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factors and their role in tumourigenesis. Eur J Cancer 2005, 41 (16) : 2449–2461.CrossRefPubMed 26. Saito N, Kameoka S, Furukawa R: Gene profile analysis of colorectal cancer cell lines by cDNA macroarray. Oncol Rep 2007, 17 (5) : 1061–1065.PubMed 27. Indraccolo S, Moserle L, Tisato V, Gola E, Minuzzo S, Roni V, Persano L, Chieco-Bianchi L, Amadori NCT-501 A: Gene therapy of ovarian cancer with IFN-alpha- producing fibroblasts: comparison of constitutive and inducible vectors. Gene Ther 2006, 13 (12) : 953–965.CrossRefPubMed 28. De Boüard S, Guillamo JS, Christov C, Lefévre N, Brugières P, Gola E, Devanz P, Indraccolo S, Peschanski M: Antiangiogenic therapy against experimental glioblastoma using genetically engineered cells producing interferon-alpha, angiostatin, or endostatin. Hum Gene Ther 2003, 14 (9) : 883–895.CrossRefPubMed 29. Qian ZR, Sano T, Yoshimoto K, Asa SL, Yamada S, Mizusawa N, Kudo E: Tumor-specific downregulation and methylation of the CDH13 (H-cadherin) and CDH1 (E-cadherin) genes correlate with aggressiveness of human pituitary adenomas. Mod Pathol 2007, 20 (12) see more : 1269–1277.CrossRefPubMed

30. Nikuseva-Martic T, Beros V, Pecina-Slaus N, Pecina HI, Bulic-Jakus F: Genetic changes of CDH1, APC, and CTNNB1 found in human brain tumors. Pathol Res Pract 2007, 203 (11) : 779–787.CrossRefPubMed click here 31. Castoldi M, Schmidt S, Benes V, Noerholm M, Kulozik AE, Hentze MW, Muckenthaler MU: A sensitive array for microRNA expression profiling (miChip) based on locked nucleic acids (LNA). RNA 2006, 12 (5) : 913–920.CrossRefPubMed 32. Castoldi M, Schmidt S, Benes V, Hentze MW, Muckenthaler MU: miChip: an array-based method for microRNA

expression profiling using locked nucleic acid capture probes. Nat Protoc 2008, 3 (2) : 321–329.CrossRefPubMed 33. van Rooij E, Sutherland LB, Qi X, Richardson JA, Hill J, Olson EN: Control of stress-dependent cardiac growth and gene expression by a microRNA. Science 2007, 316 (5824) : 575–579.CrossRefPubMed 34. Choong ML, Yang HH, McNiece I: MicroRNA expression profiling during human cord blood-derived CD34 cell erythropoiesis. Exp Hematol 2007, 35 (4) : 551–564.CrossRefPubMed 35. Gottardo F, Liu CG, Ferracin M, Calin GA, Fassan M, Bassi P, Sevignani C, Byrne D, Negrini M, Pagano F, Gomella LG, Croce CM, Baffa R: Micro-RNA profiling in kidney and IWR-1 nmr bladder cancers. Urol Oncol 2007, 25 (5) : 387–392.PubMed 36. Shukla V, Vaissière T, Herceg Z: Histone acetylation and chromatin signature in stem cell identity and cancer. Mutat Res 2008, 637 (1) : 1–15.PubMed 37. Allen A: Epigenetic alterations and cancer: new targets for therapy. IDrugs 2007, 10 (10) : 709–712.PubMed 38.

Nonetheless, some conclusions can be derived from the data. ArcA represses both glcB and aceB expression, thus both enzyme activities should increase in the knockout strain (assuming that there is no translational regulation involved). This explains the twentyfold increment in malate synthase activity in the ΔarcA strain under glucose limiting conditions. Rather small differences are noticed between the wild type and the ΔiclR strain in both growth conditions, implying that IclR does not greatly affect malate synthase activity. Either IclR has a moderate influence on gene expression of malate synthase A, or post-translational BAY 80-6946 datasheet effects are taking place, or the malate synthase

activity is primarily the result of the malate synthase G activity (glcB), as IclR is not a regulator of the glc operons. If IclR has a limited influence on aceB expression, one expects a similar action on aceA as both genes are members of the same operon. Second, if the activity is heavily affected by post-translational events, one does not expect such great differences between the ΔarcA strain and the wild type or ArcA should

have an influence on the post-translational process. Since the former phenomena GF120918 research buy were not Selleckchem BIBF 1120 observed, it is very likely that the malate synthase activity is predominantly the result of glcB expression. Other regulators of the glc operon, besides ArcA and Crp, are GlcC, IHF, and Fis (Figure 3B). The action of these other regulators can explain the results of the batch cultures. The activator

IHF has limited activity in exponentially growing cells [42], but the regulation of the glc operon is even further complicated by the possibility of acetate cross-inducing the operon [43]. Because of the interference of the malate synthase G activity in the tetracosactide measurement of malate synthase activity, it can be concluded that the measurement of isocitrate lyase activity is a better indicator for glyoxylate pathway activity. Glycogen and trehalose content The aberrantly higher redox balance noticed in the ΔarcAΔiclR strain (see Additional file 1) indicates that the biomass composition is slightly different in this strain. For example, as a reaction to unfavorable conditions, microorganisms can store certain polymers and fatty acids [44, 45]. These compounds will increase the net weight of the biomass and will consequently alter the relative biomass composition. Thus, a measured higher biomass yield does not necessarily imply a higher biomass synthesis in terms of RNA, DNA, and protein. The two predominant molecules that E. coli can store under different environmental conditions are glycogen and trehalose [46–49] and therefore the contents of these compounds were determined in both the wild type and the ΔarcAΔiclR strain under glucose abundance and glucose limitation. Trehalose was not detected in any of the cases. For both growth conditions, the glycogen content was higher in the double knockout strain compared to the wild type (see Table 3).

Therefore, larger resistance changes resulted from the increased tunneling and contact resistance. Conclusions This study used a flexible substrate to incorporate a highly sensitive horizontally oriented MWCNT network

in INK-128 pressure sensing performance. A horizontally oriented MWCNT network with low density was grown on an AuFe catalyst. The nanotube network Selleckchem OSI-906 was successfully transferred from the silicon-based substrate to a flexible substrate with 90% yield rate. Both the as-grown and as-transferred nanotubes were characterized to examine the variations in their morphologies and electrical properties. The fabricated pressure sensor showed a great potential in sensing a small change of pressure with a sensitivity eFT508 nmr of approximately 1.68%/kPa. A larger portion of isolated nanotubes could enhance the modifications of the contact area and tunneling distance per nanotube, which limited the transport and hopping of electrons due to the loss of contact among the nanotubes. Such modifications eventually increased the resistance changes and pressure sensitivity of the network. Acknowledgements This research was supported by the National Nanotechnology Directorate Funding NND/ND/(2)/TD11-012 and the eScience Funding 01-03-04-SF0027 under the Ministry of Science, Technology, and Innovation (MOSTI), Malaysia as well as the ERGS 203/PMEKANIK/6730069 under the Ministry

of Higher Education (MOHE), Malaysia. References 1. Odom TW, Huang JL, Kim P, Lieber CM: Structure and electronic properties of carbon nanotubes. J Phys Chem B 2000, 104:2794–2809.CrossRef 2. Tombler TW, Zhou C, Alexseyev L, Kong J, Dai H, Liu L, Jayanthi CS, Tang M, Wu SY: Reversible

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The ligated product was introduced into the E. coli strain JM109 by chemical transformation. One colony from each cloning reaction was selected. The recombinant plasmids were purified using Wizard® Plus SV Minipreps DNA purification system (Promega, Madison, USA) and bidirectional sequenced using universal primer T7 and SP6. DNA sequencing was conducted by 1st Base Pte. Ltd., Singapore.

The chromatograms were validated and assembled in BioEdit version 7.0.1. Phylogenetic analysis The sequences were multiple-aligned with a set of Leishmania strains retrieved from the GenBank using ClustalX, version 2.0.12 [23]. The pairwise genetic distances among isolates were estimated using program MEGA (Molecular Evolutionary Genetics Selleck Sepantronium Analysis), version 4.0 [24]. To investigate the relationships among L. siamensis isolates and other Leishmania species, Leishmania sequences of each locus examined in this study from GenBank were included in the dataset. The evolutionary history was inferred by phylogenetic tree construction using three methods, i.e., Neighbor Joining (NJ), Maximum Parsimony (MP) and Bayesian inference. The NJ and MP trees were constructed using program MEGA, version 4.0 [24]. Reliability of the inferred trees was tested by 1000 Linsitinib bootstrap replications.

For the Bayesian method, starting trees were random: four simultaneous Markov chains were run for 500,000 generations, burn-in values were set at 30,000 XMU-MP-1 generations and trees were sampled every 100 generations. Bayesian posterior probabilities were calculated using a Markov Chain Monte Carlo sampling approach implemented in MrBAYES, version 3.1.2 [25]. The Akaike information criterion in Modeltest, version 3.06, was used to select a DNA substitution model of all phylogenetic analyses [26]. The following models were selected for the dataset of each gene: K2P (SSU-rRNA), TrN+Γ (ITS1 and hsp70), and GTR+Γ (cyt b). The nucleotide sequences generated in this study have been deposited in GenBank under accession

no. JX195633-JX195637, JX195639-JX195640, and KC202880-KC202883. Results Sequence analysis PCR amplification of each target locus resulted in amplicons of the expected sizes as follows: SSU-rRNA (540 bp), nearly ITS1 (340–348 bp), hsp70 (1422 bp), and cyt b (865 bp). Due to the limited amount of DNA samples, studied loci of some samples were not successfully amplified. Twelve amplicons were successfully amplified and bidirectionally sequenced. As a result, a total of 15L. siamensis sequences were analyzed in this study. These consisted of four isolates from SSU-rRNA (CU1, PCM1, PCM2, and PCM4; sequences of PCM1 and PCM2 were reported by Bualert et al. [8]), four isolates from ITS1 (CU1, PCM1, PCM2, and sequences of PCM4; PCM1 were reported by Sukmee et al. [7]), four isolates from hsp70 (CU1, PCM2, PCM4, and PCM5), and three isolates from cyt b (CU1, PCM1, and PCM2).

British journal of cancer 2003, 89:593–601.PubMedCrossRef 7. Sakata K, Someya M, Matsumoto Y, Hareyama M: Ability p38 kinase assay to repair DNA double-strand breaks related to cancer susceptibility and radiosensitivity. Radiation medicine 2007, 25:433–8.PubMedCrossRef 8. Winrow ChristopherJ, Pankratz DanielG, Vibat Cecile: Aberrant recombination involving the granzyme locus occurs in Atm -/- T-cell lymphomas. Human Molecular Genetics 2005,14(18):2671–2684;.PubMedCrossRef 9.

Helt CE, Cliby WA, Keng PC, Bambara RA, O’Reilly MA: Ataxia telangiectasia mutated (ATM) and ATM and Rad3-related protein exhibit selective target specificities in response to different forms of DNA damage. J Biol Chem 2005, 280:1186–92.PubMedCrossRef 10. Barzilai A, Rotman G, Shiloh Y: ATM deficiency and oxidative stress: a new dimension of defective response to DNA damage. DNA Repair (Amst) 2002, 1:3–25.CrossRef 11. Kastan MB, Lim DS: The many substrates and functions of ATM. Nat Rev Mol Cell Biol 2000, 1:179–186.PubMedCrossRef 12. Herzog KH, Chong MJ, Kapsetaki M, Morgan JI, McKinnon PJ: Requirement for Atm in ionizing radiation-induced cell death in the developing central nervous system. Science 1998, 280:1089–91.PubMedCrossRef 13. Chong MJ, Murray MR, Gosink Fludarabine datasheet EC, Russell HR, Srinivasan A, Kapsetaki M, Korsmeyer SJ, McKinnon PJ: Atm and Bax cooperate in ionizing radiation-induced apoptosis in the central nervous system. Proc Natl Acad Sci USA 2000, 97:889–94.PubMedCrossRef

14. Lee Y, Chong MJ, McKinnon PJ: Ataxia telangiectasia mutated-dependent apoptosis after genotoxic stress in the developing nervous system is determined by cellular

differentiation status. J Neurosci 2001, 21:6687–93.PubMed 15. Borges HL, Chao C, Xu Y, Linden R, Wang JY: Radiation-induced apoptosis in developing mouse retina exhibits dose-dependent requirement for ATM phosphorylation of p53. Cell Death Differ 2004, 11:494–502.PubMedCrossRef 16. Zou Jian, Qiao Xiaoming, Ye Huiping, et al.: Antisense inhibition these of ATM gene enhances the Thiazovivin order radiosensitivity of head and neck squamous cell carcinoma in mice. Journal of Experimental & Clinical Cancer Research 2008, 27:56.CrossRef 17. Van Waes Carter: Molecular Biology of Squamous Cell Carcinoma. Head and neck surgery997–1003. 18. Sak A, Stuschke M, Wurm R, et al.: Selective inactivation of DNA-dependent protein kinase with antisense oligodeoxynucleotides: consequences for the rejoining of radiation-induced DNA double-strand breaks and radiosensitivity of human cancer cell lines. Cancer Res 2002,62(22):6621–4.PubMed 19. Leonard CE, Chan DC, Chou TC, et al.: Paclitaxel enhances in vitro radiosensitivity of squamous carcinoma cell lines of the head and neck. Cancer Res 1996,56(22):5198–204.PubMed 20. Muller PY, Janovjak H, Miserez AR, Dobbie Z: Processing of gene expression data generated by quantitative real-time RT-PCR. Biotechniques 2002,32(6):1372–4. 1376, 1378–9PubMed 21.

Now the accepted etiological agent of KS is KS-associated herpesvirus (KSHV)/human herpesvirus 8 (HHV-8) [2]. KSHV is also associated with another lymphoproliferative disorders: primary effusion lymphoma (PEL, also termed body cavity-based lymphoma, or BCBL) and multicentric Castleman’s disease (MCD) [3]. All herpesviruses, this website including KSHV, display two patterns of infection: latent and lytic phases [4]. During latency, only a

restricted set of viral genes is expressed. Upon induction of lytic infection, viral replication and transcription programs become fully activated, and new virions are packaged and released from the cells. Regulation of viral infection cycle is critical to the initiation and progression of KS. However, KSHV infection appears to be necessary but not sufficient for the development of KS without the involvement of other cofactors to reactivate KSHV lytic replication. Previously, we demonstrated that both interleukin-4 (IL-4)/signal transducer and activator of transcription 6 (STAT6) and IL-6/Janus kinase ACY-738 price 2 (JAK2)/STAT3 signal pathways modulated HIV-1 transactivative transcription protein (Tat)-induced KSHV replication [5]. Recently, we have also shown that herpes simplex virus type 1 (HSV-1) was another important cofactor

that reactivated the lytic cycle replication of KSHV, and the production of IL-10 and IL-4 from HSV-1-infected BCBL-1 cells partially contributed to KSHV replication [6]. These facts led us to hypothesize that HSV-1 might reactivate KSHV lytic

cycle replication by modulating GPX6 multiple signal pathways of BCBL-1 cells on the basis of changing cellular cytokines protein expression profile [6]. To verify this hypothesis, in this study, we focused on the major pathways activated by IL-10/IL-10 receptor (R) and IL-4/IL-4R to evaluate their functions in HSV-1-induced KSHV lytic cycle replication. By transfecting a series of dominant negative mutants and protein expressing constructs and using pharmacologic inhibitors, we found that either IL-10/JAK1/STAT3 or IL-4/JAK1/STAT6 signaling was not involved in HSV-1-induced KSHV replication. However, activation of both phosphatidylinositol 3-kinase (PI3K)/protein kinase B (PKB, also called AKT) and extracellular signal-regulated protein kinase (ERK) mitogen-activated protein kinase (MAPK) signal pathways contributed to HSV-1-induced KSHV replication. These novel findings are believed to be the first report on the mechanisms of KSHV activation by HSV-1 and shed light on the pathogenesis of KSHV-induced malignancies. 2. Methods 2.1. Cell culture and virus infection BCBL-1 cells (KSHV-positive and EBV-negative PEL cell lines) were obtained through acquired immunodeficiency syndrome (AIDS) 4SC-202 cell line Research and Reference Reagent Program, National Institutes of Health. Vero cells (African green monkey kidney fibroblasts) were obtained from American Type Culture Collection (ATCC).

Description of the CAPIH Web interface The CAPIH interface provides five query schemes: by gene accession number, gene description, gene ontology, protein domain, and expressing tissue (Figure 2A). Alternatively, the user can also look up the proteins of interest in the protein table, which includes all the proteins analyzed in the interface. All the proteins that match the query key word will be shown with a plus “”+”" sign in front (Figure 2B). Detailed information of each protein can be shown by clicking on the “”+”" sign (Figures. 3 and 4). Note that the information page of each protein is composed of three sections (“”Genome Comparison Statistics”", “”Multiple

Sequence Alignments”", and “”Protein Interactions”"). By default only the first section will be deployed when the page is shown. The user can deploy the other two sections PF-6463922 nmr by clicking the “”+”" sign before https://www.selleckchem.com/products/Fludarabine(Fludara).html each section. The user can further refine the search by submitting a second key word, or return to the homepage and start a new search. For each protein of interest, CAPIH shows the statistical pie diagram of species-specific

variations in the “”Genome Comparison Statistics”" section (substitutions in light blue, GDC-0994 concentration Indels in purple, and PTMs in green color; Figure 3A). For substitutions and indels, the diagram gives species-specific variations in amino acid sequences, InterPro-predicted protein domains, CDSs, 3′UTR, and 5′ UTR (in the top-down direction). Each filled block represents 10 variations. That is, 10 nucleotide substitutions (for CDS and UTRs), amino acid changes (for amino Selleckchem Rucaparib acid and IPR domains), indels, or PTMs. For example, 12 species-specific changes will be shown as 2 filled blocks in the graph. However, if the number of species-specific changes exceeds 40, only 4 filled blocks will be shown (Figure 3A). Note that nucleotide substitutions in coding regions do not necessarily cause amino acid substitutions, whereas indels do. Also note that one indel event may affect more than one amino acids. Therefore, the total numbers of indels and nucleotide substitutions in CDS do not necessarily

equal the number of amino acid changes. Figure 2 (A) The query schemes of CAPIH. (B) All the proteins that match the query key word will be shown with a plus “”+”" sign in front. Detailed information of each protein can be shown by clicking on the “”+”" sign. Figure 3 (A) Statistics of species-specific changes in different regions. Each filled block represents ~10 species-specific genetic changes. AA: amino acid; IPR: Interpro-predicted protein domain; CDS: coding sequence; 3/5 UTR: 3′/5′ untranslated regions. (B) Multiple amino acid sequence alignment wherein species-specific changes (PTMs, and substitutions) and InterPro domains are shown in colored boxes. Indels are not color-shaded. The colors can be shown or hidden by checking the boxes in the “”Feature Settings”" panel.

Branch AD: A good antisense molecule is hard to find. Trends Biochem Sci 1998, 23:45–50.PubMedCrossRef 15. Ciardiello F, Bianco R, Damiano V, De Lorenzo S, Pepe S, De Placido S, et al.: Antitumor activity of sequential treatment with topotecan and anti-epidermal growth factor receptor monoclonal antibody

C225. Clin Cancer Res 1999, 5:909–916.PubMed 16. Hunt CR, Dix DJ, Sharma GG, Pandita RK, Gupta A, et al.: Genomic Instability and Enhanced Radiosensitivity in Hsp70.1- and HSP70.3-Deficient Mice. Mocecular and Cellular Biology 2004, 24:899–911.CrossRef 17. Horky M, Wurzer G, Kotala V, Anton M, Vojtesek B, JiriVcha , Wesierska-Gadek Jozefa: Segregation of nucleolar components coincides with caspase-3 activation in cisplatin-treated HeLa cells. J Cell Sci 2000, 114:663–670. selleck 18. Ma Nan, Matsunaga Sachihiro, Takata Hideaki, Ono-Maniwa NSC23766 mw Rika, Uchiyama Susumu, Fukui Kiichi: Nucleolin functions in nucleolus formation and chromosome congression. J Cell Sci 2007, 120:2091–2105.PubMedCrossRef Competing interests The authors declare that they have no competing interests. Authors’ contributions

JX is responsible for experiment design and perform as well as data analysis. KW is designed the anti-sense oligos. XZ is responsible for data selleck screening library analysis guide. DH is responsible for IHC staining. YQ, and XZ participate design and coordination of the experiment. YQ is responsible for designing the experiment and writing the paper. All authors read and approved the heptaminol final manuscript.”
“Background Drug resistance poses a significant challenge to achieving clinical control of pancreatic

cancer. Resistance to chemotherapy frequently results in disease relapse and tumor recurrence, leading to shorter survival times for patients with pancreatic cancer than those with other gastrointestinal cancers. Elimination or minimization of drug resistance will improve our ability to control pancreatic cancer and increase patient survival. However, there are multiple etiologies for drug resistance, and they are not well understood. PKCα is a classic member of the protein kinase C family, and some studies have demonstrated an association between PKCα and drug resistance in human cancers [1, 2]. PKCα-associated drug resistance is likely mediated by P-gp, which is encoded by the multidrug resistant gene 1 (MDR1) gene. P-gp belongs to the ATP-binding cassette (ABC) transporter superfamily, and it functions as a drug efflux pump in multidrug resistance. PKCα modulates the function of P-gp via phosphorylation of the P-gp intracellular domain or activation of the MDR1 gene promoter. Curcumin [3], hammerhead ribozymes [4], and antisense oligonucleotides [5], which all target P-gp, have been shown to improve the efficacy of chemotherapy in a variety of cancer models. However, the molecular mechanism of PKCα/P-gp-initiated drug resistance in pancreatic cancer is poorly understood. There are three subtypes of transforming growth factor-β in humans: TGF-β1, TGF-β2, and TGF-β3.

Finally sedoheptulose-7-bisphosphate and glyceraldehydes-3-P can be converted to ribose-5-P and xylose-5-P using transketolase again. While enzyme assays have not been carried out to determine the substrate specificity of ATM Kinase Inhibitor datasheet fructose-1,6-bisphosphate aldolase and PPi-dependent 6-phosphofructokinase in C. thermocellum, it is tempting to propose a similar hexose-to-pentose conversion mechanism. Pyruvate formation from phosphoenolpyruvate While

most organisms convert phosphoenolpyruvate (PEP) to pyruvate via pyruvate kinase, producing ATP from ADP [78], sequence https://www.selleckchem.com/products/a-1210477.html homology-based annotation has not revealed the presence of a pyruvate kinase in C. thermocellum. However, several alternative proteins are expressed that may result in a tightly regulated pathway node (Figure  3a, Additional file 4) leading to pyruvate synthesis. Phosphoenolpyruvate can be reversibly converted to pyruvate via pyruvate phosphate dikinase (PPDK), producing ATP and Pi from AMP, and PPi, or using PEP synthase (PEPS) which produces

ATP and H2O from AMP, and Pi. While PPDK was expressed at high levels in exponential phase, PEPS was not (RAI = 3.32 vs 0.11). Alternatively, PEP carboxykinase (PEPCK), which was also highly expressed (RAI = 5.98), can convert PEP to oxaloacetate while generating ATP. Oxaloacetate can subsequently be converted MCC950 either directly to pyruvate via oxaloacetate decarboxylase (OAADC), or indirectly through malate via malate dehydrogenase (MDH) and malic enzyme (ME), all of which were also highly expressed. High NADH-dependent MDH and NADP+-dependent ME activities (Rydzak et al., unpublished) suggest that MDH/ME facilitate transhydrogenation from NADH to NADP+, resulting

in NADPH for biosynthesis, or potential H2 or ethanol synthesis [55]. Interestingly, all the enzymes in this node, with the exception of PEPS and MDH, decrease ~1.4 to 1.6-fold during stationary phase, generally consistent with reported mRNA profiles of cellulose grown cells [37]. Regulation of carbon flux through this node cannot be simply attributed to changes in protein expression level Inositol monophosphatase 1 since ME has been shown to be regulated allosterically. Ammonia has been reported as an activator of ME in C. thermocellum, and thus, transhydrogenation of NADH to NADP+ via MDH and ME is only allowed when sufficient NH4 + is present for biosynthesis [79]. More recently, PPi inhibition of ME has been demonstrated (Taillefer and Sparling, unpublished). While this may be counterintuitive given that high levels of PPi are present in the cell during rapid growth and biosynthesis, which in turn increases the demand for NADPH, the regulatory aspects with MDH and ME are tightly knit with PPDK, which either uses PPi during glycolysis, allowing for NADPH formation using MDH and ME, or produces PPi during carbon starvation and gluconeogenesis, inhibiting the MDH/ME pathway accordingly to the cells NADPH demand.

5 months. Conclusions FOLFIRI appears an effective and safe treatment option for pretreated metastatic gastric cancer patients. However, second-line chemotherapy comparative trials are needed to better check details define the role of FOLFIRI in gastric cancer (e.g. versus monochemotherapy). Acknowledgements We thank Tania Merlino for technical assistance. References 1. Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D: Global cancer statistics. CA Cancer J Clin 2011, 61:69–90.PubMedCrossRef 2. Cervantes A, Roda D, Tarazona N, Roselló

S, Pérez-Fidalgo JA: Current questions for the treatment of advanced gastric cancer. Cancer Treat Rev 2013, 39:60–67.PubMedCrossRef 3. Glimelius B, Ekström K, Hoffman K, Graf W, Sjödén PO, Haglund U, Svensson C, Enander LK, Linné T, Sellström H, Heuman R: Randomized comparison between Captisol datasheet chemotherapy plus best supportive care with best supportive care in advanced gastric cancer. Ann Oncol 1997, 8:163–168.PubMedCrossRef 4. Murad AM, Santiago FF, Petroianu A, Rocha PR, Rodrigues MA, Rausch M: Modified therapy with 5-fluorouracil,

doxorubicin, and methotrexate in advanced gastric cancer. Cancer 1993, 72:37–41.PubMedCrossRef 5. Pyrhönen S, Kuitunen T, Nyandoto P, Kouri M: Randomised comparison of fluorouracil, epidoxorubicin and methotrexate (FEMTX) plus supportive care with supportive care Nepicastat alone in patients with non-resectable gastric cancer. Br J Cancer 1995, 71:587–591.PubMedCrossRef 6. Van Cutsem E, Moiseyenko VM, Tjulandin S, Majlis A, Constenla M, Boni C, Rodrigues A, Fodor M, Chao Y, Voznyi E, Risse ML, Ajani JA: V325 Study Group. Phase III study of docetaxel and cisplatin plus fluorouracil compared with cisplatin and fluorouracil as first-line therapy for advanced gastric cancer: a report of the V325 Study Group. Dimethyl sulfoxide J Clin Oncol 2006, 24:4991–4997.PubMedCrossRef 7. Koizumi W, Narahara H, Hara T, Takagane A, Akiya T, Takagi M, Miyashita K, Nishizaki T, Kobayashi

O, Takiyama W, Toh Y, Nagaie T, Takagi S, Yamamura Y, Yanaoka K, Orita H, Takeuchi M: S-1 plus cisplatin versus S-1 alone for first-line treatment of advanced gastric cancer (SPIRITS trial): a phase III trial. Lancet Oncol 2008, 9:215–221.PubMedCrossRef 8. Bang YJ, Van Cutsem E, Feyereislova A, Chung HC, Shen L, Sawaki A, Lordick F, Ohtsu A, Omuro Y, Satoh T, Aprile G, Kulikov E, Hill J, Lehle M, Rüschoff J, Kang YK, ToGA Trial Investigators: Trastuzumab in combination with chemotherapy versus chemotherapy alone for treatment of HER2-positive advanced gastric or gastro-oesophageal junction cancer (ToGA): a phase 3, open-label, randomised controlled trial. Lancet 2010, 376:687–697.PubMedCrossRef 9.