating T-cell repertoire data and HLA class I detection information, and leveraging the Multimodal-AIR-BERT machine learning model, with the hypothesis that the parameters of this predicted TCR repertoire may exhibit a stronger correlation with immunotherapeutic efficacy.
Enrollment
Sex
Ages
Volunteers
Inclusion criteria
Exclusion criteria
Loading...
Central trial contact
Henan Province Cancer Hospital Ethics Committee Henan Province Cancer Hospital Ethics Committee
Data sourced from clinicaltrials.gov
Clinical trials
Research sites
Resources
Legal