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The combination of gemcitabine with platinum agents is a widely used chemotherapy regimen for a number of tumour types. Gemcitabine plus cisplatin remains the current therapeutic choice for biliary tract cancer. Gemcitabine is associated with multiple cellular drug resistance mechanisms and other limitations and has thereforelined in use. NUC-1031 (Acelarin) is a phosphorylated form of gemcitabine, protected by the addition of a phosphoramidate moiety, developed to circumvent the key limitations and generate high levels of the cytotoxic metabolite, dFdCTP. The rationale for combination of gemcitabine and cisplatin is determined by in vitro cytotoxicity. This, however, does not offer an explanation of how these drugs lead to cell death. In this study we investigate the mechanism of action for NUC-1031 combined with cisplatin as a rationale for treatment. NUC-1031 is metabolised to dFdCTP, detectable up to 72 h post-treatment and incorporated into DNA, to stall the cell cycle and cause DNA damage in biliary tract and ovarian cancer cell lines. In combination with cisplatin, DNA damage was increased and occurred earlier compared to monotherapy. The damage associated with NUC-1031 may be potentiated by a second mechanism, via binding the RRM1 subunit of ribonucleotide reductase and perturbing the nucleotide pools; however, this may be mitigated by increased RRM1 expression. The implication of this was investigated in case studies from a Phase I clinical trial to observe whether baseline RRM1 expression in tumour tissue at time of diagnosis correlates with patient survival.

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The capacity to deal with stress declines during the aging process, and preservation of cellular stress responses is critical to healthy aging. The unfolded protein response of the endoplasmic reticulum (UPRER) is one such conserved mechanism, which is critical for the maintenance of several major functions of the ER during stress, including protein folding and lipid metabolism. Hyperactivation of the UPRER by overexpression of the major transcription factor, xbp-1s, solely in neurons drives lifespan extension as neurons send a neurotransmitter-based signal to other tissue to activate UPRER in a non-autonomous fashion. Previous work identified serotonergic and dopaminergic neurons in this signaling paradigm. To further expand our understanding of the neural circuitry that underlies the non-autonomous signaling of ER stress, we activated UPRER solely in glutamatergic, octopaminergic, and GABAergic neurons in C. elegans and paired whole-body transcriptomic analysis with functional assays. We found that UPRER-induced signals from glutamatergic neurons increased expression of canonical protein homeostasis pathways and octopaminergic neurons promoted pathogen response pathways, while minor, but statistically significant changes were observed in lipid metabolism-related genes with GABAergic UPRER activation. These findings provide further evidence for the distinct role neuronal subtypes play in driving the diverse response to ER stress.

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Humans are living longer, but this is accompanied by an increased incidence of age-related chronic diseases. Many of these diseases are influenced by age-associated metabolic dysregulation, but how metabolism changes in multiple organs during aging in males and females is not known. Answering this could reveal new mechanisms of aging and age-targeted therapeutics. In this study, we describe how metabolism changes in 12 organs in male and female mice at 5 different ages. Organs show distinct patterns of metabolic aging that are affected by sex differently. Hydroxyproline shows the most consistent change across the dataset, decreasing with age in 11 out of 12 organs investigated. We also developed a metabolic aging clock that predicts biological age and identified alpha-ketoglutarate, previously shown to extend lifespan in mice, as a key predictor of age. Our results reveal fundamental insights into the aging process and identify new therapeutic targets to maintain organ health.

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Despite the higher incidence of cancer with increasing age, few preclinical or clinical studies incorporate age. This, coupled with an aging world population, requires that we improve our understanding of how aging affects cancer development, progression, and treatment. One key area will be how the tumor microenvironment (TME) changes with age. Metabolite levels are an essential component of the TME, and they are affected by the metabolic requirements of the cells present and systemic metabolite availability. These factors are affected by aging, causing different TME metabolic states between young and older adults. In this review, we will summarize what is known about how aging impacts the TME metabolic state, and suggest how we can improve our understanding of it.

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INTRODUCTION: Fluoropyrimidines, principally 5-fluorouracil (5-FU), remain a key component of chemotherapy regimens for multiple cancer types, in particular colorectal and other gastrointestinal malignancies. To overcome key limitations and pharmacologic challenges that hinder the clinical utility of 5-FU, NUC-3373, a phosphoramidate transformation of 5-fluorodeoxyuridine, was designed to improve the efficacy and safety profile as well as the administration challenges associated with 5-FU. METHODS: Human colorectal cancer cell lines HCT116 and SW480 were treated with sub-IC50 doses of NUC-3373 or 5-FU. Intracellular activation was measured by LC-MS. Western blot was performed to determine binding of the active anti-cancer metabolite FdUMP to thymidylate synthase (TS) and DNA damage. RESULTS: We demonstrated that NUC-3373 generates more FdUMP than 5-FU, resulting in a more potent inhibition of TS, DNA misincorporation and subsequent cell cycle arrest and DNA damage in vitro. Unlike 5-FU, the thymineless death induced by NUC-3373 was rescued by the concurrent addition of exogenous thymidine. 5-FU cytotoxicity, however, was only reversed by supplementation with uridine, a treatment used to reduce 5-FU-induced toxicities in the clinic. This is in line with our findings that 5-FU generates FUTP which is incorporated into RNA, a mechanism known to underlie the myelosuppression and gastrointestinal inflammation associated with 5-FU. CONCLUSION: Taken together, these results highlight key differences between NUC-3373 and 5-FU that are driven by the anti-cancer metabolites generated. NUC-3373 is a potent inhibitor of TS that also causes DNA-directed damage. These data support the preliminary clinical evidence that suggest NUC-3373 has a favorable safety profile in patients.

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The pancreatic tumor microenvironment drives deregulated nutrient availability. Accordingly, pancreatic cancer cells require metabolic adaptations to survive and proliferate. Pancreatic cancer subtypes have been characterized by transcriptional and functional differences, with subtypes reported to exist within the same tumor. However, it remains unclear if this diversity extends to metabolic programming. Here, using metabolomic profiling and functional interrogation of metabolic dependencies, we identify two distinct metabolic subclasses among neoplastic populations within individual human and mouse tumors. Furthermore, these populations are poised for metabolic cross-talk, and in examining this, we find an unexpected role for asparagine supporting proliferation during limited respiration. Constitutive GCN2 activation permits ATF4 signaling in one subtype, driving excess asparagine production. Asparagine release provides resistance during impaired respiration, enabling symbiosis. Functionally, availability of exogenous asparagine during limited respiration indirectly supports maintenance of aspartate pools, a rate-limiting biosynthetic precursor. Conversely, depletion of extracellular asparagine with PEG-asparaginase sensitizes tumors to mitochondrial targeting with phenformin.

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The classification of biological neuron types and networks poses challenges to the full understanding of the human brain's organisation and functioning. In this paper, we develop a novel objective classification model of biological neuronal morphology and electrical types and their networks, based on the attributes of neuronal communication using supervised machine learning solutions. This presents advantages compared to the existing approaches in neuroinformatics since the data related to mutual information or delay between neurons obtained from spike trains are more abundant than conventional morphological data. We constructed two open-access computational platforms of various neuronal circuits from the Blue Brain Project realistic models, named Neurpy and Neurgen. Then, we investigated how we could perform network tomography with cortical neuronal circuits for the morphological, topological and electrical classification of neurons. We extracted the simulated data of 10,000 network topology combinations with five layers, 25 morphological type (m-type) cells, and 14 electrical type (e-type) cells. We applied the data to several different classifiers (including Support Vector Machine (SVM), Decision Trees, Random Forest, and Artificial Neural Networks). We achieved accuracies of up to 70%, and the inference of biological network structures using network tomography reached up to 65% of accuracy. Objective classification of biological networks can be achieved with cascaded machine learning methods using neuron communication data. SVM methods seem to perform better amongst used techniques. Our research not only contributes to existing classification efforts but sets the road-map for future usage of brain-machine interfaces towards an in vivo objective classification of neurons as a sensing mechanism of the brain's structure.

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EBV gene expression is repressed during viral latency to prevent an immune response, but it is not known how metabolism contributes to this silencing. In this issue of Cell Metabolism, Guo et al. describe how methionine restriction reactivates the expression of EBV genes, offering new therapeutic approaches against EBV-driven diseases.

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Aim: A model of progressively endocrine-resistant breast cancer was investigated to identify changes that can occur in signaling pathways after endocrine manipulation. Methods: The MCF7 breast cancer model is sensitive to estrogens and anti-estrogens while variant lines previously derived from wild-type MCF7 are either relatively 17ß-estradiol (E2)-insensitive (LCC1) or fully resistant to estrogen and anti-estrogens (LCC9). Results: In LCC1 and LCC9 cell lines, loss of estrogen sensitivity was accompanied by loss of growth response to transforming growth factor alpha (TGFα), heregulin-beta and pertuzumab. LCC1 and LCC9 cells had enhanced AKT phosphorylation relative to MCF7 which was reflected in downstream activation of phospho-mechanistic target of rapamycin (mTOR), phospho-S6, and phospho-estrogen receptor alpha Ser167 [ERα(Ser167)]. Both AKT2 and AKT3 were phosphorylated in the resistant cell lines, but small interfering RNA (siRNA) knockdown suggested that all three AKT isoforms contributed to growth response. ERα(Ser118) phosphorylation was increased by E2 and TGFα in MCF7, by E2 only in LCC1, but by neither in LCC9 cells. Multiple alterations in E2-mediated cell cycle control were identified in the endocrine-resistant cell lines including increased expression of MYC, cyclin A1, cyclin D1, cyclin-dependent kinase 1 (CDK1), CDK2, and hyperphosphorylated retinoblastoma protein (ppRb), whereas p21 and p27 were reduced. Estrogen modulated expression of these regulators in MCF7 and LCC1 cells but not in LCC9 cells. Seliciclib inhibited CDK2 activation in MCF7 cells but not in resistant variants; in all lines, it reduced ppRb, increased p53 associated responses including p21, p53 up-regulated modulator of apoptosis (PUMA), and p53 apoptosis-inducing protein 1 (p53AIP1), inhibited growth, and produced G2/M block and apoptosis. Conclusions: Multiple changes occur with progression of endocrine resistance in this model with AKT activation contributing to E2 insensitivity and loss of ERα(Ser118) phosphorylation being associated with full resistance. Cell cycle regulation is modified in endocrine-resistant breast cancer cells, and seliciclib is effective in both endocrine-sensitive and resistant diseases.

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Viruses hijack host cell metabolism to acquire the building blocks required for replication. Understanding how SARS-CoV-2 alters host cell metabolism may lead to potential treatments for COVID-19. Here we profile metabolic changes conferred by SARS-CoV-2 infection in kidney epithelial cells and lung air-liquid interface (ALI) cultures, and show that SARS-CoV-2 infection increases glucose carbon entry into the TCA cycle via increased pyruvate carboxylase expression. SARS-CoV-2 also reduces oxidative glutamine metabolism while maintaining reductive carboxylation. Consistent with these changes, SARS-CoV-2 infection increases the activity of mTORC1 in cell lines and lung ALI cultures. Lastly, we show evidence of mTORC1 activation in COVID-19 patient lung tissue, and that mTORC1 inhibitors reduce viral replication in kidney epithelial cells and lung ALI cultures. Our results suggest that targeting mTORC1 may be a feasible treatment strategy for COVID-19 patients, although further studies are required to determine the mechanism of inhibition and potential efficacy in patients.

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Mitochondrial respiration is critical for cell proliferation. In addition to producing ATP, respiration generates biosynthetic precursors, such as aspartate, an essential substrate for nucleotide synthesis. Here, we show that in addition to depleting intracellular aspartate, electron transport chain (ETC) inhibition depletes aspartate-derived asparagine, increases ATF4 levels, and impairs mTOR complex I (mTORC1) activity. Exogenous asparagine restores proliferation, ATF4 and mTORC1 activities, and mTORC1-dependent nucleotide synthesis in the context of ETC inhibition, suggesting that asparagine communicates active respiration to ATF4 and mTORC1. Finally, we show that combination of the ETC inhibitor metformin, which limits tumor asparagine synthesis, and either asparaginase or dietary asparagine restriction, which limit tumor asparagine consumption, effectively impairs tumor growth in multiple mouse models of cancer. Because environmental asparagine is sufficient to restore tumor growth in the context of respiration impairment, our findings suggest that asparagine synthesis is a fundamental purpose of tumor mitochondrial respiration, which can be harnessed for therapeutic benefit to cancer patients.

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BACKGROUND: Statins inhibit HMG-CoA reductase, the rate-limiting enzyme of the mevalonate pathway. Epidemiological and pre-clinical evidence support an association between statin use and delayed prostate cancer (PCa) progression. Here, we evaluated the effects of neoadjuvant fluvastatin treatment on markers of cell proliferation and apoptosis in men with localized PCa. METHODS: Thirty-three men were treated daily with 80 mg fluvastatin for 4-12 weeks in a single-arm window-of-opportunity study between diagnosis of localized PCa and radical prostatectomy (RP) (ClinicalTrials.gov: NCT01992042). Percent Ki67 and cleaved Caspase-3 (CC3)-positive cells in tumor tissues were evaluated in 23 patients by immunohistochemistry before and after treatment. Serum and intraprostatic fluvastatin concentrations were quantified by liquid chromatography-mass spectrometry. RESULTS: Baseline characteristics included a median prostate-specific antigen (PSA) level of 6.48 ng/mL (IQR: 4.21-10.33). The median duration of fluvastatin treatment was 49 days (range: 27-102). Median serum low-density lipoprotein levels decreased by 35% after treatment, indicating patient compliance. Median PSA decreased by 12%, but this was not statistically significant in our small cohort. The mean fluvastatin concentration measured in the serum was 0.2 µM (range: 0.0-1.1 µM), and in prostatic tissue was 8.5 nM (range: 0.0-77.0 nM). At these concentrations, fluvastatin induced PCa cell death in vitro in a dose- and time-dependent manner. In patients, fluvastatin treatment did not significantly alter intratumoral Ki67 positivity; however, a median 2.7-fold increase in CC3 positivity (95% CI: 1.9-5.0, p = 0.007) was observed in post-fluvastatin RP tissues compared with matched pre-treatment biopsy controls. In a subset analysis, this increase in CC3 was more pronounced in men on fluvastatin for >50 days. CONCLUSIONS: Fluvastatin prior to RP achieves measurable drug concentrations in prostatic tissue and is associated with promising effects on tumor cell apoptosis. These data warrant further investigation into the anti-neoplastic effects of statins in prostate tissue.

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Gemcitabine is a fluoropyrimidine analogue that is used as a mainstay of chemotherapy treatment for pancreatic and ovarian cancers, amongst others. Despite its widespread use, gemcitabine achieves responses in less than 10% of patients with metastatic pancreatic cancer and has a very limited impact on overall survival due to intrinsic and acquired resistance. NUC-1031 (Acelarin), a phosphoramidate transformation of gemcitabine, was the first anti-cancer ProTide to enter the clinic. We find it displays important in vitro cytotoxicity differences to gemcitabine, and a genome-wide CRISPR/Cas9 genetic screening approach identified only the pyrimidine metabolism pathway as modifying cancer cell sensitivity to NUC-1031. Low deoxycytidine kinase expression in tumour biopsies from patients treated with gemcitabine, assessed by immunostaining and image analysis, correlates with a poor prognosis, but there is no such correlation in tumour biopsies from a Phase I cohort treated with NUC-1031.

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OBJECTIVE: The statin family of cholesterol-lowering drugs has been shown to induce tumor-specific apoptosis by inhibiting the rate-limiting enzyme of the mevalonate (MVA) pathway, HMG-CoA reductase (HMGCR). Accumulating evidence suggests that statin use may delay prostate cancer (PCa) progression in a subset of patients; however, the determinants of statin drug sensitivity in PCa remain unclear. Our goal was to identify molecular features of statin-sensitive PCa and opportunities to potentiate statin-induced PCa cell death. METHODS: Deregulation of HMGCR expression in PCa was evaluated by immunohistochemistry. The response of PCa cell lines to fluvastatin-mediated HMGCR inhibition was assessed using cell viability and apoptosis assays. Activation of the sterol-regulated feedback loop of the MVA pathway, which was hypothesized to modulate statin sensitivity in PCa, was also evaluated. Inhibition of this statin-induced feedback loop was performed using RNA interference or small molecule inhibitors. The achievable levels of fluvastatin in mouse prostate tissue were measured using liquid chromatography-mass spectrometry. RESULTS: High HMGCR expression in PCa was associated with poor prognosis; however, not all PCa cell lines underwent apoptosis in response to treatment with physiologically-achievable concentrations of fluvastatin. Rather, most cell lines initiated a feedback response mediated by sterol regulatory element-binding protein 2 (SREBP2), which led to the further upregulation of HMGCR and other lipid metabolism genes. Overcoming this feedback mechanism by knocking down or inhibiting SREBP2 potentiated fluvastatin-induced PCa cell death. Notably, we demonstrated that this feedback loop is pharmacologically-actionable, as the drug dipyridamole can be used to block fluvastatin-induced SREBP activation and augment apoptosis in statin-insensitive PCa cells. CONCLUSION: Our study implicates statin-induced SREBP2 activation as a PCa vulnerability that can be exploited for therapeutic purposes using clinically-approved agents.

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MYC is an oncogenic driver that regulates transcriptional activation and repression. Surprisingly, mechanisms by which MYC promotes malignant transformation remain unclear. We demonstrate that MYC interacts with the G9a H3K9-methyltransferase complex to control transcriptional repression. Inhibiting G9a hinders MYC chromatin binding at MYC-repressed genes and de-represses gene expression. By identifying the MYC box II region as essential for MYC-G9a interaction, a long-standing missing link between MYC transformation and gene repression is unveiled. Across breast cancer cell lines, the anti-proliferative response to G9a pharmacological inhibition correlates with MYC sensitivity and gene signatures. Consistently, genetically depleting G9a in vivo suppresses MYC-dependent tumor growth. These findings unveil G9a as an epigenetic regulator of MYC transcriptional repression and a therapeutic vulnerability in MYC-driven cancers.

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The metabolic state of a cell is influenced by cell-extrinsic factors, including nutrient availability and growth factor signaling. Here, we present extracellular matrix (ECM) remodeling as another fundamental node of cell-extrinsic metabolic regulation. Unbiased analysis of glycolytic drivers identified the hyaluronan-mediated motility receptor as being among the most highly correlated with glycolysis in cancer. Confirming a mechanistic link between the ECM component hyaluronan and metabolism, treatment of cells and xenografts with hyaluronidase triggers a robust increase in glycolysis. This is largely achieved through rapid receptor tyrosine kinase-mediated induction of the mRNA decay factor ZFP36, which targets TXNIP transcripts for degradation. Because TXNIP promotes internalization of the glucose transporter GLUT1, its acute decline enriches GLUT1 at the plasma membrane. Functionally, induction of glycolysis by hyaluronidase is required for concomitant acceleration of cell migration. This interconnection between ECM remodeling and metabolism is exhibited in dynamic tissue states, including tumorigenesis and embryogenesis.

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The statin family of drugs preferentially triggers tumor cell apoptosis by depleting mevalonate pathway metabolites farnesyl pyrophosphate (FPP) and geranylgeranyl pyrophosphate (GGPP), which are used for protein prenylation, including the oncoproteins of the RAS superfamily. However, accumulating data indicate that activation of the RAS superfamily are poor biomarkers of statin sensitivity, and the mechanism of statin-induced tumor-specific apoptosis remains unclear. Here we demonstrate that cancer cell death triggered by statins can be uncoupled from prenylation of the RAS superfamily of oncoproteins. Ectopic expression of different members of the RAS superfamily did not uniformly sensitize cells to fluvastatin, indicating that increased cellular demand for protein prenylation cannot explain increased statin sensitivity. Although ectopic expression of HRAS increased statin sensitivity, expression of myristoylated HRAS did not rescue this effect. HRAS-induced epithelial-to-mesenchymal transition (EMT) through activation of zinc finger E-box binding homeobox 1 (ZEB1) sensitized tumor cells to the antiproliferative activity of statins, and induction of EMT by ZEB1 was sufficient to phenocopy the increase in fluvastatin sensitivity; knocking out ZEB1 reversed this effect. Publicly available gene expression and statin sensitivity data indicated that enrichment of EMT features was associated with increased sensitivity to statins in a large panel of cancer cell lines across multiple cancer types. These results indicate that the anticancer effect of statins is independent from prenylation of RAS family proteins and is associated with a cancer cell EMT phenotype.Significance: The use of statins to target cancer cell EMT may be useful as a therapy to block cancer progression. Cancer Res; 78(5); 1347-57. ©2017 AACR.

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BACKGROUND: Metastatic clear cell renal cell cancer (mccRCC) portends a poor prognosis and urgently requires better clinical tools for prognostication as well as for prediction of response to treatment. Considerable investment in molecular risk stratification has sought to overcome the performance ceiling encountered by methods restricted to traditional clinical parameters. However, replication of results has proven challenging, and intratumoural heterogeneity (ITH) may confound attempts at tissue-based stratification. METHODS: We investigated the influence of confounding ITH on the performance of a novel molecular prognostic model, enabled by pathologist-guided multiregion sampling (n = 183) of geographically separated mccRCC cohorts from the SuMR trial (development, n = 22) and the SCOTRRCC study (validation, n = 22). Tumour protein levels quantified by reverse phase protein array (RPPA) were investigated alongside clinical variables. Regularised wrapper selection identified features for Cox multivariate analysis with overall survival as the primary endpoint. RESULTS: The optimal subset of variables in the final stratification model consisted of N-cadherin, EPCAM, Age, mTOR (NEAT). Risk groups from NEAT had a markedly different prognosis in the validation cohort (log-rank p = 7.62 × 10-7; hazard ratio (HR) 37.9, 95% confidence interval 4.1-353.8) and 2-year survival rates (accuracy = 82%, Matthews correlation coefficient = 0.62). Comparisons with established clinico-pathological scores suggest favourable performance for NEAT (Net reclassification improvement 7.1% vs International Metastatic Database Consortium score, 25.4% vs Memorial Sloan Kettering Cancer Center score). Limitations include the relatively small cohorts and associated wide confidence intervals on predictive performance. Our multiregion sampling approach enabled investigation of NEAT validation when limiting the number of samples analysed per tumour, which significantly degraded performance. Indeed, sample selection could change risk group assignment for 64% of patients, and prognostication with one sample per patient performed only slightly better than random expectation (median logHR = 0.109). Low grade tissue was associated with 3.5-fold greater variation in predicted risk than high grade (p = 0.044). CONCLUSIONS: This case study in mccRCC quantitatively demonstrates the critical importance of tumour sampling for the success of molecular biomarker studies research where ITH is a factor. The NEAT model shows promise for mccRCC prognostication and warrants follow-up in larger cohorts. Our work evidences actionable parameters to guide sample collection (tumour coverage, size, grade) to inform the development of reproducible molecular risk stratification methods.

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Hypoxic cancer cells exhibit resistance to many therapies. This study compared the therapeutic effect of targeting the pH regulatory proteins (CAIX, NHE1 and V-ATPase) that permit cancer cells to adapt to hypoxic conditions, using both 2D and 3D culture models. Drugs targeting CAIX, NHE1 and V-ATPase exhibited anti-proliferative effects in MCF-7, MDA-MB-231 and HBL-100 breast cancer cell lines in 2D. Protein and gene expression analysis in 2D showed that CAIX was the most hypoxia-inducible protein of the 3 targets. However, the expression of CAIX differed between the 3 cell lines. This difference in CAIX expression in hypoxia was consistent with a varying activity of FIH-1 between the cell lines. 3D expression analysis demonstrated that both CAIX and NHE1 were up-regulated in the hypoxic areas of multicellular tumor spheroids. However, the induction of CAIX expression in hypoxia was again cell line dependent. 3D invasion assays conducted with spheroids showed that CAIX inhibition significantly reduced the invasion of cells. Finally, the capability of both NHE1 and CAIX inhibitors to combine effectively with irradiation was exhibited in clonogenic assays. Proteomic-mass-spectrometric analysis indicated that CAIX inhibition might be combining with irradiation through stimulating apoptotic cell death. Of the three proteins, CAIX represents the target with the most promise for the treatment of breast cancer.

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Targeted cancer therapy aims to disrupt aberrant cellular signalling pathways. Biomarkers are surrogates of pathway state, but there is limited success in translating candidate biomarkers to clinical practice due to the intrinsic complexity of pathway networks. Systems biology approaches afford better understanding of complex, dynamical interactions in signalling pathways targeted by anticancer drugs. However, adoption of dynamical modelling by clinicians and biologists is impeded by model inaccessibility. Drawing on computer games technology, we present a novel visualization toolkit, SiViT, that converts systems biology models of cancer cell signalling into interactive simulations that can be used without specialist computational expertise. SiViT allows clinicians and biologists to directly introduce for example loss of function mutations and specific inhibitors. SiViT animates the effects of these introductions on pathway dynamics, suggesting further experiments and assessing candidate biomarker effectiveness. In a systems biology model of Her2 signalling we experimentally validated predictions using SiViT, revealing the dynamics of biomarkers of drug resistance and highlighting the role of pathway crosstalk. No model is ever complete: the iteration of real data and simulation facilitates continued evolution of more accurate, useful models. SiViT will make accessible libraries of models to support preclinical research, combinatorial strategy design and biomarker discovery.

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