Clinical relationships between the intratumoral microbiome and risk factors for head and neck cancer.

A bioinformatic analysis is a promising approach to understand the relationship between the vast tumor microbiome and cancer development. In the present study, we studied the relationships between the intratumoral microbiome and classical clinical risk factors using bioinformatics analysis of the Cancer Genome Atlas (TCGA) and the Cancer Microbiome Atlas (TCMA) datasets. We used TCMA database and investigated the abundance of microbes at the genus level in solid normal tissue (n = 22) and the primary tumors of patients with head and neck squamous cell carcinoma (HNSCC) (n = 154) and identified three major tumor microbiomes, , , and . The tissue level of was higher in primary tumors than in solid normal tissue. However, univariate and multivariate analyses of these 3 microbes showed no significant effects on patient survival. We then extracted 43, 55, or 59 genes that were differentially expressed between the over and under the median groups for , , or using the criteria of >2.5, >1.5, or >2.0 fold and  < 0.05 in the Mann-Whitney test. The results of a pathway analysis revealed the association of and -related genes with the IL-17 signaling pathway and infection, while -associated pathways were not extracted. A protein-protein interaction analysis revealed a dense network in the order of , , and . An investigation of the relationships between the intratumoral microbiome and classical clinical risk factors showed that high levels of were associated with a good prognosis in the absence of alcohol consumption and smoking, while high levels of were associated with a poor prognosis in the absence of alcohol consumption. In conclusion, intratumoral and may affect the prognosis of patients with HNSCC, and their effects on HNSCC are modulated by the impact of drinking and smoking.