Analysis of the TMZ resistant (TMZres) variants in conjunction with their parental, sensitive cell lines shows that acquisition of TMZ resistance is accompanied by broad phenotypic changes, including increased proliferation, migration, chromosomal aberrations, and secretion of cytosolic lipids. Importantly, each TMZ resistant model captures a different facet of the “go” (8MGBA-TMZres) or “grow” (42MGBA-TMZres) hypothesis of GBM behavior. These in vitro model systems will be important additions to the available tools for investigators seeking to define molecular mechanisms of acquired TMZ resistance.Glioblastoma (GBM) is an aggressive and incurable tumor of the brain with limited treatment options. Current first-line standard of care is the DNA alkylating agent temozolomide (TMZ), but this treatment strategy adds only ~4 months to median survival due to the rapid development of resistance. While some mechanisms of TMZ resistance have been identified, they are not fully understood. There are few effective strategies to manage therapy resistant GBM, and we lack diverse preclinical models of acquired TMZ resistance in which to test therapeutic strategies on TMZ resistant GBM. In this study, we create and characterize two new GBM cell lines resistant to TMZ  Over the past 33 years – 1980–2013 – 570 clinical trials were conducted where almost 33,000 patients were treated with different novel therapeutics to better understand and treat GBM2. From these extensive studies one chemotherapeutic agent – temozolomide (TMZ) – was found to moderately improve overall survival3. In the last decade there has been little advancement in treatment, with the standard of care being radiotherapy and surgery, followed by TMZ4. However, resistance to TMZ is rapid, and a broadly effective second line of treatment has not yet been established5. For these reasons, we need better models to understand mechanisms of TMZ resistance and how to develop improved therapies for the future.Glioblastoma (GBM) is the most common glioma among adults and confers an abysmally low overall survival with only 5% of patients surviving at the 5-year markN7-guanine, N3-adenine, and O6-guanine positions. The cytotoxic effect was shown to be mainly through the O6-guanine adduct, which can be reversed by the O6-methylguanine methyl transferase (MGMT). MGMT is a suicide repair protein which removes the O6-guanine adduct and allows for proper DNA repair6. Even with this information, targeting MGMT with both small molecule drugs and mimetics has been unsuccessful, and its expression does not always correlate with resistance to TMZ11. Therefore, new models of resistance need to be developed in order to better define molecular mechanisms of GBM resistance to TMZ.Cell line models have been invaluable in elucidating the molecular mechanisms behind the uncontrolled growth of cancer cells. As resistance to TMZ is rapid in clinical models, cell lines were used to better understand the mechanism behind the initial efficacy of TMZ sensitivity. TMZ is a prodrug that is preferentially activated in a more alkaline environment, which the brain provides, that spontaneously breaks down to highly reactive methyldiazonium cations. These byproducts preferentially methylate DNA bases at the 12. After continual exposure to TMZ in culture, both cell lines no longer undergo TMZ-mediated G2/M arrest. As the cell lines acquired resistance to TMZ both cell lines gained expression of MGMT, showed an increase in nuclear size and chromosome number, and an increase of early endosomes and extracellular lipids. However, as they differed in their growth and migratory capacity, these cell lines may give us insight into the “go or grow” model for GBM recurrence13. The 42MGBA-TMZ resistant cell line had an increase in growth capturing the “go” of the “go or grow” model for resistance. By contrast, the 8MBGA-TMZ resistant cell line had an increase in migration, encompassing the “grow” aspect of resistance. These models will be useful tools for the field to better define essential drug resistance mechanisms in GBM. These two TMZ-resistant (TMZres) models from both a male and female patient have evolved distinct resistant phenotypes and therefore serve as valuable resources to investigate the heterogeneity of TMZ-resistant GBM.In this study, we present two unique TMZ-resistant GBM cell lines derived from the 42MGBA and 8MGBA parental lines which were first characterized in 1997. The 42MGBA line was derived from a temporal lobe tumor resected from a 63-year old male. The 8MGBA line was derived from a frontal lobe tumor resected from a 54-year old femaleTo better recapitulate acute temozolomide (TMZ) resistance models, we created cell lines that were resistant to 200 µM TMZ and were challenged in 100 µM TMZ for all experiments. The overall time to acquired resistance varied from approximately 2 months for the 8MBGA cell line to ~3 months for the 42MBGA cell line. Cells were defined as resistant when each no longer showed a G2/M arrest or apoptosis in response to TMZ treatment Fig. . While b14. Because BCNU can still be a component of second-line treatment for GBM18, we tested whether our TMZres cells exhibited altered responsiveness to BCNU. Since the resistant cell lines are populations selected from the wild type cell lines they have a more reproducible phenotype as the variability or heterogeneity of the cell line has decreased. Therefore, the TMZres cells still showed a statistically significant G2/M arrest upon BCNU treatment. However the biological effect is dramatically reduced, with a 74% increase in G2/M vs 8% increase in G2/M for the 42MBGA-WT vs. 42MBGA-TMZres cells compared to controls, respectively , leads to an increased sensitivity to TMZely Fig. . This isely Fig. .5. As cells have already copied their DNA at this point in the cell cycle, if a cell is to survive TMZ-treatment they may also be retaining the extra copies of chromosomes that have already been duplicated. The 42MGBA-WT cell line has a hypertetraploid karyotype (88–95 chromosomes) with 8% polyploidy, while the 8MGBA-WT cell line has a hyperdiploid karyotype with 15% polyploidy and contains 47–52 chromosomes . 42MGBA-TMZres cells showed a significant increase in total nuclear area  . We observed that 96% of the 42MBGA-TMZres cells had three or more copies of the X chromosome compared to only 7% of the 42MBGA-WT cells (93% of those cells had 2 copies). In contrast, this dramatic shift was not observed in 8MBGA-TMZres cells, where only a small subpopulation of cells showed an increase in the number of chromosomes 17 (18% had 3 or more copies) compared to the parental cells (6% had 3 or more copies). Taken together, these findings tracked with the stability of TMZ-resistance, with the 42MBGA-TMZres cells showing a more stable phenotype compared to 8MBGA-TMZres cells . We observed an increase in overall chromosome number in the majority of the 42MBGA-TMZres cells in contrast to the 8MBGA-TMZres cells where only a small subpopulation of cells had an increase in overall chromosome number Fig. . We alsoSH) Fig. . The cholls Fig. .Figure 3We then determined how TMZ-resistance affected cell size and proliferative vs migratory phenotypes. 42MBGA-TMZres cell size was not changed vs 42MGBA-WT, though their basal growth rate was dramatically increased Fig. . They al19. Consistent with our observation of increased extracellular vesicles, there was an increase in palmitic acid and stearic acid lipids in the GC-TOF-MS metabolites from the 8MBGA-TMZres cell line conditioned media  are implicated in TMZ responsiveness26.The enrichment of lipid metabolites and aminomalonate identified in conditioned media from resistant cells by LC-MS and GC-TOF-MS, respectively, could suggest dysregulation of mitochondrial metabolism. We therefore determined whether the expression of electron transport chain (ETC) subunits is altered between sensitive and resistant lines. There were no changes between ETC subunits in the 42MBGA-WT and -TMZres lines. However, there was an increase in three ETC subunits in the 8MBGA-TMZres cell line as compared to its WT control: MT-CO1 (Complex IV), SDHB (Complex II), and NDUFB8 (Complex I) Fig. . Increasin vitro. True to the heterogeneous nature of clinical GBM, the phenotypes displayed by these resistant cells were similar, but not identical. TMZ treatment no longer induced G2/M arrest in either of these cell lines, and both were markedly less responsive to BCNU, the previous standard of care for GBM. Both resistant cell lines also gained expression of the MGMT protein, which is responsible for removing one of the DNA adducts caused by TMZ treatment5.In the present study, we created two new GBM cell lines that are resistant to the standard of care drug TMZ 18. These TMZres cell line pairs may therefore also prove to be valuable resources for defining contexts in which BCNU is or is not appropriate second-line treatment, and for identifying other, more appropriate therapies for TMZ-resistant GBM.An important finding of the present study is that both TMZres models have severely impaired response to BCNU. For decades BCNU was the standard of care for GBM, and it is still a component of some second-line regimens. Findings from clinical studies examining the efficacy of BCNU in recurrent GBM post-TMZ treatment are inconsistent, with some suggesting BCNU remains active while others demonstrate no benefitin vitro as opposed to isolation from a resistant tumor is the ability to directly compare them to their respective sensitive parental lines. There was an increase in nuclear size in both resistant cell lines when compared with their parental cell lines. In the 42MGBA-TMZres cell line there was also a change in nuclear morphology which has been described in other GBM cell lines that have acquired resistance to TMZ28. This may be associated with stability of the resistant phenotype, as we observed that the 42MBGA-TMZres cell line resistant phenotype can be maintained without continuous TMZ treatment. However, the 8MGBA-TMZres cell line, which has not undergone nuclear structure reorganization, and showed two distinct populations with respect to metaphase spreads, regained partial sensitivity when cultured in the absence of TMZ.A key advantage provided by creating these resistant cell lines 29. In these novel TMZ resistant models, we hypothesized that the increase in nuclear size was a function of retained chromosomes. This is consistent with the mechanism of action of TMZ, which induces a G2/M arrest in cells. Cells which escape TMZ-mediated cell cycle arrest and death have already replicated their DNA, and may therefore retain sister chromatids that were not able to separate during anaphase. Because both parental GBM cell lines were initially polyploid with distinct karyotypes, we assessed two different chromosomes – 17 for the 8MBGA-WT and –TMZres cell lines, and X for the 42MBGA-WT and –TMZres cell lines – as an indicator for chromosomal copy number alterations. Both TMZ resistant variants showed significant copy number gains. Of note, our chromosome 17 locus specific probe targets the STAT5 gene, which has already been implicated as a pro-tumorigenic factor in GBM30. The increased copy number of the STAT5 locus in the 8MBGA-TMZres cell line is consistent with previous work and suggests that the observed increase in nuclear size is at least partially attributable to an increase in chromosome number. Because chromosome 17 existed in multiple copies in the 42MBGA-WT cell line, we chose an X-centromeric probe to test chromosomal copy number changes in the 42MBGA-TMZres line. Again, we saw an increase in X-chromosome copy number in the 42MBGA-TMZres line, and an overall increase in the total number of chromosomes. While it can be energetically disadvantageous to increase ploidy, we hypothesize that, as for STAT5, there may be X chromosome genes that when duplicated give a proliferative advantage to these cells.Increases in nuclear size can be driven by increased chromosome numbers or impaired transport of mRNA or proteins out of the nucleus31. However, these phenotypes are rarely displayed by the same cells, giving rise to the “go or grow” hypothesis to explain aggressive behavior and drug resistance28. Our novel in vitro models of TMZ-resistant GBM provide examples of both phenotypes. The 42MBGA-TMZres cell line did not exhibit any significant changes in migration, cytoskeletal structure, or cell size when compared to its parental cell line, but it did proliferate significantly faster. In contrast, the 8MBGA-TMZres cell line had a significantly increased migratory capacity, F-actin thickness, and overall cell size relative to 8MGBA-WT cells, but no accompanying increase in proliferation. These divergent alterations in basal growth rate and migratory capacity provide two unique models – one adapting the “go” (8MGBA-TMZres) and the other the “grow” (42MBGA-TMZres) strategy of TMZ resistance13. There have been many hypotheses as to what determines the switch between “go or grow”, including mutational status, hypoxia, and influences of the surrounding cell secretome33. Activation of the FAK and MAPK/ERK pathways have been shown to be differentially regulated between a “go” and “grow” phenotype33, respectively. Others have also hypothesized that remaining cells from the “go” population lead to recurrence of GBM13. Therefore, more insight needs to be gained into potential common pathways between the “go or grow” phenotypes that could be used as therapeutic targets for both cell populations. Candidate strategies to revert “go” phenotypes could include inhibition of the integrin signaling axis, either through blockade of integrin engagement35 or inhibition of FAK36, while MEK inhibition could suppress the “grow” phenotype38. These four cell lines are therefore valuable tools that can be used to provide important insight into the differential mechanisms of TMZ resistance.Two major challenges in the clinical management of GBM, particularly after TMZ resistance has developed, are rapid tumor cell proliferation and widespread local migration or invasionin vitro setting, Oliveira et al. showed that the in vitro secretome can affect the “go or grow” phenotype of murine GBM cells32. Therefore is it important to identify potential in vitro mechanisms that can be further extrapolated to in vivo models in the future. The increase in early endosome marker EEA1 expression is interesting, as others have shown EEA1 to interact directly with RRAD, STAT3, and EGFR to regulate EGFR’s subcellular localization and resistance to TMZ39. Clinically, higher EEA1 mRNA expression is associated with poor survival. EGFR and its structural variants have been targeted extensively in GBM, but with limited success. We suggest further study of the mechanisms by which EEA1 contributes to the TMZ resistant phenotype could provide a new way to target EGFR by modifying its subcellular localization rather than activation40. In addition to an accumulation of early endosomes, we observed vesicles expelled into the media of the resistant cell lines. Others have shown that TMZ-resistant glioma stem cells release more exosomes than their sensitive counterparts, which was consistent with our in vitro created models41. This was reflected in the putative increase of lipids from the LC-MS analysis. Another hit, indoleacetaldehyde, is a product of tryptophan metabolism, hyperactivation of which occurs in GBM and is thought to suppress anti-tumor immunity19. Extracellular lipids, stearic and palmitic acid, were also found and validated in the GC-TOF-MS analysis along with citric acid. Citric acid is a key regulator of metabolism, and when increased in the cerebral spinal fluid of GBM patients confers a lower overall survival23. The top hit from GC-TOF-MS was the non-aminogenic amino acid aminomalonate. Aminomalonate inhibits aminolevulinic acid synthase, the rate-limiting enzyme of the protophorphyrin IX (PpI IX)/heme synthesis pathway20. PpI IX pathway activity is exploited for intra-operative imaging in GBM, and has more recently been used for potential therapeutic gain43. Defining the drivers of aminomalonate secretion in our TMZ-resistant models may be an important future strategy to identify when PpI IX pathway-based imaging and therapeutic approaches may be warranted.Acquisition of TMZ resistance was associated with a marked increase in the number of intracellular and extracellular vesicles in our models. While there are always potential limitations to studying metabolism in an In conclusion, we present two novel TMZ-resistant GBM cell lines from both a male and female patient that have distinct proliferative and migratory capacities while sharing certain GBM resistance characteristics such as increased chromosome number, nuclear size, and vesicle formation Fig. . These mMycoplasma contamination, and were maintained in a humidified incubator with 95% air: 5% carbon dioxide. All cell lines were fingerprinted by the LCCC Tissue Culture Shared Resource to verify their authenticity using the standard 9 STR loci and Y-specific amelogenin. Both the 42MBGA-TMZres and 8MGBA-TMZres fingerprinted the same as their parental cell line. 42MGBA and 8MBGA cells were grown in DMEM with 10% FBS. 42MBGA-TMZres and 8MBGA-TMZres cells were grown in DMEM with 10% FBS and 100 µM TMZ. TMZ  was dissolved in DMSO to 130 mM and used at concentrations indicated. Bis-chloroethylnitrosourea (BCNU) was a kind gift from Dr. Esther Chang, and was dissolved in ethanol to 100 mM before use at concentrations indicated.42MBGA and 8MGBA cell lines were provided by Dr. Jeffrey Toretsky (Lombardi Comprehensive Cancer Center (LCCC), Georgetown University, Washington DC). 42MBGA-TMZres and 8MGBA-TMZres were developed by our lab with constant exposure of the parental cell lines to increasing concentrations of TMZ, from 12.5, 25, 50, 100, 200 µM, over the course of 2–3 months. All cells tested negative for On day 0, cells were seeded at 100,000–150,000 cells per well in 6-well plastic tissue culture dishes one day prior to treatment with the indicated concentrations of drug. For experiments with TMZ or BCNU cells were treated for 72 hours. After 72 hour treatments, cells were collected, ethanol-fixed, stained with propidium iodide, and analyzed for cell subG1 (fragmented) DNA content and cell cycle profile by fluorescence activated cell sorting.Cells were lysed in RIPA buffer for protein extractions and separated by a 4–12% gradient gel . They were then transferred onto Nitrocellulose membranes  with the iBlot 2 and probed with antibodies against MGMT , Beta-Tubulin , PARP , Actin , and Electron Transport Chain antibody cocktail . Proteins were detected with horseradish peroxidase-conjugated secondary antibodies  and enhanced chemiluminescent detection HyGLO Quick Spray Chemiluminescent (Denville) for dark room development.44. For metaphase chromosomal copy number determination, chromosomes were stained with 4′,6-diamidino-2-phenylindole (DAPI). FISH analysis was performed using a standard protocol47. A 17q21.1-21.2 locus-specific FISH probe (Stat5A/B locus) was used to evaluate chromosome 17 copy number change in the 8MGBA-TMZres and WT cell lines, as described earlier45. For the X chromosome enumeration in the 42MGBA-TMZres and WT cell lines, an X chromosome centromeric probe obtained from Empire Genomics  was used according a manufacturer’s protocol. Scoring of cells and digital image acquisition were performed using a Leica DMRBE microscope  equipped with the appropriate optical filters and a CCD camera45.Metaphase and interphase slide preparation was done using a standard protocol48 to determine percent closed with 0% being at 0 hr.Cells were plated at 150,000–200,000 cells/well and allowed 48 hours to create a monolayer. After monolayer formation, a P200 tip was used to make the scratch. Images were taken at 0 hr, 24 hr, and 48 hr time points. Analysis was done in ImageJ48) was used to measure the thickness of F-actin fibers. Grayscale images of phalloidin-stained cells were converted to binary using the Threshold tool (black/white). The BoneJ plugin49 was then used to measure fiber thickness in pixels. The mean thickness per cell is reported for 28-29 individual cells per cell line.FIJI  with 0.2% Triton X-100 in PBS for 5 minutes at room temperature. Three washes were performed with PBS in the 12-well plate, then coverslips were inverted onto 100 μl of primary antibody in the antibody block  on strips of parafilm and incubated for one hour. Coverslips were first stained with EEA1 , an early endosomal marker . Phalloidin , and DAPI  stains were added to the secondary antibody mixtures. Each coverslip was washed three times with PBS after primary incubation and then were inverted onto 100 µL of the appropriate secondary antibody, DAPI dihydrochloride, and (where appropriate) ActiStain-488-phalloidin  in antibody block in the dark for 20 minutes. Coverslips were again washed 3x with PBS, then gently dipped three times into molecular biology-grade water before inversion onto one drop of FLUOROGEL  then allowed to air-dry in the dark for at least 10 minutes. Slides were stored at 4 °C until image collection on the LCCC Microscopy & Imaging Shared Resource’s Leica SP8 microscope with the 63x oil objective.2. The 25 µL sample was deproteinized using cold acetonitrile (40%): methanol (25%): water (35%) (175 µL) containing internal standards . All solvents used were LC-MS grade . Samples were vortexed and incubated on ice for 10 min. Incubated samples were centrifuged at 13000 rpm for 20 min at 4 °C. The supernatant was evaporated in a speed-vac with no heat. Dried samples were kept at −80 °C until analysis. For analysis, the dried samples were reconstituted in acetonitrile (1%): methanol (5%): water (94%) (200 µL). Samples were centrifuged for 20 min at 4 °C and the supernatant transferred to a vial for LC-MS analysis. Briefly, samples were injected (2 μL) into a Waters Acquity UPLC system coupled to a Xevo® G2 QTOF-MS using Leucine enkephalin as Lockspray® for accurate mass calibration. Data was processed, aligned, and analyzed using MassLynxTM , XCMS online50, Metaboanalyst, and R51.Cell culture media (500 µL) was concentrated to 25 µL under NInternal standards (1 µM 4-nitrobenzoic acid) were added to culture media (500 μL) that was deproteinized as above and then evaporated in a speed-vac and transferred to a GC vial with a silanized insert. Derivatization and injection was performed with a Gerstel  autosampler with automated liner exchange and cooled injection system. The dry residue was derivatized with 20 μL O-Methoxyamine-Hydrochloride  at 40 °C with constant agitation (30 min), and then with 80 μL of N-Methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA)/with 1% trimethychlorosilane (TMCS) (Thermo Scientific prod # TS48915) at 40 °C with constant agitation (30 min). Samples were incubated at 20 °C for 4 hrs before injection (1.5 μL) for GC-TOF-MS analysis.52. Electron impact ionization (70 eV) at full scan mode (m/z 40–600) was used, with an acquisition rate of 30 spectra/sec. Fatty acid methyl esters , alkanes , and quality control standards  were run to ensure reproducibility of retention indices and derivatization. Data was processed, aligned, and analyzed using ChromaTOF v. 4.51.6.0 with the statistical compare function , Metaboanalyst, and in house software MetaboLyzer53 as previously described52.Samples were injected in split mode (1:5) into an Agilent 7890B GC system  that was coupled to a Pegasus HT TOF-MS . Separation was achieved on a Rtx-5 w/Integra-Guard capillary column , with helium as the carrier gas at a constant flow rate of 1.0 mL/min. The temperature of the inlet, transfer line, and ion source was set to 150, 270, and 230 °C, respectively. The GC temperature programming was set to 0.2 min of isothermal heating at 70 °C, followed by 10 °C/min ramp to 270 °C, a 4.0 min isothermal heating of 270 °C, 20 °C/min ramp to 320 °C, and a 2.0 min isothermal heating of 320 °C as previously describedCells were seeded at a density of 1,000 cells per well in 3, 96-well plastic tissue culture dishes per cell line on day 0. On day 1, one plate was stained with crystal violet . For staining, plates were rinsed 1 time with 1X PBS to remove excess cellular debris. After, 100 µL of 3.2% PFA was added to each well and incubated at room temperature for 5 minutes followed by three washes in 1X PBS. Then, 200 µL of 0.5% crystal violet in 25% methanol was added to each well and incubated at 4 C for 10 min. The stain was then removed and the plate was rinsed 4–6 × with diH2O to remove excess stain. The plates were left to air-dry overnight. On day 8 and 10, all plates were rehydrated with 100% methanol and read at an absorbance of 550 nm.Cell size was determined by the Countess 2 (Invitrogen) using trypan blue dye exclusion of dead cells. The Countess 2 was also used to determine number of cells for 72-hour growth assays. 100,000 cells were seeded per 6-well on day 0. 24, 48, and 72 hours post-seeding, cells were collected and total cell number was determined by trypan blue dye exclusion.51.Results are represented as mean values ± standard error (SD) and considered statistically significant where p-value < 0.05. Three independent biological replicates were done for each experiment, with the exception of metabolomics where six independent replicates were performed. Statistical significance has been calculated using GraphPad Prism version 7.00 for Mac, GraphPad Software, La Jolla California USA (www.graphpad.com) for the Student’s t-test, Mann Whitney U test, one-way ANOVA with Dunnett’s correction, or χ2 analysis of 2 × 3 contingency table. The RStudio packages survival, GGally, ggplot2, readr, and magrittr were used for violin plots and big data sets Supplementary Figures


Mutations to fibroblast growth factor receptor 3 (FGFR3) and phosphatase and tensin homologue (PTEN) signalling pathway components  are common in bladder cancer, yet small-molecule inhibitors of these nodes (FGFR/PTENi) show only modest activity in preclinical models. As activation of autophagy is proposed to promote survival under FGFR/PTENi, we have investigated this relationship in a panel of 18 genetically diverse bladder cell lines. We found that autophagy inhibition does not sensitise bladder cell lines to FGFR/PTENi, but newly identify an autophagy-independent cell death synergy in FGFR3-mutant cell lines between mTOR  pathway inhibitors and chloroquine (CQ)—an anti-malarial drug used as a cancer therapy adjuvant in over 30 clinical trials. The mechanism of synergy is consistent with lysosomal cell death (LCD), including cathepsin-driven caspase activation, and correlates with suppression of cSREBP1 and cholesterol biosynthesis in sensitive cell lines. Remarkably, loss of viability can be rescued by saturating cellular membranes with cholesterol or recapitulated by statin-mediated inhibition, or small interfering RNA knockdown, of enzymes regulating cholesterol metabolism. Modulation of CQ-induced cell death by atorvastatin and cholesterol is reproduced across numerous cell lines, confirming a novel and fundamental role for cholesterol biosynthesis in regulating LCD. Thus, we have catalogued the molecular events underlying cell death induced by CQ in combination with an anticancer therapeutic. Moreover, by revealing a hitherto unknown aspect of lysosomal biology under stress, we propose that suppression of cholesterol metabolism in cancer cells should elicit synergy with CQ and define a novel approach to future cancer treatments. Our data reveal little evidence for autophagy in the promotion of survival under FGFR/PTENi, but highlight an autophagy-independent synergistic cell death between AKT or mTOR inhibition and CQ in FGFR-dependent cell lines.We have investigated a function for autophagy in a panel of 18 bladder cancer cell lines treated with small-molecule inhibitors targeting nodes of potential therapeutic relevance: FGFR, PI3Kβ/δ, AKT and mTOR (FGFR/PTENi). Modulation of cell death was quantified under these conditions and a function for autophagy was assayed by knockdown of multiple essential components , CRISPR/Cas9 Synergistic cell death showed features of lysosome-initiated apoptosis, including cathepsin-dependent caspase activation. We show that inhibition of FGFR/PI3Kα/AKT/mTOR nodes suppress the expression of enzymes regulating cholesterol metabolism in FGFR-dependent cell lines, correlating with the degree to which these compounds potentiate CQ-induced cell death. This form of CQ-driven synergistic cell death is profoundly inhibited by saturating cellular membranes with cholesterol, or recapitulated by inhibiting cholesterol metabolism with atorvastatin (Ato) and knockdown of cholesterol biosynthesis enzymes. Moreover, we found that all FGFR3-mutant cell lines regulate cSREBP1 expression in an mTORC1/2-dependent manner, sensitising these—but not FGFR-wild type (FGFR-WT)—cell lines to CQ-induced cell death under mTORi. These results elucidate how CQ, which is currently being used as a cancer therapy adjuvant in over 30 clinical trials, synergises with inhibitors of mTOR signalling and defines a patient cohort predicted to respond to this combination. This work also highlights a fundamental feature of lysosomal membrane biology, suggesting that cancer therapeutics that impact cholesterol metabolism should combine with CQ and provide an innovative approach to cancer treatment.25 Data relating to RT112, which express constitutively active FGFR3 (FGFR3-TACC3), are shown in 26 RT112 cultures showed marked sensitivity to both FGFRi and mTORi, but tolerated AKTi and PI3Kβi , PI3Kβ/δi (AZD8186), AKTi (AZD5363) and mTORi (AZD2014); and assayed cell death over 5 days.d PI3Kβi . This pad PI3Kβi . Neverthd PI3Kβi . Westernd PI3Kβi .27The contribution of autophagy to survival under FGFR/PTENi was assayed by small interfering RNA (siRNA)-mediated knockdown of key signalling components coupling mTOR to autophagy activation: ATG13, ULK1/2 and VPS34; and the core autophagy protein ATG7 . ConsideATG7 KO clones from RT112 cultures using CRISPR/Cas9. RT112 ATG7 KO cultures were disabled for LC3 lipidation and autophagy  was included to inhibit mTORC1. Over 4 days, a clear difference emerged in the pattern of cell death across the bladder panel, dividing the cell lines into three types . Type-I 28 Overall, this screen shows that chemical autophagy inhibitors do not generally increase the sensitivity of bladder cell lines to AKT or mTOR inhibitors, yet highlights an intriguing response to these compounds in combination with CQ in FGFR-dependent cells.Disruption to autophagy by BafA1 and CQ is confirmed by the accumulation of LC3-II by immunoblotting and immunocytochemistry, revealing that lysosomes swell to 2–5 times their original size under these conditions . In contATG7 KO cells, to demonstrate conclusively that autophagy is unrelated to this cytotoxicity =48 μm; P=0.003) versus wild-type (WT) (cdEC50)=30 μm), their ultimate sensitivity also confirms that CQ-induced cell death is autophagy-independent. CQ is known to cause lysosomal membrane permeabilisation, cathepsin leakage and activation of BID and caspases.30 We therefore investigated the role of cathepsins in caspase activation and cell death induced by CQ in combination with AKTi and mTORi. We find that CASP3 activity is only observed when AKTi or mTORi are combined with CQ, whereas treatment with AKTi, mTORi or CQ alone is not sufficient to induce its activation  expression, which we now found to also underlie mTORi cytotoxicity. Both FGFRi- and mTORi-induced cell death is rescued by oleic acid, the product of SCD1 activity (m) does not induce cell death, but potentiates CQ-induced cell death, we used this concentration for subsequent experiments.34Given that AKTi and mTORi only potentiate CQ-induced cell death in FGFR-dependent cell lines, we investigated how FGFR3 signalling might regulate lysosomal cell death (LCD). A possible link between these two pathways was found in reports showing that (i) FGFR3 maintains the expression of genes required for fatty acid and cholesterol biosynthesis via SREBP1; and (ii) lysosomal cholesterol can regulate membrane integrity and LCD.activity , and corr (R2)=0.871 , but similarly exacerbated by PI3Kαi (P=0.0008 to ctrl) and AKTi . However, inhibition of mTOR (P<0.0001 to ctrl) and FGFR (P=0.0003 to ctrl) further potentiate CQ-induced cell death, although the curve for FGFRi is clearly different to the other conditions, suggesting interference by additional factors. To further investigate cholesterol biosynthesis in CQ-induced LCD, we inhibited HMGCR—a rate-limiting enzyme in cholesterol biosynthesis—with Ato, or saturated cellular membranes with water-soluble cholesterol.37Immunoblotting shows that FGFRi and mTORi fully suppress the expression of cSREBP1 and cholesterol enzymes in RT112 cultures, whereas AKTi and PI3Kαi partially suppress this pathway . RemarkaImportantly, at low doses of CQ, a clear synergy is observed with mTORi and AKTi, which is robustly (mTORi) or completely (AKTi) suppressed by cholesterol . However38c release, before the onset of caspase activation , indicating that CQ may considerably improve the efficacy of these compounds in vivo.49The induction of LCD by CQ has been well characterised in HeLa cells and recently shown to be potentiated by a dual PI3K/AKT inhibitor in neuroblastomas.52 Moreover, we found that all FGFR3-mutant cell lines stabilise cSREBP1 via mTORC1/2, yet do not show the same regulation of cSREBP1, or potentiation of CQ-induced cell death, with FGFRi or AKTi  signalling. This is consistent with reports that SREBP1 is regulated by multiple pathways and indicates that the complete suppression of cSREBP1 is required to maximally potentiate CQ-induced cell death. or AKTi . Since S26 Other transforming RTK mutations may similarly control cholesterol biosynthesis and present opportunities for eliciting synergistic cell death between relevant inhibitors and CQ. We provide proof of principle for this approach by showing that inhibition of cholesterol metabolism with a statin, or knockdown of key cholesterol biosynthesis enzymes, recapitulates synergistic cell death in numerous cell lines. However, in RT112 cells, knockdown of HMGCS1 and DHCR7, or Ato treatment, exacerbated cell death to a similar extent as AKTi, rather than to the level observed with mTORi. Additionally, the suppression of cSREBP1 by mTORi in FGFR3-mutant lines only partially inhibited the expression of cholesterol enzymes, yet resulted in a similar potentiation of CQ toxicity to Ato. Conversely, some FGFR3-WT cells showed mTORi-induced suppression of cholesterol enzyme expression in the absence of changes to cSREBP1 expression and CQ-induced cell death. Thus, additional mechanisms may regulate the expression of these enzymes and the availability of cellular cholesterol, which will require further elucidation.As activating FGFR3 mutations are found in up to 80% of low-grade noninvasive bladder tumours, the combination of CQ with mTOR pathway inhibitors may therefore benefit a substantial population of patients.56 Thus, under inhibition of both cholesterol uptake  and cholesterol biosynthesis , osmotic stress is enhanced, resulting in accelerated membrane permeabilisation, cathepsin release and cell death  neutralisation of the endo/lysosomal system blocks the processing of extracellularly derived cholesterol esters, rendering cells dependent on the biosynthesis pathway; and (ii) lysosomal membrane cholesterol decreases permeability to water and ions, suppressing swelling and destabilization under osmotic stress.Our results delineate for the first time the mechanistic basis for synergy between CQ and a targeted anticancer therapeutic and stress caution in the interpretation of studies reporting enhanced drug efficacy in combination with CQ. These data also highlight the exciting therapeutic potential for CQ in combination with mTOR pathway inhibitors in patients with activating FGFR3 mutations. Finally, by revealing a role for cholesterol biosynthesis in maintaining lysosomal integrity under stress, we propose that therapeutics which suppress cholesterol metabolism in other cancer types may present similar opportunities for eliciting synergistic cell death with CQ, thereby defining a novel approach to future cancer treatments.l-glutamine at 37 °C (5% CO2) and passaged weekly. For nutrient starvation, cells were washed three times in prewarmed EBSS . AZD4547, AZD8186, AZD8835, AZD5363, AZD2014 and Ato were made by AstraZeneca  and resuspended in dimethyl sulfoxide to 10 mm. All other reagents were reconstituted in dimethyl sulfoxide except: CQ ); 3MA (20 mm DMEM); cycloheximide (10 mg/ml water), cholesterol (10 mg/ml PBS); and N-acetyl-l-cysteine (100 mm DMEM). CA-074Me was obtained from Calbiochem . Free cholesterol was quantified using ab65359 Kit . SmartPOOL ON-TARGET siRNAs  were resuspended in water at 10 μm and reverse transfected by adding nine volumes of cell suspension to one volume of siRNA  premixed with Lipofectamine RNAiMAX  in OPTI-MEM (Gibco).Reagents were obtained from Sigma , except where indicated. Cell lines were sourced from: RT112/84 ; TCC-SUP, J82, SW780, T24, 1A6, UM-UC-3, HT-1197, HT-1376, 5637, RT4, SCaBER ; VM-CUB-1, 647-V, BFTC-905, KU-19-19, SW1710 ; MGH-U3 and 97-7 ; and human fibroblasts . All cell lines tested mycoplasma negative by Chan test. Cells were cultured in DMEM (Dulbecco's modified Eagle's medium) containing 10% fetal calf serum and 1% m in an IncuCyte ZOOM  for 5 days. The frequency of NucView-488 signals was quantified using ZOOM GUI version 2014A, and normalised for cell confluency using processing definitions adapted for each cell line.Cells were seeded at a density of 5 000/ml in 96-well plates and stained with SYTOX Green Nucleic Acid Stain  and Hoechst 33342 (1 μg/ml) following treatment. Total and dead cells were quantified using a Cellomics ArrayScan XTI  with appropriate filter settings. cdEC50s were calculated using Origin 7.5 SR6 . For CASP3 activation assays, NucView-488 Caspase-3 substrate  was incubated with cells at 1 μ4/ml and formalin-fixed for 20 min following treatment. Cultures were washed three times in PBS and blocked  for 1 h before overnight incubation (4 °C) with primary antibodies and 1 h incubations with secondary antibodies. For LC3 and LAMP-I immunostaining, cultures were postfixed in 100% ice-cold methanol for 15 min. Antibodies were purchased from Cell Signalling Technologies  except: anti-galectin-3 , anti-cathepsin L (Abcam). Secondary antibodies from Molecular Probes were used at a 1:500 and visualised by ArrayScan. LAMP-I puncta were quantified using ImageJ  by measuring the area of the three largest and clearly defined immunopositive structures per cell . Galectin-3-positive cells were defined by the presence of three or more cytosolic aggregates. For filipin staining, fixed cultures were quenched in glycine , rinsed and incubated with 25 μg/ml filipin-PBS (60 min) washed and visualised by ArrayScan.Cells were seeded in 96-well plates at a density of 0.5–5x105/ml and lysed in sodium dodecyl sulphate-based buffer following treatment. Lysates were normalised for protein concentration , boiled in sample buffer  and loaded at 10 μg per lane on Criterion gels (4–20%). Gels were transferred to nitrocellulose, blocked (5% milk-TBS-T) and incubated overnight (4 °C) with primary antibodies. All antibodies were from Cell Signaling Technology except: cathepsin B , HMGCS1 (Sigma), FRS-2 (R&D Systems) and HMGCR, IDI-I and DHCR7 (Abcam). Horseradish peroxidase-conjugated secondary antibodies were incubated for 1 h and visualised by ECL  using film  or CCD . Films were scanned at 600 dpi and analysed for densitometry using ImageJ (NIH). Cellular fractionation was performed using Kit No. 9038 from Cell Signalling.Cells were seeded at 0.5–2x10A sequence targeting ATG7 exon 1 (5′-AAGCTGAACGAGTATCGGC-3′) was synthesised (Sigma) within a guide RNA plasmid also encoding Cas9-GFP. The Cas9/gRNA was purified by Endo-free maxi prep , transfected using FuGENE HD . Cells were sorted for GFP fluorescence after 48 h  and seeded at 1 cell per well in 96-well plates. Cultures were monitored for single clones until confluency, passaged and assayed for ATG7 and LC3-II expression by western blotting.post hoc test to compare treatment means to control means . Where indicated, Student's t-test was used to compare means from at least three independent experiments.Data were analysed for statistical significance using one-way analysis of variance followed by Dunnett's


Consequently, for experiments where cells require irradiation and observation for extended time periods, it is important to provide a controlled environment. The highly customised nature of the microscopes used on VMB systems means that there are no commercially available environmentally controlled microscope systems for VMB systems. The Automated Microbeam Observation Environment for Biological Analysis (AMOEBA) is a highly flexible modular environmental control system used to create incubator conditions on the end of a VMB. The AMOEBA takes advantage of the recent “maker” movement to create an open source control system that can be easily configured by the user to fit their control needs even beyond VMB applications. When applied to the task of controlling cell medium temperature, CO2 concentration and relative humidity on VMBs it creates a stable environment that allows cells to multiply on the end of a VMB over a period of 36 h, providing a low-cost (costing less than $2700 to build), customisable alternative to commercial time-lapse microscopy systems. AMOEBA adds the potential of VMBs to explore the long-term effects of radiation on single cells opening up new research areas for VMBs.Vertical Microbeams (VMB) are used to irradiate individual cells with low MeV energy ions. The irradiation of cells using VMBs requires cells to be removed from an incubator; this can cause physiological changes to cells because of the lower CO Noticeatabolism . It was Vertical Microbeams(VMBs) such as at Columbia University’s Radiological Research Accelerator Facility (RARAF) or at Surrey University’s Ion Beam Centre comprise the disciplines of ion-beam physics, radiation biology and microscopy. This makes them unique tools that allow for the simultaneous observation and irradiation of cells using particle radiation ,8. Experhttps://www.python.org/) and the Arduino environment , computer-automated manufacturing techniques, for example, 3D printing, and widely available sensors to allow for quick development times the AMOEBA system provides a low cost homemade alternative to the high cost commercial systems. AMOEBA’s open source nature, relatively low cost (costing less than $2700) and flexibility also make AMOEBA a useful technology for the new Do-It-Yourself Biology (DIYBio) movement allowing experimental capabilities that cost $100,000 s to be carried out on equipment of that costs a fraction of that [The Automated Microbeam Observation Environment for Biological Analysis (AMOEBA) was developed to integrate environmental control into VMBs. The AMOEBA is a modular environmental control system which taps into the vast resources of the “maker” community reducing development costs and allowing easy reproduction of parts, ultimately creating a system that can be reproduced in other laboratories . By taki of that ,13. The The AMOEBA was designed with the flexibility to be applied to other applications without having to write any additional code. This meant that different sensors and actuators could be configured independently depending on the task at hand. This flexibility was achieved by designing the system around a single Controller Area Network (CAN) bus to which all the devices are connected, a schematic is shown in The AMOEBA has two main parts, the desktop software and a collection of different AMOEBA modules that connect together using CAT 5 cable. The server module connects the AMOEBA system to a computer using a USB  cable and each of the other modules has a different sensor or actuator attached.The structure of an AMOEBA module can be seen in The single ATMEGA 328P microcontroller used in each AMOEBA module was chosen as the standard AMOEBA microcontroller for many reasons. First, the microcontroller is capable of controlling devices that operate using many standard bus protocols including I2C, SPI , and serial communication. It is also capable of reading analogue signals and outputting pulse width modulated signals that can be easily converted to an analogue output. These microcontrollers are compatible with the Arduino programming environment, which is widely used by the “maker” community so numerous resources exist to interface with off-the-shelf sensors, significantly reducing development time. The Arduino software is designed to be used by those who do not have a background in electronics, so it hides a lot of the intricacies of developing embedded code from the user. This simplified setup will allow 3rd party users who wish to use the AMOEBA to more effectively implement their own sensors. The Arduino programming environment is also useful because it works across a range of ATMEGA microcontrollers; this means that the code designed for the ATEMGA 328P can easily be used on a more powerful ATMEGA microcontroller if a module requires it.A CAT5 cable is used for communication between the modules and to supply power. Of the eight wires available in a CAT5 cable three are used for ground, two are used for power, two are used for the CAN bus, and one is spare. If any module requires more than 0.5A then an external power supply can be connected to the device.There are four different types of AMOEBA modules that are connected to the bus: sensor modules, actuator modules, server modules and terminator modules. Sensor modules are modules that monitor system parameters, such as temperature. Actuator modules are modules that control a parameter, for example, a variable valve or a heater. The server module connects the AMOEBA system to a computer running the AMOEBA desktop client by a USB interface; it contains the main power supply and sets up the bus at the start of the experiment and can interface with up to 254 other modules. Finally, there is a sole terminator module used to terminate the AMOEBA bus. Each module on the AMOEBA system communicates using a standard protocol designed for the AMOEBA system, this means that any actuator module can process the data gathered by any sensor module. With this modular approach, the AMOEBA system can be quickly configured to suit any application.The AMOEBA system uses a CAN 2.0 bus that links all the modules together. The packets used are structured so that each module can communicate with any other module. This is achieved by using the first byte in each packet to designate the packet type. Each module also has its own unique address and a common shared address that can be used to send commands to other modules. The majority of the AMOEBA modules are either sensor or actuator modules, these are used to control or monitor various parameters. At the start of an experiment, each controller module on the bus is configured by the server module to monitor a certain sensor on the bus and the set point of that sensor. Once a start command is received the actuator module repeatedly polls the sensor module and adjusts its output accordingly. This continues until the actuator receives a stop command. We configured the AMOEBA system to work in a polled mode, it could easily be modified to operate in a triggered mode although this would not be required for environmental control since environmental control on cell culture does not require a fast response time.A computer running the AMOEBA desktop client connects to the server module by a USB cable. The AMOEBA software records the data gathered by the sensors and sets up the bus to control the environment. Once gathered, the data can be saved either into a specific AMOEBA XML file or to a character separated file that can be read using a customised script or any commercial spreadsheet software. For more complex experiments, the AMOEBA desktop client is also capable of running customised Python scripts specific to the experiment. 2 concentration and cell medium temperature. This was achieved by creating a controlled volume above the cells in which relative humidity and CO2 are controlled and by heating the cell dish to regulate cell medium temperature.Recreating incubator conditions on the end of a microbeam requires the control of 3 parameters: relative humidity, CO2 rich atmosphere can be seen in 2 within the shroud is read by a CO2 sensor ) and maintained (e.g. at 5%) by the variable valve module that controls the flow of CO2 from a gas cylinder. The humid air and CO2 mix within the environmental shroud to create a humid CO2 rich atmosphere.The processes used to create the humid, CO2 required to maintain 5% atmosphere is very low (0.05 l per hour); but if desired it would be possible to design and build a sealed chamber if desired.An AMOEBA environmental shroud  is used 3. To construct it uses a total volume of 157 cm3 of material to print with 100% infill. It is compatible with cell dishes with a diameter below 86 mm and could be easily be redesigned to cater for other plating systems if necessary without having to change any of the electronics.This work uses a shroud designed around the RARAF microbeam endstation to validate the AMOEBA ,10. The 2 monitoring, and mass flow analyser. The actuator modules are a variable valve, under dish heater, heated pipes and a solenoid valve module. There is also a sole server and terminator module. Collectively these modules cost $2380 to construct including the cost of the sensors.Since a variety of factors need to be controlled using the RARAF AMOEBA, it uses a variety of self-contained independent modules each serving their own purposes. The sensor modules are thermocouples, relative humidity and COthermocouple module is a bank of eight thermocouples, where each channel contains its own MAX31855KASA+  thermocouple preamplifier, which communicates with the microcontroller using an SPI bus with a maximum sensor refresh time of 100 ms. Although eight thermocouples are available the RARAF AMOEBA configuration uses four thermocouples: two are used to monitor the temperature of the compressed air, one is used to measure cell media temperature, and the fourth is used to measure the temperature of the water in the humidifier. The two thermocouples used to measure the temperature of the compressed air were adapted so that they can fit inside the airline by sealing it inside a Wye Push to Connect gas fitting using Permapoxy 5 min General Epoxy Resin . The Thermocouples module cost $120 to build and the thermocouples cost $90. It has a mass of 0.477 kg.The relative humidity and CO2monitoring is a single module with two HYT 271 relative humidity and temperature probes  and a Gas Sensing Solutions SprintIR 100% CO2 sensor. The HYT 271 communicate with the module’s microcontroller via an I2C bus with a 1 s sampling time. The CO2 sensor communicates with the AMOEBA microcontroller using UART  serial communication with a 50 ms sampling time. During most AMOEBA experiments only one relative humidity and the ambient temperature sensor is used since the relative humidity and ambient temperature is only measured inside of the AMOEBA chamber. The module cost $45 to build, each of the Relative Humidity and Temperature sensors costs $36 each and the CO2 sensor costs $155. The module has a mass of 0.266 kg.The variable valve module is used to control the flow rate of the CO2 gas. The module uses an FSV12  electronically controlled proportional valve that allows a maximum flow rate of 13LPM (216.7 cm3 s−1) of air. The behaviour of the valve is controlled using a Proportional-Integral-Derivative (PID) control algorithm on the module’s microcontroller that can be tuned by the user depending on the application [The under dish heater module is a MOSFET switch that controls the current going through an under dish heater, created by wrapping nichrome wire around the brass cap protecting the microbeam exit window. The under dish heater module cost $43 to construct. The mass of the module is 0.218 kg.In microbeam experiments, the dish containing cells is often in close proximity to a metallic section of beam pipe that can serve as a major heat sink. The heated pipe module heats air to create the humid environment necessary for the cells. Three 1 m sections of heated pipe were created by wrapping nichrome wire around 0.25-inch outer diameter PTFE (Polytetrafluoroethylene) pipe. The pipe is heated by passing an electrically controlled current through the wire that surrounds the pipe. Each section of heated pipe is attached to a heated pipe control board, which contains a MOSFET switch to control the current through the Nifethal 70 wire by pulse width modulation and an onboard MAX31855KASA+  thermocouple preamplifier to monitor the external temperature of the pipe. Each section of heated pipe cost $40 to build. Each heated pipe module has a mass of 160 g.The solenoid valve module for gas control consists of three solenoid valves controlled using the digital output pins on the microcontroller and they are driven using MOSFET switches. The valves are used to turn the CO2 and compressed airflow on at the start of an experiment and to turn them off at the end of the experiment. The three valves cost $200 and the electronics to control them cost $50. The mass of the module is 1.239 kg.The server module is used to interface between the AMOEBA software and the AMOEBA modules. The server module contains an Arduino Uno that was connected to additional CAN circuitry so it could interface with the AMOEBA modules. It also contained a 15 V 10A power supply that provides the power for all the AMOEBA modules. The cost of the server module was $125. The mass of the server module is 1.432 kg.The terminator module that contains a resistor that is used to terminate the bus. The terminator modules cost $15 to construct. The terminator has a mass of 0.1 kg.CAN buses need to be terminated to achieve their best operation; as a result, the AMOEBA system has a The AMOEBA system is also capable of interfacing with pre-existing lab equipment through the use of communication protocols such as GPIB, RS-232, USB or Ethernet. An example of this is the RS-232 AMOEBA module. It was created to interface with the JENCO 6230N handheld metre that connects to a range of ion sensors that can be used to measure factors such as dissolved oxygen or pH. This can be achieved due to the flexibility of the ATMEGA328P microprocessors used by each module and a large amount of freely available code already available online.mass flow analyser module is available to measure gas flow although it is not often used because the flow rates it can measure is too low. A Dwyer Instruments GFM-1108 Gas Mass Flow Metre  is used and it outputs a 0–5 V signal that is read by the module’s microcontroller and converted to a flow rate. The GFM-1108 is capable of measuring airflow up to 2 l per Minute (LPM) (33.3 cm3 s−1). It is also capable of measuring other gases using the supplied calibration factor. The mass flow analyser cost $785 and the control electronics cost $40 to produce. The module had a mass of 930 g.A 2 and 99% ± 1% relative humidity) environment. To test the stability of the AMOEBA system, an AMOEBA experiment was set up using a cell dish containing 2 ml of cell media and run for 6 h; the dish was removed from the environmental shroud every 2 h to measure the mass of the cell dish. The second step was to test its ability to sustain cells within the device. To test this, cells were observed in the AMOEBA system for 36 h, with an image being taken every 10 min.The application of the AMOEBA system for environmental control on the RARAF VMBs was tested in two steps. The first step was to test the ability of the AMOEBA system to create and sustain an incubator like   on the polypropylene sheet and cells were added on top of this.HeLa  cells were first grown in DMEM  supplemented with 10% Foetal Bovine Serum  and 1% of Pen/Strep  using T75 culture flasks in a 5% COprotocol . The mic−1 Cell-Tak solution and 10 μl of 0.2 M sodium bicarbonate solution  into to the well. The dish was then placed in a Series 8000 Direct-Heat CO2 Incubator (Thermo Fisher Scientific) at 37 °C and 5% CO2 for 30 min. Once removed from the incubator the dish was rinsed 3 times with 5 ml of sterile phosphate buffered saline solution. After this, the dishes can be stored for up to two weeks in a refrigerator.The dish wells coated with Cell-Tak were coated by putting 10 μl of 100 μg ml5cell/ml in a 1–3 μl volume droplet. Once placed into the cell dish the well was covered with a 22 mm by 22 mm autoclaved glass coverslip  and the cell dish was placed into the incubator for half an hour. Upon removal from the incubator, the coverslip was taken off and 5 ml of DMEM was added to the cell dish, before returning it to the incubator at 37 °C and 5% CO2. The dish was left in the incubator for a minimum of 3 h before being placed onto the microbeam endstation for observation.Cells were plated by placing a droplet containing 100–300 cells into the Cell-Tak coated well of the dish at a density of 102 with the stain for 30 min and then the medium was replaced with fresh DMEM supplemented with 10% Foetal Bovine Serum and 1% Pen/Strep prior to observation.To observe the cells using the RARAF endstation, cells were stained using Hoechst 33342  at a concentration of 100 nM in DMEM . The celA detailed description of the microscope system used on Microbeam II, including details on the hardware and software systems used to control the endstation and camera can be found in Bigelow et al. . It cons2 5% ± 0.5% and relative humidity 99.5% ± 0.5%. The spikes seen every two hours in the relative humidity, cell dish temperature and ambient CO2 are caused by the removal of the cell dish from the system so that it can be weighed and would not occur if the system was left for normal operation.2 within the chamber initially peaked at 8%, settling to 5% within 145 s after inserting the dish. When the dish was removed from the chamber to weigh it, ambient CO2 spiked to a maximum of 14.2% after the chamber was closed. The mean settling time of the system after being disturbed was 371 s (6.19 min), the signal oscillated within the acceptable boundaries at an approximate frequency of 8mHz. Over the 6 h period, the mean CO2 value was 4.994% and the RMS Error of the CO2 signal was 0.370%, including the spikes caused by removing the cell dish. In the times between the spikes, the means and RMS error values can be seen in When first inserted into the AMOEBA the cell dish temperature reached 37 °C within 6 min, reaching a maximal overshoot temperature of 40 °C, with the dish temperature above 38 °C for 121 s. The same occurred when the dish was replaced after being weighed. The dish temperature spiked to a maximum of 41 °C, these temperatures returned back to the acceptable limits within 130 s. The mean dish temperature over the 6 h period was 36.840 °C and the RMS Error was 2.754 °C including the spikes experienced when the dish was removed the temperature oscillated within the acceptable boundaries at a frequency of 10.2 mHz. The CO2. Once the environment was established during the 6 h period, the relative humidity did not drop below 99% other than the times the system was disturbed to measure the mass of the cell dish.During the undisturbed periods of operation when the system exceeded the bounds the AMOEBA successfully restored the parameter to the acceptable limits within a maximum of 1.2 min for cell dish temperature and 36 s for ambient CO−1 and the maximum mass loss was 0.067 g h−1. The mean mass loss was 6 mg h−1 with a variance of 0.002 g h−1. The control experiments shown in −1 with a variance of 0.0002 g h−1. As a result the AMOEBA system has improved the loss of medium due to evaporation by a factor of 94.5 times. If the mean evaporation rate was sustained over a 12 h period the dish would lose 72 mg and over a 36 h period the dish would lose 216 mg.Two other similar experiments were carried out using the AMOEBA; the results of these experiments can be seen in A dish of Hoechst 33342 stained HeLa cells was examined under the microscope for 36 h; during the 36-h experiment, the AMOEBA regulated the environment at incubator conditions and an image was taken every 10 min. Cell division was successfully observed with two examples are highlighted in The AMOEBA was designed to be a modular environmental control system that would be flexible enough to be applied to many situations beyond the area of environmental control. The single bus design allows modules to be easily added to and removed from the AMOEBA system. Its flexibility is also attested to by two facts: firstly that the AMOEBA system has worked on two beamlines, the Permanent Magnet Microbeam and Microbeam 2, at the RARAF facility, secondly, the AMOEBA system is in use in two VMB laboratories each with their own unique environmental setups(RARAF at Columbia University and at the Surrey Ion Beam Centre at Surrey University) .The AMOEBA system is portable and can be moved between systems with little effort. The AMOEBA system can be adapted to almost any microscope since it would only require a new environmental shroud rather than require the whole system to be redesigned. If another parameter needs to be controlled, such as oxygen, the sensor would simply require a new module to be developed before adding it to the system.Another testimony of the power and flexibility of the AMOEBA system is its ability to use standard communication protocols, this is shown by the RS-232 module that is able to interface with a Jenco 6230N . This feature of the AMOEBA system means that items of lab equipment with standard interface protocols such as USB, RS232 or GPIB, can be used as part of the AMOEBA control system.2 levels stayed within the desired bounds of 5% ± 0.5% over the whole 6 h period; when it did briefly stray from outside this range it returned within 2 min.In this work, we demonstrated that the AMOEBA is capable of creating an incubator-like environment for extended live cell experiments. During the 6 h test, the temperature of the cell media stayed within the desired temperature bounds (37 °C ±1 °C) once it had reached its desired temperature. The four occasions when the temperature did exceed these bounds the temperature of the cell dish returned to desired range within 2 min. Likewise, the CO2 values briefly overshot their desired set point, however, these parameters settled within minutes. Of these two values the temperature is the most critical for cell health, but the temperature spike is too short to damage the cells [When starting the system the temperature and the COhe cells . This ov2 initially dropped to below 1% due to the chamber being opened, the relative humidity also dropped for the same reason but because there was still a net flow of humid air and CO2 into the chamber, and the chamber was not opened for long enough for more CO2 or humid air to diffuse out of the chamber, as a result the relative humidity and CO2 did not drop to ambient levels. The temperature measured by the thermocouple measuring cell medium temperature dropped when the cell dish was being weighed because when the cell dish was removed to be weighed the dish and the thermocouple measured the temperature of the air in the chamber. When the dish was replaced the CO2 experienced a spike because the variable valve had opened more to compensate for the drop in CO2, resulting in an increased flow of CO2 in the shroud causing a spike when the chamber was closed.When the cell dish was removed, the COWe used the AMOEBA to observe cells for a 36 h period including instances of cell division. The unique culture conditions required to irradiate cells VMB, likely reduced and delayed cell division during this time. This delay is likely to have been caused by the polypropylene substrate, this can be deduced because Hoechst 33342 has previously been demonstrated to not be toxic to HeLa cells , and theThe AMOEBA system provides a flexible low-cost alternative to commercial environmental control systems. Unlike commercial systems, its modular design means it can be rearranged and within minutes be ready for almost any task that is required of it. The AMOEBA system opens up the potential of VMBs to irradiate and observe cells for extended periods of time. This system will enable microbeams to carry out experiments that were not possible previously, paving the way for microbeams to be able to assess cell motility, explore the effects of radiation over several cell divisions and to observe mutagenic effects of particle radiation without having to remove the cells from the microbeam.Supplemental


The drug discovery and development pipeline is a long and arduous process that inevitably hampers rapid drug development. Therefore, strategies to improve the efficiency of drug development are urgently needed to enable effective drugs to enter the clinic. Precision medicine has demonstrated that genetic features of cancer cells can be used for predicting drug response, and emerging evidence suggest that gene-drug connections could be predicted more accurately by exploring the cumulative effects of many genes simultaneously.50) from 140 drugs. DeSigN successfully predicted the right drug sensitivity outcome in four published GEO studies. Additionally, it predicted bosutinib, a Src/Abl kinase inhibitor, as a sensitive inhibitor for oral squamous cell carcinoma (OSCC) cell lines. In vitro validation of bosutinib in OSCC cell lines demonstrated that indeed, these cell lines were sensitive to bosutinib with IC50 of 0.8–1.2 μM. As further confirmation, we demonstrated experimentally that bosutinib has anti-proliferative activity in OSCC cell lines, demonstrating that DeSigN was able to robustly predict drug that could be beneficial for tumour control.We developed DeSigN, a web-based tool for predicting drug efficacy against cancer cell lines using gene expression patterns. The algorithm correlates phenotype-specific gene signatures derived from differentially expressed genes with pre-defined gene expression profiles associated with drug response data  contains supplementary material, which is available to authorized users. The drug discovery and development pipeline is a long and arduous process, one that is resource-intensive and time-consuming, making these the main barriers for rapid drug development. Furthermore, the attrition rate is high, underscoring the need to improve strategies in drug development and in expanding the usage of already approved drugs . FortunaSince the late 1980s, the NCI-60 panel of cancer cell lines has been used to systematically identify anti-cancer compounds and more recently, to identify biomarkers of response , 8. In 2The development of computational tools that could take advantage of the availability of high throughput gene expression data to mine patterns of association between drug sensitivity and gene expression signatures began with the seminal work by Lamb et al. who developed the Connectivity Map (CMap) algorithm . SubsequWhile GDSC provides large amounts of drug response data from arrays of cell lines, additional analyses are needed to extrapolate drug efficacy to new datasets. For example, GDSC shows that the head and neck cancer cell lines FADU and HSC-3 are reported to respond to the heat shock protein 90 (Hsp90) inhibitor 17-AAG [To exploit the GDSC data for predicting drug sensitivity, we developed DeSigN , a CMap-inspired  bioinfor50 data, with the aim of identifying novel drugs that have good potential to be repurposed for cancer therapy. The DeSigN algorithm . Cell lines with IC50 that were U standard deviations larger than the median IC50 of all cell lines were considered to be resistant; those that were L standard deviations smaller were considered to be sensitive. We chose the parameters U and L carefully on a case-by-case basis. These two cut-offs were generally values where sharp transitions in IC50 were observed in the scatter plot of –log10(IC50) against rank. About 20 cell lines each from the sensitive and resistant phenotype were thus defined. The list of sensitive and resistant cell lines defined for the 140 inhibitors in DeSigN is provided in Additional file We built the reference database using baseline microarray data and drug sensitivity data obtained from the Genomics of Drug Sensitivity in Cancer (GDSC) project. We first downloaded the raw CEL microarray data files of solid tumour cell lines from GDSC  . This reference database was used to connect the queries and return rank-ordered list of inhibitors for a particular query  algorithm . The resery Fig. .p-value and fold change [2 fold change > 1 and p-value < 0.01  obtained from microarray or RNA-Seq gene expression data of cell lines of two different phenotype classes were used to query DeSigN. DEGs were selected using joint filtering of d change , with th.01 Fig. .50 drug sensitivity profiles.A pattern-matching algorithm based on the nonparametric Kolmogorov-Smirnov (KS) statistic  was usedN be the total number of genes in the reference database, and T the number of genes in the query signature for up- or down-regulated genes. For every drug in the reference database, we compute the rank-ordered (using moderated t-statistic) list R for all N genes. Let j index the query genes in such a way that R(j), the rank of the j-th gene in the N total number of genes, is monotone increasing. For j = 1, 2, …, T, we compute the following two values for each up- and down-regulated gene signatures:The Connectivity Score is computed according to  as folloi, the KS-like statistics for up- and down-regulated query gene signature, ksupi and ksdowni, are computed as (subscript omitted)Subsequently, for each inhibitor ES1) for drug i in the reference database is set to zero if both ksupi and ksdowni have the same sign; otherwise, ESi = ksupi − ksdowni. The Connectivity Score (Si) for non-zero instances is a normalized Enrichment Score computed as:P = maxiESi and Q = miniESi are the normalizing constants.The Enrichment Score  and −1   Fig. .Si, we used a permutation approach to simulate the null distribution of Si. Thus, m random gene sets, each having the same size as the size of the input gene signature, were simulated. Each gene set then yields Srandomi(k), where k indexes the random gene set. The p-value was computed asIA is the indicator function that takes the value 1 if event A occurs, and 0 otherwise. Here, we set m = 1000.To evaluate the statistical significance of http://design.cancerresearch.my/. Its web interface is implemented in PHP (v7.0) with the support of jQuery (v1.4.2), and hosted using the Apache Server. The reference database is generated and managed using MySQL database (v5.5.49). DeSigN makes use of the AJAX feature to quickly load content without reloading the pages. All queries are sent to the Java-based computing cluster to perform parallel computation. A help document providing a guide for users to query and navigate DeSigN is available in the website, with examples given. Except the pattern-matching algorithm, which was programmed in Java and the Graphical User Interface (GUI), which was built using PHP, the other methods were implemented in R version 3.3.0.The DeSigN website is freely available at 50 < 1 μM and resistant cell lines as having IC50 > 1 μM. The choice of these four studies was guided by several inclusion and exclusion criteria. We included studies where: (i) The median of the distribution of gene expression values of each sample were more or less equal; (ii) The subject of the drug sensitivity study was Homo sapiens; (iii) Drug treatment was given for at least 48 h; (iv) Only one inhibitor was used. We excluded blood cancer-related studies. For each study, a list of DEG was identified and used to query DeSigN.To demonstrate how DeSigN could be used to predict candidate drugs, we used differentially expressed genes generated from ER-positive breast cancer versus normal tissue reported by Clarke et al.  that canFive oral squamous cell carcinoma  and three normal oral keratinocyte (NOK) cultures previously developed in our laboratory [2 at 37 °C.All ORL cell lines and HSC-4 (sensitive control for response to bosutinib) were cultured in Dulbecco’s Modified Eagle Medium (DMEM)/F12 (1:1) supplemented with 10% (v/v) heat-inactivated fetal calf serum (FBS), 100 IU Penicillin/Streptomycin and 0.5 μg/ml hydrocortisone as described previously . NOK wer3 cells per well as described previously [t-test was used to assess whether the difference in the sample mean of IC50 between the tested cell lines was statistically significant . Experiments were repeated at least three times.The effect of bosutinib on the selected OSCC cell lines was determined using MTT assay with 1.5–8 × 10eviously . Cells wt-test was used to test whether the mean of total number of apoptotic events differed significantly  between bosutinib-treated cells and the vehicle control (0.01% DMSO) cells. Experiments were repeated at least two times.Apoptosis was quantified using a FITC Annexin V Apoptosis Detection Kit  according to the manufacturer’s instructions. Briefly, floating and attached cells were collected at 24, 48 and 72 h after bosutinib treatment at 1 μM, and then stained using FITC Annexin V/Propidium iodide (PI). Apoptosis detection was performed using BD FACSCANTO™ II flow cytometer and data was analyzed using the BD FACSDiva™ software . For each of the three time points, the two-sample t-test was used to test whether the difference in the relative percentage of EdU+ cells differed significantly  between treatment and vehicle control for the three cell lines. Experiments were repeated at least two times.The anti-proliferative effect of bosutinib on the OSCC cell lines were examined using Click-iT EdU Cell Proliferation Assay Kit  as previously described . The celTo demonstrate how DeSigN can be used to generate a list of prioritized candidate drugs, we tested differentially expressed genes (DEG) generated from ER-positive breast cancer cell line compared to normal tissues . As expected, gefitinib was returned as the top-ranked inhibitor with Connectivity Score of 1.00 and p-value < 0.001 .GSE4342 is a study that demonstrated the sensitive response of 17 non-small cell lung cancer (NSCLC) cell lines to gefitinib (EGFR-inhibitor) treatment . By querp-values  and bosutinib (ranked eighth), have been recently reported to be effective against head and neck squamous cell carcinoma (HNSCC) cell lines [As we demonstrated that DeSigN could correctly predict drug response from published data, we next used DeSigN to identify inhibitors that could control the growth of OSCC cell lines. The gene signature for differential gene expression between OSCC cell lines and NOK contained 69 and 86 up- and down-regulated genes . Against the resistant control, MCF-7, all three OSCC cell lines also had significant lower mean IC50 , indicating the cytotoxic effect of bosutinib in these OSCC cells.For experimental validation of bosutinib’s efficacy against OSCC, we tested it in three OSCC cell lines . All three OSCC cell lines  whilst ORL-48 showed growth inhibition of ~40% following bosutinib treatment at 1 μM for 72 h   compared to the non-treated cells Fig. . ORL-196We have developed DeSigN, a web-based bioinformatics tool that allows users to query large public database of cancer cell line gene expression and drug response data such as GDSC. We showed explicitly that querying DeSigN using differentially expressed gene signatures could reveal potentially efficacious candidate drugs, as shown in the GSE4342 analyses. BIBW2992 (a newer generation of EGFR inhibitor currently approved for treating NSCLC patients who are refractory to gefitinib and erlotinib), for example, could potentially replace gefitinib, a first-generation EGFR tyrosine kinase inhibitors (TKI) that is increasingly becoming a non-viable solution as cancer cells of NSCLC patients treated with gefitinib inevitably develop resistance and relapse, with 8–10 months of median time to progression –28To date, many cases of successful drug repurposing studies have been reported, an exemplary study being that of methotrexate, a drug first developed for treating leukemia, and subsequently repurposed to treat a wide spectrum of cancers ranging from breast, ovarian, bladder to head and neck cancers , 30. HerWhile tools such as NFFinder, DMAP and FMCM that adopted the CMap concept make use of large public databases such as GEO, DrugMatrix, STITCH and HAPPI as their reference, DeSigN has its uniqueness whereby it explicitly capitalizes on the large panel of 707 human cancer cell lines in GDSC that have well-characterized gene expression and drug response data Table . SpecifiThe new leads derived from DeSigN are important for accelerating the discovery of new drugs for HNSCC treatment, which is currently limited to cetuximab, where this drug remains the only FDA-approved targeted therapy for advanced HNSCC . ImportaThe current implementation of DeSigN uses differentially expressed genes as starting points to associate gene signatures with drug response phenotype. This input is not necessarily optimal, as genes that are involved in dysregulated pathways in the pathogenesis of cancer may not always have their expression substantially altered . Since hFor future work, we also intend to expand drug coverage in Version 1.0 of DeSigN by incorporating the gene expression and drug response data from Cancer Therapeutics Response Portal (CTRP)  and otheDeSigN provides proof-of-concept for the feasibility of using a computational approach to shortlist the most promising drug candidates for effective drug repurposing in cancer treatment. We expect that DeSigN will continue to evolve based on usage feedback from the community of cancer researchers, as well as improvements in methods for mining gene signatures that have strong network context.


ERCC8 and MLH1, respectively) increases PARPi response. The highest sensitivity was observed when genes in both the HR and either NER or MMR pathways were concomitantly down regulated. Using clinical samples, patients with these concurrent down regulations could be identified. Based on these results, a novel model to predict PARPi sensitivity is herein proposed. This model implies that the extreme responders identified in clinical trials have deficiencies in HR and either NER or MMR.PARP inhibitors (PARPi), such as Olaparib, have shown promising results in high-grade serous (HGS) epithelial ovarian cancer (EOC) treatment. PARPi sensitivity has been mainly associated with homologous recombination (HR) deficiency, but clinical trials have shown that predicting actual patient response is complex. Here, we investigated gene expression microarray, HR functionality and Olaparib sensitivity of 18 different HGS EOC cell lines and demonstrate that PARPi sensitivity is not only associated with HR defects. Gene target validation show that down regulation of genes in the nucleotide excision repair (NER) and mismatch repair (MMR) pathways ( BRCA1 and BRCA2 which significantly increases risk   was classified as sensitive with an IC50 of 0.01 μM. However, OV4485, the cell line harboring a BRCA1 mutation, had an IC50 that was classified as intermediate , has been shown to increase PARPi sensitivity  and in two intermediate [TOV2295(R) and OV4485] cell lines to further verify whether these siRNAs could increase sensitivity to Olaparib. Figure 50 of both resistant cell lines upon downregulation of each of the four selected genes. More precisely, down-regulation of MLH1 (MMR pathway), ERCC8 (NER pathway) or MRE11A (HR pathway) induced an approximate 10-fold decrease in the Olaparib IC50  cells, siRNA against both MRE11A and MLH1, but not MLH3 and ERCC8, produced a significant decrease in Olaparib IC50. The insignificant effect of ERCC8 down-regulation in this cell line was not expected and we speculate that the NER pathway could be compromised. A recent study has described that 8% of HGS EOC exhibited mutations or homozygous deletions of NER genes  also demonstrated a decrease in Olaparib ICe Figure , Table 3n Figure . As expes Figure , Table 3ER genes . FurtherTo further validate the siRNAs and their targets, siMLH1 and siMLH3 were tested in OV1946 a sensitive cell line that had lower expression for these two proteins based on gene expression microarray analyses relative to resistant cell lines Table . As expeMLH1, MLH3 and ERCC8 knockdown in HR proficient OV866(2) and OV1369(R2). As expected, knocking down these genes did not alter RAD51 foci number in total or geminin-positive cells  was assayed for Olaparib sensitivity, single siRNA treatment against MRE11A or MLH1 resulted in an increase in sensitivity, while a double knockdown of MRE11A and MLH1 displayed an even greater enhancement when compared to the parental cell line  the double knockdown was more effective than each single knockdown in both the TOV2295(R) and OV4485 cells  in intermediate cells, TOV2295(R) did not display a significant change in sensitivity between single and double knockdowns Figure . The sams Figure . In the s Figure , indicatin vitro. However, based on results with OV4485, once HR and one other pathway are compromised, there is no added benefit to a third pathway being compromised.These findings suggest that defective HR is vitally important for PARPi sensitivity, but insufficient on its own to render a cell fully sensitive to PARPi and that a second pathway must be deregulated (either MMR or NER) to achieve the highest sensitivity observed MRE11A and MLH1 expression  and MRE11A and ERCC8 expression , indicating that defects in HR and MMR/NER pathways could co-occur in clinical specimens. Approximately 25% of the specimens exhibited concomitant low expression levels of these biomarkers pairs   Network  Figure . Our ress Figure , and accs Figure , patient) Figure , and we PARP1 exerts significant effects on several biological functions that are critical for cell growth and survival –9. In th50 comparable to EOC Olaparib resistant cell lines (data not shown). Similar to the HR pathway, the MMR and NER pathways are involved in the repair of DSB  cell lines. A list of genes was obtained for each sensitive cell line, following the strict criteria that genes must be differentially regulated when compared to all the other cell lines within the resistant group. Gene lists were uploaded onto the Ingenuity Pathway Analysis program (Qiagen Inc.) to obtain a list of canonical pathways affected in each cell line. Only significantly  was performed using the MultiExperiment Viewer software (MeV_4_8_1 from TM4), a free, open-source tool for microarray analysis.In another approach, probe sets of DNA repair genes were selected and mean expression values were analyzed to identify common differentially affected genes between Olaparib sensitive MLH1 and MLH3; and siRNA#3 for MRE11A and ERCC8). To verify off target issues, a different siRNA for each gene was used in a subset of experiments . Scramble siRNA  (see le siRNA  was usedp < 0.05.In the present work we used a HGS EOC tissue microarray (TMA) containing 213 cases (two cores per patient), which has been previously described . The TMAhttps://tcga-data.nci.nih.gov/docs/publications/ov_2011/) as a table format. This table contained normalized expression of 11864 genes from 489 HGS EOC samples as previously described [p < 0.05.The Unified Expression dataset of HGS EOC gene microarray from the TCGA was directly uploaded from The Cancer Genome Atlas (NCI/NIH) website (


The maximum tolerated dose in mice of NUC013 is greater than 120 mg/kg administered intravenously for three consecutive days a week for three weeks. With this regimen and a dose of 20 mg/kg in a human leukemia HL-60 (p53-null) NCr-nu/nu mouse xenograft model (n = 10/group), NUC013 demonstrated a survival benefit  = 26.5 days, NUC013 MS = 32 days and hazard ratio (HR) = 0.26 (p = 0.032)). In a colon cancer LoVo (TP53 WT) xenograft, mice treated with decitabine at 5 mg/kg had worse survival than saline controls ). At a dose of 20 mg/kg NUC013, mean tumor volume in the LoVo xenografts was lower than controls by 50.9% and at 40 mg/kg by 53.7% (both p < 0.0001).Tumor suppressor genes can be silenced genetically as well as epigenetically. One approach to reversing epigenetic suppression of tumor suppressor genes is to inhibit DNA methyl transferase. 5-aza-2′,2′-diflurorodeoxycytidine (NUC013) is a novel DNA methyl transferase and ribonucleotide reductase inhibitor that is a more potent inhibitor of growth than decitabine in the NCI 60 cancer cell line panel. NUC013 is more active than decitabine against p53-null/mutant cancer cell lines ( An aberrant gain of DNA methylation at the promoter CpG islands and enhancer regions of critical tumor suppressors is observed in most cancers and leads to the inactivation of the expression of genes that suppress tumorigenesis . The gen®, Celgene, Summit, NJ, USA) or 5-aza-2′-deoxycytidine, also known as decitabine,  conjugated with the sugar moiety of gemcitabine   is a novel nucleoside analog designed to be a DNA methyl transferase inhibitor (DNMTI) and ribonucleotide reductase inhibitor (RNRI). NUC013 consists of the base of 5-azacytidine (VidazaUSA) see .Both 5-azacytidine and decitabine are approved in the United States for the treatment of myelodysplastic syndrome (MDS). More recently, decitabine has been approved in the European Union for the treatment of acute myeloid leukemia . These nTo be active as a DNMTI, 5-azacytidine must first be reduced in vivo to the deoxy-analog, decitabine. Decitabine must then be phosphorylated to decitabine triphosphate and incorporated in DNA before inhibiting DNA methylation . Both drGemcitabine is approved as a first line treatment for pancreatic cancer and as combination therapy for other solid tumors. It is an inhibitor of DNA synthesis and, most relevant to NUC013, gemcitabine diphosphate inhibits RNR. Inhibition of RNR causes a reduction in the concentrations of deoxynucleotides, including deoxycytidine triphosphate (dCTP). As gemcitabine triphosphate competes with dCTP for incorporation into DNA, the reduction in the intracellular concentration of dCTP enhances the incorporation of gemcitabine triphosphate into DNA (a mechanism that has been described as self-potentiation) .50) for 5-azacytine was 0.62 µM versus 4.54 µM for NUC013. In HCT-116, NUC013 at 1 µM achieves 53.4% inhibition of total DNMT in a colorimetric assay compared to 19.2% for 5-azacytidine . At 10 µM, NUC013 inhibition of total DMNT was 48.5% versus 48.6% for 5-azacytidine.NUC013 and 5-azacytidine were first tested for growth inhibition against human colon cancer cell line HCT-116 (TP53 WT), which is also part of NCI 60 cell line panel. The concentration of drug that inhibited 50% of cell growth (GIThese results were confirmed and extended in human leukemia Kasumi-1 (TP53 R248Q mutant) and THP-1 (TP53 null) cell lines. In these cell lines, NUC013 demonstrated DNMT1 inhibition by western blot comparable to decitabine at 0.1 and 0.2 µM in THP-1 cells, though DNMT1 inhibition in the same concentration range is weaker than decitabine in Kasumi-1 cells See A.In these same cell lines, NUC013 demonstrated apoptosis after 24 h starting at a concentration of 0.25 µM in Kasumi-1 and 0.2 µM in THP-1 B, comparRNR inhibition by NUC013 was evaluated by exposing Hela cells to drug and then determining by high-performance liquid chromatography (HPLC) whether deoxynucleotide synthesis was inhibited when compared to negative control cells. Gemcitabine was used as a positive control.Extensive testing has been performed on the activity of NUC013 in cancer cell lines, including the NCI 60 cell line panel. The panel comprises human cancer cell lines representing nine different tissues of origin: breast, colon, central nervous system, renal, lung, melanoma, ovarian, prostate and hematogenous. These cells lines are very well characterized, and their TP53 status has been reported in the literature .50 is <−5.0 M or ≥−5.0 M, while for NUC013 whether at 10 µM percent growth is ≥50% or <50%. Only cell lines that were tested for both compounds are presented, as the composition of the panel has undergone some minor changes with time . Hence, it is only possible to compare activity at 10 µM; for decitabine, whether the log GItime see .p = 0.0002).Using the cut-off of 10 µM, it is possible to summarize and compare the activity of decitabine and NUC013 in the NCI 60 cell line panel and determine what influence, if any, the presence of TP53 WT has on growth inhibition by decitabine or NUC013 in 2 × 2 contingency tables. As shown in p = 0.66 confirmed a very high probability of a true null hypothesis, i.e., that TP53 status had no effect on decitabine GI50. In contradistinction, data in p = 0.013) between TP53 status and cell growth inhibition. Another way to look at the data is that while a comparison of NUC013 efficacy versus decitabine in TP53 null/mutant cell lines was statistically significant , results in TP53 WT cell lines reach an even more stringent level of statistical significance .In 50 was greater than 50 µM for decitabine in both cell lines, while for NUC013, the GI50 was 1.3 µM for Ls174T and 3.0 µM for LoVo . Drugs were administered IV for 3 consecutive days a week for 3 weeks. HL-60 is a human leukemia cell line (TP53 null) that is part of the NCI 60 cell line panel and can be grown in nude mice. LoVo is a colon cancer cell line (TP53 WT) that demonstrated good in vitro activity of NUC013.NUC013 was tested against a positive control (decitabine) and a negative control  in two mouse models  of treated groups did not significantly differ from that of saline control  significantly improved MS (p = 0.032)  were noted on study days 18 through 28  B. Furtheh 28 see B, reachip < 0.0001)  (see 3 at treatment initiation), the graph shows trends towards improved survival  on study days 9 through 51, compared to saline control. As with the dose of 5 mg/kg, mean tumor volume in treated mice decreased the most compared to control mice 8 days following the end of treatment (study day 30): 50.9% in mice treated with 20 mg/kg and 53.7% when mice where treated with 40 mg/kg   versus saline (001) see C. At equled) see C. In theival see D. Mean tled) see D.50 (4.54 µM), while such was not the case for 5-azacytidine (GI50 = 0.62 µM) where the concentration required to achieve similar levels of inhibition was greater than 1 µM but likely less than or equal to 10 µM. NUC013 was confirmed as a DNMT1 inhibitor in leukemic cell lines THP-1 and Kasumi-1.In colon cancer cells , NUC013 showed a greater than 50% total DNMT inhibition at 1 µM. NUC013 achieved this level of DNMT inhibition at a concentration that was lower than its GILike all 5-azacytidines, the 5-azacytosine base of NUC013 is susceptible to hydrolysis at the 6-position of the cytosine ring see  with relMany 2′-substituted-2′-deoxynucleotides have been shown to be a potent mechanism based RNRI. Detailed studies on 2-fluoro, 2-chloro and 2-azido derivatives have provided the basis for a general mechanism of inhibition by these substrate analogs . There aThe p53R2 gene encodes a small subunit of RNR and has been identified as a p53-inducible gene. While gemcitabine does not induce p53R2, it has been shown to result in its inhibition . ConversDecitabine has been thought of as an S-phase specific agent . HoweverThe inhibition of RNR by gemcitabine has been reported to lead to depletion of dCTP, a potent feedback inhibitor of deoxycytidine kinase, leading to a more efficient phosphorylation of gemcitabine. Moreover, since gemcitabine competes with dCTP, a decrease in dCTP pools increases incorporation of gemcitabine into DNA, a mechanism that has been described as self-potentiation . This saEvidence suggests that tumor suppressor gene silencing is an early initiating event in the oncogenic process and that maintaining expression of these genes may well impede the onset of tumorigenesis and tumor progression . The tump = 0.013) against TP53 WT cell lines. This result is compatible with the experimental data generated by Nieto and others that decitabine unexpectedly induced more apoptosis in TP53 null cells than in TP53 WT cells [NUC013 has been shown to inhibit the growth of hematogenous tumor cell lines by more than 50% at 10 µM and at least one cell line from all solid tumor tissues tested in the NCI 60 cell line panel, including breast, colon, central nervous system, renal, lung, melanoma, ovarian and prostate. While decitabine is no more effective against TP53 WT than TP53 null/mutant cell lines, NUC013 is significantly more effective , the mean GI50 of NC013 can be estimated to be no better than 10-fold lower than decitabine. Hence, the therapeutic index of NUC013 may be conservatively estimated, depending on the actual MTDs, to be in the range of 100- to 150-fold better than decitabine.On a schedule of 3 consecutive daily IV doses per week for 3 weeks, NUC013 has been shown to be safer than decitabine in mice. The maximum tolerated dose (MTD) of decitabine is under 5 mg/kg while that of NUC013 is over 120 mg/kg when administered to nude mice on the same schedule, a greater than 24-fold difference. A mean GIIn xenograft models implanted with cell lines sensitive to NUC013 and relatively resistant to decitabine, better activity was demonstrated for NUC013. In mice treated with NUC013, survival was significantly improved for a hematogenous tumor (p53 null) and tumor growth significantly inhibited for a solid tumor (p53 WT) compared to untreated mice. This suggests that in vitro activity in other cell lines, whether solid or hematogenous, p53 null or WT, may also translate to activity in vivo.NUC013 was originally synthesized at Sonus Pharmaceuticals  and more recently by NuChem Therapeutics .TM DNA Methyltransferase Activity/Inhibition Assay Kit  [Total DNMT activity was measured in the colon cancer cell line HCT-116. The assay was performed using the EpiQuickNY, USA) . The HCTApproximately 100 µg of cytoplasmic and nuclear protein extracts from cells, together with molecular weight markers, were subjected to SDS-PAGE on 4–12% gradient gels  followed by transfer to polyvinylidene fluoride membranes (Invitrogen). Blots were probed using antibodies for DNMT1 (Abcam ab16632).5) were washed and incubated for 30 min with FITC-conjugated Annexin-V at room temperature. Cells were then resuspended in binding buffer containing PI and immediately analyzed by flow cytometry.Apoptosis was detected by Annexin-V and propidium iodide (PI) co-staining using the APOAF commercial kit . Cells  of Eurofin Panlabs Taiwan Ltd (AAALAC Accreditation: 001553).n = 3 animals per timepoint at 8 timepoints  and control animals . Blood aliquots (300–400 µL) were collected via cardiac puncture from anesthetized mice in anticoagulant coated tubes, then kept on ice and centrifuged at 2500× g for 15 min at 4 °C. The plasma was harvested and kept frozen at −80 °C. Plasma samples were processed using acetonitrile precipitation and analyzed by HPLC-MS/MS. A plasma calibration curve was generated and a reportable linear range determined, along with the lower limit of quantitation.Twenty-four mice were administered 10 mg/kg NUC013 IV, The tolerability study and the tumor xenograft studies (below) were performed at the same institution. These studies were carried out in strict accordance with the recommendations of the NIH Guide for the Care and Use of Laboratory Animals. The protocols were approved by the IACUC of Southern Research Institute  (AAALAC Accreditation: 000643).Three mice were placed in a dose group on the first day of treatment (Day 1). Animals were treated with the selected dose of NUC013 administered intravenously for 3 consecutive days a week for 3 weeks. Animals were observed daily for mortality and moribundity. Body weights were measured daily starting on day 1. Animals were observed for up to 14 days after the last day of treatment. The MTD was determined by the highest dose at which animals did not die or were not euthanized and had less than 10% weight loss from the start of the study.7 tumor cells from culture in Matrigel™ of HL-60 human leukemia or LoVo colon cancer were implanted subcutaneously in the flank of 1.75-fold the number of NCr-nu/nu mice required for the study. Study initiation began when the required number of mice had tumors of approximately:3 (target group mean tumor volume of approximately 175 mm3) for the first set of studies.100 to 250 mm3 (target group mean tumor weight of approximately 30 mm3) for the second set of studies.14 to 63 mmFirst, 102/2 = Volume (mm3). The experiments were scheduled to last for 60 days from the day of tumor implant. Any animal whose weight decreased more than 30% from the weight on the first day of treatment or whose tumor reached 4000 mm3 in volume, ulcerated or sloughed off, or was moribund was euthanized prior to study termination.Mice with tumors in the proper volume range were arbitrarily assigned to groups. Mice received test article on 3 consecutive days per week for 3 weeks. Mice were observed daily for mortality and moribundity with weights and the tumor measurements taken twice weekly. Tumor volume was determined using the formula for an ellipsoid sphere: Length × WidthNUC013 has been shown to be a DNA methyl transferase inhibitor and an inhibitor of ribonucleotide reductase. In the NCI 60 cell line panel, NUC013 has demonstrated activity against significantly more cell lines than decitabine, particularly against TP53 WT cell lines. The effectiveness of NUC013 against TP53 WT cell lines may be mediated, at least in part, by derepression of TP53 and inhibition of p53R2 thus facilitating incorporation of NUC013 through self-potentiation. In animal models of human leukemia (TP53 null) and human colon cancer (TP53 WT), NUC013 has been shown to be significantly safer and more effective than decitabine at the tested doses and schedules.