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Updated: Jun 26, 2025
Enrichment and Characterization of the Tumor Immune and Non-immune Microenvironments in Established Subcutaneous Murine Tumors
Published on: June 7, 2018
Colorectal cancer subtyping and immune landscape analysis based on natural killer cell-related genes
Mei Ding1, Jianchao Gao2, Jinyan Wang2
1Surgical Research Division, Tangshan Vocational & Technical College, Tangshan, Hebei 063000, China; Department of Laparoscopy and Colorectal Surgery, Tangshan Central Hospital, Tangshan, Hebei 063000, China.
Background And Study Aims:
The prognosis of colorectal cancer (CRC) is related to natural killer (NK) cells, but the molecular subtype features of CRC based on NK cells are still unknown. This study aimed to identify NK cell-related molecular subtypes of CRC and analyze the survival status and immune landscape of patients with different subtypes.
Patients/Material And Methods:
mRNA expression data, single nucleotide variant (SNV) data, and clinical information of CRC patients were obtained from The Cancer Genome Atlas. Differentially expressed genes (DEGs) were obtained through differential analysis, and the intersection was taken with NK cell-associated genes to obtain 103 NK cell-associated CRC DEGs (NCDEGs). Based on NCDEGs, CRC samples were divided into three clusters through unsupervised clustering analysis. Survival analysis, immune analysis, Gene Set Enrichment Analysis (GSEA), and tumor mutation burden (TMB) analysis were performed. Finally, NCDEG-related small-molecule drugs were screened using the CMap database.
Results:
Survival analysis revealed that cluster2 had a lower survival rate than cluster1 and cluster3 (p < 0.05). Immune infiltration analysis found that the immune infiltration levels and immune checkpoint expression levels of cluster1_3 were substantially higher than those of cluster2, and the tumor purity was the opposite (p < 0.05). GSEA presented that cluster1_3 was significantly enriched in the chemokine signaling pathway, ECM receptor interaction, and antigen processing and presentation pathways (p < 0.05). The TMB of cluster1_3 was significantly higher than that of cluster2 (p < 0.05). Genes with the highest mutation rate in CRC were APC, TP53, TTN, and KRAS. Drug prediction results showed that small-molecule drugs that reverse the upregulation of NCDEGs, deoxycholic acid, dipivefrine, phenformin, and other drugs may improve the prognosis of CRC.
Conclusion:
NK cell-associated CRC subtypes can be used to evaluate the tumor characteristics of CRC patients and provide an important reference for CRC patients.
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