Construction of a survival model for Esophageal Squamous Carcinoma and prediction of potential treatment with herbal medicine-Reference-Cited by-同舟云学术

Construction of a survival model for Esophageal Squamous Carcinoma and prediction of potential treatment with herbal medicine

Published:2023-06-26 Issue: Volume: Page:
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Author:

Zhang Zhenhu¹,Zhang Guodong¹,Xiao Zhaohua²,Mao Xinyu¹,wang Dong¹

Affiliation:

1. Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University

2. Department of Thoracic Surgery, The Second Hospital of Shandong University

Abstract

Abstract Purpose Esophageal squamous cell carcinoma (ESCC) accounts for 80% of esophageal cancers worldwide, with a 5-year survival rate of only 30%. Herbal medicine has been extensively used in Asian medicine for more than 5000 years, yet little is known about its application in ESCC. Zhenqi Fuzheng Granules (ZQFZ) is a classic Chinese herbal formula used to improve immunity, but research on the mechanism is lacking. Methods We verified 25 ZQFZ substances from the Traditional Chinese Medicine System Pharmacology (TCMSP) database for this study, downloaded GSE20347 and GSE38129 datasets from the GEO database to find the targets of ESCC, and plotted Venn diagrams to obtain the co-targets of ZQFZ and ESCC. GO and GSEA enrichment analyses have been performed to look into the levels of expression and biological functions of the key genes. Key targets were obtained using the LASSO machine learning algorithm and the cytoHubba plugin in Cytoscape 3.8.2, respectively, and further validated with datasets GSE45670, GSE161533, and the GEPIA database. Immune infiltration analysis was performed using the CIBERSORTx algorithm and correlations between core targets and common immunosuppressive checkpoints were analyzed using Pearson correlation coefficients to explore the immune function and validated using the TIMER 2.0 database. Data on esophageal squamous cancer survival was obtained from the TCGA database, and key genes were evaluated using univariate and multivariate Cox analyses. Differential genes were then added to create a Nomogram analysis. To further assess the potential effects of the selected drugs on ESCC, molecular docking was performed. Results From the 35 differential genes, we extracted 5 of the most closely related genes and 6 of the prognosis-related genes, respectively. Immunoassay showed that CXCL10 was closely associated with immune infiltration, while the CHEK1 gene was associated with patient survival prognosis. The 11 core genes were analyzed and docked one by one, showing good results. Conclusion In conclusion, ZQFZ may act through multiple pathways on a range of targets to treat ESCC. This study presents a novel method for treating ESCC and lays the basis for ZQFZ clinical application.

Publisher

Research Square Platform LLC

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