NF2-driven tumorigenesis based on known effects of the absence of merlin, the product of the NF2 gene. We tested priority compounds based on known biology with traditional dose-concentration studies in meningioma and schwann cell systems. Concurrently, we studied functional kinome and gene expression in these cells pre- and post-treatment to determine merlin deficient molecular phenotypes. Cell viability results showed that three agents  had the greatest activity across schwannoma and meningioma cell systems, but merlin status did not significantly influence response. In vivo, drug effect was tumor specific with meningioma, but not schwannoma, showing response to GSK2126458 and Panobinostat. In culture, changes in both the transcriptome and kinome in response to treatment clustered predominantly based on tumor type. However, there were differences in both gene expression and functional kinome at baseline between meningioma and schwannoma cell systems that may form the basis for future selective therapies. This work has created an openly accessible resource (www.synapse.org/SynodosNF2) of fully characterized isogenic schwannoma and meningioma cell systems as well as a rich data source of kinome and transcriptome data from these assay systems before and after treatment that enables single and combination drug discovery based on molecular phenotype.Neurofibromatosis 2 (NF2) is a rare tumor suppressor syndrome that manifests with multiple schwannomas and meningiomas. There are no effective drug therapies for these benign tumors and conventional therapies have limited efficacy. Various model systems have been created and several drug targets have been implicated in  NF2 mutations [Neurofibromatosis 2 (NF2) is a rare neurogenetic disorder  that is characterized by multiple schwannomas and meningiomas [utations . In mostutations –7. Hencein vitro and in vivo assay model systems based on hypotheses about tumor pathogenesis [NF2 gene on chromosome 22q, followed by somatic inactivation of the remaining copy of NF2 (either by mutation or loss of a large section of the surrounding chromosome). Merlin is the NF2 tumor suppressor protein, and loss of merlin function results in dysregulation of multiple aspects of cellular behavior [NF2/Nf2 mutant in vivo and in vitro model systems [NF2 mutant tumors include: variable metrics of efficacy applied across individual laboratories and systems, limited focus on drug targets implicated by merlin loss, and histologically specific drug assessment (meningioma versus schwannoma) rather than assessment of the effect of the underlying NF2 mutation on drug response. To address these limitations a multi-disciplinary team created a panel of in vitro assay systems  to perform traditional drug screening studies in a systematic fashion with an initial set of drugs chosen for their potential relevance to NF2 biology.A conventional approach to developing drug therapies for tumors is for individual laboratories to test new or repurposed drugs in various ogenesis . NF2-assbehavior . This kn systems –20. ThesNF2 driven tumors.Simultaneously, we performed an integrated analysis of transcriptome and kinome data across these cell culture systems at baseline and after treatment to discover tumor, species and merlin specific therapeutic targets, identify differential responses to treatment, and potentially identify mechanisms of acquired resistance. The goal was to compare drug efficacy readouts with traditional drug discovery approaches versus systems biology approaches via systematic drug assays in fully characterized isogenic pairs of schwannoma and meningioma model systems . The ultWe assembled a panel of tumor-relevant cells  confirmed to have suppressed or inactivated merlin and, whenever possible, their merlin-wildtype control .NF2 inactivation , along with the immortalized merlin-deficient benign meningioma (MN) line Ben-Men-1 (Syn6) [To represent the biology of meningiomas we assembled a primary screening cohort of 12 human cell lines, either merlin-wildtype or merlin-null. These included 5 isogenic clonally-derived arachnoidal cell (AC-CRISPR) lines , of whicNF2-shRNA suppressed with ~3% merlin protein expression by Western blotting and ~7% RNA expression by RNA sequencing versus wild-type) as well as a series of four mouse merlin-wildtype and -deficient SC and a merlin-deficient schwannoma lineS [NF2 or Nf2 inactivation, respectively, failed to exhibit merlin protein  lines,  and  biological activity in clinical trials in NF2 patients, (2) activity against targets in key pathways regulated by merlin, (3) FDA-approved or in the late stages of clinical development .All 19 compounds were assessed in AC/MN and SC/schwannoma lines simultaneously. Dose response curves (DRCs) were generated for all meningioma-relevant (Syn1–Syn12) and schwannoma-relevant  cell lines using the CellTiter-Glo or CellTiter-Fluor viability assay (Promega), respectively. For AC/MN cells, there were two stages of screening. In the first stage, CellTiter-Glo was assessed at 72 hours of treatment using 5 dilution points  of each drug, ranging from 0.04 μM to 25 μM. Based upon DRCs generated for each cell line and compound, 8 of the 19 compounds were eliminated due to minimal or no effect, even at the highest concentrations. For the remaining 11 compounds, drug treatment was expanded to a second stage. In the second stage, immortalized AC-CRISPR and Ben-Men-1 lines (Syn1-Syn6) as well as three primary MN lines  were evaluated by generating DRCs using 10 dilution points  of each drug ranging from 12.8 pM to 25 μM . Four drFor the human SC panel, cell viability was assessed with CellTiter-Fluor at 48 hours with increasing concentrations at half-log concentrations, ranging from 0.001 μM to 10 μM. Five drugs, including Panobinostat, GSK2126458, CUDC-907, Bortezomib and Ganetespib, revealed IG50 <500 nM with a maximum response > 50% inhibition in merlin-deficient HS01 , S2B Figin vitro with the goal of selecting drugs that had the highest likelihood of efficacy against both tumor types in vivo resulted in three compounds being selected to be advanced to in vivo testing: CUDC-907 , Panobinostat (HDAC inhibitor), and GSK2126458 .Comprehensive evaluation of the compounds’ performance across both AC/MN and SC/schwannoma assay systems F-test (testing the null hypothesis the β coefficient is zero). Among these three covariates, tumor type showed the greatest correlation with drug efficacy as measured by area under the curve (AUC) of each drug’s dose response curves  and cranial nerves [PostnCre; Nf2floxflox mice had comparable disrupted architecture consistent with schwannoma irrespective of treatment  model of NF2, l nerves . Each drl nerves –46. GSK2reatment . Finallyreatment .in vitro and in vivo as well as to explore the potential for drug discovery driven by molecular and protein characterization via global gene expression and kinome analysis. We hypothesized that the latter might reveal molecular differences that could point to specific therapeutic targets not previously apparent with toxicity specific to merlin-deficient cells. Accordingly, the most reliable and reproducible lines from the meningioma and schwannoma assay systems were selected for transcriptome and kinome analysis. The seven meningioma-relevant and schwannoma-relevant cell lines were treated for 24 hours either with DMSO alone or with the doses of GSK2126458, Panobinostat, CUDC-907 chosen as described in Materials and Methods . Principal components analysis (PCA) of rank-normalized gene counts indicated that the three models  showed substantial transcriptional differences between species and tumor type ; concordPathway analysis of gene ontology (GO) terms  with thehttp://dgidb.genome.wustl.edu/)   and manyunitinib ,53, amonDespite these substantial differences between the transcriptomes of merlin-deficient and merlin-wildtype cells, the three drugs that were chosen from our cellular screening for further testing produced no significant differential effect in our cell viability assays, suggesting that they do not target processes that are preferentially important to viability of merlin-deficient cells. However, they did elicit extensive changes in gene expression in the human cell lines , with soTo understand dynamic changes in the functional kinome, we employed multiplexed Type I kinase inhibitor bead (MIB)/mass spectrometry (MS) kinome profiling. MIBs have preferential affinity for the activated form of kinases, and MIB-binding is dependent on affinity, expression, and activation state of the kinase ,55. GravA comparison of the MIB/MS kinome profiles of merlin wild-type and deficient cells identified several differentially expressed and activated kinases associated with loss of merlin . Among tIn addition to human models, MIB/MS kinome profiles were obtained for a single run of the merlin-deficient (MS03) and merlin-wildtype (MS12) mouse SC lines . Consiststring-db.org) for potential subnetworks that were selectively induced in the merlin-deficient cell lines.We next compared perturbations to the kinome in the meningioma and schwannoma cell systems after treatment with CUDC-907, GSK2126458, Panobinostat, or vehicle. To analyze the effect of all three drugs on the kinome of all three cell line pairs, we also queried a protein interaction database  exhibited dramatic MIB binding loss in all cell lines tested . Dual inFollowing our assessment of the predominant drug-specific kinome responses, we examined the specific kinome response in the merlin-deficient AC and SC  versus tOverall, HDAC inhibitors generated the largest fold-changes in MIB-binding and at 24 hours clustered separately from GSK458-mediated responses . The HDAAs several nodes common to the human merlin-deficient models and the three drugs tested were identified, it is possible that cells lacking merlin have a similar kinomic response to treatment with these three drugs. Shown in a kinome tree plot, similarities between CUDC-907-induced and Panobinostat-induced changes were evident . In response to treatment with GSK2126458, CUDC-907 and Panobinostat, both human and mouse merlin-deficient SC cells had increased PTK2B levels when compared to wild-type control cells . The difTo assess the relationship between transcriptome and kinome changes, we performed an integrated analysis of these two datasets at baseline and after CUDC-907, Panobinostat and GSK2126458 treatment of the meningioma- and schwannoma-relevant cell models. In particular, we focused on a comparison between merlin-deficient cells and merlin-wildtype cells for kinases showing a log2 difference of greater than 0.5 or less than -0.5 in the kinome, and/or greater than 1 or less than -1 in the transcriptome (labeled in per se (as presented for merlin-deficient cells in EPHB1 gene expression (<-1 LogFC) in Syn5 compared to Syn1. A number of kinases displayed relatively higher activity in the absence of relative differences beyond the threshold for mRNA levels . Overall, the integrated analysis suggests that the kinome and transcriptome measures provide somewhat different windows on the response of cells to drug treatment and that both together and separately, they can reveal cell type and genotype (merlin status) differences that can provide additional targets for single or combination drug treatment.We also studied the correlation of merlin-dependent changes in the kinome and transcriptome of AC and SC due to drug treatment , right. NF2 driven schwannomas and meningiomas. However, despite priming the pipeline with 19 drugs chosen for potential relevance to NF2 biology, we observed relatively little difference overall in the sensitivity of merlin-wildtype cells compared with merlin-deficient cells. Instead, the strongest influences on drug efficacy were cell type (AC vs. SC), followed by species of origin (human vs. mouse).Schwannomas and meningiomas are the most common brain tumors in humans world-wide and despThese are important findings that would not have been possible without assembling a robust, isogenically matched panel of cell lines for the tumors and mutation of interest. The lack of differential drug activity relative to merlin status underscores the inherent difficulty of choosing candidates for testing based upon phenotypic measures alone. While tumor formation is initiated by loss of merlin, many of the consequent characteristics and altered pathways observed in tumors and tumor cells may not be essential for their propagation and therefore may not be useful targets for genotype-specific therapeutic development. An assessment of such features is particularly difficult in primary tumor specimens where a truly comparable normal tissue sample is usually lacking. By establishing a cell-based system with genetically-matched merlin-expressing and merlin-deficient cells representing the cellular targets of the two major tumor types in NF2 patients, we provide the capacity to go beyond the phenotypic candidate approach to strategies informed by genotype-dependent systems analyses or to larger, mechanism-agnostic drug screens.NF2 driven tumors.The cell type and species differences seen in the drug screen were reinforced with the transcriptome and kinome analyses of isogenic pairs of merlin-deficient and merlin-wildtype cells. In the transcriptome studies, the absence of merlin resulted in global differences in gene expression in SC and AC versus their wild-type counterparts. In both human and mouse SC pairs and in the human AC pair, the gene expression changes indicated that loss of merlin function disrupts processes related to the plasma membrane and extracellular region/space. However, the actual genes dysregulated were largely non-overlapping, suggesting that the loss of functional merlin affects shared processes in different ways, in different cell types. This is an important, yet subtle, discovery that will inform drug development strategy for Principal components analysis of the global gene expression data emphasized that cell type and species differences outweigh the effects of merlin deficiency. Similarly, kinome analysis revealed the activation of different kinases in human AC compared to human SC. Taken together, these data suggest that while schwannomas and meningiomas are both initiated by merlin loss, distinctly different responses to that loss likely dictate tumor propagation. Clinically, this means that a single drug is unlikely to be optimally effective in both cell types. Further, when selecting a drug for one tumor type, caution will be required about potential transcriptome and kinome effects on the other tumor type.in vivo testing based on traditional markers of activity in vitro across all cell lines. We saw activity, notably for GSK2126458 and Panobinostat, in the meningioma in vivo model, but none of the three agents was active in vivo in the GEM schwannoma model. The difference in vitro versus in vivo activity for schwannoma may be due to contributions from the microenvironment that are not addressed in either the in vitro schwannoma systems or in the allograft meningioma system [in vivo. The lack of strong selective toxicity against merlin-deficient cells with the initial 19 drug candidates screened likely indicates that they all target processes whose role in determining viability in vitro is not dependent on merlin, although it cannot be excluded that a role for merlin activity in determining viability in a system more faithful to the 3D in vivo environment might reveal selectivity for one or more of these compounds.In the absence of strong selective toxicity to merlin deficient cells for the 19 drugs tested, we chose three, CUDC-907 , Panobinostat (HDAC inhibitor), and GSK2126458  for a system . It alsoNF2-null human AC and MN cell lines in this study a therapeutic trial was undertaken in vitro and in vivo that indeed showed synergy between dasatinib and a dual mTORC inhibitor that was predicted by kinome results[Developing advanced assays and screening a much larger panel of chemical compounds are two potential approaches to achieving selective toxicity for the merlin-deficient tumor cells while sparing their wild-type counterparts. Indeed, we would have altered the drug panel screened if had baseline transcriptome and kinome data before starting the drug screen. For example, the emergence of increased activity of ephrin receptor kinases in merlin-deficient cells would have prompted the addition of Dasatinib to the screen and increased CAMK4 in human merlin-deficient SC would have suggest the drug KN-93 ,60. In fe results. There aPerhaps the most important outcome of this work was the validation of diverse cell lines with isogenic pairs allowing the generation of transcriptome and kinome data at baseline and in response to drug. This is a rich data source to mine to identify combination therapies that influence transcriptome or kinome; potentially engaging merlin deficiency in determining viability. Combination therapy guided by such molecular data may reveal circumstances in which response to a single agent in merlin-deficient cells creates a vulnerability to be exploited by a second agent, achieving selective toxicity. Future work may use the differences between merlin-wildtype and merlin-deficient cells in their molecular response to CUDC-907, Panobinostat, and GSK2126458, to identify potential agents that will be additive or synergistic. For example, the AMP-activated protein kinase NUAK1 (inhibitor: WZ4003)  was seleNF2 mutation and the absence of merlin influence tumor cell behaviour in both meningiomas and schwannomas and succeeded in: (1) creating a new pipeline of well-validated cell lines for NF2-associated drug discovery with fully characterized isogenic pairs of meningioma and schwannoma cell systems; (2) gaining conceptual insights into disease mechanisms via transcriptome and kinome interrogation that indicate that different drugs are likely to be needed to treat meningioma and schwannoma; (3) validating pathways and targets that are altered based on tumor type  and in response to targeted pathway inhibition in the setting of NF2; and 4) building an openly accessible (www.synapse.org/SynodosNF2) database for community sharing and mining of drug treatment, transcriptome and kinome data from isogenic schwannoma and meningioma cell systems. These data already present several targets to consider for single agent and combination therapy in the short term and provide a deep and rich open access data resource for the broader research community seeking treatments for NF2 associated meningioma and schwannoma for the long term.The ongoing efforts of the Synodos for NF2 Consortium have already filled a critical gap of understanding of how the Detailed materials and methods can be found in S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table2) and the total number of data points in the model (Observations) are also shown.Multiple linear modeling was used to test the association of each assay variable with differences in area under the curve (Simpson AUC). This table shows the effect of each variable on the AUC as determined by the model , the 95% confidence interval (CI) for the beta coefficient, and calculated significance (p) for the beta coefficient. Only drugs common to both cell types were included in the analysis. The fraction of observations that are explained by the model (R(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 TableTranscriptomic differences in isogenic pairs of untreated and drug-treated merlin -deficient and merlin-wildtype human arachnoidal cells and Schwann cells (A) and mouse Schwann cells (B)(XLSX)Click here for additional data file.S6 Table(XLSX)Click here for additional data file.S7 Table(XLSX)Click here for additional data file.S8 Table(XLSX)Click here for additional data file.S9 Table(XLSX)Click here for additional data file.S1 Fig(A) Immunoblotting of isogenic immortalized AC-CRISPR clones (iACs) using the N-terminal anti-MERM antibody N21 (raised to a common epitope shared between merlin and other ERM protein family members) shows loss of merlin in Syn3-5 compared to merlin-wildtype Syn2, with intact expression of other ERM family members. )(B Immunoblotting of representative panels of iACs (AC-CRISPR clones Syn1-5), immortalized MN , and primary MN cell lines  show merlin-deficient (-) compared to merlin-wildtype (+) Syn1 and Syn2 lines. Loading controls included housekeeping proteins ribosomal S6 subunit (left and center panel) and GAPDH (right panel). (C) Representative merlin Western blots of whole cell extracts from primary mouse Schwann cells MS11 (WT) and merlin-deficient  MS01, MS02 lines, isogenic MS12 (WT) and MS03 (MD), and isogenic HS11 (WT) and HS01 (MD). β-actin was immunoblotted as a loading control. (D) Confocal images of mouse Schwann /schwannoma cell lines MS11, MS01, MS02, MS12 and MS03 showing the SC marker S-100 (green). Human Schwann cell lines HS11 and HS01 displaying S-100 (green) and human nuclear antigen . DAPI stained nuclear DNA (blue), and F-actin  is also shown. Scale bar: 50 μm.(TIF)Click here for additional data file.S2 Fig(A) Human arachnoidal and meningioma cells. CellTiter-Glo was assessed at 72 hours of drug treatment (B) Human Schwann cells. CellTiter-Fluor was assessed at 48 hours of drug treatment with increasing concentration at half-log concentrations, ranging from 0.001 μM to 10 μM.(TIF)Click here for additional data file.S3 FigCellTiter-Fluor was assessed at 48 hours of drug treatment with increasing concentration at half-log concentrations, ranging from 0.001 μM to 10 μM.(TIF)Click here for additional data file.S4 Fig(A) Acetylated histone lysine was evaluated in Syn6 tumors as a readout of HDAC inhibition. (B) pAKT(Thr308 and Ser473) and pS6(S235/236) reduction demonstrate AKT pathway inhibition in Syn6 tumors after treatment with all three drugs. (C) pS6(S235/236) and (D) Ki67 was reduced in Syn6 tumors after treatment with GSK2126458, Panobinostat, and CUDC-907, while (E) pFAK (Tyr397) was increased.(TIF)Click here for additional data file.S5 Fig(A) Plotting of transcript reads against the exon structure of NF2 demonstrates the complete skipping of the CRISPR/Cas9-targeted exon 8 and presence of a novel antisense RNA in Syn5 compared with Syn1. (B)Nf2 transcripts show complete skipping of exon 2, a floxed exon removed by Cre recombinase, in MS03 compared with MS12.(TIF)Click here for additional data file.S6 Fig(A) Volcano plots showing the significance and log2 fold-change (logFC) for all gene transcripts reliably detected in the RNA-seq analysis after treatment of Syn5 or HS01 with the noted drug, in comparison with exposure to the DMSO vehicle. Yellow dots represent genes altered at BH adjusted significance P<0.05.(B) Venn diagrams showing the overlap between the genes downregulated (left) and upregulated (right) due to the above drug treatments.(TIF)Click here for additional data file.S7 Fig(TIF)Click here for additional data file.S8 FigTop kinome changes in merlin deficient human AC (Syn5) and SC (HS01) treated with CUDC-907, Panobinostat or GSK2126458. Data presented are the median log2 fold change from 3 experiments, error bars are standard error.(TIF)Click here for additional data file.S9 Fig(A) and mouse (MS12 and MS03) (B) merlin-deficient SCs compared to wild-type control. Membranes were treated with merlin and PYK2 antibodies as indicated. 25 μg of lysates were used and equal loading was controlled by Ponceau S staining. These immunoblots are representative of three independent experiments.Both merlin-deficient mouse and human Schwann cells (SCs) increase PYK2 levels in response to DMSO, CUDC-907, Panobinostat and GSK2126458. Immunoblot analysis of human (HS11 and HS01) (TIF)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.S2 Text(DOCX)Click here for additional data file.S3 Text(DOCX)Click here for additional data file.S4 Text(DOCX)Click here for additional data file.S5 Text(DOCX)Click here for additional data file.


RBM10 is an RNA binding protein involved in message stabilization and alternative splicing regulation. The objective of the research described herein was to identify novel targets of RBM10-regulated splicing. To accomplish this, we downregulated RBM10 in human cell lines, using small interfering RNAs, then monitored alternative splicing, using a reverse transcription-PCR screening platform.RAS signaling to be most affected by RBM10 KD. Of particular interest was the finding that splicing of SMN pre-mRNA, encoding the survival of motor neuron (SMN) protein, was influenced by RBM10 KD. Inhibition of RBM10 resulted in preferential expression of the full-length, exon 7 retaining, SMN transcript in four cancer cell lines and one normal skin fibroblast cell line. SMN protein is expressed from two genes, SMN1 and SMN2, but the SMN1 gene is homozygously disrupted in people with spinal muscular atrophy; as a consequence, all of the SMN that is expressed in people with this disease is from the SMN2 gene. Expression analyses using primary fibroblasts from control, carrier and spinal muscle atrophy donors demonstrated that RBM10 KD resulted in preferential expression of the full-length, exon 7 retaining, SMN2 transcript. At the protein level, upregulation of the full-length SMN2 was also observed. Re-expression of RBM10, in a stable RBM10 KD cancer cell line, correlated with a reversion of the KD effect, demonstrating specificity.RBM10 knockdown (KD) provoked alterations in splicing events in 10–20% of the pre-mRNAs, most of which had not been previously identified as RBM10 targets. Hierarchical clustering of the genes affected by RBM10 KD revealed good conservation of alternative exon inclusion or exclusion across cell lines. Pathway annotation showed SMN2 alternative inclusion.Our work has not only expanded the number of pre-mRNA targets for RBM10, but identified RBM10 as a novel regulator of The online version of this article (doi:10.1186/s12867-017-0096-x) contains supplementary material, which is available to authorized users. We addeWe initially examined predominantly cancer-associated genes known to have ASEs that change between normal and cancer tissues. This initial screen consisted of 96 ASEs from 92 genes (see below for link to data with list of genes). RNA from five cancer cell lines  was used. Representative electropherogram data, from the capillary electrophoresis of specific ASEs in individual cell lines with one siRNA, can be seen in Fig. http://rnomics.med.usherbrooke.ca/palace?purl=data/related/1811)  being changed in ≥3/5 cell lines  demonstrated that 28/96 ASEs (29%) were changed in one or more cell line(s)  only SRP19 did not involve exon inclusion in the KD. Refer to Fig. Almost 68% 19/28) of the changes occurring in one or more cell line(s) involved exon inclusion in the RBM10 KD, while within the cluster of changes common to three or more cell lines  experienced more changes than either of the two breast cancer (MCF-7 and MDA-MB-231) or one prostate cancer (PC-3) cell lines . When we applied unsupervised hierarchical clustering analysis to look for patterns in cell line association, however, while the data showed a good separation of the 28 changes into two major clusters—those consistently experiencing preferential exon exclusion associated with RBM10 KD, and those consistently experiencing preferential exon inclusion associated with RBM10 KD, there was no clustering of changes to either ovarian cancers or breast cancers . These units corresponded to a selection of the best events from previous RT-PCR screenings in 10 different cell lines that displayed good yield and reproducibility , with 8.C5orf5/FAM13B, SIAHBP1 and SMN2) occurred in all five cell lines. Refer to Fig. As shown in Fig. KIF9, LOC219854/TMEM218 and RNF135) showed a shift in the BJT cells opposite to that which occurred in the cancer cells; however, in each of the three instances, preferential exon exclusion was seen in the cancer cells, but preferential exon inclusion in the BJT cells. Unfortunately, whether or not these differences relate to non-cancer versus cancer, skin versus other tissue type, or fibroblast versus epithelial cell, cannot be determined from the limited number of cell lines examined. The fact that as many changes occurred in the non-cancer cell line (24) as some of the cancer cell lines, e.g., MCF-7 (19), MDA-MB-231 (20) and PC3 (30), did demonstrate, however, that the regulatory effect of RBM10 on alternative splicing was not restricted to cancer cells.Hierarchical clustering analysis Fig.  revealedFor a previous study, we had generated a stable RBM10 KD MCF-7 human breast cancer subline . We deciSIAHBP1/PUF60, SMN2, KIAA1191, POAX and SMPD4), we demonstrated that the alternative splicing changes that occurred in the transient RBM10 KD cells also occurred in the stable RBM10 KD MCF-7 cells  is the ligand for the tyrosine kinase receptor c-KIT, involved in growth and development, particularly of haematopoietic and germ cells [KITLG transcript encodes a precursor transmembrane form of the protein, which can be proteolytically cleaved within the exon 6-encoded region to produce a secreted KITLG isoform [KITLG exon 6 alternative splicing was investigated in five cancer cell lines. In two breast and one of two ovarian cancer cell lines having RBM10 KD, KITLG exon 6 was preferentially included, with normal RBM10 levels associated with exon 6 exclusion. Our findings suggest that, since RBM10 levels are increased in many cancers, RBM10 may be a potential therapeutic target for those cancers harbouring elevated KITLG .RBM10 expression is most frequently associated with exon exclusion [RBM10 expression and SIAHBP1/PUF60 exon 5 exclusion [DLG4 exon 18 alternative splicing, which itself regulates synaptogenesis [PUF60 exon 5 exclusion, preferential DLG4 exon 18 exclusion and synaptic repression [RBM10 RNA binding motif, identified in a previous study [DLG4 exon 18, but does occur in PUF60 exon 5, suggesting that the regulation of DLG4 splicing by RBM10 may be an indirect effect that is mediated by the splicing factor PUF60 [Secondly, our work supports previous findings that xclusion , 3, 6. Nus study , occurs or PUF60 .RBM10 expression levels impact both cancer-associated and non-cancer-associated genes. We found that the most significantly affected signaling pathway resulting from RBM10 inhibition was the RAS signaling pathway, which is involved in the regulation of cell growth, differentiation and survival in all cell types. RAS proteins are small GTPases that transmit signals throughout the cell, turning on many genes involved in a range of processes. The five RAS pathway associated genes, from Arrays-96 and -191, that were affected by RBM10 inhibition, were a non-receptor tyrosine kinase (ABL2), a tyrosine kinase ligand (KITLG), a G-protein subunit (GNB3), a growth factor receptor (FGFR4) and a phospholipase (PLD1). Interestingly, recent work [RAS signaling associated protein FilGAP, a RAC-specific GTPase activating protein that regulates cell adhesion and migration. Our work therefore supports a potentially fundamental role for RBM10 in signal transduction regulation.Thirdly, our work confirms that changes in ent work  showed tSMN transcript. SMN codes for survival of motor neuron (SMN), a protein that is integral to the function of spinal motor neurons [SMN1, since a single nucleotide transition in the SMN2 gene exon 7 results in exclusion of exon 7 in the majority of expressed RNA, the production of a truncated protein (SMNΔ7), and only a small amount of SMNFL produced from that locus. As a consequence, in individuals who have loss of SMN1 function , SMNFL encoded by SMN2 cannot entirely compensate. Reduced SMNFL leads to a progressive degeneration of motor neurons, spinal muscular atrophy and eventual pulmonary failure [FL produced (related to SMN2 gene copy number), the more severe the disease [SMN2 exon 7 alternative splicing include hnRNP G, hnRNP M, hnRNP Q, PSF, Sam68, SRSF1, SRSF9 and TRA2β [SMN pre-mRNA was not found using PAR-CLIP in HEK293 cells [SMN alternative splicing might be indirect. As suggested for the regulation of DLG4 alternative splicing (mentioned above), RBM10 associated regulation of SMN2 alternative splicing may occur through PUF60, since changes in PUF60 expression levels have previously been shown (in HeLa cells) to alter SMN2 exon 7 splicing [We also identified a novel role for RBM10, as a potential regulator of motor neuron function. One of three consistently altered splicing events that was observed in our arrays occurred in the  neurons . SMN pro neurons . In heal failure . The les disease . Regulatnd TRA2β –43 and and TRA2β . Bindingsplicing .FL following downregulation of RBM10, RBM10 may be a potential target for SMA therapy. The usefulness of our findings, with regards to SMA, would depend on the identification of an RBM10 antagonist that could specifically target motor neurons important to SMA, since downregulation of RBM10 (particularly during embryonic development) is the causative agent for TARP syndrome [FL is also involved in RNA processing, the relationship between RBM10 downregulation, increased production of SMNFL and RNA processing in both TARP syndrome and SMA warrants further investigation.In our study, because all of the cell lines examined showed increased expression of RNA encoding SMNsyndrome , 10. Thesyndrome . The finAdditional file 1.http://rnomics.med.usherbrooke.ca/palace?purl=pcrreactiongroup/list/299. Genomics Platform-Palace: Overview Page.Additional file 2.http://rnomics.med.usherbrooke.ca/palace?purl=data/related/1811. Array-96--RBM10 Knockdowns in MCF-7, MDA-MB-231, SKOV-3, OVCAR-3 and PC-3.Additional file 3: Table S1. Array-96: List of genes with changes, by cell line.Additional file 4.http://rnomics.med.usherbrooke.ca/palace?purl=data/related/2493. Array-191--RBM10 Knockdowns in BJ-TIELF, MCF-7, MDA-MB-231, SKOV-3, and PC-3.Additional file 5: Table S2. Array-191: List of genes with changes, by cell line.Additional file 6: Figure S1. Verification of splicing changes in a stable MCF-7 RBM10 KD.Additional file 7: Table S3. List of changes that occurred in cell lines common to both Array-96 and Arrar-191, and the GeneCard database designation used for pathway analysis.


EBV) is a ubiquitous oncogenic virus that is associated with B cell lymphomas, including Burkitt lymphoma and Hodgkin lymphoma. Previous studies have shown that the phosphatidylinositol 3‐kinase (PI3K)/Akt pathway is activated in EBV‐associated lymphomas and can be a novel therapeutic target. An oral dual inhibitor of PI3Kγ and PI3Kδ, duvelisib, is in clinical trials for the treatment of lymphoid malignancies. In this study, we evaluated how duvelisib affects the activity of the PI3K/Akt signaling pathway and if it has antitumor effects in EBV‐associated lymphoma cell lines. We found that the PI3K/Akt signaling pathway was activated in most of the B and T cell lymphoma cell lines tested. Additionally, duvelisib treatment inhibited cellular growth in the tested cell lines. Overall, B cell lines were more susceptible to duvelisib than T and NK cell lines in vitro regardless of EBV infection. However, the additional influence of duvelisib on the tumor microenvironment was not assessed. Duvelisib treatment induced both apoptosis and cell cycle arrest in EBV‐positive and ‐negative B cell lines, but not in T cell lines. Furthermore, duvelisib treatment reduced the expression of EBV lytic genes (BZLF1 and gp350/220) in EBV‐positive B cell lines, suggesting that duvelisib suppresses the lytic cycle of EBV induced by B cell receptor signaling. However, duvelisib did not induce a remarkable change in the expression of EBV latent genes. These results may indicate that there is therapeutic potential for duvelisib administration in the treatment of EBV‐associated B cell lymphomas and other B cell malignancies.Epstein–Barr virus ( Epstein–Barr virus (EBV) is the primary agent causing infectious mononucleosis and persists asymptomatically for life in nearly all adults. EBV infection is associated with the development of B cell lymphomas, posttransplant lymphoproliferative disease (PTLD), natural killer (NK)/T cell lymphoma, and chronic active EBV disease κB) signaling LMP1 is considered a major EBV oncoprotein that mediates activation of multiple cellular signaling pathways, such as c‐Jun‐N terminal kinases (JNK), tumor necrosis factor (TNF) receptor associated factor TRAF, and nuclear factor kappa beta  signaling, proliferation/survival, and migration δ is aberrantly activated in a variety of B cell malignancies such as chronic lymphocytic leukemia (CLL) and acute myeloid leukemia δ has emerged as a promising therapeutic target in hematological malignancies. In fact, in a phase III clinical trial testing the oral selective PI3Kδ inhibitor idelalisib in combination with rituximab, the survival of CLL patients improved considerably The PI3K/Akt signaling pathway has been associated with many virus‐associated cancers. Moreover, it is known to regulate numerous biological activities, including cellular growth, survival, and proliferation γ in addition to PI3Kδγ and PI3Kδ by duvelisib may be another therapeutic target for the treatment of CLL and may overcome resistance formed against idelalisib γ or PI3Kδ inhibitors on EBV‐associated lymphoma cells have not been investigated. In this study, we evaluated the activity of the PI3K/Akt signaling pathway and antitumor effects of duvelisib on EBV‐associated lymphoma cell lines.Duvelisib is a molecule previously found to inhibit the PI3K/Akt signaling pathway, thereby inhibiting BCR signaling, diminishing chemotaxis, and inhibiting cytokine‐induced CLL cell proliferation with minimal apoptosis The cell lines used in this study are summarized in Table 5/mL) were cultured for 48 and 72 h in the presence of duvelisib or idelalisib at concentrations from 0.1 to 5 μmol/L. Viable cells were determined using a Countess™ Automated Cell counter . Subsequent experiments were performed in triplicate at minimum.Cells , PI3Kγ, PI3Kδ, and caspase‐3 , poly ADP ribose polymerase (PARP) and β‐actin .Collected cell extracts were diluted in sample buffer, and prepared for SDS‐PAGE. Equal amounts of cellular protein extracts were loaded on 4–15% polyacrylamide gel. 5/mL) were seeded in 24‐well plates and treated with 5 μmol/L of duvelisib or DMSO for 48 h. Cells were then washed in PBS and incubated with Annexin V‐phycoerythrin (PE) in a buffer containing 7‐aminoactinomycin D (7‐AAD). Apoptotic cells  were analyzed using flow cytometry.Apoptosis was assessed using an Annexin V‐PE/7‐AAD Apoptosis Detection Kit , following manufacturer's instructions. Briefly, cells (2 × 105/mL) were treated with 5 μmol/L of duvelisib or DMSO for 48 h. Cells were then fixed with ice‐cold 70% ethanol, and then washed with PBS. Fixed cells were re‐suspended in 50 μg/mL propidium iodide (PI) solution (Sigma‐Aldrich) with DNase‐free RNase, and then analyzed using flow cytometry. Experiments were performed in triplicate.Cells . Contaminating DNA was removed using the RNase‐Free DNase set (Qiagen). The expression of two lytic (BZLF1 and glycoprotein 350/220) and six latent  EBV genes was quantified by one‐step multiplex real‐time RT‐PCR using QuantiFast Multiplex RT‐PCR kits (Qiagen) and an Mx3000P instrument  as described previously β2‐microglobulin mRNA.RNA was extracted from 1 × 10μmol/L of duvelisib and viable cells were counted after 48 and 72 h. We found that duvelisib inhibited cell growth in EBV‐positive and ‐negative B cell lines, except in P3HR1, in a dose‐dependent manner ], EBV‐positive B cell lines , EBV‐negative T cell lines (MOLT4 and Jurkat), EBV‐positive T cell line (SNT16), EBV‐negative NK cell line (KHYG1), and EBV‐positive NK cell line (KAI3), cell lines were treated with 0.1–5 δ inhibitor idelalisib on B, T, and NK cell lines, 0.1–5 μmol/L of idelalisib was used to treat cells. Viable cells were counted after 72 h of treatment  in cell lines , Akata (+), and Jurkat. Conversely, the phosphorylated form of Akt was detected in all cell lines tested, indicating activation of Akt regardless of EBV status. Duvelisib treatment induced the inhibition of Akt phosphorylation in five of eight tested cell lines  , compared to DMSO control treated cells in six of seven tested B cell lines Fig. A. HoweveThe cleavage of caspase‐3 and PARP was also investigated in B and T cell lines to identify apoptosis after duvelisib treatment for 48 h. Duvelisib treatment induced cleavage of PARP in BJAB, Akata (+), and Mutu I  were equivalent to its effects on CLL cell lines Most of the B cell lines used in this study were cells originating from Burkitt lymphoma. To our knowledge, this is the first study to show the antitumor effects of duvelisib on Burkitt lymphoma cell lines because antitumor effects of duvelisib have been exclusively investigated in CLL γ and PI3Kδ. Compared to idelalisib, a selective PI3Kδ inhibitor, duvelisib showed slightly more cell growth inhibition of T cell lines such as Jurkat or MOLT4. However, cell growth inhibition by duvelisib was modest in T or NK cell lines. Overall, the antitumor effects of idelalisib and duvelisib were similar in the cell lines that were tested. Furthermore, duvelisib did not induce apoptosis in T cell lines. On the other hand, G1 cell cycle arrest was observed in all B and T cell lines tested except P3HR1. Duvelisib treatment could inhibit T cell proliferation by inducing cell cycle arrest. However, its antitumor effects on T cells were limited because apoptosis was not induced.It was expected that duvelisib would have antitumor effects on T or NK cell lines as well as B cell lines because duvelisib is a dual inhibitor of PI3KWe found that duvelisib treatment reduced the expression of BZLF1 and gp350/220 mRNA in EBV‐positive B cell lines, suggesting that duvelisib suppresses the lytic cycle of EBV. In EBV‐positive B cell lines, BCR signaling induces BZLF1 activation, and previous studies have shown that PI3K inhibitors such as wortmannin and idelalisib inhibit the EBV lytic cycle In conclusion, we demonstrated that the PI3K/Akt signaling pathway was activated in EBV‐positive and ‐negative B cell lines. Further, duvelisib treatment induced apoptosis and cell cycle arrest. Although some progress has been achieved with treatments for EBV‐associated lymphomas such as anti‐CD20 antibody and adoptive EBV‐specific cytotoxic T lymphocyte transfer, the effects of these new therapies are still restricted. Our results may indicate that duvelisib has therapeutic potential for the treatment of EBV‐associated B cell lymphomas.None declared.


While problems with cell line misidentification have been known for decades, an unknown number of published papers remains in circulation reporting on the wrong cells without warning or correction. Here we attempt to make a conservative estimate of this ‘contaminated’ literature. We found 32,755 articles reporting on research with misidentified cells, in turn cited by an estimated half a million other papers. The contamination of the literature is not decreasing over time and is anything but restricted to countries in the periphery of global science. The decades-old and often contentious attempts to stop misidentification of cell lines have proven to be insufficient. The contamination of the literature calls for a fair and reasonable notification system, warning users and readers to interpret these papers with appropriate care. The misidentification of cell lines is a stubborn problem in the biomedical sciences, contributing to the growing concerns about errors, false conclusions and irreproducible experiments , 2. As aThe problems with cell line misidentification  have beeThe current calls for action and remediation activities are almost exclusively concerned with avoiding future contaminations, such as through systems for easier verification of cell line identities. Various solutions have been proposed –29, amonBefore any action can be taken, it is essential that we get a sense of the size and nature of the problem of contaminated literature. This raises several questions. First, how many research articles have been based on misidentified or contaminated cell lines? How wide is their influence on the scientific literature? Second, what can we say about origins and trends in the contaminated literature? Is the problem getting better, or restricted to peripheral regions of the world’s research, where perhaps protocols are less strict? Third, what could be appropriate ways to deal with the contaminated literature? To answer these questions, we searched the literature for research papers using cell lines that are known to have been misidentified. In order to put the results of this search in perspective, we analysed the precise complications of misidentification for three particular cell lines.To study the scale of literature contamination, we need to understand the process of setting up, distributing, and publishing about cell lines. This process is illustrated in primary literature based on a cell line.Briefly, setting up a novel cell line commences with a tissue sample from an organism, human or other. If this culture grows successfully, the establishment of a new cell line is sometimes reported in what we will call an ‘establishing paper’. Subsequently, scientists may share or obtain this cell line, either via their personal network or via cell banks. These scientists may perform research on this cell line and publish their findings in scientific journals, thereby setting up what we call the At some point, a cell line may be found to be misidentified. This observation may be published in a ‘notifying paper’, leading to a registration in the International Cell Line Authentication Committee’s (ICLAC) database of cross-contaminated or misidentified cell lines . Based osecondary literature: those articles referring to the primary literature, hence potentially building on questionable materials.In this paper, we focus on the first category only: cell lines without any reported original stock. In this case, it must be assumed that all primary literature could be based on false grounds and should at least be treated with caution. In addition, we tried to estimate the size of the http://iclac.org/databases/cross-contaminations/). From this list we only used table 1, listing those cell lines for which no authentic stock of the originally presumed cell line is reported. This list holds 451 cell lines. The identification of research articles using any of these misidentified cell lines was more difficult than expected. Although any article based on research using one of the listed cell lines supposedly mentions this cell line, the information is frequently not incorporated in one of the searchable fields in large databases , not even in otherwise well-documented biomedical databases such as PubMed. Therefore, the exact number of papers based on misidentified cell lines cannot be established. However, we could identify articles that either refer to the establishing article of a misidentified cell line, or that name the cell line in their title, abstract or key words. This search was carried out within the Web of Science database, because this platform allows for detailed citation analysis. We used the following two search methods to obtain conservative estimates of the number of research articles based on misidentified cell lines:Version 8.0 of the ICLAC list of misidentified cell lines  was publFor any cell line on the ICLAC list we tried to find an original article that reports the establishment of the cell line. These ‘establishing articles’ were searched using the Cellosaurus database , and subIt could be argued that we went too far back in time. It is a common phenomenon that articles have a limited ‘lifespan’, the time during which they receive citations, which would mean that older establishing articles would currently be poorly cited as the cell lines they announced are no longer relevant. To test for this we considered the citation lifespan of all establishing articles published before 1980. They turned out to have an average citation lifespan of over 40 years and the majority of them still received citations in 2016 or 2017. Hence we believe there are good reasons to be inclusive of even relatively old establishing papers.We searched the WoS database for all articles stating the names of one of the 451 listed cell lines in their title, abstract or keywords, as well as one of the words: ‘cell(s)’ or ‘cell line(s)’. In order to provide for more accurate search results, we only searched articles in the 25 research fields (as defined by WoS) that were most common among the results of the first search method. Thereby we excluded articles that use misidentified cell lines, but were classified in fields in which research on cell lines is less common. We note that even though the research areas as defined by WoS may overlap, classifying articles in more than a single research area, this has not lead to double counting in our analysis: all articles included in one of the 25 identified research areas were only counted once.Several strategies were employed to verify the validity of the data and to reduce the number of ‘false positives’ . Regarding search method 1, we closely verified all establishing articles that resulted in at least 100 hits of primary articles in our database (n = 41). In this verification we found one article that was actually a notifying paper instead of an establishing paper and hence deleted it from our search. In addition, four articles were found that report on the establishment of several cell lines, some of which are not listed in the ICLAC database. In two of these cases, the establishing article reports on both the establishment of the contaminated cell line as well as the contaminating cell line (in the cases of EJ138 and HPB-MLT). We decided to not delete those establishing articles from our database, because they yield only few false positives (order of magnitude of tens) in our database.th hit. We checked whether the articles found actually used one of the listed cell lines, this was done by first reading the abstract of the found articles and, in case of doubt, further consulting the full text. If the research reported in the article did not use one of the listed cell lines, the search term that found this article was either replaced by: “name of cell line cell*” (e.g. “WISH cell*” instead of “WISH”), which was done in 26 cases, or the search term was deleted from the query (in cases of very generic words such as in the case of the ‘OF’ cell line), which was done in 15 cases , this search created noise. Therefore we used an iterative process to delete this noise. This process proceeded as follows: we observed a random sample of 100 articles, sampled by ordering the articles on publication data and selecting every 200Subsequently, the process of randomly selecting 100 articles was iterated four times and was executed independently by both authors. Concluding from the results in the random samples, our search method provides reliable results. Nevertheless, the results inevitably contain remaining false positives, the extent of which is estimated to a maximum of 10% of the contaminated primary literature, judged by our verification through random samples of the set, in which 6.5% of the articles was found to consist of false positives The set of false positives contains, among others, articles using cells in the ICLAC register that are nonetheless reported with their correct origin .All claims in this article are based on a dataset of articles found through either method 1 or 2. Both searches were performed without additional software tools, but with manual searches working with complex Boolean search strings. To gather information on the secondary literature, i.e. those articles citing the articles in the primary literature, we used the standard WoS ‘citation report’. In the secondary literature we excluded self-citations in order to observe the actual ‘spreading’ of the contaminated literature. The exclusion of self-citations is a standard option in the WoS’ citation report.In order to verify the collected data and to get a deeper understanding of how knowledge based on misidentified cell lines spreads through the literature, we performed three case studies in which we tracked the publications concerning a single cell line or a family of cell lines. All three are misidentified cell lines for which no original stock was reported and were selected at random from the ICLAC database. The case studies were performed on the cell lines: ALVA-31, a family of thymic cell lines , and JCA-1. The results of the case studies indicate that our search method indeed renders accurate data, with only very few ‘false positives’, and rather conservative estimates.We performed several analyses on the contaminated primary literature’s origins based on WoS data, analysing their temporal and geographical origin and the distribution over research areas. The development over time uses the WoS publication date of the definitive version of the article; hence electronic versions may have been published prior to this date. The WoS goes back to 1945, but is incomplete for the first decades of the database. For the geographical origin of the research records, we employed the WoS category ‘Country/Territory’, which is based on the affiliation of the authors. The origins of the contaminated primary literature are compared with the total literature on research involving cell lines. This total literature comprises the articles that mention any word starting with ‘cell’  in their title, keywords or abstract (hence not only misidentified cells), and belong to the 25 WoS-defined research areas that were most common among the dataset of contaminated primary literature. This reference group was also used to estimate what fraction of the relevant total literature is contaminated (see under the heading Contamination of the scientific literature).Database of Cross-Contaminated or Misidentified Cell lines [Web of Science (WoS) [th, 2017) based on cell lines that are currently known to be different from the cell lines reported in these publications. As we only searched for cell lines known to be misidentified, this constitutes a conservative estimate of the scale of contamination in the primary literature. Moreover, to avoid false positives, we excluded several cell lines, such as the ones with non-unique identifiers or the cell lines for which verified stock is still in circulation. With non-unique identifiers we refer to names of cell lines that do not only refer to the cell line but  also to other phenomena. For example the case of the ‘OF’ cell line or the ‘WISH’ cell line. With ‘non-unique identifier’ we hence do not refer to cell lines that have multiple names or names with multiple spellings . In cases of multiple spellings of cell line names, we stuck to the spelling indicated in the ICLAC database. Thereby we probably missed many articles using these cell lines in search method 2, again leading to conservative estimates.Using ICLAC’s ll lines , we searce (WoS)  to identIn addition, research based on misidentified cell lines has a wide impact on the scientific literature, as it appears that these research papers are comparatively highly cited. WoS does not allow for precise total numbers, but we can give indications of this ‘secondary contamination’ of the literature. Analysing citations to primary contaminated articles, we found 46 papers with more than a thousand citations and over 2600 contaminated articles with over a hundred citations. Furthermore, over 92% of the contaminated papers are cited at least once, which is more than average for biomedical literature . In totaA spreadsheet with all results can be found in the Supplementary Material . This taThe total number of research articles on cells can be estimated between 4.5 and 5 million see . TherefoAn objection to our findings might be that our general search methods do not provide a proper overview of how specific misidentified cell lines actually affect research. To get a deeper understanding of how knowledge based on misidentified cell lines spreads through the literature, we present three case studies in which we tracked the publications concerning a single cell line or a family of cell lines. All three are misidentified cell lines for which no original stock was reported and were selected at random from the ICLAC database.This cell line was originally established in 1993 as a human prostate carcinoma , but wasIn this case, one could argue that it might do little harm to use ALVA-31 cells, while actually working with PC-3 cells, because both are human prostate carcinoma and share many characteristics. However, in some cases, even researchers themselves argue that the precise identity of ALVA-31 is essential: “To exclude a cell type-specific effect, we extended ALVA-31 studies to other human PCa cell types” . SubsequIn a 1994 report, the establishment of a group of novel thymic cell lines   was annoThe JCA-1 cell line was originally established in 1990  and founAs these case studies show, merely listing a cell line as misidentified does not deter scientists from using it. This constitutes additional evidence for the claim that avoiding future contaminations does not form a complete solution to the issue of cell line misidentification. Instead, demonstrably misidentified cell lines continue to have an impact on research, either directly because scientists keep using them, or indirectly because scientists build on previous research employing misidentified lines. One might wonder whether the contamination of the research literature is mainly a problem of the past, given that the first concerns about misidentified cell lines were expressed half a century ago , 10 and Based on the set of 32,755 records of primary contaminated literature, we analysed the publication dates of the articles. The majority of the articles, 57%, were written since 2000 and the number of articles using misidentified cell lines is still growing see . ClearlyNature in 1968 [Science in 1981 that demonstrated large-scale contamination of cell cultures by HeLa cells [ in 1968 . Second, in 1968 , 8, culmLa cells . From thLa cells , the annSimilar to the primary literature, the number of articles in the secondary literature is also still growing. In 2016, over 40,000 papers were published that referred to primary contaminated literature. In addition, from the information in the Supplementary Material , we concAnother objection to our findings could be that cross-contamination occurs particularly in regions with new or emerging research communities, in which levels of training or access to testing facilities may be limited. For example, several recent publications indicate levels of cell line contamination for China between 25%  and 46% However, the majority of the articles using misidentified cell lines originate from countries holding well-established research traditions . Relative to their share of total research output, authors from these countries often perform research on misidentified cell lines. In fact, mainly due to their enormous share of total literature on cell lines, over 36% of all contaminated primary literature stems from the US. Last, we analysed which research disciplines were most affected by the use of misidentified cell lines. However, analysis of citations obtained by the primary literature indicates that the secondary literature spreads to a much more diverse range of research areas. The articles in the secondary literature originate also in fields rarely using cell lines for their research, such as psychiatry, engineering and agriculture science, see Our results seem to present worrying problems for the biomedical sciences. Although the issue of misidentified cell lines has long been known, its effect on the scientific literature has not been properly recognised, let alone properly treated , 48. Hownot to label articles that employ misidentified cell lines, for two reasons. To begin with, it is currently up to every individual scientist to judge the status of an article every time they cite or read it, by first checking the ICLAC database of misidentified cell lines to see whether any of the cell lines used in an article are in this database, and subsequently judging the influence that the misidentification may have on the results. This is a cumbersome and unlikely assumption about how researchers cite their literature, given the low levels of awareness indicated in our analysis. In addition, the secondary literature spreads into research fields that do not commonly use cell lines for their research. It is particularly doubtful whether scientists from these fields are aware of the potential issues with research on cell lines and whether they are in the position to make informed decisions about the validity of the claims in research articles based on misidentified cell lines.First, it has been asserted that, in some cases, the origin or specific characteristics of a cell line might be of little influence on the results of an experiment. Indeed, in some cases all that a researcher needs is ‘a cell line’, independent of type, origin or status. In fact, this argument was already mentioned by Gartler in 1968 to put his findings into perspective . To be sSecond, it has been argued that no remedial action is needed, as the problem will be addressed by new verification techniques. Similarly, it has been argued that the problem is already widely known, that scientists may be expected to implement effective lab protocols and be sufficiently critical about cell lines and their literature. Hence contaminated literature should have faded beyond the time horizon of literature considered relevant for current research and have disappeared from the relevant research record . HoweverOver the past decades thorough attention has been paid to the improvement of authentication testing for cell lines. Authentication of cell lines, and hence the ability to demonstrate cross contamination, became possible by the introduction of genetic markers by Gartler in 1967 , and thehonest error’, with no intention to deceive, notifying all those articles as potentially erroneous, or worse: retracting them, would have a disproportionate impact on several scientists’ careers. This would undermine, rather than support, an effective clean-up operation. However, in addition to catching cell line contamination at the source, initiatives to label contaminations ‘downstream’ in the published literature are direly needed. We can make several suggestions.Despite measures to authenticate new and existing cell lines , researcNeither retractions nor corrections, they alert readers that there may be an issue with a paper, when the full story is not yet clear.” [First, notifications should be posted alongside previously published articles using misidentified cell lines. This could be done in the form of ‘expressions of concern’, which are described as “ clear.”  If clear clear.” , could bSecond, to allow for simple future identification of articles using misidentified cell lines, we recommend that authors mention the employed cell lines in easily searchable parts of their article, such as the keywords or abstract. Some journals have already suggested measures in this direction, but implementation seems to be slow . HoweverIn addition, better use could be made of paper trails for cell line provenance . A clearBesides being of use in terms of recognition of erroneous research, the paper trail might also serve other purposes, such as mapping the existing knowledge on a certain cell line  and providing a stage for the publication of negative results of experiments on cell lines. The publication of such results has long been proposed as a way of fostering integrity in research .Nearly half a century after the first concerns about misidentified cell lines, the initiatives to improve authentication need to be complemented by attention to the already contaminated literature. Our analysis shows that the task is sizeable and urgent.S1 FileNames of cell lines that were adjusted for the search in method 2 or that were excluded from the search and included research areas (as defined by WoS) in search method 2.(DOCX)Click here for additional data file.S2 FileData by country and by cell line.(XLSX)Click here for additional data file.


Despite many efforts, colibactin has not yet been purified, and its structure remains elusive. Interestingly, the pks island is found in members of the family Enterobacteriaceae (mainly Escherichia coli and Klebsiella pneumoniae) isolated from different origins, including from intestinal microbiota, septicaemia, newborn meningitis, and urinary tract infections. Colibactin-producing bacteria induce chromosomal instability and DNA damage in eukaryotic cells, which leads to senescence of epithelial cells and apoptosis of immune cells. The pks island is mainly observed in B2 phylogroup E. coli strains, which include extra-intestinal pathogenic E. coli strains, and pksE. coli are over-represented in biopsies isolated from colorectal cancer. In addition, pksE. coli bacteria increase the number of tumours in diverse colorectal cancer mouse models. Thus, colibactin could have a major impact on human health. In the present review, we will focus on the biological effects of colibactin, the distribution of the pks island, and summarize what is currently known about its synthesis and its structure.Cyclomodulins are bacterial toxins that interfere with the eukaryotic cell cycle. A new cyclomodulin called colibactin, which is synthetized by the  Escherichia coli: two able to inhibit proliferation  and one able to promote proliferation  . Thi. Thipks  E. coli ,35.E. coli and therefore a connection between siderophore and colibactin production [At the beginning of the assembly line, ClbA, a phosphopantetheinyl (PPant) transferase, is responsible for the activation of the NRPS and PKS enzymes by the addition of a PPant onto the NRPS and PKS carrier protein domains. Interestingly, ClbA is also involved in the synthesis of the siderophores enterobactin and yersiniabactin by replacing EntD. Hence, there is evidence of a possible trans-complementation between PPants in oduction . The enzN-myristoyl-d-Asn, a prodrug motif, which is accepted by ClbB [3H3) formation [pks E. coli which lack any component of the AM biosynthetic machinery are not genotoxic [pks assembly line  suggesting that AM could be incorporated more than once into colibactin [3H3NS) generated by ClbK [The first study aimed at elucidating colibactin biosynthesis focused on ClbN and ClbB, the NRPS enzymes involved in the initiation of colibactin biosynthesis . It was  by ClbB . ClbB ad by ClbB  . In Δclb E. coli, precolibactins are accumulated, allowing their identification by mass spectrometry. However, the purification and characterization of precolibactins still remain a challenge, and compounds isolated so far have been obtained in extremely small quantities. Bian and colleagues were the first try to purify precolibactin molecules [E. coli, 1.8 mg of N-myristoyl-d-Asn and a number of analogues with different acyl chain lengths (C12 to C16). However, because of the low yields, it was not possible to purify them for further elucidation and the purified product N-myristoyl-d-Asn had no cytotoxic activity. Vizcaino and colleagues also reported the presence of N-myristoyl-d-asparagine and several new colibactin metabolites [1). Unfortunately, none of these compounds exerted genotoxic activity against HeLa human epithelial cells, suggesting that other metabolites within the colibactin network possess this activity.Despite intensive research, the structure of colibactin remains unknown probably owing to its high instability. Since colibactin cannot be purified directly from a olecules . They isabolites   [pks island underlying the complexity of colibactin biosynthesis. Spiro-cyclopropane resembles the ring systems found in DNA-alkylation agents such as the duocarmycins [pks E. coli are able to induce DNA interstrand cross-links in cellulo [3). Interestingly, using LC–MS, it was found that ClbP is able to process the precolibactin A metabolite, thereby confirming that the spirocyclic ring motif is present in precolibactin [A molecule containing a spiro-cyclopropane, a structural motif rare among NRPS and PKS products, was reported in 2015 (2) ,51,52. Tarmycins  and illuarmycins , suggestarmycins . This acarmycins . It has  cellulo . In euka cellulo . Thus, i cellulo . On the  cellulo   [6, precolibactin C) [Large-scale cultures confirmed the presence of the compounds already described ,52 and r, and 5) . Compoun, and 5) . Using pactin C)  which haactin C) . The bitactin C) .clbQ ΔclbP strain since ClbP is the enzyme responsible for final colibactin maturation [7). Interestingly, this compound exerted a greater cytotoxic effect on human epithelial cells (HCT-116 and HeLa) than less-advanced precolibactins already purified [clbP strains such as precolibactin-886 could arise from non-natural reaction pathways [8) [9 which had the highest DNA-alkylation properties in vitro) [pks E. coli. Interestingly, a new reactive precolibactin metabolite structurally close to molecule 9 was characterized a few months ago from bacteria [10). Although this latest purified molecule contains potentially genotoxic structures, its genotoxic activity has not yet been tested.The most advanced precolibactin compounds purified so far have been obtained by Li and co-workers starting from 1000 L of media . To purituration ,48 and Cturation ,44. Usinturation   . Howeverbacteria   after infection. Bacterial culture conditions are important, in particular shaking since it increases the transcription levels of clbA to clbH genes [clbA transcription via pathways dependent and independent of the ferric uptake regulator Fur and the small noncoding RNA RyhB [E. coli heat shock protein Hsp90Ec has been shown to be crucial for the production of colibactin [Ec can either facilitate the folding of Clb proteins and/or increase their stability. Given the serious side effects of colibactin on cells, it is important to understand the regulation of its synthesis. Since so far it has been impossible to assay colibactin concentration, the easiest way to assess the regulation of its expression is to measure the transcriptional levels of bH genes . The comRNA RyhB ,62. Finalibactin . AuthorsE. coli strains isolated from urinary infections, it has been shown that the expression of the pks island was up-regulated when urine was used as the culture medium [pks genes was also observed in patients with urinary tract infection [To our knowledge, few data are available about the effects of in vivo conditions on colibactin expression. In e medium . More imnfection .Il10-/- mice (colitis) and AOM/Il10-/- mice  monocolonized with a pks E. coli strain isolated from a mouse gut [E. coli genes was driven by cancer status. Interestingly, 5 pks island genes  were upregulated among the 66 genes significantly affected. This important study clearly suggests that variations in the microenvironment during colorectal cancer development directly affect colibactin expression, pointing to the complexity of pks gene regulation. Further evidence of this complexity has been provided by an assessment of the genotoxicity of pks E. coli exposed to deoxynivalenol (DON), the most prevalent mycotoxin food contaminant. DON exacerbated the genotoxicity of pks E. coli in vitro and in rats intestinal epithelial cells [clb genes. These observations suggest that synergy between toxins may occur. Although the regulation of colibactin synthesis and its possible interactions with other toxins/food contaminants remain largely unknown, these recent studies show that the environment plays a crucial role in the production and genotoxicity of colibactin. Thus, we can speculate that many people harbour pks bacteria in which colibactin expression is repressed. However, when certain changes occur in external or internal conditions, colibactin expression can be turned on and consequently profoundly affect health.Two elegant studies using mouse models have assessed the regulation of colibactin synthesis in the gut. First, Arthur et al., investigated the effect of intestinal inflammation and colorectal cancer development using germ free ouse gut . Transcrpks E. coli requires live bacteria and direct contacts with epithelial cells, suggesting that colibactin is either poorly diffusible or highly unstable [The signature of colibactin is the induction of DNA double-strand breaks, in vitro and in vivo, ,8,14,67 unstable ,68. Thuspks E. coli [pks E. coli strains to the offspring has been confirmed in rats [pks E. coli in newborn rats impaired intestinal permeability [E. coli strains exacerbate DNA damage in intestinal epithelial cells of neonates and cause chromosomal instability [pks E. coli since the bacteria increase the rate of cell apoptosis, which is compensated by an increase in cell proliferation leading to an abnormal crypt fission rate [Since clinical studies showed that the newborn’s gut is frequently colonized by  E. coli ,8, expereability , which eeability . This prpks E. coli are frequently found in gut microbiota [Because crobiota ,5,6 and E. coli is highly suspected of being involved in CRC development. It has been known for almost 20 years that human CRC biopsies are highly colonized by E. coli [E. coli are found in 55–67% of colorectal cancer patients but in less than 20% of controls [clbA was found to be over-represented in the stools of CRC patients compared to those of controls  [APC (adenomatous polyposis coli) tumour suppressor gene [pks E. coli (68%) compare to healthy subject mucosa (22%) [pks positive genes found in the faeces of CRC patients and healthy controls [pks (which is consistent with previous reports). In contrast, 46% of controls were positive for pks, which is much higher than the prevalence reported in previous studies. Microbiota composition depends on the geographic area considered [pks island in the Japanese sample was different than that in Europe and in the USA. It would be interesting to perform more epidemiological studies in Asia to see if this discrepancy is confirmed.Most CRCs (~90%) are sporadic and therefore influenced by external factors such as diet and microbiota ,71,72,73 E. coli . Closer  E. coli ,14,15. Rcontrols ,14. In actively) . Patientsor gene . It has sa (22%) . All thesa (22%) , and Swesa (22%) ) and in sa (22%) . To datecontrols . In thisnsidered , which cbacterial drivers”) would initiate the CRC thereby altering the intestinal niche that favours the proliferation of opportunistic bacteria . Current experimental data on animals suggest that pks E. coli are unable to spontaneously induce CRC [pks bacteria need to be in close contact with intestinal stem cells [pks E. coli, until their exposure to the specific conditions required for the production of colibactin and for the contact between bacteria and epithelial cells, pks E. coli will not have deleterious effects on intestinal epithelial cells.A bacterial driver-passenger model has recently been proposed in the development of CRC . In thisduce CRC . Howeverduce CRC ,16,17,18em cells  and to bE. coli increased epithelial cell proliferation in vivo [E. coli induced inhibition of the mutL homologue 1 (MLH1) mismatch repair protein [pks E. coli infection [pks E. coli induces the expression of microRNA-20a-5p, which is responsible for p53 post-translational modification -conjugated p53), which in turn leads to cellular senescence [pks E. coli [pks bacteria, the use of inhibitors of colibactin synthesis could be an interesting adjuvant strategy to limit cell proliferation [Colibactin-producing  in vivo ,16,28, t in vivo ,16,17,18 protein , which cnfection ,8. Howevnfection . It has nescence . Howevernescence . Importa E. coli ,67, and  E. coli . This prferation .pks is widely distributed among E. coli K1 strains isolated from cases of meningitis [pks island is functional in E. coli K1 strains and induces DNA damage but, more importantly, pks contributes to the bacterial virulence [E. coli K1 necessarily involves the translocation of bacteria from the immature gut to the blood. Using animals models, it has been shown that inactivation of clbA or clbP reduces the capacity of bacteria to colonize the gut and consequently to translocate to the blood [pks E. coli induce apoptosis of T lymphocytes and exacerbate lymphopenia associated with septicaemia, thereby decreasing the survival rate of rats with sepsis [Klebsiella pneumoniae (the most common pathogen of community-acquired meningitis in Taiwan) significantly decreased K. pneumoniae hyper-virulence in the key steps towards the development of meningitis [As ningitis , its funirulence ,84. In nhe blood ,69. Onceningitis .E. coli Nissle 1917, a probiotic strain commercially available and used to treat intestinal disorders [pks island [pks island is mandatory for this strain to exercise its anti-inflammatory effects in a colitis mouse model [pks island. In addition, the pks island is responsible, in this probiotic strain, for the production of an analgesic lipopeptid (C12AsnGABAOH), which is able to cross the epithelial barrier and inhibit the calcium flux induced by nociceptor activation in sensory neurons via the GABAB receptor. As a result, this abrogates visceral hypersensitivity in mice [pks island is the production of one or more antibiotic molecules. The N-myristoyl-d-Asn released during colibactin maturation exerts mild growth-inhibitory activity against Bacillus subtilis NCIB 3610 [Staphylococcus aureus and, more importantly, that of methicillin-resistant S. aureus strains and strains resistant to “last-resort” antistaphylococcal antibiotics [While numerous studies have evidenced the deleterious effects of colibactin, some studies have pointed out that things are probably more complicated than initially thought. For example, isorders , possesss island . A functse model , suggest in mice . AnotherCIB 3610 . On the ibiotics . These ipks bacteria have emerged as major players in human health. Owing to its pleiotropic effects, colibactin profoundly influences cellular physiology, inducing DNA breaks that lead to senescence or apoptosis. Numerous in vitro and, more importantly, in vivo studies have evidenced the harmful effects of colibactin in sepsis, meningitis, and the intestinal tract. Colibactin is also strongly suspected of being involved in the development of CRC. The use of Clbs inhibitors has been suggested as a means of preventing its deleterious effects and a proof of concept has been made. However, in addition to the genotoxic effects of colibactin, studies have clearly shown that some products generated by the pks island are of interest since they exert antibiotic, analgesic, or anti-inflammatory effects. Further studies are needed to find a means of preventing the genotoxic effect of colibactin, and work should be done on the purification of the diverse products generated by the pks island, since some of them could be potentially used in human medicine.In just one decade,


Interestingly, it has been found that intracellular and extracellular S100A11 have different functions in cell viability. In this study, we focused on the impact of extracellular S100A11 in MPM and explored the therapeutic potential of an S100A11-targeting strategy. We examined the secretion level of S100A11 in various kinds of cell lines by enzyme-linked immunosorbent assay. Among them, six out of seven MPM cell lines actively secreted S100A11, whereas normal mesothelial cell lines did not secrete it. To investigate the role of secreted S100A11 in MPM, we inhibited its function by neutralizing S100A11 with an anti-S100A11 antibody. Interestingly, the antibody significantly inhibited the proliferation of S100A11-secreting MPM cells in vitro and in vivo. Microarray analysis revealed that several pathways including genes involved in cell proliferation were negatively enriched in the antibody-treated cell lines. In addition, we examined the secretion level of S100A11 in various types of pleural effusions. We found that the secretion of S100A11 was significantly higher in MPM pleural effusions, compared to others, suggesting the possibility for the use of S100A11 as a biomarker. In conclusion, our results indicate that extracellular S100A11 plays important roles in MPM and may be a therapeutic target in S100A11-secreting MPM.Malignant pleural mesothelioma (MPM) is an aggressive tumor with an unfavorable prognosis. The standard therapeutic approaches are limited to surgery, chemotherapy, and radiotherapy. Because the consequent clinical outcome is often unsatisfactory, a different approach in MPM treatment is required. S100A11, a Ca While surgical resection is the treatment of first choice for early-stage disease, recurrence of the disease often makes the prognosis poorer. In addition, most MPM cases are of advanced-stage disease, for which the benefits of a standard chemotherapeutic regimen with cisplatin and pemetrexed are very limited. These considerations demand the development of novel therapeutic strategies for MPM.Malignant pleural mesothelioma (MPM) is a highly invasive and aggressive tumor that develops in the mesothelial lining of the pleura. The median survival of patients with MPM from the time of diagnosis is usually less than 1 year2+ sensors and as extracellular factors5.Proteins of the S100 family are small molecules (ranging from 9 to 14 kDa) with two EF-hands and in humans, the family is composed of 20 different members . This group of proteins modulates a variety of cellular processes, including cell proliferation, differentiation, and intracellular signaling by functioning both as intracellular Ca6. We previously reported that S100A11 has two ambivalent functions in the cells. Namely, in the cytoplasmic compartment, S100A11 inhibits the growth of normal human keratinocytes in response to high Ca2+ or transforming growth factor β8. Contrarily, the binding of extracellular S100A11 to the receptor for advanced glycation end products (RAGE) enhances the production of epidermal growth factor family proteins, resulting in growth stimulation9. Based on these findings, we have studied the biological activity of S100A11 by focusing both on intracellular and extracellular S100A11. As for the function of intracellular S100A11, we have shown that the intracellular S100A11–ANXA2 complex helps plasma membrane repair, which was critical for survival and metastasis, in metastatic breast cancer cell line10. Additionally, it is reported that intracellular S100A11 promotes pseudopodial actin dynamics, which plays a critical role in tumor metastasis and the suppression of S100A11 results in inhibition of cell migration and invasion, and the reversion of Epithelial to mesenchymal transition (EMT) in various metastatic cell lines11. Regarding extracellular S100A11, we have recently reported that, in mesothelioma cells, S100A11 dimerizes in the peroxisome after transportation of monomeric S100A11 through the interaction with PEX14, an essential component of peroxisomal import machinery, and actively secreted12. However, despite advances in the understanding of the biological activity and mechanisms of this protein, little is known about its therapeutic or diagnostic potential. In this study, we investigated the relationship between extracellular S100A11 and MPM, and explored the possibility of an intervention in S100A11 function for MPM treatment and diagnosis.S100A11, also called S100C or calgizzarin, was cloned from chicken gizzard in 1991We first examined the secretion level of S100A11 in the culture media of various cell lines by enzyme-linked immunosorbent assay (ELISA). Seven MPM, 2 normal mesothelial, 12 lung cancer, 3 gastric cancer, 3 colorectal cancer, and 3 breast cancer cell lines were used for this analysis, and the result is shown in Fig. 13. Similarly, we confirmed that the screened antibody decreased the quantity of S100A11 in the cell culture media  . In addition, we found that anti-apoptotic Bcl-2 protein was significantly elevated with a similar manner to those of Cyclin D in both H2452 and H2052 cells . These results suggest that the secreted S100A11 positively regulates not only cell cycle, especially in a specific activation of the G1 phase and following G1/S transition through an induction of Cyclin D, but also survival via induction of Bcl-2.To gain insight into the intracellular signaling events induced by the neutralization of extracellular S100A11, we investigated the key molecules regarding to cancer progression. MPM cells were cultured with the anti-S100A11 antibody (1 μg/ml), S100A11 recombinant protein (100 ng/ml), or mouse control IgG (1 μg/ml). Lysates were extracted every 6 h and subjected to western blot analysis , 11 benign asbestosis (BA) patients, and 12 patients who underwent thoracic surgery at the Okayama University Hospital and the National Hospital Organization Yamaguchi-Ube Medical Center . Postoperative pleural effusions were obtained from lung cancer (n = 10) or pulmonary cyst (n = 2) patients after postoperative day 2. The concentration of S100A11 was measured by ELISA. As shown in Fig. P = 0.014). Furthermore, we found that the secretion level of S100A11 was significantly higher in pleural effusion from BA patients than that from postoperative patients (P = 0.041).To explore the possibility of using S100A11 as a useful marker for diagnosis of MPM, we examined the secretion levels of S100A11 in several types of pleural effusions. We obtained pleural effusions from 29 MPM patients , and some members of the S100 family, including S100A1122. Moreover, RAGE has been shown to have many distinct biological functions. For instance, van Zoelen and colleagues23 demonstrated that RAGE signaling contributed to an effective antibacterial defense during Escherichia coli infection , and RAGE deficiency resulted in enhanced organ injuries due to liver necrosis. Thus, the adverse effects due to the inhibition of RAGE signaling are still unclear and as a therapeutic target for MPM, it seems more convenient to inhibit extracellular S100A11 than RAGE at present.In our experiments, growth inhibitory effect of sRAGE was limited and insufficient in comparison with the that of anti-S100A11 antibody, indicating that an additional S100A11 receptor, such as CD36, might activate survival or proliferative pathways in the cells27; this along with our results suggest that S100A11 may be involved in chronic inflammation.Although “High” cells (H290 and H28) displayed resistance to the S100A11 antibody at lower concentration (100 ng/ml), the effect of S100A11 antibody was shown when much higher concentration of it (1 μg/ml) was used. Thus, the secretion of S100A11 in MPM cells was prerequisite for the antibody approach and measurement of the secretion level of S100A11 was quite important index to predict an effectiveness of the S100A11 antibody. We hence examined the secretion level of S100A11 in pleural effusion. The concentration of S100A11 in MPM pleural effusions was significantly higher than that in pleural effusions of BA and postoperative patients, though the amount of secreted S100A11 is high in pleural effusions from both patients with MPM and BA. Generally, BA is not regarded as a precancerous lesion of mesothelioma. Taking it into account, we consider that MPM cells actively secrete S100A11 in pleural effusion. These results suggest that S100A11 can be not only a therapeutic target but also an early diagnosis marker. In addition, it is of note mentioning that the concentration of S100A11 in the pleural effusions of patients with BA was significantly higher than that of postoperative patients. The association between high expression of proteins of the S100 protein family and inflammatory diseases has been reportedIn conclusion, we showed that extracellular S100A11 plays an important role in MPM progression and neutralization of extracellular S100A11 directly linked to marked suppression of MPM developments in vitro and in vivo. Our results suggest that extracellular S100A11 can be a novel, selective and effective therapeutic target in S100A11-secreting MPM, since normal cells displayed no secretion phenotype of S100A11.28. Three MPM cell lines , two lung cancer cell lines (HCC4011 and H82 obtained in 2008), and two extrapulmonary small-cell cancer cell lines (H1048 and H1870 obtained in 2008) were kindly gifted by Dr. Adi F. Gazdar 29. YUMC44 cell line was established by one of the authors (H.Y.)30. MSTO-211H, MeT-5A, N87 cell lines, seven lung cancer cell lines , three breast cancer cell lines , and three colorectal cancer cell lines  were purchased from the American Type Culture Collection . Two gastric cancer cell lines (KATO III and SH-10-TC) were obtained from the Cell Resource Center for Biomedical Research Institute of Development Aging and Cancer, Tohoku University . LP-9 cell line was purchased from the Coriell Cell Repository . PC-9 cell line was purchased from Riken Cell Bank . The cell lines within 30 passages were used in this study and the cumulative culture length was less than 6 months. For cell lines with long-term preservation in liquid nitrogen, DNA fingerprinting analysis by short tandem repeat profiling  was performed for the cell authentication. All the cell lines, except for LP-9 and breast cancer cell lines, were maintained in RPMI-1640 medium  supplemented with 10% fetal bovine serum (FBS). The three breast cancer cell lines were cultured in Dulbecco’s modified Eagle’s medium  with 10% FBS. LP-9 was cultured in Ham’s F12 medium /Medium 199  (1:1 mixture) with 10% FBS, 2 mM l-glutamine , 1.7 nM epidermal growth factor , and 1100 nM hydrocortisone . All the cell lines were grown in a humidified incubator with 5% CO2 at 37°C and routinely tested for mycoplasma by Venor GeM OneStep kit . Soluble receptor for advanced glycation end products (RAGE) Fc chimera (sRAGE) , static , trametinib (GSK-1120212) , Taselisib (GDC-0032) , and the mouse IgG-isotype control  were obtained from the designated sources. S100A11 recombinant protein was prepared as described previously5.We used seven human MPM cell lines , two human normal mesothelial cell lines (MeT-5A and LP-9), 10 human lung cancer cell lines , two human extrapulmonary small-cell cancer cell lines [NCI-H1048 (H1048) and NCI-H1870 (H1870)], three gastric cancer cell lines , three colorectal cancer cell lines , and three breast cancer cell lines . Two MPM cell lines (HP-1 and H2452) were established by one of the authors (H.I.P.)The concentration of S100A11 was measured using the CircuLex S100A11 ELISA Kit  according to the manufacturer’s protocol. The standard curve for the ELISA was obtained using various concentrations of recombinant human S100A11. Samples were diluted 5- to 10-fold. The absorbance was measured at the dual wavelengths of 450/540 nm using the Flex Station 3 microplate reader  and the concentration of S100A11 (in pg/ml) was calculated according to the standard curve.31. The primary antibodies used for western blot analyses were as follows: EGFR , phospho- (p-)EGFR (Tyr1068) (#3777), Stat3 (#12640), p-Stat3 (Tyr705) (#9145), Akt (#9272), p-Akt (Ser473) (#4060), p44/p42 MAPK (#9102), p-p44 ⁄ p42 MAPK (#9101), Cyclin B1 (#4138), Cyclin D1 (#2922), Bcl-2 (#2872) , S100A11 , and β-actin (used as a loading control) . The following secondary antibodies were used: goat anti-rabbit  or anti-mouse  immunoglobulin G (IgG)-conjugated horseradish peroxidase . To detect specific signals, the membranes were examined using the ECL Prime Western Blotting Detection System  and LAS-3000 imager .The detailed protocol has been described previously32.MPM tissues were obtained from patients who underwent surgery at the Okayama University Hospital, in Okayama City, Japan. The experimental protocol was approved by the Institutional Review Board/Ethical Committee of the Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences and Okayama University Hospital (Permit Number: 1508-027) and informed consent, including publication of patient photos, was obtained from all the patients. Tissue samples were fixed in 10% formaldehyde and embedded in paraffin. The immunohistochemical (IHC) staining for S100A11 was performed using an S100A11 primary antibody . The detailed protocol for the IHC staining has been described previously4 cells were seeded into each well of a 24-well plate. After 24 h of incubation, the plates were placed in the Incucyte Zoom system. Images were taken every 6 h for the indicated amount of time. The percent of confluence over time was calculated using the Incucyte Zoom software. For experiments testing the effect of sRAGE on cell proliferation, the thiazolyl blue tetrazolium bromide (MTT)  dye reduction method was used, as described previously33.To examine the effect of the anti-S100A11 antibody  on cell proliferation, the IncuCyte Zoom Live Cell Imaging System  was used. In brief, 1.0 × 1034.Cell migration and invasion were analyzed using a Boyden chamber assay. The cells were cultured with an antibody (100 ng/ml) for 24–48 h (for migration assays) or 48–72 h (for invasion assays). The detailed protocol has been described previouslyn = 3 for each group). Each cell line (5 × 106 cells) suspended in 200 µL RPMI-1640 media and Matrigel Basement Membrane Matrix  was subcutaneously injected into the backs of the mice either with 1 µg/ml anti-S100A11 antibody (proteintech Group) or mouse IgG-isotype control (two tumors per mouse). The injection was repeated five times every 3 days. Four weeks after the first injection, the mice were sacrificed and the tumors were harvested, measured, and photographed. The tumor volume was calculated using the empirical formula V = 1/2 × [(shortest diameter)2 × (the longest diameter)]. No randomization and no blinding was performed. Sample size estimates were based on our previous experience.The protocol was approved by the Animal Care and Use Committee of Okayama University (Permit Number: OKU-2016205). Six-week-old NOD⁄SCID female mice were purchased from Charles River Laboratories . To evaluate the effect of the anti-S100A11 neutralizing antibody, mice were randomly divided into two groups: an antibody-administered group and a control group (http://software.broadinstitute.org/gsea/index.jsp).Before and after treatment of H2052 and H2452 cells with the anti-S100A11 antibody (Proteintech Group), total RNAs were extracted from cell lines using an RNeasy Mini Kit . Purified total RNA samples were hybridized on the Human Whole Genome DNA Microarray system  to obtain the altered gene expression profile. The fold change in the expression of individual genes was calculated and genes with fold changes exceeding 2-fold or below 2-fold were considered up- and downregulated, respectively . The Student’s t-tests was used to compare means of continuous scores between two independent groups. Otherwise, the Mann–Whitney U-test was used. An F-test to compare variances was performed, if necessary. All statistical tests were two-sided, and probability values less than 0.05 indicated statistically significant differences.All in vitro experiments were performed at least three times. Data are expressed as the mean±standard deviation. All data were analyzed using the JMPSupplementary Figure S1Supplementary Figure S2Supplementary Figure legendsSupplementary table