While pralatrexate (PDX) has been successfully developed for the treatment of T‐cell lymphoma, the mechanistic basis for its T‐cell selectivity and acquired resistance remains elusive. In an effort to potentially identify synergistic combinations that might circumnavigate or delay acquired PDX resistance, we generated resistant cells lines over a broad concentration range. PDX‐resistant cell lines H9‐12 and H9‐200 were developed, each exhibiting an IC50 of 35 and over 1000 nM, respectively. These lines were established in vitro from parental H9 cells. Expression analysis of the proteins known to be important determinants of antifolate pharmacology revealed increase expression of dihydrofolate reductase (DHFR) due to gene amplification, and reduced folate carrier1 downregulation, as the putative mechanisms of resistance in H9‐12 and H9‐200 cells. Cross resistance was only seen with methotrexate but not with romidepsin, azacitidine (AZA), decitabine, gemcitabine, doxorubicin, or bortezomib. Resistance to PDX was reversed by pretreatment with hypomethylating agents in a concentration‐dependent fashion. Comparison of gene expression profiles of parental and resistant cell lines confirmed markedly different patterns of gene expression, and identified the dual specificity phosphatase four (DUSP4) as one of the molecular target of PDX activity. Reduced STAT5 phosphorylation following exposure to PDX was observed in the H9 but not in the H9‐12 and H9‐200 cells. These data suggest that combination with hypomethylating agents could be potent, and that DUSP4 and STAT5 could represent putative biomarkers of PDX activity. PDX received regulatory approval for the treatment of relapsed or refractory PTCL in 2009. Early preclinical and clinical experiences have suggested an extraordinarily high level of activity in T‐cell malignancies, with minimal to no activity in patients with B‐cell lymphoid neoplasm or carcinomas.Intrinsic resistance to PDX appears to be overcome to some extent through the use of combinations, as preclinical and clinical data evaluating PDX combinations have shown marked synergy with histone deacetylase inhibitors (HDACi) like romidepsin,While the mechanistic basis for the PTCL selectivity and acquired resistance to PDX are still not entirely understood, it is clear the T‐cell malignancies represent one of those neoplastic diseases characterized by high rates of intrinsic drug resistance, and a penchant for rapid emergence of acquired resistance. Herein, we have developed a series of PDX‐resistant cell lines as a strategy to better understand mechanisms of acquired resistance and as a strategy to potential identify companion agents that might overcome mechanisms of intrinsic resistance.22.1All drugs were purchased from Selleckchem  and were prepared in 100% DMSO.2.2The cutaneous T‐cell lymphoma line H9 was obtained from the American Type Culture Collection . Parental and derived resistant cells were grown in RPMI 1640 medium with 10% fetal bovine serum.2.3Western blotting was performed according to standard protocols, using chemiluminescence detection system . Primary antibodies against SLC19A1 , DHFR , dual specificity phosphatase four (DUSP4), STAT5, phospho‐STAT5 and β actin .2.4Cytotoxicity was performed on cultured cells using the Cell Titer Glo assay  as previously described.2.5H9 cells were seeded at concentration of 3 × 102.6RNA samples extracted from wild‐type and resistant cell lines were used for gene expression profiling and reverse transcription polymerase chain reaction (RT‐qPCR) analysis. cDNA was made using Omisncript RT Kit . Taqman Fast Advanced Master Mix and FAM‐MGB primers were purchased from Thermo Fisher . RFC (Hs00953344_m1), folylpolyglutamate synthetase (FPGS) (Hs00191956_m1), DHFR (Hs00758822_m1), gamma‐glutamyl hydrolase (GGH) (Hs00914163_m1). Reactions were conducted on a StepOnePlus Real‐Time PCR System .2.6.1Genomic DNA was extracted using a Quick‐DNA kit  and bisulfite treatment was carried out using a EZ DNA Methylation kit  following the manufacturer's instructions. Primers specific for the RFC promoter A and B regions and reaction condition were as previously described.2.7Total RNA was extracted using RNeasy mini kit  from cells collected after 24 hours incubation with or without drugs (MTX and PDX) and RNA quantitation and quality over assessed by the Agilent Bioanalyzer 2100. RNA libraries prepared from poly‐A pull‐down enrich mRNAs , were sequenced at the Columbia Genome Center using Illumina HiSeq2500/HiSeq4000. DEseq software, an R package based on a negative binomial distribution that models the number reads from RNA‐seq experiments and test for differential expression, was employed to test for differentially expressed genes under various conditions. For visualization, raw counts were normalized sample‐wise to reads per million and differential expression was calculated for each cell line as a z‐score centered at untreated controls. Hierarchical clustering was calculated by euclidean distance using the hclust function in the stats R package and visualized using the heatmap.2 function within the gplots R package. Unclustered heat maps were also generated with the heatmap.2 function with samples organized by cell line and drug concentrations and genes organized by pathway annotation. Principal component analysis (PCA) was prcomp function in the stats R package. In the matrix, each column represents a sample and each row represents a gene.33.1Two drug resistant cell lines, named H9‐12, and H9‐200, were derived from exponentially growing H9 cells, following exposure to increased PDX concentrations. H9‐12 and H9‐200 cells showed no sensitivity to drug concentrations that clearly induce cell death in the H9 parental cell line, indicating the emergence of a resistant phenotype. Cell viability of H9‐12 cells was not affected by a 20‐fold increase in drug concentration relative to H9 parental cells while H9‐200 cells showed no sensitivity to all tested PDX concentrations (≥1 mM). Figure A significant fold increase was observed in the concentration of PDX and MTX required to affect cell viability by 50% in drug resistant cells relative to their corresponding parental cells. The IC50 for PDX and MTX, after 48 hours of drug exposure, were estimated to be 3.3 and 6.4 nM for H9 cells, 34 and 170.2 nM for H9‐12 cells, and >1000 and 4073 nM for H9‐200 cells, respectively , an anthracycline (doxorubicin), the synthetic pyrimidine nucleoside prodrug gemcitabine and the proteasome inhibitor bortezomib. Concentration and time dependent sensitivity of the parental and the two resistant cell lines to all six single agents were similar . As shown in Figure DHFR gene was identified in the H9‐12 cell line. Increase (0.5‐fold) in DHFR RNA levels was also observed in the H9‐200 cells though of a lesser extent. Western blot analysis confirmed a corresponding increase in DHFR protein levels in the H9‐12 and H9‐200 cells  and decitabine (DAC) in order to determine if these hypomethylating agents could restore RFC expression and consequently sensitivity to PDX. As first step, H9, H9‐12, and H9‐200 were exposed to increased concentrations of AZA and DAC. Concentration and time dependent sensitivity of the parental and the two resistant cell lines to the two single agents were similar  of parental and resistant T‐cell lymphoma lines  exposed to single agents drugs were performed. Unsupervised hierarchical clustering and PCA revealed a clear distinction and close distribution based on cell types and treatment, indicating the consistency of the experiments as well as the specificity of treatment effects , and successfully confirmed the genes found to be up‐regulated in the differential expression analysis , affected by exposure to both MTX and PDX. An additional 43 and 33 genes that belong to the immune system and cell cycle were affected by exposure to MTX but not PDX. In contrast, exposure to PDX but not MTX affected 47 genes that belong to the metabolism of proteins canonical pathway. Lastly, exposure to both single agents affected the metabolism of RNA pathway but by modulating different (nonoverlapping) set of genes, 20 in case of MTX, 40 for PDX Figure . A superThe DUSP4 was among the genes whose expression was found upregulated after exposure to MTX or PDX Figure . As show4DHFR gene amplification and reduced RFC1 mRNA expression represent the two major mechanisms resulting in resistance to MTX and PDX, respectively  to elucidate the molecular mechanisms of action of PDX, (b) to clarify the mechanisms underlying clinical resistance to the drug, and (c) to evaluate new therapeutic strategies aimed at overcome drug resistance.O. O'. C. is a member of the Data Safety Monitoring Board at Celgene. He also receives research support from Celgene. Receives research support from Spectrum Pharmaceuticals. E. M. consulting for Spectrum Pharmaceuticals, Mundipharma. F. M. receives support from Seattle Genetics.Supporting information Figure 1 H9‐12 and H9‐200 retain resistance to PDX and MTX. (A) Growth inhibition curves following 24, 48 and 72 hours exposure of H9‐200 cells up to a 10.000 nM of pralatrexate (PDX). (B) Growth inhibition curves following 24, 48 and 72 hours exposure of H9‐12 (blue) and H9‐200 (red) cells, grown for a month in absence of drug, to increased PDX or methotrexate (MTX) concentration. IC50 values given in nanomolar concentrations for each time point. Error bars represent the SD of three or more separated experiments.Click here for additional data file.Supporting information Figure 2 H9, H9‐12 and H9‐200 similar sensitivity to bortezomib, doxorubicin and gemcitabine. Growth inhibition curves following 24 (blue), 48 (red) and 72 (green) h exposure to increased bortezomib, doxorubicin and gemcitabine concentration. IC50 values given in nanomolar concentrations for each time point. Error bars represent the SD of three or more separated experiments.Click here for additional data file.Supporting information Figure 3 Western blot analysis of transcription factor expression in parental and resistant cell lines. Sp1, Sp3, JUN and USF1 protein levels in H9, H9‐12 and H9‐200 cells as determined by western blot analysis.Click here for additional data file.Supporting information Figure 4 Unsupervised analyses of GEP of T cell lymphoma lines exposed to MTX and PDX. (A) Unsupervised hierarchical clustering divided the samples according to cell type and within each cell type to drug treatment. In the matrix, each column represents a sample and each row represents a gene. The color scale bar shows the relative gene expression changes normalized by the SD (0 is the mean expression level of a given gene). (B) Principle component analysis (PCA) showed a clear distinction based on cell types and treatment.Click here for additional data file.Supporting information Table 1 (Methotrexate)Supporting information Table 2 Click here for additional data file.


Naja spp.) contain high abundances of cytotoxins, which contribute to tissue necrosis in cobra envenomation. The tissue-necrotizing activity of cobra cytotoxins, nevertheless, indicates anticancer potentials. This study set to explore the anticancer properties of the venoms and cytotoxins from Naja sumatrana  and Naja kaouthia (monocled cobra), two highly venomous species in Southeast Asia. The cytotoxicity, selectivity, and cell death mechanisms of their venoms and cytotoxins  were elucidated in human lung (A549), prostate (PC-3), and breast (MCF-7) cancer cell lines. Cytotoxins were purified through a sequential fractionation approach using cation-exchange chromatography, followed by C18 reverse-phase high-performance liquid chromatography (HPLC) to homogeneity validated with sodium dodecyl sulfate-polyacrylamide gel electrophoresis, and identified by liquid chromatography-tandem mass spectrometry (LCMS/MS). The cobra venoms and their respective cytotoxins exhibited concentration-dependent growth inhibitory effects in all cell lines tested, with the cytotoxins being more potent compared to the corresponding whole venoms. NS-CTX and NK-CTX are, respectively, P-type and S-type isoforms of cytotoxin, based on the amino acid sequences as per LCMS/MS analysis. Both cytotoxins exhibited differential cytotoxic effects in the cell lines tested, with NS-CTX (P-type cytotoxin) being significantly more potent in inhibiting the growth of the cancer cells. Both cytotoxins demonstrated promising selectivity only for the A549 lung cancer cell line  but not in prostate (PC-3) and breast (MCF-7) cancer cell lines (selectivity index < 1). Flow cytometry revealed that the A549 lung cancer cells treated with NS-CTX and NK-CTX underwent necrosis predominantly. Meanwhile, the cytotoxins induced mainly caspase-independent late apoptosis in the prostate (PC-3) and breast (MCF-7) cancer cells lines but lacked selectivity. The findings revealed the limitations and challenges that could be faced during the development of new cancer therapy from cobra cytotoxins, notwithstanding their potent anticancer effects. Further studies should aim to overcome these impediments to unleash the anticancer potentials of the cytotoxins.Venoms of cobras ( Cancer is a disease characterized by abnormal and uncontrollable cell division. It has become the second leading cause of death globally, with 9.6 million deaths reported by the WHO in 2018 . ConventNaja spp.) causes fatal paralysis and debilitating complications resulted from extensive tissue necrosis  and Naja kaouthia (monocled cobra), which cause significant tissue necrosis in envenomed patients  venom was supplied by Queen Saovabha Memorial Institute (Bangkok), an antivenom manufacturing facility in Thailand. N. sumatrana (NS) venom was sourced from specimens in Negeri Sembilan  in Malaysia, provided by local snake keepers. The venoms were both pooled samples of the respective species comprising multiple adult snakes of mixed sexes. The collection of venom was conducted in accordance with protocol approved by the Institutional Animal Use and Care Committee (IACUC) of Faculty of Medicine, University of Malaya, Malaysia (code: #2013-11-12/PHAR/R/TCH). Both venoms were lyophilized samples stored at −20°C until use.Naja sumatrana and N. kaouthia venoms were separately reconstituted in eluent A  and fractionated with Resource S cation-exchange chromatography  applying the Shimadzu LC-20AD high-performance liquid chromatography (HPLC) system . The system was pre-equilibrated with eluent A, followed by elution with eluent B  using a linear-gradient flow of 0–30% B from 5 to 40 min and 30–100% from 40 to 65 min. The flow rate was set at 1 ml/min. Protein elution was monitored at 280 nm absorbance, and the fractions containing cytotoxins (CTX) were manually collected with reference to the venom proteomes reported earlier for N. sumatrana (N. kaouthia (umatrana  and N. kkaouthia . The proN. sumatrana and N. kaouthia venoms) were reconstituted in Solvent A [0.1% trifluoroacetic acid (TFA) in ultrapure water]. The cytotoxins were subjected to further purification using LiChrospher WP 300 C18 (5 μm pore size) reverse-phase column applying the Shimadzu LC-20AD HPLC system . The column was pre-equilibrated with solvent A, followed by elution with solvent B (0.1% TFA in acetonitrile), with a linear gradient of 5% for 10 min, 5–15% for 20 min, 15–45% for 120 min, and 45–70% for 20 min, as described by Cytotoxin-containing fractions eluted from Resource S cation-exchange chromatography . Electrophoresis was conducted at 90 V for 2.5 h. Visualization of proteins was achieved by Coomassie Brilliant Blue R-250 stain.Five micrograms (μg) of the purified NS-CTX and NK-CTX were subjected to 15% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) under reducing conditions for purity check. The molecular weights of the proteins were calibrated with the ExcelBand® C18 pipette tip . Digested peptides were subsequently subjected to nano-electrospray ionization-liquid chromatography-tandem mass spectrometry (nano-ESI-LC-MS/MS) with Agilent 1200 HPLC-Chip/MS Interface, coupled with Agilent 6520 Accurate-Mass Q-TOF LC/MS system, as previously described by 18 enrichment column, followed by 75 μm × 150 mm analytical column (Agilent No. G4240-62010); 0.1% formic acid in water and 90% acetonitrile in water with 0.1% formic acid were used as eluting solvents A and B, respectively. A stepwise linear gradient was applied: 3–50% solvent B for 30 min, 50–95% for 2 min, and 95% for 5 min. The ion polarity was set to positive. Drying gas was set to 325°C with a drying gas flow rate of 5 l/min. Capillary voltage was adjusted to 1995 V while the fragmentor voltage was set to 175 V. Spectra acquisition was done in MS/MS mode with MS scan range of 110–3000 and 50–3000 m/z. Precursor change selection was set to include a doubly, triply, or more charged state, excluding the precursors 922.0098 m/z (z = 1) and 121.0509 (z = 1) which were used as reference ions. Data were obtained with MH+ range between 600 and 4000 Da and processed using Agilent Spectrum Mill MS Proteomics Workbench software packages. The peptide finger mapping was searched against the non-redundant NCBI database of Serpentes (taxid: 8570)1. Carbamidomethylation of cysteine was set as a single modification. Protein identification was validated with the following filtering parameters: protein score > 11, peptide score > 6, and scored peak intensity (SPI) > 60%. The peptide information of cytotoxin identification was included as Separately, 5 μg of the purified NS-CTX and NK-CTX were subjected to LCMS/MS for protein identification. The CTXs were reduced with dithiothreitol (DTT), alkylated with iodoacetamide (IA), and digested with MS grade Pierce trypsin protease  according to the manufacturer’s protocol. The digested peptides were then desalted and extracted with Millipore ZipTip2 using Jalview  were cultured in DMEM  with 10% FBS  and 1% penicillin-streptomycin ; lung  and prostate  cancer epithelial cells were maintained in RPMI  with 10% FBS and 1% penicillin-streptomycin; normal breast epithelial cells  were grown in MEBMTM  with 10% FBS and 1% penicillin-streptomycin; normal lung epithelial cells  raised in Ham’s F-12 medium  with 10% FBS and 1% penicillin-streptomycin. Normal prostate epithelial cells  were cultivated in GibcoTM Keratinocyte-SFM  with 1% penicillin-streptomycin. All cells were grown in sterile flasks (T25/T75) at <90% confluence at 37°C with 5% CO2 in a humidified atmosphere. Cells were passaged in accordance with ATCC guidelines, with trypsin-EDTA  and cryopreserved in its respective complete medium with 10% DMSO  in Mr. FrostyTM freezing container  at −80°C.Both cancer and normal cell lines were obtained from ATCC . Breast cancer epithelial cells  and N. kaouthia (NK-CTX) in complete culture medium (μg/ml) or equal volume of complete medium without venom as the negative control or 5-fluorouracil  as positive control. Cytotoxicity was assessed 72 h post-treatment with 10% MTT, incubated at 37°C in the dark for 3 h. Cells were ruptured and the purple formazan was dissolved with 200 μl of DMSO. Finally, data were quantified by obtaining the absorbance at 570 nm using ChameleonTM VS Multilabel microplate reader . All assays were performed in triplicates. Cell viability percentage was calculated as:Cytotoxicity was tested with MTT  assay. Twenty-four hours prior to venom treatment, 100 μl aliquots of optimum cells (3000–4000 cells/well) were seeded into 96-well microtiter plates. Cells were introduced with 200 μl of diluted suspensions of crude venom or purified CTX of 50) and statistical significance was determined using one-way ANOVA, with Bonferroni post-test  via GraphPad Prism (Version 5.03). The results were expressed as mean of triplicates ± SEM.Half maximal inhibitory concentration (IC–/PI–), early apoptosis (annexin V+/PI–), late apoptosis/secondary necrosis (annexin V+/PI+), or necrosis (annexin V–/PI+). In brief, 500,000 cancer cells  were seeded in sterile T25 flasks 24 h prior to treatment with their respective IC50 of purified cytotoxins or 5FU (positive control) for 72 h. The cells were then washed twice with cold Dulbecco’s Phosphate Buffered Saline , resuspended in binding buffer, and stained for 15 min in the dark with Annexin V and propidium iodide as per manufacturer’s instructions ; 10,000–15,000 events were compensated and acquired with flow cytometer , equipped with blue laser (488 nm) and emission filters of 488/10 for FITC and 585/42 (556 LP) for PI. The FACSDiva software  was utilized in data analysis.Flow cytometry with Annexin-V-fluorescein isothiocyanate (FITC) conjugated/propidium iodide stains was used to determine phosphatidylserine externalization. The cells were grouped as viable (annexin V3 via the iProX partner repository (The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortiumpository  with theN. sumatrana (NS) and N. kaouthia (NK) exhibited concentration-dependent cytotoxic activities toward the three cancer cell lines tested, with varying half maximal inhibitory concentrations (IC50) (50 = 2.21-3.26 μg/ml), moderately cytotoxic to the prostate cancer cell line , and least cytotoxic toward breast cancer cell line   (p < 0.001). N. kaouthia venom had a narrower range of cytotoxicity across the three cancer cell lines, with the activity being highest in the A549 cell line (IC50 = 3.26 ± 0.39 μg/ml) (p < 0.001).The venoms of s (IC50) . Both co7 μg/ml) . N. suma18 reverse-phase HPLC. The major CTXs of N. sumatrana (NS-CTX) and N. kaouthia (NK-CTX) were eluted within 110–125 min , respectively  < PC-3 (IC50 = 3.13–4.46 μg/ml) < A549 (IC50 = 0.88–1.22 μg/ml) (50 = 2.83–6.21 μg/ml) and prostate (RWPE-1: IC50 = 0.35–0.65 μg/ml) were more susceptible to NS-CTX and NK-CTX compared to their respective cancer cell lines, demonstrating no cancer cell-type selectivity. In contrast, NS-CTX and NK-CTX showed selectivity for lung cancer cell line (A549) over the normal lung cell line (NL20), with a selective index of 2.17 and 2.26, respectively  showed dose-dependent cytotoxic activities in the cancer cell lines tested  and their corresponding normal cell lines  . In canc2 μg/ml) . NS-CTX ectively .Microscopic observation revealed morphological changes of cell clustering and shriveling in both cancer and normal lung (A549 and NL20) and prostate (PC-3 and RWPE-1) cell lines treated with NS-CTX and NK-CTX . In breaFlow cytometry demonstrated varying cell death mechanisms, predominantly necrosis and late apoptosis in the cancer cell lines upon treatment with NS-CTX and NK-CTX . Both NSN. sumatrana and N. kaouthia venoms in lung (A549), prostate (PC-3), and breast cancer (MCF-7) cell lines. The venom cytotoxic effects were more prominent in A549 and PC-3 cell lines than MCF-7 cell line, suggesting higher tissue specificity toward the lung and prostate cancer cell lines. The major cytotoxins from both venoms were purified to homogeneity, validated by LCMS/MS, and investigated for their cytotoxic properties in the cancer cell lines. The respective cytotoxins also exhibited a similar trend of tissue specificity as with their venoms toward the A549 and PC-3 cancer cell lines, unveiling the therapeutic potentials of cobra-derived cytotoxins against these cancers. The purified CTXs were apparently more potent (with lower IC50) compared to the respective crude venoms, supporting that these proteins are the main cytotoxic component in the cobra venoms implicated in tissue necrosis , on the other hand, indicated that the genes of both P-type and S-type CTX could well be conserved in other cobra species  and breast (MCF-7) cancer cell lines, implying limited application of the toxins against these cancer cells. The higher selective cytotoxicity of the cytotoxins in A549 cell lines could be attributed to the unique characteristic of non-small lung cancer cell membrane, in which phosphatidylinositols are present abundantly , tested on assorted cancer cell lines , prostate (PC-3), and breast (MCF-7) cancer cell lines. Overview of the IC50 of cytotoxins from various Naja spp. showed wide-ranging differential cytotoxicity  in the different mammalian cell lines, treated with cytotoxin between 12 and 72 h. However, a much broader range of IC50 was seen in the purified cytotoxins of N. oxiana, N. haje, and N. nigricollis, with values wide ranging from 0.33 to 132 μM tested in lung, peripheral blood, breast, and colon cancer cell lines (N. naja and N. oxiana), and that the normal breast cell line tested in the present study (184B5) was indeed the corresponding normal mammary gland epithelial cells, in contrast to the MCF10A cell line which was the immortalized, normal-like mammary gland epithelial cells (with fibrocystic disease background) used in the previous studies  treated with N. atra and N. naja cytotoxins appeared in the late apoptotic stage  and N. kaouthia (NK-CTX) were highly potent in inhibiting the growth of the lung (A549), prostate (PC-3), and breast (MCF-7) cancer cell lines but lack selectivity for the latter two cell lines. Although NS-CTX and NK-CTX exhibited good selectivity in the lung A549 cancer cell line , the cell death pathway was predominantly by necrosis, questioning its use as a safe anticancer candidate. The study underscores the need for a comprehensive, fundamental investigation that addresses the selectivity and cell death mechanism of venom proteins, in the quest of novel anticancer agents. The anticancer potential of the toxins, however, may be further improved through structural modification to deliver a more specific, molecularly targeted cancer therapy in the future.The development of peptide-based anticancer drug has been gaining momentum in recent years due to the possibility of improved potency, efficacy, and minimal systemic toxicity. The cobra cytotoxins have such potentials but their highly evolved, diet-adapted cytotoxic nature might have limited the intended application as a safe and effective drug. The present study demonstrated such challenges and dilemma in developing these cytotoxic proteins as anticancer therapies. The cytotoxins from All datasets presented in this study are included in the article/CHT and KYT conceptualized the study, designed the study and methodology, and provided resources. HPC was involved in the investigation, analysis, data validation, and writing the original draft of manuscript. All authors reviewed, edited, and approved the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Feline mammary tumors (FMT) are very common in cats, associated with very aggressive behavior and a short life expectancy. Surgery is the most used treatment but tumor recurrence is common. Currently, available therapies are insufficient, therefore, new molecular targets are needed to develop more efficient therapeutics. Histone deacetylases inhibitors (HDACis) have been developed to target tumor cells, by disrupting gene expression and leading to cell death. Microtubules inhibitors (MTIs) have also been a focus of research, to target polymerization of microtubules, and consequently disturbing the cytoskeleton and leading to cell cycle arrest and apoptosis. However, there are few studies on the use of HDACis and MTIs in cats. In this study, we addressed if these two drug classes could be used as new therapeutic options in FMTs. All HDACis and MTIs exhibited suitable and dose-dependent antitumor effects in FMT cell lines. Immunoblot analysis confirmed that the mode of action of HDACis is conserved in feline mammary tumor cell lines. Finally, flow cytometry showed that exposure with HDACis and MTIs lead to the induction of cellular apoptosis. In summary, HDACis and MTIs possess antitumor properties suggesting further studies on their use in the treatment of feline mammary tumors.Feline mammary carcinoma (FMC) is the third most common type of neoplasia in cats, sharing similar epidemiological features with human breast cancer. In humans, histone deacetylases (HDACs) play an important role in the regulation of gene expression, with HDAC inhibitors (HDACis) disrupting gene expression and leading to cell death. In parallel, microtubules inhibitors (MTIs) interfere with the polymerization of microtubules, leading to cell cycle arrest and apoptosis. Although HDACis and MTIs are used in human cancer patients, in cats, data is scarce. In this study, we evaluated the antitumor properties of six HDACis  and four MTIs  using three FMC cell lines , and compared with the human breast cancer cell line (SK-BR-3). HDACis and MTIs exhibited dose-dependent antitumor effects in FMC cell lines, and for all inhibitors, the IC50 values were determined, with one feline cell line showing reduced susceptibility (FMCm). Immunoblot analysis confirmed an increase in the acetylation status of core histone protein HDAC3 and flow cytometry showed that HDACis and MTIs lead to cellular apoptosis. Overall, our study uncovers HDACis and MTIs as promising anti-cancer agents to treat FMCs. In addition to the clinicopathological characteristics, the molecular immunophenotyping of feline mammary carcinomas (FMCs) is similar to what is described for human breast cancer ,2. MoreoHistone deacetylases (HDACs) play an important role in the regulation of gene expression at the chromatin level, and their dysregulation has been associated with the development of cancer ,8. In reIn parallel, microtubules (MT) are dynamic structures composed of tubulin polymers that play an important role in cell growth, division, and intracellular trafficking, and have been the focus of research for cancer treatment ,11. MT iSo far, very few studies on the use of HDACis and MTIs have been published in cats ,13,14. Iv/v) fetal bovine serum  and incubated at 37 °C in a humidified atmosphere of 5% (v/v) CO2. All cell lines were inspected periodically for their cellular morphology and proliferation rate.The three feline mammary carcinoma cell lines used in this work were CAT-MT , FMCp, and FMCm . For comparison purposes, we used the human breast cancer cell line SK-BR-3 . CAT-MT and SK-BR-3 cell lines were maintained in Dulbecco’s Modified Eagle Medium , whereas FMCp and FMCm cell lines were maintained in Roswell Park Memorial Institute 1640 Medium , all supplemented with heat-inactivated 20% , progesterone receptor (PR), epidermal growth factor receptor type 2 (HER2), cytokeratin 5/6 (CK 5/6), and Ki-67 proliferation index (Ki-67) was performed in feline  and in human (SK-BR-3) cell lines, as previously reported . Briefly3 cells/well for CAT-MT and FMCp, 1.5 × 104 cells/well for FMCm, and 1 × 104 cells/well for SK-BR-3). Then, cells were left unexposed or exposed to increasing concentrations of each HDACi  or MTIs . Dimethyl sulfoxide, knowns as DMSO  and ethanol (for colchicine) were used as vehicle control at a maximum final concentration of 1%. After 72 h of drug exposure, the WST-1 reagent was added, followed by an incubation period of 4 h at 37 °C. Absorbance at 440 nm was measured using a plate reader . Duplicate wells were used to determine each data point and three independent experiments were performed on different days. Best-fit IC50 values were calculated using the log (inhibitor) vs. response (variable slope) function in GraphPad Prism .To investigate the effect of six HDACis  and four MTIs , cell viability assays were performed using the Cell Proliferation Reagent WST-1 , according to the manufacturer’s instructions. Briefly, the feline cell lines CAT-MT, FMCp and FMCm, and the human cell line SK-BR-3 were seeded in 96 well plates to obtain confluency of 90% after 24 h . Then, cells were left unexposed or exposed to the IC50 concentration of each HDACi. DMSO was used as vehicle control at a maximum final concentration of 1%. After 72 h of drug exposure, cells were collected using 50 μL of RIPA lysis buffer  supplemented with 1% 100× Halt™ protease inhibitor cocktail EDTA-free  and 2 mg/mL Iodoacetamide , and stored at −80 °C. Before immunoblotting, total cell protein extracts were resuspended in 10 μL of SDS-PAGE Loading Buffer 5× , denatured 10 min at 100 °C, and resolved in 12% SDS-PAGE. Proteins in the gel were transferred onto nitrocellulose membranes  and blocked in 4% (w/v) dried skimmed milk diluted in PBS containing 0.1% (v/v) Tween-20. The membranes were probed with primary and horseradish peroxidase-conjugated secondary antibodies  and detected using ECL Clarity , in a Chemidoc XRS+ System . Three independent experiments were performed on different days. Densitometry of the correspondent bands was performed using Fiji Image J (open-source version for Windows®) and statistical analyses were conducted using GraphPad Prism . The p-values were calculated by a two-tailed unpaired Student’s t-test relative to non-treated cells .To prepare total cell protein extracts, the feline cell lines CAT-MT and FMCp and the human cell line SK-BR-3 were seeded in 24 well plates (two wells per sample) in order to obtain confluency of 90% after 24 h . Cells were then left unexposed or exposed to the IC50 concentration of each HDACi. DMSO  and ethanol (colchicine) were used as vehicle control at a maximum final concentration of 1%. After 72 h of exposure, supernatants were harvested and the remaining attached cells were trypsinized and added to the correspondent supernatants. Samples were centrifuged for 5 min at 500 g and at room temperature, washed with PBS, and resuspended in 500 μL PBS containing 2% FBS. To each sample, 50 μL Guava Nexin reagent was added and incubated for 20 min at room temperature (protected from light), before acquisition in a BD LSR Fortessa ×20 . Data were analyzed using FlowJo™ v10.6.1 .The percentage of apoptotic cells after HDACis or MTIs exposure was measured by using the Guava Nexin Assay , according to the manufacturer’s instructions. The different staining of the cells allows to distinguish between viable (Annexin V/7-AAD double negative), early apoptotic (Annexin V positive/7-AAD negative), and late-apoptotic/dead cells (Annexin V/7-AAD double positive). The feline cell lines CAT-MT and FMCp, and the human cell line SK-BR-3 were seeded in 24 well plates (two wells per condition) to obtain confluency of 90% after 24 h  and four MTIs , using the three above mentioned feline cell lines and the human breast cancer cell line, as control. CAT-MT, FMCp, FMCm, and SK-BR-3 were incubated with increasing concentrations of each HDACi or MTIs for 72 h and the cytotoxicity of the compounds was measured using the WST-1 assay. As shown in The main mode of action of the HDACi compounds is to modify the acetylation status of core histone proteins. The inhibition of histone deacetylation enzymes results in the accumulation of the acetylated forms inside the cell nucleus, leading to chromatin relaxation and subsequent cytotoxicity due to disrupted gene expression. To understand if HDACis are inhibiting histone deacetylation in the feline cell lines, we evaluated the acetylation status of the histone H3 by immunoblot and densitometry. CAT-MT, FMCp, and SK-BR-3 cell lines were incubated with the correspondent IC25 and IC50 of each compound for 72 h , and totTo confirm that the reduction in cell viability of the feline cell lines after exposure with HDACi or MTI compounds is consistent with the induction of apoptosis, we analyzed Annexin V/7-AAD staining by flow cytometry, following 72 h of incubation with the IC50 concentration of each HDACi or MTI . As showBecause the majority of FMTs are malignant, early detection and effective therapy have a major impact on survival time . Thus, tNew drugs for breast cancer treatments have been investigated mainly in murine cancer models, such as genetically engineered mice or human-mouse xenograft models. Although their unquestionable value, they have some limitations ,19. WhilIn this study, both HDCAis and MTIs showed promising results in CAT-MT and FMCp cell lines. However, the FMCm cell line exhibited a pattern of reduced susceptibility when exposed to these compounds. Indeed, the acetylation levels of histone H3 remain unchanged in the FMCm cell line, after exposure to the IC50 values obtained for CAT-MT (data not shown). Drug resistance has a dramatic effect on cancer therapy and a drastic impact on patient survival. Drug resistance can develop at the cell level (changes in the target protein) or as a consequence of poor accessibility of the compound (changes in the transport in and out of the cell) . MultiplRegarding the veterinary clinical setting, the therapeutic potential of HDACis have been demonstrated, but mainly on dogs. Vorinostat (SAHA) was evaluated in canine cell lines and corresponding xenograft models and showed promising results in the treatment of relevant dog cancers, such as canine urothelial carcinoma, osteosarcoma, prostatic carcinoma, T-cell lymphoma, and melanoma ,28. The This study tested six HDACis and four MTIs in feline mammary carcinoma cell lines, demonstrating its antitumor effect, and also a conserved genetic and cell death mechanisms, by comparison with the human cell line, SK-BR-3. Moreover, this study suggests new molecular targets for the treatment of mammary tumors in cats, and extend the knowledge about the similarities between the feline mammary tumor and human breast cancer, further supporting the utility of the domestic cat as a valuable model for comparative oncology studies.


We aimed to discover cell line‐specific overexpressed HOX genes responsible for chemoresistance and to identify the mechanisms behind HOX‐induced cell line‐specific chemoresistance in EOC. Ten HOX genes and eight EOC cell lines were tested for any cell line‐specific overexpression that presents a mutually exclusive pattern. Cell viability was evaluated after treatment with cisplatin and/or siRNA for cell line‐specific overexpressed HOX genes. Immunohistochemical (IHC) staining for HOXB9 was performed in 84 human EOC tissues. HOXA10 and HOXB9 were identified as cell line‐specific overexpressed HOX genes for SKOV‐3 and RMUG‐S, respectively. Inhibiting the expression of cell line‐specific HOX genes, but not of other HOX genes, significantly decreased cell viability. In SKOV‐3 cells, cell viability decreased to 46.5% after initial 10 µM cisplatin treatment; however, there was no further decrease upon additional treatment with HOXA10 siRNA. In contrast, cell viability did not significantly decrease upon cisplatin treatment in RMUG‐S cells, but decreased to 65.5% after additional treatment with HOXB9 siRNA. In both cell lines, inhibiting cell line‐specific HOX expression enhanced apoptosis but suppressed the expression of epithelial‐mesenchymal transition (EMT) markers such as vimentin, MMP9, and Oct4. IHC analysis showed that platinum‐resistant cancer tissues more frequently had high HOXB9 expression than platinum‐sensitive cancer tissues. HOXB9, which is overexpressed in RMUG‐S but not in SKOV‐3 cells, appeared to be associated with cell line‐specific platinum resistance in RMUG‐S. Inhibiting HOXB9 overexpression in RMUG‐S cells may effectively eliminate platinum‐resistant ovarian cancer cells by facilitating apoptosis and inhibiting EMT. Different expression patterns and its prognostic value of HOX genes across distinct histologic subtypes of EOC have also been shown in several other studies.HOX genes drive normal organogenesis through morphogenesis and terminal differentiation. Cheng et al showed that several HOX genes are differentially expressed in the fallopian tubes, uterus and vagina, but not in normal ovarian epithelium.This study aimed to discover any cell line‐specific overexpressed HOX genes that may be attributed to chemoresistance, as well as identify the mechanisms underlying HOX‐induced cell line‐specific chemoresistance in EOC cell lines.22.1SKOV‐3, a human ovarian cancer cell line of serous histology, was purchased from the American Type Culture Collection (ATCC). RMUG‐S, a human ovarian cancer cell line of mucinous histology, was obtained from the Japanese Collection of Research Bioresources Cell Bank (JCRB). siRNAs for human HOXA10 (5′‐ CCGGGAGCUCACAGCCAACUUUAAUUU −3′) and HOXB9 (5′‐ GGAAGCGAGGACAAAGAGAGGUU −3′) were synthesized by Genolution , and the control siRNA (sc‐37007) was purchased from Santa Cruz Biotechnology. The transient transfection experiment with the synthesized and control siRNAs was performed using Lipofectamine RNAi MAX™ according to the manufacturer's instruction (Invitrogen).2.2Cells were lysed, and proteins were transferred to a polyvinylidene fluoride (PVDF) membrane. Membranes were incubated with anti‐HOXA10 (sc‐271954), anti‐HOXB9 (sc‐398500), anti‐E‐cadherin (#3195), anti‐Vimentin (#5741), anti‐MMP9 (#3852), anti‐SOX2 (#2748), anti‐Nanog (#3580), anti‐Oct4 (#2750) and anti‐alpha‐tubulin (sc‐5286) antibodies.Cellular RNA was extracted from cells using the TRIzol reagent according to the manufacturer's instructions. Complementary DNA (cDNA) was synthesized from 2 µg of RNA using a reverse transcription kit (Promega) and each primer pair (Yingjun Biotechnology Corporation).2.3Annexin V‐FITC assay was carried out using the FITC Annexin V Apoptosis Detection Kit (BD Bioscience) according to the protocols provided. Flow cytometric analysis was performed using a FACS Calibur (BD Bioscience) flow cytometer, by analysing at least 10 000 cells per sample.2.4HOXA10 or HOXB9 siRNA for 72 hours. TUNEL was subsequently performed using the In Situ Cell Death Detection Kit (Roche) according to the manufacturer's instructions.The cells were transfected with either 2.5HOXA10 or HOXB9 siRNA, were incubated overnight or until a monolayer formed. The monolayers were scratched with a 200‐µL sterile pipette tip and then washed with media to remove the detached cells and debris.The cells, which were transfected with 5 cells were added to each transwell invasion chamber coated with 1 mg/mL Matrigel . After transfection with either HOXA10 or HOXB9 siRNA, the remaining cells on the membrane were fixed for 10 minutes in methanol, stained with 1% crystal violet solution, and then washed with PBS.Cell invasion was measured in a transwell chamber. In brief, 2 × 102.6HOXB9 nuclear staining was graded: negative, weak (1+), moderate (2+) or strong (3+). IHC scoring was performed according to the following criteria by MK and JYC  staining of ovarian cancer tissues from an 84‐tissue microarray (TMA) was approved by the Institutional Review Board. The TMA was established using tissue from women who underwent surgery for the treatment of EOC between February 2000 and November 2009. Intensity of 2.7t test was applied. Progression‐free survival (PFS) and overall survival (OS) were evaluated using the Kaplan‐Meier method. Statistical significance was taken as P < .05.Data are presented as means with standard deviations. When comparing between two groups, Student's 3HOX genes whose expression levels were tested in eight EOC cell lines, HOXA10 in SKOV‐3 and HOXB9 in RMUG‐S were identified to have cell line‐specific overexpression with a mutually exclusive pattern between the two cell lines  and HOXB9 siRNAs , respectively, compared with those treated with non‐targeting siRNA controls  female patients. Unlike the results observed in the cell lines, high HOXB9 expression was not associated with mucinous histology in EOC patients . However, high HOXB9 expression was not associated with 5‐year PFS  and OS . High expression of 4HOXB9 may contribute to platinum resistance in RMUG‐S by promoting apoptosis escape, as well as EMT.Apoptosis escape and EMT have been considered to be key processes in chemoresistance according to previous studies.HOXB9 to possibly be responsible for chemoresistance in a mucinous EOC cell line, RMUG‐S. Demonstration of the association of HOXB9 high expression and platinum resistance using clinical data and human tissue was also a strength of our study; although, we were unable to show any independent survival impact due to HOXB9 high expression. This may be attributed to the small sample number of our study, as well as to the use of a small fractionated TMA block instead of whole ovarian cancer tissues.There were only a few studies that reported on the impact of HOX expression on chemoresistance or prognosis in EOCs.HOXB9, which was found to be overexpressed in RMUG‐S but not in SKOV‐3 cells, appeared to be associated with cell line‐specific platinum resistance. Inhibiting HOXB9 overexpression in RMUG‐S cells can effectively kill platinum‐resistant ovarian cancer cells by facilitating apoptosis and inhibiting EMT. Further in vivo studies and clinical trials are necessary to develop an individualized strategy for effectively controlling chemoresistance in mucinous type EOCs.The authors confirm that there are no conflicts of interest.M. Kim, D. H. Suh and Y. B. Kim conceived and designed the study; M. Kim, D. H. Suh, J. Y. Choi, S. Lee and J. R. Bae performed the data analysis and interpreted the results; M. Kim wrote the manuscript and K. Kim, J. H. No and Y. B. Kim reviewed and revised the manuscript. All authors reviewed the final manuscript. Click here for additional data file. Click here for additional data file.


Predicting the drug response of the cancer diseases through the cellular perturbation signatures under the action of specific compounds is very important in personalized medicine. In the process of testing drug responses to the cancer, traditional experimental methods have been greatly hampered by the cost and sample size. At present, the public availability of large amounts of gene expression data makes it a challenging task to use machine learning methods to predict the drug sensitivity.In this study, we introduced the WRFEN-XGBoost cell viability prediction algorithm based on LINCS-L1000 cell signatures. We integrated the LINCS-L1000, CTRP and Achilles datasets and adopted a weighted fusion algorithm based on random forest and elastic net for key gene selection. Then the FEBPSO algorithm was introduced into XGBoost learning algorithm to predict the cell viability induced by the drugs. The proposed method was compared with some new methods, and it was found that our model achieved good results with 0.83 Pearson correlation. At the same time, we completed the drug sensitivity validation on the NCI60 and CCLE datasets, which further demonstrated the effectiveness of our method.The results showed that our method was conducive to the elucidation of disease mechanisms and the exploration of new therapies, which greatly promoted the progress of clinical medicine. In recent years, the study of cell death process has always been the hot topics in biology and medicine . With thCell perturbation signatures are closely related to the cell viability with the action of the compounds. In the study of drug sensitivity and anticancer drug response prediction, we can predict cell phenotypes from different high-coverage molecular data since compounds control the expression and function of target proteins or enzymes in the apoptotic pathway and induce abnormal cell apoptosis. Because clinical collection of experimental data on patient and drug interactions are expensive and impractical, it was expected that the preclinical prediction models based on large-scale pharmacogenomics of cancer cell lines could be applied. In recent years, the prediction model scheme designed by machine learning method from the perspective of cell viability research has made breakthrough progress. Based on the genomic background of each cell lines, Michael P. Menden. et al. trained a neural network model to predict its IC50 distribution throughout the cell lines .They fouIn this study, we developed the WRFEN-XGBoost algorithm to predict the cell viability under the drug induction using LINCS-L1000 perturbation signatures. Firstly, we screened and matched the three data sets, including perturbation transcriptomics signatures (LINCS-L1000), cancer treatment response portal (CTRP) and cancer dependence map database (Achilles), and divided them into nine data subsets. Secondly, we proposed a weighted fusion algorithm based on random forest and elastic nets to effectively extract non-linear features between differentially expressed genes and cell viability, and completed the selection of key genes. Then, we used the XGBoost algorithm to predict the cell viability and analyzed the apoptosis response under the action of drug toxicity and gene silencing. At the same time, in order to avoid the problem of tedious parameter adjustment, we introduced the FEBPSO algorithm into the XGBoost learning algorithm. Finally, in order to measure the feasibility of our method, we completed cross-dataset validation between compounds and shRNAs at different perturbation times. In addition, we validated the drug sensitivity inference on the two benchmark data sets of CCLE and NCI60.https://www.ncbi.nlm.nih.gov/geo/. To analyze the cellular response of the cancer cell lines to specific therapeutic drugs, we used the Cancer Treatment Response Portal (CTRP), which covered the link between compound sensitivity and genetic or lineage characteristics in 70,000 cancer cell lines. We selected post-quality-control cell viability values as a target for our modeling, which could be downloaded from the website https://ocg.cancer.gov/programs/ctd2/data-portal [https://portals.Broadinstitute.org/achilles and we selected the log fold scores of effects change before and after shRNA treatment for our model analysis [We used five datasets in this study, including the perturbation transcriptomics signatures (LINCS-L1000), the Cancer Therapeutics Response Portal (CTRP), the Cancer Dependence Map Database (Achilles), the Cancer Cell Line Encyclopedia (CCLE) and NCI-60 dataset. LINCS adopted L1000 technology to detect the transcriptome expression data in human cancer cell lines under various external stimulation. The expression of the whole genome was extrapolated by detecting the expression levels of 978 genes , 13. Thea-portal . The thianalysis .https://dtp.cancer.gov/discovery_development/nci-60, and we set GI50 value as the evaluation standard for drug sensitivity [https://portals.broadinstitute.org/ccle, and we used the active area of the drug as the evaluation standard for drug sensitivity [To verify the effectiveness of our prediction model, we used the NCI-60 dataset and the Cancer Cell Line Encyclopedia (CCLE) as validation datasets in the end, respectively. The NCI-60 dataset could be downloaded from website sitivity . The lassitivity .Cdose was the concentration value corresponding to the cancer treatment drug in CTRP, and Ldose was the concentration value corresponding to the perturbation signatures in LINCS-L1000.We first merged the two-stage perturbation screens LINCS-L1000-PhaseI and LINCS-L1000-PhaseII, and obtained the genome-wide gene expression levels under various perturbations in LINCS-L1000. To further analyze the cell viability of different cell lines under the compound perturbation, we correlated it with the cell viability data after drug treatment in CTRP. We matched the sample instances based on the same cell line and the drug identification number provided by the Broad Institute. We referred to , we used a weighted fusion algorithm of the random forest and elastic network (referred as WRFEN) to select key genes.We ranked the key genes in the random forest and elastic network respectively, and use  to perfok-th decision tree for the i-th sample on the selected differentially expressed gene set DEGs. K is the number of decision trees. Then during the t-th iteration of the sample, the model’s predicted value i during the k-th iteration, i during the k-th iteration, w is the inertial weight, XGBoost is one of the most competitive prediction algorithm in machine learning. It improves the integration of the gradient boosting algorithm and has high performance in solving both classification and regression problems . We usedproblems . Meanwhiproblems . In the T denotes the maximum number of iterations, k is the current number of iterations, In order to overcome the shortcomings of premature convergence and falling into local extremes of particle swarm optimization, we used the formula shown below to update the weights .6\documeWe used WRFEN for core gene selection and FEBPSO-XGBoost for predictive analysis. Through this, we formed a complete prediction model and explained the complete apoptotic levels observed in cell lines with specific drugs and concentrations.Based on the latest transcriptomic perturbation screens in LINCS-L1000, we conducted the study with the cell viability after the drug treatment in CTRP and the effect change score before and after the treatment with shRNA in the Achilles project, respectively. From the perspective of gene regulation, we examined the relationship between key genes and drug response. At the same time, the FEBPSO-XGBoost machine learning algorithm was used to predict the cell viability of different cell lines with the treatment of various drugs or shRNA by using the expression levels of characteristic genes under the action of different perturbation times and different drug concentrations.In the feature selection process, we firstly selected 40 trees for the establishment of a random forest, and the results were ranked according to the variable contribution. Secondly, the ratio of the lasso penalty term was set to 0.1, 0.2,0.5,0.7,0.95,1 and the coefficient penalty term was controlled to from 0.1 to 1.0 by step 0.1 in the elastic net. The best combination of the parameters was decided on the validation set. Then, we sorted the variables according to their contribution and deleted the non-contributing genes. Finally, we calculated the selected characteristic genes according to Formula . In the NCI60 dataset, when the efficacy was within the range of 50% growth inhibition concentration, it corresponded to the GI50 value in the drug sensitivity evaluation index. When the efficacy was not effective within the 50% growth inhibition concentration range, it was recorded as the highest concentration value. In this study, we would define the drug concentration difference variable, which portrayed the efficacy of the drugs and was calculated as shown in Formula . In otheIn this study, ROC curve and PR curve were used to measure the contribution of the algorithm in evaluating the drug effectiveness. By observing the ROC curve shown in Fig. Furthermore, we also matched and correlated the LINCS-L1000 perturbation screens, CTRP data and NCI60 data according to the matching method described above. The drug with the perturbation time of 24 h was recorded as LINCS-L1000-CTRP-NCI60-24h. In this experiment, we used CTRP-L1000-6h, CTRP-L1000-24h and Achilles-L1000-96h models to predict the cell viability in three major data sets, which had drugs and cell lines in common. We also binarized the drug sensitivity data in NCI60.Finally, we used the ROC curve and PR curve to discuss and analyze the experimental results. As shown in Additional file While predicting the effectiveness of the drugs, we required that the predictors used in this study could make effective predictions. In addition, whether the appropriate features could be selected during the feature selection stage directly affected the predictive performance of the predictors. To do this, we correlated the selected feature genes with the effectiveness of the drug. We observed whether the differential expression levels of selected characteristic genes have significantly different expression patterns under the action of effective or ineffective drugs. For this reason, we mapped the differential expression levels of the first 15 differentially expressed genes selected in the feature selection stage under the treatment of effective drugs and ineffective drugs. Figure So far, we had completed inferring the effectiveness of the drug from the predicted cell viability of each model. To further examine whether there was a significant difference between the effective and ineffective drugs on the cell viability, we used a non-parametric Mann Whitney test to analyze the cell viability prediction results, as shown in Fig. Our model was also verified on CCLE, and we used the active area as the evaluation criterion of drug sensitivity. In order to achieve binarization of drug sensitivity on the CCLE data set, we first normalized the active area in CCLE to zero mean. Meanwhile, we defined the active area with 0.8 variance above the mean as an effective drug, and the active area with 0.8 variance below the mean as an ineffective drug. We then searched for common combination pairs of cell lines and drugs in the LINCS-L1000 perturbation screen. Since there were only a small number of 24 drugs in the CCLE data set, we used the PubChem database to find synonymous drugs. We marked the data after matching as LINCS-L1000-CCLE. Similarly, we screened the drugs corresponding to the perturbation time of 24 h, which were included in LINCS-L1000-CCLE-24h. At the same time, we selected the drugs whose concentration was greater than or equal to 10 micromoles. In addition, when multiple drug perturbation signatures were presented, we choose the lowest cell viability value.We used the ROC curve shown in Additional file In order to evaluate the effectiveness of the algorithm in this paper, we analyzed and compared our algorithm with other existing methods including PCA-Lasso, PCA-SVR, FTest-RF, MI-KNN, VAE  and DAE-In the present paper, we used the Pearson correlation coefficient, coefficient of determination (mentclass2pt{minimCompared with PCA-Lasso, PCA-SVR, FTest-RF, MI-KNN,VAE and DAE-NN algorithms, Pearson correlation coefficient of our method increased by 5.50%, 5.33%, 4.77%, 3.32%, 0.39%, 3.59% and mentclass2pt{minimIn addition to reliably and effectively inferring cell viability through the predictive models, we also needed to correlate our results with the literature on cell viability, as shown in Fig. In this paper, we managed to predict the drug-induced cell viability from the differential gene expression data through the WRFEN-XGBoost algorithm. The study of cell phenotype was firstly correlated with the drugs and shRNA perturbation signatures. In addition, we have completed the selection of key genes based on the WRFEN algorithm and proposed a novel FEBPSO-XGBoost machine learning method to predict the cell viability. Through the connection between cell viability and pharmacogenomics, the establishment of the prediction model trained from perturbation transcriptomics signatures, cell phenotype and drug response data has been completed. At the same time, the robustness and effectiveness of our proposed modeling strategy in drug sensitivity analysis were verified on CCLE and NCI-60 datasets. This study could provide help for the biomedical researchers in drug screening and promote the analysis of anticancer drugs in pharmacogenomics.However, in the clinical application of cancer cell lines and anticancer therapies, it is urgent to identify the biomarkers that can distinguish between drug-sensitive cell lines and drug-resistant cell lines. Firstly, besides gene expression, drug characteristics can be integrated into the model to achieve better accuracy. Secondly, a more appropriate supervised machine learning algorithm is hoped to be designed to reveal the sensitivity between cancer cell lines and drug treatment. Finally, we will continue to reveal new biomarkers that are sensitive and resistant to the cancertherapies. It provides more opportunities for exploring the biological behavior of cancer cell lines at the cellular level, and it is also the direction of our future research.Additional file 1. Supplementary Material contains supplementary figures and supplementary tables of the results in this study.


Pralatrexate  and belinostat  are registered for the treatment of patients with peripheral T-cell lymphoma (PTCL) and are being considered for other lymphomas. In this study we investigated whether BLS had the ability to potentiate the cytotoxicity of PLX. A panel of lymphoma cell lines was used for the combination studies: the B-cell SUDHL-4, SUDHL-5, HT, Jeko-1 and T-cell Karpas-299 and Hut-78. Uptake of PLX was mediated by the reduced folate carrier (RFC). PLX showed a 6-fold better RFC substrate affinity compared to methotrexate, and 2-fold better than levoleucovorin (l-LV). Sensitivity expressed as the concentration that resulted in 50% growth inhibition (IC50) after 72 hr exposure to PLX varied from 2.8 to 20 nM and for BLS from 72 to 233 nM, independent of the background of the cell lines. The interaction between BLS and PLX was studied using the median-drug effect analysis. At a fixed molar ratio between the drugs based on the IC50 concentration the average combination index (CI) for all cell lines showed additivity (CI: around 1.0). In three selected cell lines  sequential exposure , did not improve interaction (CI: 0.9–1.4). As an alternative approach a non-fixed ratio was used by exposing SUDHL-4, SUDHL-5, and HT cells to IC25 concentrations of either BLS or PLX in combination with the other drug. Exposure to IC25 of PLX did not decrease the IC50 for BLS (CI from 0.6–1.2), but exposure to IC25 of BLS markedly increased PLX sensitivity (low CIs from 0.40 to 0.66). Mechanistic studies focused on induction of apoptosis, and showed cleavage of predominantly caspase-9 in HT and SUDHL-4 cells for both drugs at their IC50s, being similar in the combination setting. Moreover, at these concentrations, the drugs were shown to confer an S-phase arrest. In conclusion, the combination of PLX and BLS showed additivity in various lymphoma cell lines, with a schedule-dependent synergism in B-cell lymphoma. Based on these data, proficient inhibition of HDAC activity by BLS holds promise in sensitization of tumor cells to PLX. Peripheral T-cell Lymphoma (PTCL) accounts for over 6,000 to 9,000 cases in the United States annually and worldwide this type of cancer represents 10 to 15% of all non-Hodgkin’s lymphoma . PTCL isIn 2009 the FDA approved the antifolate Pralatrexate (PLX) for the treatment of patients with relapsed or refractory PTCL . PLX is Belinostat (BLS) is a hydroxamic acid-based pan-histone deacetylase (HDAC) inhibitor that inhibits all of the zinc-dependent HDAC enzymes, with high affinity for the Class I, II and IV isozymes . HDAC inTherefore, both the efficacy of BLS and PLX for relapsed PTCL patients, and a potential synergistic/additive interaction of these drugs, encouraged us to investigate their combination. Although PLX and BLS have different intracellular targets, we hypothesize that PLX and BLS will interact at least additive and possibly synergistically, inducing more apoptosis than would be expected on their separate effects. We investigated the interaction of these two drugs in a panel of B- and T-cell lymphomas and determined whether the effect of the combination was mediated by an increased cell death.®), PLX and BLS were a gift from Spectrum , Pemetrexed (PMX) was a gift from Eli Lilly and Company . Folic acid was from Sigma Chemical Co . The drugs were first diluted in dimethyl sulfoxide, and then in medium before use. Radioactive compounds, -(6S)-Leucovorin (25 Ci/mmol) and, -folic acid, diammonium salt (21.0 Ci/mmol) were obtained from Moravek Biochemicals .RPMI-1640 medium, Fetal Bovine Serum, penicillin/streptomycin (100 μg/mL) and Hank’s Balanced Salt Solution (HBSS) were purchased from Lonza . Cell culture flasks were purchased from Greiner Bio one. l-Leucovorin  for 2 min at 37°C. CEM-7A cells overexpress the RFC 30-fold over wild-type CCRF-CEM cells  served as reference drug. The accumulation of 2.5 μM [3H]-l-LV was performed at 37°C; essentially as described for the RFC assay, but the incubation time was 3 min and was performed at pH 5.5, the optimal pH for PCFT, with increasing amounts of unlabeled drug. Also for PCFT relative affinities were expressed as the concentration of unlabeled drug necessary to inhibit [3H]-LV influx.The affinity for PCFT of PLX was assessed in competition with 2.5 μM 2 incubator with 100% humidity at 37°C, 150 μL acidified 2-propanol was added to the plates to dissolve the formazan crystals. The yellow-colored MTT stock solution is taken up and reduced to a purple formazan in living cells, which directly correlates to the amount of viable cells. As final step, the plates were measured at 540 (or 492) nm by the SPECTRAfluor spectrophotometer. Drug sensitivity was evaluated by determination of the IC50 value, which is the drug concentration resulting in 50% growth inhibition.Growth inhibition of the suspension cell lines (lymphoma and CEM) was routinely determined with the  assay , however>0.5  were averaged for each specific experiment. The means of the separate experiments were subsequently averaged so that a mean ± Standard Error of the Mean (SEM) was calculated from three or more separate experiments. Experimental conditions with a growth inhibition of <50%  are generally considered as clinically less relevant, since it only represents a minor level of growth inhibition . Drug combinations were designed based on the standard CalcuSyn approach in which a series of drug concentrations were combined in a fixed molar ratio, based on the IC50 of each drug. A variation of this approach was a sequential scheduling in which cells were exposed for 72 h to BLS, while in the combination PLX was added after 24 h and cells were exposed from 24 to 72 h. In the non-fixed ratio approach one drug was used at the IC25 (concentration that results in 25% growth inhibition) and the other drug was added in a concentration range.Drug interaction in combination experiments was evaluated using the median-drug effect analysis using CalcuSyn software . In orde6 cells were harvested after exposure to the drugs for 24, 48, or 72 h. Cells were snap-frozen in liquid nitrogen and stored at −80°C. Before blotting the protein content was determined using the Bicinchoninic based protein assay, as described previously (TM), electrophoresed for 45 min at 150 V, transferred to a polyvinylidene fluoride (PVDF) membrane and incubated with a suitable antibody against a cleaved caspase  and rabbit-anti-caspase 9, # 9501 , for Enhanced chemiluminescence. β-actin  was used as control for equal protein loading on the gels.Western blotting was performed, essentially as described earlier . In shoreviously . The celPropidium iodide staining (DNA staining) was used to determine cell cycle distribution and the extent of cell death. Cells  were exposed to PLX or BLS or the combination for 24, 48, or 72 h. Cells were harvested, suspended in 1.0 ml phosphate buffered saline/1% Bovine serum albumin and fixed with 70% ethanol. After centrifugation the pellet was resuspended in hypotonic propidium iodide (0.1 mg/ml), Triton-X-100 (0.1%), sodium citrate (1 mg/ml) and RNAse A (0.5 mg/ml)  and stored in dark on ice for 30 min . DNA cont-test. Level of significance is p = 0.05, if not otherwise stated.Experiments were performed at least in triplicate. Data were expressed as mean ± SEM and analyzed by a P < 0.001), which is considered to be one of the best substrates  . In coctively) . TherefoSince PLX and BLS are registered for the treatment of PTCL , we inveInitial experiments were designed according to the standard procedure of the median-effect program, simultaneous combination of the drugs at a fixed molar ratio based on the IC50 values. An example growth curve is shown in Both drugs have been described as affecting the cell cycle and inducing cell kill, which might be enhanced by modulation via HDAC inhibition of DNA repair. Indeed both drugs increased accumulation of cells in the S-phase, which was more pronounced for BLS, while in the combination the effect was similar to that of BLS , FACS anClinicalTrials.gov: NCT00481871; ClinicalTrials.gov: NCT02701673), and no further evaluation of the dual combination BLS and gemcitabine was performed yet.In this investigation we show that BLS can potentiate the effect of PLX when combined at a modulating concentration. However, most other combinations were additive. Both PLX and BLS have been tested earlier in various combinations, such as the combinations of PLX with gemcitabine in Non-Hodgkin Lymphoma models, in which sequential addition was five times more effective in inducing apoptosis compared with simultaneous exposure . UnfortuThe efficacy of BLS was comparable to earlier studies with lymphoma cell lines such as Diffuse Large B-Cell Lymphomas (DLBCL) cell lines with IC50 values in subnanomolar range , while aEarlier data also show a similarly high sensitivity of DLBCL for PLX . The effOur data indicate that the interaction of BLS and PLX may be related to an increase in cell death, although both drugs were potent by themselves. For both BLS and PLX it was shown that they can induce cell death via the intrinsic and extrinsic apoptosis pathway , althougin vivo mouse models, since earlier experiments by us and others clearly demonstrated that endogenous high folate levels in mouse blood and tissues (including tumor models) (We did not proceed with testing PLX in  models)  protecte models) . MoreoveAltogether, these data show that a combination of PLX and BLS seems worthwhile to be explored in the treatment of B-cell lymphoma, since their activity is synergistic to additive in various model systems. However, these data also indicate that the combination should be evaluated carefully, since both drugs seem to induce this effect via similar apoptotic pathways, which may lead to increased toxicity to normal cells.The raw data supporting the conclusion of this article will be made available by the authors, without undue reservation.GJP, GR, and GJ: conceptualization. FPAvG and IK: experimentation. GJP and GJ: supervision. SAGM: cell lines and design of apoptosis. FPAvG and GJP: initial writing. All authors contributed to the article and approved the submitted version.GJP and GJ received an educational grant from Spectrum Pharmaceuticals. GR was an employee of Spectrum Pharmaceuticals, Irvine, CA, United States. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Typhonium flagelliforme leaves extract known to have an antiproliferation activity, while interferons (IFNs) one of the cytokines that first used as an antiviral agent was also known to have antitumor activity. Nowadays, the treatment of tumors using a traditional way, including the use of herbal substances, becomes popular. Some limitations of the antitumor activity due to resistant development of the cell to some substances were one of the problems on why the treatment of cancer was unsuccessful. This study aimed to elaborate the synergistic effect on the antiproliferation and anti-angiogenesis activities of the combinations between T. flagelliforme leaves ethanol extract and canine natural  and recombinant (recombinant canine IFN [rCaIFN]) IFNs on tumor-derived cell lines to find the new potential antitumor substances.Tumor disorder is one of the degenerative diseases that affected human and animals and recently is tend to increase significantly. The treatment of tumor diseases can be performed through surgical, chemotherapy, radiotherapy, biological substances, and herbs medicine. T. flagelliforme leaves was performed using the maceration method and followed by phytochemical screening assays. According to the result of LC50 by the brine shrimp lethality test, the dose used for T. flagelliforme extract was 120 ppm while the dose of IFNs was 102 U/ml. The tumor-derived cell lines  and normal rabbit endothelial cells were cultured and maintained on Dulbecco’s Modified Eagle’s Medium DMEM/Ham-F12 medium supplemented with 10% fetal calf serum, antibiotic, and antifungal. The antiproliferation activity was assayed by calculated the total cell number after treated with the tested substances. The antiangiogenesis assay was performed using in vitro method on rabbit normal endothelial cells and in ovo using chicken chorioallantoic membrane (CAM).The extraction of T. flagelliforme leaves ethanol extract indicated that the compound consisted of flavonoid, steroid, and tannin. The antiproliferation activity was increased in the combination of substances compared to the single exposure of each substance on all tested tumor-derived cell lines. There was no significantly different on the antiproliferation activity between a combination of T. flagelliforme with nCaIFN or rCaIFN in every single tested cell lines, but the comparison of this activity among the three tumor-derived cell lines seem that the antiproliferation activity is more effective on CSCC cell lines compared to the canine mammary gland benign mixed tumor and FSCC cell lines. A similar pattern of synergistic effect was also detected on the anti-angiogenesis activity in vitro using rabbit endothelial cells as well as in ovo assays. The most effective of the in vitro and in ovo anti-angiogenesis activity was observed on the combination substances between T. flagelliforme extract and rCaIFN compared to other treatments.The phytochemical screening test of the T. flagelliforme and canine IFNs  and this result could be developed as another alternative on the cancer treatments.There was a synergistic effect on the antiproliferation and antiangiogenesis activities of the combination between  Tumor is a disturbance of growth characterized by excessive, abnormal, and uncontrolled proliferation of transformed or altered cells at one or more primary points within the host, and frequently at one or more metastatic sites . The cauTyphonium flagelliforme. This plant belongs to the family of Araceae and known as “Keladi Tikus” in Indonesian. Our previous study reported that T. flagelliforme leaves ethanol extract had the antiproliferation activity on tumor epithelial cells lines derived from canine acanthomatous epulis (MCA-B1) and canine mammary gland benign mixed tumor cell lines/MCM-B2 [The most common treatments applied for tumor cases are chemotherapy and surgical procedures. Other treatments that can be performed for tumor are the usage of biological substances and herbs medicine. Nowadays, peoples prefer to use herbs medicine for some medicinal treatments. Indonesia is a mega biodiversity country of flora and fauna. The usage of herbs plant for therapy had been done from many centuries ago, but it was not well documented . One of s/MCM-B2 .Another medicinal treatment for tumor is the usage of biological substances such as interferon (IFN). IFN is one of the cytokines, which is produced due to the response to stimulation of intracellular antigens and widely known as antiviral agents . Our preT. flagelliforme leaves ethanol extract with natural and recombinant CaIFNs (nCaIFN and rCaIFN) on tumor-derived cell lines to increase the potency of both substances on these activities.This study aimed to elaborate on the antiproliferation and antiangiogenesis activities of the combination between This study was approved by the Animal Ethics Committee, Faculty of Veterinary Medicine, IPB University, certificate No. 108A/KEH/SKE/X/2018.The study was carried out in the Division of Veterinary Pathology, Faculty of Veterinary Medicine, IPB University and Tropical Biopharmaca Research Center, IPB University from July 2018 – April 2019.T. flagelliforme plant was identified by the Research Center for Biology of Indonesian Institute of Sciences Bogor. The extraction of the plant was done according to the maceration method of our previous study [T. flagelliforme leaves was ground to 60 mesh size. About 500 g of ground simplicia was soaked into 70% ethanol as the solvent for 24 h. The macerated simplicia was then filtered and the obtained dregs were soaked into the same solvent and then filtered. The filtrates were evaporated by rotary evaporator to get the viscous extract.us study . BrieflyPhytochemical screening was performed to analyze the extract for the presence of secondary metabolite compounds, such as flavonoid, alkaloid, tannin, steroid, triterpenoid, and saponin, according to standard methods .2SO4 about 3-5 drops then homogenized. The obtained acid fraction was reacted with Dragendorff, Meyer, and Wagner reagents. The appearance of yellow to red (Dragendorff), white (Meyer), and brown to black (Wagner) precipitate indicated the presence of alkaloid.About 40 mg of the extract was added by 2 ml of chloroform and ammonia then filtered. The filtrate was added by HHundred milliliters of hot water were added into 40 mg of the extract and boiled for 5 min then filtered. About 0.05 mg of Mg and 1 ml of HCl were added into 5 ml of filtrate and homogenized. The discoloration to red, yellow, or orange indicates the presence of flavonoid.3. The presence indication of tannin was the discoloration of the solution to greenish-black color.Forty milligrams of the extract were added with 10 drops of 1% FeCl3COOH and 2 drops of H2SO4 were added into 40 mg of the extract, shaken and then stand for several minutes. The presence of steroid release blue or green color, while the presence of triterpenoid release red or purple color.Ten drops of CHForty milligrams of the extract were added with 10 ml of water then shaken for 1 min. The presence of saponin was showed by stable foam for 5 min.2 U/ml according to our previous study [CaIFNs used in this study were natural (nCaIFN) and recombinant (rCaIFN) which prepared and provided by our previous study . The IFNus study .6 cells/ml and stored in liquid nitrogen until use. The frozen cell lines suspension was thawed at room temperature. The cell lines suspension was homogenized and prepared to be ready to use. The medium for cultivation of the cell line was Dulbecco’s modified Eagle’s medium (DMEM)/Ham-F12 supplemented with fetal calf serum (FCS), antibiotic, and antifungal.Cell lines used were canine squamous cell carcinoma (CSCC) and feline squamous cell carcinoma (FSCC) , canine T. flagelliforme ethanol extract, combinations between T. flagelliforme ethanol extract and IFNs (nCaIFN and rCaIFN), and doxorubicin as the positive control. All treatments were in three replicates. The cell lines were cultivated onto 24-wells microplates containing complete culture medium . The concentration of T. flagelliforme ethanol extract was 120 ppm which based on LC50 calculation from our previous study [2 U/ml for CaIFNs [2 for 4 days. After the cells on the control holes were confluent, all cells in the treatment holes were then harvested and counted under a phase-contrast microscope using a hemocytometer with Trypan Blue dye exclusion. The percentage of antiproliferation activity was obtained by calculated the total number of cells using the formulation below:Cells lines were treated with three treatments, i.e., us study  and 102 r CaIFNs . CultivaIn vitro assay of antiangiogenesis was performed using a rabbit endothelial cell lines developed in our previous study [in vitro assay method of antiangiogenesis had the same method with antiproliferation. The endothelial cell lines were treated with T. flagelliforme ethanol extract, nCaIFN, rCaIFN, and combination between T. flagelliforme ethanol extract with CaIFN (nCaIFN and rCaIFN) on three replicates for each treatment.us study . The in th [Antiangiogenesis assay was applied using a chicken CAM assay on 5 days old of embryonic eggs. The embryonic eggs were perforated on the air sac region for injected the treatment substances. The hole was closed with a wax to make the embryonic development process continue. The incubation of the eggs was continue in an incubator until the observation was finished. The growth of blood vessels (angiogenesis) was observed directly by (1) candling the eggs and (2) breaking the eggshell. Both observations were performed every 3 days until day 14th . All embth .T. flagelliforme simplicia, the whole extract on the form of a brown-black sticky substance  showed lower activity compared to the combination treatment groups between T. flagelliforme ethanol extract with CaIFNs (p<0.05).In the bstances . The higin ovo antiangiogenesis assay in the chicken CAM showed a similar pattern with the in vitro antiangiogenesis using rabbit endothelial cells. The development of blood vessels was increased significantly in the un-treated egg compared to the treated eggs with a single substance or with the combination of substances between T. flagelliforme ethanol extract and CaIFNs. In the un-treated eggs, the formation of the blood vessel was very high and compact with many large blood vessels and its capillary branching. Very fine blood vessels were commonly seen on the whole of the membrane .The moderate increase of blood vessels formation was observed both in single treatment of Bombyx mori system as other’s study [IFNs are first known as a potent of antiviral agents and this was widely used in veterinary clinical practice for treated of some viral infections. IFNs also regulate other important biological properties such as cell growth and immunomodulation . There w’s study .There has been known that there are three types of IFNs ; type I in vitro and in vivo [IFNs can affect different phases of the mitotic cycle, mostly IFN therapy results in a cell cycle arrest at the G1 phase or in a prolongation and accumulation of cells in the S-phase due to the disability to complete DNA replication by the downregulation and impaired activity of cycling and cycling-dependent kinases . The dir in vivo .Our previous study on the antiproliferation activity of single exposure of this both CaIFNs (nCaIFN and rCaIFN) on three different tumor-derived cell lines indicated that they have an activity to inhibit the tumor cell proliferation, and this activity seemed more sensitive to the canine cells compared to the feline cells . BesidesT. flagelliforme [T. flagelliforme some of them were four pheophorbide related compounds, namely, pheophorbide-a, pheophorbide-a’, pyropheophorbide-a, and methyl pyropheophorbide-a were identified in the most active fraction on antiproliferation activity against cancer cells [T. flagelliforme were found to inhibit the growth of NCI-H23 non-small cell lung carcinoma cell line significantly and the D/F21 fraction was found to be the active and cancer cell line specific fraction of T. flagelliforme [T. flagelliforme was reported to contain saturated hydrocarbons and aliphatic acids [It was widely known that many plants as natural products are valuable sources of bioactive compounds and have been used in almost all cultures and communities in the world for thousands of years ,36. Theslliforme . The preer cells . Severallliforme . The hexic acids , while tic acids .T. flagelliforme leaves ethanol extract which can trigger apoptosis. Apoptosis is a programmed cell death mechanism that functions to maintain the balance of cell populations in the body. The inhibition of the apoptosis is caused by proteins produced in the mitochondria, such as Bcl-2, Bcl-XL, and Mcl-1, which are classified as anti-apoptotic proteins. Flavonoids are known to be able to inhibit the proliferation activity through the intrinsic pathway of the apoptotic mechanism in several tumor cell lines. This compound can reduce the expression of anti-apoptotic proteins and increase pro-apoptotic proteins such as Bax, Bad, and Bak [T. flagelliforme leaves are tannins that can inhibit the tumor cell lines proliferation by arresting the cell cycle activity in the G2/M phase and increasing apoptosis in ovarian cancer cells [Decreased proliferation activity of the cell lines is influenced by compounds contained in  and Bak . The fla and Bak . Other cer cells . The arrer cells .Angiogenesis is the process of new blood vessel formation and it was also very important in the tumor progression . FormatiScutellaria barbata [Jatropha curcas [Salvia triloba [Plant extracts were also known to have an anti-angiogenesis activity such as  barbata , Jatropha curcas , Salvia  triloba , and oth triloba . Plant m triloba . Another triloba .T. flagelliforme is also has an anti-angiogenesis activity by its metabolites compound such as flavones, as shown in T. flagelliforme was exposed to the endothelial cell, it was inhibited the cell growth of rabbit endothelial cells. This feature was also in parallel when the extract was exposed to the chick embryo in CAM assay. The metabolites flavones, as well as tannin in the T. flagelliforme extract, could be acting as the enhancing substance. Based on the antiproliferation activity capability of T. flagelliforme ethanol extract, we combine these two substances to looking for an increase in the antiproliferation activity.T. flagelliforme extract and CaIFNs were singly exposed to the tumor cell lines, the antiproliferation activity was lower compared to the combination forms. This phenomenon indicated that there is a synergistic effect of these two substances, even this combine mechanism is not clear yet. We still looking for the mechanism of these combine substances on how the synergistic effect was work, by the accumulation of its single effect of every substance or they work together by creating another pathway.To the best of our knowledge, there is no study reported on the antiproliferation and anti-angiogenesis of the combination between plant extract and CaIFNs. Our present study showed that when the T. flagelliforme ethanol extract and CaIFNs has a synergistic effect to enhance the activity as antiproliferative and anti-angiogenesis and this combined materials have a potential to be developed as a new strategy to establish an antitumor substance.We concluded that the combination between BPP and EH were involved in designing the study. RRs, WN, RRd, and LNS carried out the preparation of the extract of the herbs. RRs, BPP, and EH carried out the antiproliferation and anti-angiogenesis experiment. BPP, RRs, EH, and WN performed data collection, statistical analysis, data interpretation, and manuscript writing. BPP, EH, and RRs were involved in the monitoring of research and manuscript editing. All authors have read and approved the final manuscript.


Scientific Reports 10.1038/s41598-017-03534-x, published online 12 June 2017Correction to: This Article contains errors.The “Collection of data” section is incomplete and does not make it clear which of the public datasets were used as control input against H3K27me3 treated sample files for peak identification. This information should be included as below.In the Methods, the “Collection of data” subsection which reads:18.“Three Sequence Read Archive files, SRR3159917 for normal cell type (MCF10A), SRR3159923 for tumor related to MCF7 cancer cells and SRR3159929 for tumor related to MDA-MB-231 cancerous cells, were downloaded from Gene Expression Omnibus database with accession number  of National Center for Biotechnology Information (NCBI)Three well-established human mammary cell lines were utilized for studying the H3K27me3 gene suppression activity. These data were obtained from breast cancer patient tumor samples. Normal like subtype MCF10A and two epithelial subtypes, MCF7 (ESR/PGRþ) and MDA-MB-231 (ESR/PGR/HER2-) were selected for the study.”should read:18. These input files were used as the control against H3K27Me3 treated sample files for peak identification. Similarly, the three H3K27Me3 treated sample Sequence Read Archive files, SRX1569788 for normal cell type (MCF10A), SRX1569794 for tumor related to MCF7 cancer cells and SRX1569800 for tumor related to MDA-MB-231 cancerous cells, were downloaded from Gene Expression Omnibus database with accession number GSM2058899 for normal; GSM2058905 for MCF7 cell line and GSM2058911 for MDA-MB-231 cell line. MCF10A cell line data was used only for the comparison purpose. All the data in the original manuscript were downloaded from Gene Expression Omnibus dataset series GSE77772.“Three Sequence Read Archive files, SRR3159917 for normal cell type (MCF10A), SRR3159923 for tumor related to MCF7 cancer cells and SRR3159929 for tumor related to MDA-MB-231 cancerous cells, were downloaded from Gene Expression Omnibus database with accession number  of National Center for Biotechnology Information (NCBI)Three well-established human mammary cell lines were utilized for studying the H3K27me3 gene suppression activity. These data were obtained from breast cancer patient tumor samples. Normal like subtype MCF10A and two epithelial subtypes, MCF7 (ESR/PGRþ) and MDA-MB-231 (ESR/PGR/HER2-) were selected for the study.”The authors apologise for this error.


Pancreatic ductal adenocarcinoma (PDAC) is one of the most intractable and devastating malignant tumors. Epigenetic modifications such as DNA methylation and histone modification regulate tumor initiation and progression. However, the contribution of histone variants in PDAC is unknown. Here, we demonstrated that the histone variant H2A.Z is highly expressed in PDAC cell lines and PDAC patients and that its overexpression correlates with poor prognosis. Moreover, all three H2A.Z isoforms  are highly expressed in PDAC cell lines and PDAC patients. Knockdown of these H2A.Z isoforms in PDAC cell lines induces a senescent phenotype, cell cycle arrest in phase G2/M, increased expression of cyclin-dependent kinase inhibitor CDKN2A/p16, SA-β-galactosidase activity and interleukin 8 production. Transcriptome analysis of H2A.Z-depleted PDAC cells showed altered gene expression in fatty acid biosynthesis pathways and those that regulate cell cycle and DNA damage repair. Importantly, depletion of H2A.Z isoforms reduces the tumor size in a mouse xenograft model in vivo and sensitizes PDAC cells to gemcitabine. Overexpression of H2A.Z.1 and H2A.Z.2.1 more than H2A.Z.2.2 partially restores the oncogenic phenotype. Therefore, our data suggest that overexpression of H2A.Z isoforms enables cells to overcome the oncoprotective barrier associated with senescence, favoring PDAC tumor grow and chemoresistance. These results make H2A.Z a potential candidate as a diagnostic biomarker and therapeutic target for PDAC. Pancreatic ductal adenocarcinoma (PDAC) represents one of the most lethal cancers in the world, primarily due to its late diagnosis and resistance to gemcitabine, the first-line chemotherapy , 2. PDACH2A.Z is a conserved histone variant found in different organisms, and it displays 60% identity with its canonical histone H2A . Three hGiven, the wide variety of functions of H2A.Z and the complexity resulting from the presence of three different isoforms, H2A.Z overexpression is crucial for the development of several cancer types , includi. However, whether histone variants contribute to PDAC development is unknown. Therefore, we first determined expression of the histone H2A.Z in PDAC using a commercial antibody, which recognizes the H2A.Z.1 and H2A.Z.2.1 isoforms, but not the H2A.Z.2.2 isoform. We found that H2A.Z was upregulated significantly in three different PDAC cell lines  compared to the normal ductal pancreatic cell line hTERT-HPNE  using cDNA from the control cell line hTERT-HPNE and the three PDAC cell lines PANC-1, Capan-1, and MiaPaCa-2 Fig.  with speTo determine the functional role of the overexpression of the three H2A.Z isoforms in PDAC biology, we depleted their expression levels in the cell line PANC-1 using two H2A.Z-targeting short hairpin RNAs (shRNA) , 26. OneDiminished proliferation of the KD clones could be explained by increased apoptosis or cellular senescence. However, we did not observe any significant difference neither in the processing of PARP nor caspase 3 Fig. . MoreoveAs expected, growth curves for PANC-1, PGAPDH, PZT-1, and PZT-2 cells over 5 days showed lower rates of cell proliferation over time for both KD clones compared to control cells Fig. , which wTo determine whether reduced DNA replication is associated with senescence, we measured SA-β-galactosidase activity and found that both KD clones had higher SA-β-galactosidase activity than the control cell lines Fig. a, b. In To determine which genes are dysregulated by the depletion of the H2A.Z isoforms, we performed RNA sequencing (RNA-seq) of PANC-1, scrambled shRNA (PSCR) cells, (as specificity control), and the KD clone PZT-2 that showed the strongest senescent phenotype. As expected, we found that both controls (PSCR and PGAPDH) had a similar phenotype that the parental PANC-1 cell line . Tissues were collected over a period of 12 years (2006–2017). Clinical features are shown in Table This study was approved by the Center for Research and Advanced Studies (CINVESTAV) Committee of Bioethics for Human Research (035/2016) and by the Research and Ethic on Research Committee of INCan .® CRL-1469TM), Capan-1 (ATCC® HTB-79TM), MiaPaCa-2 (ATCC® CRL-1420TM), and the non-cancerous pancreatic ductal cell line hTERT-HPNE (ATCC® CRL-4023TM) were purchased from the American Type Culture Collection (ATCC) and cultured according to their protocols. The hTERT-HPNE cell line was grown in DMEM medium without glucose (Sigma D-5030), supplemented with 25% M3 Base medium (Incell Corp M300F-500), 2 mM l-glutamine, 1.5 g/L sodium bicarbonate, 5% fetal bovine serum (FBS), 10 ng/mL human recombinant EGF, 5.5 mM d-glucose and 750 ng/mL puromycin. The MiaPaCa-2 and PANC-1 cell lines were grown in DMEM medium (ATCC® 30-2002TM) supplemented with 10% FBS. Capan-1 cells were grown in IMDM medium (ATCC® 30-2005TM), supplemented with 20% FBS. The cell lines were cultured in a humid atmosphere, with 5% CO2 at 37 °C. The absence of mycoplasm was confirmed by PCR.The PDAC cell lines PANC-1 . The GraphPad Prism v6.01 software  was used to perform all statistical analyzes. To compare more than two groups, a one-way ANOVA was performed. To compare two groups, Student’s Supplementary Figure 1.Supplementary Figure 2.Supplementary Figure 3.Supplementary Figure 4.Supplementary Figure 5.Supplementary Table 1.Supplementary Table 2.Supplementary Table 3.Supplementary FiguresSupplementary TablesSupplementary Methods