An Immunogram for the Cancer-Immunity Cycle: Towards Personalized Immunotherapy of Lung Cancer.

ABSTRACT

INTRODUCTION: The interaction of immune cells and cancer cells shapes the immunosuppressive tumor microenvironment. For successful cancer immunotherapy, comprehensive knowledge of antitumor immunity as a dynamic spatiotemporal process is required for each individual patient. To this end, we developed an immunogram for the cancer-immunity cycle by using next-generation sequencing. METHODS: Whole exome sequencing and RNA sequencing were performed in 20 patients with NSCLC (12 with adenocarcinoma, seven with squamous cell carcinoma, and one with large cell neuroendocrine carcinoma). Mutated neoantigens and cancer germline antigens expressed in the tumor were assessed for predicted binding to patients' human leukocyte antigen molecules. The expression of genes related to cancer immunity was assessed and normalized to construct a radar chart composed of eight axes reflecting seven steps in the cancer-immunity cycle. RESULTS: Three immunogram patterns were observed in patients with lung cancer T-cell-rich, T-cell-poor, and intermediate. The T-cell-rich pattern was characterized by gene signatures of abundant T cells, regulatory T cells, myeloid-derived suppressor cells, checkpoint molecules, and immune-inhibitory molecules in the tumor, suggesting the presence of antitumor immunity dampened by an immunosuppressive microenvironment. The T-cell-poor phenotype reflected lack of antitumor immunity, inadequate dendritic cell activation, and insufficient antigen presentation in the tumor. Immunograms for both the patients with adenocarcinoma and the patients with nonadenocarcinoma tumors included both T-cell-rich and T-cell-poor phenotypes, suggesting that histologic type does not necessarily reflect the cancer immunity status of the tumor. CONCLUSIONS: The patient-specific landscape of the tumor microenvironment can be appreciated by using immunograms as integrated biomarkers, which may thus become a valuable resource for optimal personalized immunotherapy.