P = .003 and 18% vs. 7%, P = .02, respectively). There was no association between cellular composition of grafts and transplant-related mortality, AML relapse, incidence of chronic GVHD and survival. Neither engraftment itself nor the kinetics of engraftment were affected by the cell dose. In multivariate analysis, CD3+ and CD34+ doses were the only adverse predicting factors for grade III-IV aGVHD , P = .04, respectively). These results suggest that careful assessing the CD3+ and CD34+ graft content and tailoring the cell dose infused may help in reducing severe acute GVHD risk without negative impact on the other transplantation outcomes.Inconsistent results have been reported regarding the influence of graft composition on the incidence of graft versus host disease (GVHD), disease control and survival after reduced-intensity conditioning (RIC) allogeneic peripheral blood stem cell transplantation . These discrepancies may be at least in part explained by the differences in disease categories, disease status at transplant, donor type and conditioning. The current retrospective EBMT registry study aimed to analyze the impact of CD3+ and CD34+ cells dose on the outcome of RIC allo-PBSCT in patients with acute myelogenous leukemia (AML) in first complete remission, allografted from HLA-matched unrelated donors (10 of 10 match). We included 203 adults. In univariate analysis, patients transplanted with the highest CD3+ and CD34+ doses  had an increased incidence of grade III-IV acute (a) GVHD (20% vs. 6%,  Accordid so far –13. ThesTwo hundred and three patients were enrolled. Their median age was 58 range, 21-73). Detailed patient and transplant characteristics are summarized in (Table -73. DetaThe probabilities of OS and LFS at 2 years from transplantation for the whole study group were 64% (95% CI : 56-71) and 60% (53-68), respectively. The relapse rate was 24% (18-30), whereas NRM 16% (11-22). The incidence of grade II-IV acute GVHD was 31% (25-38), whereas severe grade III-IV was 10% (6-14). Chronic GVHD rate was estimated at 44% (37-52).vs. 26%, P = .007) and grade III-IV , respectively  was observed  and from females to males . There was no association between cellular composition of grafts and the incidence of chronic GVHD. Use of in-vivo T-cell depletion was a protective factor for the presence of chronic GVHD .In a univariate analysis, patients transplanted with the highest CD3+ doses  had an increased incidence of acute GVHD grade II-IV (45% P = .005) and together with CD34+ dose for acute GVHD grade III-IV . Use of in-vivo T-cell depletion was an independent predictor for lower incidence of chronic GVHD . There was also no significant correlation between the number of CD3+ and CD34+ cells infused (Spearman correlation coefficient: P = .2). However, there was a trend towards more patients transplanted with the highest CD3+ cell numbers (>347 × 10^6/kg) in in the group of patients with CD34+ cell dose higher than 8.25 × 10^6 /kg, P = .08.In a multivariate analysis, CD3+ dose was the only adverse predicting factor for acute GVHD grade II-IV , P = .93) nor in those that were given upper quartile CD34+ cell counts (18 (1-27) vs. 17 (6-28), P = .46). Likewise, the rates of full donor chimerism were not statistically higher in case of infusion of the highest CD3+  nor CD34+  cell doses.The engraftment rate equaled 99% and was not affected by CD3+ nor by the CD34+ counts. Only one patient did not engraft and one patient experienced a late graft failure. Kinetics of engraftment was not faster in patients given upper quartile CD3+ cell counts (17 days (1-18) There was no association between cellular composition of grafts and AML relapse, NRM and survival (both OS and LFS). Factors that independently affected unfavorable outcome were: time from diagnosis to CR1 above median for NRM, time from CR1 to allo-SCT below median and unfavorable karyotype for LFS and OS, and unfavorable karyotype for relapse incidence. Detailed results of univariate and multivariate analyses for significant factors are presented in Tables In the current study we have addressed the issue of the potential impact of PB grafts composition on the outcome of RIC allo-SCT. Although this topic has been already studied, it still raises controversy because of the lack of unequivocal conclusions coming from the studies published so far , 19–21. 6 / kg) of CD34+ cells with higher incidence of acute GVHD grades II-IV [6 CD34+ cells / kg was in turn correlated with less relapses and lower incidence of chronic GHVD [Existing data on the correlation between cell dose and transplantation outcome in the setting of RIC allo-PBSCT from unrelated donors are mainly concentrated on the impact of CD34+ cells on outcome. Our results are in accordance with a single center Swedish study that reported the association between transplantation of high doses  did not yield a difference in post-transplant symptom burden or engraftment time [The potential impact of CD34+ cell dose on GVHD incidence, with similar to our threshold levels, was also demonstrated in the MAC allo-SCT setting from sibling donors. In the study by Przepiorka et al. transplantation of more than 8.2×10^6 CD34+/kg was associated with increased risk of acute GVHD II-IV . Zaucha nic GVHD . The samHD [6/kg . Also UrHD [6/kg . The praHD [6/kg –17. Thisent time .ex vivo T-cell depletion or in vivo T-cell depletion using ATG reduce the incidence of GVHD in a dose dependent way [The role of CD3+ cell counts is even less-well characterized. Baron et al. previously reported that high numbers of infused CD3+, CD4+, CD8+ and CD34+ cells in the setting of non-myeloablative (fludarabine and TBI 2 Gy) allo-SCT were associated with higher levels of day 28 donor T-cell chimerism . In contdent way . We havedent way –23. In-vdent way –26. TypeIn conclusion, our results suggest that the incidence of severe acute GVHD post RIC allo-SCT, still a major cause of morbidity and mortality, is associated with the composition of the PBSC grafts, specifically it positively correlates with higher numbers of infused CD3+ and CD34+ cells. As graft composition can be manipulated, e.g. by cryopreservation of a part of stem cell product, careful assessing the CD3+ and CD34+ graft content and tailoring the cell dose infused may help in reducing the risk of severe acute GVHD risk and improving transplantation outcome. Prospective randomized trials looking at the impact of cell dose on outcomes should be conducted to avoid potential limitations coming from retrospective analyses published so far.Data for this study were provided and approved by the Acute Leukemia Working Party of the EBMT group registry. Audits are routinely performed to determine the accuracy of the data. Since 1990, patients provide informed consent authorizing the use of their personal information for research purposes.de novo AML in CR1, 2) age ≥18 years, 3) allo-SCT performed from matched unrelated donor, 4) mandatory 10 out of 10 loci compatibility for HLA-A, -B, -C, -DRB1, and -DQB1, 5) peripheral blood as a source of stem cells, 6) reduced intensity conditioning regimen defined according to EBMT guidelines  form) and published working definitions  or on total body irradiation (TBI) ≤ 6 Gy) [in vivo antithymocyte globulin (ATG) or Campath was allowed, whereas ex vivo T-cell depletion was an exclusion criterion.Inclusion criteria were as follows: 1) patients with  ≤ 6 Gy) ,28, 7) tvs. lower CD34+  and also CD3+ doses . The median transplanted CD34(+) dose was 6.53 × 10^6 cells per kg . The median CD3(+) dose was 250 × 10^6 cells per kg . The median follow-up was 22 months (3-105). Detailed patient and transplant characteristics are summarized in  and 57% of them were male. One hundred forty two (70%) of the patients had intermediate and 42 (21%) unfavorable AML cytogenetic features, while only four (2%) of them were categorized as having favorable cytogenetics. The karyotype risk category was unknown for 15 (7%) of the patients. Median donor age was 34 (19-61) years. The preparative regimen was based on chemotherapy in 143 (70%) of transplants whereas in 60 (30%) TBI was applied. In-vivo T-cell depletion was used in 166 (82%) of the transplants. Patients received GVHD prophylaxis mostly with cyclosporine and methotrexate  or with cyclosporine and mycophenolate mofetil . The CD34+ and CD3+ cell counts were determined by the cell processing laboratories at participating transplantation centers and reported to the EBMT registry. The transplanted doses were calculated based on actual body weight of the patient. The body mass index (BMI) and Karnofsky performance status did not statistically differ between patients transplanted with the highest -73 and 5in vivo T cell depletion, use of TBI in the conditioning regimen, infused dose of CD3 and CD34 cells. Continuous variables (CD34+ and CD3+ cell counts) were categorised as follows: each variable was first divided into four categories according to the quartiles. If the relative event rates  in two or more adjacent categories (and the mean times-to-event) were not substantially different, these categories were grouped. If a linear trend was observed in the relative event rates, the variable was used as a continuous factor. Otherwise, the median was used as a cut-off point. Cumulative incidence functions (CIF) were used to estimate the probabilities for acute and chronic GVHD, neutrophil recovery, RI and NRM in a competing risks setting, since death and relapse are competing together [Leukemia-free survival (LFS) was defined as survival with no evidence of relapse. Non-relapse mortality (NRM) was defined as probability of death while in CR. Acute and chronic GVHD were assessed and graded according to standard criteria –30. Engrtogether . Probabitogether . Univaritogether –34. All


Because C4 plants are higher yielding than C3 plants, efforts are underway to introduce the C4 pathway into the C3 crop rice. This is an ambitious endeavor; however, the C4 pathway evolved from C3 on multiple independent occasions over the last 30 million years, and steps along the trajectory are evident in extant species. One approach toward engineering C4 rice is to recapitulate this trajectory, one of the first steps of which was a change in leaf anatomy. The transition from C3 to so-called “proto-Kranz” anatomy requires an increase in organelle volume in sheath cells surrounding leaf veins. Here we induced chloroplast and mitochondrial development in rice vascular sheath cells through constitutive expression of maize GOLDEN2-LIKE genes. Increased organelle volume was accompanied by the accumulation of photosynthetic enzymes and by increased intercellular connections. This suite of traits reflects that seen in “proto-Kranz” species, and, as such, a key step toward engineering C4 rice has been achieved.The C •GLK genesOrganelle development in rice vascular sheath cells is induced by maize •Cells with activated organelles form more plasmodesmatal connections than wild-type•GLK-induced anatomy mimics a key step in the evolutionary transition from C3 to C4•The intermediate proto-Kranz leaf anatomy appears to bear no fitness cost in rice GOLDEN2-like genes induces a suite of traits in C3 rice leaves that is reminiscent of proto-Kranz anatomy, an intermediate state in the evolutionary trajectory from C3 to C4. A key step toward engineering C4 rice has thus been achieved.Wang et al. report that constitutive expression of maize  Cell volume was then used to quantify the number of chloroplasts/cell volume.Average of individual chloroplast area and chloroplast numbers in isolated cells were quantified for 15 bundle sheath cells per individual . 15 was ZjPCKpro:ZmG2, ZmPEPCpro:ZmGLK1, ZmUBIpro:ZmG2, and ZmUBIpro:ZmGLK1 lines (ZmUBIpro:ZmG2 and wild-type sections immuno-labeled for RuBisCo and RuBisCo activase (1)Total planar area of photosynthetic tissue (TP) was quantified as:M = % planar Mesophyll, TBS = % planar Bundle Sheath, TMS = % planar Mestome Sheath)2)Total photosynthetic organellar area (PO) in planar cross section (%) was quantified as:3)The % of organelles invested in each cell-type was quantified as:M = (TM/TP) OMPlanar cell area covered by total chloroplasts and mitochondria was quantified using ImageJ, sampling 15 mesophyll, bundle sheath or mestome sheath cells from TEM images of leaf 7 for each of three individuals from K1 lines . Similaractivase . The samactivase   followed by a Games-Howell post hoc test was performed. An ANOVA and a Tukey’s test was used for normally distributed data. Presence or absence of plasmodesmata between bundle sheath-mesophyll and between bundle sheath-mestome sheath cells was recorded as absence = 0, presence = 1. Relative frequency of plasmodesmata was calculated by dividing the number of cells which had plasmodesmatal connections with the adjacent cell with the total number of observed cells for that cell-type. A GLM for binary data was performed where presence and absence of plasmodesmata between cell-types was the dependent variable, line was the fixed factor, and bundle sheath planar chloroplast and mitochondria area per planar cell area were covariates, using line as the main effect and a confidence interval of 95%.Standard errors for heading time, days to harvest and filled seed weight, and ANOVA were calculated using the Statistical Tool for Agricultural Research (STAR) 2.01 software.Experimental Concept and Design, P.W., R.K., S.K., W.P.Q., R.F., T.L.S., and J.A.L.; Generation of Transformation Constructs and Genotypic, qPCR, and Phenotypic Analyses of Kitaake Lines, P.W.; Generation of IR64 Lines and Genotypic and Phenotypic Analyses of IR64 Lines, S.K.; Organelle Counts and TEM Analysis, R.K.; qPCR of IR64 Lines, R.T., C.P.B., and S.K.; DNA Gel Blot Analysis of IR64 Lines, C.P.B.; Data Analysis and Interpretation, P.W., R.K., S.K., A.B., W.P.Q., R.F., T.L.S., and J.A.L.; Initial Manuscript Preparation, P.W., R.K., S.K., T.L.S., and J.A.L. All authors contributed to the final version of the manuscript.


Aberrant hypermethylation of cellular genes is a common phenomenon to inactivate genes and promote tumorigenesis in nasopharyngeal carcinoma (NPC).CLDN11 that was both hypermethylated and downregulated in NPC. Bisulfite sequencing, qRT-PCR, immunohistochemistry staining of the NPC clinical samples and addition of methylation inhibitor, 5’azacytidine, in NPC cells were performed to verify the correlation between DNA hypermethylation and expression of CLDN11. Promoter reporter and EMSA assays were used to dissect the DNA region responsible for transcription activator binding and to confirm whether DNA methylation could affect activator’s binding, respectively. CLDN11 was transiently overexpressed in NPC cells followed by cell proliferation, migration, invasion assays to characterize its biological roles. Co-immunoprecipitation experiments and proteomic approach were carried out to identify novel interacting protein(s) and the binding domain of CLDN11. Anti-tumor activity of the CLDN11 was elucidated by in vitro functional assay.Methyl binding domain (MBD)-ChIP sequencing of NPC cells, microarray data of NPC biopsies and gene ontology analysis were conducted to identify a potential tumor suppressor gene CLDN11, was identified as differentially hypermethylated gene in NPC. High methylation percentage of CLDN11 promoter in paired NPC clinical samples was correlated with low mRNA expression level. Immunohistochemistry staining of NPC paired samples tissue array demonstrated that CLDN11 protein expression was relatively low in NPC tumors. Transcription activator GATA1 bound to CLDN11 promoter region − 62 to − 53 and its DNA binding activity was inhibited by DNA methylation. Re-expression of CLDN11 reduced cell migration and invasion abilities in NPC cells. By co-immunoprecipitation and liquid chromatography-tandem mass spectrometry LC-MS/MS, tubulin alpha-1b (TUBA1B) and beta-3 (TUBB3), were identified as the novel CLDN11-interacting proteins. CLDN11 interacted with these two tubulins through its intracellular loop and C-terminus. Furthermore, these domains were required for CLDN11-mediated cell migration inhibition. Treatment with a tubulin polymerization inhibitor, nocodazole, blocked NPC cell migration.A tight junction gene, CLDN11 is a hypermethylated and downregulated gene in NPC. Through interacting with microtubules TUBA1B and TUBB3, CLDN11 blocks the polymerization of tubulins and cell migration activity. Thus, CLDN11 functions as a potential tumor suppressor gene and silencing of CLDN11 by DNA hypermethylation promotes NPC progression.The online version of this article (10.1186/s13046-018-0754-y) contains supplementary material, which is available to authorized users. Aberrant DNA hypermethylation of tumor suppressor genes is a well-studied epigenetic gene silencing event, which promotes cancer formation and progression –3. Nasopclaudin 11 (CLDN11) in NPC cells. Claudins are a family of genes with 27 members. They are integral membrane proteins containing four transmembrane domains which serve as crucial tight junction components and cell barrier for cells  and transcription start sites (+ 1) are indicated. (PDF 44 kb)Additional file 6:Figure S4. Co-immunoprecipitation of interacting proteins of Flag-tagged CLDN11. (a) Co-immunoprecipitation assays were performed using anti-Flag M2 beads (Sigma) on cell lysates transfected with either vector  or CLDN11-3F (C) expressing plasmid. The immunoprecipitated protein samples were separated in 12% SDS-PAGE. The gel was stained with Coomassie Blue (left panel). (b) For Western blot analysis, the SDS-PAGE was loaded with 1% input lysate, 25% immunoprecipitated lysate, and 1% flow through (FT), and was detected by anti-Flag antibody. (PDF 165 kb)Additional file 7:Table S2. Identified proteins from CLDN11-3flag Co-IP by LC-MS/MS. (PDF 222 kb)Additional file 8:Identified peptide sequence of TUBA1b, TUBB3 and CLDN11-3flag by LC-MS/MS. (XLSX 19 kb)Additional file 9:Figure S5. Tubulin polymerization assays. (a) Tubulin polymerization assays were performed in standard condition (TUB), TUB with purified GST, TUB with purified GST-CLDN11, and TUB with 10 µM nocodazole (tubulin polymerization inhibitor). Tubulin polymerization was monitored using an ELISA reader (340nm) every 30 s for 60 min (upper panel). (b) The rate of tubulin polymerization (?mOD/min) was plotted (lower panel) and the Vmax for each reaction is indicated by an arrow. (c) The purified GST and GST-CLDN11 protein were detected by western blotting using either anti-GST or anti-CLDN11 antibody. (PDF 203 kb)


We synthesized a panel of conformationally constrained peptides with either α-helix or β-hairpin conformations. We tuned the amphiphilicity of these constrained peptides with different distributions of charged or hydrophobic residues and compared their cellular uptake efficiencies in different cell lines. Due to their enhanced stability and cell permeability, cyclic cell-penetrating peptides have been widely used as delivery vectors for transporting cell-impermeable cargos into cells. In this study, we synthesized a panel of conformationally constrained peptides with either α-helix or β-hairpin conformations. We tuned the amphiphilicity of these constrained peptides with different distributions of charged or hydrophobic residues and compared their cellular uptake efficiencies in different cell lines. We found that the amphipathicity of these conformationally constrained peptides correlates well with their cellular uptake efficiency. We proposed that peptides with larger hydrophobic moments (HMs) have stronger binding affinities with the cell membrane which further accelerates the endocytosis process. This finding should provide an approach towards the design of more potent conformationally constrained cell-penetrating peptides for biomedical applications. Herein, we set out to utilize the above two nucleation templates with the same macrolactamization chemistry to access amphipathic cell-penetrating peptides in both α-helix and β-hairpin conformations with different topological distributions of hydrophilic and hydrophobic residues, and study their cellular uptakes in different cell lines. The design of the constrained peptides was based on the different topological distributions of hydrophilic arginine and hydrophobic leucine. Molecular three-dimensional structure projections of the peptides are shown in Linear CPPs are generally unstructured in solution, and thus it remains an open question as to how specific conformations influence the cellular uptake of constrained cell-penetrating peptides. In addition, different conformations in turn lead to entirely different topological distributions of positively charged residues and hydrophobic residues, which we believe should play an important role in interacting with and crossing biological barriers. A number of chemical approaches have been reported to successfully constrain unstructured peptides into protein secondary structural elements, including peptide stapling, template nucleation and diaminodiacid-based macrocyclization.To confirm the conformational preference of our designed constrained peptides experimentally, we characterized the secondary structures of each peptide both in deionized water and 25 mM sodium dodecyl sulfate (SDS) using circular dichroism (CD) spectroscopy . An anioet al., a series of stapled peptides was synthesized to determine the biophysical parameters that dictate cell penetration.versus the retention times in different cell lines (Fluorescence-activated cell sorting (FACS) analysis was next performed to quantify the cellular uptake of the constrained peptides in different cell lines. The cells were incubated with 5 μM FITC-labelled peptides for 1 hour in a serum-free cell medium. Then, the cells were incubated with 0.25% trypsin for 10 min. In order to quench extracellular fluorescence, the cells were incubated with 0.05% (w/v) trypan blue for 3 min prior to analysis. A control experiment showed that extensive fluorescence quenching was observed when Triton-X100 was added to permeabilize the cells in the presence of trypan blue Fig. S1.40,41 Thll lines . Our datll lines .  correlates well with the cellular uptake efficiency. We first performed the helix/hairpin wheel projection of these peptides and calculated the HMs based on the primary sequence from the equation According to Pei’s work in 2016, the binding affinity of a peptide to the cell membrane is correlated with the cellular uptake efficiency.Finally, we set out to investigate the delivery capacity of these short constrained peptides as molecular transporters as a proof of principle. The most potent cyclic peptides A1 and B1 were used as model peptides. We synthesized biotinylated peptides A1 and B1. The biotin moiety was site-specifically incorporated into the N-terminus of the peptides using a PEG spacer. Commercially available FITC-labelled avidin was then pre-incubated with biotinylated peptides of equal molarity at 37 °C for 30 min to form peptide–avidin complexes through biotin–avidin interactions. Live-cell confocal microscopy imaging was then performed to monitor the internalization of the conjugates in HEK293T cells over 1 hour. The real-time monitoring of the representative peptide–avidin conjugates is shown in In conclusion, we synthesized a series of constrained peptides with either α-helix or β-hairpin conformations. These short constrained peptides confer the same number of charged residues but differ in their topological distributions. Their cellular uptake efficiencies in different cell lines were tested. By modelling the structures of these constrained peptides, we calculated the amphipathicity of the peptides. We found that the amphipathicity of the peptides correlates well with the cellular uptake efficiency. We proposed that peptides with larger HMs have stronger binding affinities with the cell membrane which further accelerates the endocytosis process. We envision that this finding will shed further light on the design principle of potent conformationally constrained cell-penetrating peptides for biomedical applications.There are no conflicts to declare.Supplementary informationClick here for additional data file.


BRCA1/2) or HRD scores. Instead, we found several proteomic markers that predicted PDX response, including high levels of SLFN11 and E-cadherin and low ATM. SLFN11 and E-cadherin were also significantly associated with in vitro sensitivity to cisplatin and topoisomerase1/2 inhibitors . Treatment with cisplatin or PARP inhibitors downregulated SLFN11 and E-cadherin, possibly explaining the rapid development of therapeutic resistance in SCLC. Supporting their functional role, silencing SLFN11 reduced in vitro sensitivity and drug-induced DNA damage; whereas ATM knockdown or pharmacologic inhibition enhanced sensitivity. Notably, SCLC with mesenchymal phenotypes  signature scores) displayed striking alterations in expression of miR200 family and key SCLC genes . Thus, SLFN11, EMT, and ATM mediate therapeutic response in SCLC and warrant further clinical investigation as predictive biomarkers.Small cell lung cancer (SCLC) is one of the most aggressive forms of cancer, with a 5-year survival <7%. A major barrier to progress is the absence of predictive biomarkers for chemotherapy and novel targeted agents such as PARP inhibitors. Using a high-throughput, integrated proteomic, transcriptomic, and genomic analysis of SCLC patient-derived xenografts (PDXs) and profiled cell lines, we identified biomarkers of drug sensitivity and determined their prevalence in patient tumors. In contrast to breast and ovarian cancer, PARP inhibitor response was not associated with mutations in homologous recombination (HR) genes (e.g.,  BRCA1/2, ATM) . As . As ZEB1) Figure  28]. We. WeZEB1,) Figure . In generprising .Using an approach similar to that applied to SLFN11, we then investigated other drug classes for which E-cadherin might be a predictive marker of response in SCLC. Based on the bimodal index, we found that high E-cadherin level was associated with sensitivity to several drug types, including PARP inhibitors (n=5), alkylating agents (n=8), TOP2A/B inhibitors (n=4), HDAC1 inhibitors (n=3), BCL2 inhibitors (n=3), and IGF1R inhibitors (n=4) Figure . Many ofOur findings suggest that high SLFN11 and low ATM expression levels predict PARP inhibitor response in PDX models and/or cell lines, whereas standard biomarkers of PARP inhibition defined in other cancer types  do not . We alsoATM knockdown increased PARP inhibitor and cisplatin sensitivity, suggesting that loss of ATM expression has a direct impact on drug sensitivity. Further supporting this, we found that the combination of ATM and PARP inhibitors overcame resistance to single-agent PARP inhibition in lines with low SLFN11. These findings—together with recent clinical data showing that ATM mutations are associated with response to the PARP inhibitor olaparib in prostate cancer patients [Although low ATM levels were associated with talazoparib response in PDX models, we had an insufficient number of ATM-low cell lines to test its predictive value across our cell line panel. However, we found that patients —support Based on levels of SLFN11 and ATM observed in treatment-naïve SCLC tumors, we expect that up to half of SCLC patients could respond to PARP inhibitors in the front-line setting. However, given that these cancers develop chemotherapy resistance within a few months after initial treatment, we predicted that SLFN11—a biomarker of cisplatin and PARP inhibitor response—may be downregulated following platinum-based chemotherapy. Indeed, cell lines treated with cisplatin or PARP inhibitors had reduced SLFN11 levels. This implies that archival (diagnostic) tumor tissue may not accurately predict response to PARP inhibitors in patients who have developed cisplatin resistance and, therefore, re-biopsy may be necessary to accurately assess biomarker status.PARP1 reduced SLFN11 levels, loss of PARP1 expression , may meSLFN11 in early-stage SCLC, including 16 Type I IFN signaling pathway genes and targetable immune markers PDL1 and CTLA4. SLFN11 is expressed by T-cells and monocytes and is an IFN-stimulated gene in peripheral blood mononuclear cells [SLFN11 is also a potential surrogate marker of T-cell or macrophage infiltration and a biomarker for response to immunotherapy drugs targeting PDL1 and CTLA4, but this requires further testing in a clinical setting. Given the recent addition of immunotherapy to treatment options for relapsed SCLC (www.NCCN.org), these findings merit further investigation given their potential clinical impact [SLFN11 promoter contains several ETS binding sites and functions as an ETS factor response gene, with ETS transcription factors FLI1 and ETS1 having proposed roles in regulating SLFN11 expression in colon, breast, and prostate cancers [EHF is elevated in SCLC tumors, positively correlated with SLFN11 response (cell line and tumors) and predicts drug response. In contrast, EHF is negatively correlated with SLFN11 expression in other cancers from NCI60 and CCLE data sets [SLFN11 functions as an ETS response gene, the particular ETS transcription factor that regulates SLFN11 expression is cancer type–specific. In agreement with previous studies showing that hypermethylation regulates SLFN11 and is correlated with cisplatin sensitivity in NCI60 cell lines [in vitro sensitivity to both cisplatin and PARP inhibitors. However, treatment with decitabine and/or an HDAC inhibitor was insufficient to raise SLFN11 levels in SCLC cell lines. This suggests that methylation or other epigenetic modifications may not be dominant regulators of SLFN11 levels in SCLC, but may be useful as a biomarker of response to both cisplatin and PARP inhibitors.SLFN11 levels directly confer chemotherapy and/or PARP inhibitor sensitivity in a number of cancer types, but it is unclear how this is controlled. Proposed mechanisms of SLFN11 regulation include IFN signaling , ETS traar cells . Howeverl impact . The SLF cancers . In our ata sets . These fll lines , we founZEB1/2, FOXO1, and NEUROD1; and decreased levels of stem cell markers  and other SCLC drivers  [We and others have previously shown an important role for EMT in modulating drug resistance in NSCLC. However, this is the first report linking EMT with resistance to multiple drug classes in SCLC. We found a significant association between EMT and resistance to PARP inhibitors, cisplatin, and other novel drug classes such as Bcl-2 inhibitors. In SCLC lines and patient tumors, loss of E-cadherin and high EMT gene signature score were associated with changes at the protein, miRNA, and mRNA level in genes and miRNA well known to regulate EMT, further supporting the presence of a mesenchymal subset of SCLC. This included downregulation of miR-200 family members  , 38; hig, ASCL1) , 39. ASC, ASCL1) .To further explore the association between EMT and drug resistance, we expanded our analysis to a large screen of oncology drugs . In addiPARP1 may represent a novel mechanism of acquired resistance to PARP inhibitors. Finally, E-cadherin levels and EMT score are linked with SCLC response to PARP inhibitors, chemotherapy, and other targeted therapies. Future studies should investigate methods to restore SLFN11 levels in resistant models and mechanisms regulating EMT, in order to develop means to therapeutically alter EMT while inhibiting PARP in SCLC.In conclusion, our findings support the notion that more than one biomarker is needed to predict SCLC response to PARP inhibition and/or chemotherapy and that expression of these biomarkers is dynamically regulated by drugs used in frontline therapy. In addition, our results show that SLFN11 and ATM directly regulate drug sensitivity, which suggests that therapeutically targeting these proteins may reduce or delay drug resistance in SCLC. Our results also show that the dependence of SLFN11 levels on A pathologist specializing in lung cancer (J.F.) reviewed each PDX model for hematoxylin and eosin and standard SCLC IHC markers  to confirm that tumor pathology was consistent with SCLC.IHC markers assessed in this study included those used routinely in the clinical diagnosis and characterization of lung cancers  and candidate biomarkers .DNA from PDX tumors was profiled using the clinical comprehensive genomic profiling FoundationOne hybrid-capture based NGS test  . MutatioCells were grown in suggested media supplemented with fetal bovine serum and penicillin/streptomycin. Cells were passaged less than 6 months from the time they were received, and cell lines were routinely subjected to DNA fingerprinting as described previously .SLFN11 (L-016764–01-0005) or ATM (L-003201-00-0005) and their corresponding scramble control  or EHF (S25399) and the Silencer Select Negative Control No. 2  were transfected into H209 and DMS79 cells for 72 hours. The cells were then plated for 7-day proliferation assays or 24-h single-agent drug treatment. Knock down efficiency was validated by quantitative reverse transcription polymerase chain reaction and western blot analyses. PARP1 was stably knocked down in H209 and H526 cell lines using plasmid vectors. The PARP1 shRNAs were from GE Dharmacon . Knock down efficiencies were assessed with western blotting.For gene silencing, pooled small interfering RNAs (siRNAs) targeting To determine effect of drug treatment on protein expression, H209 and H526 cells were plated for 24 h and then treated with 1 μM cisplatin, 1 μM olaparib, 100 nM talazoparib. Cells were collected 72 h later, and protein lysates were isolated. SLFN11, E-cadherin, and ATM expression were assessed by western blotting. For the demethylation/HDAC inhibition experiments, H69, H526, H841, and H209 cells were plated for 24 h and then treated for 72 h with dimethyl sulfoxide or 5 μM decitabine  or with 100 ng/ml trichostatin A (Sigma Aldrich) added in the last 16h. All experiments were performed in triplicate.


DCK gene silencing due to the hypermethylation of a CpG island and reduced DCK activity due to a nonsynonymous variant allele were not associated with Ara‐C sensitivity. Clofarabine is a second‐generation deoxyadenosine analog rationally synthesized to improve stability and reduce toxicity. The IC50 of clofarabine in 79 BCP‐ALL cell lines was approximately 20 times lower than that of Ara‐C. In contrast to Ara‐C, although the knockout of DCK induced marked resistance to clofarabine, sensitivity to clofarabine was only marginally associated with DCK gene expression level, suggesting a possible efficacy of clofarabine for BCP‐ALL that shows relative Ara‐C resistance due to low DCK expression.Cytosine arabinoside (Ara‐C) is one of the key drugs for the treatment of acute myeloid leukemia. It is also used for consolidation therapy of acute lymphoblastic leukemia (ALL). Ara‐C is a deoxyadenosine analog and is phosphorylated to form cytosine arabinoside triphosphate (Ara‐CTP) as an active form. In the first step of the metabolic pathway, Ara‐C is phosphorylated to Ara‐CMP by deoxycytidine kinase (DCK). However, the current cumulative evidence in the association of the Ara‐C sensitivity in ALL appears inconclusive. We analyzed various cell lines for the possible involvement of DCK in the sensitivities of B‐cell precursor ALL (BCP‐ALL) to Ara‐C. Higher DCK expression was associated with higher Ara‐C sensitivity. DCK knockout by genome editing with a CRISPR‐Cas9 system in an Ara‐C‐sensitive‐ALL cell line induced marked resistance to Ara‐C, but not to vincristine and daunorubicin, indicating the involvement of DCK expression in the Ara‐C sensitivity of BCP‐ALL.  DCK gene into Ara‐C‐resistant rat leukemic cell line restored in vitro Ara‐C sensitivity DCK mRNA expression level was associated with a poor therapeutic outcome DCK gene expression relapsed more frequently than those with higher DCK gene expression. A recent single‐nucleotide polymorphism array analysis of the Ara‐C‐resistant xenograft model of ALL revealed that an Ara‐C‐resistant ALL subline, which spontaneously expanded during Ara‐C treatment, acquired a homozygous deletion of the DCK gene DCK gene expression tended to correlate with in vitro Ara‐C resistance in infant ALL.Cytosine arabinoside  is one of the key drugs for the treatment of acute myeloid leukemia (AML). It is also used for consolidation therapy of acute lymphoblastic leukemia (ALL). Ara‐C is a deoxycytidine analog that is phosphorylated into cytosine arabinoside triphosphate (Ara‐CTP) as an active form, which competes with deoxycytidine triphosphate (dCTP) for incorporation into DNA 2 and pegylated asparaginase (PEG‐ASP) 1 × 2500 iu/m2 was significantly more effective than standard therapy consisting of high‐dose Ara‐C 4 × 3 g/m2 and PEG‐ASP 1 × 2500 iu/m2 for newly diagnosed ALL patients. A significantly lower minimal residual disease level was found at the end of induction therapy with clofarabine, suggesting the antileukemic activity of clofarabine is clinically higher than that of Ara‐C. Clofarabine is phosphorylated to its monophosphate derivatives primarily by DCK Clofarabine (2‐chloro‐9‐[2‐deoxy‐2‐fluoro‐b‐D‐arabinofuranosyl] adenine) is a second‐generation deoxyadenosine analog rationally synthesized to improve stability and reduce the potential for dose‐limiting toxicity DCK gene expression. Our observations suggest efficacy of clofarabine for BCP‐ALL that shows relative resistance to Ara‐C due to low DCK expression.In the present study, we tried to clarify the possible involvement of DCK in sensitivities to Ara‐C and clofarabine using a wide variety of B‐cell precursor ALL (BCP‐ALL) cell lines. Higher DCK expression was associated with higher Ara‐C sensitivity, and the knockout of DCK expression by a genome editing procedure using a CRISPR‐Cas9 system MLL‐rearranged (MLL+) cell lines , 16 t‐ALL cell lines , 4 t‐ALL cell lines , 3 t‐ALL cell lines , and 31 other cell lines . Seven BCP‐ALL cell lines  were established from non‐Japanese patients, whereas seventy‐two BCP‐ALL cell lines were established from Japanese patients 2 at 37°C.Seventy‐nine BCP‐ALL cell lines were analyzed, which included 14 Philadelphia chromosome‐positive (Ph+) cell lines , 11 ALP), 4 t;19‐ALL c5 cells were plated into a 96‐well flat‐bottom plate and cultured in triplicate in the absence or presence of seven concentrations of each drug for 68 h. After a 6‐h additional incubation with alamarBlue, the absorbance at 570 nm was monitored by a microplate spectrophotometer using 600 nm as a reference wavelength. Cell survival was calculated by expressing the ratio of the optical density of treated wells to that of untreated wells as a percentage. The concentration of agent required to reduce the viability of treated cells to 50% of untreated cells was calculated, and the median of three independent assays was determined as IC50. For detection of apoptosis, cells were cultured in the absence or presence of Ara‐C or clofarabine for 48 h, stained with FITC‐conjugated Annexin V and 7‐aminoactinomycin D (7AAD) , and analyzed by flow cytometry .To determine the IC50s of Ara‐C and clofarabine, an alamarBlue cell viability assay  was performed; 1 − 4 × 10DCK, ABCG2 (BCRP1), ENT1, ENT2, NT5C2, and DGUOK were performed using Taqman probe kit . As an internal control, ACTB was quantified using Taqman RT‐PCR kit (Hs01060665_g1). For sequencing of the coding region of the DCK gene, 859‐bp region of exons 1–7, which contained 783 bp of entire open reading frame, was amplified with a forward primer (5′‐CCTCTTTGCCGGACGAGC‐3′) and a reverse primer (5′‐GGAACCATTTGGCTGCCTGT‐3′) and analyzed for direct sequencing with a reverse primer.Total RNA was extracted using TRIzol reagent , reverse transcription was performed using a random hexamer  and Superscript II reverse transcriptase (Invitrogen), and the sample was then incubated with RNase (Invitrogen). Real‐time reverse transcription (RT)–polymerase chain reaction (PCR) analyses of DCK gene using the CRISPR design tool . We selected 5′‐atcaagaaaatctccatcgaagg‐3′, which showed the highest off‐target hit score, and the synthesized oligomers were cloned into CRISPR‐Cas9 vector . After electroporation of the DCK‐targeting CRSIPR‐Cas9 vector using Neon electroporation transfection system (Thermo Fisher Scientific), the transfected cells were divided into 24‐well plates and cultured in the presence of 100 ng/mL of Ara‐C for 4 weeks. Untransfected cells were also divided into 24‐well plates and cultured in the same way. After the selection, genomic DNA was extracted from the Ara‐C‐resistant clones and amplified by PCR using a forward primer (5′‐GCCGCCACAAGACTAAGGA‐3′) and a reverse primer (5′‐GGAAAGCCCTCACCGAGTTG‐3′). The PCR products of clones #1 and #2 were sequenced using a TOPO TA‐cloning kit (Thermo Fisher Scientific). Protein expression of DCK was analyzed by immunoblotting, as previously reported To knockout DCK expression in KOPN41, an Ara‐C‐sensitive cell line established from t‐ALL patient 7 cells) resuspended into 50 μL of water with 1 μL internal standard of 13C‐UTP  was vortexed for 30 sec and subsequently vortexed with 70% HPLC grade acetonitrile  for 1 min. Five microliter of each supernatant of the sample mixture centrifuged at 13,200 × g for 10 min was applied into the LC‐MS/MS system composed of AQUITY H‐class ultra‐performance liquid chromatography and XevoTQD triple‐quadrupole tandem mass spectrometer  and analyzed using MassLynx 4.1 software . InertSustain AQC18 metal free PEEK column  was used for separation. Column temperature and flow rate were set at 40°C and 0.3 mL/min, respectively, and autosampler temperature was set at 4°C. Gradient elution program was conducted for chromatographic separation with 5 mmol/L formic ammonium  and acetonitrile as follows: 0 min (A 100%), 1.5 min (A 100%), 5.5 min , 9.5 min , and 10 min (A100%). The mass spectrometry was operated in the ESI positive mode and quantified by multiple reactions monitoring (MRM). Nitrogen gas at 350°C with 1000 L/h of flow rate and argon gas with 50 L/h of flow rate were used as desolvation and collision, respectively. Capillary voltage was set at 3.5 kV. The MRM transitions were used for the quantification as follows: 483.99 to >112.01 for Ara‐CTP with collision energy of 20 V and 493.92 to >101.95 for 13C‐Uridine triphosphate with collision energy of 24 V. Retention time for Ara‐CTP and 13C‐UTP were 0.95 and 0.91 min, respectively. Calibration curve of standard Ara‐CTP  at the concentrations of 0.5–2000 nmol/mL was y = 0.0020 + 0.6612 (r2 = 0.995).Intracellular concentration of Ara‐CTP was measured by liquid chromatography–mass spectrometry (LC/MS). Triplicated samples of wild‐type and DCK knockout clone (#1) of KOPN41 cultured in the absence or presence of Ara‐C for 6 h were washed with PBS. Each frozen cell pellet (1.5 × 10DCK gene by PCR with a forward primer (5′‐ GTTGTTTGGGGTAGAGGTTTTT‐3′) and a reverse primer (5′‐ CTAAACCAAATCCTAACCTACC‐3′) using one cycle of 95°C for 4 min, 40 cycles of 95°C for 30 sec, 55°C for 30 sec, 72°C for 1 min, and with a final cycle of 72°C for 7 min. Bisulfite‐modified DNA of two cell lines (KOPN66bi and Kasumi2) was also amplified for a CpG island of the BIM gene ™ 2 System using an Ion PGM™ Template OT2 400 Kit (Thermo Fisher Scientific) to produce 400 base‐read libraries. Sequencing was performed using an Ion PGM™ Hi‐Q Sequencing Kit (Thermo Fisher Scientific) and 850 flows on an Ion 318 Chip Kit v2 (Thermo Fisher Scientific) according to the manufacturer's protocol. After sequencing, single processing and base‐calling were performed using Torrent Suite 5.0.2 (Thermo Fisher Scientific). Methylation analysis was performed using Methylation Analysis_Amplicon plug‐in v1.3 (Thermo Fisher Scientific).Genomic DNA was subjected to sodium bisulfite modification with an EZ DNA Methylation‐Lightning kit . Bisulfite‐modified DNA was amplified for a CpG island of the t‐test was for comparison in the same subject, and Pearson's correlation analysis was for correlation between two factors using Excel software .Mann–Whitney test was applied for comparison of drug sensitivities, chi‐square test was for comparison of deletion incidence, a paired P = 0.0357 in a Mann–Whitney test) and MLL+ALL cell lines . Although statistically not significant probably due to limited numbers of cell lines, t‐ALL cell lines  were relatively resistant, whereas t‐ALL cell lines (79 ng/mL) were relatively sensitive.We, firstly, analyzed Ara‐C‐sensitivity of 79 BCP‐ALL cell lines using an alamarBlue assay. Based on a dose–response curve in triplicate experiments Fig. A, the meDCK gene expression with Ara‐C sensitivity DCK in 79 BCP‐ALL cell lines by real‐time RT‐PCR. Gene expression of DCK in t‐ALL cell lines  was significantly lower than that in Ph+ALL cell lines  and MLL+ALL cell lines  and 39 cell lines with lower DCK gene expression  than 39 cell lines with lower DCK gene expression (700 ng/mL); however, the gene expression of DCK was not significantly correlated with the IC50 of Ara‐C (r = −0.293). We next investigated an association between the gene and protein expression of DCK in six representative BCP‐ALL cell lines, three cell lines each with high and low DCK gene expression  of 24 wells of the CRISPR‐Cas9‐transfected cells. We performed PCR of the genomic DNA extracted from the Ara‐C‐resistant clones using primers that were designed at both sides of the target sequence. Electrophoresis of the PCR products revealed extra products with abnormal sizes in all of the seven clones  of Ara‐C for 6 h, using liquid chromatography–mass spectrometry (LC/MS). As shown in Figures The above observations indicated that the DCK expression level is associated with Ara‐C sensitivity in BCP‐ALL cell lines. To directly verify the involvement of DCK in the antileukemic activity of Ara‐C in BCP‐ALL, we tried to knockout DCK expression by a genome editing procedure using a CRSIPR‐Cas9 system ene Fig. A, which nes Fig. . The PCRnes Fig. B. A wildnes Fig. C. We nexWe investigated Ara‐C sensitivity in two knockout clones (#1 and #2) of KOPN41 in comparison with parental KOPN41 cells using an alamarBlue assay Fig. E and floDCK gene DCK gene expression and subsequently Ara‐C sensitivity. To verify this possibility, we sequenced the CpG island of the DCK gene after bisulfite treatment of genomic DNA. After PCR amplification of the region, which contains 33 CG dinucleotide sites, we determined the sequence using a next‐generation sequencer and quantified the % methylation of each CG dinucleotide site. As representatively shown in Figure DCK gene was <1% in all cell lines . Next, we focused on three previously known nonsynonymous single‐nucleotide polymorphisms (SNPs) of the DCK gene, rs66878317 (I24V), rs66472932 (A119G), and rs67437265 (P122S) DCK gene expression, respectively.Considering the association of 878317 I2V, rs6647ABCG2 (an efflux membrane transporter) and hENT2 (an uptake transporter) were not associated with Ara‐C sensitivity. Unexpectedly, cell lines with relatively higher hENT1 (an uptake transporter) gene expression were more resistant to Ara‐C than those with lower expression (P = 0.020 in a Mann–Whitney test), although statistically significant correlation (R2 > 0.2) was not observed between the gene expression of hENT1 and the IC50 of Ara‐C (r = 0.310). Gene expression level of DGUOK was not associated with Ara‐C sensitivity. Among inactivating factors, an association of CDA gene was not evaluable due to low or undetectable expression. Gene expression level of NT5C2 was not associated with Ara‐C sensitivity.Previous reports revealed possible associations of transporters such as ABCG2 BCRP1)  1, and hr = 0.575, P = 2.9 × 10−8). Correlation was significant in Ph+ALL, MLL+ALL, t‐ALL, and other ALL cell lines, while it was insignificant in t‐ALL and t‐ALL cell lines. The median IC50s of clofarabine and Ara‐C were 8.5 and 163 ng/mL, respectively. The IC50 of clofarabine was approximately 20 times lower than that of Ara‐C. Among 20 Ara‐C‐resistant cell lines, whose IC50 of Ara‐C was 1000 ng/mL or higher, 12 cell lines (60%) were sensitive to clofarabine (IC50 of clofarabine <20 ng/mL). Although clofarabine sensitivity was correlated significantly to Ara‐C sensitivity, no significant association was observed between the types of translocation and the IC50s of clofarabine , and t‐ALL cell lines (5000) than that in cell lines having favorable translocations such as t‐ALL cell lines (11.2) and t‐ALL cell lines (5.3), as well as other BCP‐ALL cell lines (8.2).We next evaluated sensitivity to clofarabine using alamarBlue assays Fig. A. The inDCK gene expression in 79 BCP‐ALL cell lines was marginal  were slightly lower (P = 0.044) than those in 39 cell lines with lower DCK gene expression (11.1 ng/mL). In contrast, the ratios of IC50 of Ara‐C divided by that of clofarabine for the cell lines with higher DCK gene expression  were significantly lower (P = 0.0024) than those for the cell lines with lower DCK gene expression .In the present study, to verify the involvement of DCK in the antileukemic activity of Ara‐C against BCP‐ALL, we knocked out DCK expression in an Ara‐C‐sensitive cell line using the CRISPR‐Cas9 system DCK gene DCK gene promoter with sensitivity to nucleoside analogs in tumor cell lines is unlikely. However, direct sequencing and methylation‐specific PCR of the bisulfite‐treated genomic DNA in previous studies displayed limitations in terms of sensitivity and quantitative performance. Thus, in the present study, we applied a next‐generation DNA sequencing platform to precisely analyze the methylation status of 79 BCP‐ALL cell lines. We demonstrated that the % methylation was <5% at all 33 CG dinucleotide sites in the approximately 250‐bp region of the DCK gene promoter, which was almost identical to the region that was analyzed in the previous reports. Our observations clearly demonstrate that DCK gene silencing by methylation is not the mechanism for Ara‐C resistance, at least in BCP‐ALL cell lines.A CpG island exists in the promoter region of the NT5C2PRPS1 genes DCK gene is critically involved in the antileukemic activity of Ara‐C, and more than half of the cell lines were established from relapsed ALL patients, we speculated that somatic mutations in the coding exons of the DCK gene may be associated with Ara‐C resistance in some BCP‐ALL cell lines. However, mutations were not observed in 79 BCP‐ALL cell lines, demonstrating that the acquisition of a somatic mutation in the coding exons of the DCK gene is uncommon as a mechanism for Ara‐C resistance.Recently, next‐generation sequencing analyses of relapsed childhood ALL samples revealed somatic mutations in critical genes for drug metabolism, suggesting mechanisms for acquired drug‐resistant phenotypes; mutations in DCK gene rs66878317 (I24V), rs66472932 (A119G), and rs67437265 (P122S). Our sequence analyses of the coding exons of the DCK gene identified a variant allele at rs67437265, but not at rs66878317 and rs66472932, in which variant allele frequencies were reported to be 0% in the normal Japanese population in the database of the 1000‐genome project. Lamba et al. Km and Vmax in a substrate kinetic study. Epstein–Barr virus‐transformed lymphoblast cell lines from individuals with a heterozygous mutant allele demonstrated significantly lower DCK activity compared with cell lines from homozygous wild‐type subjects. However, it is unclear whether reduced DCK activity due to a variant allele of rs67437265 is subsequently associated with reduced sensitivity to Ara‐C. In the present study, eight cell lines and one cell line showed a heterozygous and homozygous variant allele, respectively. The allele frequency in 72 BCP‐ALL cell lines established from Japanese patients was almost identical to that in the normal Japanese population. Of note, there was no significant difference in the IC50 values of Ara‐C between nine cell lines with a variant allele and 63 cell lines with a homozygous wild‐type allele. These observations suggest that the impact of a variant allele of rs67437265 on Ara‐C sensitivity may be less significant than the impact of DCK gene expression on Ara‐C sensitivity in BCP‐ALL cell lines.Lamba et al. NT5C2 gene expression with Ara‐C sensitivity was not clear in 79 PCB‐ALL cell lines. Gene expression of ABCG2, an efflux membrane transporter hENT2, an uptake transporter DGUOK, an activating factor hENT1, an uptake transporter hENT1 gene expression and Ara‐C sensitivity is that significance of hENT1 in Ara‐C sensitivity might be substantially negligible in comparison with that of DCK, when hENT1 is expressed above a certain level. In this context, gene expression level of hENT1 is somehow interrelated with that of DCK in BCP‐ALL cell lines. Indeed, gene expression level of hENT1 was relatively lower in the cell lines with higher DCK gene expression than that in the cell lines with lower DCK gene expression (P = 0.078 in a Mann–Whitney test). Sensitivity to clofarabine was not associated with any of five factors tested.Although Ara‐CMP is dephosphorylated by NT5C2 MLLr, and t, were significantly more resistant to Ara‐C than the cell lines with favorable translocations such as t and t. The gene expression of DCK was significantly lower in t‐ALL cell lines consistent with their Ara‐C resistance, but not in Ph+ALL and MLL+ALL cell lines despite their Ara‐C resistance. These observations suggested that low DCK gene expression may not be the main mechanism for Ara‐C resistance in Ph+ALL and MLL+ALL cell lines. In contrast to Ara‐C, clofarabine showed similar antileukemic activity against BCP‐ALL cell lines with poor prognostic translocations as well as those with favorable translocations, suggesting that clofarabine treatment may be more beneficial for patients with poor prognostic translocations than patients with favorable translocations.Sensitivity to Ara‐C was significantly associated with the types of translocation. BCP‐ALL cell lines with poor prognostic translocations, such as Ph1, M.H., K.M., and Y.T. performed the research, analyzed the data, and wrote the paper; T.I. designed the research study, performed the research, analyzed the data, and wrote the paper as principal investigator; K.K., M.A., A.W., S.S., T.S., H.O., K.A., and K.G. performed the research; H.G., M.M., and S.I. contributed essential cell lines; E.S. designed the research study; K.S. supervised the project; and all authors contributed to the final draft.The authors declare no competing financial interests.Figure S1. Electrophoresis of genomic PCR products in Ara‐C–resistant clones of the CRISPR–Cas9 treansfected KOPN41.Figure S2. Chromatograms of wild‐type and DCK knockout clone of KOPN41 cultured in the absence or presence of 20 μM Ara‐C.Figure S3. Ara‐C specific resistance in DCK knockout clones.Figure S4. Sequencing of RT–PCR products in codon 122 of the DCK gene.Click here for additional data file.


These findings indicated CDK2 as a promising candidate therapeutic marker for OS and therefore we assessed the efficacy of the CDKs-inhibitor roscovitine in both drug-sensitive and -resistant OS cell lines. All cell lines resulted to be responsive to roscovitine, which was also able to increase the activity of cisplatin and doxorubicin, the two most active DNA damaging drugs used in OS chemotherapy. Our results indicated that combined treatment with conventional OS chemotherapeutic drugs and roscovitine may represent a new candidate intervention approach, which may be considered to enhance tumour cell sensitivity to DNA damaging drugs.Cyclin-dependent kinase 2 (CDK2) has been reported to be essential for cell proliferation in several human tumours and it has been suggested as an appropriate target to be considered in order to enhance the efficacy of treatment regimens based on the use of DNA damaging drugs. We evaluated the clinical impact of CDK2 overexpression on a series of 21 high-grade osteosarcoma (OS) samples profiled by using cDNA microarrays. We also assessed the in vitro efficacy of the CDKs inhibitor roscovitine in a panel of drug-sensitive and drug-resistant human OS cell lines. OS tumour samples showed an inherent overexpression of CDK2, and high expression levels at diagnosis of this kinase appeared to negatively impact on clinical outcome. CDK2 expression also proved to be relevant for  Osteosarcoma (OS), the most common malignant tumour of bone, is usually treated with neoadjuvant chemotherapy protocols based on cisplatin (CDDP), doxorubicin (DX), methotrexate (MTX) and ifosfamide –3. The fDeregulation of cell cycle control mechanisms and aberrant activities of cell cycle-related kinases have been associated with neoplastic evolution and progression of several human cancers, including OS –10. Key Regulation of CDKs activity occurs at multiple levels, and human cancer cells frequently present deregulated CDKs activities, which allows them to escape the normal cell cycle regulation machinery , 5, 10. CDKs are essential not only for cell cycle regulation and cell division, but also for cellular response to DNA damaging agents, with important consequences for chemotherapy response –18. The For all these reasons CDKs have been considered as attractive targets for cancer therapy and several CDK inhibitors have been developed and are now available for clinical use , 21, 22.Data about CDK2 impact and relevance in OS, as well as information on CDKs inhibitors acitivity in this tumour, are still very scarce. In the present study, we have assessed the biologic relevance of CDK2 expression in OS cells with the aim to define whether this kinase may be considered as a new candidate target for therapeutic interventions based on the use of roscovitine. The efficacy of roscovitine has then been tested on a panel of drug sensitive and resistant human OS cell lines, which were treated with either roscovitine alone or in combination with the drugs used in conventional OS chemotherapy.CDDP, DX, and MTX were purchased, respectively, from Teva Italia , Wyeth Lederle  and Sandoz . Roscovitine was purchased by Santa Cruz Biotechnology . Stock solutions of CDDP (500 μg/ml) and MTX (25 mg/ml) were stored at 4°C. Stock solution aliquots of DX (2 mg/ml) were stored at -20°C. Roscovitine was dissolved in DMSO at 10 mM concentration and stock solution aliquots were stored at -20°C. For all drugs, working concentrations were prepared by diluting stock solutions in culture medium immediately before use.2 atmosphere.The cell line panel used for this study included seven drug-sensitive  and six drug-resistant human OS cell lines. U-2OS, Saos-2, HOS (CRL-1543) and MG-63 cell lines were obtained from the American Type Culture Collection . IOR/OS9, IOR/OS10, IOR/OS14, IOR/OS18, and SARG human OS cell lines were established from bioptic clinical specimens obtained from OS patients at the Laboratory of Experimental Oncology of the Rizzoli Orthopaedic Institute . VariantThe series of clinical samples used in this study included 21 conventional OS . Samples were obtained from surgical biopsies at diagnosis and patients were successively treated with neoadjuvant chemotherapy protocols based on DX, MTX, CDDP and ifosfamide. After the end of chemotherapy treatment, patients were continuously followed and clinical data updated. Adverse events were defined as recurrence of the tumor at any site or death during remission, and event-free survival was calculated from the date of initial diagnosis. Median follow-up was 91 months (range 63–218 months). Written informed consent for using their biologic material for research purposes was obtained from each patient entering the study. The study was approved by the institutional Ethics Committee.http://r2.amc.nl).RNA was isolated from both human OS cell lines and clinical samples. Before extraction, all clinical samples were histologically examined for tissue quality in order to isolate RNA only from representative specimens containing at least 90% tumour cells. RNA was extracted by using TRIzol reagent (Invitrogen Ltd) according to standard procedures. After isolation, RNA concentration and quality were evaluated by spectrophotometry using NanoDrop ND-1000  and by electrophoresis on a 1.5% agarose gel. Fragmentation of cRNA, hybridization to hg-u133 plus 2.0 microarrays and scanning were performed as previously described by [Cells were seeded in 6-well plates in drug-free IMDM 10% FBS without antibiotics. After 24 h, medium was replaced with FBS- and antibiotic-free IMDM supplemented with Lipofectamine 2000 (Invitrogen Ltd) and 25 nM Dharmacon ON-TARGET plus SMARTpool siRNA  specific for CDK2  or scrambled SMARTpool siRNA (D-001810-02-20). Controls were cultured in the same media without siRNA. After 5 h, transfection medium was replaced with IMDM 10% FBS without antibiotics and cells were maintained in culture for additional 24–96 h. After evaluation of cell morphology, cells were harvested, counted with the trypan blue dye exclusion method, and processed for cell cycle analysis and for RNA and protein extraction.For single gene expression analyses, 500 ng of total RNA were reverse transcribed using the High Capacity cDNA Archive Kit  according to the manufacturer’s protocol. cDNAs were aliquoted and stored at -20°C until use. To quantify the fold-change in gene expression between silenced samples and controls, the TaqMan Gene Expression Assay CDK2 Cyclin-dependent kinase 2  was used on the ABI PRISM 7900 SDS instrument (Applied Biosystem). GAPDH  was used as reference gene.3VO4, 1mM phenylmethylsulfonyl fluoride, and 10 μg/mL aprotinin). Cell suspensions were shaked in ice for 30 minutes. Lysates were centrifuged at 13,000 rpm for 15 min at 4°C. Equal amounts of cell lysates were dissolved with SDS-PAGE and then transferred to PVDF membranes . Membranes were incubated in blocking solution consisting of 5% powered milk in TBST solution  at room temperature for 1 h and then with one of the following primary antibodies: 1:1000 anti-CDK2 mouse monoclonal antibody , 1:1000 Poly ADP-ribose polymerase-1  and 1:1000 Cleaved Caspase-3 (Asp175)  both purchased from Cell Signaling Technology . To verify the protein loading of each sample, the same membranes were immunostained with 1:50000 mouse anti-actin, clone C4, monoclonal antibody . Protein bands were visualized by using an enhanced chemiluminescence detection system .Cells were scraped, washed twice in cooled phosphate buffered saline solution (PBS) and then lysed in RIPA buffer or lysis buffer for phosphoproteins containing 50mM Tris HCl pH 7.4, 150 mM NaCl, 1% NP-40, 0.25% NaDesoxycholate, 1mM EGTA, 1mM NaF, and inhibitors -2,5-dephenyltetrazolium bromide (MTT) assay kit  or the CellTiter-Fluor Cell Viability Assay kit  after 96 h of drug treatment. For each cell line, the IC50 value (drug concentration that induced 50% growth inhibition compared to untreated controls) was determined.The in vitro interactions between roscovitine and conventional chemotherapeutic drugs, human OS cell lines were incubated with different regimens of two-drugs combinations. Cell lines were treated with combinations of increasing drug dosages defined by the ratio of the specific IC50 values obtained for each cell line. Drug interaction effects were evaluated after 96 h of combined treatment. In drug sequence experiments, cell lines were sequentially exposed for 24 h to increasing dosages of DX or CDDP and then to increasing dosages of roscovitine for additional 48 h. The type of interaction in terms of synergism, antagonism or additivity, was defined on the basis of the combination index (CI) of each two-drugs combination, which was calculated with the equation of Chou-Talalay by using the CalcuSyn software . By following the range of CI values indicated in the CalcuSyn software manual, we classified the drug–drug interaction as synergistic when CI was lower than 0.90, as additive when 0.90≤CI≤1.10, or as antagonistic when CI was higher than 1.10.To evaluate 2 athmosphere at 37°C, harvested, and fixed in 70% ethanol for 30 min. After DNA denaturation with 2N HCl, cells were processed for indirect immunofluorescence with the B44 anti-bromodeoxyuridine mouse monoclonal antibody  diluted 1:8, followed by an anti-mouse FITC antibody (Sigma-Aldrich Co.) diluted 1:200. For the simultaneous determination of DNA content, cell nuclei were counterstained with 20 μg/ml propidium iodide (Sigma-Aldrich Co.). All samples were analysed by flow cytometry .Assessment of drug-induced cell cycle perturbations was performed by seeding drug-sensitive and -resistant cell lines in IMDM 10% FBS. After 24 h, medium was changed with IMDM 10% FBS without (control) or with the IC50 concentration of DX  or CDDP  for 24 h and then to the IC50 concentrations of roscovitine for additional 48 h. Additional controls were also included by culturing cells in IMDM 10% FBS additioned with DMSO concentrations corresponding to those of drug-treated samples. At the end of drug exposure, cells were incubated with 10 mM bromodeoxyuridine  for 1 h in a humidified 5% COTo estimate the extent of DNA damage on individual cells, the alkaline comet assay was chosen on the basis of its sensitivity and flexibility . All celThe alkaline comet assay was conducted according to the procedure developed by , with a Differences among means were analysed by Student’s t test. Kaplan-Meier and log-rank methods were used to draw and evaluate the significance of survival curves. The non parametric Mann-Whitney test was used to assess the significance of the difference in DNA-damage quantified on the basis of the evaluation of the TM. Significance was set at P ≤ 0.05.http://r2.amc.nl). Gene expression profiling analyses showed that CDK2 expression level was significantly higher in OS samples in comparison to human normal muscles and other normal tissues  and inhibitors. CDKs activity is commonly altered in cancer cells, and several human neoplasms present increased CDKs expression, indicating that these kinases are essential or play a relevant role for tumour growth and proliferation , 6.One of the leader members of CDKs family is CDK2, which is centrally involved in cell cycle regulation together with CDK1, while the other CDKs appear to play an auxiliary role , 21. MorSince CDK2 has not yet been analysed in detail in OS, the first part of our study focused on its evaluation in this neoplasm. We demonstrated that human OS clinical samples and cell lines present an inherent increased CDK2 expression compared to several human normal tissues, indicating that this kinase is relevant for OS biology. Moreover, patients with higher levels of CDK2 expression presented a trend toward a worse outcome suggesting that it may also impact on OS prognosis, despite this evidence needs further confirmation.Based on this body of information, we proceeded with the evaluation of the biologic relevance of CDK2 for OS cell growth. Silencing experiment results clearly showed that CDK2 depletion reduced the proliferation of OS cells, indicating that negatively interfering with this kinase may inhibit OS cell growth. This evidence is in agreement with findings reported for other tumours, which demonstrated that downregulation or inhibition of CDK2 prevents cancer cells proliferation , 37–39.We therefore tested the activity of roscovitine, a CDKs inhibitor with high affinity for CDK2, on a panel of drug-sensitive and -resistant human OS cell lines. In the drug-sensitive cell lines, roscovitine proved to be markedly active, with IC50 values in a low micromolar range, as also described in other tumour cell lines , 40. IntCombined treatments demonstrated that roscovitine positively interacted with DX or CDDP, when it was sequentially administered after these two anticancer agents. This positive interaction is in agreement with the reported evidence that CDKs play an important role in DNA-damage-induced checkpoint control and repair, and that their inhibition increases sensitivity to DNA damaging agents .On the other hand, association of roscovitine with CDDP mainly produced negative interactions. This findings can be explained by the fact that, in drug association treatments, the effectiveness of CDDP may be reduced by the cell cycle perturbations induced by roscovitine, as described in other experimental systems .Association with MTX proved to be almost invariably antagonistic, most probably because of the cytostatic effects that roscovitine produced in OS cell lines, which negatively interfered with the activity of this S phase-specific drug. However, sequential treatment of MTX followed by roscovitine mainly resulted in additive interactions.status [et al demonstrated that roscovitine preferentially induced apoptosis in prostate cancer and melanoma cells expressing wild-type P53 [status [In our experimental models, roscovitine was also able to induce apoptosis, but only in Saos-2 and not in U-2OS cell lines. These results are concordant with what has been reported in the literature for OS, which demonstrated roscovitine-induced PARP-1 cleavage in Saos-2 (P53-negative) cells , while dstatus . For exatype P53 , 44, whe [status , 46.Catalytic activities of CDKs also play a critical role in drug-induced DNA damage response , 18, 36.Since three out of the four drugs that are most frequently used for OS chemotherapy  produced DNA damages, we investigated whether the roscovitine-induced CDK2-inhibition could also negatively interfere with the DNA repair activity in OS cells, therefore increasing their sensitivity to DNA damaging drugs. Our results provided evidence that roscovitine treatment delays the normal activation of DNA repair systems, leading to an accumlation of DNA double strand breaks and, consequently, to an increase of DX and CDDP cytotoxicity. This evidence indicated that inhibition of CDK2 and other roscovitine-targeted CDKs can successfully synergise with DNA-damaging agents used in OS treatment and could therefore be considered for clinical purposes.In conclusion, our results indicated that combined treatment with conventional OS chemotherapeutic drugs and roscovitine may represent a new candidate intervention approach, which may be taken into consideration to improve conventional chemotherapy effectiveness. This indication is in agreement with other studies, which proved that roscovitine can increase conventional chemotherapy efficacy in sarcomas  and otheS1 FigOriginal films of CDK2 and Actin protein detection by western blot after siRNA transfection in U-2OS (A) and Saos-2 (B) human osteosarcoma cell lines. CDK2 and actin protein levels were assessed at different time points after the end of siRNA treatment . Legend: CTR, control, not-treated cells; SCR, cells transfected with scrambled siRNA; CDK2, cells transfected with anti-CDK2 siRNA; AURKA, cells transfected with anti-Aurora Kinase siRNA; h, hours after siRNA transfection. In Saos-2 films, samples 1, 4, 7, and 10 are control, not-treated cells; samples 2, 5, 8, and 11 are cells transfected with scrambled siRNA; samples 3, 6, 9, and 12 are cells transfected with anti-CDK2 siRNA.(JPG)Click here for additional data file.S2 Fig(JPG)Click here for additional data file.S3 FigA) Drug association experiments. B) Drug sequence experiments. Graphs refer to one representative experiment.(PDF)Click here for additional data file.S4 FigOriginal western blot films for the analyisis of cleaved caspase 3 and relative actin on U-2OS/DX580 and U-2OS/CDDP4μg cell lines (A) and of PARP-1 and relative actin on Saos-2 and Saos-2/DX580 (B). Legend: CTR 24h, control, not-treated cells harvested after 24h from seeding; CTR 72h, control, not-treated cells harvested after 72h from seeding; DX 24h, CDDP 24h, ROS 48h, cells treated with their respective IC50 dosage of doxorubicin (DX), cisplatin (CDDP) or roscovitine (ROS) harvested after 24h or 48h of treatment; SEQ, cells sequentially treated with DX or CDDP for 24h followed by roscovitine ROS for 48h. Positive controls (last lane) are represented by U-2OS and Saos-2 cell lines treated, respectively, with 5 μg/ml or 10 μg/ml CDDP for 48 h.(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.


Human cancer cell lines are the most frequently used preclinical models in the study of cancer biology and the development of therapeutics. Although anatomically diverse, human papillomavirus (HPV)-driven cancers have a common etiology and similar mutations that overlap with but are distinct from those found in HPV-negative cancers. Building on prior studies that have characterized subsets of head and neck squamous cell carcinoma (HNSCC) and cervical squamous cell carcinoma (CESC) cell lines separately, we performed genomic, viral gene expression, and viral integration analyses on 74 cell lines that include all readily-available HPV-positive  and CESC  cell lines and 55 HPV-negative HNSCC cell lines. We used over 700 human tumors for comparison. Mutation patterns in the cell lines were similar to those of human tumors. We confirmed HPV viral protein and mRNA expression in the HPV-positive cell lines. We found HPV types in three CESC cell lines that are distinct from those previously reported. We found that cell lines and tumors had similar patterns of viral gene expression; there were few sites of recurrent HPV integration. As seen in tumors, HPV integration did appear to alter host gene expression in cell lines. The HPV-positive cell lines had higher levels of p16 and lower levels of Rb protein expression than did the HPV-negative lines. Although the number of HPV-positive cell lines is limited, our results suggest that these cell lines represent suitable models for studying HNSCC and CESC, both of which are common and lethal. Head and neck squamous cell carcinoma (HNSCC) is the seventh most common cancer worldwide, with over 600,000 cases annually . More thin vitro and in vivo biomarker and targeted therapy identification for HNSCC. In order to tease out the genomic alterations attributable to HPV, we also included CESC cell lines, which are predominantly HPV-positive, in our analyses. The purpose of this study was to determine the genomic profiles—including mutations, HPV integration, and viral gene expression—of a large number of frequently used HPV-negative HNSCC cell lines and a majority of the HPV-positive tumor cell lines. Through these analyses, we found similar incidences of common mutations and genomic alterations in targetable genes as observed in previously performed preclinical studies as well as in the clinical samples curated by the cancer genome atlas (TCGA), suggesting that these cell lines are suitable candidates for studying HNSCC and CESC.Although HPV-associated and non-HPV-associated HNSCCs display clinical, epidemiologic, and molecular differences, the therapeutic regimens remain the same for both etiologies . The dist test p = 0.12).Despite the recent increase in the incidence of HPV-positive HNSCC and the high global prevalence of CESC, only 17 HPV-positive cell lines are widely used in research (9 HNSCC and 8 CESC cell lines). We characterized these cell lines and, for comparison, 2 commonly used HPV-negative CESC cell lines and 55 HPV-negative HNSCC cell lines, for a total of 74 cell lines . Like thTP53 mutations were detected in 98% of the HPV-negative HNSCC cell lines and 82% of the 431 HPV-negative HNSCC tumors from TCGA. In contrast, TP53 mutations were far less common (5%) in the 194 TCGA CESC tumors, which are predominantly HPV-positive and TP53 was mutated in only the 2 HPV-negative CESC cell lines [TP53 mutation, as previously reported [KMT2D, which encodes the protein lysine methyltransferase 2D and was mutated in 31% of the cell lines – predominantly in the HPV negative lines (39%). KMT2D was also mutated in tumors, but at a lower frequency (12–16%). The most frequently mutated genes in HPV-positive cell lines were NOTCH1, EP300, and CASP8 (24%), which were also mutated in 7, 11, and 0% of HPV-positive HNSCC and 6, 10, and 5% of CESC tumors from TCGA respectively. In contrast to HNSCC tumors, no HPV-positive HNSCC cell lines had PIK3CA mutations, although 2 (25%) HPV-positive CESC cell lines did. CDKN2A (9%), FAT1 (23%), SMAD4 (11%), and CASP8 (13%) mutations were only present in HPV-negative HNSCC cell lines, which was consistent with the HNSCC TCGA data, where each of these mutations occurred in only 1 HPV-positive HNSCC patient tumor. NOTCH1 mutations were present in 15 (28%) HPV-negative HNSCC cell lines, 2 (22%) HPV-positive HNSCC lines, and 2 (25%) HPV-positive CESC cell lines.Whole exome sequence analysis revealed distinct genetic mutations in HPV-positive and HPV-negative cell lines Figure . TP53 mull lines . Only 1 reported . The secThe roles of HPV oncoproteins E6 and E7 that promote apoptosis and cell cycle progression by respectively targeting p53 and Rb proteins for degradation are well established , 20. To We used transcriptome analysis (RNASeq) to identify the HPV genes expressed -2 and inWe investigated HPV integration in the cell lines and patient tumors from the TCGA using whole exome sequencing data. Similar to several previous reports summarizing studies of HPV integration sites, we confirmed HPV integration sites in HeLa, SiHa, CaSki, UPCISCC090, 93VU147T, HMS001, UDSCC2, and UMSCC47 cell lines by using RNASeq , 27. FurKLF12 (n = 15), MYC (n = 7), POU5F1B (n = 7), and TP63 (n = 6); a candidate oncogene, PVT-1 (n = 11); a DNA repair protein, RAD51B (n = 7); and the receptor tyrosine kinase ERBB2 (n = 6) (Table PD-L1) (n = 3) , POU5F1B (HeLa cells), and TP63 (UMSCC47 cells).Most of the observed HPV integration sites in the HNSCC and CESC cell lines were not recurrent, as they were identified in only 1 cell line Figure . Cell li) Figure . The recFOXE1 in UPCISCC090 and UPCISCC152 cell lines and of SLC47A2 in UMSCC104 cells [NR1P1, a nuclear receptor protein, and USP25, a ubiquitin-specific peptidase, in UPSCISCC154 cells  varied significantly between tumors from the TCGA. Although more than 3 decades of research on HPV-associated cancers has solidified the importance of viral oncogenes E6 and E7 , 34, thein vivo , 36. In in vivo –39 whichOne limitation of our study is that we identified HPV integration sites using whole exome sequencing, which is limited to exomes and prevents the detection of HPV integration events that do not occur in protein-coding regions of the genome. Whole genome sequencing may have identified additional sites of integration but was not performed because of its cost. Another limitation was the small number of HPV-positive cell lines that were available for study. The large disparity between the number of available HPV-positive and HPV-negative cell lines makes it difficult to perform statistical analyses that may reveal differences in gene and protein expression levels. Another limitation is a lack of HPV-positive oropharynx cell lines.In summary, in this panel of 74 human HNSCC and CESC cell lines, the frequency and patterns of mutations resembled those found in human tumors. In the HPV-positive cell lines, viral gene expression and integration largely mirrored that found in human tumors. These results suggest that these widely used HNSCC and CESC cell lines are suitable models for studying HNSCC and CESC and may be useful in research that could lead to new therapies while emphasizing the need for the development of more HPV-positive models. Our analyses and characterization of these cell lines will serve as a valuable resource for the cancer research community.A panel of 74 HNSCC and CESC cell lines  were maiGrowth curve analyses were performed on cells prior to the tenth passage after thawing. The cells were passaged during log phase growth before they reached confluence. Cells were trypsinized with 0.25% trypsin/ethylenediaminetetraacetic acid and allowed to detach for 2 to 3 minutes at 37°C. Following trypsin inactivation with serum-containing media, the cells were counted and serially diluted from 2500 cells/mL to 40,000 cells/mL. The cells were then seeded in a 384-well plate (50 μL/well and 36 wells per dilution). The plated cells were allowed to attach at room temperature for 45 minutes and then placed in the cell culture incubator overnight. Each day for 4 days, 7 wells from each cell dilution were fixed, stained with 4′,6-diamidino-2-phenylindole, and counted. The doubling times were calculated using the formula For each cell line, genomic DNA was extracted from 1 to 2 million cells using the ArchivePure DNA cell/tissue kit  following the manufacturer’s instructions. The extracted DNA was stored in nuclease-free water . For each cell line, RNA was isolated from 5 million cells using the RNeasy Plus Kit  according to the manufacturer’s protocol and eluted into ribonuclease-free water.cDNA was synthesized from 1 μg of RNA using the iScript cDNA Synthesis Kit  according to the manufacturer’s protocol. The synthesized cDNA was used as a template to determine the HPV E6 and E7 gene expression levels for HPV types 16, 18, 33, 45, and 68. To determine relative HPV viral gene expression levels, genomic DNA was isolated, and HPV E6, E7, and GAPDH primers were used for real-time, quantitative PCR . Each 206/mL in 10-cm dishes. The following day, cells were harvested and lysed using cell lysis buffer  supplemented with a protease inhibitor cocktail. Cell lysates were incubated for 15 minutes on ice and then centrifuged for 5 minutes at 14,000 rpm. The collected supernatants were stored at −80°C. Protein concentrations were determined using a bicinchoninic acid assay . Ten micrograms of total protein was separated by sodium dodecyl sulfate polyacrylamide gel electrophoresis, transferred onto a nitrocellulose membrane, and detected using ECL detection reagents . The nitrocellulose membranes were blocked for 1 hour using blocking buffer . The cells were incubated with anti-HPV16 E7  (1:500) overnight at 4°C. Protein expression was normalized using β-actin .Cells were seeded at a density of 0.5 × 10RNA was isolated from the cell lines using the RNeasy Plus kit (Qiagen). Illumina-compatible libraries were prepared using a TruSeq Stranded Total RNA Sample Prep Kit . Briefly, 500 ng of DNase I-treated total RNA was depleted of ribosomal RNA using biotinylated, target-specific oligos. Following purification, the RNA was fragmented using divalent cations, and first-strand cDNA synthesis was carried out using random primers. Following second-strand synthesis, the ends of the resulting double-stranded cDNA fragments were repaired, 5′-phosphorylated, and 3′-A tailed. Illumina-specific Y-shaped indexed adapters were ligated. The products were then purified and enriched using PCR to create the final cDNA library. The libraries were quantified using qPCR , assessed for size distribution using an Agilent Bioanalyzer , and then multiplexed and sequenced on an Illumina HiSeq3000 sequencer using the 75-bp paired-end format. After sequencing, BCL files were converted to “.Fastq.gz” files, and individual sample libraries were de-multiplexed using CASAVA 1.8.2 software (Illumina) with no mismatches.NimbleGen SeqCap EZ libraries  were prepared per the manufacturer’s protocol. Briefly, indexed libraries were prepared from 0.5–1.0 μg of sheared and RNase-treated genomic DNA using the KAPA HTP Library Preparation Kit (Kapa Biosystems). The indexed libraries were amplified by 7 cycles of ligation-mediated PCR. Following amplification and reaction cleanup using Agencourt AMpure XP beads , the libraries were quantified fluorometrically using the Qubit dsDNA HS Assay  and assessed for size distribution using the Fragment Analyzer . Library concentrations were normalized, and the libraries were pooled at 250 ng/library with 4 to 6 libraries/pool. Each multiplexed library pool was hybridized to a probe pool from the SeqCap EZ Human Exome Enrichment Kit v3.0 (Roche-NimbleGen). Following capture, the exome-enriched libraries were amplified using 6 cycles of PCR and then purified using Agencourt AMpure XP beads. The libraries were then quantified fluorometrically using the Qubit dsDNA HS Assay and assessed for size distribution using the Fragment Analyzer. Exome enrichment efficiency was determined using qPCR. Sequencing was performed on a HiSeq4000 Sequencer (Illumina) using the 75-nt paired-end format, with 1 pool (4–6 libraries) sequenced per lane. Following sequencing, BCL files were converted to “.Fastq.” files, and individual sample libraries were de-multiplexed using bcl2fastq2 conversion software version 2.17.1.14 (Illumina).http://broadinstitute.github.io/picard/). Then, the Genome Analysis Toolkit indel realignment, base quality score recalibration, and SNP and INDEL discovery tools were applied for variant calling [The paired-end reads were aligned to human reference genome hg19 using BWA . SAMtool calling –51. The  calling .To account for the lack of matched normal DNA for established cancer cell lines, we employed several levels of variant filtering, as previously reported, to perform somatic mutation calls , 53. TheCell lysates were serially diluted twofold for 5 dilutions (from undiluted to 1:16 dilution) and arrayed on nitrocellulose-coated slides in an 11 × 11 format, as we described previously , 57. We http://gib-v.genes.nig.ac.jp/). Next, the paired-end reads of the samples were aligned against hg19 for human sequence subtraction using the MOSAIK algorithm [For HPV detection and integration analysis, we applied the VirusSeq pipeline previously developed in the Department of Bioinformatics and Computational Biology at The University of Texas MD Anderson Cancer Center . The HPVlgorithm , 60. UnmTo detect HPV integration, the reference genome and annotation files were prepared. The reference genome was a hybrid genome that combined the human hg19 and selected virus genomes containing different types of HPV and other viruses. Paired-end reads were aligned against the hybrid genome, hg19Virus, using MOSAIK to generate files containing all of the discordant reads for each chromosome. The read pair was reported as discordant if the paired-end reads were uniquely mapped with one end to a human chromosome and the other to the virus chromosome. Next, the first mate and the second mate of the paired-end reads were separately aligned against the hybrid hg19Virus genome in order to generate the genomic location for each uniquely mapped read, including information on readID, read sequences, and read mapping orientation. This information was then used for annotating the discordant reads generated previously. A curated refFlat file was used to annotate the discordant reads with human and virus genes. Finally, HPV integration sites were identified using VirusSeq and reported if there were at least 4 supporting discordant read pairs.https://portal.gdc.cancer.gov/). HPV calls were made as described above and demonstrated 100% concordance with previously published calls [http://firebrowse.org/) [TCGA RNA sequencing files were downloaded from the NCI Genomic Data Commons  , 62.https://pave.niaid.nih.gov/). The read counts for HPV genes were counted using a Python script developed in house. The reads per kilonucleotide per million-read (rpkm) values were calculated by dividing the read count by the total number of reads in millions and the gene length in kilonucleotides.To compare global gene expression patterns in HNSCC and CESC cell lines, we performed unsupervised clustering in an unbiased manner using Pearson correlation metrics with Ward’s linkage of the 5000 most variable genes, measured by median absolute deviation, in the 74 cell lines. RNAseq reads were first mapped to human genome hg19 using Tophat/2.0.13 . The rea