NPDI-BcCov: A Network Pharmacology Approach for Simultaneous Inference of Drugs Targeting Breast Cancer and COVID-19

Author:

Huang Zhijian1,Xue Jinsong1,Zhao Xiangqian2,Qiu Xiaoting1,Zhang Chenglong1,Yang Jingwen1,Yang Yong3,Tong Shanhe4,Li Nani1,Yang Jialiang4

Affiliation:

1. Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital

2. Fujian Normal University Biomedical Research Center of South China

3. Beth Israel Deaconess Medical Center, Harvard Medical School

4. Geneis (Beijing) Co., Ltd

Abstract

Abstract The coronavirus disease (COVID-19) has emerged as a significant threat to public health, especially for individuals battling cancer. It is crucial to prioritize the care and attention given to breast cancer patients who have also infected with COVID-19, as they face a higher risk of severe outcomes compared to the general population. These patients typically undergo concurrent treatment for both conditions, which can be risky due to potential drug interactions and adverse effects. Therefore, there is an urgent need to identify drugs that can effectively target both breast cancer and COVID-19. In this study, we have developed a novel computational framework called Network Pharmacology-based Drug Inference for Breast Cancer and COVID-19 (NPDI-BcCov). Our framework aims to identify genes associated with both breast cancer and COVID-19, as well as drugs that target these specific genes. To achieve this, we identified 132 genes by overlapping differentially expressed genes (DEGs) associated with breast cancer in the Cancer Genome Atlas (TCGA) and genes associated with COVID-19 in Genecards. Among these genes, we identified 6 prognostic-related genes (NCAM1, AMH, MYOM2, IGHE, PPP2R2C, and PLK1) using both COX and LASSO regression methods. Moreover, we developed an enhanced risk scoring model based on these 6 prognostic genes and proposed a nomogram to verify the relationship between clinicopathological characteristics, risk score, and prognosis. Additionally, we screened for potential drugs targeting these genes and found several drugs for the gene PLK1, with luteolin being prioritized due to its anti-viral and antioxidant properties. We also observed significant differences in tumor mutation burden (TMB) and gene mutation profiles between high-PLK1 and low-PLK1 expression groups. Furthermore, we discovered a strong hydrogen bond between luteolin and PLK1 in their three-dimensional structure, suggesting a close molecular interaction. Finally, we explored the biomedical function and therapeutic mechanism of luteolin in BRCA/COVID-19 patients. Overall, our study presents the first evidence highlighting luteolin as a potential drug for the simultaneous treatment of patients with both breast cancer and COVID-19.

Publisher

Research Square Platform LLC

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