GR50) and efficacy (GRmax) that are analogous to the more familiar IC50 and Emax values. In this work, we report GR-based, proliferation-corrected, drug sensitivity metrics for ~4,700 pairs of breast cancer cell lines and perturbagens. Such data are broadly useful in understanding the molecular basis of therapeutic response and resistance. Here, we use them to investigate the relationship between different measures of drug sensitivity and conclude that drug potency and efficacy exhibit high variation that is only weakly correlated. To facilitate further use of these data, computed GR curves and metrics can be browsed interactively at http://www.GRbrowser.org/.Traditional means for scoring the effects of anti-cancer drugs on the growth and survival of cell lines is based on relative cell number in drug-treated and control samples and is seriously confounded by unequal division rates arising from natural biological variation and differences in culture conditions. This problem can be overcome by computing drug sensitivity on a per-division basis. The normalized growth rate inhibition (GR) approach yields per-division metrics for drug potency ( IC50, the drug concentration at which cell count is half the control value, which is a traditional measure of potency, and Emax, the maximum effect at the highest concentration tested, which is a measure of efficacy. Although in use for many decades, this calculation is sensitive to the number of cell divisions taking place over the course of the assay, which differ when cell division rates vary. As a consequence, it is possible for IC50 values for a single drug in a single cell line to vary 100-fold or more simply as a consequence of exogenously imposed changes in the rate of division2. Natural cell division rates vary from one cell line to the next, often in a systematic manner depending on tissue of origin3, media composition, culture conditions, and plating density1. Because division rate is a powerful confounder in the calculation of IC50 and Emax values, and because it is often poorly controlled, we speculate that it is a contributor to the observed irreproducibility of drug dose-response data2–5.The prioritization of compounds for lead discovery, identification of pharmacogenomic associations, and study of cellular machinery requires reproducible and accurate data on drug response in cultured cell lines. In the case of anti-cancer drugs, which act by slowing cell proliferation or increasing the rate of cell death, the traditional approach is to expose cells to a drug over a range of concentrations, measure the number of cells at the end of a fixed period of time  and then compare that number to the number of cells in a vehicle-only control. The ratios are usually fitted to a sigmoidal curve from which it is possible to compute et al.2 corrects for variation in division rates by estimating the magnitude of drug response on a per-division basis. The GR value in the presence of drug at concentration c is GR(c)=2k(c)/k(0)−1 where k(c) is the growth rate of drug-treated cells and k(0) is the growth rate of untreated control cells. Growth rates can be estimated using time course data or, as in this paper, the number of cells prior to and at a fixed time after the addition of drug. Metrics of drug potency, GR50, and efficacy, GRmax, can then be calculated from the dose-response curve. The sign of the GR value is related directly to response phenotype: negative values reflect cytotoxicity, a value of 0 corresponds to complete cystostasis, and positive values reflect partial growth inhibition. GR calculations are described in detail at http://www.GRbrowser.org/, and a detailed method for performing the calculations with web-based software and an R pipeline is also available7.The normalized growth rate inhibition (GR) method recently introduced by Hafner 9 as well as substantial new data and comprise, after filtering low-quality data points, GR-based dose-response data for 71 breast cancer cell lines from all three major subtypes of breast cancer  and 107 perturbagens . We found that low growth was a good criterion for filtering out data with high relative error, as judged by standard error of the mean (SEM) for GR values, presumably because: (a) a very low division rate (fewer than one division per 72 h) is an indicator that the experimental setup is not optimized for the growth of a particular cell line; (b) fixed error in Cell Titer-Glo (CTG) assays makes measurement of smaller differences in cell number between control and experimental samples unreliable; and (c) partial cell cycle synchronization introduced during plating of cells with division times longer than the assay duration violates the assumption in GR calculations that growth is homogenous and constant10. As a quality control filter, we therefore eliminated from further consideration all samples in which the vehicle-only controls underwent too few divisions. Despite the need to filter out some data, the 4,700 unique cell line/perturbagen pairs described in this paper represent one of the largest collections of growth-corrected drug-response measurements currently available.The datasets presented here make use of drug dose-response data that have been described previously11. This required adjusting passage and plating conditions for each line.The original dataset  comprised the effects of 139 perturbagens  on 73 breast cancer cell lines, some in multiple cell growth conditions, determined by plating cells at a density such that they remained in logarithmic growth during the assayCells were allowed to attach overnight onto 96-well plates before being treated in technical triplicate for 72 h with nine doses of each perturbagen in a 1:5 serial dilution. The concentration range was optimized on six cell lines, and, for most cell line/perturbagen pairs, the highest concentration tested fell between 33 μM and 167 μM.12. A background CTG value was obtained from wells containing culture medium but no cells . Dataset DS0 [Data Citation 1] comprises all raw CTG values.Cell count was estimated using the Cell Titer-Glo (CTG) Luminescent Cell Viability Assay (Promega) after three days in drug (the endpoint of the assay). Cell count was also measured in untreated plates at the time of treatment. The raw CTG assay readout values were considered proportional to the number of viable cells and used as surrogates for cell count values, which is a widely used assumption with some caveatsDataset DS1 [Data Citation 2] comprises data for the 107 perturbagens  and 71 cell lines that could be unambiguously identified , representing 87% of the original dataset selected for further analysis (see Data Records). First, background CTG value was subtracted from the raw CTG values  in drug-treated wells. Background-corrected values below 1 or negative, which represented <0.1% of the data, were set to 1 to eliminate artefacts from near-background CTG values. Then, we calculated the following values:x(c), a robust average of three technical replicates for the background-subtracted CTG value following drug treatment at concentration c; x(c)=mean({xi∈x | abs(log10(xi)–log10(mean(x)))<1}) where x is the vector of treated values.–xctrl, the robust average background-subtracted CTG value in DMSO-treated control wells from the same plate; xctrl=mean({xi∈x | abs(log10(xi)–log10(mean(x)))<1.5)}) where x are all DMSO-treated control values.–x0, the background-subtracted median value from the untreated samples  measured at the time of treatment.–1:Dataset DS1 [Data Citation 2] comprises the GR value for each treated condition calculated as followset al.6. Given the data points and fitted equation, we extracted the response parameters:GR values for a specific drug across multiple concentrations were fitted to a sigmoid curve with the equation GR50: the primary metric of drug potency; the concentration of drug c at which GR(c)=0.5. If the value for GRinf (see below) is above 0.5, GR50 cannot be defined and we set its value to +∞. If GRinf is below 0.5 but the inferred GR50 value is half an order of magnitude (3.16-fold) above the highest tested concentration, we set the GR50 value to +∞ to avoid artefacts due to extrapolation (this affected 0.6% of conditions). In plots of GR50 values, GR50 values were capped at 100 μM for visualization purposes.GRmax: the primary metric of drug efficacy; the GR value at the highest tested dose of the drug. GRmax lies between –1 and 1; negative values correspond to a cytotoxic response (i.e. cell death), a value of 0 corresponds to a fully cytostatic response (no increase or decrease in cell number), and positive values less than one correspond to partial growth inhibition. GRmax can only be compared across drugs or cell lines when the highest tested doses are the same.GRAOC: the integrated effect of the drug across a range of concentrations as estimated from the ‘area over the curve’. A value of 0 means no effect of the drug across the full dose-response range. GRAOC can only be compared across drugs or cell lines when the dose range is the same.GRinf: a measure of drug efficacy extrapolated to an infinitely high drug concentration as determined from the asymptote of the dose-response curve; GRinf is similar to GRmax.hGR: the Hill coefficient of the fitted curve; it reflects the steepness of the dose-response curve. We constrained its value between 0.1 and 5.GEC50: an analogy to EC50 corresponding to the concentration of drug at half-maximal effect. GEC50 is relevant for drugs that have poor potency and that do not reach a GR value below 0.5. In the fitting procedure, GEC50 is constrained to lie within two orders of magnitude of the highest and lowest tested drug concentrations.Emax values, but fewer than 1% of the responses in the overall dataset were sufficiently cytotoxic that Emax values would not have been biased by the low division rate. Following filtering, we obtained 4,788 unique cell line/perturbagen pairs, the majority of which were recorded in biological duplicate for a total of 8,882 cell line/perturbagen pairs, each tested at nine doses in technical triplicate. Before averaging biological replicates when available, we further filtered the data to exclude measurements for which division time was greater than 80 h (corresponding to 0.9 division over the course of a 72 h assay). We included this cutoff based on preliminary data showing that GR values obtained from slow-growing cell lines had high uncertainty . The final dataset comprised 4,650 cell line/perturbagen pairs corresponding to a median of 88 perturbagens per cell line .We excluded from further consideration cell line/perturbagen pairs in which fewer than 0.3 cell divisions (a 23% increase in cell number) were recorded for the no-treatment control over the course of a 3-day assay . This was done because GR values quantify the effects of drugs on cell growth. If untreated control cultures are not growing, the response to drug is generally weak, and GR values become highly variable and biologically meaningless. In principle, it is possible to quantify the effects of highly cytotoxic drugs under these conditions using traditional 6 and found on the GitHub repo at https://github.com/datarail/gr_metrics. Other analysis was performed using MATLAB standard functions.GR calculation, curve fitting, and extraction of metrics was performed using scripts published in Hafner et al.8 and Daemen et al.9 and additional data generated subsequently (Data Citation 1). DS1 reports relative cell counts estimated from the available CTG values as well as computed GR values and nominal division rates for all cell line/perturbagen pairs from the raw dataset for which the cell line and perturbagen reagents used could be unambiguously identified  and for which the cell line demonstrated sufficient growth over the course of the assay to exceed our cutoffs (see Methods). DS2 reports the calculated GR metrics for the same set of cell line/perturbagen pairs. DS3 and DS4 report the median, upper quartile, and lower quartile GR metrics per perturbagen and per perturbagen class, respectively, across all cell lines in DS2. DS0 consists of a downloadable zip file containing multiple reference files necessary for annotating the raw data file with reagent identifiers and perturbagen concentration details, reference file metadata in the form of data column lookup tables (LUTs), experimental metadata including a detailed protocol, and a ReadMe file. DS1, DS2, and DS3 each consist of a downloadable zip file containing a data file, data file metadata in the form of a data column LUT, experimental metadata including a detailed protocol and reagent metadata tables, and a ReadMe file. DS4 consists of a downloadable zip file containing a data file, data file metadata in the form of a data column LUT, experimental metadata including a detailed protocol, and a ReadMe file. All files are provided in their original format and, where relevant, also in a non-proprietary, preservation-friendly format . All dose-response curves and metrics corresponding to DS2 also are available for interactive viewing at http://www.GRbrowser.org.This manuscript describes 4 new datasets  that are publically available as a single data package in the Dryad Digital Repository (Data Citation 2) alongside a fifth file bundle (DS0) consisting of the reference files used to process the file containing the raw dose-response data described in Heiser et al.1, and the code has been validated on multiple datasets. Use and installation instructions, as well as bug fixes, are available at our GitHub repo (https://github.com/datarail/gr_metrics). Methods for plating cells, adding drugs, and performing CTG assays have also been described in Heiser et al.8 and elsewhere. We have recently published an in-depth protocol10 for performing drug dose-response experiments in cell lines that includes advances in methodology not available at the time the current data were collected. We recommend that future studies follow these more recent guidelines.The GR method used to perform calculations in this paper has previously been describedx(c), xctrl, and x0 are more sensitive to fixed measurement noise in the case of slow growing cultures. Low division number can arise because some cells are inherently slow growing, but sporadic examples of slow growth are more likely to reflect defects in the plate, excess evaporation of the medium, or pipetting error. Regardless, eliminating data for these slow growing conditions improved the SEM of the GR values and metrics.One of the key biological premises implicit in computing GR metrics is that cells in untreated wells are proliferating in a uniform, exponential, and continuous manner. In principle, this should be true for all established cell lines, but in a large-scale drug-response experiment it is inevitable that some variability will be encountered. For this reason, we discarded any plate in which control cells underwent fewer than 0.3 cell divisions. When we examined cell line/perturbagen pairs in which cells had undergone more than 0.9 divisions in the absence of drug, we observed a substantially lower standard error of the mean SEM; . The 95tGR50 across all perturbagens and cell lines was low , but this estimate is biased by the many cases in which cells are resistant for which GR50 is set at infinity. For the subset of cell line/perturbagen pairs in which a substantial biological response is observed (GR50 <10 μM), 77% of the data have SEM values below half an order of magnitude. This is consistent with the GEC50 values, whose SEM is below an order of magnitude for 75% of the cell line/perturbagen pairs. Overall, the sigmoidal fit was good (r2>0.75) for 90% of the cell line/perturbagen pairs that show a substantial biological response (GRmax<0.5). Taken together, these results show that, for this dataset, differences in GR value above 0.2 or in GR50 values above half an order of magnitude should reflect substantial differences in sensitivity.The SEM of the GR values was below 0.1 for 75% of the data in dataset DS1, but 10% of the conditions in DS1 remained substantially variable across replicates (SEM > 0.2). Among the GR values with SEM > 0.2, we observed little bias by cell line. We therefore concluded that the data were impacted primarily by sporadic rather than systematic error (see Methods). With respect to estimation of drug potency, the SEM for 2: (1) it ensures that enrichment analysis is not biased by differences in division rate, and (2) it makes it possible to distinguish genes associated with drug-induced cytotoxicity  from cytostasis . In the current study, we first compared potency, as measured by GR50 values, and efficacy, as measured by GRmax values, by drug class across cell lines (see GR50), whereas HDAC inhibitors and DNA cross-linkers have the highest efficacy (low GRmax). Many drugs induced a cytotoxic response at the highest concentrations , but most MAPK inhibitors and the majority of the ErbB, PI3K, and RTK inhibitors had positive GRmax values, showing that such drugs are partially cytostatic in most breast cancer cell lines. When results were sorted by clinical subtype, we found, for example, that tubulin-binding drugs were generally less efficacious in non-malignant (NM) and hormone-receptor-positive cell lines (HR+) than in HER2-amplified (HER2amp) and triple-negative (TNBC) cells; such drugs are used most widely in the treatment of TNBC.Uses of our data include identifying cell lines or subtypes that are particularly sensitive or resistant to a class of drugs (or the converse) for follow-up investigation. Using GR metrics for systematic pharmacogenomics studies has two advantages relative to standard approachesIC50 and Emax values for the Heiser et al.8 dataset are highly variable across drugs and cell lines13. When we repeated this analysis using the expanded dataset and GR-based drug metrics described in this work, we came to the same conclusion, namely that values for GR50, GRmax, GRAOC, and hGR are variable across cell lines and drugs , we observed no correlation between GR50 and GRmax (Spearman’s p > 0.05).Contemporary analysis of tool compounds and therapeutic drugs focuses almost entirely on comparing differences in drug potency, with relatively little attention paid to efficacy as measured by maximum drug effect. We have previously shown, however, that both nd drugs . For somGR50 values for tubulin-binding drugs are very similar across cell lines; variation in response primarily involves GRmax values, many of which are negative .Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Plasmablastic lymphoma (PBL) is a very aggressive variant of diffuse large B-cell lymphoma initially described in the oral cavity of HIV-infected individuals. PBL represents a diagnostic challenge given its characteristic morphology and lack of CD20 expression, and also a therapeutic challenge, with early responses to therapy, but with high relapse rates and poor prognosis. In recent years, our understanding and clinical experience with PBL has increased in both HIV-positive and -negative settings. However, given its rarity, most of the data available rely on case reports and case series. The main goal of this article is to systematically review the most recent advances in epidemiology; pathophysiology; clinical, pathologic, and molecular characteristics; therapy; and prognosis in patients with PBL. Specific covered topics include new pathological markers for diagnosis, its association with Epstein-Barr virus, and the need of more intensive therapies.


In this study, we report a miRNA122a based targeted gene therapy for hepatocellular cancer stem cells (CSCs). First, we assessed the levels of miRNA122a in normal human hepatocytes, a panel of hepatocellular carcinoma (HCC) cell lines and hepatocellular CSCs observing its significant downregulation in HCC and CSCs. The miRNA122a binding site was then incorporated at the 3’-UTR of reporter genes gaussia luciferase (GLuc) and eGFP which resulted in significant hepatocyte detargeting. Using this strategy for the delivery of gene directed enzyme prodrug therapy (GDEPT) utilizing the cytosine deaminase/5-fluorocytosine (CD/5-FC) system, we showed significant killing in cells with low or no miRNA122a while those cells, such as hepatocytes with high miRNA122a were largely spared. Next, we showed that CSC enriched tumorspheres exhibit a significant downregulation of miRNA122a expression providing a rational to exploit its binding site for targeted gene delivery. Using plasmids harboring reporters GLuc and eGFP with or without miR122a binding sites, we showed high reporter expression in the CSCs and little reported expression in the non-enriched cultures. Finally, we demonstrate the efficacy of miRNA122a based post-transcriptionally targeted GDEPT for hepatocellular CSCs. Hepatocellular carcinoma (HCC) is the most prevalent form of primary malignancy in the liver and is the third leading cause of cancer related death worldwide , 2. CurrCancer stem cells (CSCs) represent a subpopulation of cancer cells with innate resistance to radio and chemotherapies and are vital for tumor progression and recurrence after therapy , 7. AccumicroRNAs (miRNAs) are small non-coding RNA molecules which post-transcriptionally regulate the expression of genes that are involved in a variety of cellular functions including development, maintenance and/or elimination of cancer stem cells by binding to its complementary site usually present at the 3′-UTR of the corresponding gene. A number of miRNAs have been reported to be dysregulated in HCC derived CSC . miRNA12In this study, we demonstrate the utility of a miRNA122a based strategy to target HCC and hepatocellular CSCs for gene delivery which is pivotal for targeted cancer gene therapy. We show that hepatocellular CSCs exhibit significant downregulation of miRNA122a and that including the miRNA122a binding site into the 3’-UTR of a vector results in significant hepatocyte detargeting and subsequent targeting of HCC and hepatocellular CSCs.We quantified the levels of expression of miRNA122a in primary human hepatocytes, and a panel of HCC and non-HCC cell lines. The copy number of miRNA122a was reported as copies per 1000 copies of human positive control. Using this method, primary human hepatocytes were found to contain an average of 5655 copies of miRNA122a per 1000 copies of control while the expression of miRNA122a was not detected in HCC cell lines Hep3B, SKHep1, PLC/PRF/5, and SNU423    was significantly inhibited in primary human hepatocytes after transfection with CMV-GLuc-miR122a*3  Figure . Similar) Figure . In cont) Figure  and 2E.p < 0.001). The addition of miRNA122a inhibitors did not alter the luciferase expression in the low/non-expressing HCC cell lines (data not shown).In order to confirm that miRNA122a expression was responsible for the detargeting of our vectors, we utilized miRNA122a inhibitors and mimics to alter miRNA expression in hepatocyte and HCC cell lines. Using the miRNA122a inhibitor, we showed a significant increase in luciferase expression in both primary human hepatocytes Figure  and Hepap < 0.005). Luciferase expression decreased from 89.8% to 27.3%, 75% to 1.8%, 70% to 1.7%, and 101% to 12% (p < 0.005) in HCC cell lines Hep3B, PLC/PRF/5, SKHep1 and SNU423 respectively  whereas the miRNA122a negative HCC cell lines showed no significant difference in proliferation  and examined their ability to inhibit cellular proliferation and induce cytotoxicity. CD functions by converting the prodrug 5-FC into a cytotoxic metabolite. In the proliferation study, cells transfected with CMV-CD-miR122a*3 and incubated with 5-FC were normalized against proliferation observed with cells transfected with an untargeted CMV-CD construct. The HuH7 cell line, expressing miRNA122a at similar levels to that of normal hepatocytes, transfected with CMV-CD-miR122a*3 had a significantly higher proliferation than those transfected with the untargeted CMV-CD constructs , whereas no significant difference in cell death was observed between groups CMV-CD and CMV-CD-miR122a*3 in HCC cell lines Hep3B, PLC/PRF/5, SKHep1 , CD133 (p < 0.005), CD90 (p < 0.005), and Oct4 (p < 0.005)  in HuH7 cultures enriched for CSCs  Figure  normalizs Figure . These rP < 0.05).Next, we investigated whether the miRNA122a binding site could be utilized for targeting CSCs derived from HCC. To do this, we transfected HuH7 and HuH7 CSCs with CMV-eGFP-miR122a*3, and CMV-GLuc-miR122a*3 and normalized the expression of reporters with CMV-eGFP and CMV-GLuc respectively. We showed that HuH7 cultures, enriched for CSCs, had a significant increase in the expression of GLuc Figure  and eGFPP < 0.05) with a 1.91 fold higher cell death observed  by including disease specific regulatory elements like tumor specific promoters and miRNA binding sites , 23. In et al. it was shown that CD133+ CSCs isolated from the human HCC cell line, PLC/PRF/5 also exhibited a significant reduction in miRNA122a compared to non-CSCs [The well-known intra and inter-tumoral heterogeneity of HCC means that not all subtypes may have a reduced miRNA122a profile , 30. Whenon-CSCs . In thisnon-CSCs . Given tExploiting the differential expression of miRNA122a between functional hepatocytes, HCC and hepatocellular CSCs, we designed vectors incorporating 3 copies of the binding site of miRNA122a with the goal of limiting expression of transgenes to those cells with reduced miRNA122a expression, i.e. HCC and hepatocellular CSCs. Using luciferase as a marker transgene, we showed that cells expressing miRNA122a (primary hepatocytes and HuH7) had a significant decrease in luciferase expression. Conversely, HCC cells with little or no miRNA122a had significantly higher luciferase expression. These results were in line with previous studies exploiting the miRNA122a binding site for efficient hepatocyte detargeting , 33. AftTo explore the potential therapeutic benefit of using miRNA122a binding sites in HCC, we constructed vectors expressing the suicide gene cytosine deaminase (CD) with or without the miRNA binding sites (pCMV-CD-miR122a*3 and pCMV-CD). The CD gene produces an enzyme that converts the non-toxic 5-FC prodrug to the cytotoxic 5- fluorouracil (5-FU). We found that the use of post-transcriptional targeting of HCC and the subsequent detargeting of hepatocytes using miRNA122a was both feasible and effective, with significantly more killing and the inhibition of proliferation in HCC cells. Cell death and inhibition of proliferation was directly related to the presence or absence of miRNA122a in the cells. Using the pCMV-CD-miR122a*3 vectors in the CSC enriched cultures, we also showed significant cytotoxicity in line with miRNA122a expression and confirmed its utility in targeting CSCs. By targeting CSCs with a suicide gene therapy approach, such as the CD/5-FC system used in this model, there is the potential for a double bystander effect. The first induced by the CD/5-FC itself, where the non-toxic 5-FC is processed by the CSCs expressing CD into the toxic anabolite 5-fluorouracil (5-FU) . 5-FU thThe increasing knowledge of the genetic makeup of HCC and the CSCs derived from them allows identification of specific expression patterns which make them different from the normal liver cells. Initial work on utilising this knowledge for targeted gene therapy centred on the use of HCC restricted tumour specific promoters, such as that for alpha- fetoprotein (AFP), to drive transgene expression . The usemiRNA122a negative HCC cell lines Hep3B, PLC/PRF/5, SKHep1, and SNU423 were obtained from ATCC and maintained in DMEM  media supplemented with 10% fetal bovine serum (FBS)  and 1% penicillin/streptomycin (P/S) (Gibco). miRNA122a positive HCC cell line HuH7 was provided by Dr. Kim Bridle (University of Queensland). Cell line ID service was provided by the Australian Genome Research Facility (AGRF) and cell line genotyping was performed to confirm identity of cell lines. Breast cancer cell line T47D and prostate cancer cell lines LNCaP and DU145 were maintained in DMEM media with 10% FCS and 1% P/S. Melanoma cell lines 92.1, Mel202, Mel270 (gifted by Nicholas Hayward) and ovarian cancer lines SKOV3, CAOV3, TOV21G were cultured in RPMI media (Thermo Fisher Scientific) supplemented with 10% FCS and 1% P/S. Human retinal pigmental epithelium cell line ARPE-19 was maintained in DMEM/F12 media (Thermo Fisher Scientific) with 10% FCS and 1% P/S. Cryopreserved human hepatocytes (HUCS10P)  containing pooled hepatocytes from 10 donors were cultured as per the manufacturer's recommendations in human hepatocyte maintenance media.3D tumorspheres of HuH7 were maintained in a serum free, stem cell conditioned NSA media as previously described . The NSAEndogenous expression levels of miRNA122a was quantified by quantitative real time PCR (qRT-PCR) with Bioline Lo-Rox Sybr  using the ViiA7 RT-PCR machine (Thermo Fisher Scientific) at following conditions: 95° C- 2mins followed by 40 cycles of 95° C- 5 s, 60° C -15 s and 70° C -15 s on the cDNA which was synthesized from total RNA isolated with trizol using the MystiCq microRNA cDNA Synthesis Mix (Sigma Aldrich) as per the manufacturer's recommendations. MystiCq Universal PCR  and 5′- TGGAGTGTGACAATGGTGTTTGT- 3′ primers were used and the levels if miRNA122a was calculated as number of copies per 1000 copies of human positive control using formula (2^(Ct control-Ct sample))*1000. Similarly, HCC stemness markers CD44, EpCAM, and Oct4 were quantified as number of copies per 1000 copies of GAPDH housekeeping gene using primers listed in Table The gene encoding gaussia luciferase (GLuc) with three miRNA122a binding sites (ACACCATTGTCACACTCCAAC*3) at the 3′-UTR was artificially synthesized (Thermo Fisher Scientific). The gene with and without miRNA binding sites was then cloned in the pscAAV-GFP  using enzymes EcoRI, StuI and EcoRI, EcoRV to obtain CMV-GLuc and CMV-GLuc-miR122a*3 (Supplementary Information) respectively. Similarly, artificially synthesized cytosine deaminase (CD) was cloned in the above mentioned plasmids replacing GLuc to obtain CMV-CD and CMV-CD-miR122a*3.All transfection studies for studying GLuc and eGFP expression were performed with Lipofectamine 3000 (Thermo Fisher Scientific) as per the manufacturer's protocol. Briefly, 30,000 cells were seeded in a 24 well plate and transfection was performed with 500 ng of plasmids. 72 hours post-transfection, the amount of secreted GLuc was quantified with the Pierce gaussia luciferase glow assay kit (Thermo Fisher Scientific) as per the manufacturer's recommendations. The chemiluminescence measurement was done with the Infinite 200 Pro NanoQuant . For primary human hepatocytes, the transfections were performed an hour after seeding and the amount of secreted GLuc was measured after 24 hours. In order to account for the difference in transfection efficiencies across cell lines, chemiluminescence detected with CMV-GLuc-miR122a*3 was normalized against that with CMV-GLuc for individual cell type. Tumorspheres of HuH7 were transfected at day 3 after seeding in the NSA media and secreted GLuc was quantified after 48 hours. Similarly, to quantify the percentage of eGFP positive cells, flow cytometry was performed with the FACS Canto II and data was analysed with FCS express version 3 . Percentage of GFP positive cells after transfection with CMV-eGFP-miR122a*3 was normalized with CMV-eGFP.miRNA122a inhibition experiments in primary hepatocytes were performed by co-transfecting miRNA122a inhibitor  (5pmol) and either CMV-GLuc or CMV-GLuc-miR122a*3 in a 24 well plate using Lipofectamine 3000 as per the manufacturer's protocol. 24 hours post transfection, secreted GLuc was quantified with Pierce gaussia luciferase glow assay kit. Similarly, HCC cell lines Hep3B, SKHep1, PLC/PRF/5, and SNU423 were co-transfected with miRNA122a mimic  (5 pmol) and either CMV-GLuc or CMV-GLuc-miR122*3. The amount of secreted GLuc for each group was reported as a percentage of CMV-GLuc.For cell proliferation assays, 10,000 cells were transfected with CMV-CD or CMV-CD-122a*3 in a 96 well plate and media containing 10 μm 5-FC was added after 24 hours. CellTiter96 Aqueous One Solution Cell Proliferation Assay kit  was used to quantify cell proliferation after 48 hours of incubation with 5-FC containing media. Absorbance was measured at 540 nm with the Infinite 200 Pro NanoQuant. Percentage proliferation was calculated for CMV-CD and CMV-CD-122a*3 for each cell line and percentage proliferation with CMV-CD-122a*3 was reported relative to CMV-CD in order to account for the difference in transfection efficiencies across cell lines.To quantify cell apoptosis, flow cytometry based on Annexin/PI staining was used (Life Technologies). 30,000 cells were transfected with CMV-CD and CMV-CD-122a*3 in a 24 well plate and incubated for either 24 hours (for tumorspheres) or 48 hours (adherent cells) with 10 μm 5-FC containing media. Cells were then washed with PBS, collected and co-stained with Annexin V and PI as recommended by the manufacturer. Annexin V/PI positive cells were quantified with the FACS Canto II and data analysis was performed with FCS express 3. The percentage of apoptotic cells after transfection with CMV-CD-122a*3 was normalized with CMV-CD.t-test was performed to test the difference between groups (GraphPad Prism v7) .All experiments were repeated at least thrice in triplicates and results were presented as mean ± SD. Two-tailed student's


Brain tumor glioblastoma has no clear molecular signature and there is no effective therapy. In rodents, the intracellular distribution of the cyclic AMP (cAMP)-dependent protein kinase  R2Alpha subunit was previously shown to differentiate tumor cells from healthy brain cells. Now, we aim to validate this observation in human tumors. The distribution of regulatory (R1 and R2) and catalytic subunits of PKA was examined via immunohistochemistry and Western blot in primary cell cultures and biopsies from 11 glioblastoma patients. Data were compared with information obtained from 17 other different tumor samples. The R1 subunit was clearly detectable only in some samples. The catalytic subunit was variably distributed in the different tumors. Similar to rodent tumors, all human glioblastoma specimens showed perinuclear R2 distribution in the Golgi area, while it was undetectable outside the tumor. To test the effect of targeting PKA as a therapeutic strategy, the intracellular cyclic AMP concentration was modulated with different agents in four human glioblastoma cell lines. A significant increase in cell death was detected after increasing cAMP levels or modulating PKA activity. These data raise the possibility of targeting the PKA intracellular pathway for the development of diagnostic and/or therapeutic tools for human glioblastoma. Glial tumors of the brain are classified into four grades according to World Health Organization staging. Glioblastoma multiforme (GBM) is the most malignant (grade IV) glial tumor, with a dismal prognosis, despite recent therapeutic advances. GBM is highly invasive and recurs in nearly 90% of cases at the original site . MultiplPKA are tetramers of two regulatory and two catalytic subunits, present in every cell where they regulate several processes . When thdf = 1, p < 0.001 (Inspection of data from the The Cancer Genome Atlas (TCGA) database was performed on the expression signals for the regulatory PKA subunits in 540 cases of GBM, compared to non-tumor brain samples from the Genotype Tissue Expression (GTEX) study . R2A app < 0.001 a). These < 0.001 . ApparenThe presence of the catalytic and regulatory subunits of PKA was examined by Western blot in four human GBM cell lines, fractionated into soluble and membrane-bound fractions. All the four cell lines were positive for nestin b, NES. BThe insoluble and soluble fractions of human glioblastoma biopsies were compared to the corresponding fractions of the primary culture derived from the same biopsy, showing the same pattern of reactivity for both R2 and CD133 c, case 6To establish whether the cAMP-activated intracellular signaling pathway could be a target for glioblastoma pharmacological treatment, we tested a panel of cAMP/PKA-affecting agents, and examined their effect on survival of four human GBM cell lines. Interference with the cAMP–PKA pathway induced cell death . A signiThe in vitro data showed that PKA levels could vary in tumor cells, and that PKA activity could influence cell survival. The next step was to examine the complex brain tumor tissue for the distribution of PKA subunits. Immunofluorescence on the GBM specimens showed that R1 was present in isolated clusters throughout the tissue, in variable grades: under the present conditions, some GBM specimens were not labeled at all, while others presented clusters of R1 in some areas of the tumors . A dotteAt the cellular level, PKA R2 subunit distribution was reminiscent of that observed in cell cultures, and co-localized with a Golgi marker u. The saTo date, the treatment options for malignant gliomas are disappointing. Interference with intracellular signaling pathways that modulate cell proliferation may be a viable target. GBM presents neither clear molecular signatures nor peculiar genetic alterations , and thePRKAR2B gene resides, and alterations in chromosome 17, which hosts the PRKAR1A gene. In this way, the balance of PKA R1 to R2 subunits is altered [The anomalies found in GBM are diverse and numerous. Among the most frequent are the gain of chromosome 7, in which the  altered . This baInteractions among different intracellular pathways ultimately determine the cellular response. Hence, even minor changes in the organization of a single pathway may have large and unexpected consequences on cell function. Moreover, activation of the signaling pathway, that controls cellular functions critical to maintaining cancer characteristics, may be reversed by changing intracellular conditions. For example, an increase in cAMP concentration may shift the activation pattern from R1 (high affinity) to R2 (low affinity) subunits, in turn affecting their downstream effectors . It has In four human glioma cell lines, R2 and the catalytic subunit may be found in soluble and particulate cell fractions. In contrast to what is seen in normal brain primary cultures, both the glioma cell line and GBM primary culture present a diffuse R1 cytoplasmic labeling and a striking hotspot of R2 co-localized with the Golgi marker, similar to what was observed in rat and mouse GBM cell lines . TherefoImmunohistochemistry on GBM biopsies revealed that R1 is scarcely present (in isolated hotspots) in some specimens. Even the catalytic subunit is present in discrete clusters. The most striking feature of GBM samples is however the consistent R2 immunoreactivity in the tumor cells, located at the Golgi, an association that was previously observed in different cells . R2 distThese data suggest that R2 immunoreactivity may be exploited for diagnostic purposes in GBM samples. However, it should be considered that after irradiation and chemotherapy, the tissue was too autofluorescent to be examined with reliability. The amount of intracellular cAMP varies during cell cycle in malignant gliomas, being higher in G0/G1 and lower at mitosis: cAMP arrests the cell cycle and induces differentiation and apoptosis, possibly by altering the rate of PKA subunit degradation , in thisIEX-1 [Of note, the effects of cAMP on glioma cells are reversible, and a few cells are not sensitive to cAMP action . TherefoIEX-1 , and GFAIEX-1 ,40. GFAPConceivably, the cAMP system is not a suitable pharmacological target because of its universal distribution and its implication in almost every cellular process, in both normal and pathological cells. Therefore, a more selective targeting of GBM-specific features should be exploited. If generic PKA acting agents are not specific enough and may induce off-target unwanted effects, other strategies could involve the targeting of pathways that use PKA in GBM-specific processes. For example, it could be interesting to act on different pathways that use PKA as an effector. Various dopamine receptors have been implicated in GBM stem cell survival and proliferation . They acTherefore, the activation of PKA in glioma cells induces several processes, that ultimately lead to differentiation. If the presence of R2A is higher in GBM than in healthy brain tissue, then it would be desirable to reduce it, with the aim of sponsoring the expression of the other PKA subunits that are necessarily induced for healthy cell survival.PRKARIIA, PRKARIIB, PRKARIA and PRKARIB) in GBM samples (n = 540). Data were interrogated using the r2 platform (https://hgserver1.amc.nl/cgi-bin/r2/main.cgi) to obtain Kaplan–Meier plots that were thresholded at the best expression level predictive of survival. Independent validation was obtained by interrogating the REMBRANDT database, which collects data from 178 GBM patients generated with Affymetrix® HG U133 v2.0plus using the BETASTASIS resource (http://www.betastasis.com/glioma/rembrandt/), thresholding at the median value to discriminate high and low expression. The TCGA database was also explored with the University of California Santa Cruz (UCSC) XENA browser (https://xenabrowser.net/), to compare the data from GBM patients to data obtained from normal brains in the GTEX study (n = 158), generated with Illumina TrueSeq RNA sequencing and Affymetrix® Human Gene 1.1 ST Expression Array V3. The analysis of survival was performed with chi-square comparing the two groups .The TCGA database was searched to obtain gene expression data for PKA regulatory subunit coding genes . Patients gave their written informed consent for taking the samples  and were recruited at the University of Padova Medical School. Twenty-eight patients were examined , unless otherwise stated. Reagents for cell cultures were from Gibco .PTEN and CDKN2A), U87 , and LN229 (mutated in P53) were obtained from ATCC . Human GLI36 glioblastoma cells were obtained from the University of California [2. Primary cell cultures were obtained from biopsies (see above) and maintained in DMEM supplemented with antibiotics and 10% fetal bovine serum [Human high-grade glioma cell lines A172  with protease inhibitor cocktail  and forced 40 times through a 27-gauge needle. They were then centrifuged for 15 min at 6000 rpm at room temperature. The supernatant was collected, and the pellet was washed again with the same volume of PBS and centrifuged as above twice. The second and third supernatants were discarded and the pellet resuspended in the same volume of PBS. The protein extraction from the 30 mg biopsy was performed as above in 40 volumes of PBS. Pellets and the first supernatant were run on a 12% polyacrilamide gel, then blotted on nitrocellulose membrane, blocked for 60 min with 1.5% bovine serum albumin, and incubated overnight with primary antibodies against: PKA catalytic subunit, PKA RIIA subunit, or PKA RIB subunit , CD133  or nestin , incubated for 2 h with horseradish peroxidase (HRP)-conjugated antirabbit secondary antibody  and revealed through chemiluminescence . Cells were grown in coverslips, washed in PBS, and frozen. After thawing, they were incubated for 5 min in 2% Triton X-100 in PBS at room temperature and fixed in 5% formalin and 1% Triton X-100 for one minute at 37 °C. Tissues were cut on a cryostat at 20 μm. Slides were air dried and post-fixed for one hour in 5% formalin at 18 °C, followed by 30 min in 2% Triton X-100 in PBS. Primary antibodies were incubated overnight. The following antibodies were used : RIIA (rThe present data suggest that the intracellular distribution of the different PKA isoforms is characteristic of each cell type. PKA distribution varies during physiological modifications and/or pathological transformations, and could be exploited as a diagnostic or therapeutic target in glioblastoma.


MET amplification but exhibited the epithelial-mesenchymal transition (EMT) phenotype. Overexpression of EMT inducers, Snail or Slug, in the parental lines promoted their resistance to gefitinib. The gefitinib-resistant cell lines regained their sensitivity to gefitinib and displayed reverse EMT phenotypes after long-term culture in gefitinib-free culture medium. Blockage of reverse EMT by stable expression of Snail or Slug prevented the regain of TKI sensitivity. In conclusion, reverse EMT is one of the major mechanisms for the regain of TKI sensitivity in TKI-resistant NSCLC cells, suggesting that the development of small molecules targeting the EMT process may prolong the efficacy of TKIs in NSCLC patients with EGFR mutations.Tyrosine kinase inhibitors (TKIs) are currently the first-line treatment for non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutations. These patients receive platinum-based chemotherapy as the second-line treatment after they develop resistance to TKIs. Many patients regain sensitivity to the TKIs used in the first-line treatment after the failure of chemotherapy. However, the molecular mechanism for the regain of TKI sensitivity is largely unknown. In this study, we established gefitinib-resistant PC9 and HCC827 cell lines, which did not harbor the EGFR T790M mutation and  Approximately 50% of non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutations, such as exon 19 deletion and L858R point mutation, receive tyrosine-kinase inhibitors (TKIs) as their first-line treatment. Despite the initial response to TKI therapy, the tumor eventually recurs due to acquired drug resistance to the TKIs. In 50% of these patients, the resistance against TKIs can be explained by secondary EGFR mutations, mainly T790M point mutation. A third-generation TKI, osimertinib, targeting the EGFR T790M mutation has been recently developed and prolongs disease-free survival of NSCLC patients [human epidermal growth factor receptor 2 (HER2) amplification, and activation of secondary pathways, such as MET-mediated pathway [Although osimertinib is very effective in lung cancer patients with the secondary EGFR mutation, the other 50% of patients who do not develop the T790M mutation receive platinum-based chemotherapy as their second-line treatment, and the prognosis of these patients is poor . Interes pathway . HoweverEpithelial-to-mesenchymal transition (EMT) is a reversible process that controls the phenotypic changes due to cell mobility , metabolEMT has long been linked to resistance of lung cancer cells to chemotherapy , 19 and 2 at 37°C. For long-term culture, all the cell lines were tested for mycoplasma every month. The gefitinib-resistant sublines were established by stepwise escalation of gefitinib concentrations from 0.5 μM to 10 μM. Gefitinib was purchased from LC Laboratories . The culture medium was replaced every 3 days. After 6 months, the resistant cells were regularly maintained in culture medium containing 10 μM gefitinib. For gefitinib-withdrawal experiments, the doubling time for the PC9-WGR and HCC827-WGR cells was determined, approximately 36.8 hours and 55.7 hours, respectively. During the gefitinib withdrawal, the PC9-WGR and HCC827-WGR cells were passaged every 3 days, and the cells were seeded at 30–40% confluency.The human non-small cell lung cancer cell lines PC9 and HCC827, carrying EGFR exon19del E746-A750, were purchased from American Type Culture Collection. Both cell lines were maintained in RPMI-1640 medium supplemented with 10% fetal bovine serum, 100 U/mL penicillin and 100 μg/mL streptomycin. The cell lines were kept in a humidified incubator containing 5% CO3 cells/well were seeded in 96-well microtiter plates. Different concentrations of gefitinib were added 24 hours after seeding. After 72 hours of incubation, CellTiter® 96 non-radioactive cell proliferation assay  was performed according to the manufacturer’s instructions, and the optical density was determined at 560 nm by using a microtiter plate reader . The mean absorbance at each drug concentration was normalized to the control. The IC50 was defined as the drug concentration that caused a 50% reduction in relative absorbance.To determine the cytotoxic effect of gefitinib in sublines of PC9 and HCC827, cells at the density of 5×10Slug , Snail  and Twist1   were cloned into the pLex-MCS lentiviral vector. The shRNA-containing lentiviral vectors were provided by the National RNAi Core Facility, Academia Sinica, Taiwan. The identifier (ID) numbers of the two shRNA clones used for E-cadherin knockdown are as follows: TRCN0000130433 (shE-cad #1), TRCN0000131097 (shE-cad #2). The lentiviral particles for all expression plasmids and shRNAs were prepared by co-transfection with SPAX2 and pMD2G plasmids into HEK293T cells. Stable clones of individual infected cell lines were established by using puromycin (1–3 μg/mL).For generation of the gene expression lentiviral plasmids, synthesized DNA fragments of Total RNA isolation and reverse transcription were conducted using the method described previously . QuantitFor Western blot analysis, the cells were harvested and lysed in 1X RIPA buffer containing protease inhibitors and phosphatase inhibitors . Protein concentration was determined using a Bio-Rad DC protein assay kit . Total protein (20 μg) was loaded onto a 10% SDS-polyacrylamide gel for electrophoresis. Specific antibodies against E-cadherin , N-cadherin , Vimentin , Snail , Slug , and Twist1  were applied to detect the targets. Monoclonal anti-Actin antibody  was used as the loading control. The following secondary antibodies were used: goat anti-rabbit or anti-mouse immunoglobulin G (IgG)-conjugated horseradish peroxidase . To detect the specific signals, the membranes were examined using the ECL Prime Western Blotting Detection System .p<0.05 was considered significant. Statistical analyses were performed using SPSS  software.For the quantitative real-time PCR and cell viability assay, three independent experiments were conducted, and three technical replicates for each sample in every independent experiment were performed. For all Western blot analysis, three independent experiments (cell lysate from different passages of the cell cultures) were performed. The quantitative data are presented as the mean±SD. Two-sided Student’s T-test was performed. 50) of gefitinib for PC9-GR (24.0±7.2 μM) and HCC827-GR (25.7±3.2 μM) sublines were dramatically increased compared to their parental cell lines   . Unlike ctively) . The HCCctively) . By usinll lines . In parall lines . The occll lines .50 = 0.04±0.02 μM, 9.0±1.8 μM and 11.8±2.0 μM for the PC9-pLex, PC9-pLex-Slug and PC9-pLex-Snail cells, respectively)   (Slug has been identified as an EMT inducer and contributes to gefitinib resistance in NSCLC . In addictively) . In the ctively) . Similarctively) . Since tctively) . Howeverctively) .Clinical observations showed that lung cancer patients with EGFR mutations who developed TKI-resistance and received chemotherapy as the second-line treatment remained responsive to the original TKIs as the third-line treatment. To demonstrate this possibility in vitro, gefitinib was removed from the culture medium (PC9-WGR and HCC827-WGR) of the PC9-GR and HCC827-GR sublines, which were maintained in gefitinib-containing culture medium. The cell morphology, gefitinib response and EMT status of the parental, GR and WGR PC9 and HCC827 sublines were monitored every 10 passages. Bright-field microscopy images showed that the cell morphology of the PC9-WGR subline gradually reverted to the spindle-like shape of the parental PC9 cells after 30 passages . Accompa50 of gefitinib in the PC9-WGR subline, while the IC50 of gefitinib was significantly reduced in the vector-only control group. In parallel, the forced expression of Slug or Snail blocked the regain of gefitinib sensitivity in the HCC827-WGR subline. Together, these results demonstrated that the regain of gefitinib sensitivity after prolonged withdrawal of gefitinib was mediated by reverse EMT in the TKI-resistant lung cancer cells.To investigate whether reverse EMT is the cause of the regain of gefitinib sensitivity, Slug or Snail was ectopically expressed in the PC9-GR and PC9-WGR sublines. In the vector-only control group, reverse EMT occurred after prolonged withdrawal of gefitinib from the culture medium. Ectopic expression of Slug or Snail diminished the increase in E-cadherin and decrease in N-cadherin and Vimentin in the PC9-WGR subline . SimilarSince the discovery of TKIs, targeted therapy has become the most effective way to manage lung cancer. Despite the initial response of patients to TKIs, most of the patients still experience tumor recurrence due to acquired resistance to TKI and receive chemotherapy as their second-line treatment . HoweverIn addition to findings in vitro, EMT has been linked to the poor clinical outcomes of lung cancer patients , 28, espMET amplification) does not alter the gefitinib-resistant phenotype of the cells [MET amplification regain the sensitivity to gefitinib [MET amplification, but displayed EMT phenotypes. Similar observation was also reported from other groups [Dose-escalation protocols have been widely used to establish TKI-resistant NSCLC cell lines with EGFR mutations. However, different experimental procedures between the protocols may lead to phenotypic or genotypic variations of the TKI resistant cells. For example, continuous exposure of PC9 cells to increasing concentrations of gefitinib results in the frequent T790M mutation, but intermittent treatment did not . Importahe cells , 33, butefitinib , which iefitinib . Howeverr groups , 34. Ourr groups . Due to Unlike Snail and Slug, the overexpression of Twist1 did not induce EMT under our experimental conditions, although these three transcription factors inhibit the expression of E-cadherin , 36. It Many environmental factors and intracellular proteins that can promote EMT have been identified . However


CCND2) is a member of the D-type cyclins, which plays a pivotal role in cell cycle regulation, differentiation and malignant transformation. However, its expression status and relative regulation mechanism remains unclear in renal cell cancer (RCC). In our study, the mRNA expression level of CCND2 is down-regulated in 22/23 paired RCC tissues (p<0.05). In addition, its protein expression level is also decreased in 43/43 RCC tumor tissues compared with its corresponding non-malignant tissues (p<0.001). We further detected that CCND2 was down-regulated or silenced in 6/7 RCC cell lines, but expressed in “normal” human proximal tubular (HK-2) cell line. Subsequently, MSP and BGS results showed that the methylation status in CCND2 promoter region is closely associated with its expression level in RCC cell lines. Treatment with 5-Aza with or without TSA restored CCND2 expression in several methylated RCC cell lines. Among the 102 RCC tumors, methylation of CCND2 was detected in 29/102 (28%) cases. Only 2/23 (8.7%) adjacent non-malignant tissues showed methylation. We then analyzed the correlation of clinical features and its promoter methylation. Collectively, our data suggested that loss of CCND2 expression is closely associated with the promoter aberrant methylation.Cyclin D2 ( RB), a critical negative regulator of G1/S transition [RB inactivates it and leads to the activation of transcription factors such as E2F suppressed by RB, which then increased the activation of transcription of genes involved in DNA synthesis and induced cells to enter S phase [In mammals, loss control of cell cycle is a distinctive feature of human carcinogenesis. The regulation of cell cycle mainly associated with the orderly change of phase-specific protein, such as cyclins, cyclin-dependent kinases (CDKs) and CDK inhibitors . Among tansition . The pho S phase . Owing t S phase ,6.CCND2, located at chromosome 12p13, is a member of the D-type cyclin family and mainly mediates the extracellular signaling environment with cell cycle progression [CCND2 was generally considered as a protooncogene in various tumors, overexpression of CCND2 has been reported in testicular germ cell tumor cell lines [CCND2 expression was observed in breast [CCND2 has also been reported to be the only one of D-type cyclins, being up-regulated in the conditions of growth arrest, ectopic expression of CCND2 blocked the progression of cell cycle [CCND2 might function as a tumor suppressor gene in a cancer-type dependent manner.Cyclin D2/gression . CCND2 wll lines , colon cll lines  and gastll lines ,10. Althll lines  and inhin breast ,13–15, ln breast , pancrean breast  and gastn breast . CCND2 hCCND2 has been reported in various cancers and the mechanism underlying CCND2 silencing in these mentioned cases is the aberrant promoter methylation [CCND2 promoter methylation was more frequently observed in high Gleason score tumors [CCND2 and the regulation mechanism underlying renal cell cancer has not been reported before.Aberrant promoter methylation of tumor suppressor gene is a common feature of renal cell cancer –21 and ahylation ,14–18. Ae tumors  and was e tumors .However,CCND2 in different type of tumors, we aimed to assess the expression of CCND2 and the status of promoter methylation in RCC cell lines, tumors and adjacent non-malignant tissues. Our results showed that CCND2 was down-regulated in RCC cell lines and primary RCC tissues. Moreover, the methylation status of CCND2 was more frequently observed in RCC tissues than adjacent non-malignant tissues. Demethylation treatment of RCC cell lines restored CCND2 expression, which suggested that epigenetic alteration might be the mainly regulated manner of CCND2 expression.Owing to the controversial role of The experimental methods and usage of clinical samples were approved by the Ethics Committee of the Peking University First Hospital. All these specimens were diagnosed by two urological pathological pathology physicians with patients’ written consent.2 (5%) incubator.The RCC cell lines 786-O, A498, CAKI-1, CAKI-2, OSRC, 769P, KOTO3 and HK-2  were originally obtained . These cell lines were routinely maintained in RPMI1640 or DMEM medium with 10% fetal bovine serum (FBS) , 1% penicillin G, and 1% streptomycin at 37°C in humidified COAll the RCC samples (fresh tissues and paraffine section tissues) were obtained from the Urology Department, Peking University First Hospital, Beijing, People’s Republic of China. All the RCC tissues and corresponding non-malignant tissues were collected from radical surgical resection without adjuvant therapy. All these specimens were diagnosed by two urological pathology physicians with patients’ written consent. A 2002 AJCC TNM stage and a Fuhrman nuclear grade were used for the classification of the tumor histopathology.For RNA extraction, fresh frozen tissues and cell lines were homogenized in TRI Reagent  and isolated as previously described . Total gCCND2 in RCC cell lines, reverse transcription PCR (RT-PCR) with GoTaq® Green Master Mix  and Real-time PCR with  were used according to the manufacturer’s protocol. Then we used Real-time PCR to examine CCND2 mRNA status in 23 paired RCC tumors and adjacent non-malignant tissues. The primers were: CCND2-F: CATGGAGCTGCTGTGCCACG; CCND2-R: CCGACCTACCTCCAGCATCC. The RT-PCR reaction condition was 35 cycles . Real-time PCR was done for 45 cycles . GAPDH primers were: GAPDH-F: TCCTGTGGCATCCACGAAACT; GAPDH-R: GAAGCATTTGCGGTGGACGAT, which was used as an internal control.To evaluate the mRNA expression of 6 cells/ml in six-well plate, after overnight culture, cells were treated with 10μM demethylation agent 5-Aza (5-aza-2’-deoxycytidine) for 96 hours, some RCC cell lines were further treated with 100 nmol/L histone deacetylase inhibitor TSA (trichostatin A) for additional 24 hours. After the treatment, the cells were collected for DNA and RNA extractions.Six RCC cells were primarily seeded at a density of 1x10CCND2 promoter to indentify the CCND2 promoter methylation status. The methylated and unmethylated primers of CCND2 were CCND2-m1: TACGTGTTAGGGTCGATCG; CCND2-m2: CGAAATATCTACGCTAAA-CG (276-bp product); CCND2-u1: GTTATGTTATGTTTGTTGTATG; CCND2-u2: TAAAATCCACCAACACAATCA (223-bp-product). The MSP was conducted in a 12.5μl reaction solution with GoTaq® Green Master Mix  for 35 cycles . PCR products were analysed in 2% agarose gels. To further confirm our MSP results, BGS was used to analyze the detailed methylation status. The BGS primers were CCND2-BGS1: GGAGGAAGGAGGTGAAGAA; CCND2-BGS2: CCCCTACATCTACTAACAAAC. 40 cycles/58°C annealing temperature of PCR were performed using GoTaq® Green Master Mix. The PCR products were connected into the pEASY-T5 zero vectors , then 5–9 colonies were randomly selected and sequenced.MSP and BGS were performed on the bisulfite-modified DNA samples using primer sets targeting the CpG-rich region in CCND2  in 1:250 dilution. All the photographs were taken randomly and measured using Image Pro Plus .Immunohistochemistry was carried out on forty-three paraffin-embedded RCC tissues and paired adjacent non-malignant tissues microarray with the primary antibody CCND2 vectors were bought from company . Then 786-O and OSRC cells were transfected with pLVX-IRES-ZsGreen1 and pLVX-IRES-ZsGreen1-CCND2 using Lip 3000 kit (Invitrogen) according to the manufacturer’s instruction.pLVX-IRES-ZsGreen1 and pLVX-IRES-ZsGreen1-CCND2 and vector were harvested and then plated in 96-well plate at a density of 2000 per well and incubated overnight at 37°C. The Cell Counting Kit-8  was used to analyze the cell proliferation. 10μL CCK-8 solution was added into each well with 100μL serum-free optional medium and incubated for 40 minutes. The absorbance was measured at 450nm. All the results were obtained from three independent experiments.Cells transfected with t test, Fisher’s exact test and Chi-square test were used. Statistical analyzed using the SAS version 9.0 software. A p-value was considered significant when less than 0.05.Data were presented as mean ± standard deviation (SD). Student’s http://www.proteinatlas.org/) had previously revealed that, CCND2 expression level was significantly lower in RCC tissues. To check the validity of these findings, we performed Real-time PCR to evaluate the mRNA status of CCND2 in 23 paired RCC tumors and adjacent non-malignant tissues. The expression of CCND2 was noted in 22/23 adjacent non-malignant tissues. In contrast, only 1/23 adjacent non-malignant tissue showed slightly decreased expression of CCND2 compared with RCC tumor tissue (p<0.05). Moreover, we used immunohistochemical staining to examine the CCND2 protein expression in 43 RCC tumors paired with adjacent non-malignnat tissues. We found that CCND2 was downregulated in RCC tissues inordinately. Interestingly, CCND2 protein expression was decreased in 43/43 RCC tumors compared with the corresponding adjacent non-malignant tissues . Thus, in both mRNA and protein status, specific loss of CCND2 was observed.Serial analysis of gene expression  cell line, RT-PCR was used with GAPDH as an internal control. As is shown in CCND2 was significantly down-regulated in 6/7 RCC cell lines and weakly decreased in CAKI-2 cell line comparing with HK-2 cell line. This is accordance with the results of RCC clinical samples. As is known to all, both genetic and epigenetic aberrant alteration influence the expression of genes. By analyzing the promoter region, we found two typical CpG islands in CCND2 promoter region (http://cpgislands.usc.edu/). To further assess the relationship between epigenetic regulation and CCND2 expression, methylation specific PCR (MSP) was performed to evaluate the methylation of CCND2 promoter. Hypermethylation at CpG-rich region with no mRNA expression of CCND2 was detected in 5/6 RCC cell lines , but was not detected in CAKI-2 and HK-2 with CCND2 mRNA expression  or treatment with histone deacetylase inhibitor trichostatin A (TSA) should result in the up-regulation of CCND2. Indeed, when six RCC cell lines were treated with 5-Aza with or without TSA, five out of six cell lines showed a differently increased expression of CCND2 , two with low CCND2 expression . 769P and 786-O showed higher methylation status than HK-2 cell line, which is consistent with the previously results of MSP. From this part we concluded that hypermethylation may lead to the CCND2 silencing in RCC cell lines. Meanwhile, BGS results were consistant with the MSP result before or after pharmacological demethylation treatment  was performed. The CpG-rich region of reatment . These rCCND2 promoter, MSP was used to examine the methylation status in 102 RCC tumors and 23 adjacent non-malignant tissues. As is shown in CCND2 was observed in 29/102 (28%) of RCC tumors, but only 2/23 (8.7%) in adjacent non-malignant tissues . CCND2 mRNA was also decreased in 6/7 RCC cell lines as the RT-PCR results showed. Furthermore, lack of protein expression was also observed in 43 paired RCC samples (p<0.001). After ectopic expression of CCND2, we found the ability of tumor growth was inhibited. These findings may indicate a tumor suppressive role of CCND2 in RCC, and its down-regulation may be related to tumorigenesis.As previously reported, overexpression of c factor . It was f tumors ,9. In rest, lung ,13–15 anst, lung . The differation , but it G1 phase . Thus, wCCND2 by aberrant promoter methylation has been reported in many kinds of tumors. In prostate cancer, the frequency of CCND2 methylation status was much higher in prostate cancer samples than in non-malignant prostate tissues (p<0.005). By analyzing the clinicopathological correlations, greater CCND2 methylation frequency was found to occur in high Gleason score group and in patients with higher mean PSA value. In addition, methylation of CCND2 correlates with prostate poor prognosis [CCND2 mRNA (18 of 24) and protein (10 of 13). In contrast, CCND2 was expressed in normal luminal and myoepithelial breast tissues. The silencing of CCND2 expression was associated with its promoter aberrant methylation by MSP. The methylation of CCND2 promoter was also detected in ductal carcinoma in situ, which suggested that loss of CCND2 is an early event in tumorigenesis and may associated with the evolution of breast cancer [CCND2 expression by promoter methylation is also observed in gastric cancer [CCND2 in renal cell cancer, we then test the methylation of CCND2 promoter as a possible cause that lead to the silence of this gene.Multiple mechanisms underlying inactivation of genes have been reported in various types of cancers, such as loss of heterozygosity, point mutations, homozygous deletions, and aberrant promoter methylation . Aberranrognosis . Likewist cancer . The absND2 mRNA  of 24 anCCND2 was significantly higher in RCC tissues than in adjacent non-malignant samples  of RCC patients. Many genes are known to be aberrantly methylated in RCC [CCND2 may be an useful part of the panel of markers that could be used for clinical diagnosis. Further exploration is needed to verify our previous results.As the results showed, the methylation level of  samples . Moreoved in RCC ,21,35,36CCND2 is down-regulated in renal cell cancer strongly suggests that the function of CCND2 is not only limited to its role in cell cycle transition from G1 to S. The cancer-specific loss of CCND2 in renal carcinoma and suppression of RCC cell growth provide clues for investigating a possible role of CCND2 in carcinogenesis in kidney and the methylation of its promoter may function as an optional biomarker for clinical application.In conclusion, the result that


Cellular responses to proton beam irradiation are not yet clearly understood, especially differences in the relative biological effectiveness (RBE) of high-energy proton beams depending on the position on the Spread-Out Bragg Peak (SOBP). Towards this end, we investigated the differences in the biological effect of a high-energy proton beam on the target cells placed at different positions on the SOBP, using two human esophageal cancer cell lines with differing radiosensitivities.10 for each position of the target cell lines on the SOBP was determined based on the results of the cell survival assay conducted after photon beam irradiation. In addition, the number of DNA double-strand breaks was estimated by quantitating the number of phospho-histone H2AX (γH2AX) foci formed in the nuclei by immunofluorescence analysis.Two human esophageal cancer cell lines  with different radiosensitivities were irradiated with a 235-MeV proton beam at 4 different positions on the SOBP , and the cell survivals were assessed by the clonogenic assay. The RBEIn regard to differences in the RBE of a proton beam according to the position on the SOBP, the RBE value tended to increase as the position on the SOBP moved distally. Comparison of the residual number of γH2AX foci at the end 24 h after the irradiation revealed, for both cell lines, a higher number of foci in the cells irradiated at the distal end of the SOPB than in those irradiated at the proximal end or center of the SOBP.The results of this study demonstrate that the RBE of a high-energy proton beam and the cellular responses, including the DNA damage repair processes, to high-energy proton beam irradiation, differ according to the position on the SOBP, irrespective of the radiosensitivity levels of the cell lines.The online version of this article (doi:10.1186/s13014-017-0849-1) contains supplementary material, which is available to authorized users. Proton Beam Therapy (PBT) has been used clinically, with or without concurrent chemotherapy, for several cancers, including locally advanced non-small cell lung cancer or esophageal squamous cell carcinoma (ESCC) –5. PBT iIn the application of PBT to clinical cancer treatment, we routinely adopt a Relative Biological Effectiveness (RBE) of 1.1. The RBE is approximated based on reported results from in vivo and in vitro experiments using a hamster non-tumor cell line and rodent cancer cell lines –9. EvaluWhile the RBE has been regarded as being constant throughout the range of the SOBP, recent studies have suggested that the RBE of a 62-MeV proton beam increased as the position on the SOBP became more distal, along with increase of the linear energy transfer (LET) , 11. HowThe number of DNA double-strand breaks (DSBs), which are well-known to play a major role in cell killing, after proton beam irradiation, has been shown as a useful predictor of the tumor radiosensitivity , 19. HowTherefore, we investigated the differences in the RBE and the cellular responses, especially focusing on DNA-DSB repair processes, depending on the position of the target cells on the SOBP, in response to high-energy proton beam irradiation of the target cells using 2 ESCC cell lines with differing radiosensitivity levels.2 at 37 °C.The human esophageal cancer cell lines OE21 and KYSE450 were obtained from the cell banks of Public Health England  and the National Institutes of Biomedical Innovation , respectively, and used within 20 passages for the present experiments. Both the cell lines were authenticated for their identity by Short Tandem Repeat analysis. The cell lines were selected based on the results of preliminary experiments carried out using 6 cell lines that showed different sensitivities to a photon beam, i.e., the OE21 cells were moderately sensitive to a photon beam, while the KYSE450 cells showed a low sensitivity . For the photon irradiation, both cell lines were irradiated with a 6-MV x-ray beam at the dose rate of 6 Gy/min, using Linac . For the proton irradiation, both cell lines were irradiated with a 235-MeV proton beam . Proton beams dispersed by a double-scattering method were shaped down with a brass collimator to irradiate a field size of 20 cm × 20 cm. The depth of irradiation was precisely modulated by placing polyethylene plates of appropriate thickness, considering the water equivalent thickness of 3 mm calculated by the thickness of the flask or dish and medium on the incident side, at a position between the collimator and the samples. The field size was 15 cm × 20 cm and the flask surface dose homogeneity was ≥95%. To evaluate the difference in the cellular responses to the proton beam irradiation according to the position on the SOBP, the cells were irradiated at 4 different positions on the SOBP, which was 8 cm in width (position #1) At entry (49 mm); position # 2) Just proximal to the SOBP (107 mm); position #3) Center of the SOBP (135 mm); position #4) Distal end, at the fall-off, of the SOBP (163 mm), at the dose rate of 6 Gy/min. The dosimetry error in the absolute dose was estimated to be a maximum of 1% at the center of the SOBP. The dose distribution within the irradiation field was also examined and the error range was 1% to 5% at the center of the SOBP.2 flasks  or 35-mm μ-dishes , and placed on polyethylene plates at the time of irradiation of the perpendicular proton or photon beam. All experiments were conducted in triplicate.The cells were seeded onto 25-cm2 tissue culture flasks containing 5 ml of the culture medium at 400 to 1600 cells per flask, depending on the irradiation dose, and incubated for 24 h prior to the irradiation. The flasks were irradiated with the proton or photon beams and returned to the CO2 incubator at 37 °C. After 8 or 12 days, the colonies were fixed with 4% formalin solution and stained with 1% crystal violet. Colonies that contained more than 50 cells were counted, and the surviving fractions were calculated as the ratio of the plating efficiencies of the irradiated to unirradiated cells. Cell survival curves were fitted to a linear-quadratic model:The OE21 and KYSE450 cells were seeded in triplicate onto 25-cmhttps://root.cern.ch/). The RBE10 and RBE37 (doses required to obtain a reduction in the fraction of the surviving cells to 10% (D10) and 37% (D37), respectively), relative to that of a 6-MV photon beam, were calculated for each position on the SOBP [where S represents the surviving fraction, and D represents the dose of radiation, α and βare adjustable parameters. Non-linear regression analysis was carried out using the ROOT software  and fixing with 4% formaldehyde for 15 min at each time-point. They were then washed again with PBS three times for 5 min each and blocked with blocking buffer containing 1% filtered bovine serum albumin  and 1% TritonX-100  in PBS, followed by incubation for 1 h at room temperature. Thereafter, the cells were incubated with anti-rabbit antibody directed against phospho-histone H2A.X Serine139  overnight at 4 °C. After incubation with the primary antibody, the cells were washed again three times with PBS, followed by the addition of blocking buffer containing goat anti-rabbit Alexa Fluor 488 IgG secondary antibody  was added; the cell suspensions were then left to stand for 2 h at room temperature. Thereafter, the cells were washed again with PBS 3 times before the addition of mounting medium containing DAPI . The experiments were performed in triplicate. Images were obtained under the Carl-Zeiss LSM710 confocal fluorescence microscope. We randomly examined six to nine microscopic fields for γH2AX (green) foci and nuclei stained with DAPI (blue).Cells were seeded onto 35-mm μ-dishes at the density of 1.0 × 10https://imagej.nih.gov/ij/) and the mean number of foci per nucleus was calculated. More than 100–200 cells were evaluated after the irradiation.The γH2AX foci in each cell were counted using the National Institutes of Health Image J software , and also between position #2 and position #4 (p = 0.012). The surviving fraction of the KYSE450 cells following irradiation at the dose of 6 Gy was significantly between position #1 and position #3 or position #4 (p = 0.002), and between position #2 and position #3 or position #4 (p = 0.031); furthermore, the surviving fraction of the cells following irradiation at 8 Gy was also significantly different between position #1 and position #3 or position #4 (p = 0.003), and between position #2 and position #3 or position #4 (p = 0.007) , and a trend towards a higher RBE than the routinely used fixed RBE value of 1.1 at the distal end of the SOBP. The differences in the RBE10 and RBE37 in the OE21 cells between position #2 and position #4 were 6.0% and 5.4%, respectively. The differences in the RBE10 among the positions on the SOBP were also significant  in the KYSE450 cells. Furthermore, the differences in the RBE10 and RBE37 in the KYSE450 cells between position #2 and position #4 were 24% and 17%, respectively. Consistent with these findings, the RBE10 and RBE37 of both cell lines were significantly different between beam entry and positions on the SOBP, and the differences among positions within the SOBP were also over 5%.The survival curve after photon irradiation showed that the shoulder of the survival curves was larger for the OE21 cells  than for the KYSE450 cells  , while the correlation between the RBE37 and LET in the KYSE450 cells (p = 0.04) was statistically significant.Figure Additional file p = 0.000, p = 0.002, and p = 0.007, respectively). A similar trend was noted in the KYSE450 cells. There were significant differences in the number of γH2AX foci in the cells at 24 h after irradiation between position #1 and position #4 and between position #2 and position #4 .Figure 2 = 0.76 and R2 = 0.99, respectively). Additional file The correlation between the surviving fraction after irradiation at 8 Gy (SF8) and the residual number of γH2AX foci/cell at 24 h after irradiation is shown in Fig. The RBE tended to be higher at the distal end of the SOBP than that at the proximal portion of the SOBP, irrespective of the radiosensitivity of the cell lines used. In addition, the amount of unrepaired double-stranded DNA breaks, as assessed by the number of γH2AX foci formed in the cells, at 24 h after irradiation was higher for irradiation at the distal end of the SOBP. Our findings indicate that the RBE as well as the cellular responses, including DNA damage repair processes, in response to proton beam irradiation differed according to the position on the SOBP.The RBE of proton beam irradiation against two ESCC cell lines of differing radiosensitivities in this study differed according to the position on the SOBP, and varied in the range of 1.03 to 1.40. Previous reports have shown differences in the RBE, ranging from 1.3 to 2.8, according to the depth, namely, position on the SOBP, for lower-energy proton beams (62–87-MeV) , 12, 13.Evaluation of the differences in the RBE depending on the position along the SOBP in previously reported studies has mainly been conducted using rodent cells and human malignant tumor cells  cells, human cervical carcinoma (HeLa) cells, head and neck squamous carcinoma (SQ20B) cells, and human melanoma HTB140) cells [0 cells , 23. HowDifferences in the RBE for irradiation targets in different positions along the SOBP would also be expected to influence the cellular responses to the proton beam. In explaining the mechanism underlying the correlation between the RBE and the cellular responses, LET has an important role. LET has been demonstrated to increase steeply at the distal end of the SOBP , 20, 24.When DSBs occur in cells exposed to photon- or proton-beam irradiation, formation of γH2AX foci represents one of the earliest events of the DNA damage repair process; these foci appear within minutes and reach their peak number at 0.5 h . In the In contrast, the residual number of γH2AX foci at 24 h after the irradiation was significantly higher for position #4  of the SOBP in both cell lines.The residual number of γH2AX foci has been interpreted as being reflective of persistent unrepaired DNA damage and as a predictor of the tumor radiosensitivity , 19, 29.The residual number of γH2AX foci is usually increased by high-LET irradiation. Bracalente et al. showed that the residual number of γH2AX foci at 6 h after high-LET irradiation was higher than that after γ-ray irradiation in a Chinese hamster ovary cell line . AntonelIn the clinical setting, we often select the physical proton dose based on the RBE of 1.1, assuming homogeneity along all positions of the SOBP. However, our current study demonstrated that the RBE differed according to the position on the SOBP. Moreover, the differences in the RBE among the positions on the SOBP in both cell lines were 5% or more . Thus, it may be necessary to take into consideration an inhomogeneous distribution of the RBE in the range of the SOBP for treatment planning in patients scheduled to undergo PBT. Further clinical studies are needed to clarify how the inhomogeneity of the RBE within the range of the SOBP would affect the clinical outcomes.Our study had the following limitations. First, we evaluated only 2 cancer cell lines. The RBE and cellular responses to proton beam irradiation could differ depending on the cell line used. Therefore, caution should be exercised in extrapolating the results of this study to other type of tumors or normal cells. Second, it seemed that the number of γH2AX foci at 0.5 h after irradiation of 8Gy using the National Institutes of Health Image J software was low. Thus, further analysis using another technique, such as flow cytometry, would be needed. Third, the current study was performed in vitro. In order to apply the results to clinical treatment, investigations in vivo would be needed, because the microenvironments of tumors and/or normal tissues could be expected to affect the RBE and cellular responses to proton beam irradiation. Thus, further investigations are warranted to confirm the validity of the results of this study. In addition, while PBT has been used with concurrent chemotherapy for locally advanced cancers, such as locally advanced non-small cell lung cancer, in clinical practice, there are few radiobiological reports regarding the effect of PBT used in combination with chemotherapy. Therefore, we should clarify the influence of differences in the radiosensitizing effects of the chemotherapeutic agents used on the differences in the effects of proton beam irradiation depending on the position on the SOBP.In this study, we demonstrated that the RBE of a high-energy proton beam and the cellular responses, including the DNA damage repair processes, to irradiation with a high-energy proton beam, differed according to the position on the SOBP, regardless of the radiosensitivity levels of the cells, in two human cancer cell lines.Additional file 1: Figure S1.Survival curves of 6 different esophageal squamous cell carcinoma cell lines irradiated with a 150-kV photon beam in preliminary experiments. Each experiment was conducted in triplicate. Error bars indicate the standard error of the mean. (TIFF 343 kb)Additional file 2: Figure S2.p < 0.05, **p < 0.01, ***p < 0.001) (TIFF 337 kb)Surviving fraction following irradiation at 6 Gy and 8 Gy in the OE21 and KYSE450 cells. Error bars indicate the standard error of the mean.  antibody and DAPI (blue). (TIFF 2421 kb)Additional file 4: Figure S4.2 = 0.81 and R2 = 0.79, respectively). (TIFF 225 kb)Correlation with the mean number of foci per cell at 24 h after the irradiation and the linear energy transfer (LET). The clear and filled circles show the results for position #1 and position #2, respectively. The clear and filled squares show the results for position #3 and position #4, respectively. Error bars indicate the standard error of the mean. A strong positive correlation between the mean number of foci formed per cell and the LET was observed in both the OE21 and KYSE450 ells (R


During the course of this study, we developed a novel methodology of loading a single site with multiple payloads using an in situ generated multi-drug carrying peptidic linker that allowed us to rapidly screen for optimal conjugation sites. Using this methodology, we were able to identify a double-cysteine mutant ADC delivering four-loaded thailanstatin that was very efficacious in a gastric cancer xenograft model at 3mg/kg and was also shown to be efficacious against T-DM1 resistant and MDR1 overexpressing tumor cell lines.Antibody drug conjugates (ADCs) are no longer an unknown entity in the field of cancer therapy with the success of marketed ADCs like ADCETRIS and KADCYLA and numerous others advancing through clinical trials. The pursuit of novel cytotoxic payloads beyond the mictotubule inhibitors and DNA damaging agents has led us to the recent discovery of an mRNA splicing inhibitor, thailanstatin, as a potent ADC payload. In our previous work, we observed that the potency of this payload was uniquely tied to the method of conjugation, with lysine conjugates showing much superior potency as compared to cysteine conjugates. However, the ADC field is rapidly shifting towards site-specific ADCs due to their advantages in manufacturability, characterization and safety. In this work we report the identification of a highly efficacious site-specific thailanstatin ADC. The site of conjugation played a critical role on both the  Despite the enthusiasm generated by these drugs, there is still much to be improved regarding their homogeneity, efficacy and safety  wer wer20] wpression . Similarnjugates , only a 2 to a variety of antibodies that incorporated engineered cysteine residues  were evaluated (ADC4-11) were uncapped by first reducing the engineered cysteines and the interchain disulfides using excess TCEP followed by the re-oxidation of the hinge cysteines using dehydroascorbic acid (DHA) and treatment with excess linker-payload 2. After workup and purification, the DAR of the resulting site-specific ADCs ranged from 1.7–2.0. Similar to the hinge cysteine conjugates, the site-specific single cysteine based ADCs showed excellent potency against high Her2 expressing N87 cell lines . The relative exposure of the conjugated payload to bulk solvent was assessed by hydrophobic interaction chromatography, as previously described [The cytotoxicity of ADCs that were generated by site-specific conjugation of the thialanstatin LP valuated . Auristavaluated , ADC4-11in situ and subsequently conjugated to a model antibody (4) Concurrently, we generated a two-payload carrying azido peptide by conjugating the lysines of the N-terminal azidoacetyl substituted peptide (SKGSK) with an N-hydroxysuccinimide (NHS) ester of PEG5-MMAD (5). A small, fairly neutral 5-mer peptide with two lysines separated by glycine-serine was chosen to reduce any potential instability. The excess NHS ester was quenched with ethanolamine and the resulting double-payload carrying peptide linker (7) was then conjugated to the DBCO-preprogrammed antibody (6) via an in situ copper free click reaction thus yielding a site-specific ADC with a DAR of 3.8 (ADC11). This ADC was purified using size-exclusion chromatography (SEC) and characterized by LC-MS and analytical SEC. The cytotoxicity of ADC11 was measured against cancer cell lines with various levels of Her2 expression and the ADC was found to be extremely potent against Her2 expressing N87 (IC50 = 0.49 nM) and 361 (IC50 = 0.39 nM) cell lines and exhibited approximately 1000 fold selectivity against the non-Her2 expressing 468 cell line. By comparison, a DAR4 lysine conjugate of 5 (not shown) exhibited an IC50 of 0.95 nM against N87 cells and 0.16 nM against 361 cells.As we have previously shown that the potency of lysine thailanstain ADCs  are highantibody  by clickantibody , 4 ConcuEG5-MMAD , 5. A smR of 3.8 , ADC11. 8) to yield a double thailanstatin conjugated azidopeptide. This dual-loaded peptide was then conjugated to four different DBCO preprogrammed single cysteine mutant trastuzumab antibodies using copper free click conjugation  exhibited low nM activity against the 361 cell line followed by ADC13 (392C) > ADC12 (114C) > ADC15 (k183C).Having demonstrated the ability to load an auristatin payload using the MPP chemistry, the N-terminal azidoacetyl SKGSK peptide was conjugated to the NHS ester of thailanstatin A , 8 to yijugation . This mejugation  one highell line . SurprisADC14 and ADC13, respectively) in the nude mouse N87 xenograft tumor model. The mice were injected with ADCs intravenously at two different doses of 1.5 mg/kg and 3 mg/kg as described previously. While at the 1.5 mg/kg dose the ADCs were only marginally efficacious . Gratifyingly, this double mutant showed much improved activity against moderate Her2 expressing 361 cell lines and maintained potent cytotoxicity towards the N87 cell lines in the in vitro cytotoxicity assay. To assess if the activity against the moderate antigen expressing cell lines is not just a characteristic of higher loaded site-specific ADC, we evaluated the cytotoxicity of four more ADCs (ADC17-20) generated by other combinations of engineered cysteine sites, 347+k183, 388+421, 347+392 and 443+k183. Two of the ADCs that were generated on antibodies where at least one site of conjugation was either 443 or 392 (ADC19 and ADC20) exhibited improved cytotoxicity against the 361 cell lines, as compared to the other two ADCs that were not conjugated at these preferred sites (ADC17 and ADC18)  .ADC16) in an N87 tumor xenograft bearing nude mouse study as described above. Three doses  were administered (IV) and a dose dependent tumor regression by this site-specific ADC was observed  ADCs which continue to suffer from poor therapeutic efficacy in the clinic [Thailandensis burkholderia MSMB43 that exerts its activity by binding to the SF3b subunit of the U2 snRNA subcomplex of the spliceosome [T. burkholderia that allows for gram-scale production of thailanstatin A [50 values against multiple cancer cell lines. Overexpression of MYC, an aggressive oncogene, is one of the most common drivers of human cancer and MYC dependent cell lines have remained resistant to therapeutics. Recently, Westbrook et al. reported that in vivo inhibition of the spliceosome impairs tumorigencity of MYC-dependent breast cancers and their metastatic potential [Despite the success of ADCs like ADCETRISe clinic . One appe clinic , 27. In e clinic , 18. We iceosome , 28, 29.statin A . The mecotential . Thus, ootential , 32 due 50 values of the resulting hinge-cysteine ADCs were very high against the 361 cell lines in spite of their high DARs (6.3 to 7.0). Despite lower potency against the moderate Her2 expressing 361 cell lines, we wanted to evaluate these ADCs in vivo in an N87 gastric cancer xenograft model due to their potent in vitro activity against the N87 cell line. Therefore, one of the thailanstatin ADCs (ADC1) which displayed excellent in vitro potency against a high Her2 expressing N87 cell line was selected for in vivo evaluation. Dosed at 3 mg/kg (qdx4), this ADC exhibited only marginal activity in an N87 gastric cancer xenograft model compared to the vehicle control  and were selective against the non-antigen expressing cell lines (IC50’s of >1000 nM). However, none of the ADCs were very potent against the moderate Her2 expressing 361 cell line, exhibiting IC50’s of > 1000 nM , was conjugated to the two lysines of a peptide (SKGSK) derivatized with an azidoacetyl group at the N-terminus. The resulting double-MMAD loaded azido-peptide (7) was conjugated in situ to trastuzumab A114C that had been pre-loaded with a maleimide DBCO (6). This four loaded site-specific MPP ADC (ADC11) showed potent cytotoxicity against the antigen expressing cell lines and was selective against non-antigen expressing cell lines . In vitro cytotoxicity against the moderate antigen expressing 361 cell line indeed displayed excellent potency with much improved IC50 values while maintaining potency against the N87 cell line and selectivity against the non-expressing 468 cell lines (ADC1). This data clearly suggests that site of conjugation can play a critical role in the enhancement of thailanstatin ADC cytotoxicity.Based on the improved potency and efficacy of the 443 and 392 MPP ADCs, we hypothesized that a double-cysteine ADC generated by conjugating thailanstatin iodoacetamide payload directly to the 443 and 392 sites might show a similar level of improvement in efficacy. Therefore, a double cysteine mutant of trastuzmab 443 + 392 was generated and linker-payload ll lines . This isll lines , ADC1. TADC19 and ADC20, ADC16), a loading of four linker-payloads was obtained for these double-cysteine mutants. The conjugates derived from both trastuzumab (T)-347C+k183C (ADC17) and T- 388C+421C (ADC18) were not very potent against the 361 cell lines, whereas T-347C+392C (ADC19) and T-443C+k183C (ADC20), both of which carry one of the preferred sites, exhibited slightly improved potency against the 361 cell line . This ADC is also cytotoxic against cell lines that are resistant to the clinically approved ADC, T-DM1 [ADC16 was over 100 times more potent than T-DM1  linker ADC allowed us to screen for these preferred conjugation sites by increasing the DAR on a single site of attachment. MPP ADCs and the double-cysteine mutant ADC generated on these sites showed substantially improved tumor regression in comparison to the approved drug T-DM1  was dialyzed into Dulbecco’s Phosphate Buffered Saline . The dialyzed antibody is reduced with addition 5 equiv of tris(2-carboxyethyl)phosphine hydrochloride  and diluted to 15 mg/mL final antibody concentration using DPBS, 5 mM 2, 2', 2", 2‴-tetraacetic acid (EDTA), pH 7. 0. The reaction is incubated at 37°C for 1.5 h and then cooled to room temperature. Conjugation was performed in 50 mM borate buffer, pH 8.5 by addition of 11 equiv of iodoacetamide thailanstatin payload (1–3)  that was2 that was dissolved as a 10 mM solution in DMA. The conjugation was performed at 10 mg/mL for 16 h at room temperature. The ADC was purified and characterized as described earlier [Site-directed mutagenesis, antibody expression, and purification were performed as previously described . The ant earlier . Briefly50 values were calculated using a four-parameter logistic model with XLfit  and are the arithmetic mean of multiple determinations.Cell lines and Cytotoxicity Assay: N87 (gastric cancer) and MDA-MB-468 (breast cancer) cell lines were obtained from ATCC ; MDA-MB-361-DYT2 (breast cancer) cells were generously provided by Dr. Dajun Yang at Georgetown University. TDM1-resistant MDA-MB-361-DYT1-TM and N87-TM cells were generated as described previously , 24. N876 of N87 cells respectively in 50% Matrigel . Mice were randomized into study groups when tumors reached approximately 150 mm3 to 300 mm3. Either phosphate buffered saline , trastuzumab-thailanstatin ADCs with different DAR, or PT-DM1 at different doses were administered intravenously starting on day 0 for a total of four doses, 4 days apart (Q4d x4). Tumors were measured at least weekly with a calibrator  and the tumor mass was calculated as volume = (width X width X length)/2.All animal studies were approved by the Pfizer Institutional Animal Care and Use Committee according to established guidelines. Female athymic nu/nu  were injected subcutaneously in the flank with suspensions of 1 X 104; Sigma-Aldrich, catalog no. 760676) was performed as described earlier.[7) was prepared by reacting 2mM aizoacetyl-Ser-Lys-Gly-Ser-Lys  with 8 mM NHS-ester payload [7 was reacted with 5–10 mg/mL of 6 in DPBS for 3h at 37°C. The resulting MPP ADC was then purified and characterized as described above.Conjugation of cysteine-mutant antibody with Malemide-PEG4-DBCO Click here for additional data file.S1 FigADC14 in N87 gastric cancer xenograft model dosed at 3 mg/kg (q4d x 4) showing three complete regression.(A) In vivo efficacy of MPP ADC 13 and MPP ADC14 in N87 gastric cancer xenograft model dosed at 1.56 mg/kg (q4d x 4). (B) Individual mouse in vivo efficacy of MPP ADC13 in N87 gastric cancer xenograft model dosed at 3 mg/kg (q4d x 4) showing two complete regression. (C) Individual mouse in vivo efficacy of MPP (PDF)Click here for additional data file.S2 FigADC16 in N87 efficacy model.(A) Individual mouse in vivo efficacy of MPP-ADC 16 in N87 gastric cancer xenograft model dosed at 3 mg/kg (q4d x 4) showing three complete regression. (B) Body weight data in grams for mice treated with 3 mg/kg (q4d x 4) of (PDF)Click here for additional data file.S3 Fig(PDF)Click here for additional data file.