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Abstract Background Esophageal adenocarcinoma (EA) may develop metastases even in early stage (pT1) disease, but molecular bi-omarkers are lacking to guide therapeutic decisions regarding the type of treatment. Endoscopic submucosal dis-section (ESD) is an effective treatment of early esophageal adenocarcinomas. However, ESD only an option for patients without lymph node metastases. The aim of this study is to detect possible biomarkers with which one could estimate lymphatic metastasis. Methods A multi-array miRNA study with consecutive in silico analysis of dependent genes and in situ analysis of selected proteins was chosen to detect possible biomarkers. A retrospective analysis including twenty cases of EA of the distal esophagus/esophagogastric junction after ESD without or after esophagectomy with lymph node metastasis (each n=10) was performed. The DNA of the Formalin-Fixed Paraffin-Embedded (FFPE) material of these patients was analysed using an advanced miRNA Human Card (spotted with 754 unique microRNAs) with consecutive in silico gene regulation and immunohistochemical analysis of the associated proteins. Result The multi-array miRNA of the tumour sample with EA showed an upregulation of 25 and a downregulation of 20 microRNAs, with the highest differences for the miRNAs miR-100-5p, miR-501-3p and miR-576-5p (upregulation) and miR-150-3p, miR-190a-5p and miR-545-3p (downregulation). The in silico analysis of these mirRNAs revealed the downstream paired partners RDX-Rock2, DICER1-AGO2, YAF2-EZF6 and TET2-5HMC, which were significantly differentially expressed by in-situ immunohistochemical staining. Biologically relevant downstream gene and pro-tein targets, which were also significantly differentially expressed in-situ in relation to the tumour stage of EA could be found. Conclusion This molecular study provides evidence for a specific miRNA marker profile when comparing cases with localized and advanced EA. These preclinical experimental biomarker analyses may help to guide therapeutic decisions in cases with EA, although validation in a larger cohort of EA is necessary to draw firm conclusions.
Koch et al. (Sun,) studied this question.