Novel drug candidates for treating esophageal carcinoma: A study on differentially expressed genes, using connectivity mapping and molecular docking
- Yu‑Ting Chen
- Jia‑Yi Xie
- Qi Sun
- Wei‑Jia Mo
Published online on: November 2, 2018
Copyright: © Chen et al.
This is an open access article distributed under the terms of Creative Commons Attribution License.
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Patients with esophageal carcinoma (ESCA) have a poor prognosis and high mortality rate. Although standard therapies have had effect, there is an urgent requirement to develop novel options, as increasing drug tolerance has been identified in clinical practice. In the present study, differentially expressed genes (DEGs) of ESCA were identified in The Cancer Genome Atlas and Genotype‑Tissue Expression databases. Functional and protein‑protein interaction (PPI) analyses were performed. The Connectivity Map (CMAP) was selected to predict drugs for the treatment of ESCA, and their target genes were acquired from the Search Tool for Interactions of Chemicals (STITCH) by uploading the Simplified Molecular‑Input Line‑Entry System structure. Additionally, significant target genes and ESCA‑associated hub genes were extracted using another PPI analysis, and the corresponding drugs were added to construct a network. Furthermore, the binding affinity between predicted drug candidates and ESCA‑associated hub genes was calculated using molecular docking. Finally, 827 DEGs (|log2 fold‑change|≥2; q‑value <0.05), which are principally involved in protein digestion and absorption (P<0.005), the plasminogen‑activating cascade (P<0.01), as well as the ‘biological regulation’ of the Biological Process, ‘membrane’ of the Cellular Component and ‘protein binding’ of the Molecular Function categories, were obtained. Additionally, 11 hub genes were obtained from the PPI network (all degrees ≥30). Furthermore, the 15 first screen drugs were extracted from CMAP (score <‑0.85) and the 9 second screen drugs with 70 target genes were extracted from STITCH. Furthermore, another PPI analysis extracted 51 genes, and apigenin, baclofen, Prestwick‑685, menadione, butyl hydroxybenzoate, gliclazide and valproate were selected as drug candidates for ESCA. Those molecular docking results with a docking score of >5.52 indicated the significance of apigenin, Prestwick‑685 and menadione. The results of the present study may lead to novel drug candidates for ESCA, among which Prestwick‑685 and menadione were identified to be significant new drug candidates.