Among all malignant tumors in the whole universe, the incidence and mortality of lung cancer disease rank first. Especially in the past few years, the occurrence of lung cancer in the urban population has continued to increase, which seriously threatens the lives and health of people. Among the many treatments for lung cancer, chemotherapy is the best one, but traditional chemotherapy has low specificity and drug resistance. To address the above issue, this study reviews the five biological pathways that common terpenoid compounds in medicinal plants interfere with the occurrence and development of lung cancer: cell proliferation, cell apoptosis, cell autophagy, cell invasion, metastasis, and immune mechanism regulation. In addition, the mechanism of the terpenoid natural traditional Chinese medicine monomer compound combined with Western medicine in the multipathway antilung cancer is summarized.

Cisplatin (DDP) based chemotherapy occurs a reduced therapeutic effect on the later treatment of ovarian cancer (OC) due to DDP resistance. Astragaloside II (ASII), a natural product extracted from Radix Astragali, has shown promising anticancer effects. However, the effects of ASII on OC have not been clarified. In this study, we found that ASII inhibited cell growth and promoted cell apoptosis of DDP-resistant OC cells in vitro and in vivo. Further study showed that ASII downregulated multidrug resistance-related protein MDR1 and cell cycle-related protein Cyclin D1 and PCNA, and also upregulated apoptosis-related protein leaved PRAP and cleaved caspase-3. In addition, ASII induced autophagy, characterized by upregulation of LC3II expression, downregulation of p62 expression, and elevation of LC3 punctuation, may be associated with inhibition of the AKT/mTOR signaling pathway.Moreover, the messenger RNA-sequencing was used to identify potential molecules regulated by ASII. In conclusion, these findings indicated that ASII increased sensitivity of DDP in the treatment of OC.

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Objective. To perform gene set enrichment analysis (GSEA) and analysis of immune cell infiltration on non-small-cell lung cancer (NSCLC) expression profiling microarray data based on bioinformatics, construct TICS scoring model to distinguish prognosis time, screen key genes and cancer-related pathways for NSCLC treatment, explore differential genes in NSCLC patients, predict potential therapeutic targets for NSCLC, and provide new directions for the treatment of NSCLC. Methods. Transcriptome data of 81 NSCLC patients and the GEO database were used to download matching clinical data (access number: GSE120622). Form the expression of non-small cell lung cancer (NSCLC). TICS values were calculated and grouped according to TICS values, and we used mRNA expression profile data to perform GSEA in non-small-cell lung cancer patients. Biological process (GO) analysis and DAVID and KOBAS were used to undertake pathway enrichment (KEGG) analysis of differential genes. Use protein interaction (PPI) to analyze the database STRING, and construct a PPI network model of target interaction. Results. We obtained 6 significantly related immune cells including activated B cells through the above analysis (Figure 1(b), p < 0.001 ). Based on the TICS values of significantly correlated immune cells, 41 high-risk and 40 low-risk samples were obtained. TICS values and immune score values were subjected to Pearson correlation coefficient calculation, and TICS and IMS values were found to be significantly correlated (Cor = 0.7952). Based on non-small-cell lung cancer mRNA expression profile data, a substantial change in mRNA was found between both the high TICS group as well as the low TICS group (FDR 0.01, FC > 2). The researchers discovered 730 mRNAs that were considerably upregulated in the high TICS group and 121 mRNAs that were considerably downregulated in the low TICS group. High confidence edges (combined score >0.7) were selected using STRING data; then, 191 mRNAs were matched to the reciprocal edges; finally, an undirected network including 164 points and 777 edges was constructed. Important members of cellular chemokine-mediated signaling pathways, such as CCL19, affect patient survival time. Conclusion. (1) The longevity of patients with non-small-cell lung cancer was substantially connected with the presence of immature B cells, activated B cells, MDSC, effector memory CD4 T cells, eosinophils, and regulatory T cells. (2) Immune-related genes such as CX3CR1, CXCR4, CXCR5, and CCR7, which are associated with the survival of NSCLC, affect the prognosis of NSCLC patients by regulating the immune process.