Medical Significance of Uterine Corpus Endometrial Carcinoma Patients Infected With SARS-CoV-2 and Pharmacological Characteristics of Plumbagin

Abstract

Background: Clinically, evidence shows that uterine corpus endometrial carcinoma (UCEC) patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may have a higher death-rate. However, current anti-UCEC/coronavirus disease 2019 (COVID-19) treatment is lacking. Plumbagin (PLB), a pharmacologically active alkaloid, is an emerging anti-cancer inhibitor. Accordingly, the current report was designed to identify and characterize the anti-UCEC function and mechanism of PLB in the treatment of patients infected with SARS-CoV-2 via integrated in silico analysis.

Methods: The clinical analyses of UCEC and COVID-19 in patients were conducted using online-accessible tools. Meanwhile, in silico methods including network pharmacology and biological molecular docking aimed to screen and characterize the anti-UCEC/COVID-19 functions, bio targets, and mechanisms of the action of PLB.

Results: The bioinformatics data uncovered the clinical characteristics of UCEC patients infected with SARS-CoV-2, including specific genes, health risk, survival rate, and prognostic index. Network pharmacology findings disclosed that PLB-exerted anti-UCEC/COVID-19 effects were achieved through anti-proliferation, inducing cytotoxicity and apoptosis, anti-inflammation, immunomodulation, and modulation of some of the key molecular pathways associated with anti-inflammatory and immunomodulating actions. Following molecular docking analysis, in silico investigation helped identify the anti-UCEC/COVID-19 pharmacological bio targets of PLB, including mitogen-activated protein kinase 3 (MAPK3), tumor necrosis factor (TNF), and urokinase-type plasminogen activator (PLAU).

Conclusions: Based on the present bioinformatic and in silico findings, the clinical characterization of UCEC/COVID-19 patients was revealed. The candidate, core bio targets, and molecular pathways of PLB action in the potential treatment of UCEC/COVID-19 were identified accordingly.

Keywords: cancer; clinical; mechanism and characterization; pharmacologic (drug) therapy; target.

Figure 1

Screening of mutual genes between UCEC and COVID-19. (A), candidate, mutual genes of UCEC and COVID-19 in a Venn diagram. (B), differentially expressed genes from mutual genes shown in a volcano-plot map.

Figure 2

Clinical features of UCEC/COVID-19-related genes. (A), Univariate Cox determination was conducted to identify 44 candidate genes. (B), Multivariate Cox analysis identified 13 specific genes, including CCL2, ANPEP, CLEC4M, SCARA3, CP, ABCA4, KHK, SLC8A1, ZYG11B, GHR, TNF, FOSL2, and PLAU. The survival analysis suggested statistical significance associated with 13 specific genes in the overall survival between high- and low-risk groups. (C, D), Further analysis showed the greater the patient’s risk value, the higher the patient’s risk score; similarly, higher mortality and lower survival.

Figure 3

Clinical correlation analysis of 13 genes was carried out and assessed; the results showed that each gene has no correlation with clinical single factors (A–P).

Figure 4

Preliminary findings of network pharmacology. (A), The candidate, mutual genes of PLB and UCEC/COVID-19 in a Venn diagram. (B, C), GO-based biologic process and KEGG-based signaling pathway of PLB against UCEC/COVID-19 following enrichment analysis.

Figure 5

Bioinformatics characteristics of PLB against UCEC/COVID-19. (A), a gene-assayed network connection of PLB against UCEC/COVID-19. (B), 5 identified predictive core bio targets of PLB in the potential treatment of UCEC/COVID-19.

Figure 6

Interaction network connection of candidates, core bio targets, BP, functions, and molecular pathways of PLB in the treatment of UCEC/COVID-19 by using Cytoscape analysis.

Figure 7

Biological molecular docking findings of PLB against UCEC/COVID-19. (A), molecular affinity and the binding energy of PLB docked with core proteins, including MAPK3, TNF, and PLAU. (B–E), in silico characteristics of PLB, docked with core proteins.