Background: Tumor-associated antigens and neoantigens play a critical role in eliciting antitumor immune responses, leading to a significant amplification of tumor-specific T cell clones. Consequently, the detection of tumor-associated immune signaling in peripheral blood is expected as a promising strategy for cancer screening. Notably, due to the amplification effect of the immune response, the identification of tumor-related immune signals demonstrates higher abundance compared to the direct detection of tumor-derived molecules, such as circulating tumor DNA (ctDNA). This increased abundance allows for the extension of the screening time window, underscoring its potential for early cancer detection. The present study aims to identify lung cancer-associated T cell receptor (TCR) signatures, and develops a predictive model for to recognize lung cancer based on TCR repertoire sequencing.