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      Uncovering the Pharmacological Mechanism of 2-Dodecyl-6-Methoxycyclohexa-2,5 -Diene-1,4-Dione Against Lung Cancer Based on Network Pharmacology and Experimental Evaluation

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          Abstract

          Background: 2-Dodecyl-6-Methoxycyclohexa-2, 5-Diene-1,4-Dione (DMDD) was purified from the roots of Averrhoa carambola L. Previous research demonstrated that DMDD is a small molecular compound with significant therapeutic potential for tumors. However, the potential targets and pharmacological mechanism of DMDD to treat lung cancer has not been reported.

          Methods: We employed network pharmacology and experimental evaluation to reveal the pharmacological mechanism of DMDD against lung cancer. Potential therapeutic targets of DMDD were screened by PharmMapper. Differentially expressed genes (DEGs) in The Cancer Genome Atlas (TCGA) lung cancer data sets were extracted and analyzed by GEPIA2. The mechanism of DMDD against lung cancer was determined by PPI, gene ontology (GO) and KEGG pathway enrichment analysis. Survival analysis and molecular docking were employed to obtain the key targets of DMDD. Human lung cancer cell lines H1975 and PC9 were used to detect effects of DMDD treatment in vitro. The expression of key targets after DMDD treated was validated by Western Blot.

          Results: A total of 60 Homo sapiens potential therapeutic targets of DMDD and 3,545 DEGs in TCGA lung cancer datasets were identified. Gene ontology and pathway analysis revealed characteristic of the potential targets of DMDD and DEGs in lung cancer respectively. Cell cycle and pathways in cancer were overlapping with DMDD potential targets and lung cancer DEGs. Eight overlapping genes were found between DMDD potential therapeutic targets and lung cancer related DEGs. Survival analysis showed that high expression of DMDD potential targets CCNE1 and E2F1 was significantly related to poor patient survival in lung cancer. Molecular docking found that DMDD exhibited significant binding affinities within the active site of CCNE1 and E2F1. Further tests showed that DMDD inhibited the proliferation, migration and clone formation in lung cancer cell lines (H1975 and PC9) in a dose and time dependent manner. Mechanistically, DMDD treatment decreased the expression of CDK2, CCNE1, E2F1 proteins and induced cell cycle arrest at the G1/S phase in H1975 and PC9 cells.

          Conclusion: These results delineated that DMDD holds therapeutic potential that blocks tumorigenesis by cell cycle regulation in lung cancer, and may provide potential therapies for lung cancer.

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            Cancer statistics, 2020

            Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States and compiles the most recent data on population-based cancer occurrence. Incidence data (through 2016) were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data (through 2017) were collected by the National Center for Health Statistics. In 2020, 1,806,590 new cancer cases and 606,520 cancer deaths are projected to occur in the United States. The cancer death rate rose until 1991, then fell continuously through 2017, resulting in an overall decline of 29% that translates into an estimated 2.9 million fewer cancer deaths than would have occurred if peak rates had persisted. This progress is driven by long-term declines in death rates for the 4 leading cancers (lung, colorectal, breast, prostate); however, over the past decade (2008-2017), reductions slowed for female breast and colorectal cancers, and halted for prostate cancer. In contrast, declines accelerated for lung cancer, from 3% annually during 2008 through 2013 to 5% during 2013 through 2017 in men and from 2% to almost 4% in women, spurring the largest ever single-year drop in overall cancer mortality of 2.2% from 2016 to 2017. Yet lung cancer still caused more deaths in 2017 than breast, prostate, colorectal, and brain cancers combined. Recent mortality declines were also dramatic for melanoma of the skin in the wake of US Food and Drug Administration approval of new therapies for metastatic disease, escalating to 7% annually during 2013 through 2017 from 1% during 2006 through 2010 in men and women aged 50 to 64 years and from 2% to 3% in those aged 20 to 49 years; annual declines of 5% to 6% in individuals aged 65 years and older are particularly striking because rates in this age group were increasing prior to 2013. It is also notable that long-term rapid increases in liver cancer mortality have attenuated in women and stabilized in men. In summary, slowing momentum for some cancers amenable to early detection is juxtaposed with notable gains for other common cancers.
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              Metascape provides a biologist-oriented resource for the analysis of systems-level datasets

              A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets. Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results. Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists. In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal. Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments. Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs. Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era.
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                Author and article information

                Contributors
                Journal
                Front Pharmacol
                Front Pharmacol
                Front. Pharmacol.
                Frontiers in Pharmacology
                Frontiers Media S.A.
                1663-9812
                02 February 2021
                2021
                : 12
                : 617555
                Affiliations
                [ 1 ]Key Laboratory of Longevity and Aging-related Diseases of Chinese Ministry of Education, Center for Translational Medicine and School of Preclinical Medicine, Guangxi Medical University, Nanning, China
                [ 2 ]Department of Pharmacology, Guangxi Medical University, Nanning, China
                Author notes

                Edited by: Wendy Wu, Berry Oncology Corporation, China

                Reviewed by: Jingfa Xiao, Chinese Academy of Sciences, China

                Dake Zhang, Beihang University, China

                *Correspondence: Renbin Huang, huangrenbin518@ 123456163.com ; Chunlin Zou, zouchunlin@ 123456sohu.com

                This article was submitted to Pharmacology of Anti-Cancer Drugs, a section of the journal Frontiers in Pharmacology

                Article
                617555
                10.3389/fphar.2021.617555
                7887632
                33613291
                af88e979-80b0-49f4-97d2-dba625369e13
                Copyright © 2021 Wang, Yang, Song, Fu, Wang, Du, Chen, Cao, Huang and Zou.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 16 October 2020
                : 06 January 2021
                Categories
                Pharmacology
                Original Research

                Pharmacology & Pharmaceutical medicine
                dmdd,lung cancer,network pharmacology,cell cycle arrest,tcga

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