An international report on bacterial communities in esophageal squamous cell carcinoma

Abstract

The incidence of esophageal squamous cell carcinoma (ESCC) is disproportionately high in the eastern corridor of Africa and parts of Asia. Emerging research has identified a potential association between poor oral health and ESCC. One proposed biological pathway linking poor oral health and ESCC involves the alteration of the microbiome. Thus, we performed an integrated analysis of four independent sequencing efforts of ESCC tumors from patients from high- and low-incidence regions of the world. Using whole genome sequencing (WGS) and RNA sequencing (RNAseq) of ESCC tumors and WGS of synchronous collections of saliva specimens from 61 patients in Tanzania, we identified a community of bacteria, including members of the genera Fusobacterium, Selenomonas, Prevotella, Streptococcus, Porphyromonas, Veillonella, and Campylobacter, present at high abundance in ESCC tumors. We then characterized the microbiome of 238 ESCC tumor specimens collected in two additional independent sequencing efforts consisting of patients from other high-ESCC incidence regions (Tanzania, Malawi, Kenya, Iran, China). This analysis revealed a similar tumor enrichment of the ESCC-associated bacterial community in these cancers. Because these genera are traditionally considered members of the oral microbiota, we explored if there is a relationship between the synchronous saliva and tumor microbiomes of ESCC patients in Tanzania. Comparative analyses revealed that paired saliva and tumor microbiomes are significantly similar with a specific enrichment of Fusobacterium and Prevotella in the tumor microbiome. Together, these data indicate that cancer-associated oral bacteria are associated with ESCC tumors at the time of diagnosis and support a model in which oral bacteria are present in high abundance in both saliva and tumors of ESCC patients. Longitudinal studies of the pre-diagnostic oral microbiome are needed to investigate whether these cross-sectional similarities reflect temporal associations.