Advances in detection techniques and treatment have increased the diagnosis of breast cancer at early stages; however, recurrence occurs in all breast cancer subtypes, and both recurrent and de novo metastasis are typically treatment resistant. A growing body of evidence supports the notion that metabolic plasticity drives cancer recurrence. RON and DEK are proteins that promote cancer metastasis and synergize mechanistically to activate β-catenin, but the metabolic consequences are unknown.To ascertain RON-DEK-β-catenin dependent metabolic pathways, we utilized an NMR-based metabolomics approach to determine steady state levels of metabolites. We also interrogated altered metabolic pathway gene expression for prognostic capacity in breast cancer patient relapse-free and distant metastasis-free survival and discover a metabolic signature that is likely associated with recurrence.RON-DEK-β-catenin loss showed a consistent metabolite regulation of succinate and phosphocreatine. Consistent metabolite alterations between RON and DEK loss (but not β-catenin) were found in media glucose consumption, lactate secretion, acetate secretion, and intracellular glutamine and glutathione levels. Consistent metabolite alterations between RON and β-catenin loss (and not DEK) were found only in intracellular lactate levels. Further pathway hits include β-catenin include glycolysis, glycosylation, TCA cycle/anaplerosis, NAD+ production, and creatine dynamics. Genes in these pathways epistatic to RON-DEK-β-catenin were used to define a gene signature that prognosticates breast cancer patient survival and response to chemotherapy.The RON-DEK-β-catenin axis regulates the numerous metabolic pathways with significant associations to breast cancer patient outcomes. This hiThe RON receptor tyrosine kinase is overexpressed in >50% of breast cancers encompassing all subtypes and has been identified as a biomarker of recurrent breast cancer with predictive capacity for distant metastasis and early death –7. Thus,There is increasing evidence that metabolic plasticity, in addition to genetic and epigenetic plasticity, plays a significant role in cancer metastasis and residual disease –16. Give+ production, and creatine/phospho-creatine dynamics. These data implicate the RON-DEK-β-catenin axis in regulating energy metabolism in support of cell proliferation/growth and plasticity for cell survival. From these pathways, we generated a signature of epistatic (relative to RON-DEK-β-catenin) metabolism genes that show prognostic survival and predictive chemotherapy response utility for breast cancer patients.Here we report that breast cancer cells with perturbations of the RON-DEK-β-catenin axis show altered metabolite levels associated with the following pathways: glycolysis, glycosylation, TCA cycle, anaplerosis, NADR7 (control), R7sgRON, R7shDEK, MRBC FL, and MRBC KO murine breast cancer cell lines were generated as previously described ,18 and w3CN) to halt the metabolic activity, and the addition of nanopure water (CH3CN/H2O at 2:1.5 (V/V)) to facilitate cell scraping and collection. Polar and non-polar metabolites were extracted using the solvent partition method acetonitrile: water: chloroform (CH3CN: H2O: CHCl3) at rations 2: 1.5: 1 (V/V) [Metabolites were extracted from the 5 cell lines. After 24 h of incubation all dishes were at 80–90% of confluency. At time of collection, the medium was aspirated, and the cells were washed three times with ice-cold phosphate-buffered saline, followed by subsequent quenching with ice cold acetonitrile (CH 1 (V/V) . The aqug for 15 min at 4°C to remove debris. 250 μL of the supernatant were transferred to a new tube and weighted. Media small metabolites were separated from macromolecules by centrifugal ultrafiltration using 3 kDa molecular-weight-cutoff membrane. 250 μL of culture media were added to a pre-washed 3 K spin filter  and centrifuged at 14000 x g for 60 min at 4°C. The filtrate flow through was collected in a new tube, weighed, and lyophilized for subsequent NMR analysis.From each cell replicate an aliquot of 500 μL of media was harvested at 0 h and after 24 h of incubation. All media samples were centrifuged at 3500 x 2O). 200 μL of each sample was transferred to a 3 mm NMR tube for analysis. All NMR spectra were acquired at 288 K on a Bruker Avance III HD 600 MHz spectrometer (Bruker Biospin) equipped with a 5 mm Broad Band Observed (BBO) Prodigy probe. For each sample, one-dimensional (1D) 1H-NMR experiments were acquired using the noesygppr1d pulse sequence with presaturation of the water resonance using a 25 Hz bandwidth, 256 transients, a 15-ppm spectral width, a 4.0 s relaxation delay, and a 2.0 s acquisition time corresponding to 44640 data points. Before Fourier transformation, each 1H spectrum was zero-filled to 128 K data points and apodized with a 1 Hz exponential line-broadening function. All spectra were recorded and transformed with the used of Topspin 3.6.2 software  and processed (phased and baseline corrected) using MestReNova software . Spectra were internally calibrated to the methyl resonance of the TSP at 0.0 ppm. A total of 34 different metabolites were identified and assigned (S1 Table) using in-house databases, in combination with public databases HMDB  and 2D 1H, 13C Heteronuclear Single Quantum Correlation (HSQC) experiments were recorded to facilitate the identification of biochemical substances.For the analysis of intracellular and extracellular metabolites, the lyophilized cell and media polar extracts were resuspended in 220 μL of NMR buffer , 1 mM trimethylsilyl propionic acid-d4 sodium salt (TSP) as internal standard, and 1 mg/mL sodium azide in 100% deuterium oxide (Ddatabase ) and liti) by calibration against the known amount of the internal standard TSP (peak at 0 ppm) added to the sample according to the formula: ni = v(Ai/As)cs, where, v is the volume of the sample, Ai and As are the peak areas of the compound resonance and of the standard, and cs is the concentration if the standard. The nmoles of metabolites in each sample were then normalized to the concentration of protein quantified by BCA derived from each dry residue pellet obtained during the metabolite processing as a proxy of cell amount. Metabolite quantification from 0 h and 24 h media samples were used to define the rates of nutrient uptake and product excretion. The change of metabolic product abundances with time was calculated as the difference between the number of moles of metabolites consumed or excreted per unit of time per unit of protein at the final time point (media t = 24 h) and the metabolite levels at baseline (media t = 0 h). An unsupervised multivariate analysis by Principal component analysis (PCA) was performed with the use of the “prcomp” R package: to summarized the relationship among the observations and better understand and interpret the role of the RON-DEK-β-catenin axis. The univariate statistical analysis of the data was performed using a one-way ANOVA to compare R7, R7sgRON, R7shDEK cell lines and two-tailed Student’s t-test for the MRBC FL and MRBC KO comparison. Significance was defined as p values < 0.05. Data were displayed as mean ± SEM.To determine the metabolite abundance across the samples, both in cell and in culture media samples, the area of each assigned and well resolved metabolites were manually integrated using global spectra deconvolution (GSD), a line-fitting deconvolution algorithm available in MestReNova software , which returns the area of each peak of interest. The peak area was divided by the number of protons contributing to that signal. For absolute quantification the corrected peak areas were converted into nmoles  was utilized to stratify breast cancer patient outcomes with respect to relapse-free survival (RFS) and distant metastasis-free survival (DMFS) in the Gene Expression Omnibus-derived KMPlot datasets [MST1R) expression in stratifying breast cancer patient outcomes [MST1R/DEK/CTNNB1) was also analyzed comparatively to the Metabolism signature, and a Combined signature encompassing the Metabolism and MST1R/DEK/CTNNB1 signature. Each signature was subjected to sliding cutoff and FDR procedures. Both, the Metabolism and Combined signatures were then validated using the Cancer Genome Atlas (TCGA) Pan Cancer dataset [The capacity of metabolic genes in the nominated pathways . MRBC FL cells, harbor biallelic β-catenin floxed genes [S1A Fig) to create MRBC KO cells. To investigate how cellular metabolism responds to targeted deletion of RON, DEK or β-catenin, we compared the water-soluble metabolome of the mutants and the corresponding control cell lines using 1H-NMR spectroscopy. To this end, cells were grown for 24 hours to examine the metabolic exchange between cells and media. Cell growth curves showed no significant differences between groups during this time frame supporting that changes in metabolites are unlikely to be associated with differences in cell proliferation . We also employed Seahorse extracellular metabolic flux analysis to characterize the RON-DEK-β-catenin dependent regulation of metabolic states from a cell biology perspective. Using the Real-Time ATP Rate Assay wherein cells growing in vitro are sequentially challenged with inhibitors of oxidative phosphorylation (oligomycin) and mitochondrial membrane complexes (rotenone/antimycin A) while measuring oxygen consumption and extracellular acidification. Oxygen consumption rates  and extracellular acidification rates  under these dynamic conditions were used to create an Energy Map  which describes RON loss, DEK loss, and β-catenin loss as leading towards a more energetic state under these growth conditions. Next, we assessed mitochondrial mass and activity using Mitotracker Green  and Mitotracker Red  staining. Mitchondrial mass was found to be significantly upregulated under RON loss, DEK loss, and β-catenin loss . Mitochondrial membrane potential was found to be unchanged across RON-DEK-β-catenin modulations .R7 and MRBC are murine breast cancer cells that express RON, DEK, and β-catenin. Both cell lines were derived from a mammary tumor from mice selectively overexpressing RON in the mammary gland (MMTV-RON mice) ,13. The 1H-NMR. A representative 600 MHz 1H-NOESY spectrum can be seen in  The selected regions of the spectra show the peak integration strategy by using GSD and the signal-to-noise ratio (SNR) calculation for low abundant metabolite. For some of these specific metabolites, although the SNR may be below the standard for quantification , all the cited metabolites are well above the limit of detection and show a reproducible peak integration among the samples. This potential limited precision and accuracy in the quantification of the low abundant metabolites has been carefully considered in the interpretation of the data. A complete list of metabolites identified in the 1H-NOESY spectra can be viewed in S1 Table. Principal component analysis (PCA) was employed to determine the extent to which samples vary based on metabolite profiles which revealed discrete segregation of our experimental groups . This supports that the RON-DEK-β-catenin axis acts to regulate metabolic states within breast cancer cells, and warrants closer dissection of individual changes to metabolites.In parallel, replicates of these groups were quenched, fractionated, and polar phase extracted for analysis via Fig 1A). Glucose and other nutrients are imported from the culture media into the cells. The carbons derive from glucose flux through glycolysis, which takes place in the cytosol. Pyruvate is transported into the outer mitochondrial matrix through the voltage-dependent anion channel (VDAC), and then into the inner mitochondrial matrix via monocarboxylate transporters (MCTs) [Fig 1B). Interestingly, extracellular pyruvate levels were elevated upon RON loss, reduced upon DEK loss and unchanged upon β-catenin loss . Intracellular glucose levels were unchanged across all R7 modulations and not detected in MRBC cell lines, but lactate levels were significantly reduced upon RON or β-catenin loss not with DEK loss . An alternative utilization of glucose for glycogen synthesis and the addition of glucose to other biomolecules involves uridine diphosphate (UDP) conjugation of glucose, which is implicated in supporting breast cancer migration, metastasis, and treatment resistance [Fig 1C). The TCA cycle involves the conversion of pyruvate produced during glycolysis into acetyl-CoA, which is condensed with oxaloacetate to produce citrate . We examined the levels of three critical metabolites at various points in the TCA cycle: citrate, succinate, and fumarate . An interesting pattern emerged when examining citrate, as RON loss, and even more so DEK loss, elevated citrate levels, whereas β-catenin loss reduced citrate levels . Succinate levels were reduced with RON, DEK, or β-catenin loss, and DEK loss increased fumarate levels. . While numerous metabolites show overlapping regulation patterns by RON/DEK  or RON/β-catenin (intracellular lactate), only succinate was consistently regulated by RON/DEK/β-catenin.Glycolysis and TCA cycle are prominently featured pathways in metabolic analyses because they feed into both anabolic and catabolic processes which can lead to diverse cellular responses (pathways summarized in s (MCTs) . Glucosesistance ,29. UDP-Fig 2A. Extracellular alanine levels were found to be elevated upon RON loss but reduced upon DEK loss and unchanged with β-catenin loss . The amino acid alanine can be readily transaminated to pyruvate once inside the cell. In R7 cells lines no changes were observed in intracellular alanine levels. In contrast, knock out of β-catenin resulted in a significant decrease . Furthermore, the exogenous levels of alanine and pyruvate revealed the same pattern reflecting a typical substrate-product relationship. Acetate, a two carbon metabolite, participates in anabolic processes including lipogenesis and filling of the acetyl-CoA pool in addition to serving as a carbon source for epigenetic modifications in parallel to other central carbon metabolism pathways [Fig 2C). Extracellular acetate levels were virtually ablated by RON loss and reduced by DEK loss, but elevated by β-catenin loss . Glutamine serves as primary source of nitrogen for the biosynthesis of proteins and nucleotides, but also as a carbon source via flux into the TCA where it can be further metabolized. Glutamine was less avidly depleted from the media upon DEK loss, suggesting a lower degree of glutamine dependence .To gain a deeper understanding of altered metabolic pathways, we next examined metabolites that can feed in (anaplerosis) or draw from TCA (anabolism); such entry/exit points to/from TCA cycle are summarized in pathways . Acetatepathways , in addiFig 2C). Glutamate is the downstream product of glutamine and can similarly be deaminated to form the TCA cycle metabolite α-ketoglutarate. However, the addition of an amino group to the γ-carbon of glutamate results in glutamine. Glutamate levels were unchanged across RON/DEK/β-catenin conditions, whereas glutamine levels were reduced by RON or DEK but not β-catenin loss . Glutamate is also used for glutathione production, which is involved in cellular redox homeostasis, and is formed through the condensation of glutamate with the amino acids cysteine and glycine. Interestingly, RON or DEK loss elevated levels of glutathione, whereas β-catenin loss reduced them . Intracellular adenosine mono-/di-/triphosphate (AXP) was elevated by DEK loss but reduced by RON loss and unchanged by β-catenin loss. With respect to anabolism/anaplerosis regulation by the RON-DEK-β-catenin axis, there was no consistent regulation across individual losses of RON/DEK/β-catenin, but glutathione, intracellular glutamine, and extracellular acetate showed consistent regulation between RON/DEK loss.Deamination of alanine to pyruvate allows for mitochondrial transport and conversion to acetyl-CoA which then condenses with oxaloacetate to form citrate. The malate-aspartate shuttle transports cytoplasmic hydride (from NADH) into the mitochondria as malate, which can be converted back to OAA by MDH, and the OAA transaminated via GOT2 with Glu forming Asp and 2OG. Aspartate levels are elevated upon RON or β-catenin loss but reduced upon DEK loss  then to NAD+ . Additionally, nicotinamide can be synthesized using dietary tryptophan by conversion into quinolinic acid via the kynurenine pathway.From a bioenergetics standpoint, the purpose of the TCA cycle is to continually produce electrons in the form of NADH to reduce oxygen to water via the electron transport chain (ETC), and couple this to efficient ATP production. The oxidized NAD+ levels were observed by either DEK or β-catenin, but not RON loss . Because L-tryptophan levels were unchanged across conditions it is unlikely that its biosynthesis was altered . In contrast, the trend of NADP+ concentration changes is opposite to its precursor NAD+; however, NADP+ levels did not significantly change across conditions . Interestingly, NMN was strikingly elevated upon DEK loss, suggesting salvage pathway regulation and showing an opposite behavior than the corresponding NAD+ for the same cell lines. . These data suggest NAD+ regulation by DEK may exert regulatory effects on NAD-dependent pathways, specifically the step catalyzed by the enzyme NMNAT-1.Decreased NADFig 4A. 1H-NMR spectra of phospho-creatine (p-creatine) and creatine represent the differences observed between groups . P-creatine levels are elevated by RON, DEK, or β-catenin loss while creatine levels were only elevated by DEK loss . The ratio of P-creatine to creatine was significantly elevated following RON or β-catenin, but not DEK loss . Of all our analyses, phosphocreatine was the most striking consistent change across loss of RON/DEK/β-catenin. These data implicate regulation of creatine dynamics, and perhaps the state of bioenergetics as a whole by the RON-DEK-β-catenin axis.As an energy reservoir, creatine allows for cells to replenish ATP as described in S4A Fig) and extracellular  compartments, myo-inositol , choline , phosphocholine , and glycerophosphocholine . Intracellularly, amino acids tyrosine, phenylalanine, histidine, isoleucine, and valine show minute, but statistically significant reductions under RON loss and DEK loss, but not β-catenin loss . Taurine is significant increased under RON loss, and to an even greater extent under DEK loss, but is unchanged under β-catenin loss . Extracellularly, amino acids were largely removed from the assay medium resulting in negative values, but glycine shows elevated levels indicating release to the medium; under RON loss and β-catenin loss, but not DEK loss, there is an elevated extent of glycine secretion . Isoleucine release was unchanged across experimental conditions, however release of α-ketoisoleucine was elevated under RON loss and β-catenin loss, but reduced under DEK loss; this same pattern was observed for ketoisoleucine . Myo-inositol levels are elevated under RON loss and to a greater extent under DEK loss, but are slightly reduced under β-catenin loss . While choline levels are unchanged across experimental conditions , phosphocholine (PC) is reduced under RON loss and DEK loss, but significantly elevated under β-catenin loss . Glycerophosphocholine (GPC) is significantly elevated under RON loss and β-catenin loss and to a lesser extent DEK loss .Some additional metabolites not yet mentioned were also analyzed. This includes amino acids from both intracellular , TCA/anaplerosis , NAD+/Kynurenine and NAD+ salvage , and creatine  is shown with respective p-values input for FDR procedure (5% cutoff) with the multiple testing [Tables 1 and 2.From the pathways identified in our metabolomics study , we determined whether the expression of genes encoding critical metabolic enzymes within these pathways (irrespective of their expression relationship with RON/DEK/β-catenin) could prognosticate breast cancer outcomes. The KMPlot  webtool  testing  webtool Fig 6A). Importantly, the metabolism signature shows a larger hazard ratio (HR = 1.77) value than the MST1R/DEK/CTNNB1 signature (HR = 1.48) suggesting a greater extent of patient survival stratification. The combined signature shows the highest HR value (HR = 1.81), albeit marginally larger than the metabolism signature . With respect to DMFS both signatures and the combined signature again prognosticated poorer survival with higher signature expression, with the MST1R/DEK/CTNNB1 HR (HR = 1.82) being slightly higher than the metabolism signature (HR = 1.77) and the highest HR from the combined score  implying the greatest extent of patient survival stratification.High expression of the composed metabolism signature showed significantly poorer RFS than that of the low expression, which was true of a MST1R/DEK/CTNNB1  signature, and metabolism + RON/DEK/β-catenin combined signature . Finally, we tested the metabolism signature on predicting breast cancer response to therapy in the GEO-derived dataset queried via the ROCplot [Fig 5D). Taken together, these data validate the prognostic/predictive value of the MST1R/DEK/CTNNB1 signature, demonstrate the prognostic/predictive value of the newly developed metabolism signature, and suggest that a combination of the two may provide the strongest clinical utility.We next tested the metabolism signature in another dataset, the Cancer Genome Atlas (TCGA) Pan Cancer dataset to examine the prognostic capacity of the metabolism signature on disease-specific survival (DSS) of breast cancer patients. In this dataset, the metabolism signature performed strongly (HR = 3.51), the MST1R/DEK/CTNNB1 signature to a lesser extent (HR = 2.00), and the combined signature performed somewhere in between  breast cancer examined the impact of early locoregional treatment showing no improvement in survival or quality of life in aggressive treatment of the primary tumor when distant metastases were already present [A recently concluded clinical trial in patients with metastatic  in regu+ salvage pathway is reportedly overexpressed in numerous cancer types including breast cancer and treatment of cancer cells with the NAMPT inhibitor, FK866, is an active area of preclinical testing [+ as a significant driver of lactic fermentation (the Warburg effect) as a mechanism to re-establish bioenergetics , which was a previously unknown role for NAD+ [+ by the RON/DEK/β-catenin axis may have profound effects on several metabolic pathways including glycolytic flux from central carbon and NAD+ perspectives, glycosylation, and TCA cycle and its interactions with other pathways via anabolism and anaplerosis.With respect to specific reprogramming based on RON/DEK/β-catenin status, glycolysis and the TCA cycle represent the most canonical and established pathway alterations in cancer . With re testing . Moreovefor NAD+ . Thus, tCreatine serves as an energy shuttle that can be reversibly phosphorylated by ATP via Creatine Kinase (CK) and may act with Adenylate Kinase (AK) to maintain ATP levels through interchange of phosphocreatine and ATP; increase of phosphocreatine when ATP is abundant (via CK activity) and decrease of phosphocreatine when ATP is depleted (via AK activity). Creatine synthesis occurs in the kidney and creatine enters the circulation through the SLC6A8 transporter. Phosphorylation of creatine supports the local ATP pool through phosphate movement between compartments. Thus, readily actionable energy from phosphocreatine is mobile within the tumor microenvironment . Our datThis study examined gene-metabolite relationships by focusing on the RON/DEK/ signaling axis, which is a known driver of breast cancer metastasis and recurrence. We defined steady state metabolic programming by RON, DEK and/or β-catenin and discovered associations between related enzyme expression and breast cancer outcomes regardless of RON/DEK/β-catenin expression. We posit that metabolic reprogramming regulated by RON/DEK/β-catenin may be similarly controlled by other oncogenic drivers of metastasis/recurrence and may therefore more broadly define key metabolic drivers of breast cancer stages responsible for the majority of cancer-related deaths. Given the capacity of this metabolism gene signature to stratify breast cancer patients in multiple datasets and predict response (or lack thereof) to chemotherapy, we provide further evidence that metabolic plasticity is associated with a metastatic phenotype in breast cancer. The prognostic/predictive value of this signature will be further refined in future studies to integrate multi-omics datasets that may show significant clinical utility. Feasibility of multi-omics approaches in breast cancer has been demonstrated through use of both tumor tissue and other non-invasive, metabolically sensitive specimens  .Fig 6 with respect to overlapping and unique alterations. Overall, these include glucose consumption and utilization via glycolysis  and UDP-conjugation (for glycogen synthesis or glycosylation), steady state positions of TCA intermediates  and anaplerotic/anabolic pathways , NAD+ and NAD+ salvage intermediates, and both total creatine and phosphocreatine levels. These data are a cross section of the steady-state positions of metabolic pathways that constantly flux.The data presented herein using an NMR metabolomics approach support the notion that the RON-DEK-β-catenin axis regulates several metabolic pathways previously implicated in supporting cancer progression, and other pathways with unclear connections to cancer. RON-DEK-β-catenin pathway dependent metabolic alterations are summarized in The identified pathways were used to produce a list of metabolic genes with epistatic expression relative to the RON-DEK-β-catenin axis (regulating these pathways) that show value in prognosticating breast cancer patient outcomes. This metabolic gene signature showed prognostic value in GEO-derived data and TCGA data and was predictive in node-positive breast cancer patient response to chemotherapy. These data suggest that the identified pathways mark a more aggressive breast cancer course and poor outcome and may themselves be drivers of metastatic progression and recurrence.S1 FigA) Western blot analysis of cell lysates from R7, R7sgRON, R7 shDEK cells , and MRBC FL and MRBC KO cells probed for RON, DEK, β-catenin, or actin (loading control). (B) Cell growth assays of R7, R7sgRON, R7shDEK cells and MRBC FL and MRBC KO (right) cells. Seahorse Real-Time ATP Rate Assay analysis of (C) oxygen consumption rates (OCRs) of R7 Control, R7 sgRON, and R7 shDEK (top) and MRBC FL and MRBC KO cells (bottom) and (D) extracellular acidification rates (ECARs) of R7 Control, R7 sgRON, and R7 shDEK (top) and MRBC FL and MRBC KO cells (bottom). (E) Energy maps of R7 Control, R7 sgRON, and R7 shDEK (top) and MRBC FL and MRBC KO cells (bottom) from the Real-Time ATP Rate Assay. (F) Relative mitochondrial mass measured via Mitotracker Green staining of R7 Control, R7 sgRON, R7 shDEK, MRBC FL, and MRBC KO cells. (G) Relative mitochondrial membrane potential normalized to mitochondrial mass (Mitotracker Green) measured via Mitotracker Red staining of R7 Control, R7 sgRON, R7 shDEK, MRBC FL, and MRBC KO cells. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001; ****P ≤ 0.0001.((TIF)Click here for additional data file.S2 FigA) Expansion of the region δ 5.66–5.50 ppm containing the peaks corresponding with UDP-glucose. (B) Magnification of the region δ 7.55–6.50 ppm containing fumarate, tyrosine (Tyr), histidine (His), phenylalanine (Phe) and tryptophan (Trp). (C) Enlargement of the region δ 9.00–9.60 ppm containing nicotinamide mononucleotide-N4 (NMN-N4), NADP+-N6, NAD+-N6, NADP+-N2, NAD+-N2, NMN-N6, NMN-N2.The presented regions are characterized for presenting low abundant metabolites. The metabolites present in this regions were assigned and the calculated the signal to noise ratio (SNR) of those peaks used for quantification. ((TIF)Click here for additional data file.S3 FigA) R7 (control), R7sgRON and R7shDEK comparison; (B) MRBC FL and MRBC KO; (C) R7 (control) and R7sgRON; (D) R7 (control) and R7shDEK; (E) R7sgRON and R7shDEK.The principal component analysis (PCA) score plot (left) and loading plot (right) of the first two principal components from each comparison. Samples were projected by group labeled. The combined distribution of the variable in the loading plots defines. The color of the variables in the loading plot reflects the higher (red) or lower (blue) contribution of each variable on the group discrimination. ((TIF)Click here for additional data file.S4 FigA) Intracellular amino acid metabolites quantified from 1H-NMR spectra and normalized to the protein content after 24 h of cell incubation. (B) Extracellular amino acid metabolites imported or released by the cells into the culture media. (C) Extracellular levels of isoleucine imported or released by the cells into the culture media as well as derivatives a-ketoisoleucine and ketoisoleucine. Bar graphs indicate mean and error bars represent SEM of replicates. Replicates of each cell line are shown as individual dots (n = 6–7). Statistical significance was assessed using one-way ANOVA and two-tailed Student’s t-test for R7 and MRBC comparisons, respectively. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001; ****P ≤ 0.0001.((TIF)Click here for additional data file.S5 FigA) Myo-Inositol, (B) choline, (C) phosphocholine (PC), (D) glycerophosphocholine (GPC). Statistical significance was assessed using one-way ANOVA and two-tailed Student’s t-test for R7 and MRBC comparisons, respectively. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001; ****P ≤ 0.0001.Intracellular levels of ((TIF)Click here for additional data file.S6 FigA) relapse-free survival (RFS) and (B) distant metastasis-free survival (DMFS). Individual genes of the Glycosylation pathway comprising the metabolism gene signature stratifying (C) RFS and (D) DMFS. Combined Glycolysis pathway stratification of (E) RFS and (F) DMFS and combined Glycosylation pathway stratification of (G) RFS and (H) DMFS.Individual genes of the Glycolysis pathway comprising the metabolism gene signature stratifying ((TIF)Click here for additional data file.S7 FigA) relapse-free survival (RFS) and (B) distant metastasis-free survival (DMFS). Combined Anapleurosis/TCA cycle pathway stratification of (C) RFS and (D) DMFS.Individual genes of Anapleurosis/TCA cycle pathway comprising the metabolism gene signature stratifying ((TIF)Click here for additional data file.S8 FigA) relapse-free survival (RFS) and (B) distant metastasis-free survival (DMFS). Individual genes of the NAD salvage pathway comprising the metabolism gene signature stratifying (C) RFS and (D) DMFS. Combined Kynurenine/NAD synthesis pathway stratification of (E) RFS and (F) DMFS and combined NAD salvage pathway stratification of (G) RFS and (H) DMFS.Individual genes of the Kynurenine/NAD synthesis pathway comprising the metabolism gene signature stratifying ((TIF)Click here for additional data file.S9 FigA) relapse-free survival (RFS) and (B) distant metastasis-free survival (DMFS). Combined Creatine/phospho-creatine pathway stratification of (C) RFS and (D) DMFS.Individual genes of the Creatine/phospho-creatine pathway comprising the metabolism gene signature stratifying ((TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.


Paris polyphylla. PPI has been demonstrated to have strong anticancer activity. However, its effect on the stemness of liver cancer stem cells (LCSCs) is not completely understood. Herein, we aimed to investigate the effect of PPI on the stem cell-like features of LCSCs and hepatocellular carcinoma (HCC). LCSCs were enriched in a serum-free medium and treated with PPI, sorafenib (Sora), or PPI and Sora. Several endpoints, including spheroid formation and differentiation, cell proliferation, surface markers of LCSCs, PPI binding targets, and stemness-associated protein expression, were evaluated. Immunofluorescence staining, quantitative real-time polymerase chain reaction, siRNA transfection, and coimmunoprecipitation ubiquitination assays were conducted for in-depth mechanistic studies. Evaluation of in vivo antitumor efficacy demonstrated that PPI effectively inhibited the proliferation of liver cancer cells and the self-renewal and differentiation of LCSCs. Flow cytometry indicated that PPI suppressed the expression of the stem cell surface markers EpCAM and CD13. Molecular docking showed a high affinity between PPI and proteins of the Wnt/β-catenin signaling pathway, including AKT, GSK-3β, and β-catenin, with the binding energies of -5.51, -5.32, and -5.40 kcal/mol, respectively, which suggested that PPI might regulate the Wnt/β-catenin signaling pathway to affect the stem cell-like properties of HCC. Further ex vivo experiments implied that PPI activated the AKT/GSK-3β-mediated ubiquitin proteasomal degradation of β-catenin and subsequently attenuated the prooncogenic effect of LCSCs. Finally, the anticancer property of PPI was confirmed in vivo. It was found that PPI inhibited the tumor growth in an HCC cell line xenograft model. Taken together, molecular docking analysis and experimental data highlighted the novel function of PPI in suppressing the stem cell-like characteristics of LCSCs via the AKT/GSK-3β/β-catenin signaling pathway.Polyphyllin I (PPI), also called Chong Lou saponin I, is a steroidal saponin isolated from the rhizome of  Cancer is a leading cause of death worldwide, accounting for 10 million deaths in 2020 . Most paCancer stem cells (CSCs) in HCC are characterized by continuous self-renewal, differentiation, and tumorigenic capabilities, which are considered the cause of therapeutic resistance, tumor emergence, recurrence, and metastasis , 7. AlthHowever, the mechanistic aspects of LCSC-mediated HCC development are relatively unknown. Studies have revealed that Wnt signaling proteins play an important role in the culture of CSCs , 11. LCSParis polyphylla (Chong Lou) is a well-known medicinal plant that has been used in various traditional Chinese formulations for wound healing and anticancer therapy [Traditional Chinese medicine has been practiced for thousands of years and has become a promising strategy for cancer therapy, with minimal side effects and a high efficiency.  therapy , 18. Pol therapy . Previou therapy –26; therβ-catenin. PPI was also found to restrain xenograft tumor growth in nude mice. Taken together, the results of our study provide supporting evidence for the anti-LCSC activity of PPI against HCC.In this study, we found that PPI inhibited the proliferation of liver cancer cells and limited the self-renewal and differentiation ability of LCSCs, possibly via proteasomal degradation of PPI (S9114), sorafenib , and SC79 were purchased from Selleck Chemicals . Cycloheximide  and MG132 (474790) were obtained from Sigma–Aldrich . Dimethyl sulfoxide was used to dissolve PPI and Sora, which were then stored at -20°C. The structure of PPI is displayed in 2.The HepG2 human hepatoma cell line was obtained from ATCC and maintained according to the ATCC guidelines. The human HCC cell line Huh-7 was purchased from MEIXUAN Biological Science and Technology . HepG2 cells were cultured in Eagles Minimum Essential Medium  with 10% fetal bovine serum  and 1% penicillin and streptomycin . RPMI-1640 medium (Gibco) with 10% FBS and 1% P/S was used to culture Huh-7 cells. LCSCs were cultured in DMEM/F12 medium (Gibco), with B27 (Invitrogen), insulin (Sigma), recombinant human epidermal growth factor (BD Biosciences), 1% P/S, and 0.4% bovine serum albumin . All cells were cultured at 37°C in a humidified incubator with 5% COμM) for 24, 48, and 72 h. Finally, the CCK-8 reagent was added to each well, and the plates were incubated in a humidified incubator for 3 h. Half-maximal inhibitory concentration (IC50) values were calculated, and cell proliferation curves for both HepG2 and Huh-7 cells were plotted.The cytotoxicity of PPI was detected using Cell Counting Kit-8, . HepG2 and Huh-7 cells were seeded in 96-well plates and incubated overnight. The cells were then treated with PPI . The cells were then cultured for 2 weeks in fresh complete media to gain a further insight into the long-term effects of PPI. Subsequently, cell colonies were fixed with 4% paraformaldehyde and stained with 0.5% crystal violet (Beyotime Biotechnology).For a colony formation assay, HepG2 and Huh-7 cells were seeded in 6-well plates and incubated overnight for cell attachment, followed by the intervention with PPI at different concentrations  three times. Images were directly observed using a fluorescence microscope.HepG2 and Huh-7 cells were seeded in 24-well plates with 500 LCSCs derived from HepG2 and Huh-7 cells were selectively cultivated in the CSC culture medium in 6-well ultralow-adhesion plates. The medium was exchanged with a fresh complete cell medium using the half-change method every other day. PPI, Sora, and PPI plus Sora were added to the CSC culture medium to investigate their effects on the formation of tumor spheres. The size and number of primary spheres were assessed by microscopy. Lastly, following 10 days of culture, CSC spheres were cultured in 6-well plates with complete medium for 48 h to determine their differentiation ability and observe morphological changes by microscopy.5 cells/well in 6-well plates and cultured overnight. After treatment with PPI, Sora, or PPI plus Sora for 48 h, the cells were digested, rinsed, and resuspended. EpCAM-FITC and CD13-PE antibodies (BD Biosciences) were added to the cell suspensions, and the mixtures were incubated for 30 min in the dark. FITC- and PE-labeled isotype IgG1 antibodies served as negative controls. Subsequently, the cells were washed with 1x PBS three times and measured using a BD LSRFortessa flow cytometer (BD Biosciences). The results were analyzed using the FlowJo software.HepG2 and Huh-7 cells were seeded at a density of 3 × 10β-catenin, p53, PI3K, PPARα, AKT, and GSK-3β were analyzed using the AutoDock v4.2.6 and AutoDock-Tools v1.5.6 software. The three-dimensional structure of PPI was downloaded from PubChem (https://pubchem.ncbi.nlm.nih.gov/), and the crystal structures of β-catenin, p53, PI3K, PPARα, AKT, and GSK-3β were obtained from the RCSB Protein Data Bank (http://www.rcsb.org/pdb/). Before docking, the PPI and protein structures were prepared by adding polar hydrogen atoms, computing the Gasteiger charge, and assigning the AD4 atom type. A grid box with a size of 60 × 60 × 60 Å and a grid spacing at 0.375 Å that was centered on the ligand were used to cover the residues at the binding site. Finally, docking between PPI and β-catenin, p53, PI3K, PPARα, AKT, and GSK-3β were performed using Lamarck's genetic algorithm. Parameters including the number of individuals in the population, maximum number of energy evaluations, and maximum number of generations were studied, with the number of GA runs set to 150, 5.0 × 106, 2.7 × 104, and 50. The Discovery Studio client and PyMOL software were used to analyze and visualize the docking results.PPI interactions with and binding affinities for ΔΔCt). The selected β-actin and β-catenin primers were designed by Sangon Biotech. The primer sequences were as follows: β-actin (F) 5′-TCCTTCCTGGGCATGGA-3′ and (R) 5′-AGGAGGAGC-AATGATCTTGATCTT-3′ and β-catenin (F) 5′-ACAGCACCTTCAGCACTCT-3′ and (R) 5′-AAGTTCTTGGCTATTACGACA-3′.Isolation and reverse transcription of total RNA were performed according to standard procedures. qPCR was carried out using a Bio-Rad ViiA7 system, a reverse transcription-PCR kit, and a SYBR Green kit (Takara). Calculations of relative RNA levels were performed using the comparative Ct method . The protein bands were then transferred to enhanced chemiluminescence reagents (Millipore) and imaged using a Tanon detection system. Band intensities were quantified using the ImageJ software.LCSC spheres were treated with PPI, Sora, and PPI plus Sora for 48 h, followed by lysis with radioimmunoprecipitation assay buffer (Beyotime) supplemented with a protease inhibitor mixture (Roche Diagnostics) for 30 min at 4°C. Total protein concentrations were measured using a protein quantitation kit (KeyGen Biotech). Subsequently, equal amounts of protein were subjected to 10% SDS-PAGE, and the proteins were transferred to polyvinylidene fluoride microporous membranes (Millipore). The membranes were then blocked with 5% skim milk for 2 h and incubated with primary antibodies at 4°C overnight, followed by incubation with the respective secondary antibodies (Abcam) for 1 h at room temperature (RT). The following primary antibodies were used: NANOG, OCT-4, AKT, p-AKT, GSK-3LCSCs were treated with PPI for 48 h, and Co-IP ubiquitination analysis was performed using the Capturem™ IP and Co-IP kit (Takara) according to the manufacturer's instructions. Samples of precipitated input controls and proteins were subjected to western blot analysis with the corresponding antibodies, as indicated in the previous section.β-catenin, 1 : 100, CST) for 2 h at RT and washed with 1x PBS three times for 5 min. The cells were then incubated with a goat anti-rabbit IgG H&L Alexa Fluor 488 secondary antibody  for 1 h in the dark. The cell climbing slices were washed three times for 5 min each with 1x PBS. Staining was performed 2-(4-amidinophenyl)-6-indolecarbamidine dihydrochloride (DAPI) for 15 min at RT under darkness. The slides were sealed with antifluorescence quenching tablets (Solarbio) after cell climbing. For image acquisition, a Zeiss LSM laser scanning confocal microscope was used with 405, 488, and 570 nm excitation, and images were analyzed using the Zen software (Zeiss).Cells were seeded in climbing slices and treated with PPI or Sora for 48 h, followed by fixation for 1 h. The cells were then blocked and permeabilized using 5% BSA (Sigma) in 0.1% Triton X-100/PBS for 2 h at RT, followed by incubation with a primary antibody (β-Catenin and nonspecific siRNAs were constructed by GenePharma. Transfection of the siRNAs was performed with the HiPerFect transfection reagent (HanBio Biotechnology). First, 3 × 105 cells were seeded in a 6-well plate with 2 mL of complete medium. Next, the siRNAs or NC were mixed with the transfection reagent, and the mixtures were incubated at RT for 10 min. Subsequently, the complexes were transfected into LCSCs for 24 h, and the transfection reagent was replaced by a fresh complete medium.in vivo. This research was approved by the Animal Care and Use Committee at Guangzhou University of Chinese Medicine. Approximately 5 × 106 Huh-7 CSCs with Dual Luciferase were resuspended in 100 μL of Matrigel (Corning) and injected into the right flanks of the mice. The mice were randomly assigned to each experimental group, including control , Sora (30 mg/kg), PPI (1 mg/kg), and PPI (1 mg/kg) combined with Sora (30 mg/kg) groups. Body weights and tumor volumes were measured and recorded every 3 days. D-luciferin (PerkinElmer) was injected intraperitoneally for the acquisition of tumor optical images using the IVIS Lumina XR imaging system (PerkinElmer). The mice were sacrificed when the tumors in the control group reached 20 × 20 mm. Tumors and other organs were then collected from the four groups for hematoxylin and eosin (H&E) staining and immunohistochemistry (IHC).Twenty-four male BALB/c nude mice were purchased from the Medical Experiment Center in Guangdong Province to study the inhibitory effect of PPI on tumor growth in vivo. Xenograft tumors were dehydrated and embedded in paraffin, and serial sections with a slice thickness of 4 μm were prepared. Samples were then dewaxed and hydrated according to a standard procedure. For H&E staining, 10% hematoxylin was used to stain the cell nuclei for 5 min, and eosin was used to counterstain the cytoplasm for 2 min. The stained sections were then dehydrated, hyalinized, and sealed with neutral gum. For IHC, methanol with 0.3% hydrogen peroxide was used to block endogenous peroxidase activity, and goat serum was used to decrease nonspecific binding. The sections were then incubated with primary antibodies against KI67, NANOG, OCT-4, and β-catenin at 4°C for 12 h, and a DAB substrate–chromogen solution was applied for color development after incubation with secondary antibodies. The sections were counterstained with hematoxylin and sealed with neutral gum. Finally, the sections were photographed and stored.H&E staining and IHC analysis were performed to further assess the anticancer efficacy of PPI t-test was used for two groups of data in accordance with independence, normality, and homogeneity of variance, and one-way analysis of variance was performed for comparison among multiple groups. P < 0.05 was considered statistically significant.Data are presented as the mean ± standard deviation. All statistical analyses were conducted using the SPSS software (version 19.0) and plotted with GraphPad Prism 7.0. An independent-samples 50 values of 2.177 and 2.094 μM were obtained for HepG2 and Huh-7 cells, respectively, after treatment with PPI for 24 h, then decreased to 1.298 and 1.010 μM, respectively, when exposure was prolonged to 48 h, and to 0.5543 and 0.58 μM, respectively, after 72 h . Similar effects were observed for Huh-7 CSCs, with the groups that received PPI, with or without Sora, displaying relatively lower EpCAM+CD13+ expression than the control group  and the highest interaction. However, the binding energy of +3.98 kcal/mol between PPI and PPARα indicated that PPI did not bind well to PPARα. To further identify whether PPI could regulate the Wnt/β-catenin signaling pathway in LCSCs, dockings between PPI and AKT and GSK-3β were conducted. We found that PPI was able to bind to AKT and GSK-3β with binding energies of -5.51 and -5.32 kcal/mol , suggesting that PPI is a negative factor in β-catenin stabilization. Furthermore, available data suggest that GSK-3β is a downstream target of AKT, and the inhibition of GSK-3β phosphorylation at Ser9 as a result of PPI treatment might depend on AKT. We found that p-AKT was also significantly suppressed by PPI in LCSCs , AKT activator SC79 and the GSK-3β inhibitor LiCl were used to suppress the activity of AKT and GSK-3β, respectively. The result of following experiments showed that the expression of β-catenin in the LCSCs was further decreased by PPI in the presence of LY treatment, and the inhibition of β-catenin expression by PPI is rescued by SC79 (the Akt activator). Meanwhile, PPI could offset the β-catenin-enhanced effect of LiCl partially  that originates from the rhizome of chanisms . Availabchanisms . Neverthin vivo experiment, we first conducted a CCK-8 assay to assess the inhibitory effect of PPI against HCC cells, with the results indicating that PPI suppressed the proliferation of HepG2 and Huh-7 cells in dose- and time-dependent manners. Subsequently, a colony formation assay showed that PPI treatment exerted long-term inhibitory effects against these HCC cell lines. An assay investigating the tumor sphere-forming ability of LCSCs demonstrated that PPI treatment, with or without Sora, restrained the growth of suspended stem-like spheres that were derived from HepG2 and Huh-7 cells. Furthermore, flow cytometry indicated that the proportion of EpCAM+CD13+ cells decreased after treatment with PPI or Sora. Collectively, PPI not only restricted the proliferative capacity of HCC cells but also suppressed the characteristics of LCSCs.Before performing the β-catenin pathway and that β-catenin is involved in the regulation of canonical markers of LCSCs [β-catenin and of the CSC markers NANOG and OCT-4 were upregulated in LCSCs compared with that in HCC. Furthermore, both the total and fractional expression levels of β-catenin were downregulated in HepG2 and Huh-7 CSCs treated with PPI or Sora. In addition, an immunofluorescence assay showed that PPI and Sora suppressed nuclear accumulation of β-catenin in LCSCs, while PPI did not facilitate the degradation process of β-catenin in the presence of MG132, indicating that PPI might regulate β-catenin levels through proteasomal degradation. The stimulation of the canonical Wnt pathway by specific ligands deactivates GSK-3β via specific phosphorylation at Ser9, thereby stabilizing β-catenin and leading to its translocation to the nucleus [β at the Ser9 residue, resulting in the inactivation of GSK-3β and stabilization of the β-catenin protein [β (Ser9), suggesting that PPI is a negative factor for β-catenin stabilization, which might lead to proteasomal degradation of β-catenin. In addition, p-AKT was found to be significantly inhibited by PPI or Sora in LCSCs, suggesting that the inhibition of AKT activation is involved in the PPI-induced β-catenin degradation. For in-depth analysis of the mechanism of action of PPI on the AKT/GSK-3β pathway, the AKT inhibitor LY and the GSK-3β inhibitor LiCl were used to suppress the activity of AKT and GSK-3β, respectively. LY treatment decreased the expression of β-catenin, and PPI exacerbated this effect, whereas PPI administration counteracted the β-catenin-enhanced effect of LiCl. Overall, these results showed that PPI suppressed the LCSC stemness and likely promoted β-catenin degradation through the AKT/GSK-3β signaling pathway.It has been demonstrated in numerous studies that HCC could exhibit the aberrantly activated Wnt/of LCSCs , 50. Our nucleus . Moreove protein . Both PPβ-catenin is an essential mediator of LCSC stemness, LCSCs with β-catenin silencing were constructed using lentivirus vector transfection. Our results demonstrated that β-catenin silencing could effectively inhibit the proliferation of LCSCs. Furthermore, the β-catenin siRNA not only led to a reduction in β-catenin expression but also abolished the stem cell-like properties of LCSCs. Meanwhile, no significant reduction was observed in the PPI combined with siRNA group compared with that in the PPI-alone or the siRNA-alone group, indicating that PPI might abolish the stem cell-like properties of HCC by modulating the stability of β-catenin. Co-IP combined with a ubiquitination experiment was used to gain a deeper insight into the underlying regulatory mechanism of β-catenin. The results demonstrated that PPI might activate the ubiquitination process of β-catenin in LCSCs.To confirm that in vitro experiments in in vivo experiments. As live imaging showed, PPI, with or without Sora, could suppress the tumor growth, and the combination of PPI and Sora exerted the strongest inhibitory effect. H&E and IHC experiments also revealed that both PPI and Sora could limit the expression of β-catenin, NANOG, and OCT-4. To summarize, these results indicated that PPI had an anticancer effect and reduced the stemness of LCSCs via proteasomal degradation of β-catenin through the AKT/GSK-3β pathway.In addition, we confirmed the results of β-catenin, thereby restraining the growth of HCC cells and blocking the activation of LCSCs, both in vivo and in vitro. To the best of our knowledge, this is the first report suggesting that PPI limits tumor sphere formation by restraining stem cell-like characteristics. This study elucidated the anticancer effects of PPI in the treatment of HCC, highlighted the importance of β-catenin in maintaining the stemness of LCSCs, and provided evidence for the clinical application of PPI. There are also limitations such as that flow cytometry would be a more appropriate means for measuring LCSC markers in mice. Additional studies are needed to further explore the effects of PPI on LCSCs and HCC.The results of this study showed that a natural compound, PPI, activated the proteasomal degradation of


The magnetic navigation system (MNS) with gradient and uniform saddle coils is an effective system for manipulating various medical magnetic robots because of its compact structure and the uniformity of its magnetic field and field gradient. Since each coil of the MNS was geometrically optimized to generate strong uniform magnetic field or field gradient, it is considered that no special optimization is required for the MNS. However, its electrical characteristics can be still optimized to utilize the maximum power of a power supply unit with improved operating time and a stronger time-varying magnetic field. Furthermore, the conventional arrangement of the coils limits the maximum three-dimensional (3D) rotating magnetic field. In this paper, we propose an electrical optimization method based on a novel arrangement of the MNS. We introduce the objective functions, constraints, and design variables of the MNS considering electrical characteristics such as resistance, current density, and inductance. Then, we design an MNS using an optimization algorithm and compare it with the conventional MNS; the proposed MNS generates a magnetic field or field gradient 22% stronger on average than that of the conventional MNS with a sevenfold longer operating time limit, and the maximum three-dimensional rotating magnetic field is improved by 42%. We also demonstrate that the unclogging performance of the helical robot improves by 54% with the constructed MNS. Magnetic robots and tools have attracted considerable attention as alternatives to conventional medical devices such as catheters, endoscopes, grippers, and forceps ,5,6,7,8.A simple coreless MNS combines several pairs of Helmholtz coils (HCs) and Maxwell coils (MCs). These circular coils are structurally simple; hence, many researchers have used this combination to actuate magnetic robots ,23,24,25In this study, an electrical optimization method is proposed on the basis of a novel arrangement of the MNS with five pairs of coils. First, two pipes for installing the five pairs of coils were determined so as to have the required inner space. Then, we propose a novel arrangement of the five pairs of coils that enables the MNS to generate similar three-axis magnetic fields per current because the available amplitude of a 3D rotating magnetic field is restricted by the coil that generates the smallest magnetic field. Next, the objective functions, design variables, and constraints were defined for optimization, with some assumptions to simplify the calculation. The constraints include the inductance effect and current density of the coils such that the MNS can generate a strong time-varying magnetic field under a given temperature limit. The MNS was optimized using an optimization algorithm with the given constraints. Finally, the optimized MNS was constructed and verified. Then, the performance was compared with the conventional MNS. We confirmed that the optimized MNS could generate a stronger magnetic field in both static and dynamic conditions. The improved magnetic field can be used to enhance the quasi-static and dynamic motion of magnetic robots. As one example, we demonstrated that the optimized MNS can effectively improve the unclogging performance of a helical robot.k-th coil, respectively, the subscripts h, m, g, uy, and uz represent the HC, MC, GSC, and y- and z-directional USCs, respectively, and x, y, and z are assumed to be negligible around the center of the MNS, where the workspace is located. Then, the magnetic torque is generated by three components , the sign is determined on the basis of the location of the coil attached to the pipe. If the coil is attached to the outside, it has a positive sign (+); if the coil is attached to the inside, it has a negative sign (−). Finally, the objective function of the k-th coil can be rewritten using the two design variables (The MNS has three magnetic field components (In Equations (10) and (11), the resistivity , We also constrained We developed an optimization algorithm using Equations (10) and (11) and the given constraints, shown in The optimized MNS was constructed, as shown in The constructed MNS had considerable geometrical errors because there was no available winding machine for the coils, owing to their unusual size and shape. In particular, the circular HC and MC were wound with the larger radius . We calculated the magnetic field of each coil considering the correction factor, and xy-plane, the operating time limit would be much longer than 40 min because we discontinuously utilize the HC and USCy below the maximum output power.The electrical insulation system for the wires was divided into different classes by temperature; we used an F-class wire for each coil. The F-class wire has an allowable temperature of 155 °C; this must be a temperature limit for safe use. The temperature rise due to the current of the coils was measured using an infrared thermometer, as shown in k-th coil, respectively. Because the magnetic field is proportional to the current in Equation (3), the calculated maximum magnetic field and field gradient in Each coil was designed to have a minimum inductance within the maximum output range of the power supply unit. The current drop due to the inductance effect can be expressed as follows :(18)Ik=VTo verify the optimized MNS, we compared it with the conventional MNS in ,22, as sThe maximum 3D rotating magnetic field of the optimized MNS was 42% larger than that of the conventional MNS in the static state. This improvement of static magnetic field can enhance the quasi-static motions such as steering motion of a magnetic catheter and sampling motion of a magnetic capsule ,31. In aIn this paper, we proposed an electrical optimization method based on a novel arrangement of the MNS with saddle coils. The MNS was optimized to generate a greater magnetic field and field gradient than a conventional MNS with the same output power and similar size. As a result, each coil could generate an average of 22% stronger magnetic field or field gradient, and the maximum 3D rotating magnetic field was improved by 42%. The proposed optimization method also minimized the current density and inductance of the coils so that the MNS could generate a stronger time-varying magnetic field, with at least sevenfold longer operating time. The optimized MNS could effectively enhance the magnetic robots. As one example, we demonstrated that the unclogging performance of a helical robot was improved by 54%.Through this study, we verified that, even if the coil is geometrically optimized, the performance of the coil can be limited in the case that the electrical characteristics are not properly designed. In contrast to coreless MNS, many researchers have studied the optimization method of MNSs with a core ,16,17, bThe proposed optimization method increases the cross-sectional area of the coils to suppress the temperature rise of the coils by reducing the current density. However, this may increase the material cost because copper coil is quite expensive. Thus, an excessively large cross-sectional area of the coil is not recommended in terms of cost. Although the thickness of the wire was limited, it was still too thick to manufacture complex coils without manufacturing errors; therefore, the thickness of wires should be carefully determined considering the shapes and volumes of the coils.


Body condition-dependent risk-taking is observed in many animal taxa but is little explored in cetaceans. We used model simulations to explore how uncertainties surrounding this behaviour and the metabolic physiology of deep-diving cetaceans may be limiting our understanding of the energetic consequences of anthropogenic disturbance. Lipid-store body condition is fundamental to how animals cope with environmental fluctuations, including anthropogenic change. As it provides an energetic buffer, body condition is expected to influence risk-taking strategies, with both positive and negative relationships between body condition and risk-taking posited in the literature. Individuals in good condition may take more risks due to state-dependent safety (‘ability-based’ explanation), or alternatively fewer risks due to asset protection and reduced need to undertake risky foraging (‘needs-based’ explanation). Such state-dependent responses could drive non-linear impacts of anthropogenic activities through feedback between body condition and behavioural disturbance. Here, we present a simple bioenergetic model that explicitly incorporates hypothetical body condition-dependent response strategies for a cetacean, the sperm whale. The model considered the consequences of state-dependent foraging cessation and availability of wax ester (WE) lipids for calf provisioning and female survival. We found strikingly different consequences of disturbance depending on strategy and WE availability scenarios. Compared with the null strategy, where responses to disturbance were independent of body condition, the needs-based strategy mitigated predicted reductions in provisioning by 10%–13%, while the ability-based strategy exaggerated reductions by 63%–113%. Lower WE availability resulted in more extreme outcomes because energy stores were smaller relative to the daily energy balance. In the 0% availability scenario, while the needs-based strategy reduced deaths by 100%, the ability-based strategy increased them by 335% relative to null and by 56% relative to the same strategy under the 5%–6.7% WE availability scenario. These results highlight that state-dependent disturbance responses and energy store availability could substantially impact the population consequences of disturbance. Our ability to set appropriate precautionary disturbance thresholds therefore requires empirical tests of ability- vs needs-based response modification as a function of body condition and a clearer understanding of energy store availability. Published by Oxford University Press and the Society for Experimental Biology.

Received February 8, 2022; Revised September 29, 2022; Accepted October 13, 2022
 When making behavioural decisions, animals must balance multiple opportunities and threats, including reproductive investment and the risks of predation and starvation . The risBody condition is a state variable that can influence state-dependent behavioural responses . In contPopulation consequences of disturbance (PCoD) models are important tools for understanding the conservation importance of anthropogenic disturbance, particularly in long-lived, highly mobile marine mammals, for which direct study of vital rates is often impractical (Mirounga angustirostris) under risk of detection by visual predators  followed a needs-based strategy when deciding to rest or forage. As their condition improved over the course of the season, they sacrificed increasing amounts of the most energy-efficient nocturnal foraging time to rest in the comparative safety of darkness. Hyperoodon ampullatus), suggesting a positive relationship between body condition and risk-taking, which corresponds to an ability-based strategy over the range of body conditions observed in that study.In cetaceans, sensitivity to disturbance is positively correlated with intensity of response to predators, consistent with the risk-disturbance hypothesis  and beaked whales (Ziphiidae) also have high concentrations of WEs in their blubber , of 106 animals for each WE availability scenario  used in ‘full’ model simulations (see ‘Lipid-store body condition’ and Our approach to modelling body condition-dependent behaviours required setting body condition thresholds (see ‘Lipid-store body condition’ and M). The resulting tissue compartment masses were then multiplied by the respective TAG and WE percentages reported in the academic literature to give total lipid store for each compartment. These lipid stores were then partitioned into available reserves versus unavailable structural mass depending on WE availability scenario  was defined as the lipid reserve mass divided by total body mass , which represents the optimal trade-off between the benefits of increased stored energy and the costs of accumulating additional stores. Such costs may include increased cost of transport . Above this threshold, fitness is maximised by provisioning milk to the calf. Below this threshold, the individual is expected to prioritize survival over the current reproductive investment . This represents the average body condition of the population and was used to parameterize state-dependent disturbance responses  was set from Lockyer  was equal to unmodified provisioning at central body condition (rρ). As individual body condition reduced, provisioning was progressively reduced and, at values less than or equal to lactation body condition , ceased entirely. Calf demand was set to decline with age, such that it was equal to 1 for the first year and then declined at an increasing rate until it ceased entirely after 2 years. As Hin et al. note, empirical estimates of these parameters do not exist for any odontocete species and would be extremely difficult to collect. We have therefore followed their approach of developing functional forms that qualitatively reflect our theoretical expectations  was therefore assumed to be equal to the sum of unmodified provisioning (uσ) and field metabolic rate  was added to prevent body condition from increasing above realistic bounds after provisioning ceased. Following wρ) approached target body condition (tρ), essentially offsetting the reduction in energy invested in provisioning towards the end of lactation. As with the state-dependent provisioning function, a lack of empirical data required a qualitative parameterization of the function. Daily stochastic variability in patch quality (δ) was modelled by drawing a value for each whale from a normal distribution centred on 1 and with standard deviation equal to the coefficient of variation in number of buzzes per dive from bχ) was then calculated by multiplying unmodified energy acquisition by foraging effort and patch quality  were not included.. Response intensity was defined as the increase in ‘non-foraging active state’ (NFA), during which echolocation ceases but the animal remains active rather than recovering at the surface or exhibiting stereotypical resting behaviour , conditional on a given WE scenario, the function produced the full range of response intensities observed empirically by wρ) is equal to central body condition (rρ), response intensity , which here was assumed to be equal to disturbance source duration, to give daily response cost  was simulated to demonstrate the emergent properties of the system.Full simulations were carried out under both baseline and disturbed conditions. The baseline scenario included no disturbance. For the disturbed scenario, an extreme disturbance source duration (The model equations described above and in T). Sensitivity was assessed by changing each parameter by 10% while holding all others constant at the values reported in We conducted a sensitivity analysis to check that our results were not overly influenced by non-empirical assumptions, relative to the daily disturbance duration (rρ), driven by state-dependent provisioning. As provisioning progressively reduced following Day 365  and were able to fully recover after weaning (ψ) and more rapid positive feedback within simulations . The amount by which provisioning was reduced varied between strategies, with reduction in total provisioning improving under the needs-based strategy across WE scenarios  and worsening under the ability-based strategy (by 63.1%–113.0%) relative to the null strategy see ; Table 4The number of days on which any milk was provided to the calf followed similar patterns  died across all WE availability scenarios. For the ability-based strategy, costs of disturbance increased progressively as body condition declined and, by the time whale body condition lability , reductiIn scenarios assuming lower WE availability, deaths occurred both at a higher rate  and earlThis study used simulation modelling to explore the potential effects of body condition-dependent behavioural response modification on the consequences of disturbance. The simulations show strikingly different consequences of disturbance on mortality and calf provisioning, depending on which condition-dependent response strategies the animals followed and on the energetic availability of WE lipids. Compared with scenarios where individual responses were independent of body condition, a needs-based strategy avoided maternal death and resulted in few long periods of provisioning cessation. In contrast, an ability-based strategy exaggerated both consequences. Reduced WE availability resulted in reduced time to starvation and greater sensitivity to responses mediated by body condition.l), even the total cessation of nursing that followed was often insufficient to compensate for the increased cost of response. For long-lived species with slow life history traits, such as sperm whales, the high number of maternal deaths that resulted would be expected to have a significant impact on population status , the highest response costs were borne during times of favourable body condition. While this had the effect of limiting post-weaning recovery in body condition, which may be expected to impact future population fecundity, the most severe consequences were avoided; deaths were completely absent, and periods of provisioning cessation were relatively brief and infrequent. Conversely, under the ability-based strategy , a positive feedback cycle developed between decreasing body condition and response intensity. As a result, when body condition had declined below the lactation threshold : This work was supported by the United States Office of Naval Research (awards N00014-17-1-2757 and N00014-19-1-2479).supp_data_coac069Click here for additional data file.


Pediatric liver cancer hepatoblastoma has a low rate of genetic mutations, suggesting additional mechanisms that involve epigenetics and signal transduction pathways. In this paper, we present evidence showing that the phosphorylation-dependent activation of wildtype β-catenin leads to the opening of genomic regions  of oncogenes in HBL patients and to the subsequent development of liver cancer. The main activities of the ph-S675-β-catenin-CEGR/ALCD pathway are associated with the promotion of mitosis and proliferation of cancer cells. This study provides mutation-independent mechanisms that are involved in the development of aggressive HBL.GPC3) and Alpha Fetoprotein (AFP) are increased in HBL patients by β-catenin-TCF4-p300 complexes. Conclusions: The phosphorylation-mediated activation of the β-catenin-TCF4-p300-CEGRs/ALCDs pathway increases oncogene expression in patients with aggressive liver cancer and promotes the development of hepatoblastoma. Background and Aims: Hepatoblastoma (HBL), a deadly malignancy in children, is the most common type of pediatric liver cancer. We recently demonstrated that β-catenin, phosphorylated at S675 (ph-S675-β-catenin), causes pathological alterations in fibrolamellar hepatocellular carcinoma (FLC), by activating oncogenes and fibrotic genes via human genomic regions, known as cancer-enhancing genomic regions or aggressive liver cancer domains (CEGRs/ALCDs). The aim of this study was to determine the role of the ph-S675-β-catenin-TCF4-CEGRs/ALCDs pathway in HBL. Methods: The ph-S675-β-catenin-TCF4-CEGRs/ALCDs pathway was examined in a large cohort of HBL specimens, in HBL cell lines HepG2 and Huh6, and in patient-derived xenografts (PDXs). Results: β-catenin is phosphorylated at S675 in a large portion of tested HBL patients. In these patients, ph-S675-β-catenin forms complexes with TCF4 and opens CEGRs/ALCDs-dependent oncogenes for transcription, leading to a massive overexpression of the oncogenes. The inhibition of the β-catenin-TCF4-CEGRs/ALCDs axis inhibits the proliferation of cancer cells and tumor growth in HBL cell lines and HBL-PDXs. The ph-S675-β-catenin is abundant in mitotic cells. We found that markers of HBL Glypican 3 ( CTNNB1 (β-catenin) and NRF2 genes [Hepatoblastoma (HBL) is the most common type of liver cancer seen in children ,2. A subF2 genes ,7. In noF2 genes ,9,10. InF2 genes . β-catenF2 genes . The exiF2 genes , partialF2 genes . These rF2 genes  and in tF2 genes . Searching for mutation-independent mechanisms of pediatric liver cancers, we have identified human genomic regions (CEGRs/ALCDs) in many oncogenes. These CEGRs/ALCDs drive oncogene expressions in aggressive HBL ,17. PrevThis study was approved by the Institutional Review Board (IRB) at CCHMC. Informed consent was obtained from each study patient (or parent as indicated) prior to obtaining specimens. Aggressive HBLs were defined as displaying one or more of the following characteristics: chemo-resistance, relapse, multiple nodules at diagnosis, vascular invasion, and lung metastases at diagnosis or after the primary surgery. In this study, we used specimens from 32 HBL patients. For Western blot, Co-Ips, and ChIP assays, we used specimens from five HBL patients who did not have mutations in CTNNB1 genes and specimens from three HBL patients who had a deletion of exon 3 in the CTNNB1 gene . The amoβ-catenin  ab32572); ph-S675-β-catenin , ph-Ser33/37/Thr41-β-catenin , TCF4 , p300 , HDAC1 (EDM Millipore Corp. 2E10), DNAJB1 , p21 , PGAP1 , RUNDC1 , HACE1 , cyclin D1 , cdc2 , β-actin , polyclonal GPC3 , monoclonal GPC3 , AFP , cdk2 , and cdk4 . Liver and tumor sections from HBL patients were fixed in 4% paraformaldehyde (PFA), embedded in paraffin, and sectioned at 7 microns. The slides were deparaffinized and rehydrated through an ethanol gradient to water. Antigen retrieval was performed at high pressure and high temperature in Tris-EDTA pH 9 buffer. The samples were blocked for 1 h at room temperature. The samples were then incubated overnight at 4 °C with primary antibody diluted in blocking buffer. The next day, the samples were washed and incubated with secondary antibody diluted in blocking buffer for 4 h at room temperature, counterstained with DAPI, and mounted with FluoroMount-G (Southern Biotech 0100-01). Cultured Huh6 and HepG2 cells were fixed in 4% paraformaldehyde and IF analysis was processed as described in our previous work ,17,18. BCTNNB1 (Hs00355045_m1) HACE1 (Hs00410879_m1), NFE2L2 (Hs00975961_g1), TNFRSF19 (Hs00218634_m1), HMGA2 (Hs00171569_m1), THY1 (Hs00264235_s1), AFP (Hs00173490_m1), TCF7L2 (Hs01009044_m1), REG3A (Hs01055563_gH), GPC3 (Hs01018937_m1) CDK2 (Hs01548894_m1), CDK4 (Hs01565683_g1), MKI67 (Hs00606991_m1), CDKN1A (Hs00355782_m1), RB1 (Hs01078066_m1), TP53 (Hs01034249_m1), and 18S (Hs03003631_g1).Total RNA was isolated from human liver samples and cell lines, cDNA was synthesized, and QRT-PCR was performed as previously described ,17,18. B2, 5% β-mercaptoethanol, 10% glycerol) and centrifuged at 10,000 RPM for 10 min. The supernatant (cytoplasmic fraction) was saved, and the pellet was resuspended in buffer B (buffer A plus 0.42 M NaCl and 25% sucrose) and incubated on ice for 20 min. The samples were then centrifuged at 10,000 RPM for 10 min, and the supernatant was collected and used immediately for Western blotting or co-immunoprecipitation (Co-IP). WCEs: tissues were homogenized in buffer B and isolated in the same manner as NEs. For Western blotting, samples were loaded onto a 4–20% gradient SDS-PAGE gel, transferred to a nitrocellulose membrane, and incubated with primary and secondary antibodies. The Whole cell extracts (WCEs) and nuclear extracts (NEs) were prepared as described in our previous papers ,18. NEs:A biotinylated DNA oligomer containing the TCF4 binding site from CEGRs/ALCDs was linked to streptavidin beads and incubated with protein extracts isolated from adjacent (background) regions and tumor regions of HBL for 4 h in a buffer containing 10 mM Tris-HCL, pH 7.5, 100 mM NaCl, 5 mM β-mercaptoethanol, and 10% glycerol. The beads were washed three times with the buffer. Proteins were eluted by 1% SDS in a sample buffer and examined by Western blot with antibodies to β-catenin, TCF4, and p300, as described above.Chromatin solutions were isolated from the tissues and from cultured cells. The ChIP assay was performed as described previously ,18,19. B3 cells per well in a 96-well plate. The next morning, the cells were serum-starved for 4 h using DMEM media without FBS. After starvation, fresh DMEM supplemented with 10% FBS was applied and spiked with either DMSO or 5 μM PRI-724 for 48 or 72 h. Then, fresh media was applied along with MTT and incubated for 4 h. Finally, an SDS–HCl solution was added and allowed to incubate for 18 h, and absorbance was read at 540 nm. The percent viability was calculated as compared to the DMSO control.The MTT proliferation assay using HepG2 and Huh6 cells was performed as described in our papers ,19. BrieHomo sapiens GRCh 38 genome build using NCBI nucleotide BLAST. For gene-specific locations, CEGRs/ALCDs sequences were compared against the T-test or one way ANOVA was utilized where appropriate to determine the statistical significance. The p-value < 0.05 was considered statistically significant. All statistical analyses were performed in GraphPad Prism.Values are presented as means ± standard deviation. A two-tailed Our previous studies showed that in aggressive HBL, ph-S6-p53-PARP1 increases the expression of CEGRs/ALCDs-dependent oncogenes via opening these regions for transcription . Howevern = 34) HBL-specific CEGRs/ALCDs. CTNNB1 (β-catenin) and TCF4 genes, which code for the components of β-catenin-TCF4 complexes, as well as AFP, a protein that is frequently detectable in the serum of HBL patients at high levels. The presence of CEGRs/ALCDs in β-catenin and TCF4 genes suggested that there is an auto-activation of these genes in HBL [First, we searched HBL-specific genes containing CEGRs/ALCDs regions for TCF4 binding sites, identifying a strong binding site for TCF4 in all examined , including three samples lacking deletion/mutation in exon 3 of β-catenin (n = 32), we examined whether mRNAs of CEGRs/ALCDs encoded genes are elevated in the liver tumors of HBL patients. As shown in HACE1, NRF2, TNFRSF19, TCF4, Thy1, HMGA2, and AFP were elevated in a large portion of samples from the fresh biobank. The TNFRSF19 and HMGA2 genes were included in these studies since it has been recently shown that TNFRSF19 is a marker of HBL [HMGA2 has also been shown as potential marker of HBL [TNFRSF19, HMGA2, CTNNB1, Thy1, and AFP are elevated in the majority of the examined patients  with an active ph-S675-β-catenin-TCF4-CEGRs/ALCDs pathway. As shown in Since GPC3 is activated in HBL by ph-S675-β-catenin-TCF4-CEGRs/ALCDs pathway, we asked whether the tumors of these patients might secrete GPC3 into the bloodstream. We found that GPC3 is elevated in liver tumors and in plasma from the same HBL patient #8 . Thus, iTo examine a possible causal role of ph-S675-β-catenin in the activation of CEGRs/ALCDs-dependent oncogenes, we thought to inhibit β-catenin activity in HepG2 and Huh6 cell lines by PRI-724 and examine the effect of this inhibition on the β-catenin-TCF4-p300-CEGRs/ALCDs pathway. PRI-724 was selected for these studies since it is currently being used in clinical trials for patients with liver fibrosis/cirrhosis . We firsp53 gene  are elevated. We also detected the reduction of Rb1 and Tp53 mRNAs in HepG2 cells. Second, Western blotting confirmed the reduction of cyclin D1, cdk2, cdk4, and cdc2 as well as the elevation of p21 and HNF4 proteins in cells with inhibited β-catenin activity  from three HBL patients treated with vehicle (control) or with Ola. The total β-catenin and ph-S675-β-catenin levels were also measured in the same samples. Western blotting showed that β-catenin, ph-S675-β-catenin, GPC3, and AFP were reduced in Ola-treated PDXs compared to vehicle-treated PDXs (CEGRs/ALCDs genomic regions contain binding sites for different transcription factors ,18, inclted PDXs . To examAFP gene showed that, in addition to CEGR/ALCD in the intron 3, the promoter of this gene contains four TCF4 binding sites (AFP gene, we used primers covering the TCF4 binding site 1 that was in close proximity to the start of transcription. The examination of ph-S6-p53-PARP1 complexes on the β-catenin CEGR/ALCD showed that these complexes are removed from the CEGR/ALCD of β-catenin in the Ola-treated PDXs (GPC3 gene and on the AFP promoter showed that the Ola-mediated inhibition of β-catenin resulted in the removal of β-catenin-TCF4-p300 complexes from CEGR/ALCD of the GPC3 gene and from the AFP promoter and the consequent repression of these genes. Taken together, these results suggest that the Ola-mediated inhibition of CEGRs/ALCDs in HBL-PDXs reduces the network of CEGRs/ALCDs-containing cancer-associated genes. In particular, we found that Ola removes ph-S6-p53-PARP1 complex from the CEGR/ALCD of the β-catenin gene, leading to β-catenin reduction. The inhibition of β-catenin, in turn, leads to the reduction of β-catenin-TCF4-p300 complexes and the repression of oncogenes including GPC3 and AFP genes (The sequence analysis of the ng sites B. For thted PDXs C. This lFP genes E.Hepatoblastoma, the most common pediatric liver cancer, is extensively studied, but effective therapeutic approaches for aggressive HBL cases are not available. Since β-catenin is frequently mutated in HBL tumors, previous studies have focused on examining the β-catenin mutations in HBL. These studies have provided a solid foundation for researchers regarding β-catenin; however, it is become clear from recent studies that the development of HBL includes mechanisms independent of β-catenin mutations. Our lab has conducted detailed mechanistic studies of HBL, focusing on the post-translational modifications of oncogenes. We have found that the CEGRs/ALCDs regions of the human genome are key determinants of aggressive HBL. These regions are short, highly homological DNA sequences that have several 100% homologous subregions containing binding sites for various transcriptional complexes. In this paper, we present evidence that the β-catenin-TCF4 complex increases the expression of CEGRs/ALCDs-dependent oncogenes in HBL patients, HBL cell lines, and PDX mouse models of HBL. Although we have concentrated our studies on a small number of CEGRs/ALCDs-containing oncogenes, this pathway may function through many CEGRs/ALCDs-containing genes because TCF4 binding sites are observed in all identified CEGRs/ALCDs . An analREG3A showed that its mRNA is highly elevated in HBL patients with an active ph-S675-β-catenin-TCF4 pathway (The HBL-PDX models are best for reproducing the in vivo biology of HBL. Using this system, we discovered that oncogenes and other cancer-associated genes are part of a network of gene expression regulation that is dependent on CEGR/ALCDs. Genes dependent on CEGRs/ALCDs regulate both themselves and other genes via CEGRs/ALCDs. Among these are the genes p53, TCF4, and β-catenin. Our earlier research demonstrated that p53, which is phosphorylated at Ser6 by JUNK1/2 kinases, form complexes with PARP1, which promotes the expression of CEGRs/ALCDs-dependent genes in patients with aggressive HBL ,19. We h pathway E. In this study, we investigated five HBL patients in depth who had no β-catenin mutations and three HBL patients with deletion of exon 3 of the β-catenin gene. The exon 3 was deleted in one allele, but the patients produced WT β-catenin in the other allele. Regardless of mutation status, all eight HBL patients exhibited expressed ph-S675-β-catenin in tumor sections. Thus, we believe that the phosphorylation of β-catenin at Ser675 is one of the key events in the development of aggressive HBL. It remains to be investigated whether the mutant β-catenin is also phosphorylated at Ser675 and this phosphorylation in the mutant form also enhances its oncogenic activities. In summary, the studies of the ph-S675-β-catenin-TCF4-CEGRs/ALCDs pathway in HBL patients, in hepatoblastoma cell lines HepG2 and Huh6 and in PDX models of HBL, demonstrated the essential role of the ph-S675-β-catenin-TCF4-CEGRs/ALCDs axis in the development of aggressive HBL.