Recent studies have reported that TUBB3 overexpression is involved in docetaxel (DTX) resistance in prostate cancer (PCa). The aim of this study was to clarify the role of TUBB3 in DTX and cabazitaxel (CBZ) resistance, and cross-resistance between DTX and CBZ in PCa. We analyzed the effect of TUBB3 knockdown on DTX and CBZ resistance and examined the interaction between TUBB3 and PTEN. We also investigated the role of phosphoinositide 3-kinases (PI3K) inhibitor (LY294002) in DTX and CBZ resistance. TUBB3 expression was upregulated in DTX-resistant and CBZ-resistant cells. TUBB3 knockdown re-sensitized DTX-resistant cells to DTX and CBZ-resistant cells to CBZ. Additionally, TUBB3 knockdown re-sensitized DTX-resistant cell lines to CBZ, indicating that TUBB3 mediates cross-resistance between DTX and CBZ. Knockdown of TUBB3 enhanced PTEN expression, and PTEN knockout enhanced TUBB3 expression. LY294002 suppressed TUBB3 expression in DTX-resistant and CBZ-resistant cell lines. LY294002 re-sensitized DTX-resistant cell lines to DTX and CBZ-resistant cell lines to CBZ. These results suggest that TUBB3 is involved in DTX resistance and CBZ resistance. A combination of LY294002/DTX and that of LY294002/CBZ could be potential strategies for PCa treatment. Prostate cancer (PCa) is the most common solid malignancy among men and the second leading cause of cancer-related death in developed countries . AlthougTUBB3 gene is a microtubule protein normally expressed in neuronal cells. A recent study has shown TUBB3 to be associated with the progression of CRPC [Taxanes block cell mitosis and induce apoptosis in tumor cells by targeting microtubule activity . Microtu of CRPC . What is of CRPC ,12,13. T of CRPC . Another of CRPC ,16. CollIn this study, we use DTX- and CBZ-resistant PCa cell lines to analyze the involvement of TUBB3 in, and the effect of TUBB3 knockdown on, DTX and CBZ resistance in PCa cell lines. We also investigate the effect of LY294002 in these DTX- and CBZ-resistant PCa cell lines.We used two DTX-resistant  ,18,19 anGiven the previous reports that TUBB3 is associated with cancer progression and DTX resistance in PCa ,14, we sWe next analyzed whether knockdown of TUBB3 improves DTX and CBZ sensitivity in DTX- and CBZ-resistant PCa cells. We measured cell viability in DU145-DR and C4-2-DR cells with knockdown of TUBB3 under various concentrations of DTX. Western blotting showed that the expression of TUBB3 was suppressed in DU145-DR and C4-2-DR cells transfected with small interfering RNAs (siRNAs) for TUBB3 compared with that in DU145-DR and C4-2-DR cells transfected with siRNAs for negative control A. We fouPTEN and TUBB3 in 28 PCa tissues by qRT-PCR. There was a significant inverse correlation between PTEN and TUBB3  (TUBB3 was significantly associated with a high Gleason score (p = 0.048) and high tumor stage (p < 0.001)  A. In thi< 0.001) B. We als< 0.001) C. Furthe< 0.001) D. PTEN k< 0.001) E. These It is often reported that PTEN loss or activation of the phosphoinositide 3-kinases (PI3K)/AKT pathway leads to progression of CRPC ,25. TherDTX is the first-line therapy for patients with metastatic CRPC. Recent clinical studies have shown that early DTX treatment with androgen deprivation therapy leads to better overall survival in comparison to androgen deprivation therapy alone in patients with metastatic hormone-sensitive PCa ,33. CBZ Recently, several studies reported that cross-resistance exists between DTX and CBZ treatment in PCa cell lines ,7,34. InPTEN loss is an early and stable event in the carcinogenesis process and is associated with poor prognosis in PCa. The expression of PTEN is regulated by mutations, epigenetic and transcriptional silencing, post-translational regulation, and protein–protein interactions . Some stLY294002 is a synthetic compound that was designed as a PI3K inhibitor . SeveralThere are some limitations in this study. We performed qRT-PCR analysis for PTEN and TUBB3 expression in a relatively small sample size, and the samples were not derived from CRPC patients. Therefore, a study with a larger number of CRPC patients will be necessary to verify the current findings. Second, we showed that the combination of LY294002 with DTX or CBZ had higher efficiency than DTX or CBZ alone chemotherapy. However, we did not clarify whether the combination is synergistic or additive. Third, so far, several PI3K inhibitors have been reported, and several clinical trials using PI3K inhibitors are ongoing . FurtherIn summary, we showed that the expression of TUBB3 was upregulated in DTX- and CBZ-resistant cells in PCa. TUBB3 was involved in both DTX resistance and CBZ resistance. There was a reciprocal interaction between TUBB3 and PTEN in PCa. TUBB3 mediated cross-resistance between DTX and CBZ. LY294002 re-sensitized cells resistant to DTX treatment and also re-sensitized cells resistant to CBZ treatment. The data presented here highlight the great potential of combination therapy of LY294002 with DTX and that of LY294002 with CBZ in chemotherapy for PCa.2 and 95% air at 37 °C. DTX-resistant PCa cell lines were cultured under DTX (DU145: 2 ng/mL and C4-2-DR: 5 ng/mL). CBZ-resistant cell lines were cultured under CBZ (LNCaP-CR: 2 ng/mL and 22Rv-1-CR: 5 ng/mL).Four PCa cell lines , two DTX-resistant PCa cell lines  and two CBZ-resistant PCa cell lines  were kindly provided by Masaki Shiota . DU145 cells were maintained in MEM . LNCaP, C4-2, and 22Rv-1 cells were maintained in RPMI 1640  containing 10% fetal bovine serum , 2 mM L-glutamine, 50 U/mL penicillin, and 50 g/mL streptomycin in a humidified atmosphere of 5% CODTX, CBZ, and LY294002 were obtained from Funakoshi . An MTT assay was performed to analyze drug sensitivities as described previously . At 24 hFor Western blotting analysis, cells were lysed as described previously . PrimaryExtraction of total RNA, synthesis of cDNA, and qRT-PCR were performed as described previously . Total RWe obtained 28 PCa tissue samples for qRT-PCR. The clinicopathologic features are summarized in Silencer® Select  against TUBB3 was used for RNA interference. Two independent oligonucleotides and negative control siRNA  were used .To knock out PTEN in DU145 and 22Rv-1 cells, we used CRISPR-Cas9 technology, which was performed as described previously [t-test or Mann–Whitney U test. A p-value of <0.05 was considered statistically significant. Statistical analyses were conducted primarily using GraphPad Prism software .Statistical differences were evaluated using the two-tailed Student’s


Our appreciation of the critical role of the genome’s 3D organization in gene regulation is steadily increasing. Recent 3C-based deep sequencing techniques elucidated a hierarchy of structures that underlie the spatial organization of the genome in the nucleus. At the top of this hierarchical organization are chromosomal territories and the megabase-scale A/B compartments that correlate with transcriptional activity within cells. Below them are the relatively cell-type-invariant topologically associated domains (TADs), characterized by high frequency of physical contacts between loci within the same TAD, and are assumed to function as regulatory units. Within TADs, chromatin loops bring enhancers and target promoters to close spatial proximity. Yet, we still have only rudimentary understanding how differences in chromatin organization between different cell types affect cell-type-specific gene expression programs that are executed under basal and challenged conditions.Here, we carried out a large-scale meta-analysis that integrated Hi–C data from thirteen different cell lines and dozens of ChIP-seq and RNA-seq datasets measured on these cells, either under basal conditions or after treatment. Pairwise comparisons between cell lines demonstrate a strong association between modulation of A/B compartmentalization, differential gene expression and transcription factor (TF) binding events. Furthermore, integrating the analysis of transcriptomes of different cell lines in response to various challenges, we show that A/B compartmentalization of cells under basal conditions significantly correlates not only with gene expression programs and TF binding profiles that are active under the basal condition but also with those induced in response to treatment. Yet, in pairwise comparisons between different cell lines, we find that a large portion of differential TF binding and gene induction events occur in genomic loci assigned to A compartment in both cell types, underscoring the role of additional critical factors in determining cell-type-specific transcriptional programs.Our results further indicate the role of dynamic genome organization in regulation of differential gene expression between different cell types and the impact of intra-TAD enhancer–promoter interactions that are established under basal conditions on both the basal and treatment-induced gene expression programs.The online version of this article (10.1186/s13072-018-0220-2) contains supplementary material, which is available to authorized users. E) and promoters (P) that are located at high distance along the linear DNA sequence to close spatial proximity. Such E–P loops, a portion of which is cell type specific, mostly occur within TADs and unfrequently cross over TAD boundaries [3C-based methods measure the frequency of physical interactions between any pair of genomic loci as a proxy for their spatial proximity. These novel technologies are shedding light on the principles of 3D organization of the genome in the nucleus and its relation to gene regulation –3. A fouundaries , 10. TheOur understanding of the roles that the 3D organization of the genome plays in gene regulation has markedly increased in recent years. It emerges that TADs serve as fundamental structural and regulatory building blocks of chromosomes that constrain and largely exclude physical interactions between genes and regulatory elements located in different TADs, while providing sufficiently dynamic local environment that is required for the establishment of intra-TAD E–P links , 8. In lIntra-TAD E–P links are required for the implementation of transcriptional programs that establish and maintain cell identity and responses to environmental cues. How these regulatory interactions are modulated in response to transient perturbation is still not well understood. While some studies have shown that gene induction is accompanied by alterations of chromatin interactions and internal restructuring of TADs –14, unexHere, we carried out a large-scale meta-analysis, integrating Hi–C data from 13 different cell lines and dozens of ChIP-seq and RNA-seq datasets recorded in the same cellular systems at basal conditions and in response to various treatments, to further elucidate the intricate interplay between the hierarchical 3D organization of the genome and gene regulation.We first defined the higher-order organization of the genome into A/B compartments for 13 human cell lines for which Hi–C data are available  implies that binding sites are enriched for the A compartment and D < 1  implies that binding sites are enriched for B compartment; “As the A compartment is associated with open state of the chromatin we next systematically examined the association between A/B compartmentalization and TF binding. We analyzed 122 TF ChIP-seq datasets recorded by ENCODE for cell lines with Hi–C data  The strongest effect was observed for EP300, a transcriptional activator that marks active enhancers. In the analysis of other pairs of cell lines, we found a similar significant preference of cell-type-specific TF binding events for cell-type-specific A compartment . For each pair of cell lines, we divided the genes into four groups, based on RNA Pol-II ChIA-PET data: no promoter interactions in both cells (“00” group); promoter interactions detected only in cell line 1 (“10” genes); only in cell line 2 (“01” genes) and in both (“11” genes). Notably, differential gene expression between pairs of cell lines was strongly associated with differential engagement of promoters in chromatin interactions . Several experiments that examined responses to TNF-α and estradiol met this requirement. For each pair of cell lines treated by the same agent and profiled for the same TF, we again divided the induced TFBSs into three groups: binding sites induced upon treatment only in cell line 1, binding sites induced only in cell line 2, and binding sites induced in both. Induced TFBSs in each group were then divided into four categories—AA, AB, BA, and BB as defined above. In all comparisons, TFBSs induced only in cell line 1 showed a significant preference for AB regions over the BA ones, and vice versa for TFBSs induced only in cell line 2  and 32 out of 34 experiments had enrichment factor larger than 1.0 . For each cell line and treatment, we tested whether the set of genes that were induced upon treatment was over-represented in the A compartment . Indeed, in most conditions, we observed a significant preference of the induced genes to the A compartment  . We followed the same analysis that we applied above to TFBSs that were induced in a cell-type-specific manner Table , and appTo further explore links between the 3D organization of the genome and gene regulation, we have analyzed together Hi–C data from 13 different human cell lines and numerous ChIP-seq and RNA-seq experiments that were recorded in the same cell lines under basal conditions and in response to various treatments. We first confirmed the strong relationship between the partition of the genome into the A/B compartments and transcriptional activity. In all cell lines, expression level of genes located within the A compartment was significantly higher than expression level of genes located in B Fig. . SimilarUsing E–P links derived from Hi–C and ChIA-PET data, we found, for genes located within the A compartment, a significant correlation between gene expression levels and the extent to which promoters are engaged in chromatin interactions. This association was most pronounced in the comparison between genes with no interaction at all and those that have at least one Fig. . MoreoveWe then turned to analyze the association between the organization of the genome under basal conditions and transcriptional programs that are induced in response to various triggers. First, we showed that, typically, both induced TF binding events and induced genes are enriched in the A compartment Fig. a, c, sugCurrent techniques for determining the 3D organization of the genome are still limited in their resolution and sensitivity. Further development of these methods together with advances in their application to single cells will allow us to better understand how the genome organization in different cells is causally linked to cell-type-specific transcriptional programs both under basal conditions and in response to various challenges.Collectively, the large-scale meta-analysis that we carried out in this study further demonstrates the strong association between cell-type-specific A/B compartmentalization, modulation of landscape of TF-chromatin interactions, and differential gene expression. Moreover, our results further suggest a role for the 3D organization of the genome under basal conditions, at the layers of both A/B compartmentalization and intra-TAD enhancer–promoter interactions, in shaping TF binding events and the network of genes that are induced in response to treatment. Yet, our pairwise comparisons also show that most events of differential TF binding and gene induction occur in genomic loci assigned to A compartment in both cell types, underscoring the role of additional critical factors in determining transcriptional programs that are active in each cell type.We defined A/B compartments for 13 human cell lines for which Hi–C data are available  using TopHat2 . The numTo ensure analysis uniformity, we did not rely on peaks called by original studies, but downloaded raw sequence data and detected TF peaks ourselves. Briefly, for each ChIP-seq experiment, reads were aligned to the human genome (hg19) using Bowtie2  and peakAB density factor, D, defined as follows: Let the number of observed binding sites in region S be O(S) and number of expected binding sites in region S be E(S):D > 1 implies that binding sites are enriched for A compartment, and D < 1 implies that binding sites are enriched for B compartment. For TF binding sites, E(A)/E(B) is equal to the ratio between the genomic size of the two compartments. For induced genes, E(A)/E(B) is equal to the ratio between the number of genes located within these two compartments.For each transcription factor and cell line we computed the AB occupancy enrichment ratio R, as follows: Let the number of BSs in region S occurring only in cell line i be For pairwise comparisons between cells, to test whether cell-type-specific TFBSs occur more often in regions assigned as A compartment in the cell line where the binding event was detected and as B in the other cell line than the opposite assignment, we defined the Additional file 1: Table S1. Hi-C datasets. Table S2. Encode ChIP-seq data included in our analyses (122 TFs profiled in cell lines with Hi-C data). Table S3. Enrichment of CTCF binding sites for the A compartmentalization. Table S4A. Enrichment of cell-type-specific H3K9ac events for cell-type-specific A compartment over B compartment. Table S4B. Enrichment of cell-type-specific H3K27me3 events for cell-type-specific B compartment over A compartment. Table S5. Preference of induced TF binding sites and epigenetic marks to the A compartment. Table S6. Binding site induction and compartmentalization in two cell lines under the same treatment, for a particular TF. Table S7. Preference of induced genes to the A compartment. Table S8. Promoters of induced genes are involved, in basal condition, in higher numbers of chromatin interactions. Table S9. Preference of cell-type-specific induced genes to cell-type-specific A compartment.Additional file 2: Fig. S1. Correlation between the magnitude of the PC that represents A/B compartmentalization and gene expression level. Fig. S2. Association between changes in A/B compartmentalization and differential gene expression between cell types. A. For each pair of cell lines, we examined the difference (fold change) in expression level between genes assigned to the AB and BA sets . For 27 out of 28 pairwise comparisons , we observed a highly significant association (FDR ≪ 5%) between differential compartmentalization and expression.  B. Correlation between the change in the magnitude of PC1 and change in gene expression level in the comparison between GM12878 and four other cell lines. Fig. S3. Enrichment of TFBSs in the A compartment. ChIP-seq experiments are sorted by p value, and A-B density factors are represented by bars. Red line indicates p value = 0.01. Shown are experiments in the GM12878 cell line. Similar results were observed for all other cell lines (data not shown). Fig. S4. Preference of cell-type-specific TF binding for cell-type-specific compartments. Preference of cell-type-specific TF binding events to AB genomic regions over BA regions is measured by the AB occupancy enrichment ratio. The compared cell lines and the examined TF are indicated below each bar . Fig. S5. Enrichment of histone modifications in the A/B compartments. The analysis presented in Fig. S3 for TF binding events is applied here to histone modification peaks. Most modifications showed a significant enrichment for the A compartment. The repressive marks H3K27me3 and H3K9me3 showed markedly lower enrichment, and the latter was even significantly enriched in the B compartment (in HMEC and HUVEC cell lines). Fig. S6. Gene expression levels vs. promoter interactions in compartment A. The same analyses described in the legend of Fig. 4A-D are applied here to additional cell lines. Fig. S7. Enrichment of treatment-induced genes in the basal A compartment. The same analysis as in Fig. 6C, but calling differential genes based on FDR of 5% (rather than based on fold change criterion).


MPNSTs) are an aggressive form of soft tissue neoplasm with extremely poor prognosis and no effective medical options currently available. MPNSTs can occur either sporadically or in association with the neurofibromatosis type 1 (NF1) syndrome. Importantly, activation of RAS/RAF/MEK/ERK, PI3K/AKT/mTOR, and WNT/CTNNB1 signaling pathways has been reported in both NF1‐related and late‐stage sporadic MPNSTs. In this study, we found that DAW22, a natural sesquiterpene coumarin compound isolated from Ferula ferulaeoides (Steud.) Korov., could inhibit cell proliferation and colony formation in five established human MPNST cancer cell lines. Further molecular mechanism exploration indicated that DAW22 could target the main components in the MPNST tumorigenic pathways: namely suppress phosphorylation of AKT and ERK, and reduce levels of non‐phospho (active) CTNNB1. Using the xenograft mouse model transplanted with human MPNST cancer cell line, daily treatment with DAW22 for 25 days was effective in reducing tumor growth. These results support DAW22 as an alternative therapeutic compound for MPNST treatment by affecting multiple signaling transduction pathways in its disease progression.Malignant peripheral nerve sheath tumors ( Cooperating genes enriched in the PI3K/AKT/mTOR, mitogen‐activated protein kinase (MAPK), and WNT/CTNNB1 transduction pathways have been implicated in MPNST disease initiation and progression, as well as the main regulators in mediating cell cycle, cell division, and cell death.Therapeutic drugs used in preclinical and clinical trials for the treatment of MPNSTs currently include mTOR inhibitors and its derivatives (such as everolimus and temsirolimus), with varied response on tumor growth inhibition when combined with other candidate drugs.Ferula ferulaeoides (Steud.) Korov., has been reported to trigger glioma cell apoptosis in vitro.DAW22, a natural sesquiterpene coumarin compound isolated from the 22.1Ferula ferulaeoides (Steud.) Korov. according to previous methods.DAW22 was isolated from the root of the 2.2AKT inhibitor AZD5363 was prepared as a 100 mmol/L stock solution in DMSO.2.32. The identity of these cell lines was verified by short tandem repeats profile comparison. All the cell lines were also tested and found to be negative for mycoplasma contamination using MycoFluor™ Mycoplasma Detection Kit (Thermo Fisher Scientific).MPNST cell lines including STS‐26T,2.4MPNST cell lines were plated onto 96‐well plates at a concentration of 6000 cells per well. After 24 hours, cells were treated with either vehicle control or designated doses of DAW22 for 48 hours. The cell viability was quantified by CellTiter 96 AQueous One Solution Cell Proliferation Assay (MTS) . The cell viability assays were performed and analyzed using the Opera Phenix high‐content imaging system .2.5MPNST cell lines were seeded onto six‐well plates at a density of 1000 cells per well. After 24 hours, the medium was removed and replaced with either vehicle control or DAW22‐containing medium for 2 weeks to allow for colony growth. Following 2 weeks, media were removed and cells were fixed with 4% paraformaldehyde in phosphate‐buffered saline (PBS) for 15 minutes and stained with 0.1% crystal violet solution in PBS for 10 minutes, followed by repeated washing with PBS.2.6MPNST cell lines were seeded onto six‐well plates, followed by treatment with an indicated concentration of DAW22 for 24 hours. Next, cells were fixed with 70% ice‐cold ethanol in PBS, stained with propidium iodide , and analyzed by flow cytometer.2.7Protein was isolated from DAW22‐treated MPNST cell lines using the Qproteome Mammalian Protein Prep Kit  following the manufacturer's instructions. Concentrations of protein were determined by Bradford Protein Assay  followed by denaturation as described by the manufacturer. Protein was separated on a 12% SDS‐PAGE gel and transferred to polyvinylidene difluoride (PVDF) membrane . Protein on the membrane was first incubated with indicated primary antibodies at 4°C overnight, followed by corresponding secondary antibodies’ incubation at room temperature for 1 hour. Targeted proteins were detected using a horseradish peroxidase‐conjugated chemiluminescent kit (Millipore). AKT (#2920), phospho‐AKT (#4060), ERK (#4695), phospho‐ERK (#4370), poly(ADP‐ribose) polymerase 1 (PARP) (#9532), Non‐phospho (active) CTNNB1 (#8814), caspase 3 (CASP3), and ACTB (#4970), with the exception for CASP3 that was purchased from Santa Cruz Biotechnology , remaining primary antibodies were from Cell Signaling Technology . ACTB was used as the loading control.2.86 STS‐26T cells in 0.1 mL PBS containing 50% Matrigel . One week later, mice were randomly divided into two groups and treated with either vehicle or DAW22 at a dose of 60 mg/kg/d for 25 days by daily intraperitoneal injection. Body weights and tumor sizes were measured every 3 days. At the experimental end point (25 days) and upon necropsy, tumor sizes and weights were measured for each mouse. All animal studies were approved by the appropriate ethics committee and performed in accordance with the ethical standards stipulated by both The Hong Kong Polytechnic University and The Chinese University of Hong Kong.Six‐week‐old immunocompromised nude mice  were anesthetized with ketamine and each flank injected subcutaneously with 2 × 102.9Tissues were carefully removed from the sacrificed animal, weighed, washed, and placed in cold PBS. Formalin‐fixed paraffin‐embedded sections from various tissues were sectioned at 5 μm using a standard microtome , mounted, and heat‐fixed onto glass slides. Tissue section slides were either processed and stained with hematoxylin and eosin (HE) using standard protocols.2.10t test and ANOVA in Prism were used for statistical analyses. Value of P < 0.05 was considered as statistically significant.Raw data were analyzed using GraphPad Software Prism , and resulting values were expressed as mean ± standard error of the mean (SEM). Student's 33.1The therapeutic potential of DAW22, structure shown in Figure 50) in these five cell lines ranged from 30.42 to 46.73 μmol/L   Figure D. In ord) Figure E.4With a high rate of metastases and extremely poor prognosis, MPNSTs represents one of the most difficult‐to‐cure sarcoma. Currently, there are no effective drugs for the treatment of MPNST and surgical resection remains the most effective means of therapy, but this method is limited due to the close proximity of the affected peripheral nerves with other tissues. Better therapeutic regimes for MPNST require a greater understanding of the genetic mechanisms associated with the disease. As precision medicine becomes more important for cancer therapy, identification of accurate therapeutic targets and discovery of specific drugs to control cancer development are becoming ever more critical.Ferula ferulaeoides (Steud.) Korov., inhibited cell proliferation in both sporadic and NF1‐related MPNST cell lines at varied doses. ST8814 and T265 cell lines have a IC50 of about 45 μmol/L, compared with STS‐26T, S462, and S462‐TY cell lines, where the IC50s were around 30 μmol/L. The differences might be caused by their distinct genetic backgrounds  tumor suppressor gene,NF1 deficiency, and activated AKT‐mTOR signaling,50 concentration as S462 cells, as S462‐TY was derived from a xenograft passage of S462.TP53 expression in STS‐26T cells was completely absent,50 concentration. Cell cycle was not influenced by DAW22 based on our cell cycle assay results . This could be paraptosis‐like cell death, which could further contribute to the anti‐cancer effect. However, the molecular mechanism(s) associated with paraptosis remains to be elucidated.In our study, DAW22, a compound isolated from the plant  Figures . The apoAccumulating evidence indicated several pathways are highly related with MPNST transformation ability. NF1‐related MPNST cancer patients have activated RAS signaling, which subsequently cause activation of PI3K/AKT/mTOR and MAPK pathways. Sporadic MPNST patients also showed mutations in these pathways at the advanced disease stages. Moreover, significant activation of WNT/CTNNB1 pathway has been shown to drive human Schwann cell transformation and tumor maintenance in development of MPNST. The important roles of these pathways were further validated using inhibitors targeting AKT, mTOR, MEK, and WNT pathways either singly or in combinations.50s of AKT inhibitor AZD5363 in MPNST cancer cell lines (Figure Here, we demonstrated that DAW22 inhibited phosphorylation of AKT, ERK, and active form of CTNNB1. The data indicated that DAW22 could target multiple signaling pathways involved in MPNST disease progression Figure . In addis Figure . As AKT,In summary, our current study showed that DAW22 inhibited both sporadic and NF1‐related MPNST cancer cell proliferation and induced apoptosis by targeting AKT, ERK, and CTNNB1 pathways. In addition, DAW22 delayed tumor growth of STS‐26T cell transplanted in xenograft mice, providing strong evidence for DAW22 as a potential novel alternative therapeutic treatment for patients with MPNST.The authors have no conflict of interest. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Candidatus Profftella armatura (Betaproteobacteria), an organelle-like defensive symbiont harbored by a plant sap-sucking insect, Asian citrus psyllid Diaphorina citri (Hemiptera: Liviidae). Diaphorin belongs to the pederin family, a group of compounds that share much of their core structure with that of pederin, which is characterized by two dihydropyran rings bridged by an N-acyl aminal. Most members of this family have potent antitumor activity, making them promising anticancer drug candidates. The present study assessed the therapeutic potential of diaphorin for its antitumor activity against 39 human cancer cell lines including those from breast, brain, colon, lung, skin, ovary, kidney, stomach, and prostate. The results showed that diaphorin had inhibitory activity against all 39 cancer cell lines tested. The GI50, TGI, and LC50 values ranged from 0.28 μM– 2.4 μM, 1.6 μM –11 μM, and 7.5 μM–> 100 μM, respectively. These values are among the highest in the pederin family, indicating that the anticancer activity of diaphorin is milder than those of other pederin congeners. The inhibitory effects of diaphorin significantly differed among the distinct cancer types. The maximum difference was about 10-fold, which was similar to those of most other pederin congeners.Diaphorin is a polyketide produced by  N-acyl aminal  heated to 35°C. The mobile phase was isocratic 20% acetonitrile in water, with a flow rate of 1.5 mL/min. Diaphorin was detected at a wavelength of 200 nm. The purified samples were combined and dried in vacuo. Diaphorin was re-dissolved in methanol and quantified in an HPLC system as described above, except the mobile phase was 15% acetonitrile in water, with a flow rate of 1.0 mL/min, and an Inertsil ODS-3 analytical column  was used.Diaphorin was extracted from escribed . Briefly2.The human cancer cell line panel prepared by the Japanese Foundation for Cancer Research  consisted of 39 cell lines as follows : breast −8, 10−7, 10−6, 10−5, or 10−4 M final concentration) of diaphorin were then added to each cell line. After 48 h of additional incubation at 37°C, the plates were fixed with TCA, stained with SRB, and read with an automated microplate reader at a wavelength of 515 nm. Percentage growth inhibition was calculated as:Inhibition of the growth of human cancer cell lines was assessed using a standard sulforhodamine B (SRB) assay as described previously . Briefly[(Ti-Tz)/(C-Tz)] × 100, when Ti≥Tz[(Ti-Tz)/Tz] × 100, when Ti<Tz50: 50% growth inhibition) was calculated from [(Ti-Tz)/(C-Tz)] × 100 = 50. The concentration of diaphorin resulting in total growth inhibition (TGI) was calculated from Ti = Tz. The concentration of diaphorin resulting in a 50% reduction of the number of cells at the end of the treatment as compared with that at the beginning  was calculated from [(Ti-Tz)/Tz] × 100 = -50.. The concentration of diaphorin resulting in a 50% reduction in the cell number increase as compared with the control  .−8, 10−7, 10−6, 10−5, and 10−4 M (p < 0.05). The concentrations of diaphorin required to exert the growth inhibitory activity were at the micromolar level, which is much higher than those reported for other members of the pederin family including pederin, mycalamides, onnamides, theopederins, psymberin, and their synthetic analogs that exhibit antitumor activity at nanomolar or even subnanomolar concentrations [O-desmethyl analog of pederin . The maximum difference was about 10-fold, which is similar to those observed for most other pederin congeners. Psymberin is the only exception to this within the pederin family thus far, showing more than a 10,000-fold difference in its inhibitory activity toward distinct cancer types. Indeed, several melanoma, breast, and colon cancer cell lines were highly sensitive (LC50 < 2.5 nM) to psymberin, whereas six leukemia cell lines were invariably insensitive (LC50 > 25 μM), indicating a >104-fold difference in inhibitory activities [The sensitivity toward diaphorin significantly differed among the distinct cancer types Click here for additional data file.


Cell mechanical properties have been identified to characterize cells pathologic states. Here, we report our work on high-throughput mechanical phenotyping of androgen-sensitive and non-sensitive human prostate cancer cell lines based on a morphological rheological microfluidic method. The theory for extracting cells’ elastic modulus from their deformation and area, and the used experimental parameters were analyzed. The mechanical properties of three types of prostate cancer cells lines with different sensitivity to androgen including LNCaP, DU145, and PC3 were quantified. The result shows that LNCaP cell was the softest, DU145 was the second softest, and PC3 was the stiffest. Furthermore, atomic force microscopy (AFM) was used to verify the effectiveness of this high-throughput morphological rheological method. Prostate cancer is a commonly diagnosed cancer and the second leading cause of cancer-related death in men ,2,3. TheThere has been increasing evidence that mechanical properties of cells can be used as label-free markers to determine cell physiology or pathology, such as cell metastatic potential, and differentiation degree ,11,12,13In order to reveal the underlying difference in mechanical properties between androgen-sensitive and androgen-non-sensitive prostate cancer cells lines, this morphological rheological method was utilized to quantify the mechanical properties of three types of prostate cancer cells lines  at a high-throughput of over 100 cells/s. The results show that androgen-non-sensitive prostate cancer cells line PC3 and DU145 are stiffer than androgen-sensitive prostate cancer cells line LNCaP, which suggests that the mechanical properties of prostate cancer cells can be used as potential biomarkers for early identification of androgen-independent prostate cancer.A silicon-based mask manufactured using a traditional lithography process was utilized to fabricate the polydimethylsiloxane (PDMS)-based chip. The PDMS layer was manufactured as follows: the prepolymer mixed with the curing agents  in a ratio of 10:1 was poured into the prefabricated mask and cured for 30 min at 80 °C. Then the cured PDMS film was carefully peeled off and bonded with a glass substrate through an oxygen plasma process . In this study, the constriction channel on the microfluidic chip possessed a length of 300 μm and a cross-section of 25 μm × 25 μm. The size of the channel was larger than the measured cells which have an averaged diameter of ~20 μm, which enabled the cell to be deformed by flow shear stress, not by the channel walls.F is the applied loading force of the AFM probe, E is the Young’s modulus of the cell, δ is the indentation depth, μ is the Poisson’s ratio, and R is the contact radius. Cells are generally considered to be incompressible materials, so we used a Poisson’s ratio value of 0.5 [In this work, AFM was used to verify the accuracy of this morphological rheological method. The AFM experiment was performed with the Bioscope Resolve AFM  which was integrated with an inverted microscope . The PFQNM-LC-A-CAL probes  with spring constants of 0.1 N/m, a tip radius of 65 nm, and a tip half-angle of 18° were used for the experiment. In this experimental case, a linearized Hertz model equation can be used to fit the experimental data into the spherical indenters to calculate Young’s modulus of the cell :(1)F2/3=e of 0.5 .2 humidified atmosphere at 37 °C. PC3 cells were cultured in F12 medium supplemented with 10% fetal bovine serum  and 1% penicillin/streptomycin  in a 5% CO2 humidified atmosphere at 37 °C. To prepare the cell suspension, cells in a petri dish were firstly washed twice using phosphate buffer saline (PBS)  to remove dead cells and other impurities. Then the cells were trypsinized from the petri dish using 0.25% Trypsin/EDTA , followed by centrifugation at 1000 rpm. Then, the cells were suspended again using PBS buffer which contained methylcellulose  at a concentration of 0.5% (w/v). Here, the methylcellulose was used to reduce cell sedimentation and increase the shear viscosity [5–106 cells/mL. The prepared cells were transferred to a syringe for further experiments.All prostate cancer cells lines used in this report were purchased from ScienCell . DU145 and LNCaP cells were cultured in RPMI 1640 medium in a 5% COiscosity . The celIn the AFM experiments, all measurements were completed within two hours to ensure that the cells were in physiological state and adherent during the imaging process. A and L are the area and perimeter of the extracted cell, respectively. D is defined as the deformation of the cell.A self-developed cell contour extraction method was modified on the real-time deformability cytometry (RT-DC) method . The imaThe extracted contour data of cells was then analyzed by MATLAB R2014b and GraphPad Prism7.Q represents the flow rate, η is the viscosity, L is channel size, and E0 is the elastic moduli by simulation [Q’, η’, L’ represent the corresponding experimental parameters, respectively. In this work, the injection rate Q’ was 0.20 μL/s. According to this equation, the iso-elasticity lines were simulated as shown in In the microfluidic channel, cell deformation depends not only on its elastic modulus, but also on its size, the channel size, and flow rate . Reportsmulation . Q’, η’,In this section, the velocity distribution of PC3 cell in the 300 μm microfluidic constriction channel with an injection rate of 0.20 μL/s was analyzed. As shown in In this report, the deformation degree and elastic modulus of three types of prostate cancer cell lines PC3, DU145, and LNCaP were quantified with an injection rate of 0.2 μL/s. PC3 and DU145 are androgen-non-sensitive prostate cancer cells lines, while LNCaP is an androgen-sensitive prostate cancer cells line. Here, LNCaP, DU145, and PC3 are prostate cancer cell lines with low, moderate, and high metastatic potential, respectively . AccordiIn this work, we have applied a morphological rheological microfluidic method to quantify the mechanical properties of three types of prostate cancer cell lines  at a throughput of over 100 cells/s. The velocity distribution of cells during flowing through the narrow channel, and the deformation degree of cells induced by different flow rate was analyzed. The result showed that the elastic modulus of androgen-non-sensitive prostate cancer cell lines  were larger than that of an androgen-sensitive prostate cancer cell line , which was also supported by the results measured using AFM. The results suggest that the mechanical properties of prostate cancer cells can be used as potential biomarkers to identify and predicate the difference of androgen-sensitive and androgen-non-sensitive prostate cancer cell lines. This morphological rheological microfluidic method may be an alternative technique for illustrating how the androgen-sensitive prostate cancer progress into androgen-non-sensitive prostate cancer during executing ADT from a cellular mechanical view.


Hypericum stellatum, a species endemic to China, is used to treat hepatitis by several ethnic groups in Guizhou Province. This research was inspired by the traditional medicinal usage of H. stellatum, and aims to explore the phytochemistry and bioactivity of H. stellatum to explain why local people in Guizhou widely apply H. stellatum for liver protection. In this study, two new prenylated xanthones, hypxanthones A (8) and B (9), together with seven known compounds, were isolated from the aerial parts of the plant. Spectroscopic data as well as experimental and calculated ECD spectra were used to establish the structures of these compounds. Six xanthones isolated in this study, together with four xanthones previously isolated from H. stellatum, were evaluated for their growth-inhibitory activities against five human liver carcinoma cell lines to analyze the bioactivity and structure-activity relationship of xanthones from H. stellatum. Isojacareubin (6) showed significant cytotoxicity against five human liver carcinoma cell lines, with an IC50 value ranging from 1.41 to 11.83 μM, which was stronger than the positive control cisplatin (IC50 = 4.47–20.62 μM). Hypxanthone B (9) showed moderate cytotoxicity to three of the five cell lines. Finally, structure-activity analysis revealed that the prenyl and pyrano substituent groups of these xanthones contributed to their cytotoxicity. Hypericum have a long history of use as herbal medicines in China. There are 64 Hypericum species (33 endemic) distributed throughout China  acetate (1.7 mg) and β-sitosterol (3.5 mg). Fr. 8 was subjected to silica gel CC using  to afford 10 fractions (Fr. D1–Fr. D10). Fr. D7 was fractionated by Sephadex LH-20  into three fractions (Fr. D7a–Fr. D7c). Fr. D7b was submitted to recycling preparative HPLC (CH3OH) to afford hypxanthone A (1.4 mg), hypxanthone B (1.2 mg), and daucosterol (4.5 mg).The powdered, air-dried aerial parts of The method used for ECD calculation has been previously reported . The ROE1H- and 13C-NMR data: see m/z 343.0826 [M − H]− .Hypxanthone A. Yellow amorphous powder; UV (MeOH) λmax (log ε) 327 (4.32) nm; −3 M, MeOH) λmax (∆ε) 210 (+33.3), 250 (+18.4), 326 (+3.5) nm; 1H- and 13C-NMR data: see m/z 393.1341 [M − H]– .Hypxanthone B. Yellow amorphous powder; H. stellatum against five human liver carcinoma cell lines , as well as the immortalized non-cancerous human liver cell (LO2) by the MTS method, in vitro, with cisplatin  and Taxol  as positive controls.Considering its purported medicinal value for the treatment of liver disease, we tested the cytotoxic activities of ten xanthones isolated from H-tetrazolium  assay  acetate, β-sitosterol, and daucosterol) were isolated and identified from H. stellatum. Ten xanthones  isolated from H. stellatum were tested for their cytotoxicity against five human liver carcinoma cell lines. Isojacareubin showed stronger cytotoxic activity than the positive control cisplatin; however, it was weaker than Taxol. Analysis of the structure-activity relationship suggested that xanthone derivatives bearing substituent groups such as prenyl and pyrano groups can improve cytotoxicity towards the tested cancer cell lines. These results indicated that H. stellatum is rich in xanthones. The indigenous knowledge leading local people in Guizhou to apply H. stellatum for liver protection and to treat hepatitis needs further research to reveal in order to reveal the mechanisms.In summary, two new compounds, hypxanthone A (


To date, the most common prediction strategies are based upon machine learning or other quantitative structure-activity relationships (QSAR) based approaches. In the present research, we propose and discuss a straightforward strategy not based on any learning modelling but exclusively relying upon the chemical similarity of a query compound to reference compounds with annotated activity against cell lines. We also compare the performance of the proposed method to machine learning predictions on the same problem. A curated database of compounds-cell lines associations derived from ChemBL version 22 was created for algorithm construction and cross-validation. Validation was done using 10-fold cross-validation and testing the models on new data obtained from ChemBL version 25. In terms of accuracy, both methods perform similarly with values around 0.65 across 750 cell lines in 10-fold cross-validation experiments. By combining both methods it is possible to achieve 66% of correct classification rate in more than 26000 newly reported interactions comprising 11000 new compounds. A Web Service implementing the described approaches (both similarity and machine learning based models) is freely available at:  The usual prediction approaches addressing this problem can be divided into two major groups:The prediction of a cell-line sensitivity to chemical compounds is a very important factor to optimize Approaches based on quantitative structure-activity relationships (Q)SAR modeling. These approaches aim at establishing a model relating chemical structures with their effect on different cell lines –6.Approaches based on gene expression such as the well-known CMAP and L1000CDS2 methodologies –9. OtherThe goal of the methods using gene expression is to compare the genetic expression profile triggered by a query compound with a known reference expression pattern generated with a particular cell line-compound pair. Therefore, these methods require the gene expression profile triggered by the compounds under investigation, which is frequently unknown.On the other hand, QSAR strategies had been previously applied for drugs-cell lines sensitivity prediction –6 with sThe core idea behind any QSAR model is the similarity principle. This principle postulates that compounds sharing a high structural similarity should also have similar activities/properties. Actually, the work of Zhang et al  clearly In the present work, we went through a direct similarity-based strategy being the first time that this approach is evaluated for predictions of compounds-cell lines interactions. Under this approach, no learning based algorithm is used to model the structure-activity space and only the consideration of molecular similarity is required. It is a simple and fast approach that was first applied in the area of chemicals-proteins interactions prediction and later coined as “target fishing” –17. In tWe first evaluated the influence of the radius of the MCFPs and similarity cutoff on the performance of our “cell fishing” or similarity-based approach. The results of these analyses are summarized in In The similarity-based strategy compares a query compound with known sensitive interaction for a particular cell lines. Therefore, the goal is to detect sensitive response. Increasing the similarity cutoff reduces the chances of finding similar molecules but if detected, the confidence will be higher Figs  and 2. AAs described in the methodology section, for SVM we choose cell lines with more than 20 compounds with reported sensitive and resistant interactions (a minimum of 40 compound per cell line). However, for the similarity-based approach we only need 10 sensitive compounds. This difference reduces the cells space from 960 cell lines and 109349 compounds with 140114 sensitive and 147690 resistant LCLAs to 758 cell lines and 107195 compounds with 134565 sensitive and 145064 resistant LCLAs.It can be noticed  that cloIn general, some sensitive/resistant association are better predicted with the similarity approach and vice versa. Moreover, several cell lines are equally modelled with both methods . By keepThe objective of both considered strategies is to identify the maximal amount of interactions between a query compound and all cell lines under consideration. Therefore, the goal in this experiment is to evaluate the capacity to identify all possible sensitive/resistant interactions for new molecules. In this sense, the metrics were calculated across the interactions space. This experiment is not comparable with cross-validation results because on the later the metrics were evaluated across cell lines. That is, in the 10-fold cross-validation the true positives ratio indicates the average detection across cell lines, instead of the true positive detection ratio in all known sensitive/resistant interactions for a given set of compounds as in .Three strategies were evaluated in external validation :The algorithm based on SVM over the 758 cell lines.The similarity-based algorithm over the 758 cell lines using the similarity cutoff of 0.20, 0.25 and 0.3.The combined SVM and similarity-based algorithms over the 758 cell lines using the similarity cutoff of 0.25.The similarity-based approach apparently lead to poor prediction compared to SVM. However, it is important to remember that the similarity-based strategy is based on comparing only to similar sensitive compounds. Therefore, it is possible that some of the new compounds cannot be compared to any of the existing ones in the database.For a cutoff of 0.20, the similarity approach covers almost 92% of the compounds, which means that for 10279 new compounds at least one cell line was predicted based on similarity. In this space, the true-positive and true negative ratios are comparable to those obtained by SVM. Actually, the inclusion of SVM models for the remaining 8% of the compounds do not improve performance , model 5The model 6  is the rIn the The ChemBL database is continuously growing regarding the number of assays as well as the number of new compounds. The addition of new compounds and biological assays, if SVM models are used for LCLAs predictions, will require the reevaluation of the entire model so scalability will become an important issue. In a similarity-based strategy, this problem can be simply addressed. In both cases, the compounds additions will lead to improvements in predictability because they will necessarily increase the molecular as well as the cell lines diversity.The machine learning strategy (as used in this work) provides several advantages including the learning-based extrapolation capabilities, which is noticed in the external data set evaluation. However, compared to the similarity approach, the latter is simplest and easily scalable. Even when both strategies are relatively close in terms of cross-validation, the evaluation of the external data indicates that new chemical scaffolds will be hard to predict using the similarity based strategy (coverage reduction). This is why better results were obtained combining both approaches. Our results also suggest that comparison, whenever possible, between advanced modelling techniques and the simpler strategies (in this case the direct similarity comparison) need to be considered.The prediction of a particular property using the chemical similarity principle is sensible to the description space used for modelling. In this research, we rely upon a comparison based on Tanimoto similarity measured over Morgan fingerprints. If for a particular cell-line only a small and conserved group of molecules is available, then the similarity will be small for any other query with a new molecular scaffold. Hence, better models (using machine learning and/or similarity-based) could be obtained including other descriptions of the molecular space combined with feature selection algorithms.cell_dictionary table distributed with ChemBL v22 in MySQL format was used to extract all cell identifiers (cell_id). Only those LCLA linked to assays reporting median inhibitory concentration (IC50), the median growth inhibitory concentration (GI50) and/or the median cytotoxic concentration (CC50) were considered for further processing. The canonical smiles of each compound was independently analyzed. In cases of salts or disconnected structures, only the largest fragment was used as the input structure. Next. LCLAs established at a ligand concentration lower than or equal to 10−5 M  were labeled as “sensitive”, and the rest were labeled as “resistant”. When more than one assay is reported for the same LCLA, it is removed if there is no total agreement between assays . Finally, any cell line sensitive to less than 10 compounds was removed from the final database. The combination of several assay types (ex. IC50. GI50 and CC50) into a single classification rule has been recently used by other authors in compounds-cell-lines sensitivity prediction [The ChemBL database version 22  was filtediction ,15.Accordingly, the final database included 960 cell lines comprising 140114 sensitive and 147690 resistant LCLAs. Details on the cell lines included in the final database can be found in the In this work. the target fishing approach proposed in Liu et al and recently applied by Peng et all ,23 was an closest sensitive compounds reported in the database for that cell line is higher than a certain similarity cutoff.To measure structural similarity, chemical structures were encoded using the Circular Morgan Fingerprints (CMFP), which are equivalent to the Extended Chemical Fingerprints (ECFP). implemented in RDKit . The Tanr = 2 (ECFP4). r = 4 (ECFP8). and r = 8 (ECFP16). The effect on predictability of different similarity cutoffs were explored. However. we should keep in mind the standard of chemical similarity established for most cheminformatics applications: a pair of molecules is considered as structurally similar if they share an ECFP4 Tc equals or higher than 0.55 [In this work, we tested n = 3 based on the average molecular similarity of the top 3 closest ligands. The efficiency of several similarity cutoffs for the CMFP defined by different radii in detecting sensitive associations was also explored. The evaluated similarity cutoffs ranged from 0.2 to 0.6 with a step size of 0.05. Three different radii of the CMFP were tested: han 0.55 .Machine learning (ML) classification models were evaluated with 758 cell lines out of the initial pool of 960 cell lines employed for target fishing. A total of 202 cell lines were excluded from these experiments because of having less than 20 compounds in any of the sensitive or resistant groups. The decision of a minimum of 20 compounds was based on Tropsha et al .To train binary classification models, the two groups need to be balanced in the number of compounds that each one contains. A dataset was considered unbalanced if the majority group contained more than 1.2 times the number of compounds in the minority one. From the 758 cell lines, 213 were balanced whereas the remaining 545 ones underwent a data balancing procedure before modeling.The data balancing protocol aimed at reducing the majority group to a similar number of compounds present in the minority class. The employed protocol relied in a hierarchical clustering procedure to retain the data diversity present in the initial majority group. For this, the chemical structures of the compounds in the majority group were coded using Morgan fingerprints of radius = 8 and 1024 bits. Then, the distance matrix between all pairs of compound belonging to the class to be reduced was computed employing the Tanimoto distance. The computed distance matrix was used as input to a tree-based clustering using the linkage function with the Ward’s minimum variance method. Clusters were defined using a cutoff height of 4.5.If the number of clusters (Nc) was lower than the number of compounds in the minority group (Nm), then a number of compounds was selected from each cluster, proportional to the cluster size, until completing Nm samples. This was the case for 112 cell lines. On the other side, if Nc > Nm, then the majority group was re-clustered to obtain Nm clusters and the centroid of each one was selected for the reduced dataset. This procedure was applied to 443 cell lines.The reduced datasets containing compounds coded with the Morgan fingerprints as described above were used to train Support Vector Machine (SVM) classification models with Radial Basis Function (RBF) kernels.jAC and NjRC are the number of compounds reported in the database as establishing a sensitive and resistant association respectively with cell line j.Several performance metrics, previously reported in Peng et all  for targThe described performance metrics were computed for two different validation strategies: 1) the 10-fold cross-validation and 2) new compound with known sensitive/resistant annotations in the same cell lines space.The SVM modeling was conducted using a 10-fold cross-validation setup. On each cross-validation cycle, 90% of the data was used to train a SVM model and the remaining 10% of it was employed as test set. Before training, the SVM C and γ parameters of the kernel were optimized by means of a grid search algorithm.In order to get a comparative space between machine learning strategy and the similarity-based approach, the same compounds used in each 10-fold iterations (therefore the same compound in the partition) were evaluated with both prediction methods. All metrics (if not reported otherwise) calculated for machine learning model and the similarity-based method were computed with the initial database of 758 cell lines and 107195 compounds with 134565 sensitive and 145064 resistant LCLAs.For the second type validation we carried on the same data treatment and filtering process already described for ChemBL v22 to ChemBL v25. With these new data we extracted the entire list of new compounds emerging from v22 to v25 and all their cell lines association (from the 758 cell lines): 11266 new compounds. 20898 sensitive pairs and 5237 resistant pairs .http://bioquimio.udla.edu.ec/cellfishing.Two strategies are available as a web-service in; The CellFishing (similarity-based strategy). All 960 cell lines are included. In this section different Morgan’s Radius can be used.The SVM models obtained in 758 cell lines.S1 Table(XLSX)Click here for additional data file.S2 Table(ZIP)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.


Alkaloids are used in traditional medicine for the treatment of many diseases. These compounds are synthesized in plants as secondary metabolites and have multiple effects on cellular metabolism. Among plant derivatives with biological properties, the isoquinoline quaternary alkaloid berberine possesses a broad range of therapeutic uses against several diseases. In recent years, berberine has been reported to inhibit cell proliferation and to be cytotoxic towards cancer cells. Based on this evidence, many derivatives have been synthesized to improve berberine efficiency and selectivity; the results so far obtained on human cancer cell lines support the idea that they could be promising agents for cancer treatment. The main properties of berberine and derivatives will be illustrated. Natural compounds have been used for centuries because of their availability; those present in plants are employed in the so-called Traditional Medicine, which translates theories, beliefs and experiences into knowledge, skills and practices applied to prevent, diagnose and treat physical and mental disorders . Being rPlants have wide biological and medicinal properties, and are characterized by high safety, availability, accessibility and low cost, thus representing an invaluable source of chemicals with potential therapeutic effects ,4. Secon20H19NO5, Hydrastis canadensis, Berberis aristata, Coptis chinensis, Coptis japonica, Phellondendron amurense and Phellondendron chinenseSchneid [in vitro studies using cancer cell lines have shown that BBR inhibits cancer cell proliferation and migration, and induces apoptosis in a variety of cancer cell lines [Among the several plant secondary metabolites, alkaloids possess a variety of pharmacological properties. Berberine .BBR interacts directly with nucleic acids and with several proteins, including telomerase, DNA topoisomerase I, p53, NF-kB, MMPs and estrogen receptors. In general, BBR treatment promotes cell cycle arrest and death in human cancer cell lines, coupled to an increased expression of apoptotic factors ,15,16. TSeveral studies have shown that BBR interacts directly with DNA, inducing double-strand breaks ,17, and 0/G1 phase was recorded in breast cancer MDAMB-231 and MCF-7 [0/G1 arrest and suppressing cell proliferation [1 phase, paralleled by decreased expression levels of cyclin B1, was observed in lung cancer H1299 and A549 cell lines [2 phase [1 (accompanied by p53-dependent upregulation of p21) and a p53-independent arrest in G2/M phase [wt were found to be very sensitive to BBR, whereas cell lines lacking functional p53 do not respond to BBR treatment [wt [Cell cycle arrest has been reported in human cancer cell lines as an effect of the interaction of BBR with DNA , as suppnd MCF-7 , thyroidnd MCF-7  and ovarnd MCF-7  cell linll lines  as well /M phase . In genereatment ,16. In tment [wt .2/M phase in colorectal, breast cancer and hepatocellular carcinoma cells followed by apoptosis activation through the loss of mitochondrial membrane potential, release of cytochrome c, inhibition of anti-apoptotic proteins , activation of pro-apoptotic proteins  and cleavage of PARP-1 [It was also observed that BBR induced cell cycle arrest at the Gf PARP-1 ,35,36,371/S boundary [2+ from endoplasmic reticulum (ER). An event which causes cell cycle arrest and cell death, driven by altered functions of mitochondria followed by cytochrome c release and caspase-3 activation leading to apoptosis [This protein  or DNA damage-inducible transcript 3 (DDIT3), is involved in growth arrest and DNA damage, ubiquitously expressed at very low levels  and overboundary ,39. It hpoptosis ,39,40,412), which are implicated in inflammatory responses and also in carcinogenesis and metastasis [2 [in vivo assays, BBR was found to lower COX-2 expression in the colon of rats treated with azoxymethane (AOM), inhibiting in turn the neoplastic transformation [Two COX isoforms with distinct physiological functions have been described; COX-1 is constitutively expressed and has an important role in cell homeostasis, while COX-2 is an inducible enzyme activated by extracellular stimuli. Overexpression of COX-2 stimulates the production of prostaglandins, including prostaglandin E2  regulates a wide range of cellular signaling pathways for both cell survival and death. In neuroblastoma cells it was observed that BBR binds to DNA in the DAXX core promoter region and suppressed its transcriptional activity. The down-regulation of DAXX expression resulted in the degradation of MDM2 (murine double minute 2) by ubiquitination, followed by the activation of p53 and then apoptosis ,16.It has been demonstrated that DAXX interacts with MDM2 and HAUSP (herpes virus-associated ubiquitin-specific protease) to form a tertiary complex. This complex reduces self-ubiquitination of MDM2, to maintain a low level of p53 under non-stress conditions. In different cancer cell types, BBR induced a dissociation of the MDM2-DAXX-HAUSP complex, resulting in enhanced MDM2 ubiquitination that increases p53 protein activity, leading to apoptosis .The AMP-activated protein kinase (AMPK) is a highly conserved serine/threonine kinase that serves as a metabolic sensor for the maintenance of cellular energy homeostasis and is capable to inhibit AR (androgen receptor). AMPK becomes activated in cell starvation, hypoxia, ischemia and heat shock. In prostate cancer, AR signaling is crucial for development and progression by regulating cell proliferation, differentiation and apoptosis. After treatment with BBR, prostate cancer cells decrease their proliferation by a direct activation of AMPK, contributing to the degradation of AR and leading to apoptosis ,58.2H4PteGlu), generating dTMP and dihydrofolate [Thymidylate synthase (TS) catalyzes the reductive methylation of dUMP by 5,10-methylenetetrahydrofolate  and methotrexate, showed an increase in TS and in the intracellular pools of 5,10-methylene-THF and THF . These cThe search for new drugs that induce apoptosis in tumors refractory to the conventional therapy is crucial to develop efficient anticancer therapies. Several mechanisms by which BBR inhibits the proliferation of different cancer cell lines have been reported. Among them, the killing of cancer cells by the activation of apoptosis is the best characterized.In this context, several groups have reported the pro-apoptotic effect of BBR mediated by the impact on mitochondria. In fact, BBR was proved to alter the mitochondrial membrane potential (MMP), inhibit mitochondrial respiration leading to mitochondrial dysfunction and regulate the expression of Bcl-2 family members, as Mcl-1 ,47. AlteBBR pro-apoptotic effects could be mediated through the modulation of the HER2/PI3K/Akt ,72 and/oL after BBR treatment was observed not only in human prostate epithelial (PWR-1E) or carcinoma cells , but also in promyelocytic leukemia, gastric carcinoma and lung cancer cells, inducing cell death  together with decrease of Bcl-2/Bcl-xll death .Caspase-dependent apoptosis was reported in colon carcinoma cells treated with 13-arylalkyl BBR derivatives . BBR hasin vivo when tumor cells were injected into nude mice [BBR has been used in combination with drugs or radiation. It was found as an adjuvant therapeutic agent in combination with taxol, a frequently used clinical chemotherapeutic drug, in HER2-overexpressing breast cancer cells (SKBR-3) . Furtherude mice .in vitro could be related to the inhibition of FAK, IKK, NF-κB, u-PA, MMP-2, and MMP-9 [in vivo and in vitro analyses in B16F-10 cells, where BBR affected MMP expression through a negative regulation of ERK [Of note, BBR could interfere with tumor progression and invasion, possibly through the inhibition of 12-O-tetradecanoylphorbol 13-acetate (TPA), GTPase , PE2 recnd MMP-9 ,88,101. nd MMP-9 . The pron of ERK . The actn of ERK . The samn of ERK .Metastatic lung cancer A549 cells also appeared to be blocked in tumor progression and invasion by BBR, due to the down-regulation of several transcription factors such as c-fos, c-jun and NF-κB . The samAutophagy contrasts cellular stress conditions including nutrient deprivation and produces recycled energy originated from macromolecule degradation, thus regulating cellular homeostasis. The function of autophagy in cancer cells is to sense the presence of damaged DNA and organelles caused by chemotherapy and to degrade them, according to its own function; in this way, continuous energy is produced, which ensures cancer cell survival ,109,110.The analysis of the potential ability of BBR to induce autophagy revealed that in non-small-cell and Lewis lung cancer cell lines as well as mice with Lewis lung carcinoma xenografts, in fact autophagic hallmarks  were detected ,114. AccSeveral derivatives of BBR have been evaluated in the HCT116 colon carcinoma cell line and found to be capable of inducing vesicle formation at cytoplasmic level, where LC3I was converted into its lipidated form LC3II .Berberine offers ready functionalization and decoration at various positions on its skeleton, and can be readily converted into derivative compounds by known synthetic methodologies ,118,119.In particular, arylalkyl derivatives of berberine have been investigated ,119. UnpThe above discussed evidences suggest that multiple effects of BBR are mediated by the impact on different pathways, leading essentially to cell cycle arrest, apoptosis and controlled inflammation . The pro. The mechanism of action of miR-21-3p was postulated to be correlated to the expression of methionine adenosyltransferase (MAT) genes (MAT2A and MAT2B) [i.e., human multiple myeloma [Among the multiple studies aiming at defining the mechanism of action of BBR, it is noteworthy to mention the evidence that BBR could regulate microRNAs (miRNAs), short non-coding RNA molecules (21–23 nucleotides) generated in the nucleus and involved in a variety of biological processes, including development, cell proliferation and death. Deregulated expression of miRNAs was observed in many human cancer types, where they can act either as tumor suppressor or oncogenes . Recent d MAT2B) . In diff myeloma  and cisp myeloma , a dose


Pericharax heteroraphis collected from the South China Sea yielded one new imidazole alkaloid named naamidine J (1) along with four known ones (2–5). Their structures were established by extensive spectroscopic methods and comparison of their data with those of the related known compounds. All the isolates possessed a central 2-aminoimidazole ring, substituted by one or two functionalized benzyl groups in some combination of the C4 and C5 positions. The cytotoxicities against selected HL-60, HeLa, A549 and K562 tumor cell lines and anti-H1N1 (Influenza a virus (IAV)) activity for the isolates were evaluated. Compounds 1 and 2 exhibited cytotoxicities against the K562 cell line with IC50 values of 11.3 and 9.4 μM, respectively. Compound 5 exhibited weak anti-H1N1  activity with an inhibition ratio of 33%.Marine sponges continue to serve as a rich source of alkaloids possessing interesting biological activities and often exhibiting unique structural frameworks. In the current study, chemical investigation on the marine sponge  Pericharax heteroraphis (genus Pericharax family Leucettidae) drew our attention, as the UV characteristics of MeOH extracts showed the existence of 2-aminoimidazole alkaloids; in addition, its extracts were reported to have broad activity on cancer cell lines  ( (1) was ′, H-6′′ . Therefo2) amino}-1-methyl-1H-imidazole-2,5-dione. Yellow amorphous solid; melting point (m.p.): 102–104 °C; UV (MeOH): λmax (log ε) 225 (4.27), 275 (3.77), 392 (3.97) nm; IR (KBr): 3427, 2960, 2873, 1731, 1710, 1377, 1250, 1068, 1025 cm−1; 1H and 13C-NMR: see m/z 478.2091 [M + H]+ ; 500.1906 [M + Na]+ .Compound In vitro cytotoxicities were determined by MTT colorimetric assay against K562 (human leukemia cells) and HL-60 (human myeloid leukemia cells), SRB (Sulforhodamine B) assay against HeLa  and A549 (human lung adenocarcinoma cells). All the cell lines were purchased from Shanghai Institute of Cell Biology . Cytotoxic data  was used as a positive control, and IC50 values > 50 μM were considered to be inactive in cytotoxic assays.xic data  for comp2 and 95% air at 37 °C. Those cell suspensions (200 μL) at a density of 5 × 104 cell mL−1 were plated in 96-well microtiter plates and incubated for 24 h at the above conditions. The test compound solution (2 μL in DMSO) at different concentrations in triplicate was added to each well and was further incubated for 72 h under the same conditions. 20 μL of the MTT solution (5 mg/mL in IPMI-1640 medium) was then added to each well and incubated for 4 h. The old medium containing MTT (150 μL) was then gently replaced by DMSO and vibrated to dissolve any formazan [1-(4-Iodophenyl)-5-(4-nitrophenyl)-3-phenylformazan] crystals formed. The optical density of the solution was measured on a Spectra Max Plus plate reader at 570 nm. The IC50 value of each compound was calculated by Reed and Muench’s method.In the MTT assay , the cel5 cell mL−1. Then 2 μL of the test solutions (in MeOH) was added to each well, and the culture was further incubated for 24 h. The cells were fixed with 12% trichloroacetic acid, and the cell layer was stained with 0.4% SRB. The absorbance of the SRB solution was measured at 515 nm. Dose-response curves were generated, and the IC50 values (the concentration of compound required to inhibit cell proliferation by 50%) were calculated from the linear portion of log dose-response curves.In the SRB assay , 200 μL 50 was calculated as the compound concentration required inhibiting CPE production at 48 h post-infection by 50%. Ribavirin  was used as positive control, and compounds with an inhibition rate of >70%, >50%, and <30% at 50 μg/mL were respectively regarded as having strong, moderate, and weak activities.The antiviral activity against H1N1 was evaluated by the cytopathic effects assays (CPE) . Conflue1, 2, 3 and 5 from the genus Pericharax, and firstly reported anti-H1N1 virus activities of this type of alkaloid. Compounds 1 and 2 showed cytotoxic activity against the K562 cell line, suggesting that they might have the potential to be developed as antitumor agents. It was reported that the extract of Pericharax heteroraphis showed significant anti-AChE-inhibitory activity, and continuing investigation of the anti-AChE-inhibitory activity of the isolates is worthwhile.The present work offered one new member of 2-aminoimidazole alkaloids and the first isolation of compounds


Ovarian clear cell carcinoma is a distinct histologic subtype with grave survival. The underlying molecular mechanism is not fully elucidated. However, we don’t have many cell lines, which are useful experimental tools for research. We describe the establishment and characterization of a new ovarian clear cell carcinoma cell line from a Chinese patient.FDOV1 has been subcultured for more than 80 generations. Monolayer cultured cells are polygonal in shape, showing a transparent cytoplasm full of vacuoles. The number of chromosomes ranges from 45 to 90. FDOV1 cells produces CA-125, but not CA-199. The cells could be transplanted and produced tumors mimicking the donor tumor morphologically and immunohistochemically. Whole exome sequence showed both FDOV1 and tissue block harbored PIK3CA H1047R mutation and ARID1A frameshift mutations . More interestingly, we observed SPOP mutation (p.D82H) and ZNF217 (chromosome 20q13) amplification in FDOV1, which are quite novel.Only a few patient-derived ovarian clear cell carcinoma cell lines have been reported in the literature. FDOV1 is the very first one, to the best of our knowledge, from a Mainland Chinese patient. It showed infinite multiplication until now and tumorigenicity in vivo. FDOV1 has co-existing PIK3CA and ARID1A mutations. It also harbored SPOP mutation and ZNF217 amplification, which would probably be a good model for exploring the molecular mechanism of ovarian clear cell carcinoma.The online version of this article (10.1186/s13048-018-0429-5) contains supplementary material, which is available to authorized users. Epithelial ovarian carcinoma is the most lethal gynecologic malignancy. Ovarian clear cell carcinoma (OCCC) is the second most common histologic subtype, accounting for 5–25% of all ovarian cancer depending on geographic location , 2. It i-Rich Interactive Domain-containing protein 1A (ARID1A) and Phosphoinositide-3-kinase Catalytic Alpha (PIK3CA), representing around 50% [The two most widely reported gene mutations in OCCC are ATound 50%  and 40% ound 50% , 8 of alound 50% . What’s ound 50% , 11. Theound 50% , which shttp://www.atcc.org) and COSMIC database (https://cancer.sanger.ac.uk/cell_lines), respectively. The majority of the established cell lines were derived from Japanese patients. Besides, only one OCCC cell line TOV-21G was found with PIK3CA and ARID1A mutation. We describe here the establishment and characterization of a novel cell line (FDOV1) from a Chinese patient that harbors coexistent ARID1A-PIK3CA mutations.Cancer cell lines are affordable models for genetic and molecular profiles, reflecting the characteristics of the origin tumor. According to documentations till now, 16 OCCC cell lines were established and their characteristics have been reported –25, addeUp to now, more than 80 serial passages have been carried out successively. FDOV1 cells grew in the form of an adherent monolayer without contact inhibition ; 2n = 47 ; 4n = 86–90 . Chromosomal aberrations including complex translocations and deletions were noted, which were consistent with that of malignant tumors.A total of 45 metaphase cells from FDOV1 were examined for chromosome analysis. Chromosome numbers ranged from 45 to 90 , insertion and deletion (indel) and copy number variation (CNV). From the SNV related to cancer, it is shown that the tissue block and FDOV1 cell line shared some same somatic variations although diverse allele frequency Fig. . InteresOvarian clear cell carcinoma, as a subtype with distinct clinical behavior, is notorious for its poor survival and resistance to conventional platinum-based chemotherapy. An international phase III clinical trial was conducted to investigate the addition of irinotecan as adjuvant chemotherapy for patients with advanced-stage . UnfortuAccording to documentations, there were 16 ovarian clear cell carcinoma cell lines reported so far, in addition, TOV-21G, ES-2, which are commercially available from American Tissue Culture Center, and FDOV1. Their characteristics were compared in Table Notably, SPOP, a relatively new gene regulating DNA damage repair, is the most frequently mutated gene in prostate carcinoma , 33. MutChromosome 20q13 ZNF217 (Zinc Finger Protein 217) locus amplification, which has found in FDOV1, is one of common molecuclar genetic aberrations in OCCC . The fre. FDOV1 showed fast and unlimited multiplication until now and tumorigenicity in vivo. In addition, WES showed that it harbors concurrent ARID1A–PIK3CA mutations and SPOP mutation, also with ZNF217 amplification, which will be an ideal tool for mechanism research of ovarian clear cell carcinoma.An ovarian clear cell carcinoma cell line named FDOV1 was established from a Mainland Chinese patientA 67-year-old woman was admitted into Fudan University Shanghai Cancer Center with the chief complaint of palpable abdominal mass in May 2016. Ultrasound revealed a large pelvic mass (14 × 10 cm) with mixed components and a hyperechoic mural nodule (4 × 3 cm). Serum tumor markers including carbohydrate antigen (CA) 125 and CA199 were not elevated. Intraoperative findings were only significant for a cystic-and-solid mass (15 cm in diameter) in the left adnexa. Frozen pathology was highly suspicious of ovarian clear cell carcinoma. The patient underwent comprehensive staging surgery and the final stage was FIGO  Ia. She gave written informed consent before surgery according to institutional guideline (FUSCC 050432–4-1212B). Six cycles of TC regimen (paclitaxel + carboplatin) chemotherapy were administered. She was followed up every 3 months after treatment. The patient was admitted into outside hospital with chief complain of intestinal obstruction in May 2017. She developed multiple sites of venous thromboembolism and cerebral infarction. Unfortunately, she died 1 month later with no chance of anti-cancer treatment.3) from primary ovarian tumor was obtained during comprehensive staging surgery, and suspended in phosphate buffer solution (PBS) to get rid of necrotic and connective tissue. The material was then finely minced into 1-mm3 tissue blocks and placed in 10-cm cell culture dishes  containing Medium 199 medium  with 10% fetal bovine serum , 100 IU/ml penicillin  and 50 μg/ml streptomycin . The cells were then incubated in a humidified atmosphere containing 5% CO2 at 37 °C. After repeated passage, a new cell line of FDOV1 was successfully established with more than 80 generations. FDOV1 cells have been sent to China General Microbiological Culture Collection Center for preservation (No. 13812) in March 2017.The fresh tissue (1 cm3 cells/100 μl) were seeded in 96-well plates in sextuplicate. Ten days later, 100 μl mixture (CCK-8/medium 1:9) were added into the wells for incubation by 2 hours. We then measured the Optical Density (OD) at 450 nm (OD450) by a microplate reader .Cell proliferation and growth curve was determined by Cell Counting Kit-8 (CCK-8) test. FDOV1 cells (2 × 106 cell) were kept overnight in 3 ml 75% ethanol at − 20 °C. After treatment, the cells were collected and stained with propidium iodide solution for 20 min at 4 °C in darkness. We then assessed the cell cycle by flow cytometer .Resuspended FDOV1 cells  were injected subcutaneously into the dorsal flanks of two mice. Visible tumors were noted in both mice 20 days after transplantation.All the procedures were approved by the Department of Laboratory Animal Science in Fudan University. For in vivo studies, 4–6 weeks old NOD/SCID mice  were maintained under sterile conditions. FDOV1 cells  were used to stain 4-μm sections. The markers used for immunohistochemistry were listed as follows: HNF-1β , Napsin A , Pax-8 , ER  and PR . Microscopic slides were reviewed by a senior gynecology-dedicated pathologist (Prof. Yang).The WES was performed by 3D Medicines Corporation and the specific method was the same as a previous publication .Mutations of the specific genes in FDOV1 cells were validated by Sanger Sequencing. The RNA was extracted by Trizol Methods, then reverse transcription polymerase chain reaction (RT-PCR) was performed as our previous study . The priAdditional file 1:Table S1. The primer of Sanger sequence for specific genes mutation in FDOV1. (DOCX 15 kb)


Monotherapy with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) still leads to incomplete responses in most EGFR-mutation positive non-small cell lung cancer (NSCLC) patients, often due to acquired resistance through activation of parallel compensatory pathways. We have previously shown that co-targeting EGFR, signal transducer and activator of transcription 3 (STAT3), and Src-yes-associated protein 1 (YAP1) was highly synergistic in vitro and in vivo. In the present study, we treated EGFR-mutation positive cell lines with the combination of osimertinib plus a natural compound, pterostilbene, which has been reported to abrogate Src and STAT3 activation.Methods: Cell viability assays and immunoblotting were performed to reveal the mechanisms of action of pterostilbene, osimertinib and pterostilbene plus osimertinib in five EGFR-mutation positive NSCLC and one triple negative breast cancer (TNBC) cell lines.Results: Osimertinib plus pterostilbene yielded synergistic effects in all EGFR-mutation positive NSCLC cell lines investigated. Surprisingly, pterostilbene alone did not inhibit, nor downregulate Src phosphorylation in the EGFR-mutation positive NSCLC cell lines or the TNBC cell line, MDA-MB-231. However, the double combination of osimertinib plus pterostilbene reversed the osimertinib-induced STAT3, YAP1, and CUB domain-containing protein-1 (CDCP1) phosphorylation and slightly suppressed Src phosphorylation in PC9 and H1975 cells.Conclusion: The results of this study indicate that pterostilbene may be used to abrogate the activated resistance pathways of single osimertinib treatment in EGFR-mutation positive NSCLC. Future studies should focus on in vivo translation and confirmation of these results. OngThe genetic or pharmacologic inhibition of Src family kinases (SFKs) or YAP1 diminishes the phosphorylation of the RTK AXL and the transmembrane protein CUB domain-containing protein-1 (CDCP1) Figure 1). In this study we explored whether pterostilbene inhibits compensatory osimertinib-induced signaling pathways, and if the combination can optimize the upfront therapy of EGFR-mutation positive NSCLC cells.Pterostilbene  is a stilbene of the family of phytoalexin compounds, found in in blueberries and Pterocarpus marsupium (PM) heartwood. It is structurally similar to resveratrol, a compound found in red wine that has comparable antioxidant, anti-inflammatory, and anti-carcinogenic properties. Due to the presence of two methoxyl groups, pterostilbene has increased lipophilic and oral absorption and therefore increased bioavailability compared to resveratrol 2 37°C cell culture incubator and routinely evaluated for mycoplasma contamination.Human lung adenocarcinoma PC9 cells, harboring EGFR exon 19 deletion and 11-18 cells, harboring EGFR exon 21 L858R mutation were provided by F. Hoffmann-La Roche Ltd. , and by Dr. Mayumi Ono, , respectively. EGFR exon 19 deletion positive HCC4006 and HCC827 cells were purchased from the American Type Culture Collection (ATCC). The H1975 cell line, harboring both EGFR exon 21 L858R and resistant T790M mutation as well as the TNBC MBA-MB-231 cell line were purchased from ATCC. All cell lines were maintained in RPMI  1640 supplemented with 1% penicillin/streptomycin/glutamine (Gibco) and 10% fetal bovine serum  in a 5% CO1) was purchased from Amazon.com, Inc. , the second pterostilbene compound (hereafter referred to as pterostilbene2) was bought from Sigma Aldrich/Merck KGaA,  and osimertinib was bought from Selleck Chemicals . Drugs were prepared in dimethylsulfoxide (DMSO) at a concentration of 10-100 mM stock solutions and stored at -20°C. Further dilutions were made in culture medium to final concentration before use. All antibodies used in our study, including dilution and company catalog number can be found in Table 1.The primarily used pterostilbene compound (hereafter referred to as pterostilbene3 (PC9 and H1975) 1.5 x 103 , and incubated for 24h, as previously described 50) determination, MTT viability assays were performed using pterostilbene doses ranging from 0-150 μM. To determine the combined effect of pterostilbene and osimertinib, drug doses in viability assays were as follows: H1975 and HCC4006 cells were treated with osimertinib ranging from 0-90 nM, and pterostilbene ranging from 0-180 μM, or with the combination of both. PC9 and HCC827 cells were treated with osimertinib ranging from 0-120 nM, and pterostilbene ranging from 0-120 μM, or with the combination of both. 11-18 was treated with osimertinib ranging from 0-330 nM, and pterostilbene ranging from 0-120 μM, or with the combination of both. After 72 h of treatment incubation, 0.5 mg/ml of MTT was added to the medium in the wells for 2 h at 37 °C and formazan crystals in viable cells were solubilized with 100 μl DMSO and spectrophotometrically quantified using a microplate reader  at 565 nm of absorbance. Fractional survival was then calculated as percentage to control cells. Data of combined drug effects were subsequently analyzed by the Chou and Talalay method Cells were seeded in 96-well plates at the following densities: 1 x 10PC9 and H75 1.5 x For immunoblotting experiments, 1.5 million cells were seeded in T75 flasks . The next day, PC9, H1975 and MDA-MB-231 cells were either treated with increasing doses of pterostilbene , or with 20 nM osimertinib, 10 μM pterostilbene and a combination of both. Untreated cells received an equivalent dose of vehicle (DMSO). After 24 h cells were washed with cold PBS and re-suspended in ice-cold radioimmunoprecipitation assay (RIPA) buffer  containing protease inhibitor mixture (Roche). Following cell lysis by sonication and centrifugation at 18620x g for 10 min at 4 °C, the resulting supernatant was collected as the total cell lysate. Briefly, the lysates containing 45 μg proteins were electrophoresed on 10% SDS-polyacrylamide gels  and transferred to polyvinylidene difluoride (PVDF) membranes . Membranes were blocked in Odyssey blocking buffer . All target proteins were immunoblotted with appropriate primary and horseradish peroxidase (HRP)-conjugated secondary antibodies. Chemiluminescent (HRP-conjugated) bands were detected in a ChemiDoc MP Imaging System (Bio-Rad laboratories Inc.). β-actin was used as an internal control to confirm equal gel loading. Experiments were performed in biological triplicates with similar results, and representative blots were shown.50) of pterostilbene1 in all cell lines , it could be concluded that single pterostilbene1 treatment was not able to induce anti-proliferative effects in these cell lines, with IC50s ranging from 23.8 to 40.7 μM. However, when combining pterostilbene1 with the third-generation TKI osimertinib , we obtained synergistic results in all EGFR-mutation positive NSCLC cell lines investigated, with a combination index (CI) ranging from 0.63 to 0.70 . These results indicate a synergistic interaction between pterostilbene1 and osimertinib in these cell lines.To confirm the effects of pterostilbene on cell growth, cell viability assays were performed in 5 different EGFR-mutation positive NSCLC cell lines: PC9, H1975, HCC827, HCC4006 and 11-18. After establishing the half maximal inhibitory concentration RTKs, as can be seen in Figure . An increase of ERK, CDCP1, STAT3 and Src phosphorylation was observed upon different concentrations of pterostilbene1 treatment. In contrast, both total and phosphorylated YAP1 were inhibited by pterostilbene1 at higher concentrations. It can also be seen that phosphorylation of Src, YAP1, pCDCP1 and pAXL are correlated, indicating an interrelationship between thse signaling nodes as previously described 1 is opposite from previously published results, in which pterostilbene was reported to be a Src and MET inhibitor in TNBC To determine which signaling nodes are being abrogated by pterostilbene1 in the MBA-MB-231 TNBC cell line was determined. Cells were treated with 0 or 10 μM pterostilbene1 for 24 h, and Src activation was explored. Surprisingly, instead of inhibiting Src phosphorylation, pterostilbene1 caused an induction of Src phosphorylation . To confirm this, we purchased pterostilbene from a different supplier (pterostilbene2), and cell viability experiments were performed to compare the two drugs. In Figure  it can be seen that the two pterostilbene compounds have nearly identical anti-proliferative effects in two EGFR-mutation positive NSCLC cell lines. To verify these results in the TNBC cell line, MBA-MB-231 cells were treated with both pterostilbene compounds. The cell lysates were consequently used for immunoblotting, and again revealed similar mechanisms of action, as can be seen in Figure . Both compounds clearly induce Src phosphorylation.To explore these contradictory results, the activity of pterostilbene1. As we have previously reported, osimertinib alone attenuated ERK activation in both cell lines, but induced CDCP1 and Src activation in PC9 cells, and STAT3, YAP1 and AXL activation in both PC9 and H1975 cells . In contrast, STAT3, YAP1 and AXL phosphorylation are completely abrogated when treated with single pterostilbene1. MET phosphorylation is slightly activated upon single pterostilbene1 treatment in the PC9 cell line. While in both cell lines CDCP1 activation is inhibited compared to baseline levels, Src phosphorylation is not abrogated with single pterostilbene1 treatment. Osimertinib plus pterostilbene1 reversed the osimertinib-induced STAT3 and YAP1 phosphorylation, abolished CDCP1 and AXL activation and decreased Src phosphorylation. In the PC9 cell line, a restoration of MET phosphorylation levels to baseline was also observed with the double combination. The above results indicate that osimertinib treatment activates parallel compensatory pathways, which can be abrogated by combined osimertinib plus pterostilbene treatment.Although in our study pterostilbene was not able to inhibit Src phosphorylation, its effects on YAP1, Src, CDCP1 and AXL phosphorylation in EGFR-mutation positive cells led us to explore the combination of osimertinib plus pterostilbeneEGFR-mutation-positive NSCLC cells co-express RTKs and non-RTKs, especially, Src, YES and FAK, which cannot be inhibited by single EGFR inhibitors, including the third-generation EGFR TKI osimertinib Figure ), the combination of osimertinib plus pterostilbene was synergistic in five-, and downregulated the activation of STAT3, Src-YAP1 and CDCP1 in two EGFR-mutation positive NSCLC cell lines .Pterostilbene is a natural nutrient from blueberries that can be safely used in high doses 28 High MUC1 mRNA expression is correlated with poorer overall survival, and pterostilbene-based inhibition subverted the tumor-microenvironment to an anti-tumoral state by reducing stemness induction of TAMs. Therefore, MUC1 expression levels may predict which patients can benefit from pterostilbene treatment. Another important piece of information is that constitutively active STAT3 increases MUC1 expression levels on both the mRNA and protein level, explaining our synergistic in vitro results.29 Therefore, further investigation in terms of feasibility and in vivo experiments should be carried out.Pterostilbene was shown to modulate tumor-associated macrophages (TAMs), by modulating MUC1.Figure . This study will assess if pterostilbene is an economical but highly hopeful approach to increase the antitumoral activity of EGFR inhibitors in EGFR-mutation positive NSCLC patients, and should clarify whether this combined treatment strategy can be safely incorporated into routine clinical practice.We are currently performing a proof of concept single-center clinical study, based on the model depicted in