Reddy Yeshaswini, Desai Madhav, Tumaliuan Bernadette, Thosani Nirav
Interventional Gastroenterology at UT, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
Borland Groover Clinic, Jacksonville, FL 32216, USA.
J Pers Med. 2025 Jul 22;15(8):327. doi: 10.3390/jpm15080327.
Barrett's esophagus (BE), a metaplastic transformation of an esophageal squamous epithelium into an intestinal-type columnar epithelium, is the primary precursor to esophageal adenocarcinoma (EAC). Traditional management strategies have relied heavily on selective screening, tailored surveillance intervals, and early dysplasia detection and treatment algorithms. However, the heterogeneity in progression risk among BE patients necessitates a more nuanced, personalized approach involving precision care, tailoring decisions to individual patient characteristics, promises to enhance outcomes in BE through more targeted screening, personalized surveillance intervals, and risk-based therapeutic strategies. This review explores the current landscape and emerging trends in precision medicine for Barrett's esophagus, highlighting genomic markers, digital pathology, and AI-driven models as tools to transform how we approach this complex disease and prevent progression to EAC.
巴雷特食管（BE）是食管鳞状上皮化生为肠型柱状上皮，是食管腺癌（EAC）的主要前驱病变。传统的管理策略严重依赖于选择性筛查、量身定制的监测间隔以及早期发育异常的检测和治疗算法。然而，BE患者进展风险的异质性需要一种更细致入微、个性化的方法，即精准医疗，根据个体患者特征做出决策，有望通过更有针对性的筛查、个性化的监测间隔和基于风险的治疗策略来改善BE的治疗效果。本综述探讨了巴雷特食管精准医学的现状和新兴趋势，强调基因组标志物、数字病理学和人工智能驱动的模型作为工具，以改变我们处理这种复杂疾病并预防进展为EAC的方式。
