Antibiotic Exposure is Associated With a Risk of Esophageal Adenocarcinoma

Intratumoral microbiota: a new force in the development and treatment of esophageal cancer

Esophageal cancer (EC) ranks among the most prevalent cancers worldwide, with a particularly high incidence in the Asian population. Due to the inconspicuous nature of early symptoms, patients with esophageal cancer are typically diagnosed in the middle to late stages, resulting in suboptimal overall treatment outcomes. Consequently, there is an urgent need to explore and refine therapeutic strategies. Microorganisms have been identified in numerous tumor tissues, including EC, and these microorganisms are referred to as the intratumoral microbiome. Intratumoral microbiota and their metabolic byproducts can influence the progression and treatment of esophageal cancer through various mechanisms, such as modulating tumor cell metabolism and local immune responses. Therefore, the intratumoral microbiota may potentially serve as a target for the treatment of esophageal cancer. This review delineates the composition, origin, and diagnostic significance of intratumoral microbiota in esophageal cancer tissue, and discusses the mechanisms by which intratumoral microbiota contribute to the onset of esophageal cancer. In addition, the impact of intratumoral microbiota on the treatment of esophageal cancer and its intervention measures are also addressed.

Application of Mendelian randomization to assess host gene-gut microbiota correlations in patients with esophageal cancer

Background

Increasing evidence suggests that esophageal cancer (ESCA) may be correlated with gut flora. However, their causal connection remains unclear. This study aimed to evaluate potential causal linkages and gene-gut microbiome associations between the gut microbiota and ESCA using Mendelian randomization (MR).

Methods

We analyzed the data using genome-wide association studies. The exposure factor and outcome variable were the gut microbiota and ESCA, respectively. The MR-Egger method, weighted median, inverse-variance weighted method, heterogeneity test, sensitivity analysis, and multiplicity analysis were used for the MR analysis. And it was validated using an external dataset. Further meta-analysis was performed to validate the robustness of this relationship. Finally, we annotated single nucleotide polymorphisms in the gut microbiota that were causally associated with ESCA to explore possible host gene-gut microbiota correlations in patients with ESCA.

Results

We identified four species with potential associations with ESCA. Three of these species had a negative causal relationship with ESCA (odds ratio (OR): 0.961; 95% confidence interval (CI): 0.923-0.971; p = 0.047 for Romboutsia; OR: 0.972; 95% CI: 0.921-0.961; p = 0.018 for Lachnospira; OR: 0.948; 95% CI: 0.912-0.970; p = 0.032 for Eubacterium). A positive causal relationship was observed between one bacterial group and ESCA (OR: 1.105; 95% CI: 1.010-1.072; p = 0.018 for Veillonella). External datasets show the same trend. This is further supported by meta-analysis. None of the data showed pleiotropy, and leave-one-out analysis indicated the reliability of these findings. The gut microbiomes of patients with ESCA may correlate with the 19 identified genes.

Conclusion

Our data indicate a potential causal link between these four gut bacteria and ESCA and identify a correlation between host genes and gut microbiota in ESCA, offering novel therapeutic options.