Barrett's Epithelium to Esophageal Adenocarcinoma: Is There a "Point of No Return"?

Esophageal adenocarcinoma (EA) arises from Barrett's epithelium (BE), and chronic gastroesophageal reflux disease is considered the strongest risk factor for disease progression. All BE patients undergo acid suppressive therapy, surveillance, and BE removal by surgery or endoscopic ablation, yet the incidence of EAC continues to increase. Despite the known side effects and mortality, the one-size-fits-all approach is the standard clinical management as there are no reliable methods for risk stratification. Paired-end Illumina NextSeq500 RNA sequencing was performed on total RNA extracted from 20-week intervals (0, 20, 40, and 60 W) of an BE carcinogenesis (BEC) model to construct time series global gene expression patterns (GEPs). The cells from two strategic time points (20 and 40 W) based on the GEPs were grown for another 20 weeks, with and without further acid and bile salt (ABS) stimulation, and the recurrent neoplastic cell phenotypes were evaluated. Hierarchical clustering of 866 genes with ≥ twofold change in transcript levels across the four time points revealed maximum variation between the BEC20W and BEC40W cells. Enrichment analysis confirmed that the genes altered ≥ twofold during this window period associated with carcinogenesis and malignancy. Intriguingly, the BEC20W cells required further ABS exposure to gain neoplastic changes, but the BEC40W cells progressed to malignant transformation after 20 weeks even in the absence of additional ABS. The transcriptomic gene expression patterns in the BEC model demonstrate evidence of a clear threshold in the progression of BE to malignancy. Catastrophic transcriptomic changes during a window period culminate in the commitment of the BE cells to a "point of no return," and removal of ABS is not effective in preventing their malignant transformation. Discerning this "point of no return" during BE surveillance by tracking the GEPs has the potential to evaluate risk of BE progression and enable personalized clinical management.