Jinfukang induces cellular apoptosis through activation of Fas and DR4 in A549 cells

Integrative RNA-Seq and ATAC-Seq Analysis Reveals the Migration-Associated Genes Involved in Antitumor Effects of Herbal Medicine Feiyanning on Lung Cancer Cells

Lung cancer is one of the leading causes of cancer-associated death in the world. It is of great importance to explore new therapeutic targets. Traditional Chinese medicine formula Feiyanning has been clinically administered in China for more than a decade and raised attention due to its anticancer effect in lung cancer. However, the underlying molecular mechanisms remain to be elucidated. In the present study, we carried out cellular and molecular assays to examine the antitumor activities and understand the mechanism of the Feiyanning formula in lung cancer cells. The cellular viability of Feiyanning-treated lung cancer cells was evaluated by Cell Counting Kit-8. The effect of the Feiyanning formula on cellular migration and invasion of lung cancer cells was examined by wound healing and transwell assays. Transcriptome and chromatin accessibility analysis by RNA-seq and ATAC-seq was performed to investigate the underlying molecular mechanisms. Our results revealed that the Feiyanning formula inhibited the cellular activities of proliferation, migration, and invasion in non-small cell lung cancer cell lines A549, H1975, and 95D. Furthermore, we observed that the transcriptional activity of the migration-associated genes was downregulated upon Feiyanning formula treatment in non-small cell lung cancer cells. The chromatin accessibility of the Feiyanning-treated lung cancer genome tended to decrease, and the regulation of the cellular component movement biological process and PI3K-AKT pathway were enriched among these altered genomic regions. Taken together, the present study suggested that Feiyanning formula exerted the antitumor effects by modulating the expression and chromatin accessibility levels of migration-associated genes.

Evaluation of the Effectiveness of Herbal Components Based on Their Regulatory Signature on Carcinogenic Cancer Cells

Predicting cancer cells’ response to a plant-derived agent is critical for the drug discovery process. Recently transcriptomes advancements have provided an opportunity to identify regulatory signatures to predict drug activity. Here in this study, a combination of meta-analysis and machine learning models have been used to determine regulatory signatures focusing on differentially expressed transcription factors (TFs) of herbal components on cancer cells. In order to increase the size of the dataset, six datasets were combined in a meta-analysis from studies that had evaluated the gene expression in cancer cell lines before and after herbal extract treatments. Then, categorical feature analysis based on the machine learning methods was applied to examine transcription factors in order to find the best signature/pattern capable of discriminating between control and treated groups. It was found that this integrative approach could recognize the combination of TFs as predictive biomarkers. It was observed that the random forest (RF) model produced the best combination rules, including AIP/TFE3/VGLL4/ID1 and AIP/ZNF7/DXO with the highest modulating capacity. As the RF algorithm combines the output of many trees to set up an ultimate model, its predictive rules are more accurate and reproducible than other trees. The discovered regulatory signature suggests an effective procedure to figure out the efficacy of investigational herbal compounds on particular cells in the drug discovery process.

Combined Treatment with JFKD and Gefitinib Overcomes Drug Resistance in Non-Small Cell Lung Cancer

BACKGROUND

Gefitinib is an important drug used to treat Non-Small Cell Lung Cancer (NSCLC) with EGFR activating mutations, but drug resistance restricts its clinical application. In this present study, combined Jin Fu Kang Decoction (JFKD) and gefitinib showed specific cytotoxicity to gefitinib-resistant cancer cells (PC-9/gef).

OBJECTIVE

This study aimed to decipher the molecular mechanism of the JFKD on drug resistance when used together with Gefitinib and to find the contributing bio-active substance(s) in JFKD based on the putative mechanism.

METHODS

To investigate the combined effect of gefitinib and JFKD, in vitro experiments were conducted on the established gefitinib-resistant PC-9 subclone, while in vivo experiments were conducted on the BALB/c nude mice with PC-9/gef xenografts. Western blot was used to evaluate the protein expression, and Ultra-Performance Liquid Chromatography (UPLC) coupled with quadrupole time-offlight Mass Spectrometry (MS) was used to detect the bio-active compounds of JFKD.

RESULTS

The expression of the PTEN-relevant protein p-EGFR, p-Akt in vitro was inhibited more when combined JKFD and gefitinib were used, whereas the activities of PDCD4 and PTEN were increased; remarkably, in vivo experiments showed enhanced tumor growth inhibition when treated with this combination. Due to this combination, the effect on the gefitinib-resistant cell line, one of the JFKD-induced anti-cancer mechanisms, was found. To link the putative mechanism and the anticancer compounds in JFKD, 14 saponins and flavonoids were detected.

CONCLUSION

The results suggested that a promising TCM-participated therapy can be established by the putative mechanism of the combined treatment in resistant NSCLC and screening the contributing bio-active substance(s) in JFKD is meaningful on new TCM formula discovery.

A TCM Formula YYWY Inhibits Tumor Growth in Non-Small Cell Lung Cancer and Enhances Immune-Response Through Facilitating the Maturation of Dendritic Cells

In worldwide, lung cancer has a major socio-economic impact and is one of the most common causes of cancer-related deaths. Current therapies for lung cancer are still quite unsatisfactory, urging for alternative new treatments. Traditional Chinese Medicine (TCM) is currently increasingly popular and exhibits a complicated intervention in cancers therapy. In this study, we evaluated the anti-tumor effect and explored the mechanisms of a TCM formula Yangyinwenyang (YYWY) in non-small cell lung cancer (NSCLC) models. YYWY induced the apoptosis of lung cancer cells in vitro. In Lewis NSCLC-bearing mice model, YYWY significantly inhibited the tumor growth. Further, RNA-seq analysis and immunostaining of the tumor tissue implied the critical role of YYWY in the regulation of immune response, especially the dendritic cells (DCs) in the effect of YYWY. Therefore, we focused on DCs, which were the initiator and modulator of the immune response. YYWY facilitated the maturation of DCs through MAPK and NF-κB signaling pathways and promoted the release of the cytokines IFN-γ, interleukin (IL)-1β, IL-2, IL-12, and tumor necrosis factor (TNF)-α by DCs. Moreover, the YYWY-matured DCs enhanced the proliferation of T cells and promoted the differentiation of T cells into T helper Th1 and cytotoxic T cell (CTL). In addition, YYWY increased the ratio of Th1/Th2 (IFN-γ/IL-4 radio). Collectively, our findings clearly suggested that YYWY exerted an anti-tumor effect on NSCLC, at least partially through facilitating the mature DCs to activate the proliferation and differentiation of T cells.

Integrated Transcriptome Analysis Reveals KLK5 and L1CAM Predict Response to Anlotinib in NSCLC at 3rd Line

The oral multi-targeted tyrosine kinase inhibitor (TKI) anlotinib is effective for non-small cell lung cancer (NSCLC) in clinical trials at 3rd line. However, a fraction of patients remains non-responsive, raising the need of how to identify anlotinib-responsive patients. In the present study, we aimed to screen potential biomarkers for anlotinib-responsive stratification via integrated transcriptome analysis. Comparing with the anlotinib-sensitive lung cancer cell NCI-H1975, we found 1,315 genes were differentially expressed in anlotinib-resistant NCI-H1975 cells. Among the enriched angiogenesis-related genes, we observed high expression of KLK5 and L1CAM was mostly associated with poor clinical outcomes in NSCLC patients through Kaplan-Meier survival analysis in a TCGA cohort. Moreover, an independent validation in a cohort of ALTER0303 (NCT02388919) indicated that high serum levels of KLK5 and L1CAM were also associated with poor anlotinib response in NSCLC patients at 3rd line. Lastly, we demonstrated that knockdown of KLK5 and L1CAM increases anlotinib-induced cytotoxicity in anlotinib-resistant NCI-H1975 cells. Collectively, our study suggested serum levels of KLK5 and L1CAM potentially serve as biomarkers for anlotinib-responsive stratification in NSCLC patients at 3rd line.

Herbal formula Yangyinjiedu induces lung cancer cell apoptosis via activation of early growth response 1

Traditional Chinese Medicine (TCM) has been extensively used in clinical practices and proven to be effective against cancer. However, the underlying mechanisms remain to be investigated. In this study, we examined the anticancer activities of Chinese herbal formula Yangyinjiedu (YYJD) and found that YYJD exhibits cytotoxicity against lung cancer cells. Transcriptome analysis indicated that 2178 genes were differentially expressed (P < 0.05) upon YYJD treatment, with 1464 being (67.2%) up‐regulated. Among these, we found that the tumour suppressor early growth response 1 (EGR1) is the most activated. We demonstrated that EGR1 contributes to YYJD‐induced apoptosis in A549. Through dissecting EGR1‐associated transcriptional network, we identified 275 genes as EGR1 direct targets, some targets are involved in apoptosis. Lastly, we observed that YYJD enhances EGR1 expression and induces cell death in tumour xenografts. Collectively, these findings suggest that YYJD exerts its anticancer activities through EGR1 activation, thus providing the evidence for its potential clinical application for lung cancer patients.

Transcriptome profiling analysis reveals that CXCL2 is involved in anlotinib resistance in human lung cancer cells

BACKGROUND

Anlotinib has been demonstrated its anti-tumor efficacy on non-small cell lung cancer (NSCLC) in clinical trials at 3rd line. However, anlotinib resistance occurs during its administration, and the underlying mechanism is still unclear.

METHODS

Anlotinib resistant lung cancer cell line NCI-H1975 was established in vitro. Toxicologic effects undergoing anlotinib stress were observed upon NCI-H1975 cells and anlotinib resistant NCI-H1975 cells, respectively. Transcriptome profiling was performed to screen anlotinib resistance-associated genes between NCI-H1975 cells and anlotinib resistant NCI-H1975 cells. Functional assays were performed to examine the correlations between CXCL2 gene expression and anlotinib resistance.

RESULTS

We found anlotinib inhibits cell proliferation and cell viability in NCI-1975 cells, whereas it attenuates these activities in anlotinib resistant NCI-H1975 cells. Transcriptome profiling analysis identified 769 anlotinib-responsive genes enriched in the biological processes of microtubule-based process, cytoskeleton organization, and wound healing. Furthermore, we found 127 genes are associated with anlotinib resistance. In particular, we demonstrated that CXCL2 contributes to anlotinib resistance in NCI-H1975 cells.

CONCLUSIONS

This study suggested that CXCL2 is involved in anlotinib resistance in NCI-H1975 cells and provided an insight for understanding the resistant mechanism of anlotinib.