Abstract
Lung cancer is known as the leading cause which presents the highest fatality rate worldwide; non-small-cell lung cancer (NSCLC) is the most prevalent type of lung carcinoma with high severity and affects 80% of patients with lung malignancies. Up to now, the general treatment for NSCLC includes surgery, chemotherapy, and radiotherapy; however, some therapeutic drugs and approaches could cause side effects and weaken the immune system. The combination of conventional therapies and traditional Chinese medicine (TCM) significantly improves treatment efficacy in lung cancer. Therefore, it is necessary to investigate the chemical composition and underlying antitumor mechanisms of TCM, so as to get a better understanding of the potential natural ingredient for lung cancer treatment. In this study, we selected 78 TCM to treat NSCLC cell line (A549) and obtained 92 transcriptome data; differential expression and WGCNA were applied to screen the potential natural ingredient and target genes. The sample which was treated with A. pierreana generated the most significant DEG set, including 6130 DEGs, 2479 upregulated, and 3651 downregulated. KEGG pathway analyses found that four pathways (MAPK, NF-kappa B, p53, and TGF-beta signaling pathway) were significantly enriched; 16 genes were significantly regulated in these four pathways. Interestingly, some of them such as EGFR, DUSP4, IL1R1, IL1B, MDM2, CDKNIA, and IDs have been used as the target biomarkers for cancer diagnosis and therapy. In addition, classified samples into 14 groups based on their pharmaceutical effects, WGCNA was used to identify 27 modules. Among them, green and darkgrey were the most relevant modules. Eight genes in the green module and four in darkgrey were identified as hub genes. In conclusion, we screened out three new TCM (B. fruticose, A. pierreana, and S. scandens) that have the potential to develop natural anticancer drugs and obtained the therapeutic targets for NSCLC therapy. Our study provides unique insights to screen the natural components for NSCLC therapy using high-throughput transcriptome analysis.
Highlights
Lung cancer remained the leading cause which presents the highest fatality rate worldwide, with an estimated 1.8 million deaths (18%) in each year reported by the International Agency for Research on Cancer/World Health Organization [1]
We list the top 10 set shown in Tables 3, and selected the differentially expressed gene (DEG) set of three Traditional Chinese medicine (TCM) candidates, which were Breynia fruticosa (B. fruticosa), Argyreia pierreana (A. pierreana), and Senecio scandens (S. scandens), illustrated by a volcano plot (Figures 1(b), 1(e), and 1(h))
Some of the plant materials with potential anticancer effects were analyzed in previous studies, such as Senecio scandens, Breynia fruticosa, Salvia miltiorrhiza Bunge, Gynura procumbens, Euphorbia hirta, Forsythia suspensa, Senecio scandens, Polygonum perfoliatum, Malva verticillata var. crispa, Mallotus apelta, Pteris semipinnata, Acmella paniculate, Aristolochia tagala, Schisandra chinensis, Gelsemium elegans, and Ligustrum confusum [46, 47, 68,69,70,71]
Summary
Lung cancer remained the leading cause which presents the highest fatality rate worldwide, with an estimated 1.8 million deaths (18%) in each year reported by the International Agency for Research on Cancer/World Health Organization [1]. Lung cancer is the highest incidence of cancer and the high fatality rate in men, in 93 countries [2]. It is urgent necessity to investigate the novel therapeutic strategies, to identify the prognostic markers based on better understanding of molecular mechanism of NSCLC. It helps to improve the precision rate for diagnosis and therapy and contributes to take the further steps for NSCLC research [3, 4]
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