Identification of tumour immune infiltration-associated snoRNAs (TIIsno) for predicting prognosis and immune landscape in patients with colon cancer via a TIIsno score model

BACKGROUND: Colon cancer (CC) is the leading cause of tumour-related death worldwide. SnoRNA plays a critical role in the tumour microenvironment. The tumour microenvironment can be shaped by tumour-infiltrating immune cells, which control the destiny of immunotherapy efficacy. This study uniquely focused on snoRNAs derived from immune cells to identify new biomarkers for immune landscape. METHODS: A novel computational framework was initiated for identifying tumour immune infiltration-associated snoRNAs (TIIsno) signatures and developed a TIIsno score model from integrative snoRNA profiling analysis of 21 purified immune cell lines, 43 colon cancer cell lines, and three datasets (training, test, real-world validation set). FINDINGS: Our study found that a high TIIsno score was associated with poor CC prognosis. TIIsno scores were seen to be negatively correlated with (I) the infiltration level of most immune cells, (II) the inhibitory immune checkpoints expression level, and (III) the immune score. These findings, taken together with the observation that TIIsno score is lower in MSI-H patients, suggests that patients with a low TIIsno score may have a better response to immunotherapy. INTERPRETATION: In conclusion, we successfully identified TIIsno and constructed a TIIsno score model, a new potential biomarker of immunotherapy response, which can effectively predict the prognosis of CC patients as well. FUNDING: National Key R & D Program of China, National Natural Science Foundation of China, key projects from the Nature Science Foundation of Hunan Province, projects from Beijing CSCO Clinical Oncology Research Foundation, Fundamental Research Funds for the Central Universities of Central South University.