CELL INTELLIGENCE · 肿瘤细胞治疗研究

INTRODUCTION: 1.1Lung cancer remains the leading cause of cancer-related deaths, with most patients presenting with advanced, treatment-resistant disease. While immunotherapy has improved outcomes for some, most patients fail to mount an effective immune response due to inadequate tumor recognition. Neoantigen-based therapies offer a promising approach to personalized immunotherapy, but current discovery methods can miss immunogenic targets, particularly those with low or heterogeneous expression. To address this, we developed the ImmuniT platform, which enhances neoantigen identification by amplifying patient-specific targets from primary tumor samples, improving prediction accuracy for more precise immunotherapy. METHODS: 1.2Patients with lung cancer were recruited under an IRB-approved protocol, and freshly resected tumor tissue and matched blood samples were collected. Tumors were processed into single-cell suspensions, enriched for EpCAM+ epithelial cells, and treated to enhance neoantigen expression. Peripheral blood and tumor-infiltrating lymphocytes were co-cultured with cancer cells to expand neoantigen-reactive T cells. The nextneopi pipeline integrated tumor mutational burden (TMB), HLA typing, and transcriptomic data to predict immunogenic targets. MHC:epitope complexes were validated via tetramer staining to identify patient-derived, neoantigen-specific T cells. RESULTS: 1.3The ImmuniT platform demonstrated superior neoantigen prediction and T cell activation in vitro compared to conventional methods across five NSCLC patients. In one patient, it identified two neoantigens missed by standard approaches, which were validated based on their ability to stimulate tumor-infiltrating and peripheral blood lymphocytes. Across all tested samples, the platform identified a broader spectrum of immunogenic targets. These findings highlight its potential to enhance neoantigen discovery and improve personalized immunotherapy strategies. CONCLUSION: 1.4Our findings indicate that the ImmuniT platform improves neoantigen detection in NSCLC by identifying a wider range of tumor-specific antigens, including those overlooked by conventional methods. By expanding the pool of targetable neoantigens, this technology has the potential to enhance T cell activation and optimize immunotherapy. The ImmuniT platform represents a promising advancement towards more effective, personalized treatment strategies for lung cancer patients, particularly those who do not respond to current immunotherapies.