Dysfunctions in the PI3K/mTOR pathway have gained a lot of attention in autism research. This was initially based on the discovery of several monogenic autism spectrum disorders with mutations or defects in PI3K/mTOR signaling components. Recent genetic studies corroborate that defective PI3K/mTOR signaling might be a shared pathomechanism in autism disorders of so far unknown etiology, but functional molecular analyses in human cells are rare. The goals of this study were to perform a functional screen of cell lines from patients with idiopathic autism for defects in PI3K/mTOR signaling, to test if further functional analyses are suitable to detect underlying molecular mechanisms, and to evaluate this approach as a biomarker tool to identify therapeutic targets.We performed phospho-S6- and S6-specific ELISA experiments on 21 lymphoblastoid cell lines from the AGRE collection and on 37 lymphoblastoid cell lines from the Simons Simplex Collection and their healthy siblings. Cell lines from one individual with increased S6 phosphorylation and his multiplex family were analyzed in further detail to identify upstream defects in PI3K signaling associated with autism diagnosis.We detected significantly increased S6 phosphorylation in 3 of the 21 lymphoblastoid cell lines from AGRE compared to a healthy control and in 1 of the 37 lymphoblastoid cell lines from the Simons Simplex Collection compared to the healthy sibling. Further analysis of cells from one individual with elevated S6 phosphorylation showed increased expression of the PI3K catalytic subunit p110δ, which was also observed in lymphoblastoid cells from other autistic siblings but not unaffected members in his multiplex family. The p110δ-selective inhibitor IC87114 reduced elevated S6 phosphorylation and protein synthesis in this cell line.Our results suggest that functional analysis of PI3K/mTOR signaling is a biomarker tool to identify disease-associated molecular defects that could serve as therapeutic targets in autism. Using this approach, we discovered impaired signaling and protein synthesis through the PI3K catalytic subunit p110δ as an underlying molecular defect and potential treatment target in select autism spectrum disorders. Increased p110δ activity was recently associated with schizophrenia, and our results suggest that p110δ may also be implicated in autism.The online version of this article (doi:10.1186/s13229-015-0066-4) contains supplementary material, which is available to authorized users. The PI3K/mTOR pathway regulates a variety of functions throughout the body, including fundamental processes such as cell growth, differentiation and survival. In neurons, the PI3K/mTOR pathway was shown to regulate protein synthesis , to playSeveral monogenic autism spectrum disorders have mutations leading to defects in the PI3K pathway, such as tuberous sclerosis (TS) , fragileTogether, these findings suggest that there is a considerable subgroup of autism spectrum disorders of unknown etiology with defects in PI3K/mTOR signaling, which could qualify for a therapeutic strategy targeted at this pathway. While genetic screens are important to identify potentially pathological mutations in the PI3K/mTOR pathway, they do not directly reveal the functional consequences and how signal transduction is affected by a certain mutation in human patient cells. Understanding the exact pathological mechanisms in PI3K/mTOR signaling, which may be the sum of several mutations as well as epigenetic factors, will be essential to identify efficient, disease-targeting therapies.Here, we tested the hypothesis that functional defects in PI3K/mTOR signaling can be detected and utilized to identify potential therapeutic targets in lymphoblastoid cell lines from patients with idiopathic autism. In particular, we performed quantitative analyses of phosphorylation of the PI3K/mTOR downstream target S6 in patient cell lines from the Autism Genetic Research Exchange (AGRE) collection and in proband-sibling pairs from the Simons Simplex Collection (SSC). We identified several cell lines with increased S6 phosphorylation suggesting elevated upstream signaling. We confirmed the pathological relevance of increased S6 phosphorylation for one patient from the AGRE collection by showing that his unaffected sister did not have increased S6 phosphorylation. Analyses of upstream signaling defects and pharmacological rescue experiments using PI3K catalytic subunit-selective inhibitors suggested that increased expression and activity of the PI3K catalytic subunit p110δ, but not p110β, underlie increased S6 phosphorylation and protein synthesis in this autism patient cell line. This work supports the applicability of functional molecular screens to detect signal transduction defects in lymphoblastoid cell lines from patients with autism that could serve as therapeutic targets.proband) and the unaffected sibling, all male), and the Coriell Institute . The institutional review boards of Emory University and Cincinnati Children’s Hospital Medical Center determined that this research was “exempt” and no IRB approval was required. Cell lines were grown in RPMI supplemented with 10 % fetal bovine serum and penicillin/streptavidin (100 U/ml) and kept at a cell density between 500,000 and 800,000 cells/ml. If cell lines differed in growth rates, as monitored by change of color of the media and cell density, they were discarded, and new batches were thawed. Cell lines were only kept in culture and used for experiments for up to 5 weeks. Experimental data were obtained from at least two separate frozen vials of cell lines.Lymphoblastoid cell lines were obtained from the Autism Genetic Research Exchange , S6 antibody (#2317), and p110α antibody (#4255) were obtained from Cell Signaling Technology. p110δ antibodies  were obtained from Santa Cruz Biotechnology and R&D Biosciences, respectively. The p110β antibody (#09-482) was obtained from EMD Millipore, the α-tubulin antibody (T6074) was obtained from Sigma-Aldrich, and the anti-puromycin antibody was purchased from the Developmental Studies Hybridoma Bank (University of Iowa). Secondary antibodies for Western blotting were obtained from VWR (horseradish peroxidase-coupled anti-mouse and anti-rabbit antibodies for ECL) or from Li-COR Biosciences (IRDye 680 RD donkey anti-mouse IgG and IRDye 800CW goat anti-rabbit IgG for infrared fluorescent Western blotting). Puromycin was purchased from Life Technologies, the p110δ inhibitor IC87114 was purchased from EMD Millipore, and the p110β inhibitor TGX-221 was purchased from Selleck Chemicals.S6- and phospho-S6 ELISA kits were obtained from Cell Signaling Technology and run in triplicates and in parallel using 150 μg of protein per sample following the manufacturer’s protocol. Lymphoblastoid cell lines were lysed by sonication using the provided lysis buffer.3VO4, 50 mM NaF, 10 mM sodium pyrophosphate, and 10 mM sodium glycerol phosphate, supplemented with proteinase inhibitors). One hundred micrograms of protein was used for subsequent immunoprecipitation with a p110δ-specific antibody . PI3K assays were performed as described by the manufacturer with the following modifications: kinase reactions were conducted for 3 h in 60 μl volume; the reaction contained 75 μM ATP, 1 mM DTT, and 15 μM phosphatidylinositol  biphosphate diC8 and was terminated with 2.4 mM EDTA. The amount of phosphatidylinositol--triphosphate generated during the reaction was quantified using defined standards.PI3K activity assays were performed using the PI3-kinase activity ELISA: Pico (Echelon Biosciences Incorporated) as described previously . BrieflyEqual amounts of protein lysates (prepared as described above) were resolved on SDS protein acrylamide gels, transferred to PVDF membranes, and detected with specific antibodies by enhanced chemiluminescence using standard methods and autoradiography  or by Odyssey infrared fluorescence Western blotting (Li-COR Biosciences) using the manufacturer’s blocking buffer (PBS) for blocking and antibody incubation .NIH).Protein synthesis assays were performed using puromycinylation of nascent peptide chains as described previously , 26. Brit tests, one-way ANOVA, or two-way ANOVA as appropriate followed by post hoc analyses (indicated in the text and figure legends). Bar diagrams and error bars illustrate means and standard error of the mean; n is indicated in each figure and/or figure legend.Statistical analyses were performed using SAS® version 9.3  = 3.5; p < 0.0001, Dunnett’s post hoc comparisons of autism cell lines to the unaffected control *p < 0.05). Two of these three also had significantly increased S6 expression, suggesting that increased phosphorylation was due to an overall increase in S6  = 5.47; p < 0.0001, Dunnett’s post hoc comparisons of all autism cell lines to the unaffected control *p < 0.05). No differences in total S6 levels between any other cell line and the control cell line were detected. Consequently, one cell line (A4) had significantly increased pS6/S6 ratios suggesting a defect in the upstream signaling pathway  = 2.34; p = 0.003, Dunnett’s post hoc comparisons of all autism cell lines to the unaffected control *p = 0.013). A list of p values for all pairwise comparisons can be found in Additional file CTR-2) supported the reproducibility of the assay results and showed that there was no significant difference in S6 phosphorylation in the two control lines  after false discovery rate correction  = 1.7, p = 0.018), which was mainly driven by sibling S37 . This data further supports the validity of our approach to directly compare autistic individuals to their healthy family members to account for effects of autism-unrelated genetic predispositions or environmental influences.Dysregulated PI3K/mTOR signaling in the brain has been detected and successfully targeted to correct phenotypes in several mouse models of autism, including FXS , 27–31. F = 35.36, p < 0.0001; Tukey’s post hoc analyses *p = 0.0004; #p < 0.0001). We have previously shown that increased expression of the PI3K catalytic subunit p110β contributes to increased S6 phosphorylation in lymphoblastoid cell lines from patients with FXS [F = 0.66, p = 0.54). However, Western blot analyses revealed that cell line A4 had increased expression of the class I PI3K subunit p110δ compared to cell line A21 and the unaffected control  = 10.42, p = 0.0045; Tukey’s post hoc analyses *p = 0.0144; #p = 0.0056). In line with the increased expression of p110δ, p110δ-associated PI3K activity was also elevated in cell line A4 compared to cell line A21 and the unaffected control  = 14.73, p = 0.0001; Tukey’s post hoc analyses *p = 0.0002, #p = 0.0006). We further tested if similar defects were detectable in cell lines S1 and S11  n = 3, t(2) = 10.7, p = 0.009; (b) n = 4, t(3) = 10.39, p = 0.002; (c) n = 4, t(3) = 0.72, p = 0.525), thereby confirming our ELISA results  was increased compared to cell line A21 and the unaffected control  = 3.14, p = 0.021). Post hoc analyses comparing all family members to the healthy sister suggested that p110δ expression in the three affected sons was increased compared to the unaffected parents and sister, although statistical significance was not reached  = 3.77, p = 0.012; p values for post hoc comparisons to the unaffected sister shown in Additional file t tests, (d) t(5) = 4.99, p = 0.004; (e) t(4) = 4.81, p = 0.009). However, we cannot exclude that the difference observed in the pooled data, in particular in pS6/S6 ratios, was mainly driven by cell line A-4, which was originally identified in our screen. The cell line of one of the affected brothers (A4-B3) did not grow well and therefore was excluded from the analysis.We next took advantage of the fact that the AGRE collection stores lymphoblastoid cell lines and data from entire multiplex families. Cell line A4 was derived from an individual that has two unaffected parents , one unaffected sister (A4-S), and three brothers with autism , one of which is his twin brother (A4-B1) Fig. . WesternFinteraction = 10.73, pinteraction = 0.017; Ftreatment = 9.34, ptreatment = 0.022; Fautism = 1.20, pautism = 0.316; Sidak’s post hoc analyses *p = 0.010, #p = 0.011). Protein synthesis rates in the cell line from the unaffected sibling were not affected by the p110δ inhibitor (p = 0.907). The specificity of the effect of the p110δ-inhibitor on protein synthesis rates was further confirmed by experiments showing that a selective inhibitor of the PI3K catalytic subunit p110β, TGX-221, did not significantly affect protein synthesis in cell line A4  = 0.34, p = 0.76). In contrast, the p110δ-selective inhibitor reduced S6 phosphorylation in both cell lines, suggesting that additional p110δ-dependent mechanisms, apart from increased S6 phosphorylation, lead to increased protein synthesis rates in the cell line A4  = 35.01, pinteraction = 0.001; Ftreatment = 163.2, ptreatment = 0.001; Fautism = 4.15, pautism = 0.135; *p = 0.003, #p = 0.0005; $p = 0.0019). Of note, the p110β-selective inhibitor also reduced S6 phosphorylation in cell line A4  = 5.75, p = 0.005), similarly as we have observed previously in lymphoblastoid cell lines from a patient with FXS and a healthy control [Increased PI3K activity and S6 phosphorylation contribute to increased protein synthesis in FXS mouse models and cell lines from individuals with FXS –28, 33.  control .Fig. 6InThe development of disease-modifying therapies for autism spectrum disorders is hindered by the variety of contributing factors and the limited knowledge about the underlying pathological mechanisms. Easily assessable biomarkers that offer insight into defective molecular pathways in individual patients provide a potential avenue for the design of targeted, personalized therapeutic strategies and could help to stratify patients into sub-cohorts that would benefit from certain treatments. Ideally, these biomarkers should provide quantitative measurements that can also be used to evaluate the efficiency of treatment strategies. Here, we provide initial evidence that quantitative screens for signaling defects in peripheral cell lines from individuals with autism could fulfill these criteria for a biomarker and are suitable to detect molecular pathological mechanisms that may serve as therapeutic targets. Apart from this conceptual advance, our results also corroborate previous studies suggesting that dysregulated PI3K/mTOR signaling is a common pathological mechanism shared by a sub-cohort of autism spectrum disorders with unknown etiology.We used lymphoblastoid cell lines from patients with autism of unknown etiology obtained from the AGRE collection and the SSC to test the hypothesis that dysregulated PI3K/mTOR signaling is a shared pathological mechanism, treatment target, and biomarker in autism. This hypothesis is based on previous studies that found gene mutations in the PI3K/mTOR pathway in monogenic and idiopathic forms of autism , 12, 20.PI3K catalytic subunits exist in eight isoforms, which are categorized into class I, class II, and class III depending on their structure and function . The fouSo far, little is known about the molecular mechanisms regulated by p110δ in neurons. A previous study has shown that p110δ is important for axon outgrowth and regeneration , but theDysregulated mRNA translation was observed in several autism spectrum disorders , supportThe fact that p110δ, which is dysregulated in schizophrenia, may be altered in autism further supports the hypothesis that autism spectrum disorders and schizophrenia share common neurobiology and contributing pathological mechanisms . In non-PIK3CD gene (located on chromosome 1p36.2) in these families. Forthcoming studies will have to show if other genetic factors contribute to the observed signaling defects, for example, through targeted sequencing of candidate genes. In this study, we have found increased protein expression of p110δ. So far, the factors and signaling pathways influencing p110δ expression are mostly unknown [A large number of studies have identified gene mutations or chromosomal CNVs that are associated with an increased risk to develop autism . These s unknown , 47. In Using lymphoblastoid cell lines from patients with idiopathic autism, we confirm that defects in S6 phosphorylation occur in autism spectrum disorders of unknown etiology. For one case, we show that this defect is caused by alterations in PI3K/mTOR signaling, in particular the catalytic subunit p110δ. It is noteworthy that S6 phosphorylation is regulated by other signaling pathways, in addition to PI3K/mTOR, for example, the ERK1/2 pathway. The approach described here could thus detect alterations in several upstream signaling pathways, not only the PI3K/mTOR complex. Limitations of the analysis of lymphoblastoid cell lines are (1) that the process generating lymphoblastoid cell lines by Epstein-Barr virus-mediated transformation of blood lymphocytes may itself lead to alterations in signaling and (2) that defects that are restricted to neurons will not be detected. Artifacts in PI3K signaling that are due to the transformation of lymphocytes into lymphoblastoid cell lines could be avoided by directly analyzing lymphocytes purified from peripheral blood samples of patients. However, using fresh blood samples would make larger screens less feasible. Notably, our Western blot analyses suggest that p110δ expression is increased in lymphoblastoid cell lines from several autistic brothers within one family but not in lymphoblastoid cell lines from the unaffected sister or parents. These results suggest that the altered PI3K signaling is due to a genetic predisposition within this family and not an artifact caused by the process of lymphoblastoid cell generation. In the future, results generated with lymphoblastoid cells from patients should be confirmed in lymphocytes from peripheral blood samples. Analyzing lymphoblastoid cell lines is not suited to detect signaling defects that are restricted to neuronal cells; however, the feasibility of the method and the availability of large collections of lymphoblastoid cell lines from individuals with autism and their families justify this approach. In addition, previous studies in FXS have shown that brain defects detected in mouse models are also present in human peripheral cells, such as blood lymphocytes , lymphobThe institutional review boards of Emory University and Cincinnati Children’s Hospital Medical Center determined that this research was “exempt” and no IRB approval was required. Therefore, no consent to participate was required. No animals were used for this research.Not applicable.


Our objectives are to detect the expression of ASPP family members in p53+ BC cell lines and determine its significance in tumor cell apoptosis.The apoptosis-stimulating protein of p53 (ASPP) family comprises three members, namely, ASPP1, ASPP2, and iASPP. They regulate the promotive effect of p53 on apoptosis. Breast cancer (BC) remains as one of the leading causes of cancer or cancer-related mortality among women. However, the relationship between the ASPP family members and p53, as well as the dissemination and expression pattern of ASPP family members in p53+ BC cell lines was detected through RT-PCR and assayed using Quality-one software. The p53 protein expression was detected by immunohistochemistry. Afterward, the apoptosis indices of the five BC cell lines were detected by flow cytometry.The mRNA expression of ASPP family members in five p53p < 0.05), except that in ZR-75-30 (p > 0.05). The ASPP2 mRNA was expressed in MDA-MB-231, Bcap-37, and MCF-7, but not in HBL-100 and ZR-75-30. The p53 protein was expressed in five breast cancer cell lines. ZR-75-30 and MDA-MB-231 apoptosis indices were higher than those of other breast cancer cell line and peripheral blood mononuclear cells (p < 0.01).The iASPP mRNA was expressed in Bcap-37, MCF-7, and HBL-100. Compared with the human peripheral blood mononuclear cells, significant differences were found in the ASPP1 mRNA in Bcap-37, MDA-MB-231, MCF-7, and HBL-100 (+ BC cell lines. The results also verified that the family members have an important function in apoptosis, which was promoted by p53 protein. ZR-75-30 BC showed high apoptosis index, without expression of any ASPP family members, indicating that the pathway of apoptosis in this cell line may be related to other cell transduction pathway. MDA-MB-231, Bcap37, and MCF-7 cell lines all expressed ASPP1/2. However, the apoptosis pathway in MDA-MB-231 is different from those of the other two cell lines. The status of the different cell lines should also be considered when the functions of the ASPP family members are examined.The mRNA expression of ASPP family members varied in the five p53 Breast cancer (BC) is the most common cancer among women worldwide -4, with ASPP1 mRNA expression was observed in four BC cell lines . The expression levels were higher in MDA-MB-231, Bcap-37, and MCF-7 than that in the mononuclear cells (MNCs) and HBL-100. In addition, no expression was observed in ZR-75-30. Higher ASPP2 mRNA expression was observed in MNCs, MDA-MB-231, Bcap-37, and MCF-7, but no ASSP2 expression was observed in HBL-100 and ZR-75-30. iASPP mRNA expression was observed in MCF-7 and HBL-100, slight expression was observed in Bcap-37, and no expression was found in MNCs, MDA-MB-231, and ZR-75-30 , except in ZR-75-30. ASPP2 mRNA levels in MDA-MB-231, Bcap-37, and MCF-7 cell lines were higher than that in MNCs (p < 0.05). No ASPP2 expression was detected in HBL-100 and ZR-75-30 . The results are shown in Table To further demonstrate the relationship between p53 protein and the BC cell lines, we transfected the BC cell lines ZR-75-30 and MDA-MB-231, with high apoptosis indices, using pAd-p53-RNAi. Cell apoptosis was determined via FCM post-pAd-p53-RNAi transfection. The results are shown in Table The wild-type p53 is an important anti-oncogene and its expression induces tumor cell apoptosis. P53 protein binds with the DNA of damaged cells, which results in cell cycle arrest. Afterward, the damaged cells are repaired by the host or killed via apoptosis. Numerous studies have shown that p53 protein increased markedly in DNA-damaged cells. The process by which p53 protein induces cell apoptosis has not been elucidated. The recent discovery of ASPP explained the p53-induced cell apoptosis because this protein is a specific p53 regulator -8. The ATo date, the status and expression pattern of the ASPP family in BC cell lines have not been reported, and whether the ASPP family could be a new therapy target in BC patients remain unknown. In the current study, we analyzed the mRNA expression pattern of the ASPP family in five p53+ BC cell lines using semi-quantitative RT-PCR method. The results revealed that ASPP1 was expressed in four BC cell lines. ASPP2 was expressed in MDA-MB-231, Bcap-37, and MCF-7. iASPP was expressed only in MCF-7, HBL-100, and Bcap-37. To further study the relationship between the ASPP family members and p53+ BC cell lines, we detected the apoptosis indices of untreated BC cell lines. Results showed that the apoptosis indices of MDA-MB-231 and ZR-75-30 (non-expression iASPP) were markedly higher than those of the other BC cell lines. Our results further verified the relationship between the ASPP family members and apoptosis in p53+ BC. Apoptosis induction in p53+ BC also involves other pathways aside from the ASPP family transduction pathways.According to a previous study, 4.1% and 1.5% of p53 binds with ASPP1 and ASSP2, respectively, in normal cultural MCF-7 BC cell line, p53-ASPP2 complexes increase to 3.4 times after the cells are UV-irradiated, and p53-ASPP1 complexes remain unchanged . These r+ BC cell lines. A few reports have shown that ASPP1 and ASPP2 act as tumor suppressors and iASPP as an oncogene [+ BC cell lines.Finally, despite the increased awareness on the relationship between the ASPP family and BC, many questions remain unresolved, particularly regarding the functions of the ASPP family members in p53oncogene ,16. iASPoncogene . Inhibitoncogene . ASPP1 ioncogene , and theoncogene . These ioncogene . The ASPoncogene ,22, and 2 in a humidified atmosphere. The medium was changed every 3 d to 4 d. The cells were used up to passage 4. The experimental protocols were approved by the ethics committee of the 150th Hospital, PLA (20121008023).MDA-MB-231, Bcap-37, MCF-7, HBL-100, ZR-75-30, and MNCs were maintained in Dulbecco modified Eagle medium supplement with 100 IU/mL penicillin-G, 100 μg/mL streptomycin sulfate, , and 10% fetal bovine serum  at 37°C under 5% COTotal RNAs were extracted from the five BC cell lines using Tripure isolation reagent .RT-PCR kits  were used to synthesize cDNA from 5 μL of total RNA. cDNA synthesis was performed, as suggested by the kit protocol, using AMV reverse transcriptase. Reverse transcription was performed for 2 min at 94°C for one cycle, and then at 94°C for 40 s, at 72°C for 40 s for 30 cycles, and finally at 72°C for 10 min for one cycle extension. Appropriate temperatures for ASPP1, ASPP2, and iASPP were 62, 59, and 60°C, respectively. cDNA (5 μL) was used in amplifying the target regions of ASPP1, ASPP2, or iASPP. β-Actin cDNA fragments were also amplified as positive control. The RT-PCR primers of ASPP1, ASPP2, and iASPP were designed using Primer Premier 5.0 software . The ratio of the integrated optical density of ASPP and β-actin represented the mRNA level.5 cells/well) were fixed using acetone solution. Endogenous peroxidase activity was then blocked, and the BC cells were incubated with primary human Abs, 10 μL anti-p53 , and anti-AE1AE3 as a positive control . According to the manufacturer’s recommendations, a peroxidase-based immunocytochemistry staining method  was used for primary Ab detection, and a 3,3′-diaminobenzidine tetrahydrochloride substrate system  was used as chromogen. Negative controls without primary Abs were also prepared at the same time. Each sample was assayed in quadruplicate.The BC cell lines were used to evaluate the p53 protein expression thrice via immunocytochemistry assays. BC cells . Supernatants were loaded on a SDS-PAGE gel and transferred to PVDF membranes. After blocking for 1 h at room temperature with PBS buffer containing 6% non-fat milk powder, membranes were incubated with mouse anti-p53 primary antibody  at 4°C overnight and were subsequently incubated with the secondary HRP-IgG antibody at room temperature for 1 h.6 cells/mL. Subsequently, Annexin-V/FITC solution, PI solution, and HEPES buffer were mixed together (1:50). Moreover, 100 μL Annexin-V-FITC/PI solution with 106 cells was added into a EP tube and incubated for 15 min at room temperature. Finally, 1 mL HEPES buffer was added into the reaction tube, and the apoptosis index of the cells was detected using FCM within 1 h.After collection, the cells were washed with ice-cold PBS buffer twice. Cell concentration was adjusted to 2 × 105 BC cells were inoculated into a 12-well plate. During transfection, the plasmid mix was added gradually into each well that contains tumor cells and media. The solution was mixed well by gradual shaking. After 48 h transfection, cells were collected via FCM method to detect apoptosis.To study the effect of the p53 RNAi on the high apoptosis indices of ZR-75-30 and MDA-MB-231, we constructed the pAd-p53-RNAi. Then, 1 × 10p < 0.01 or p < 0.05.All data were expressed as median values ± standard error (SE). The statistical significance of the differences in the measured values among groups was evaluated using one-way ANOVA. For individual comparisons, an independent unpaired t-test was used. All analyses were performed using the SPSS software package . Values were considered to have statistically significant difference if Written informed consent was obtained from the patient for the publication of this report and any accompanying images.The authors declare that they have no co interests.CSW and CFG were responsible for design of the study, performed the statistical analysis and manuscript preparation. XXL, JY and YPC participated in the discussion for histological characteristics, RT-PCR, transfection and manuscript preparation. PW cultured the cell lines and carried out the FCM detection. All authors read and approved the final manuscript.


Glioblastoma is the most common primary malignant brain tumor, and despite multimodal treatment with surgery, radiotherapy, and temozolomide (TMZ) chemotherapy, the prognosis is poor, with a median survival of 16 to 19 months [A therapy anticipated to be one of the most effective anti- cancer treatments is tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) but resistance to TRAIL remains a significant challenge .Like TRAIL, TMZ induces apoptosis; however, unlike TRAIL, TMZ also induces autophagy , which mp value <0.05 was considered statistically significant.Fluorescence-activated cell sorting (FACS) and confocal imaging were utilized to assess the basal level of autophagy in the following GBM cells - MZ294, MZ304, MZ18, MZ51, MZ256, MZ327, U251, U343, U373, A172 and U87. MTT assays were utilized to measure cell viability following differing treatment combinations. Statistical analysis was performed using unpaired student t-tests. A FACS analysis demonstrated that the TMZ-resistant cell lines MZ256 and MZ51 displayed the highest basal levels of autophagy. These results were supported by the confocal imaging experiments. The same cell lines also demonstrated resistance to TRAIL and to the combined treatment of TRAIL and TMZ.Inhibition of autophagy in MZ18, MZ256, MZ51 and MZ304 with Bafilomycin A1 (Baf-A1) sensitized these cell lines to one or more of the treatment options. Specifically, MZ18, MZ256 and MZ51 have responded largely with the combination of TRAIL and Baf-A1 whereas MZ304 has responded better with the combination of TMZ and Baf-A1. But all of the four primary cell lines have a slightly higher response with the combination of TRAIL, TMZ and Baf-A1.The primary GBM cell lines display higher basal levels of autophagy than the commercial GBM cell lines, and are more resistant to treatment. Inhibiting autophagy in such cell lines resulted in a better response to treatment. These findings may help in the future treatment of glioblastoma.


These findings suggest the possibility of achieving the same outcome with the application of low-dose MTX, an extremely important result, particularly for clinical practice. Another important aspect of treatment with high-dose MTX in clinical practice is the administration of leucovorin (LV) as an antidote to reduce MTX toxicity in normal cells. For this reason, the combined application of MTX and LV was also included in our experiments; however, this application of MTX together with LV did not elicit any detectable effect. The expression analysis of genes involved in the mechanisms of resistance to MTX was a final component of our study, and the results helped us to elucidate the mechanisms of the various responses to MTX among the cell lines included in our study.Although methotrexate (MTX) is the most well-known antifolate included in many standard therapeutic regimens, substantial toxicity limits its wider use, particularly in pediatric oncology. Our study focused on a detailed analysis of MTX effects in cell lines derived from two types of pediatric solid tumors: medulloblastoma and osteosarcoma. The main aim of this study was to analyze the effects of treatment with MTX at concentrations comparable to MTX plasma levels in patients treated with high-dose or low-dose MTX. The results showed that treatment with MTX significantly decreased proliferation activity, inhibited the cell cycle at S-phase and induced apoptosis in Daoy and Saos-2 reference cell lines, which were found to be MTX-sensitive. Furthermore, no difference in these effects was observed following treatment with various doses of MTX ranging from 1 to 40  Methotrexate (MTX) is the most widely known antifolate successfully used in oncology for a long time. MTX is particularly effective in the treatment of acute lymphoblastic leukemia, non-Hodgkin lymphoma, breast carcinoma, lung carcinoma, osteosarcoma, choriocarcinoma, and some neuroectodermal tumors . AlthougThe most important effect of MTX is based on the inhibition of dihydrofolate reductase (DHFR), which blocks the reduction of folic acid and, consequently, folic acid metabolism. When the concentration of MTX exceeds the binding capacity of DHFR, all available molecules of tetrahydrofolate (THF) are gradually depleted in the cell, and the synthesis of purine and pyrimidine precursors, which are necessary for synthesis of nucleic acids, is reduced .Although MTX is included in many standard therapeutic regimens, its substantial toxicity limits its wider use, particularly in pediatric oncology. The cytotoxic effects of high-dose MTX (HD-MTX) on normal somatic cells could be reduced by the administration of an antidote, with the most frequent being leucovorin (LV). Another possibility of an MTX schedule is the repeated administration of low-dose MTX (LD-MTX) without LV ,4.RCF gene or by the downregulation of its expression   .Our study focused on a detailed analysis of MTX effects in cell lines derived from two types of pediatric solid tumors, medulloblastoma and osteosarcoma, which were chosen on the basis of their different histogenetic origin and because MTX is typically included in therapeutic protocols for both. The main aim of this study was to analyze the effects of treatment with MTX at concentrations comparable to the MTX plasma levels in patients treated with high-dose or low-dose MTX. Furthermore, an extremely important part of the treatment with high-dose MTX in clinical practice is the administration of LV as an antidote to reduce MTX toxicity in normal cells. Thus, the combined application of MTX and LV was also included in our experiments. An analysis of the expression of genes involved in the mechanisms of resistance to MTX was the final component of our study; the results helped us to elucidate the mechanisms of the various responses to MTX among the examined cell lines.Two reference cell lines and two cell lines derived in our laboratory were used in this study. Daoy (ATCC HTB-186™) medulloblastoma and Saos-2 (ATCC HTB-85™) osteosarcoma cell lines were purchased from the American Type Culture Collection . MBL-02 is an in-house cell line derived previously from a biopsy sample obtained from a 7-year-old girl suffering from desmoplastic medulloblastoma (2.Cells were grown in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% (Daoy and Saos-2) or 20% (MBL-02 and OSA-08) fetal bovine serum, 100 IU/ml penicillin, 100 mg/ml streptomycin, and 2 mM glutamine. In addition, the medium for the Daoy cells also contained 1% nonessential amino acids . Experiments with leucovorin (LV) application were performed in folate-free DMEM . Cell culture was performed under standard conditions at 37°C in a humidified atmosphere containing 5% CO50 value, 7 different concentrations of MTX ranging from 1×10−4 to 1×102μM were tested. For all other experiments, concentrations of 0.1, 1, 10 and 40 μM MTX were used; these concentrations are in the range of MTX plasma levels reached in patients suffering from cancer. The maximum used concentration of MTX, i.e., 40 μM, is comparable with the peak of the MTX plasma concentration achieved during HD-MTX treatment of pediatric solid tumors (MTX (Sigma) was prepared as a stock solution at a concentration of 20 mM in 1 M NaOH (Sigma). This stock solution was diluted in DMEM or folate-free DMEM to obtain the final concentrations used in the experiments. For determination of the IC4 cells/well in 200 μl of culture medium, and the cells were allowed to adhere overnight. The medium was then removed and a new medium containing the selected concentrations of MTX described above or control MTX-free medium was added. The plates were incubated under standard conditions, and LV at the chosen concentrations was added after 42 h. To evaluate changes in cell proliferation, medium with reagents was removed and replaced by 200 μl of DMEM containing 3--2,5-diphenyltetrazolium bromide (MTT) at 0.5 mg/ml. The plates were then incubated at 37°C for 2.5 h. Subsequently, the medium was carefully removed, and the formazan crystals were dissolved in 200 μl of DMSO. The absorbance at 570 nm with a reference absorbance at 620 nm was measured using the Sunrise Absorbance Reader .To evaluate cell proliferation, an MTT assay to detect the activity of mitochondrial dehydrogenases in living cells was used; 96-well plates were seeded with 1×10μl of total reaction volume) were reverse transcribed into cDNA using M-MLV  and oligo dT  priming. PCR was carried out in 25 μl reactions containing 12.5 μl of PPP master mix, 0.5 μl of PCR enhancer (both from Top-Bio), 0.5 μM of each primer and 5 μl of diluted cDNA. The primers used for RFC1, DHFR, TYMS, FPGS, FPGH and HSP90AB1 are described in μl of the PCR product was loaded onto a 2% agarose gel stained with Midori Green  and examined after electrophoresis. The optical density was stained and quantified using ImageJ software , and its concentration and integrity were determined spectrophotometrically. For all samples, equal amounts of RNA ] at 37°C for 30 min.To evaluate changes in the cell cycle, 1.2×106 cells were seeded in 75 cm2 Petri dishes and allowed to attach overnight. The cells were treated with MTX for 1 or 3 days. Both the detached and adherent cells were harvested together, fixed with 3% paraformaldehyde (Sigma) at room temperature for 30 min, permeabilized in 0.2% Triton X-100 (Sigma) for 1 min, and incubated with 2% BSA (PAA) for 10 min to block nonspecific antibody binding. The cells were then treated with a rabbit polyclonal anti-cleaved caspase-3 (Asp-175) primary antibody  at 37°C for 60 min. After washing with PBS twice, goat anti-rabbit IgG conjugated with Alexa Fluor® 488  was applied at 37°C for 45 min.To quantify the rate of apoptosis, 1×10The BD FACSVerse™ flow cytometer with BD FACSuite software  was employed to analyze both the cell cycle and frequency of caspase-3-positive cells at the intervals specified above. Ten thousand events per sample were evaluated in all experiments.50 values were first determined. Using the MTT assay, we analyzed cell viability at day 6 of MTX treatment in a range of MTX concentrations from 1×10−4 to 1×102μM. Both of these cell lines showed a very similar IC50 value: 9.5×10−2μM for Daoy cells and 3.5×10−2μM for Saos-2 cells  and the reference cell lines obtained from ATCC (Daoy and Saos-2), we examined the expression of genes involved in the resistance of tumor cells to MTX . For thi1, G1, S and G2/M phases were determined using flow cytometry at day 3 and 6 of treatment with MTX. All MTX concentrations had the same effect on the distribution of the cell cycle phases; an increase in cells in the S phase was accompanied by a decrease in cells in the G1 phase in the treated cell lines compared with the untreated controls. Importantly, this phenomenon was noted sooner in the Daoy cells, at day 3 of MTX treatment (1 population revealed cytotoxic effects of MTX on both cell lines (1 population was >40% in the Saos-2 cells and ~30% in the Daoy cells. The cytotoxic effect of MTX at concentrations ranging from 1 to 40 μM was nearly the same in both cell lines.Based on the results of previous experiments, both MTX-responding cell lines, i.e., the Daoy and Saos-2 lines, were chosen for cell cycle analysis. The cells were treated with different concentrations of MTX, and the proportions of cells in sub-Greatment , but wasreatment . The anall lines . The pop1 proportion after MTX treatment is caused by apoptosis induction, the MTX-treated cell populations were labeled with an anti-active caspase-3 antibody at day 1 and 3 of MTX application. Both cell lines showed a >30% increase in caspase-3-positive cells at day 3 of treatment with 1, 10 or 40 μM MTX. In contrast, treatment with 0.1 μM MTX led to a 7–8% increase in caspase-3-positive cells in comparison to the control cells (To prove whether the increase in the sub-Gol cells .2 of body surface, in combination with leucovorin, which enables reaching high plasma concentrations with enhanced anticancer and cytotoxic effects (At present, the standard protocol for cancer treatment with MTX includes the application of HD-MTX, defined as >1 g/m effects .‛Leucovo effects . Althoug effects .The main aim of this study was to analyze the effects of MTX on cell lines derived from two types of pediatric solid tumors, medulloblastoma and osteosarcoma, and to determine how these cell lines respond to doses of MTX that correspond to concentrations in a patient’s plasma during administration in clinical practice.50 value (50 value obtained for both of these cell lines was within a similar range of concentrations, i.e., 10−8 M MTX. These results are in accordance with those obtained by other research groups (μM, for both of these cell lines. In contrast, only a slight cytotoxic effect of 0.1 μM MTX was able to be reverted by LV (μM of MTX, as described by Assaraf et al (Daoy medulloblastoma and Saos-2 osteosarcoma cell lines were chosen as reference cell lines for this study and were compared to two other cell lines that were derived in our laboratory from these tumors. The Saos-2 osteosarcoma cells were apparently more sensitive to treatment with MTX than the Daoy cells, as revealed by determination of the IC50 value ; howeverh groups . The negh groups  and impoed by LV . This fiaf et al  on the bμM MTX did not induce a 50% inhibitory effect in these cells. One of the possible explanations for this difference is the low proliferation rate of these tumor cells in comparison with the reference cell lines (Both of our in-house cell lines, i.e., MBL-02 medulloblastoma and OSA-08 osteosarcoma cell lines, appeared to be strongly resistant to MTX; 100 ll lines . No obseRFC1 gene, which encodes the transmembrane solute carrier and is considered to be a main MTX transporting pathway to the cytoplasm (DHFR expression were detected in both the Daoy and Saos-2 cells compared with these levels in the in-house cell lines (de novo synthesis of purine and pyrimidine precursors plays a critical role in cell growth and proliferation, and its high expression in rapidly proliferating cells is thus expected (TYMS in both osteosarcoma cell lines were identical, marked differences in the expression of this gene were detected between the medulloblastoma cell lines, with higher levels of TYMS found in Daoy cells with higher proliferation activity (TYMS gene catalyzes dUMP conversion into dTMP and thus provides the sole source of deoxythymidylate for DNA biosynthesis (in vitro, and the high expression of TYMS in tumor tissue is also associated with poor clinical outcome in some types of cancers (FPGS and FPGH (Other possible specific mechanisms of resistance include impaired transmembrane uptake, alterations in the expression or activity of target enzymes, or impaired intracellular polyglutamylation as a determining process of drug efficacy . The RFCytoplasm , was onlytoplasm . Consequll lines . On the ll lines . On the expected . Althougactivity . The proynthesis . In fact cancers . Another cancers . Neverthand FPGH ; thus, tμM on the distribution of cell cycle phases (1 fraction following treatment with MTX was also involved in proliferation failure (μM MTX and the treatments with other concentrations (TP53 gene, which disables the transactivation function of the p53 protein, was proven in Daoy cells (The flow cytometric analysis of the MTX-sensitive cell lines, i.e., Daoy and Saos-2 cells, clearly confirmed the two main effects of MTX on tumor cells that are responsible for its ability to restrict cell proliferation. First, the cell cycle was arrested in S-phase due to the depletion of nucleotide precursors; our results showed apparent MTX-induced cell cycle arrest in S-phase . Similare phases . Secondl failure . Furthertrations , and thetrations . Caspasetrations . The apotrations  and the oy cells ,27,μM. These findings suggest the possibility of achieving the same outcome with the application of low-dose MTX, which is an extremely important result, particularly for clinical practice, and may explain the lack of clinical advantage of HD-MTX in children with advanced lymphoblastic lymphomas vs. low doses (μM.To summarize, our results showed that treatment with MTX significantly decreased proliferation activity, inhibited the cell cycle at S-phase and induced apoptosis in the Daoy and Saos-2 reference cell lines. Such effects apparently belong to the DHFR-mediated mechanism of MTX action and are based on the depletion of purine and pyrimidine precursors necessary for the biosynthesis of nucleic acids. Importantly, we noted no difference in these effects after treatment with various doses of MTX ranging from 1 to 40 ow doses . Moreove


The induced differentiation of tumor cells represents a very important strategy in modern antineoplastic therapy. Retinoids are the most frequently used group of cell differentiation inducers; however, their toxicity and intrinsic or acquired resistance to retinoids substantially limit their use in clinical protocols. Therefore, special attention has been paid to the combined treatment of cancer cells with retinoids and other compounds that may modulate (enhance or prolong) their antineoplastic effects. For example, combinations of retinoids and bile acids or inhibitors of the lipoxygenases and cyclooxygenases were reported as effective. Our research was focused on the caffeic acid (CA), a widely distributed plant phenolic compound, which is an inhibitor of 5-lipoxygenase.trans retinoic acid (ATRA) in concentration ranging from 0.05 microM to 10 microM was used as an inducer of cell differentiation. ATRA was applied alone or in combination with caffeic acid (CA) at concentrations of 13 and 52 microM; these concentrations of CA corresponded to the plasma levels obtained by its dietary uptake. Changes in cell morphology, proliferation activity, expression of differentiation markers and other cancer-related genes were evaluated in treated cell populations.Eight cell lines derived from different types of pediatric solid tumors  were chosen for this study. All-Although the cell lines showed various sensitivity to the ATRA treatment, the concentrations of CA used in this study were capable to enhance these antineoplastic effects of ATRA, especially in terms of cell differentiation.Our results clearly showed that CA, which belongs to the natural phenolic compounds and is present in honey, apple juice, grapes and some other fruits and vegetables, may potentiate the cell differentiation of tumor cells induced by retinoids. These findings were confirmed using gene expression analysis that showed an increasing expression of genes involved in the process of the induced differentiation.


Approximately 20 drugs have been approved by the FDA for breast cancer treatment, yet predictive biomarkers are known for only a few of these. The identification of additional biomarkers would be useful both for drugs currently approved for breast cancer treatment and for new drug development. Using glycoprotein expression data collected via mass spectrometry, in conjunction with statistical models constructed by elastic net or lasso regression, we modeled quantitatively the responses of breast cancer cell lines to ~90 drugs. Lasso and elastic net regression identified HER2 as a predictor protein for lapatinib, afatinib, gefitinib and erlotinib, which target HER2 or the EGF receptor, thus providing an internal control for the approach. Two additional protein datasets and two RNA datasets were also tested as sources of predictor proteins for modeling drug sensitivity. Protein expression measured by mass spectrometry gave models with higher coefficients of determination than did reverse phase protein array (RPPA) predictor data. Further, cross validation of the elastic net models shows that, for many drugs, the prediction error is lower when the predictor data is from proteins, rather than mRNA expression measured on microarrays. Drugs that could be modeled effectively include PI3K inhibitors, Akt inhibitors, paclitaxel and docetaxel, rapamycin, everolimus and temsirolimus, gemcitabine and vinorelbine. Strikingly, this modeling approach with protein predictors often succeeds for drugs that are targeted agents, even when the nominal target is not in the dataset. HER2) predicts sensitivity to pertuzumab, trastuzumab and lapatinib. Additional biomarkers would be of significant value for determining the sensitivity of tumors to drugs already approved for clinical use in breast cancer, as well as for new drug development [The U.S. Food and Drug Administration has approved roughly two dozen drugs for breast cancer treatment, but only a few predictive biomarkers are currently available to guide their use. For example, levels of the estrogen or progesterone receptor have been found to predict sensitivity to compounds that interfere with estrogen receptor signaling, and, the over-expression of human epidermal growth factor receptor 2 . One striking finding is that the cell lines vary greatly in sensitivity to various drugs, in some cases by more than four orders of magnitude. While acquired resistance to chemotherapeutics or targeted agents is well recognized and is the subject of intensive study [Large data sets describing the effects of various drugs on the growth of cancer cell lines have recently been generated for the purpose of accelerating the preclinical evaluation of new compounds –8. One ove study , the varWe applied regularized regression to model the intrinsic sensitivities of cell lines to 90 drugs  using thOur glycoprotein dataset includes 185 glycoproteins obtained from 22 breast cancer cell lines. Glycoproteins were collected using a protocol in which the first step, oxidation of the glycans using periodate, takes place on intact cells . After cProtein analyses were carried out on a Thermo LTQ ion trap mass spectrometer and a Thermo Q Exactive Orbitrap mass spectrometer. Spectral counts were used to determine relative expression levels of a glycoprotein in the various cell lines. Aliquots from the same glycoprotein sample produced similar results when analyzed on the two mass spectrometers, although less protein was required for the analyses carried out on the Orbitrap instrument. To combine samples from the two datasets, the data were plotted in a quantile-quantile plot, and a line was fit. Using the slope and intercept, the inverse transform was applied to the Q Exactive data, forcing it to have the same center and dispersion as the LTQ data. For four of the cell lines  there were only Q Exactive data. Spectral counts for these cell lines were normalized to the LTQ data using household proteins. The seven proteins in the LTQ dataset with the lowest coefficient of variation were P20645, Q9BT09, P62937, Q16563, Q9BVK6 Q08722 and P07602. The Euclidean length of the spectral counts for these seven glycoproteins was calculated for both the LTQ data and the Q Exactive data, and the ratio was used to normalize all Q Exactive spectral count data. After combining LTQ and Q Exactive data, glycoproteins with fewer than 100 spectral counts over all the cell lines were dropped from the dataset. For purposes of regression analysis one spectral count was added to all values, and the base ten logarithm taken.Exon array analysis is described in reference The data (47 cell lines) was used as provided in Additional Files Table 2 of reference The multiple reaction monitoring (MRM) mass spectrometry data (27 cell lines) are based on Table S4 of reference glmnet package in the R statistical programming language. One adjustable parameter, λ, sets the amplitude of the penalty term; a second parameter, α, is a weight that determines the mixture of L1 and L2 norm components in the penalty. Letting α = 1 gives lasso regression, and 0 < α < 1 gives elastic net regression. For elastic net regression we incremented α from 0 to 1 in steps of 0.1. For each value of α, we found the best value of λ by cross validation (cv.glmnet function), using the mean squared error (MSE) to evaluate the fit of the model to the data. Plots of MSE as a function of α showed some instability from run to run, so we used the average of 10 runs. The value of α giving the lowest MSE was selected for the elastic net model. These values differed from drug to drug. We performed cross validation by leaving out all pairwise combinations of cell lines; for the glycoprotein dataset (22 cell lines) this is similar to 10-fold cross validation. We found the correlations between each of the 21 cross validation estimates of drug sensitivities for all cell lines and the observed sensitivity values, and finally averaged these correlations. Optimal values of α and λ were determined for each training set in the cross validation as described above.The methods used are elastic net regression and lasso regression . CalculaQuantitative protein expression data may be more useful than mRNA data for predicting the responses of breast cancer cell lines to drugs. In this study we evaluated the ability of a glycoprotein dataset obtained via mass spectrometry to provide explanatory or predictor variables to fit measured drug sensitivities . The druBoth elastic net and lasso regression reduce the number of predictor variables, but they do so to different extents. Elastic net regression models usually have more predictors than do the lasso models for the same drug, as a result the fits to the data are better. The disadvantage of the elastic net method is that with more variables the model may contain some predictors with little statistical or biological significance.ERBB2, UniProt Accession number P04626), Disintegrin and metalloproteinase domain-containing protein 10  and Junctional adhesion molecule A . These three proteins are also among the 92 predictors identified in the elastic net model. Using the three proteins for ordinary least squares multiple regression gives a model in which the fitted drug sensitivities match the observed ones with a correlation coefficient of 0.91. It should also be noted that lasso regression identified HER2 as a predictor for sensitivity to everolimus and temsirolimus, two derivatives of rapamycin. While the lasso models generally do not fit the data as well as the elastic net models, they select fewer variables. For many drugs in this dataset the sensitivities could be fit well with 1–3 predictor variables (see below).Rapamycin illustrates the differences between the two methods. The breast cancer cell lines in our sample vary in their sensitivity to rapamycin by more than four orders of magnitude. The model constructed using elastic net regression had 92 predictor variables, giving a very tight fit to the observed data. Models constructed using lasso regression showed some variability of results over 1000 separate runs, but three predictor proteins appeared in all models . The thrFive of the drugs we examined were developed with the goal of inhibiting the epidermal growth factor receptor (EGFR), or its constitutively active variant, HER2. HER2 is present in the dataset and is over-expressed in three of the 22 cell lines. Lasso regression identifies HER2 as a predictor for the two HER2 inhibitors, afatinib (BIBW2992) and lapatinib, and also for two of the EGFR inhibitors, AG1478 and gefitinib. This finding serves as a positive control for the application of lasso regression to the glycoprotein data.The quantitative relationships between HER2 expression levels and drug sensitivities can be seen in the scatterplots in ERBB2 or P04626), the lasso model included SLC7A5 , BST2  and A2ML1 ; these are the four predictors identified most often in the lasso models. HER2 expression has a fairly high correlation with afatinib sensitivity, 0.65, but the SLC7A5, BST2 and A2ML1 have lower correlations, 0.61, −0.59 and 0.44, respectively. Part of their contribution is to enable the modeling of the afatinib-sensitive cell lines with normal HER2 expression (blue symbols) correctly. A model using only HER2 as a predictor would mistakenly suggest that the cell lines represented with blue symbols are not sensitive to afatinib.By adding one or more predictor variables to HER2, it is possible to fit the sensitivities of the cell lines to gefitinib, AG1478, afatinib and erlotinib, where the relation between sensitivity and HER2 expression is not linear. The elastic net model for afatinib contained nine predictor variables, compared to four in the lasso model. For both models HER2 was one of the predictor variables. The elastic net model gives a somewhat tighter fit to the observed drug sensitivities . Both mo2 values comparing the observed and fitted drug sensitivities) varied from 0.2 to nearly 0.8 (Lasso regression returned a model for 87 of 90 drugs . For eacarly 0.8 . The freFor each drug we found the best (lowest MSE) model with three predictors using the Leaps and Bounds algorithm . The coeThe magnitude of the improvement may be exaggerated somewhat, due to the possibility of over fitting as the number of predictor variables increases and the best models are selected. Over fitting can occur when the model includes variables that by chance reduce the MSE for the model in the sample under study. A model that overfits would probably perform poorly on cell line data that was not used to construct the model. Predictor variables that contribute to overfitting may have little or no biological relevance to the problem of modeling drug sensitivities.While increasing the number of predictor proteins from one to three may allow some overfitting, the proteins selected by the lasso algorithm as predictors often make biological sense. For example, the model illustrated in We used all available cell line data to create and test the models presented so far. A more demanding and realistic approach would involve building a model based on some training data, then using it to predict drug response to other cell lines not in the training set. Given the time and expense involved in obtaining mass spectrometric data, it is more efficient to use a cross validation approach than to expand the data set further. In cross validation the cell lines are divided into a training set and a test set. A regression model built from the training data is then used to predict the drug sensitivities of the test set cell lines. The coefficient of correlation between the predicted and the observed drug sensitivities gives an idea of how well the modeling performs.We carried out cross validation using elastic net regression on our glycoprotein dataset and on two related mRNA datasets: a microarray gene expression dataset that includes 74 drugs [We tested two other publicly available protein datasets for their ability to predict drug sensitivities: a reverse phase protein array (RPPA) dataset, which depends on antibody binding for quantitation , and a dIn the RPPA dataset, the 70 proteins measured were pre-selected by the investigators on the basis of known linkage of the proteins to cancer, including proteins known to be important in the control of signaling pathways, cell proliferation and DNA repair.In the MRM dataset, targeted assays were devised for 317 proteins in 30 breast cancer cell lines, of which 27 lines overlap with the drug response dataset. The proteins were selected by the authors of that study for differential expression across the cell lines. They are found in many cellular compartments and contribute to a wide range of biological processes. Quantitation was achieved by comparing the test signal intensity to that of a reference peptide labeled with a heavy, stable isotope. Only two proteins, HER2 and cadherin E, are common to the glycoprotein, RPPA and MRM datasets.The sensitivities of the cell lines to EGFR or HER2 blockers  were modeled effectively by both RPPA and MRM data, and these drugs often performed well in cross-validation .Summarizing the results so far, one dataset, the RPPA protein dataset, performed less well than the others in modeling using all cell lines, as judged from the distributions of the coefficients of determination . The arrThere are seven phosphatidylinositol-3-kinase (PI3K) inhibitors among the drugs. Three of them, BEZ235, GSK2126458  and GSK 2119563 performed well in both the modeling  and the Rapamycin, everolimus and temsirolimus are related compounds that block the mammalian target of rapamycin (mTOR); the cell lines varied in sensitivity to these drugs over 4.6, 3.3 and 3.7 orders of magnitude, respectively. mTOR is in the RPPA dataset, but was identified with very low probability as a predictor for these drugs . All thrThe sensitivities of the cell lines to paclitaxel and docetaxel varied over smaller ranges than for rapamycin. For both drugs it was possible to find predictive models with high coefficient of determination . Paclita2) = 0.52 (2 =0.36) than does AKTp473 (R2 =0.20). For the Sigma inhibitor, PDK1 alone gives a model with R2 = 0.48; adding AKTp473 does not improve the model further. Modeling triciribine sensitivity failed with these two predictors. For the two drugs in which modeling succeeded, PDK1 is the more useful predictor even though AKT is the nominal target of the drugs.The drug list includes three AKT1 inhibitors: GSK2141795, Sigma AKT 1,2 inhibitor, and triciribine. The RPPA proteins include AKT (AKT1), AKTp473, and PDK1, a kinase that phosphorylates AKT. AKTp473 and PDK1 (or PDK1p241) were found in lasso regression models for all three drugs. A regression model with AKTp473 and PDK1 as predictors allowed the fitting of the GSK2141795 sensitivities with coefficient of determination (R) = 0.52 . By itse2 = 0.77) appeared in the glycoprotein dataset, with predictors P17900 (Ganglioside GM2 activator), P28799 (Granulins) and P08842 (steryl sulfatase) (2 = 0.85) was found in the MRM dataset, with predictors G6PD (Glucose-6-phosphate 1-dehydrogenase), HRSP12 (Ribonuclease UK114) and TPM4 .These drugs are used for patients who experience recurrence after treatment with the standard of care chemotherapy. As with rapamycin, the sensitivities of the cell lines to gemcitabine and vinorelbine spanned approximately four orders of magnitude. If this variation reflects the situation in patients’ tumors, there are patients who are highly sensitive to these drugs. The best model for gemcitabine (Rlfatase) . The bes2 = 0.79, was found in the MRM protein dataset using mitochondrial thioreduxin-dependent peroxidide reductase (PRDX3), acyl-amino acid releasing enzyme (APEH) and importin subunit alpha (KPNA2).Fascaplysin, NU6102, Olomoucine II and Purvalanol are inhibitors of cyclin-dependent kinases (CDKs) and are in the main drug database studied here. Palbociclib, another CDK inhibitor, has been analyzed elsewhere on breast cancer cell lines . For allFive datasets were compared in their abilities to provide predictors for regression modeling of drug sensitivities in breast cancer cell lines. We used two criteria for evaluating performance: the agreement between observed and predicted sensitivities (coefficient of determination), and prediction error estimated by cross validation. The glycoprotein and MRM datasets, obtained via mass spectrometry, and a RNA seq dataset performed best, with the glycoprotein and MRM datasets giving more consistent results in the cross validation.Drugs that block the EGF receptor or HER2 were modeled well, at least partly because HER2 is in all the datasets. However, it is not necessary that a drug have its target in the data for this approach to work. For example, AKT and mTOR are not present in either the glycoprotein or MRM datasets, yet the Sigma Akt1,2 inhibitor and rapamycin were modeled accurately using predictors from these datasets. It appears that there is information useful for modeling drug sensitivity not just in the nominal targets of the drugs but also in the expression levels of other proteins.These results show that it is possible to predict the responses of breast cancer cell lines to drugs, particularly when mass spectrometry has been used to quantify protein expression. Can the approach be extended to patient samples? One possibility would be to use targeted assays on tumor samples. The MRM dataset targets specific proteins; various methods for targeting proteins by mass spectrometry are currently under development . MethodsSupplementary file


The green tea catechin epigallocatechin gallate (EGCG) was shown to effectively inhibit tumor growth in various types of cancer including biliary tract cancer (BTC). For most BTC patients only palliative therapy is possible, leading to a median survival of about one year. Chemoresistance is a major problem that contributes to the high mortality rates of BTC. The aim of this study was to investigate the cytotoxic effect of EGCG alone or in combination with cisplatin on eight BTC cell lines and to investigate the cellular anti-cancer mechanisms of EGCG.The effect of EGCG treatment alone or in combination with the standard chemotherapeutic cisplatin on cell viability was analyzed in eight BTC cell lines. Additionally, we analyzed the effects of EGCG on caspase activity, cell cycle distribution and gene expression in the BTC cell line TFK-1.EGCG significantly reduced cell viability in all eight BTC cell lines . Combined EGCG and cisplatin treatment showed a synergistic cytotoxic effect in five cell lines and an antagonistic effect in two cell lines. Furthermore, EGCG reduced the mRNA levels of various cell cycle-related genes, while increasing the expression of the cell cycle inhibitor p21 and the apoptosis-related death receptor 5 (p < 0.05). This observation was accompanied by an increase in caspase activity and cells in the sub-G1 phase of the cell cycle, indicating induction of apoptosis. EGCG also induced a down-regulation of expression of stem cell-related genes and genes that are associated with an aggressive clinical character of the tumor, such as cd133 and abcg2.EGCG shows various anti-cancer effects in BTC cell lines and might therefore be a potential anticancer drug for future studies in BTC. Additionally, EGCG displays a synergistic cytotoxic effect with cisplatin in most tested BTC cell lines. Biliary tract cancer (BTC) develops at different locations within the biliary tree system. The prognosis for BTC remains very poor with a five year survival rate of only 10 % . In genein vitro and in vivo. There is also evidence that EGCG has anti-cancer effects in BTC: two studies demonstrated that EGCG suppresses the growth and invasion potential of various human BTC cell lines [in vivo. They also demonstrated, that combined EGCG and gemcitabine incubation was associated with a synergistic cytotoxic effect [in vitro and in vivo [Green tea is a very popular beverage that had its origin in China several thousand years ago. Numerous studies prove that green tea consumption has cancer-preventive effects (reviewed in ). Green ll lines , 14. Lanc effect . This poc effect . These s in vivo .Based on these encouraging preliminary results and a paucity of data about a potential synergism of EGCG and cisplatin in BTC cells, we hypothesized that combined treatment of EGCG with cisplatin shows a synergistic cytotoxic effect. For this purpose, we used a comprehensive approach by testing combined EGCG and cisplatin treatment in a panel of eight different BTC cell lines. Since previous studies suggest that EGCG exhibits diverse anti-cancer effects, we explored the EGCG-caused changes in cell-cycle distribution, caspase activity and gene expression of selected cell cycle- and apoptosis-related genes as well as genes that are associated with an aggressive tumor character and potential cancer stem cell (CSC) status.2O to a stock concentration of 10 mM and stored in aliquots at -20 °C. Cisplatin was provided by the hospital’s pharmacy  as a stock solution of 3.33 mM and was stored at 4 °C. Resazurin was purchased from Sigma Aldrich and dissolved in Dulbecco’s Phosphate Buffered Saline . Overall five bile duct carcinoma cell lines CCSW-1 , 4.74*104 , 5.53*104 (SkChA-1), 6.32*104 , and 7.11*104 (MzChA-1). For EGCG, cisplatin and combined drug treatment we used serum-free DMEM (sfDMEM) to avoid possible interactions of the drugs with components of the serum.EGCG was obtained from Sigma Aldrich  and dissolved in HSW-1 (G2 ), BDC (GSW-1 (G2 ), EGI-1 SW-1 (G2 ), SkChA-SW-1 (G2 ) and thrSW-1 (G2 ) were cuSW-1 . As described by Chou [We investigated the cell line- and dose-dependent cytotoxic effect of EGCG only and combined EGCG cisplatin treatment on cells grown in 96-well microplates. Quantification of cell viability was carried out using the resazurin assay and an Infinite M200 microplate reader  as described , 26. Cel by Chou , combinaTFK-1 cells were treated with 50 μM EGCG in sfDMEM in 60 mm cell culture dishes for 24 h. Total RNA was isolated using the RNeasy Kit and QIAshredder tubes (Qiagen). cDNA synthesis was done with the ImProm-II™ Reverse Transcription System (Promega). Quantification of gene expression was performed by quantitative real time reverse transcription PCR (qRT-PCR) using the GoTaq qPCR Master Mix (Promega) and a ViiA7 real time PCR system . All samples were measured at least in biological triplicates. Melting curve analysis was performed for each sample and primer pair to verify specificity of PCR products. Samples were normalized to beta-actin and treated samples were normalized to untreated controls according to the ΔΔCt method . Down-reTFK-1 cells were seeded in 96-well microplates and incubated with 50 μM EGCG in sfDMEM for 24, 48 and 72 h, respectively. Apoptosis analysis was performed using the Caspase-Glo® 3/7 Assay (Promega) according to the manufacturer’s protocol with an Infinite M200 microplate reader (Tecan). For each time point, caspase activity was related to a corresponding untreated (sfDMEM only) control. Microscopic pictures were taken with an inverted phase contrast microscope (Motic AE31) which was equipped with a CCD-1300B digital camera  controlled by LUCIA imaging software .For cell cycle analysis, TFK-1 cells were seeded in 30 mm cell culture dishes for 72 h in sfDMEM medium containing 50 μM EGCG. After 72 h cells were harvested with 1x Trypsin-EDTA  and resuspended in 100 μL DBPS. Cells were fixed by addition of 1 ml 75 % ice-cold EtOH and incubated for 15 min on ice. After centrifugation, cells were resuspended in 200 μL DBPS containing 0.04 mg/ml propidium iodide  and 0.1 mg/ml RNase  and incubated for 30 min at 37 °C protected from light. After addition of 500 μl DPBS, cell cycle analysis was carried out on a Quanta SC flow cytometer . For data analysis FlowJo software was used  .t-test was used for calculation of significance between groups. All calculations were performed using OriginPro 9.1 . Statistical results were considered significant (*) or highly significant (**) at p < 0.05 and p < 0.01, respectively.All data points represent mean values of at least three biological replicates ± SEM. Paired student’s Treatment of eight BTC cell lines with different concentrations of EGCG (range: 0.2-400 μM) for 72 h significantly reduced the cell viability in all cell lines in a dose- and cell line-dependent manner Fig. . InteresTo assess a potential synergistic effect, we measured the cell viability for single and combined treatments and calculated the combination index (CI). Combined EGCG and cisplatin treatment caused an antagonistic effect in two cell lines (CCSW-1 and EGI-1) for both tested combinations. For one cell line (SkChA-1) the data points achieved by single treatments were not suitable for CI calculation. The remaining five BTC cell lines showed a clear synergistic effect  or a moderate synergistic effect , respectively, for combined EGCG and cisplatin treatment , again indicating apoptosis. Additionally, we observed a decrease of cells in G2/M (from 33.3 % to 19.4 %). The overall percentage of cells in G0/G1 and S-phases remained unchanged Fig. .In a last step we investigated the effect of EGCG treatment on the expression of cell cycle-  and apoptosis-related genes , genes that play a role in a potential CSC phenotype cd24, cd133) and multidrug resistance (abcg2), as well as genes that are related to general enhanced aggressiveness of BTC : EGCG reduced the expression of ccna2, ccnb1, ccnd1 and e2f1, but not of ccne1 in TFK-1 cells. This was accompanied by an enhanced level of dr5 and p21 gene expressions. In addition, we saw a reduction of mRNA levels of cd24 and cd133 as well as of abcg2 and e2f. Interestingly, we also observed a decline of the expression of the three core components of the polycomb repressive complex 2  eed, ezh2 and suz12 to different extent  almost no vital cells were measurable, whereas for BDC and SkChA-1 a certain amount of cells survived, indicating different responsiveness to EGCG treatment. These findings are in line with a study carried out by Takada and colleagues, which showed that EGCG inhibited cell growth in a dose-dependent manner in three BTC cell lines  . Furthergiocytes .It is also known from previous studies that EGCG exhibits synergistic effects with other anticancer compounds , 31–34. The cytotoxic effect of EGCG has in part been ascribed to cell cycle arrest , 9. In oEGCG also slightly reduced mRNA levels of the two stem cell-related genes cd24 and cd133, known to be associated with enhanced aggressiveness, higher tumorigenic potential and stem cell status in BTC –39. We ain vitro. EGCG significantly reduced cell viability of all eight BTC cell lines and for most cell lines a synergistic cytotoxic effect could be shown, when combined with the standard chemotherapeutic drug cisplatin. Additionally, EGCG showed a profound effect on the cell cycle, which changes were confirmed indirectly by down-regulation of various cell cycle-dependent genes, enhanced caspase activity and cell cycle arrest. Furthermore, EGCG might also have an effect on cancer stem cell properties. All these results suggest that EGCG may be a promising and versatile (adjuvant) drug for future in vivo experiments concerning BTC. Several completed or currently active and recruiting clinical phase I or II trials (n > 20) include EGCG as a chemopreventive or supportive drug in various tumor entities . Therefore, future clinical studies need to fully evaluate the potential of the green tea constituent EGCG as an adjuvant or chemopreventive drug for BTC.EGCG is a potent drug for treatment of BTC


Anaplasma centrale has been used in cattle as a live blood vaccine against the more pathogenic Anaplasma marginale for over 100 years. While A. marginale can be propagated in vitro in tick cell lines, facilitating studies on antigen production, immunisation and vector-pathogen interaction, to date there has been no in vitro culture system for A. centrale. In the present study, 25 cell lines derived from 13 ixodid tick species were inoculated with the Israeli vaccine strain of A. centrale and monitored for at least 12 weeks by microscopic examination of Giemsa-stained cytocentrifuge smears. Infection of 19 tick cell lines was subsequently attempted by transfer of cell-free supernate from vaccine-inoculated tick cells. In two separate experiments, rickettsial inclusions were detected in cultures of the Rhipicephalus appendiculatus cell line RAE25 28–32 days following inoculation with the vaccine. Presence of A. centrale in the RAE25 cells was confirmed by PCR assays targeting the 16S rRNA, groEL and msp4 genes; sequenced PCR products were 100% identical to published sequences of the respective genes in the Israeli vaccine strain of A. centrale. A. centrale was taken through three subcultures in RAE25 cells over a 30 week period. In a single experiment, the Dermacentor variabilis cell line DVE1 was also detectably infected with A. centrale 11 weeks after inoculation with the vaccine. Availability of an in vitro culture system for A. centrale in tick cells opens up the possibility of generating a safer and more ethical vaccine for bovine anaplasmosis. The cell lines were grown at either 28 °C or 32 °C in sealed flat-sided culture tubes (Nunc) containing 2.2 ml of complete culture medium , 2 mM L-glutamine, 15 mM HEPES and 0.1% NaHCO3 (ACGM) to remove traces of antibiotics and 2 ml of ACGM was added to the tube. For cultures receiving blood vaccine, ACGM was further supplemented with 5 μg/ml Amphotericin B (ACGMA).A panel of 32 tick cell lines derived from 14 ixodid tick species  were teseviously . Prior t2.2A. centrale blood vaccine comprising bovine erythrocytes with A. centrale rickettsaemia of 20%, cryopreserved with 5% DMSO as 1.8 ml aliquots containing 1 × 108 infected erythrocytes, was prepared at the Kimron Veterinary Institute and stored in the vapor phase of a liquid nitrogen refrigerator prior to and following transfer on dry ice to the Pirbright Institute. For inoculation onto tick cell lines, a vial of vaccine was thawed rapidly by immersion in a 37 °C water bath and the contents were immediately diluted in 9 ml of ACGMA at room temperature. Aliquots of 0.6–0.7 ml were immediately added to tubes of tick cells in ACGMA, the contents of each tube was mixed by gentle rocking 2–3 times, and the cultures were incubated at 28 °C or 32 °C.The Israeli 2.3Anaplasma infection. Giemsa-stained cytocentrifuge smears were prepared at 2–3 week intervals from approx. 50 μl of resuspended cells and examined at 500× and 1000× (oil immersion) for presence of A. centrale bacteria. Photomicrographs were taken using a CCD digital camera attached to a Zeiss Axioskop microscope and Zeiss Axiovision software.The medium of inoculated cultures was changed after 48 h by removal and replacement of 1.0–1.5 ml ACGMA. Thereafter, medium was changed weekly and, after the second week, ACGMA was replaced with ACGM. Cultures were examined weekly for at least 12 weeks by inverted microscope prior to the medium change for evidence of microbial contamination, general cell health and signs of 2.4A. centrale was clarified by centrifugation at 1500 × g for 5 min to remove intact cells, and 0.3–0.5 ml of clarified supernate was added to fresh cultures of the recipient cell line. All subcultures were incubated at 32 °C regardless of the normal incubation temperature of the recipient cell line.Subcultures were carried out onto a fresh cell culture of the same tick cell line by transfer of 0.3–0.5 ml of supernatent medium without centrifugation. For subculture into different tick cell lines, supernatent medium from tick cell cultures previously inoculated with material containing 3A. centrale blood vaccine and from tick cell cultures using a DNeasy blood and tissue kit (Qiagen) following the manufacturer’s instructions for Gram-negative bacteria. DNA extracts were used as templates for PCRs targeting fragments of the 16S rRNA and groEL (HSP60) genes for Ehrlichia and Anaplasma detection . Sequences were aligned using the European Bioinformatics Institute multisequence software ClustalW2  for multiple sequence alignment.Positive PCR products were purified using a High Pure PCR Product Purification kit (Roche Life Science) following the manufacturer’s instructions. Purified amplification products were sequenced in the forward and reverse directions, and homology searches were performed in the NCBI database using the BLAST search programme  and from residual A. centrale blood vaccine stored at −20 °C in the original cryovials since the day of inoculum preparation. PCR amplification of a fragment of the 16S rRNA gene produced bands of the expected size (468 bp) in the blood vaccine and in the RAE25 and IDE8 cells previously inoculated with diluted A. centrale blood vaccine  in the vaccine, a fainter band in the A. centrale-inoculated RAE25 cells, and a very faint band in the A. centrale-inoculated IDE8 cells , indicating that the A. centrale blood vaccine was not contaminated with A. marginale. The multiplex PCR was also used at 6 months post inoculation to confirm that the bacteria seen in DVE1 cells inoculated with blood vaccine were A. centrale  and A. centrale msp4 (357 bp) PCR products were identical to each other for each gene, and showed 100% identity with the sequences corresponding to the A. centrale Israeli vaccine strain deposited in GenBank  obtained from the blood vaccine in the multiplex PCR was also homologous to the A. centrale msp4 sequence ,  GenBank . The 16Sh Africa , while td strain . Unexpecsequence , indicatfor msp4 .4.3A. centrale from RAE25 cells was successfully subcultured into fresh RAE25 cells 64 days after culture initiation and, at the time of writing, has been maintained in RAE25 cells through three passages over a 210 day-period. Cell-free supernate from infected RAE25 cells was inoculated onto 18 heterologous tick cell lines  and a spotted fever group Rickettsia (D. variabilis cell line DVE1 supports growth of Rickettsia peacockii (E. canis (author’s unpublished results); in both cases the bacteria were transferred from already-infected cell lines derived from different tick species, making the present study the first report of successful isolation of an intracellular bacterium directly from mammalian cells into DVE1. In contrast to E. ruminantium which, once established in IDE8 cells was readily transferred into heterologous tick cell lines refractory to infection with mammalian stages of the bacterium , although it is unclear whether this was the field isolate of A. centrale or the vaccine strain. A single splenectomised ox inoculated with ground-up unfed adult R. simus, previously fed as nymphs on a calf that had contracted the A. centrale vaccine strain in utero, developed patent A. centrale infection. The authors failed to transmit A. centrale between splenectomised cattle by interrupted feeding of the one-host ticks Rhipicephalus (Boophilus) decoloratus and Rhipicephalus (Boophilus) microplus  of any of adult male or female Hyalomma excavatum, Rhipicephalus (Boophilus) annulatus or Rhipicephalus sanguineus ticks, although A. centrale DNA was detected in salivary glands of 1/10 R. sanguineus ticks transmission fed for 6 days.Rhipicephalus species  and four Dermacentor species  were tested for ability to support A. centrale infection and growth. Of these, there was no evidence of infection in the cell lines derived from tick species previously reported to be experimentally infectable with A. centrale – RSE8, RML-RSE, DAE15 and DAE100T – while one out of four R. appendiculatus and one D. variabilis cell lines did become infected. As far as we know, neither R. appendiculatus nor D. variabilis have been tested for ability to transmit A. centrale; the results of the present study suggest that the vector capacity of these two tick species should be investigated. As there is no cell line derived from R. simus, it was not possible to compare the in vitro susceptibility of cells from this tick species with those of R. appendiculatus.In the present study, cell lines derived from five in vitro culture systems for other Anaplasma species resulted in a rapid expansion of knowledge on many different aspects of, in particular, A. marginale and A. phagocytophilum, reviewed by A. centrale in tick cells will facilitate a similar expansion of knowledge of this enigmatic bacterium and, importantly, opens up the possibility of producing A. centrale vaccine in an in vitro system that will be much safer and more controllable than the current in vivo system (in vitro culture system, further research will be needed to determine the safety, immunogenicity and efficacy of tick cell-derived A. centrale as a putative vaccine antigen.Availability of continuous o system . Followi


Allogeneic hematopoietic stem cell transplantation  is the only treatment with curative potential for certain aggressive hematopoietic malignancies. Its success is limited by acute graft-versus-host disease (GVHD), a life-threatening complication that occurs when allo-reactive donor T cells attack recipient organs. There is growing evidence that microbes and innate pattern-recognition receptors (PRRs) such as toll-like receptors (TLR) and nod-like receptors (NLR) are critically involved in the pathogenesis of acute GVHD. Currently, a widely accepted model postulates that intensive chemotherapy and/or total-body irradiation during pre-transplant conditioning results in tissue damage and a loss of epithelial barrier function. Subsequent translocation of bacterial components as well as release of endogenous danger molecules stimulate PRRs of host antigen-presenting cells to trigger the production of pro-inflammatory cytokines (cytokine storm) that modulate T cell allo-reactivity against host tissues, but eventually also the beneficial graft-versus-leukemia (GVL) effect. Given the limitations of existing immunosuppressive therapies, a better understanding of the molecular mechanisms that govern GVHD versus GVL is urgently needed. This may ultimately allow to design modulators, which protect from GvHD but preserve donor T-cell attack on hematologic malignancies. Here, we will briefly summarize current knowledge about the role of innate immunity in the pathogenesis of GVHD and GVL following allo-HSCT. Allo-HSCT is an established treatment modality for aggressive hematological malignancies and is performed in more than 30,000 patients annually worldwide . Donor-dThe biology and function of pattern-recognition receptors (PRRs) is reviewed in detail within this research topic issue , 6. In bLactobacillus rhamnosus resulted in reduced translocation of enteric bacteria to the mesenteric lymph nodes, associated with improved survival and reduced acute GVHD in mice  and initiate adaptive immune responses, their role in the pathogenesis of acute GVHD has become a focus of intense research. A widely accepted model  constitute a family of transmembrane PRRs that are broadly expressed in hematopoietic and non-hematopoietic cells . TLR ligOther members of the TLR family have been associated with immunomodulatory capacities and suppression of GVHD. Pretreatment of mice with the TLR5 ligand flagellin resulted in reduced GVHD and improved overall survival . InteresFurthermore, it was shown that tissue inflammation induced by TLR ligation can modulate the development of GVHD at a local level . In thisIn addition, signaling via TLR9 that detects microbial CpG-DNA motifs has been implicated in the pathogenesis of acute GVHD. Studies in TLR9 deficient mice showed reduced GVHD and improved survival , 37. RepTaken together, TLR signaling can both aggravate and attenuate the development of local and systemic GVHD; critical factors seem to be the cell type primarily affected  and the time point of TLR ligation. Thus, the role of TLRs in the pathophysiology of GVHD remains controversial. Recipient mice that are genetically deficient for either the TLR signaling adaptor molecules MyD88 or TRIF were found to show less severe intestinal GVHD . In a coNOD2-deficient mice showed signs of exacerbated GVHD . NOD1 and NOD2 detect peptidoglycans as components of the bacterial cell wall . Both reted GVHD . Anotherere GVHD . Two folortality , 45. Howllo-HSCT –48.Several members of the NLR family not only detect microbial invaders but also survey cellular homeostasis and sense endogenous danger signals . Example7 leads to potassium efflux and subsequent activation of the NLRP3-inflammasome. In mice and humans undergoing allo-HSCT, increased extracellular levels of ATP were found after TBI and during the development of GVHD (P2X7 in hematopoietic cells were partially protected from GVHD. Reconstitution with wild-type DCs resulted in restored GVHD development, demonstrating a critical role for host DCs in sensing ATP and the subsequent induction of GVHD. However, significantly reduced overall survival but no alterations in GVHD severity were found in patients or corresponding donors with a loss-of-function SNP in the 7P2Xreceptor gene (+ T-cell subpopulation that has been causally linked to instances of aggravated GVHD after allo-HSCT (NLRP3 gene are associated with increased disease relapse and reduced overall survival but no alterations in GVHD severity in allo-HSCT patients (The NLRP3-inflammasome is an essential platform for caspase-1 activation in response to multiple distinct exogenous and endogenous danger signals  and its  of GVHD . ATP rel of GVHD . Chimeritor gene . After ctor gene . NLRP3 ator gene , a CD4+ llo-HSCT . Donors patients . Thus, dNOD2 SNPs between patient cohorts, and differences with conditioning, immune suppression, and antibiotic protocols (In summary, NOD2 signaling in hematopoietic cells appears to protect from acute GVHD. Conflicting data from genetic association studies in humans are most likely attributable to differences in frequency of rotocols . We referotocols  for a mo+ cells in the allograft was found to be associated with markedly reduced GVHD but no differences in the rate of leukemic relapse (NOD2 gene and the severity of GVHD found no impact on the relapse rate by these same mutations (NOD2 SNPs in transplant patients and corresponding donors could not confirm their effect on GVHD pathogenesis (NOD2 gene (Many studies have highlighted the fact that innate PRRs contribute to the inflammatory processes that lead to activation of allo-reactive T cells and the pathogenesis of GVHD. In contrast, the molecular details that shape the beneficial GVL effect remain poorly understood. Yet, only a detailed molecular understanding of the GVL effect will allow for the discrimination between GVL-pathways and allo-immune reactions that drive clinical GVHD, a prerequisite for broader application of allo-HSCT in the future. Unspecific depletion or proliferative inhibition of donor T cells is believed to come at the cost of increased relapse of the underlying malignant disease . However relapse , 61. Yetutations , 45. Thuogenesis , or showOD2 gene , 63. TheOD2 gene , their pNOD2 gene, on the other hand, correlated in some studies with adverse allo-HSCT outcome in humans, suggesting a protective role of NOD2. Furthermore, activation of the NLRP3-inflammasome during early conditioning in mice contributes to the development of acute GVHD. Other receptors involved in the local control of microbiota will be the focus of future studies. Type I interferon has been shown to play an important role in defining the balance between GVHD and GVL responses (Toll-like receptors and NLRs respond to a variety of microbial and endogenous danger signals and there is increasing evidence that they influence the development of acute GVHD. Yet, the role of TLRs in the pathophysiology of GVHD remains controversial, as studies with TLR4- and MyD88-deficient mice demonstrated that TLR signaling may not be absolutely required for the development of GVHD. Loss-of-function mutations in the esponses . Thus, Pesponses  or the responses  are of pIn light of the contradicting data regarding the role of some PRRs in acute GVHD, we would like to point out some of the major obstacles in the field of allo-HSCT research. Mouse models of GVHD are heterogeneous, with different subsets of immune cells being the main drivers of respective GVHD pathologies. In addition, innate and adaptive immunity are influenced by intestinal microbiota, which can vary critically between different breeding facilities. The effect of a given genetic alteration or therapeutic intervention may therefore differ between models and breeding facilities, and interpretation of such data must be undertaken with caution. Parts of the existing data may have to be revised in light of these new perceptions. Awareness of these difficulties together with increasing knowledge of graft and host immune and microbial physiology will, however, make this task easier in the future.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.


Monoclonal antibody (mAb) therapy has revolutionized the treatment of a vast range of diseases, mostly in the areas of oncology and autoimmune/inflammatory disorders. With a Systems biology can be used as a powerful tool for the identification of key markers of good production lines, with the aim of engineering superior host lines that more reliably produce good production clones. To date systems biology efforts have been hampered by the need to use the mouse, rat and/or human genome as a reference and has suffered from the inherent limitation in coverage of 2-dimensional gel electrophoresis or mouse or CHO cDNA microarrays. The development of new techniques such as RNA sequencing for transcriptome analysis and LC-MS/MS for proteome analysis combined with the recent release of the CHO genome has reignited interest in using quantitative proteomics and transcriptomics to study high productivity cell lines.Here we applied the latest generation of tools to two CHO cell lines that produce different levels of mAb, as described in Orellana et al. The twoRNA and protein were extracted from cells harvested in mid exponential phase. RNA samples were analysed with RNA sequencing (RNA-Seq) using the Illumina Hiseq2000 platform and 100 bp paired-end reads. TopHat and Cufflinks open-source software were useThe high producer cell line displayed a slightly slower growth rate of 0.0310 ± 0.0002 h-1 compared to the low producer cell line with 0.0340 ± 0.0004 h-1. The two cell lines achieved a titre of 104.3 ± 5.5 mg/L and 52.9 ± 2.0 mg/L on day 4 respectively, with a four-fold difference in mAb specific productivity (19.5 ± 1.0 pg/cell/day compared to 4.6 ± 0.2 pg/cell/day).More than 100 million reads were obtained for each sample by RNA-Seq, with more than 83% of the reads mapping to the CHO reference genome.14,300 transcripts and 714proteins were quantified and tested for differential expression. Despite the fact that both clones come from the same transfection pool, 58% of the quantified transcripts and 56% of the quantified proteins varied significantly. Figure Three key biological processes were identified by proteomics as up-regulated in the high producer cell line: glutathione biosynthesis, actin filament processes and intracellular transport, while several growth-related processes were down-regulated as expected from the lower growth rate. Metabolomic analysis confirmed that the high producing cell line displayed higher intracellular levels of glutathione. These processes may be important for conferring high mAb production, and as such gene candidates have been nominated for targeted engineering of high-expression cell lines.The authors would like to thank Robin Palfreyman, the Queensland node of Metabolomics Australia, the proteomics facilities at SCMB, and SAFC - Sigma Aldrich.