The mammalian two-hybrid system MAPPIT allows the detection of protein-protein interactions in intact human cells. We developed a random mutagenesis screening strategy based on MAPPIT to detect mutations that disrupt the interaction of one protein with multiple protein interactors simultanously. The strategy was used to detect residues of the human cytidine deaminase Apobec3G that are important for its homodimerization and its interaction with the HIV-1 Gag and Vif proteins. The strategy is able to identify the previously described head-to-head homodimerization interface in the N-terminal domain of Apobec3G. Our analysis further detects two new potential interaction surfaces in the N-and C-terminal domain of Apobec3G for interaction with Vif and Gag or for Apobec3G dimerization. To reveal how proteins interact in a protein complex, the detailed structure of the complex is ideally determined via crystallography methods or NMR. However, the structure determination of protein complexes remains challenging and the number of complex structures lags far behind the number of known protein interactions MAPPIT is a two-hybrid method based on reconstitution of cytokine receptor signaling for the detection of protein-protein interactions Apobec3G contains two characteristic cytidine deaminase (CDA) domains Here, we tested the effect of mutations in the dimerization interface on the interaction between Apobec3G and Gag. We present a new strategy to screen for mutations that disrupt a protein-protein interaction based on random mutagenesis in combination with MAPPIT. The strategy allows evaluating the effect of many random mutations in one protein on interaction with multiple interaction partners in parallel. Using this strategy, we identified regions in both Apobec3G domains that are involved in the interaction of Apobec3G with Apobec3G, Vif and Gag.We previously used MAPPIT to demonstrate the importance of the head-to-head interface of the Apobec3G N-terminal domain for the Apobec3G-Apobec3G and the Apobec3G-Vif interaction MAPPIT allowed the detection of the interaction of the Apobec3G bait with Gagpol and Gag, which originates from the Gagpol precursor polyprotein, coupled as prey. The Gagpol prey led to a robust MAPPIT signal, while the Gag prey resulted in a modest but reproducible MAPPIT signal  and 2. AWe showed before that four mutations at the edge of the head-to-head interface specifically affected the Apobec3G-Vif interaction: D128K and P129A disturbed the interaction with Vif whereas a T32Q and a K99D mutation increased the MAPPIT signal To investigate the role of the N- and C-terminal domains of Apobec3G in the interaction with Apobec3G, Vif and Gag, the N- and C-terminal domains of Apobec3G were coupled as MAPPIT baits. The interaction of these baits with four different MAPPIT preys containing respectively codon optimized Vif SLQ144-146AAA, wild type Apobec3G, Gagpol and SH2-Bβ, was tested. The SLQ144-146AAA mutation in the Vif prey prevents proteasomal degradation of the Apobec3G bait, and results in a higher MAPPIT signal While most reports show the interaction of Vif with the Apobec3G CD1 domain Our mapping of binding sites in Apobec3G via mutagenesis was hitherto restricted to the predicted head-to-head interface in the N-terminal domain of Apobec3G. To extend this mapping to the entire Apobec3G protein, we developed a method to screen for mutations that disrupt protein-protein interactions via a combination of random mutagenesis and MAPPIT. In this method, we randomly mutate the MAPPIT bait insert via error prone PCR and test the interaction of the different mutants with several preys by co-transfection of HEK293T cells in 384-well format .To screen for mutations in Apobec3G that decrease the interaction with Apobec3G, Vif or Gag, two slightly overlapping fragments of Apobec3G (amino acids 1 to 178 and amino acids 175 to 384) were mutated separately. 1152 potential bait mutants from each mutagenesis were isolated. The interaction of these 2304 potential bait mutants with four different MAPPIT preys containing respectively codon optimized Vif SLQ144-146AAA, wild type Apobec3G, Gagpol and SH2-Bβ, was tested.In a proof of principle experiment, the capability of the strategy to distinguish between the interaction of the Vif prey with the wild type and the W127A mutated Apobec3G MAPPIT bait, was examined. As shown in In the random mutagenesis MAPPIT screen, each transfection was performed in triplicate and the relative MAPPIT signal of the mutants compared to six control wild types was calculated as described in the Surprisingly, the relative MAPPIT signal of the SH2-Bβ prey for wild type Apobec3G is lower than for many of the Apobec3G bait mutants including the W127A mutant. Although this suggests a lower expression level for wild type Apobec3G, Western blot analysis confirms the proper expression of the wild type and mutant Apobec3G baits . The lucIn the N-terminal domain, 81 different single amino acid substitutions were identified that affect the MAPPIT signal with one or more of the preys  corresponds roughly to the head-to-head interface found in Apobec2, although the contacts are quite different. A W211A/R213A/R374E mutation in this interface abolishes the Apobec3G deaminase activity and its antiviral effect A second smaller interface (604 Å2) in the crystal structure of the Apobec3G C-terminal domain contains residues of the β2 strand and the α2 helix. This interface contains two zinc ion binding sites coordinated by H248, H250, C261 and D264. A H248A/H250A mutation does not interfere with Apobec3G oligomerization in vivo In the crystal structure, Apobec2 dimerizes via direct interactions between the β2 strands. A similar dimerization was predicted between the N-and C-terminal domain of Apobec3G, in a model where the β2 strand of the N-terminal domain interacts with the β2 strand of the C-terminal domain. The discontinuous β2 strand in the different structures of the C-terminal catalytic domain seems to prohibit this mode of dimerization Our MAPPIT assays are set up to detect clusters of mutations that affect the interaction in this assay, in order to delineate possible interaction interfaces. However, the effect of a mutation in our (and other) interaction assays should not be extrapolated automatically to an effect of the mutation on biological activity. A F268N+K270E mutation in Apobec3G affects the interaction with a Vif prey in MAPPIT and in co-immunoprecipitation. The same mutation had no effect on degradation of Apobec3G by Vif. Different assays may have different sensitivities towards a mutation, as illustrated by several examples of differing results in studies of Apobec3G. Huthoff et al. showed that mutations of Apopbec3G Y124 toW127 do not affect degradation by Vif In summary, we developed a new strategy to detect random mutations that disrupt a protein-protein interaction in intact human cells. The strategy was able to detect the head-to-head interface for Apobec3G dimerization and demonstrates its role in interaction with Vif and Gag. Moreover, a new area in the C-terminal domain that is important for the interaction of Apobec3G with Vif and Gag was detected. Our MAPPIT analyses thus identified four potential interaction surfaces in Apobec3G: a head-to-head interface, a Vif binding site and an RNA binding site in the N-terminal domain, and a binding site that is involved in binding of Vif and Gag in the C-terminal domain. The random mutagenesis MAPPIT strategy is broadly applicable and offers the advantage that the effect of many mutations of a protein on interaction with multiple interaction partners can be analyzed in parallel. Our approach thus forms a new tool that can help to gain insight in the structure of protein complexes or identify interesting mutants for functional studies.All constructs used in this report were generated by standard PCR- or restriction based cloning procedures and used primers are listed in The basic MAPPIT prey construct, pMG2, was generated in the pMET7 vector and contains a part of the gp130 chain in duplicate as previously described www.atcc.org) were cultured in a 8% CO2 humidified atmosphere at 37°C and grown in Dulbecco's modified Eagle's medium (Invitrogen) with 10% fetal calf serum (Cambrex Corp.). The transfection procedure for 6-well plates was previously described HEK293T cells  with detection via the Odyssey imager (LI-COR). Expression of the Apobec3G bait was detected using a rabbit anti-Apobec3G antibody (Sigma prestige antibodies) and a goat anti-rabbit peroxidase conjugate (Jackson Immunoresearch) with detection of chemiluminescence  via autoradiography. V5-tagged MAPPIT baits were detected using a mouse monoclonal anti-V5 tag monoclonal antibody (Invitrogen) and anti-mouse peroxidase conjugate (KPL) as described above.HA-tagged Apobec3G was co-expressed with the MAPPIT prey for VifOptLQ, Gag or SVT in HEK293T cells, by Calcium phosphate transfection as described above. Two days after transfection, cells were lysed with 50 mM Tris-HCl pH 7.5, 125 mM NaCl, 5% glycerol, 0.2% NP40 and Complete Protease Inhibitor Cocktail without EDTA (Roche). The lysates were cleared by centrifugation and incubated for 3 hours with 20 µl monoclonal anti-flag M2 agarose beads (Sigma) to precipitate the MAPPIT preys. The beads were washed four times with 1 ml lysis buffer. The precipitated MAPPIT preys and co-immunoprecipitated Apobec3G were released from the beads by incubation with 100 µg/ml synthetic FLAG peptide for 30 min at 37°C. After centrifugation of the beads, co-immunoprecipitated Apobec3G in the supernatant was detected by Western blot using rat anti-HA monoclonal antibody 3F10 (Roche) and fluorescent goat anti-rat antibody (LI-COR IRDye 800CW) with detection via the Odyssey imager (LI-COR).Apobec3G from the pCEL-Apobec3G-GFP bait is randomly mutated using the GeneMorph® II Random Mutagenesis Kit (Agilent Technologies). The N-terminal part of Apobec3G (bp 1−533) was mutated via error prone PCR of pCEL-Apobec3G-GFP with primer pair 14 from which the forward primer contains a SacI- and the reverse primer a SspI-recognition site. The total amount of plasmid DNA added to the reaction was 200 ng and 15 PCR cycles were performed. After digestion with SacI and SspI, the PCR product was introduced in the SacI-SspI opened pCEL-Apobec3G-GFP vector. For the random mutagenesis PCR of the C-terminal part (bp 522−1152), forward primer 15 and reverse primer 15 with respectively a BstBI- and StuI-site, were used. For this reaction, the amount of start DNA was 1000 ng and the number of cycles was 10. The resulting PCR fragments were digested with BstBI and StuI and ligated in the BstBI-StuI opened pCEL-Apobec3G-GFP vector. After transformation of the randomly mutated Apobec3G bait plasmids in E. coli, 1152 different colonies were picked for both mutagenesis reactions and these 2304 colonies were grown overnight in 2xYT medium in 32 96-deepwell blocks. Row A−F of each deepwell block was inoculated with 72 different mutant colonies, row G was inoculated with 12 different wild type pCEL-Apobec3G-GFP colonies, row H was inoculated with 12 different pCEL-Apobec3G W127A-GFP mutant colonies. Automated miniprep of these 32 deepwell blocks was performed using the Nucleospin® Robot-96 plasmid kit and a Freedom EVO 100 platform (Tecan). The DNA concentration was automatically measured using a Magellan UV spectrophotometer (Tecan) and diluted to 6 ng/µl.One day before transfection, 3000 cells per well were seeded in black 384-well plates. Cells were transfected overnight with 1.5 ng bait plasmid, 6.5 ng prey plasmid and 4 ng of the pXP2d2-rPAP1-luciferase reporter per well. Automated transfection via the calcium phosphate precipitation procedure was executed by a Freedom EVO 200 platform (Tecan). 8 wells were transfected with the same bait/prey mixture. Thus, one 384-well plate contained bait/prey mixtures of half of a 96-well bait DNA plate  in combination with one prey. The day after transfection, 4 of the 8 wells were stimulated overnight with 10 ng/ml hEpo, the other 4 wells were left unstimulated, so that all bait/prey combinations were assayed in quadruplicate in both unstimulated and ligand stimulated conditions. After another 24 h, luciferase activity in cell lysates was measured using an EnSpire plate reader (PerkinElmer).The MAPPIT signal was determined as fold induction of luciferase activity upon Epo stimulation, by dividing the luciferase activity of the 4 Epo stimulated wells by the luciferase activity of the 4 unstimulated wells.The MAPPIT signal of each bait mutant was compared with the MAPPIT signal of the six wild type baits on the same 384-well plate to calculate a normalized MAPPIT signal. The normalized MAPPIT signal is the result of the fold induction of the mutant divided by the median of the fold induction of the six wild types controls on that plate. The 384-well transfections were repeated three times. For each mutant, we calculated a relative MAPPIT signal. The relative MAPPIT signal is the median of the normalized MAPPIT signals of a mutant in three transfection experiments multiplied by 100. The relative MAPPIT signal of a mutant is expressed as percentage of wild type.http://www.vibgeneticservicefacility.be/). The sequences were aligned to the pCEL-Apobec3G-GFP protein sequence using NCBI BLASTx Thresholds were determined for the relative MAPPIT signal, as described in the results section. Mutations that gave rise to a relative MAPPIT signal above (SH2-Bβ prey) or below  these thresholds were selected for sequencing of the Apobec3G mutant. Sequences were determined on Applied Biosystems 3730XL DNA Analyzers at the VIB Genetic Service Facility  and the transmembrane and intracellular part a leptin receptor that lacks STAT3 recruitment sites. In the absence of an interacting prey, the bait is unable to signal via STAT3. The prey protein is fused to a duplication of a fragment of the gp130 receptor chain carrying tyrosine motifs that recruit STAT3 after phosphorylation by JAK2. Interaction between bait and prey in combination with stimulation with Epo thus leads to functional complementation of JAK2-STAT3 signaling and induction of a luciferase reporter.(TIF)Click here for additional data file.Figure S2A Gag 1–377 prey does not interact with the Apobec3G bait in MAPPIT. The interactions of an Apobec3G bait with preys for full-length Gag and for Gag 1–377 is determined via MAPPIT. The data are expressed as fold induction of luciferase activity after stimulation with Epo. The SH2Bβ prey and SVT prey are used as a positive and negative control. The MAPPIT signal for the Gag1–377 prey drops to the level of the negative SVT prey control (dotted arrow).(TIF)Click here for additional data file.Figure S3Expression control of prey and bait proteins. Western blot analysis of expression of the MAPPIT preys (A) and of selected Apobec3G MAPPIT baits (B), as described in (TIF)Click here for additional data file.Figure S4Effect of mutations on the MAPPIT signal with the SH-2Bβ prey. The luciferase activity before and after Epo stimulation with the SH2-Bβ prey is compared for different baits. This is compared to the MAPPIT interaction of these baits with the Apobec3G prey. A: Luciferase activity after Epo stimulation with the SH2-Bβ prey. B: Luciferase activity without Epo stimulation with the SH2-Bβ prey. C: Fold induction of luciferase activity with the SH2-Bβ prey. D: Fold induction of luciferase activity with the Apobec3G prey. All four baits show a similar luciferase activity with the SH2-Bβ prey after Epo stimulation (A). Only the wild type Apobec3G bait and the Q237K+R238C Apobec3G bait interact with the Apobec3G bait (D). Both baits show a high luciferase activity with the SH2-Bβ prey when not stimulated (B), leading to a lower fold induction of luciferase activity for these two baits with the SH2-Bβ prey (C). In contrast, the F268N+K270E mutant and the negative control bait (receptor without bait) do not interact with Apobec3G (D). These two baits have a low luciferase activity SH2-Bβ prey without Epo stimulation (B) and thus have a high fold induction of luciferase activity after Epo stimulation (C). The capability of an Apobec3G bait to interact with the Apobec3G prey seems to parallel its capability to induce luciferase activity with the SH2-Bβ prey in the absence of Epo stimulation.(TIF)Click here for additional data file.Figure S5Effect of mutations in a putative zinc-binding motif and of combined mutations in the C-terminal domain. Interactions between different mutant Apobec3G baits and different MAPPIT preys were determined via MAPPIT. The data are expressed as fold induction of luciferase activity after stimulation with Epo. H248A and C261A mutations have only modest effects on any of the interactions. The H250A mutant Apobec3G bait shows no MAPPIT signal with the SH2-Bβ prey, indicating that the bait is not expressed, which is in line with the Western blot analysis (supporting (TIF)Click here for additional data file.Figure S6Effect of the F268N+K270E mutation on co-immunoprecipitation of Apobec3G with MAPPIT preys for Gag and VifOptSLQ. HA-tagged Apobec3G or its F268N+K270E mutant is co-expressed with the MAPPIT preys for Gag and VifOptSLQ in HEK293T cells. After immunoprecipitation of the prey, with anti-FLAG agarose, the co-precipitated HA-tagged Apobec3G is determined via Western Blot. The asterisk indicates the HA-Apobec3G bands, the prey bands are indicated with an arrowhead. A. The F268N+K270E mutant  co-immunoprecipitates less efficiently with the Gag prey than Wild-type HA-Apobec3G . B. The F268N+K270E mutant  co-immunoprecipitates less efficiently with the VifOptSLA prey than Wild-type HA-Apobec3G .(TIF)Click here for additional data file.Table S1Primers used to obtain the described DNA constructs.(DOC)Click here for additional data file.Table S2Random single-residue mutations identified in the N-terminal CDA domain. Column 1 shows the mutations. The relative solvent accessibility of the mutated residue is shown in column 2. The relative MAPPIT signal (% of WT) of the bait mutants for interaction with the Vif, Apobec3G,Gagpol and SH2-Bβ preys is given in columns 3–6.(DOC)Click here for additional data file.Table S3Random single-residue mutations identified in the C-terminal CDA domain. Column 1 shows the mutations. The relative solvent accessibility of the mutated residue is shown in column 2. The relative MAPPIT signal (% of WT) of the bait mutants for interaction with the Vif, Apobec3G,Gagpol and SH2-Bβ preys is given in columns 3–6.(DOC)Click here for additional data file.


Cartilaginous metaplasia of vascular smooth muscle (VSM) is characteristic for arterial calcification in diabetes and uremia and in the background of genetic alterations in matrix Gla protein (MGP). A better understanding of the molecular details of this process is critical for the development of novel therapeutic approaches to VSM transformation and arterial calcification.This study aimed to identify the effects of bioflavonoid quercetin on chondrogenic transformation and calcification of VSM in the MGP-null mouse model and upon TGF-β3 stimulation in vitro, and to characterize the associated alterations in cell signaling.Mgp-/- aortae in vivo and during chondrogenic transformation of VSMCs in vitro. Quercetin intercepted chondrogenic transformation of VSM and blocked activation of β-catenin both in vivo and in vitro. Although dietary quercetin drastically attenuated calcifying cartilaginous metaplasia in Mgp-/- animals, approximately one-half of total vascular calcium mineral remained as depositions along elastic lamellae.Molecular analysis revealed activation of β-catenin signaling in cartilaginous metaplasia in Quercetin is potent in preventing VSM chondrogenic transformation caused by diverse stimuli. Combined with the demonstrated efficiency of dietary quercetin in preventing ectopic chondrogenesis in the MGP-null vasculature, these findings indicate a potentially broad therapeutic applicability of this safe for human consumption bioflavonoid in the therapy of cardiovascular conditions linked to cartilaginous metaplasia of VSM. Elastocalcinosis is a major component of MGP-null vascular disease and is controlled by a mechanism different from chondrogenic transformation of VSM and not sensitive to quercetin. In the normal vasculature, the principal function of smooth muscle cells is contraction to regulate blood pressure and blood flow throughout the body . In contRecent mechanistic studies reveal the complexity of phenotypic instability in VSMCs. The literature in this field is extensive and identifies diverse regulators including, but not limited to, growth factors, inflammatory cytokines, calcium-phosphate homeostasis, oxidized phospholipids, retinoic acid and mechanical stress, and involves multiple signaling pathways including MAPK kinases, Rho, Notch, BMP and β-catenin signaling (reviewed in –7).Lineage tracing studies have demonstrated that VSMC-derived hyperproliferative cells play a role in neointimal formation induced by either injury  or atherMgp-/- VSM resulting in the ectopic formation of cartilage in the vessel wall, extensive calcification, and ultimately rupture of the blood vessels soon after birth  in the presence or absence of quercetin (50 µmol/L) or recombinant Dkk1  at 37°C, 5% CO2. Medium was changed twice a week for up to 14 days. Sulfated glycosaminoglycan (GAG) synthesized by cultured VSMCs was detected by fixing them in 4% PFA and staining with 1% Alcian blue (8GX) dissolved in 0.1 N HCl. For quantitative analysis, Alcian blue was extracted with 4 M guanidine hydrochloride and absorbance at 590 nm was measured using an Optima spectrophotometer (PolarStar). Cell density was estimated using WST substrate (Dojindo).To induce chondrogenic transformation, VSMCs were seeded at high density (2.5x10mRNA was isolated using the RNeasy micro kit (Qiagen) and reverse transcription was performed with MaximaRT kit . Quantitative real-time PCR was performed according to the standard protocol with EVA green chemistry in a CFX96 thermocycler (Bio-Rad) using the primers in Aortas were dried at 55°C overnight and then dissolved in 0.1N hydrochloric acid (HCl) overnight. Calcium content was determined biochemically using the Calcium (CPC) LiquiColor kit as measured with o-Cresolphthalein (Stanbio). Calcium content of the aorta was normalized to dry weight of the tissue prior to HCl extraction.Aortic tissue from 5 week old mice was disrupted by rapid agitation in the presence of a stainless steel bead (5 mm mean diameter) and lysis buffer using a TissueLyser . Total RNA was isolated following the RNeasy Fibrous Tissue micro kit protocol (Qiagen) according to the to the manufacturer’s instructions and quantified with NanoDrop spectrophotometer (Thermo Scientific) prior to storage at −80°C. Reverse transcription was performed using 1 µg of RNA according to SA Biosciences’ recommendations using the RT2 First Strand kit. Gene expression analysis was done using the WNT Signaling Pathway PCR Array (PAMM-043), WNT Signaling Targets PCR Array (PAMM-243) and Osteogenesis PCR Array (PAMM-026). ΔΔCt based fold-change calculations were performed using the RT² Profiler PCR Array Data Analysis Template v3.2. In this software standard deviation is calculated for Ct values and not for final fold-changes in expression.The data are presented as mean ± standard error. For experiments containing only 2 groups, significance was determined by comparison using Wilcoxon-Mann-Whitney test. For experiments containing more than 2 groups, Levene’s test was used to determine equality of variance (homoscedasticity) followed by 1-way analysis of variance (ANOVA) and Tukey-Kramer post-hoc analysis for comparison between groups. A p-value of < 0.05 was considered to be statistically significant. *, p <0.05; **, p < 0.01; ***, p<0.001.Mgp-/- mice are characterized by the presence of ectopic cartilage in the tunica media [Mgp-/- aortae. Aortic tissue isolated from newborn, 7- and 30-day old animals was examined. 3 random cross-sections of aortae from each animal were analyzed. The percentage of Ki67-positive proliferating cells was similar between wild-type and Mgp-/- aortae at all ages examined . A number of activating Wnt ligands and transcriptional co-activators of β-catenin signaling such as Ccnd3, Pitx2 and Lef1 are induced in the Mgp-/- aortae (Mgp-/- tissue (with only Wnt3a threshold cycle number being less than 35). In addition, the drastic down-regulation of sclerostin, an inhibitor of Wnt signaling, further indicates activation of this pathway in Mgp-/- arteries . This analysis revealed a higher than 2-fold induction in 50% of the β-catenin target genes in the Mgp-/- aortae with 28 genes showing a statistically significant change  were induced to undergo chondrogenic transformation in high-density micromass cultures stimulated by dexamethasone and TGF-β3 [To determine whether activation of β-catenin signaling directly associates with chondrogenic transformation of VSM, in contrast to being potentially induced by systemic factors in the d TGF-β3 . Within Quercetin has been characterized as a potent inhibitor of β-catenin signaling, and in VSMCs quercetin stabilizes the contractile phenotype . Here weSimilar to its effects on the A10 VSMC line, quercetin significantly reduced GAG deposition by primary mouse aortic VSMCs treated with chondrogenic medium in micromass culture without affecting cell survival as evidenced by unchanged levels of LDH activity in the culture medium . AnalysiMgp-/- and Mgp+/- pups for 2 weeks with dietary quercetin  reduction in total calcium content of Mgp-/- aortic tissue  and anac tissue , althougc tissue .de novo formation of calcifying cartilaginous metaplasia but not reverse calcification already present in 3 week old animals at weaning. Therefore, to affect younger animals we treated newborn Mgp-/- mice with quercetin for 5 weeks (via the lactating moms until weaning and then in the drinking water as described above) and analyzed calcium accrual in these mice compared to Mgp+/- littermates. Quercetin treatment from birth produced a 36.3±1.7% (p<0.01) reduction in total calcium content of Mgp-/- aortic tissue , rendering this parameter similar to that of the control aortae   .Mgp-/- animals, and this increase was significantly attenuated in quercetin-treated Mgp-/- animals . In contrast, β-catenin protein was readily detected by immunofluorescence in the aortae of 5 week old Mgp-/- mice in which foci of alcian blue-positive cartilaginous metaplasia develop in the tunica media . Further, in the quercetin-treated Mgp-/- mice we did not detect any accumulation of β-catenin protein in the vessel media (Mgp-/- + Querc), suggesting that the in vivo morphological effects of quercetin correlated with attenuation of β-catenin signaling. To further clarify the relationship between β-catenin activation and calcifying chondrogenic metaplasia in vivo, we determined the location of cells with active β-catenin within arterial tissue. Nuclear β-catenin protein was detected in chondrocyte-like cells, which appear as rounded cells surrounded by alcian blue positive GAG-rich matrix, in the Mgp-/- aortae , an important regulator of β-catenin in calcifying VSM [Mgp-/- vessels in vivo [The origin of increased β-catenin activity in the ying VSM ,51, accu in vivo  and is i in vivo  it is poMgp-/- blood vessels was only partially alleviated by this flavonoid. About one-half of total mineral remained as deposits along the elastic lamellae, supporting the model that elastocalcinosis may precede chondrocyte-like transformation in VSM [Although quercetin drastically attenuated chondrogenic metaplasia and its calcification, and intercepted chondrogenic transformation of VSM as evidenced by attenuated expression of pro-chondrogenic master regulators Sox9, Twist1, and Runx2, the overall calcium accrual in n in VSM  and consn in VSM ) This fin in VSM , and empMgp-/- aortae quercetin treatment blocked accumulation and nuclear localization of β-catenin protein, supporting a role for this pathway in the phenotypic instability of VSM. While inhibition of β-catenin signaling may be one of the major mechanisms of quercetin action in this system, the possible contribution of other known quercetin activities including anti-inflammatory and anti-oxidative effects cannot be excluded. However, the equally low cell proliferation in Mgp-/- and wild type vessels demonstrated in this study and earlier [Attenuation of chondrogenic transformation in cultured VSMCs by quercetin associated with inhibition of β-catenin signaling, and in the  earlier  indicateMgp-/- mice indicating that dietary supplement of quercetin in breastfeeding females should be considered carefully for possible effects on infants.In conclusion, this study adds to the growing understanding of the complexity of MGP-mediated effects on vascular tissue by adding the β-catenin signaling pathway to the MGP-modulated cellular network that already includes BMP  and Notc


PLOS Computational Biology. I am fully aware of how hard it will be to step into the shoes of Philip Bourne, the Editor-in-Chief of the journal for the last seven years, since it was founded by him, Steven Brenner, and Michael Eisen. We are all deeply appreciative and thankful to Phil for his unique role; and we are grateful that he will be continuing his association with the journal in the future in the role of Founding Editor-in-Chief, aiding and inspiring us and the PLOS Computational Biology community. As a Deputy Editor-in-Chief, I became aware of the true family relationship in the broad PLOS organization and of the devoted and gifted editorial force so nicely fostered by Phil in PLOS Computational Biology. These played a crucial role in helping me decide to accept the invitation to become Editor-in-Chief.With much trepidation I accepted the great honor and responsibility of becoming Editor-in-Chief of PLOS Computational Biology is that it fulfills this mission while maintaining the highest standards of scientific rigor, originality, and clear biological relevance. As Editor-in-Chief I will do my best to have PLOS Computational Biology continue these traditions.I am deeply committed to the underlying principle of free public access to scientific information. In particular, what is truly unique and special about PLOS Computational Biology indicates that the apparent disadvantage is not necessarily there. While they may still need further experimental and computational validation, conclusions based on rigorous computations applied to carefully assembled and curated data, which are backed up by available experimental results, can be as reliable, insightful, and biologically significant as those based on experiments.Computational biology is often perceived as a single field; this however is not the case. Like experimental biology, computational biology is enormously broad; the only distinction from experimental biology is the means. This has disadvantages and advantages: the main disadvantage is that conclusions based on computations are often treated by biologists as less conclusive than those based on experiments; the main advantages are that computations allow researchers to analyze vast amounts of data and make testable predications, and they allow researchers to address problems that current experimental methods may not be able to treat. The high quality of papers published in PLOS Computational Biology is broad; it addresses diverse biological problems. We look forward to further expanding its scope through the inclusion of outstanding methods and resource papers, opening up significant new research directions while retaining and enhancing the strong scientific merit of PLOS Computational Biology publications. We further plan on improving the pace of submissions processing. PLOS Computational Biology is recognized by the community as the premier journal in computational biology. We will strive to continue in this tradition.PLOS Computational Biology is tightly associated with the International Society of Computational Biology (ISCB). We cherish and will continue fostering this association. The Society, its meetings, and the journal all have a common goal: enhancing and promoting excellence in computational biology. Outstanding research with clear biological relevance, which leads to fundamental new insights into important biological problems, is the hallmark of future contributions by our community to biology. As the Editor-in-Chief I shall do my utmost to achieve these goals.


Knockdown of β-catenin dramatically suppressed the motility and invasiveness of PC14PE6/LvBr4 cells, indicating β-catenin is involved in controlling metastatic potential. Since β-catenin protein was increased without a significant change in its mRNA levels, the mechanism underlying increased β-catenin stability was investigated. We found that ubiquitin-specific protease 4 (USP4), recently identified as a β-catenin-specific deubiquitinylating enzyme, was highly expressed in PC14PE6/LvBr4 cells and involved in the increased stability of β-catenin protein. Similar to β-catenin knockdown, USP4-silenced PC14PE6/LvBr4 cells showed decreased migratory and invasive abilities. Moreover, knockdown of both USP4 and β-catenin inhibited clonogenicity and induced mesenchymal-epithelial transition by downregulating ZEB1 in PC14PE6/LvBr4 cells. Using bioluminescence imaging, we found that knockdown of USP4 suppressed brain metastasis in vivo and significantly increased overall survival and brain metastasis-free survival. Taken together, our results indicate that USP4 is a promising therapeutic target for brain metastasis in patients with lung adenocarcinoma.Brain metastasis is the most common type of intracranial cancer and is the main cause of cancer-associated mortality. Brain metastasis mainly originates from lung cancer. Using a previously established  Brain metastasis is a main cause of cancer-related morbidity and mortality and occurs in approximately 20–40% of patients with advanced cancers. Lung cancer is one of the most malignant human cancers and is divided into 2 main types: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). SCLC is known to respond better to chemotherapy and radiotherapy; however, NSCLC, which accounts for 80–85% of all lung cancers, is very difficult to treat despite great advances in the development of therapeutics for lung cancerThe canonical Wnt/β-catenin pathway is highly conserved and frequently dysregulated in many cancers. Growing evidence has demonstrated that the Wnt/β-catenin pathway plays a critical role in the development of NSCLC. Several components of the Wnt/β-catenin pathway and β-catenin target genes including c-Myc, cyclin D1, VEGF-A, MMP-7, and survivin are overexpressed in NSCLCCytoplasmic β-catenin is maintained at low levels through ubiquitin-mediated degradation. Ubiquitination/proteasome degradation of β-catenin is initiated by phosphorylation of S45 by casein kinase 1α (CK1α) and subsequently by constitutively active glycogen synthase kinase 3 (GSK3) at S33, S37, and T41. Phosphorylated β-catenin is recognized by E3 ligase, ubiquitinylated, and degraded by the proteasome. In addition to ubiquitination, a deubiquitinating mechanism also plays an essential role in the regulation of β-catenin. Deubiquitinating enzymes (DUBs) remove covalently bound ubiquitin from target proteins and thereby regulate their activity and abundancein vivo brain metastasis of PC14PE6/LvBr4 cells.Through left ventricle (LV) injection of PC14PE6 lung adenocarcinoma cells, we previously isolated brain metastatic cells known as PC14PE6/LvBr4 cellsin vitro brain metastasis model through left ventricle (LV) injection of lung adenocarcinoma PC14PE6 cells, and isolated brain metastatic PC14PE6/LvBr4 cellsZEB1), sex determining region Y-box 9 (SOX9), c-Jun (JUN), cyclin D1 (CCND1), vascular endothelial growth factor A (VEGFA), and endothelin 1 (EDN1), were highly expressed in PC14PE6/LvBr4 cells. It was previously reported that brain metastatic PC14PE6/LvBr4 cells show higher invasiveness than parental PC14PE6 cellsWe established an To investigate the role of β-catenin in the regulation of metastatic potential, PC14PE6/LvBr4 cells were transfected with control (CTRL) or β-catenin-specific siRNA. The expression level of β-catenin was determined by western blot analysis . TransieWe found that β-catenin is highly expressed in PC14PE6/LvBr4 cells, but its mRNA levels were not significantly changed ; thus, wBased on the above results, we found that β-catenin was involved in the metastatic potential of PC14PE6/LvBr4 cells and that USP4 upregulated the expression of β-catenin by deubiquitinylating β-catenin. Therefore, we evaluated the effect of USP4 silencing on the invasive and migratory activities. PC14PE6/LvBr4 cells were transfected with CTRL or USP4-specific siRNA. USP4 was effectively downregulated by transient transfection of specific siRNA . KnockdoXAV939 is identified as a tankyrase inhibitor and reported to selectively inhibit β-catenin-mediated transcription by stabilizing axin, a component of destruction complex for β-catenin. To verify that β-catenin is essential for acquisition of metastatic potential, we tested the effect of XAV939 on β-catenin expression and metastatic potential. PC14PE6/LvBr4 cells treated with XAV939 showed decreased expression of β-catenin; however, USP4 expression was not affected . As expeTo investigate the role of USP4/β-catenin in clonogenicity, PC14PE6/LvBr4 cells were transfected with CTRL or siRNAs targeting USP4 or β-catenin. Transfected cells were seeded into 6-well plates and cultured for 2 weeks. After cells were stained with 0.2% crystal violet, the number of stained colonies was counted. Both siRNAs efficiently downregulated the expression of USP4 and β-catenin  and signThe EMT is known to be a leading step of the metastatic processes. EMT is characterized by the decreased expression of epithelial markers in contrast to increased expression of mesenchymal markers. Since PC14PE6/LvBr4 cells exhibited higher metastatic activities, we examined the mesenchymal characteristics of PC14PE6/LvBr4 cells by comparing E-cadherin levels. We found that E-cadherin expression was decreased in PC14PE6/LvBr4 cells, which resulted from the increased expression of ZEB1, a transcriptional suppressor of E-cadherin . Since Zin vivo. For bioluminescence imaging, PC14PE6/LvBr5-Luc cells were previously establishedin vivo study, we examined the effect of USP4 silencing on the expression of β-catenin and ZEB1. As expected, knockdown of USP4 significantly downregulated the expression of β-catenin . Bioluminescence images were acquired at 22 days post-injection (p < 0.001), suggesting that USP4 promotes the metastatic abilities of lung adenocarcinoma cells.Our results strongly suggest that USP4 plays a critical role in the control of clonogenicity, migration, and invasion. Therefore, we further investigated the function of USP4 in metastasis -catenin  and supp-catenin . Next, wnjection  and quannjection . We alsoCDH2, KIFC1, and FALZ, were identified to be highly associated with lung cancer brain metastasisDCUN1D1 gene, is amplified in several types of cancer as an oncogene and was identified as a molecular marker of lung cancer patients at high risk for brain metastasisST6GALNAC5 , which is overexpressed in brain-trophic, but not in lung- or bone-trophic, metastasized cancer cellsBrain metastasis is associated with the poor prognosis of cancer patients with systemic malignancy and mainly originates from primary lung cancer (40–50%), breast cancer 15–25%), or melanoma (5–20%)11–25%, or Approximately 85% of lung cancer is NSCLC in which the mutation of β-catenin and APS is unusual: however, Wnt/β-catenin signaling is known to be closely associated with lung cancer progression2021Emerging evidence has demonstrated that the ubiquitin/proteasome machinery is a master regulator of the Wnt/β-catenin pathway. Cellular levels of β-catenin are also tightly regulated by phosphorylation-dependent ubiquitination and subsequent proteasomal degradation. 2 main kinases are involved in the phosphorylation of β-catenin: CK1 and GSK3. Prior to GSK3-mediated phosphorylation, a prime kinase CK1 induces the phosphorylation of serine-threonine rich region, and constitutively active GSK3 is able to phosphorylate β-catenin at 2 serine residues. Several β-catenin ubiquitin ligases, including β-transducin repeats-containing proteins28The initial key step of the metastatic process is the EMT. During EMT, epithelial cells acquire mesenchymal characteristics, which confer metastatic potential including motility and invasiveness on cancer cells. The expression of E-cadherin is transcriptionally repressed by several transcriptional suppressors such as ZEB1/2, SNAI1/2, and Twist1/23637in vivo and promoted the overall survival and brain metastasis-free survival. In conclusion, we demonstrated that the USP/β-catenin axis confers metastatic ability to lung adenocarcinoma and is thus a promising target for brain metastatic lung cancer treatment.In the present study, we found that the USP4/β-catenin axis was involved in metastatic potential through USP4-mediated stabilization of β-catenin and that knockdown of USP4 and β-catenin suppressed the metastatic potential including clonogenicity, migration, and invasion, and induced MET by downregulating ZEB1 expression. Luminescence imaging experiments indicated that knockdown of USP4 suppressed brain metastasis in vivo bio-imaging experiments, PC14PE6/LvBr5-Luc cells were generated by transducing pre-made Lentiviral Expression Particles for firefly luciferase  as previously described2 in DMEM  supplemented with 10% fetal bovine serum (FBS) and 1% antibiotic-antimycotic solution .Brain metastatic PC14PE6/LvBr4 cells were previously established through left ventricle (LV) injection of PC14PE6 lung adenocarcinoma cells5 cells/dish and transfected with control (CTRL) or indicated small interfering RNAs (siRNAs) using Lipofectamine2000  according to the manufacturer’s instructions. Control and USP4-targeting siRNAs  were synthesized by ST Pharm . SiRNA for β-catenin was purchased from Santa Cruz Biotechnology . XAV939 was purchased from Sigma-Aldrich and solubilized with dimethyl sulfoxide (DMSO). PC14PE6/LvBr4 cells were treated with 10 μM XAV9393  for 24 h.Cells were plated at a density of 5 × 10For western blot analysis, whole cell lysates were prepared using RIPA buffer containing protease and phosphatase inhibitors . Equal amounts of lysate were separated by SDS-PAGE and transferred to polyvinylidene fluoride membranes . The membranes were blocked and incubated with primary antibodies overnight. After incubation with the appropriate secondary antibodies, membranes were visualized using enhanced chemiluminescence. Antibodies for β-catenin , USP4 , GAPDH , E-cadherin , and ZEB1  were used in this study.To assess mRNA levels, real-time quantitative polymerase chain reaction (RT-qPCR) was performed using the following specific primers: β-catenin, forward: CTTGGACTGAGACTGCTGATCTTG, reverse: CACCAGAGTGAAAAGAACGATAGCTA; USP4, forward: CCTGGGCTCTGTGGACTTG, reverse: TGTTGATTTCGGCTTCATACTC; E-cadherin, forward: CGGGAATGCAGTTGAGGATC, reverse: AGGATGGTGTAAGCGATGGC; ZEB1, forward: AGCAGTGAAAGAGAAGGG, reverse: GGTCCTCTTCAGGTGCCT; SOX9, forward: CCCTTCGTGGAGGAGGCGGA, reverse: GGCCTGCAGCGCCTTGAAGA; JUN, forward: CAGGTGGCACAGCTTAAACA, reverse: GTTTGCAACTGCTGCGTTAG; VEGFA, forward: ATGACGAGGGCCTGGAGTGTG, reverse: CCTATGTGCTGGCCTTGGTGAG; EDN1, reverse: CAAGGAGCTCCAGAAACAGC, reverse: GTGGACTGGGAGTGGGTTTC; GAPDH, forward: TGCACCACCAACTGCTTAGC, reverse: GGCATGGACTGTGGTCATGAG.in vitro wound closure assay, cells were cultured in 12-well plates until a monolayer had formed, and then a scratch was formed using pipette tips. After additional incubation for 24 h, the migrating distance was evaluated under a microscope. For the Transwell migration assay, cells were loaded into upper chamber in FBS-free media and migration was initiated by adding complete FBS-containing media to the lower chamber. Migrated cells were stained using crystal violet and migratory activity was assessed by measuring absorbance. Invasive activity was determined using BD BioCoat™ Matrigel Invasion Chamber Metastatic potential was determined by assessing migratory and invasive activities. To assess migratory activity, a wound closure assay and Transwell cell migration assay  were performed. For the To determine β-catenin protein stability, PC14PE6 and PC14PE6/LvBr4 cells were treated with 20 μg/ml cycloheximide  and harvested at the indicated times. β-Catenin protein levels were determined by western blotting and quantified by image analysis. To assess the effect of USP4 silencing on β-catenin protein stability, transfected cells were treated with 40 μg/ml cycloheximide to stop protein synthesis.For the clonogenicity assay, transfected cells (approximately 300 cells) were plated into a 6-well plate and cultured in complete medium for 2 weeks. After the cells were stained with 0.2% crystal violet, the number of stained colonies was counted from more than 3 independent wells.in vivo, transfected PC14PE6/LvBr5-Luc cells (2 × 105 in 100 μl of HBSS) were directly injected through the left ventricle (LV) of the heart. The body weights of the animals were measured daily, and an autopsy was performed immediately after 25% weight loss. Bioluminescence images were acquired using the IVIS Spectrum imaging system  and the in vivo bioluminescence signal was quantified by measuring the photon flux (photons/s/cm2/steradian) within a region of interest drawn around the bioluminescence signal at the indicated times. Kaplan-Meier curves and p-values for overall survival and brain metastasis-free survival were analyzed in systemic metastasis models.All animal procedures were performed according to the Guide for the Care and Use of Laboratory Animals published by the National Institutes of Health (NIH) and the Animal Experiment Guidelines of Samsung Biomedical Research Institute (SBRI). All animal experiments were approved by the Institutional Animal Care and Use Committee (IACUC) of the Samsung Medical Center (SMC). To examine experimental metastasis How to cite this article: Hwang, S. J. et al. Ubiquitin-specific protease 4 controls metastatic potential through β-catenin stabilization in brain metastatic lung adenocarcinoma. Sci. Rep.6, 21596; doi: 10.1038/srep21596 (2016).


Magnetospirillum gryphiswaldense strain MSR-1 and tested the interaction with cellular elements and anti-neoplastic activity both in vitro and in vivo, with the aim of developing new therapeutic approaches for neoplastic diseases. In vitro experiments performed on Human Colon Carcinoma HT-29 cell cultures demonstrated a strong uptake of MNs with no evident signs of cytotoxicity and revealed three phases in the interaction: adherence, transport and accumulation in Golgi vesicles. In vivo studies were performed on subcutaneous tumors in mice; in this model MNs are administered by direct injection in the tumor volume, then a protocol consisting of three exposures to an AMF rated at 187 kHz and 23kA/m is carried out on alternate days, over a week. Tumors were monitored by Magnetic Resonance Imaging (MRI) to obtain information about MNs distribution and possible tissue modifications induced by hyperthermia. Histological analysis showed fibrous and necrotic areas close to MNs injection sites in mice subjected to a complete thermotherapy protocol. These results, although concerning a specific tumor model, could be useful to further investigate the feasibility and efficacy of protocols based on MFH. Magnetic nanoparticles naturally produced and extracted from bacteria seem to be promising candidates for theranostic applications in cancer therapy.Magnetic nanoparticles (MNPs) are capable of generate heating power under the influence of alternating magnetic fields (AMF); this behaviour recently opened new scenarios for advanced biomedical applications, mainly as new promising tumor therapies. In this paper we have tested magnetic nanoparticles called magnetosomes (MNs): a class of MNPs naturally produced by magnetotactic bacteria. We extracted MNs from  Thermotherapy represents an effective tool for the treatment of many types of tumor but it is strongly hampered by poor specificity of the induced lesion In 1963, the Italian scientist Salvatore Bellini reported the first description of magnetotactic bacteria. This subtype of organisms naturally produces magnetic iron-oxide nanoparticles and uses them as a compass for geomagnetic navigation to search for optimal growth conditions Recently, MNs have been proposed as active agents in hyperthermia for cancer therapy M. gryphiswaldense, is able to internalize iron in ionic state from the environment and to synthesize iron oxide nanoparticles (size range 35-50 nm) of cubic-octahedral shape The bacterial strain considered in the present investigation, As mentioned before, MNs isolated from magnetotactic bacteria develop a high heating effect when exposed to AMF. Preliminary studies prove the possibility of using these MNs as therapeutic agents when delivered in tumors However, data on the therapeutic effect and biological interaction of MNs with living tissues are still scarce, and their toxicity has not been definitively assessed gryphiswaldense with tumor cells was investigated by using Human Colon Carcinoma cells (HT-29). Hyperthermia treatment of colorectal cancer is of particular interest for potential clinical applications: for this purpose we used a protocol that include molecular biology, histology, electron microscopy analysis and magnetic resonance imaging.In the present study, the interaction of MNs extracted from M. in vivo in nude mice. In order to assess the potential usefulness of MNs in magnetic thermotherapy, we monitored, by MRI an experimental model of colon carcinoma before and after the treatment with thermotherapy.The interaction of MNs with tumor cells and their therapeutic potential was also investigated Twenty-two nude homozygote male mice  were maintained under standard environmental conditions  under veterinarian assistance. Animals handling and surgery were performed following a protocol approved by the Animal Care and Use Committee of the University of Verona (CIRSAL), and by the Italian Ministry of Health, in strict adherence to the European Communities Council (86/609/EEC) directives, minimizing the number of animals used and avoiding their suffering.3 were injected with MNs. We observed that usually it was possible to inject a total volume of about 200 µl by using 3 to 4 separate punctures without relevant leakage of fluid from the tumor mass. These findings were then used to design the experimental protocol.In a preliminary study on a limited number of animals, one million HT-29 cells, resuspended in 200 µl of sterile PBS, were subcutaneously injected in the right flank of anesthetized mice. Ten days after inoculation of tumor cells, mice were monitored by MRI to measure the tumor size: animals whose tumor volumes ranged between 0.4 and 0.5 cmA population of n = 22 mice was divided in two groups: control and experimental. The control group (n = 12) was further divided in three subgroups: the first subgroup (n = 4) was administered with 1 mg of MNs diluted in 200 µl of PBS and did not receive AMF exposure. Administration of MNs was performed by direct injection into the tumor mass using an intradermal needle (21G). The second subgroup (n = 4) was exposed to AMF without MNs administration. The third subgroup (n = 4) did receive neither thermotherapy nor MNs administration.The experimental group (n = 10) received 1 mg of MNs diluted in 200 µl of PBS and was exposed to AMF on day 0 (immediately after injection), 2 and 4. The AMF apparatus yield a magnetic field of intensity 23 kA/m (∼29 mT) with a frequency of 187 kHz. These values are very close to those used in human application of hyperthermia All the mice were monitored by MRI at three time points: 24 h, one week and two weeks after MNs administration. The first and second points were chosen to evaluate the physiological distribution of MNs and acute effects induced by MFH inside the neoplastic mass, respectively. The last point was useful to check whether some kinds of alterations do occur after the treatment. Animals were then sacrificed and tumors excised for histological analysis. Three mice died during the first steps of the treatment, probably due to an overdose of anesthetic. Mice were sacrificed by isofluorane overdose and successively by neck dislocation. These methods were performed in according to D.L. 4 March 2014 n°26 of the Italian Ministry of Health.M. gryphiswaldense MSR-1 (DSM6361) purchased from Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH (Germany) was cultured in specific growth medium (optimized during the present study) containing 0.1 g KH2PO4, 0.15 g MgSO4*7H2O, 2.38 g HEPES, 0.34 g NaNO3, 0.1 g yeast extract, 3 g soy bean peptone, and 1 ml EDTA-chelated trace element mixture. The medium contained also 27 mM potassium l-lactate as carbon source and 100 µM of ferric citrate as iron source M. gryphiswaldense dry weight with 50 ml of 50 mM HEPES 4 mM EDTA (pH 7.4) using French-press (1.26 Kbar); 2) centrifugation at 680 g for 5 min to remove non lysated materials; 3) magnetic separation with magnetic column ; 4) MNs were eluted with 10 mM HEPES (pH 7.4), positioned on a scaffold of sucrose (55% w/w in 10 mM HEPES), MNs were centrifuged at 280,000 g for 12 h at 4°C and the pellet was incubated with 10 mM HEPES for 16 h at 4°C to allow for solubilization. After purification, MNs were dried for 5 h using a lyophilizer, irradiated with γ-rays (56 Gy for 84 min) and finally stored at -20°C.The purification of MNs was performed according to the protocol proposed by Grunberg Whole mount bacteria of different samples of MNs, extracted and purified, were fixed with glutharaldehyde 2% in Sorensen buffer pH 7.4 for 2 h, post-fixed in 1% osmium tetroxide in aqueous solution for 2 h, dehydrated in graded concentrations of acetone. At the end of dehydrating process, samples were positioned in a multi-well grid for electron microscopy and observed using an EM10 electron microscope .Specimens were fixed with glutharaldehyde 2% in 0.1 M buffered phosphate, dehydrated in graded ethanol, critical point dried , fixed to stubs with carbon-based adhesive, sputtered with carbon by MED 010 coater , and examined with an XL30 ESEM scanning electron microscope  equipped for Energy Dispersion Analysis of X-Ray (EDAX).Hydrodynamic radius of MNs was determined from a batch of 0,5 mg resuspended in 5 ml of HEPES 10 mM, ultrasonicated for 10 min and filtered using a 450 nm filter. DLS data were obtained using a He-NE 633 nm wavelength laser with a goniometric set of 173° , normalized to unity and reported in logarithmic scale.Magnetic measurements were carried out on powders  using a Quantum Design SQUID MPMS XL-7 magnetometer. The zero field-cooled and field-cooled (ZFC/FC) magnetization curves were obtained for different applied magnetic fields in the temperature range 2–300 K, while the field dependent magnetization measurements were recorded in the range of ±5 T at both 2 K and room temperature.2SO4 and HNO3 and digested using a microwave digestor. The preparation was analyzed by Atomic Adsorption Spectroscopy .A sample containing 6.7 mg of purified, sterilized and lyophilized MNs was exposed to an AMF  for 24 min. The increment of temperature was measured by an infrared camera Flir i7 . MNs were then diluted in distilled water at concentration of: 3 mg/ml, 2 mg/ml, 1 mg/ml, 0.5 mg/ml and exposed to AMF using the same frequency and field strength. In order to estimate the iron content of our nanoparticles, 4 mg of extracted MNs were dispersed in a 1∶3 mixture of H2 plates and incubated at 37°C in humidified air with 5% CO2. Medium, serum and antibiotic mix were purchased by GIBCO, Life Technologies, USA. When at confluence, cells were treated with trypsin-EDTA 1% , harvested and centrifuged at 1200 rpm for 5 min. The supernatant was discarded and cells pellet was resuspended in 1 ml of complete medium, placed in 75 cm2 plates and incubated at 37°C and 5% of CO2 until 80% confluence was detectable.Human Colon Carcinoma cells (HT-29) purchased by ATCC , were cultured in Dulbecco's Modified Eagle Medium (DMEM) with 10% of Fetal Bovine Serum (FBS) and 1% of a mix of penicillin/streptomycin 1∶1, in 25 cm3 cells per well in 96-well plates and incubated at 37°C in a mixture of air and 5% CO2. After 24 h, the medium was replaced with fresh medium containing 1, 0.5 and 0.2 mg/ml of sterilized MNs, respectively. After 6, 12 and 24 h of incubation, 10 µl of MTT solution  was added to each well. Plates were then incubated for additional 4 h . After the incubation time, plates were removed from the incubator and formazan crystals formed by the living cells were dissolved in 100 µl of dimethyl sulfoxide . The multiwell was placed into a microplate reader  for the measurement of absorbance at 570 and 630 nm. Four measurements of optical density (OD) were recorded for each sample and cell viability (%) was calculated with the following equation: CV% = (ODsample/ODcontrol) • 100.The cytotoxicity of MNs versus HT-29 cells was assessed by the loss of cells viability using 3--2,5-diphenyltetrazolium bromide) (MTT) test. Cells were plated at a density of 8*105 cells was placed in specific glasses multiwell for optical microscopy  with 1 ml of growth medium. Cells were incubated at 37°C in humidified air with 5% CO2 for 24 h. The growth medium was then discarded and replaced with fresh medium added with MNs at different concentrations: 1 mg/ml, 0.5 mg/ml, 0.2 mg/ml. Cells were incubated as previously described for 6 h, 12 h and 24 h. At each time point, the growth medium was discarded and cells were washed with 1 ml of 1X sterile phosphate buffer saline . Cells were fixed with 1 ml of 4% buffered formalin  for 30 min at room temperature. Once formalin was discarded, cells were double stained: Prussian Blue to visualize MNs and Nuclear Fast Red  to visualize nuclei. HT-29 samples were observed at 10X, 20X and 40X optical magnification using an Olympus microscope  equipped with Image ProPlus software .A plate containing 2*102 in 3 ml of growth medium. After 24 h, cells were fixed with glutaraldehyde 2% in Sorensen buffer pH 7.4 for 2 h, then post-fixed in 1% osmium tetroxide (OsO4) in aqueous solution for 2 h, and finally dehydrated in graded concentrations of acetone. At the end of dehydrating process, glasses were stained with lead citrate and observed using a XL30 ESEM scanning electron microscope .HT-29 cancer cells were plated on a 2.4 cm culture glass, positioned on the bottom of 3.5 cm Petri dishes and incubated at 37°C in humidified air with 5% of CO2 and T2* weighted images were acquired to detect the tumor and the presence of MNs respectively. T2weighted images were acquired using a RARE 3D sequence with TR  = 1200 ms, TEeff = 47.5 ms, FOV = 5×2.5×2.5 cm3, NEX  = 1, MTX  = 256/128/32, Slice Thickness  = 0.78 mm. T2*weighted images were acquired using a FLASH gradient echo sequence with TR  = 400 ms, TE  = 4.4ms, flip angle  = 10°, FOV  = 5×2.5 cm, NEX  = 2, MTX  = 256/128, NSLICES  = 8, Slice Thickness  = 2 mm.MR images were acquired in order to monitor the tumor growth at days 1, 7 and 14 both for control and experimental groups. MRI was performed using a Bruker tomograph operating at 4.7 T, equipped with an actively shielded gradient insert  having a maximum gradient strength of 40 G/cm. Animals were placed prone in a heated bed and a 3.5 cm i.d. birdcage coil was used to acquire the MR signal. TAfter the last MRI acquisition, animals were sacrificed and tumors were excised, washed with PBS 0.1 M and fixed with 10% buffered formalin for 4 h. Afterwards, samples were dehydrated with increasing concentration gradient of alcohol from 70% to 100% and then with xylene for final processing. Tissues were embedded in paraffin and sections of 5 µm were obtained and dried at 37°C for 24 h. Sections were stained with Prussian blue and Nuclear Fast Red (Bioptica) to visualize iron nanoparticles and nuclei respectively.gryphiswaldense. The cubic-octahedral structure of crystals (mean Feret's diameter of iron core  = 42±9 nm) and the surrounding membrane  upon application of AMF for 24 min , when incubated for varying time periods with HT-29 cells, do not show statistically significant negative effects  on cell viability at any dosage. The results are reported in Thermal images were acquired in each mouse during the exposure to AMF by using an infrared camera. Temperature increments ranging between 2 and 3°C were observed in tumors treated with MNs. On the other side, negligible variations of thermal maps were recorded in tumors exposed to AMF that did not receive MNs injection.2-weighted images, most of the neoplastic parenchyma was iso-intense. In the first subgroup of control group (MR images were acquired to monitor the development of tumor mass before and after hyperthermia treatment: as reported in MR images performed after a complete thermotherapy protocol (Histological examinations contributed in elucidating the effect of different treatments. Sections obtained from tumors treated with MNs and thermotherapy showed clear evidence of edematous and necrotic phenomena that were not evident in corresponding sections extracted from the control group (Concerning the persistence of the MNs, histological examinations performed two weeks after administration revealed the presence of MNPs next to the injection site, with spots also detectable in the surrounding parenchyma.A renewed interest in biomedical applications of MNPs has increased considerably over the past years, with MNs attracting widespread attention because of their prospective medical applications either as contrast agents for MRI, as heating mediators for cancer therapy by intracellular hyperthermia or as drug delivery carrier Recent studies on cancer proposed a new potential role of MNs as “theranostics” agents. The therapeutic efficacy of MNPs on mouse mammary carcinoma, glioblastoma, and prostate cancer demonstrated the feasibility and efficacy of this heating method, as well as a very low clearance rate of these nanoparticles from tumors, allowing for longitudinal treatment following a single magnetic fluid injection in vitro and in vivo, of tumor cells with MNs extracted from a strain of magnetotactic bacteria. Among different strains, we chose M. gryphiswaldense for its availability and lack of knowledge about its biological interaction with cells. TEM images on bacteria and isolated nanoparticles confirmed the cubic-octahedric shape and the organization in chains; DLS data, obtained on an homogeneous solution, showed the presence of clusters of about five elements along with a small number of single MNs. Some researches focused on chains length suggesting a relation between this parameter and the thermal properties of MNs. Our findings on ultrastructural analysis show that even though MNs extracted from bacteria are actually organized in chains of several elements as previously reported The aim of this study was to analyze the interaction, both Due to intrinsic limitations of standard histology, the interaction between MNs and tumor cells was investigated at a higher spatial resolution by electron microscopy. TEM images suggested a determined multistep pathway of MNs internalization. After adhesion to the phospholipid membrane, MNs were enclosed in vesicles, carried near the Golgi apparatus and finally included in vesicles that resemble a double layered membrane.M. gryphiswaldense included in a tumor mass with a protocol based on hyperthermia induced by an AMF and the reaction of the xenograft neoplasm was observed by MRI and histology. Contrary to what previously reported It is well known the high sensitivity of tumor cells to thermal variation. Temperatures ranging between 42 and 47°C degrees cause degenerative processes in neoplastic cells -However, we showed a local effect of MNs within tumors, with evidences of tissue necrosis both by histology and MRI -9. FurtThe physiological conditions for MNs migration still need to be clarified; a possible scenario involves the combination of passive transport mediated by reticuloendothelial system and active transport, mediated by macrophages. These processes resemble the transport pathways for conventional iron oxide nanoparticles, as described in in vitro and in vivo examination, allows for non invasive follow up of the lesions at different time points. In addition, our results demonstrate that clinical MRI could be included in protocols based on theranostic employment of MNs: both the injection site and the necrotic areas of the tumor can be detected at once in a single MRI session. Theranostic is a combination of diagnostics and therapy and our data confirms that MNs exhibit some core characteristics of the so called “theranostic agents”.The proposed experimental design, that involves both Our results do not match data available in the literature; it has to be noticed that different parameters used for hyperthermia, as well as different strain of magnetotactic bacteria used to obtain MNs and a different tumor model, are all features that could lead to some inconsistencies with previous discoveries. Future efforts will focus on the optimization of experimental conditions: initial tumor volume and MNs administration among others, to obtain a more homogeneous distribution of nanoparticles and improve the therapeutic effect of MFH based on MNs.in vivo by MRI, chains of our MNs are easily detectable if injected directly in the living tissue due to their iron content. This suggests a possible use of these nanoparticles as negative contrast agent or magnetic tracer. This behavior is useful to localize a bolus of MNs injected in a tumor mass: we were able to visualize the site of injection and follow the physiological distribution of nanoparticles within the tumor over time by MR imaging. Moreover, the same modality allows to record the effect of AMF exposures on tumors at different time points. Although we did not observe a reduction of tumor mass, areas of fibrosis and necrosis were visible at microscopic level.This study reports a multimodal approach to assess biological properties of MNPs extracted from magnetotactic bacteria. A clearly detectable increase of temperature has been recorded by exposing MNs to an AMF. In addition, the temperature increase showed a good linear relation when measured in samples with increasing concentrations of MNs. When investigated Multimodal approach is a valuable strategy to characterize several aspects of MNs. Many more efforts are needed to further understand key aspects of their interactions with living systems


Skeletal muscle, the most abundant tissue in mammal body, is indispensable for locomotion but also plays a major role in the regulation of energy metabolism. Muscle fibers are mainly generated during embryonic and fetal development, yet physiological postnatal muscle enlargement depends mostly on hypertrophic growth. Muscle regeneration after injury critically depends on activation and proliferation of muscle stem cells (MuSC), also called satellite cells. Developmental myogenesis relies on proliferation and differentiation of mesodermal progenitor cells that become specified by expression of myogenic regulators of the MyoD/Myf5 transcription factor family. During development Pax7-positive muscle progenitor cells are set aside by unknown mechanism and later form the MuSC pool. It is generally assumed that regenerative myogenesis recapitulates most aspects of developmental myogenesis although it seems likely that important differences exist . In factin vitro followed by genetic inactivation in vivo revealed a crucial function for MuSC proliferation and differentiation. Inactivation of Prmt5 in MuSC resulted in abrogation of muscle formation after acute and chronic muscle injury demonstrating a critical role of Prmt5 in control of adult muscle regeneration. Molecular studies indicated that Prmt5 epigenetically silences the cell cycle inhibitor p21 by methylation of histone H3R8. Interestingly, deletion of p21 partially restored proliferation of Prmt5 deficient MuSC suggesting that repression of p21 by Prmt5 is critical to enable proliferation of MuSC. Surprisingly, inactivation of Prmt5 in Pax7-positive muscle progenitor cells during embryonic development showed no obvious defects indicating fundamental differences between embryonic and adult myogenesis, which are -at least in part-mediated by Prmt5 [Prmt5 was identified in a functional shRNA screen of molecules that were enriched at the protein level in MuSC. Characterization of Prmt5 by loss and gain of function assays by Prmt5 .Muscle progenitor cells and MuSC are located in different microenvironments or niches and respond to distinct external myogenic stimuli. Such differences might be transformed to distinct nuclear responses leading to activation of different transcriptional programs and/or different chromatin organization. Prmt5 seems to be a positive component of the nuclear epigenetic regulatory network that silences cell cycle regulators thereby keeping adult MuSC in a primed state, ready for external stimulation and proliferation. The prevalent location of Prmt5 in the cytoplasm during embryonic development suggests that Prmt5 plays only a minor role in the epigenetic regulation of gene expression. Instead Prmt5 might regulate cytoplasmic signaling cascades although this function does not seem to be dominant during developmental myogenesis . The dif


However, in order to exploit, integrate, visualize and interpret such high-dimensional data efficiently, coequal field in oncology, leading to a delay in its maturation and, as an immediate consequence, an under-exploration of high-throughput data for translational research.For this reason, computational cancer biology aims to fill this gap. Unfortunately, computational cancer biology is not yet fully recognized as a Here we argue that this imbalance, favoring ’wet lab-based activities’, will be naturally rectified over time, if the next generation of scientists receives an academic education that provides a fair and competent introduction to computational biology and its manifold capabilities. Furthermore, we discuss a number of local educational provisions that can be implemented on university level to help in facilitating the process of harmonization. Deserven genome ,4.Interestingly, aside from the main result of the the Human Genome Project, which was to provide the first draft of the human DNA, it helped powerful highthroughput technologies to emerge . These tcomputational cancer biology or computational oncology to aggregate quantitative fields with oncology to establish computer-driven approaches, but we are well aware that other terms are sometimes used as well. Although, many may be willing to attest computational cancer biology a similar status as other fields, this liberalism comes swiftly to an end if it comes to concrete actions. For example, in terms of funding and the number of employed scientists, computational cancer biology is currently certainly not at eye level with other fields in oncology. Examples for this can be found, e.g., in the MRC strategic plan 2009-2014 that mentions in a 44 page document the term ‘computational’ just once and ‘bioinformatics’ only twice. Similar results can be found for the NCI  of the NIH  in a 88 page document. Also the number of awarded Training Fellowships by the MRC for Bioinformatics, Biostatistics and Methodology was together only 12 from to a total of 92 awarded Fellowships (13%) in all fields in 2011/12  requiring only 7% of the total Fellowship budget. In contrast, 18 (19%) non-clinical Fellowships were awarded consuming 45% of the total budget.An important question in this context is if computational cancer biology is a coequal field in oncology, similar to other sub-areas specialized in particular cancer types, e.g., breast cancer, lung cancer or lymphoma, or if it is merely an ‘auxiliary’ field. Here, we use the term This imbalance is also reflected in the number of research groups. For instance, the Cancer Research UK Cambridge Institute, a leading UK institution, employes 20 research groups of which only 2 focus on computational biology. Similarly, at the Center for Cancer Research and Cell Biology at the Queen’s University Belfast (UK) we have 38 research groups in total, but only 3 computational labs. This is also observable in institutions of other countries. For instance, the German Cancer Research Center in Heidelberg has only 9 of its over 90 research groups with such a focus and the Dana-Farber Cancer Institute in Boston (USA) employes 16 faculty member in its Department of Biostatistics and Computational Biology, whereas the Department of Cancer Biology and Department of Medical Oncology have over 200 faculty members.without analyzing original data at the same time, even though profound insights are possible from rigorously reanalyzing existing data, as one can see in [A similar imbalance can be found in the scientific literature. For instance, in journals like Nature and Science one finds rarely articles that focus on computational cancer biology n see in -19. SpecOne could wonder why one would like to establish computational cancer biology as a coequal field in oncology at all? The answer to this question is also the cause of the problem we are facing in the post-Human Genome Project era: Data!Specifically, the possibilities opened nowadays by a number of different high-throughput technologies , includioutside in order to deal appropriately with these novel data types. Here, by outside we refer to fields like statistics, computer science, physics or signal processing that deal quantitatively with different aspects of data and that developed a long-standing history of expertise and success [One problem in this context is that oncology as a field does, traditionally, not bring up quantitative scientists, but is mainly concerned with wet lab work and clinical trials. Although, also these subjects require quantitative analysis methods, these are certainly not comparable to the demands triggered by next-generation sequencing (NGS) data, not to mention the integration of different data types. For this reason, oncology needs to be complemented with expertise that comes from  success ,25. ThisPotentially, there are many ways how one could counteract this imbalance. However, a rather natural way is by means of education. Specifically, at the Center for Cancer Research and Cell Biology (CCRCB) at the Queen’s University Belfast, we are organizing since a couple of years a summer research program for students. This program is open to BSc students and senior high school (secondary school) students and runs usually between six and eight weeks throughout the summer months. During this time, the students are distributed to the separate research groups, including computational biology, at the Center according to their interests and aspirations.Imagine you are the Marketing Manager for the Centre for Cancer Research and Cell Biology (CCRCB) at Queen’s University Belfast. Your role is to promote the work of the CCRCB and Belfast Cancer Research UK Centre throughout Northern Ireland.A reflection of the value the students attribute to computational cancer biology can be seen from a recent poster competition organized by the CCRCB and Cancer Research UK (CRUK). The task the students were given was to prepare a poster conveying the following information: always a computational approach. As such: Computational cancer biology is the common denominator of modern oncology.As a result from this competition the winner Aaron Carlisle, a student from Dromore High School (UK), prepared the successful poster, shown in Figure intuitive we mean that it is not necessary to understand computational approaches in the very detail in order to realize their importance and necessity. Biologically, this may be seen as adaptability of the student population to environmental pressure in order to improve their fitness. Certainly, the analogy to a self-organizing system has its limitations, however, it may well be that there are no strong political interventions necessary that dictate, e.g., quota for grants, scientific personnel or publications in flagship journals like Nature and Science, prescribing the inclusion of computational cancer research.The outcome of this poster competition is very encouraging, because it reflects an intuitive appreciation students have for computational research in oncology. Here by local solutions that can be implemented on the School-, Institute- and Department-level.We think that, in general, there is no doubt about the importance of computational approaches for cancer research and for this reason it will only be a matter of time when computational cancer biology steps out of the shadow of its big brothers and into the light of a broad recognition. However, the establishment of certain boundary conditions will help to enhance this development. Because it is outside of our area of influence to directly change strategic programs of funding bodies, we discuss here only Summer internships Undergraduate training (BSc course)Postgraduate training (MSc course or PhD program)Postdoctoral training (seminars)Mentoring of colleagues Education is a key-element in shaping the future of any field. For this reason we consider the exposure of students to ‘computational biology’ on all relevant education levels as a necessary condition to establish a sustainable program in computational cancer biology. Specific elements are: There are various ways of engagement on these levels, e.g., via a formal establishment of BSc or MSc courses or, less formal, by providing individual modules, lecture series or lectures as a complement to existing programs. It will depend on the local needs of an institution and on the amount of commitment one is willing to make. However, even more important than the quantity of exposure of students to this subject, is the quality with which it is taught. As an example, we just want to briefly remind the reader to the meaning of a p-value and its relation to the sampling distribution of a null hypothesis. Despite the classic nature of this topic, going back to Fisher and Neyman, it causes unease in generations of students, because of two reasons. First, the topic itself is not trivial at all. Second, hypothesis testing finds such a wide-spread application, in essentially every scientific field that generates data, that the number of qualified scientists who can confidently teach such subjects is outnumbered by an order of magnitude by application focused researches. For computational approaches this means that before one can sit in front of a computer to use it for a problem one needs to understand what one wants to do, which does not require a computer. This is intimately connected to the usage of software packages that are capable of solving particular data analysis problems.Computational proficiencyStatistical proficiencyMathematical proficiencyBiomedical knowledgeOn each of the above mentioned education levels, it is necessary to teach the students four key skills and knowledge, and their mutual interplay: It is part of the problem that ‘computational biology’ is not one-dimensional, but interdisciplinary composed of different skill sets that are traditionally rooted in different subjects . However, this interdisciplinary character of computational biology is a major factor of its strength! Briefly, computational proficiency ensures independency of available software and enables the implementation of any desired algorithm for analysis or visualization. Statistical and mathematical proficiency allow to design or adapt methods in a problem-directed manner so they interrogate data in a way to extract important and sensible biological information. Finally, biological knowledge is the glue that connects the other parts together; see Figure The above outline gives only the scaffold of training programs and we would like to emphasize a number of key features that appear for us imperative in order to improve upon many existing programs. First of all, there is a crucial difference between proficiency and knowledge. For knowledge the emphasize is more on facts and information about a problem, whereas proficiency is centered around skill sets and their application. For instance, computational proficiency cannot be acquired by memorizing only the syntax of commands of a programming language. Instead, a programming language needs to be practiced hands-on in the context of sensible problems. Furthermore, a programming language needs to be taught that can be actually applied for analyzing real biological data and not just for showing toy examples. We think that the statistical programming language R  is a gooSecond, for acquiring statistical and mathematical proficiency it is necessary to connect statistical and mathematical problems with their computational implementation. For instance, the teaching of non-parametric hypothesis tests will lead to a deeper understanding of statistical inference in general and specifically the interplay between a test statistic and a sampling distribution. Such a level of understanding cannot be achieved by using ‘point and click’ software packages because they are hiding all practical detail levels resulting in an abstract black-box function. As such, the practical implementation in a programming language of a statistical model can be seen as de-black-boxing of the model.Third, all statistical models are based on a basic understanding of analysis, linear algebra and probability theory. Hence, without proficiency in these mathematical fields no statistical proficiency can be achieved. This implies that shortcuts in teaching statistical models by avoiding a deeper discussion about the former fields will corrupt a statistical understanding and its proficiency.Fourth, in order to implement the above measures one needs to schedule sufficient amount of time in the educational and training curriculum. That means, based on the background of students one needs to assess the realistic need for their training to bring them up to the desired proficiency and knowledge level in computational biology. Frequently, the scheduled time framework is over optimistically chosen resulting in frustrated students and instructors alike. Computational biology is a difficult subject and if the training of students does not lead to the desired outcome the objectives of the training are not met and the capabilities of conducting state-of-the art data analyses is severely impaired.There is one additional point we consider worth emphasizing individually. For this reason, let’s consider the following situation: You are hungry but you cannot cook. What do you do? There are three common options. First, you go out to a restaurant. Second, you learn how to cook. Third, you buy a microwave ready meal. It is immediately clear to everyone that by pursuing the third option you cannot open a restaurant. Also, the quality of your learned cooking skills may not be far above a ready meal if you do not put in the necessary effort.In the context of computational biology, this example translates as follows: In the first case, there is a facility that solves the data analysis problem for you. In the second case, you receive training, as discussed in the previous sections. The third case corresponds to the acquiring of propriety software that provides you with ready solutions for standard problems.For biomedical research including oncology that involve patients, it seem imperative that only ‘chefs’ should analyze data and the transition from someone who cannot cook to a chef takes many years. That means, the acquired expertise of trainees and students needs to be fairly assessed and limitations need to be acknowledged in order to avoid later severe problems, e.g., with respect to the reproducibility of the results.We do not want to finish this article without remarking that also research councils, e.g., the Medical Research Council , the National Institutes of Health  or the European Research Council , bear a responsibility to actively influence the evolution of computational biology that should complement the above educational initiative. For instance, the computational biology expertise on grants that propose a significant generation of data should be an enforced requirement to ensure a sound experimental design and analysis of the data. Furthermore, the funding of PhD studentships and Postdoctoral Research Associates could be stirred toward the computational data analysis rather than data generation because the availability of large public data repositories allows to work on biomedical problems without the need to generate data .https://www.casym.eu/), as an initiative to develop strategies for a realization of systems medicine rather than to provide right away an implementation of commonly agreed measures.It is clear that immediate answers to many urging questions cannot be given instantly. For this reason it is commendable that the FT7 program supports the European Network CASYM - COORDINATING ACTION SYSTEMS MEDICINE (all possible levels, from BSc students to faculty members, in order to harmonize existing differences between computational biology and other parts of oncology naturally, and the more gaps are between these different levels, the more unstable is the outcome of the educational process.In this paper, we advocated the opinion that an efficient and natural means for establishing computational biology in oncology is provided via the implementation of broad educational programs. This could lead within one education-cycle, from BSc via PhD to PDRA - namely within 8-10 years, to an assertion of the field, without the need to reformulate other parts of oncology. Here, it is important to emphasize that education, the key of this process, should take place on Finally, we would like to note that the problem discussed in this paper has already found appreciation and CASyM and the Wellcome Trust PhD program in Mathematical Genomics and Medicine are good examples. However, we are far away from a general and broad recognition of computational cancer biology as a coequal field in oncology.We hope that our contribution, which is meant to initiate a wider discussion of this important issue across all relevant communities involved in cancer research rather than as a remedy, will help to establish efficient measures to make computational cancer biology a powerful force in fighting cancer.