Research Paper Volume 16, Issue 20 pp 13104—13116
Lymph node metastasis determined miRNAs in esophageal squamous cell carcinoma
- 1 Department of Critical Care Medicine, Affiliated Hospital of Chifeng University, Chifeng 024000, Inner Mongolia Autonomous Region, China
- 2 Department of Chronic Disease, Chifeng Center for Disease Control and Prevention, Chifeng 024000, Inner Mongolia Autonomous Region, China
Received: May 22, 2024 Accepted: June 26, 2024 Published: October 14, 2024
https://doi.org/10.18632/aging.206122How to Cite
Copyright: © 2024 Bi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Purpose: There is no golden noninvasive and effective technique to diagnose lymph node metastasis (LNM) for esophageal squamous cell carcinoma (ESCC) patients. Here, a classifier was proposed consisting of miRNAs to screen ESCC patients with LNM from the ones without LNM.
Methods: miRNA expression and clinical data files of 93 ESCC samples were downloaded from TCGA as the discovery set and 119 ESCC samples with similar dataset GSE43732 as the validation set. Differentially expressed miRNAs (DE-miRNAs) were analyzed between patients with LNM and without LNM. LASSO regression was performed for selecting the DE-miRNA pair to consist the classifier. To validate the accuracy and reliability of the classifier, the SVM and AdaBoost algorithms were applied. The CCK-8 and wound healing assay were used to evaluate the role of the miRNA in ESCC cells.
Result: There were 43 DE miRNAs between the LNM+ group and LNM- group. Among them, miR-224-5p, miR-99a-5p, miR-100-5p, miR-34c-5p, miR-503-5p, and miR-452-5p were identified by LASSO to establish the classifier. SVM and AdaBoost showed that the model could classify the ESCC patients with LNM from the ones without LNM precisely and reliably in 2 data sets. miR-224-5p in the classifier as the top contributor to discriminate the two groups of patients based on AdaBoost, promoted ESCC cell proliferation and migration in vitro.
Conclusion: The classifier based on these 6 miRNAs could classify the ESCC patients with LNM from the ones without LNM successfully.