0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Integrating Network Pharmacology, Molecular Docking, and Experimental Validation to Investigate the Mechanism of (−)-Guaiol Against Lung Adenocarcinoma

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Lung adenocarcinoma (LUAD) is the most common type of lung cancer, which poses a serious threat to human life and health. -(−)Guaiol, an effective ingredient of many medicinal herbs, has been shown to have a high potential for tumor interference and suppression. However, knowledge of pharmacological mechanisms is still lacking adequate identification or interpretation.

          Material/Methods

          The genes of LUAD patients collected from TCGA were analyzed using limma and WGCNA. In addition, targets of (−)-Guaiol treating LUAD were selected through a prediction network. Venn analysis was then used to visualize the overlapping genes, which were further condensed using the PPI network. GO and KEGG analyses were performed sequentially, and the essential targets were evaluated and validated using molecular docking. In addition, cell-based verification, including the CCK-8 assay, cell death assessment, apoptosis analysis, and western blot, was performed to determine the mechanism of action of (−)-Guaiol.

          Results

          The genes included 959 differentially-expressed genes, 6075 highly-correlated genes, and 480 drug-target genes. Through multivariate analysis, 23 hub genes were identified and functional enrichment analyses revealed that the PI3K/Akt signaling pathway was the most significant. Experiment results showed that -(−)Guaiol can inhibit LUAD cell growth and induce apoptosis. Additional evidence suggested that the PI3K/Akt signaling pathway established an inseparable role in the antitumor processes of -(−)Guaiol, which is consistent with network pharmacology results.

          Conclusions

          Our results show that the effect of (−)-Guaiol in LUAD treatment involves the PI3K/Akt signaling pathway, providing a useful reference and medicinal value in the treatment of LUAD.

          Related collections

          Most cited references46

          • Record: found
          • Abstract: found
          • Article: not found

          clusterProfiler: an R package for comparing biological themes among gene clusters.

          Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            limma powers differential expression analyses for RNA-sequencing and microarray studies

            limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Cancer Statistics, 2021

              Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population-based cancer occurrence. Incidence data (through 2017) 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 2018) were collected by the National Center for Health Statistics. In 2021, 1,898,160 new cancer cases and 608,570 cancer deaths are projected to occur in the United States. After increasing for most of the 20th century, the cancer death rate has fallen continuously from its peak in 1991 through 2018, for a total decline of 31%, because of reductions in smoking and improvements in early detection and treatment. This translates to 3.2 million fewer cancer deaths than would have occurred if peak rates had persisted. Long-term declines in mortality for the 4 leading cancers have halted for prostate cancer and slowed for breast and colorectal cancers, but accelerated for lung cancer, which accounted for almost one-half of the total mortality decline from 2014 to 2018. The pace of the annual decline in lung cancer mortality doubled from 3.1% during 2009 through 2013 to 5.5% during 2014 through 2018 in men, from 1.8% to 4.4% in women, and from 2.4% to 5% overall. This trend coincides with steady declines in incidence (2.2%-2.3%) but rapid gains in survival specifically for nonsmall cell lung cancer (NSCLC). For example, NSCLC 2-year relative survival increased from 34% for persons diagnosed during 2009 through 2010 to 42% during 2015 through 2016, including absolute increases of 5% to 6% for every stage of diagnosis; survival for small cell lung cancer remained at 14% to 15%. Improved treatment accelerated progress against lung cancer and drove a record drop in overall cancer mortality, despite slowing momentum for other common cancers.
                Bookmark

                Author and article information

                Journal
                Med Sci Monit
                Med Sci Monit
                Medical Science Monitor
                Medical Science Monitor : International Medical Journal of Experimental and Clinical Research
                International Scientific Literature, Inc.
                1234-1010
                1643-3750
                2022
                25 July 2022
                21 July 2022
                : 28
                : e937131-1-e937131-29
                Affiliations
                [1 ]Department of Oncology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, PR China
                [2 ]Department of Respiratory Medicine, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, PR China
                Author notes
                Corresponding Authors: Yan Li, e-mail: yan.xiaotian@ 123456shutcm.edu.cn , Jianchun Wu, e-mail: eq219@ 123456126.com
                [A]

                Study Design

                [B]

                Data Collection

                [C]

                Statistical Analysis

                [D]

                Data Interpretation

                [E]

                Manuscript Preparation

                [F]

                Literature Search

                [G]

                Funds Collection

                [*]

                Yaoying Zeng and Yanbin Pan are Co-first author

                Article
                937131
                10.12659/MSM.937131
                9336205
                35871777
                a3a3cca8-d974-4d13-9d03-27d910c3ad3f
                © Med Sci Monit, 2022

                This work is licensed under Creative Common Attribution-NonCommercial-NoDerivatives 4.0 International ( CC BY-NC-ND 4.0)

                History
                : 04 May 2022
                : 29 June 2022
                Categories
                Database Analysis

                lung neoplasms,pharmacology,signal transduction
                lung neoplasms, pharmacology, signal transduction

                Comments

                Comment on this article