LAUSR

AIMS Colorectal cancer (CRC) is one of the most common cancers with poor prognosis worldwide. The advent of immunotherapy has greatly improved survival in refractory patients of CRC. In this study, we aimed to identify reliable immune classification and biomarkers that predict immunotherapeutic responses in CRC patients. MATERIALS AND METHODS Based on transcriptome profiles of two publicly available CRC datasets, we performed single-sample gene set enrichment analysis (ssGSEA) to calculate the relative abundance of 29 immune-related items of each sample. Unsupervised clustering was used to classify CRC patients. Furthermore, an immune prognostic signature was constructed using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. KEY FINDINGS The CRC patients were clustered into high, medium, low immune infiltration subtypes based on the immune landscape. There was significant heterogeneity among the three subtypes. The high immune infiltration group showed higher expression of programmed cell death-ligand 1 and better prognosis than the median and low immune infiltration groups. Furthermore, we constructed a 7-immune-related prognostic gene signature and found that the signature had high predictive value and was superior to other clinicopathological parameters. Finally, the correlation analysis of the signature with immune cell infiltration and immune checkpoint molecules suggested that the signature had the potential to assess the immunotherapeutic responses of CRC patients. SIGNIFICANCE The immune landscape and prognostic signature of CRC contribute to a deeper understanding of the tumor microenvironment and guide accurate immunotherapy.