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ObjectiveTo explore the active ingredients， therapeutic targets， and relative signaling pathways of Tripterygium wilfordii in the treatment of triple negative breast cancer （TNBC） based on network pharmacology， and to verify the mechanism through in vitro cell model. MethodThe active ingredients of T. wilfordii were screened from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP）. The targets of TNBC were obtained from DisGeNET and GeneCards. Venny was used to identify the potential therapeutic targets of T. wilfordii against TNBC. Protein-protein interaction （PPI） network was constructed with String database. Gene ontology （GO） annotation and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment were carried out with DAVID to predict the mechanisms of potential targets. The molecular docking between triptolide and key targets were performed with AutoDock Vina. The effect of triptolide （0， 5， 10， 20， 30， 40， 50， 60， 80 nmol·L-1） on the proliferation of MDA-MB-231 cells was determined through methyl thiazolyl tetrazolium （MTT） assay. The effect of triptolide （0， 12.5， 25， 50 nmol·L-1） on the apoptosis of MDA-MB-231 cells was detected with Hoechst 33342 staining. Western blot was performed to detect the effect of triptolide （0， 25， 50 nmol·L-1） on the expression levels of key targets. ResultT. wilfordii had 23 active ingredients related to 55 potential targets of TNBC. GO and KEGG enrichment revealed that the potential targets were associated with 103 biological processes， 15 cellular components， and 35 molecular functions， and were involved in 140 signaling pathways including atherosclerosis and apoptosis. The results of molecular docking demonstrated that triptolide could bind with the targets including threonine kinase 1 （Akt1）， vascular endothelial growth factor A （VEGFA）， cellular tumor antigen p53 （p53）， transcription factor AP-1 （JUN）， signal transducer and activator of transcription 3 （STAT3）， tumor necrosis factor （TNF）， mitogen-activated protein kinase 8 （MAPK8）， prostaglandin G/H synthase 2 （PTGS2）， and Caspase-3. According to the results of MTT assay， triptolide （20， 30， 40， 50， 60， 80 nmol·L-1） inhibited the proliferation of MDA-MB-231 cells compared with blank control （P<0.05， P<0.01）. Hoechst 33342 staining showed that triptolide （12， 25， 50 nmol·L-1） induced the apoptosis of MDA-MB-231 cells compared with black control （P<0.05， P<0.01）. Western blot showcased that 50 nmol·L-1 triptolide down-regulated the relative expression levels of p-Akt， TNF-α， and VEGFA， while 25 and 50 nmol·L-1 triptolide up-regulated the relative expression level of p53 in a dose-dependent manner compared with the blank control （P<0.05， P<0.01）. ConclusionT. wilfordii has multiple ingredients， targets， and pathways in the treatment of TNBC. It may regulate p53， VEGFA， TNF-α and other key targets to induce cell apoptosis and suppress angiogenesis and inflammatory response， which provides a scientific basis for the further investigation and clinical application of T. wilfordii.
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Aim To observe the inhibitory effect of neferine(Nef)on the migration and invasion of non-small cell lung cancer(NSCLC)H1299 cells by blocking ROCK pathway.Methods H1299 cells were taken for in vitro culture, and treated with different concentrations of Nef.H1299 cell viability was measured by CCK-8 method to determine the dose of the experimental group.The migration and invasion abilities of H1299 cells were detected by cell scratch test and Transwell chamber test.The expression of matrix metalloproteinases MMP-2 and MMP-9 secreted from lung cancer cells was detected by enzyme linked immunosorbent assay(ELISA).The protein level of ROCK1 in H1299 cells was tested by real-time fluorescent quantitative PCR and Western blot; the binding mode and affinity between Nef and ROCK1 were stimulated by AutoDock semi flexible docking method.Results The doses of Nef in the experimental group were determined as 4, 6 and 10 μmol·L-1.These three concentrations of Nef could inhibit the migration and invasion of H1299 lung cancer cells to a certain degree in a dose-dependent manner.At the same time, Nef reduced the expression of MMP-2, MMP-9 and ROCK1 proteins related to the migration and invasion of the cancer cells.In addition, the affinity of Nef to ROCK1 was significantly higher than that of fasudil, an inhibitor of ROCK, and the binding force was stronger to A-chain of ROCK1.Conclusions As a potential natural anticancer compound, Nef can inhibit the migration and invasion of NSCLC by reducing the expression of MMP-2, MMP-9 and ROCK1 proteins related to the migration and invasion of the cancer cells.
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Objective: To investigate the current status and real performance of the detection of RUNX1-RUNX1T1 fusion transcript levels and WT1 transcript levels in China through interlaboratory comparison. Methods: Peking University People's Hospital (PKUPH) prepared the samples for comparison. That is, the fresh RUNX1-RUNX1T1 positive (+) bone morrow nucleated cells were serially diluted with RUNX1-RUNX1T1 negative (-) nucleated cells from different patients. Totally 23 sets with 14 different samples per set were prepared. TRIzol reagent was added in each tube and thoroughly mixed with cells for homogenization. Each laboratory simultaneously tested RUNX1-RUNX1T1 and WT1 transcript levels of one set of samples by real-time quantitative PCR method. All transcript levels were reported as the percentage of RUNX1-RUNX1T1 or WT1 transcript copies/ABL copies. Spearman correlation coefficient between the reported transcript levels of each participated laboratory and those of PKUPH was calculated. Results: ①RUNX1-RUNX1T1 comparison: 9 samples were (+) and 5 were (-) , the false negative and positive rates of the 20 participated laboratories were 0 (0/180) and 5% (5/100) , respectively. The reported transcript levels of all 9 positive samples were different among laboratories. The median reported transcript levels of 9 positive samples were from 0.060% to 176.7%, which covered 3.5-log. The ratios of each sample's highest to the lowest reported transcript levels were from 5.5 to 12.3 (one result which obviously deviated from other laboratories' results was not included) , 85% (17/20) of the laboratories had correlation coefficient ≥0.98. ②WT1 comparison: The median reported transcript levels of all 14 samples were from 0.17% to 67.6%, which covered 2.6-log. The ratios of each sample's highest to the lowest reported transcript levels were from 5.3-13.7, 62% (13/21) of the laboratories had correlation coefficient ≥0.98. ③ The relative relationship of the reported RUNX1-RUNX1T1 transcript levels between the participants and PKUPH was not always consistent with that of WT1 transcript levels. Both RUNX1-RUNX1T1 and WT1 transcript levels from 2 and 7 laboratories were individually lower than and higher than those of PKUPH, whereas for the rest 11 laboratories, one transcript level was higher than and the other was lower than that of PKUPH. Conclusion: The reported RUNX1-RUNX1T1 and WT1 transcript levels were different among laboratories for the same sample. Most of the participated laboratories reported highly consistent result with that of PKUPH. The relationship between laboratories of the different transcript levels may not be the same.