Low-passage, serum-free cell lines cultured from patient tumour tissue are the gold-standard for preclinical studies and cellular investigations of glioblastoma (GBM) biology, yet entrenched, poorly-representative cell line models are still widely used, compromising the significance of much GBM research. We submit that greater adoption of these critical resources will be promoted by the provision of a suitably-sized, meaningfully-described reference collection along with appropriate tools for working with them. Consequently, we present a curated panel of 12 readily-usable, genetically-diverse, tumourigenic, patient-derived, low-passage, serum-free cell lines representing the spectrum of molecular subtypes of IDH-wildtype GBM along with their detailed phenotypic characterisation plus a bespoke set of lentiviral plasmids for bioluminescent/fluorescent labelling, gene expression and CRISPR/Cas9-mediated gene inactivation. The cell lines and all accompanying data are readily-accessible via a single website, Q-Cell (qimrberghofer.edu.au/q-cell/) and all plasmids are available from Addgene. These resources should prove valuable to investigators seeking readily-usable, well-characterised, clinically-relevant, gold-standard models of GBM. Despite surgery, radiotherapy and temozolomide chemotherapy, GBM patients have a median survival of <15 months and a 5-year survival rate of only 10%2. GBM almost always recurs following treatment and is then rapidly fatal with no current mainstay therapy effectively altering the course of the disease1. Two factors that contribute to treatment failure are the heterogeneity of GBM – in part represented by tumour cells with distinctly different patterns of gene expression4  – and the presence of glioma stem cells (GSCs), chemo-radiotherapy resistant cells that are able to reconstitute tumour architecture and are believed to be responsible for disease progression and recurrence7. Preclinical cell line and animal models that recapitulate these features accurately are essential if our understanding of GBM biology is to improve and more effective strategies to treat this almost uniformly fatal disease are to be developed.Glioblastoma  is the most common, and most lethal, primary malignant adult brain cancer10. These approaches not only capture the genetic diversity of human GBM, but also help preserve the genomic fidelity of such cells and enrich for the presence of GSCs, enhancing their tumour-initiating capacity11. Significantly, xenograft tumours that arise from these cells are invasive and exhibit the histological hallmarks of high grade glioma, including hypercellularity, nuclear atypia and the presence of mitotic figures, with or without microvascular proliferation and  necrosis12. In essence, such cell lines are a highly relevant model for studying GBM, capturing the heterogeneity of this disease and recapitulating its cancer stem cell biology.Low-passage, serum-free, patient-derived GBM cell lines have proven to be the gold-standard in this regard. Methods to initiate and propagate such lines from patient tumour tissue are well establishedin silico analysis should facilitate selection of lines suitable for hypothesis testing while the size, genetic diversity and subtype representation of the collection provides incentive for acquisition of the entire set to broadly and meaningfully inform studies of GBM.Despite their greater relevance for understanding human GBM, more widespread use of low-passage, serum-free, patient-derived cell lines in much GBM research appears not to be restricted by technical challenges but rather issues associated with the acquisition of patient tissue, unfamiliarity with existing lines, and/or much greater familiarity with alternative long-established  cell line models of GBM. Here we aspire to increase the wider use of low-passage, serum-free, patient-derived GBM cell lines amongst the cancer and cell biology research community by presenting a reference set - a curated, practical-size collection of genetically-diverse GBM cell lines established from different molecular subtypes of GBM - that form invasive xenograft tumours in immunodeficient mice. All lines have been characterised in significant practical detail, for interrogation and immediate use by researchers, with all data accessible via a user-friendly website. The availability of this data for In addition, we provide a set of tools to facilitate functional analysis of the lines. Lentiviral plasmids for bioluminescent and/or fluorescent labelling, expressing genes of interest and CRISPR/Cas9-targeted gene inactivation are presented. These further enhance the utility of the collection for investigating the biology of GBM.Between November 2009 and June 2011, we established GBM cell lines as serum-free, adherent cultures from tissue collected from patients undergoing surgery at the Royal Brisbane and Women’s Hospital with a success rate of 75%. Twelve morphologically-diverse, rapidly-growing cell lines, that formed xenograft tumours when injected intracranially into NOD/SCID mice, were selected as a GBM reference collection for subsequent detailed characterisation. The patient cohort from which the cell lines were established had a median age of 70 years (range 48–84 years) and included 7 males and 5 females Table .Table 1P13. Tumour tissue from both sources was mechanically and enzymatically dissociated and cultured on matrigel-coated plastic in serum-free RHB-A medium supplemented with epidermal growth factor and fibroblast growth factor 2. Medium was changed every three to four days and cells were washed with phosphate-buffered saline to remove tissue debris. Cells were passaged into larger flasks when nearing confluence and the first freezings were made from 75 cm2 flasks after continuous culture ranging from 14 to 30 days. The resultant cell lines exhibited a variety of cell morphologies  (Table Expression of O-6-methylguanine-DNA methyltransferase (MGMT) from the m rs1690652 (TableIDH1) at arginine 132 or IDH2 at arginine 172 is associated with secondary GBM, GBM that has arisen from lower grade glioma. All lines were found to be wild type for IDH1and IDH2 so can be regarded as glioblastoma, IDH-wildtype.Mutation of the gene encoding isocitrate dehydrogenase (NADP(+)) 1,  of the lines. Homozygous deletion of PTEN was detected in three lines and homozygous single nucleotide variants (SNVs) that were predicted to be pathogenic14 were present in five others. TP53 nonsynonymous SNVs were infrequent, with a homozygous predicted pathogenic missense SNV (G105C) in SJH1 and a homozygous neutral missense SNV (R110L) in JK2. At least half of the lines contained potential pathogenic changes in GBM-associated receptor tyrosine kinase (RTK) genes. Amplification of the oncogenic vIII variant of EGFR (EGFRvIII) was present in one of the lines (BAH1) and copy number gain of wild type EGFR was detected in another (RN1). Two further lines (HW1 and SB2b) contained pathogenic SNVs in EGFR that have only been reported previously in GBM15. Missense SNVs also were detected in MET and EPHA2, including a substitution in the latter that creates a variant (EphA2 R721Q) with altered signalling. Amplification of MYC, detected in only 1.5% of GBM17, was present in the cell line established from a long-term survivor (RKI1). Nonsynonymous single nucleotide variant calls for each of the cell lines, their zygosity and predicted measures of their pathogenicity are listed as Supplementary Data To catalogue the genotype of each GBM cell line, we performed exome sequencing. Genomic alterations characteristic of GBM were common among the 12 lines Fig. . Most fr4. These subtypes resemble distinct normal neural cell types, have different prognoses, respond differently to treatment and are associated with characteristic genetic alterations4, thus these distinctions appear to have patho-biological significance. Since the introduction of this classification schema by The Cancer Genome Atlas consortium, reservations have been expressed concerning the identity of the neural GBM subtype. Greatest support in the literature is found for the proneural, classical and mesenchymal subtypes18, with the suggestion that neural GBM likely represents normal brain tissue containing a small percentage of tumour cells19, an observation that could account for this subtype lacking characteristic genetic alterations20. To molecularly subtype the tumour tissue from which our GBM cell lines were derived, we measured RNA expression and performed hierarchical cluster analysis , contained a splice junction mutation (HW1) and showed gain of a premature STOP codon . PTEN expression also was not detected in a line (MN1) in which no mutations were detected in the coding sequence or splice junctions of the PTEN gene by exome sequencing. Increased expression of c-myc in the cell line (RKI1) with MYC amplification also was confirmed by western blot  and are employed to isolate these cells by flow cytometry or affinity capture. We therefore investigated the expression of GSC markers by flow cytometry in cultured GBM cell lines Fig. , includiMet Fig. . Our finMet Fig. ; intereslot Fig. . InteresDH1 Fig. , was conDH1 Fig. .Figure 511. Despite their clear benefits and ease of use, the wider adoption of such cell lines is often restrained by several factors. Initiating the necessary collaborations, applying for human research ethics approval and establishing cell lines from patient tumour tissue requires the investment of significant time and effort. Alternatively, sourcing such lines from other laboratories often comes with limited understanding regarding the origin and phenotype of the cells received as well as a lack of familiarity with working with them. Having experienced both scenarios, we have tried to increase investigator access to, and confidence with using, such cell lines by compiling a meaningfully-sized reference collection of extensively-characterised, low-passage, serum-free, patient-derived GBM cell lines, along with bespoke tools for working with them, which we hope will lead to more widespread use of this more relevant resource for investigating human GBM. While a number of laboratories have reported GBM cell line and mouse xenograft models of GBM, and a larger publicly-available, partially-phenotyped, GBM cell line collection exists26, we believe the practical size of our collection, coupled with the extent and practical-focus of its genotypic and phenotypic characterisation, meets a need in the GBM research community for a reference collection suitable for acquiring en bloc for laboratories yet to make the switch to using such cell lines or alternatively as a reliable source of individual lines with defined phenotypes and genotypes from which other laboratories can supplement their existing resources.Many preclinical and laboratory investigations of human GBM use cell lines. Historically these have been maintained in serum-supplemented medium that, while providing growth factors and other mitogens, introduces genotoxic stress. This, coupled with extensive passaging, produces cell line and xenograft models whose phenotypes diverge significantly from their tumour of origin. Low passage, patient-derived GBM cell lines that are maintained in serum-free medium supplemented with EGF and FGF2, have more recently been adopted by many investigators to circumvent these pressures and produce models that more accurately recapitulate the cardinal features of GBM27. This retains the proneural, classical and mesenchymal nomenclature  and uses a smaller number of genes (50 for each subtype) to subtype GBM. When this smaller classifying gene set was used to subtype our tumour samples , all were classified with much lower (and often nonsignificant) normalised enrichment scores. In light of this experience, there may be advantages in using the original TCGA classification system, with its larger number of classifier genes, to distinguish proneural, classical and mesenchymal GBM, with the inclusion of the neural classifier to identify samples that contain few tumour cells.During the preparation of this manuscript, a revised TCGA classification system was reported for IDH-wild type GBMin vitro culture. That most of our GBM cell lines exhibited a mesenchymal gene expression signature, regardless of the subtype of their tumour of origin, was striking yet is an inconsistent finding in the literature28. That serum-free cell lines derived from mesenchymal patient tumours often produced xenografts of a different subtype, despite retaining their mesenchymal subtype in culture, has been observed independently28. Yet to be determined is whether the apparent subtype switching is the result of the emergence of pre-existing subpopulations of cells29 or represents inherent plasticity28. While our patient tumours may contain GBM cells of more than one molecular subtype, which could account for the subtype “switch” observed between patient tumours and the derived GBM cell lines , subtype differences between the cell lines and the xenografts they produce suggest some GBM cells may be plastic and that their phenotype can change in response to their environment. We anticipate that the heterogeneity inherent in this collection of low-passage, serum-free GBM cell lines will be helpful for resolving this and other issues of GBM cell biology.The key finding of our subtype analysis of matched patient tumours, GBM cells lines and xenografts was that low-passage, serum-free cell lines most often gave rise to xenografts of the same molecular subtype as the patient tumours from which they were derived, although frequently exhibited a different GBM subtype during EGFR alterations occurring in over half of GBM tumours20. This is a common observation and may be related to a requirement in vivo that is lost in culture. As we observed that omission of recombinant Egf from the culture medium increased expression of EgfrvIII in the BAH1 cell line (data not shown), it may be worthwhile to routinely establish GBM cell lines both in the presence and absence of Egf in the culture medium in order to attempt to increase the frequency at which Egfr/EgfrvIII-amplified cell lines are established.Interestingly, only one EgfrvIII-expressing and one Egfr-amplified cell line was established despite Investigations to characterise our GBM cell lines were performed between passage 8 and 15, at which time we considered them “established”. Each line has been passaged at least 30 to 50 times now without notable change in tumourigenicity, growth rate, morphology or antibiotic sensitivity. While proneural tumours are typically less aggressive, our proneural xenograft-forming cell lines did not have the longest median xenograft survival  suggesting this behaviour may not apply to xenograft models. However, our sample size is small and larger numbers will be required to confirm this.32, investigations of GBM metabolism33, microRNA function in GBM34, GBM sensitivity to ionising radiation35, PET/MRI imaging of GBM37, GBM cell response to environmental stiffness38 and the evaluation of novel agents for treating GBM45. In light of this demonstrated utility, we anticipate this GBM cell line reference collection, and accompanying set of lentiviral plasmids, will both prove to be valuable resources for the scientific research community.In our hands, as well as in other laboratories, the GBM cell lines have proven useful for a variety of purposes. These include the identification and validation of GBM- and GSC-associated therapeutic targets13. These were cultured as adherent monolayers in matrigel (BD Biosciences)-coated vessels using RHB-A stem cell culture medium (StemCells Inc) supplemented with 20 ng/ml EGF (Gibco) and 10 ng/ml FGFb (Gibco) and containing 100 U/ml penicillin and 100 μg/ml streptomycin, or as tumourspheres using StemPro NSC SFM (Invitrogen). Cells were cultured in 5% CO2/95% humidified air at 37 °C. All cell lines were routinely tested for mycoplasma and confirmed to be mycoplasma-free.Patient tumour tissue was collected from patients undergoing surgery at the Royal Brisbane and Women’s Hospital (RBWH), with informed consent and human ethics approval from the QIMR Berghofer Medical Research Institute and RBWH human research ethics committees. All human studies have been performed in accordance with the ethical standards laid down in the 2013 version of the 1964 Declaration of Helsinki. Tumour tissue was examined by a neuropathologist (TR) to determine tumour type and grade. Patient-derived cell lines were established as reported previouslyhttps://www.atcc.org/STR_Database.aspx) using the standard match threshold of 80%.Short tandem repeat (STR) profiling to establish the unique genomic identity of each cell line and exclude cross-contamination was performed by the QIMR Berghofer Medical Research Institute Analytical Facility. Alleles for 10 human loci  were assayed and compared with the ATCC STR database -5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium] proliferation assays were performed using a CellTiter 96 AQueous One Solution cell proliferation assay kit (Promega). Cells were incubated with 20 μl of MTS reagent and incubated for one hour at 37 °C. The ratio of absorbance in the test wells to control wells (containing culture medium and no cells) was calculated as relative MTS activity and used as a surrogate for the number of viable cells in culture. Average relative MTS activity from three replicate wells was plotted against time and the doubling time calculated using GraphPad Prism software v.6.0 .Cells were seeded at a density of 2 × 1047 (a gift from John Silke). The chimaeric human CMV enhancer/chicken beta-actin promoter from pCAGIG48 (a gift from Connie Cepko) was subcloned in place of the ubiquitin promoter in both vectors and firefly luciferase was subcloned from pGL2 Basic (Promega) to generate pF CAG luc puro and in place of G147EV16 to produce pF CAG luc hygro. pF CAG luc IRES neo was created by cloning an IRES-neo cassette into pF CAG luc hygro in place of PGK-hygro. The IRES sequence was amplified by PCR from pIRES2-DsRed-Express (Clontech) and the neo sequence was amplified from pSuperior neo + GFP (OligoEngine). Genes of interest can be subcloned between the unique BamHI and NheI restriction sites in place of luciferase. pF CAG BFP2 IRES neo was created by cloning PCR-amplified BFP2 from pBAD-mTagBFP249  between the BamHI and NheI restriction sites of pF CAG luc IRES neo.Lentiviral expression plasmids were derived from pF_U_MCS_SV40Puro and pF_U_G147EV16_PGK_Hygro50  and are designed to confer resistance to puromycin, hygromycin B, G418 or blasticidin S. These were created by first destroying the MluI restriction site of lentiCRISPRv2 at nucleotide position 231 by MluI digestion followed by Klenow end-filling and re-ligation to create lentiCRISPRv2 puro, then cloning P2A-antibiotic resistance cassettes between the MluI and BamHI restriction sites of lentiCRISPRv2 puro. The P2A sequence was from lentiCRISPRv2, the hygromycin resistance gene cassette from pF CAG luc hygro, the neomycin resistance gene cassette from pF CAG luc IRES neo, and the blasticidin resistance gene cassette from pcDNA6TR (Invitrogen). Gene fusions were created by overlapping PCR. Short guide sequences can be cloned between the BsmBI restriction sites as previously described50. Cas9-only and sgRNA-only derivatives were constructed as shown in Supplementary Fig. https://media.addgene.org/cms/filer_public/53/09/53091cde-b1ee-47ee-97cf-9b3b05d290f2/lenticrisprv2-and-lentiguide-oligo-cloning-protocol.pdf).CRISPR/Cas9 plasmids were constructed from lentiCRISPRv2L-glutamine, 1 × non-essential amino acids, 1 × sodium pyruvate and 10% foetal bovine serum. The transfection medium was replaced the next day with 10 ml Opti-MEM supplemented with 1 × L-glutamine, 1 × non-essential amino acids and 1 × sodium pyruvate. Lentiviral supernatant was harvested 24 hours later, filtered through a 0.4 μm syringe filter and stored as 1 ml aliquots at −80 °C.Lentivirus was produced in 10 cm diameter petri dishes from 70–80% confluent HEK293FT cells transfected with 3 μg lentiviral plasmid, 2 μg pVSV-G (Addgene #8454) and 5 μg psPAX2 (Addgene #12260), using 72 μl of lipofectamine 2000 in 3 ml of optiMEM medium. Opti-MEM was added to a final volume of 8 ml, containing 25 μM chloroquine, 1 × GBM cell lines were transduced with lentivirus in matrigel-coated 6-well tissue culture plates in 4 ml of RHB-A medium by adding 1 ml of unconcentrated lentivirus and 1 μg/ml polybrene followed by centrifugation at room temperature for 45 minutes at 440 g. Virus-containing medium was replaced next day with fresh RHB-A medium and antibiotic selection commenced 48 hours after lentiviral transduction began.th edition 2013 and the “Queensland Animal Care and Protection Act 2001”.GBM xenograft models were initiated in 5-week old NOD/SCID mice housed under pathogen-free conditions. For intracranial cell injections 150,000 cells in 2 μl of 10 ng/ml laminin in PBS were injected 3 mm below the brain surface, 1.6 mm rostral of the bregma and 0.8 mm right of the midline, using a 25G Hamilton needle and a 2 μl syringe in a stereotaxic frame. Mice were anaesthetised with 2% isoflurane (Abbott) in oxygen at a flow rate of 0.8 litres per minute and given 100 μg of carprofen (Pfizer) subcutaneously for analgesia. The burr hole through which the cells were injected was sealed with bone wax and the midline scalp incision was closed with Vetbond (3M) tissue adhesive. Mice were euthanased when they exhibited signs of significant morbidity . All studies were conducted according to protocols approved by the Animal Ethics Committee of the QIMR Berghofer Medical Research Institute. The “Principles of laboratory animal care”  were followed as well as the “Australian code of practice for the care and use of animals for scientific purposes”, 82+ and Ca2+) intraperitoneally into isoflurane-anaesthetised NOD/SCID mice using an IVIS Spectrum In Vivo Imaging System (Perkin Elmer).Bioluminescence imaging of intracranial xenograft tumours was performed 5 minutes after injecting 0.5 mg of luciferin in 100 μl of DPBS  with RNase A treatment. Exome sequencing was performed by the Beijing Genomics Institute (BGI) using Truseq (BAH1 and WK1) or SureSelect (the remainder) exon capture and Illumina HiSeq 2000 technology. Data filtering, read alignment, SNV calling, annotation and statistics were performed by BGI.52.Where investigated, gene copy number was determined by inspection of exon reads using Integrative Genomics ViewerP value to be calculated as an estimate of gene measurements relative to background. P < 0.05 for all samples on a beadchip for a given probe was used as a cutoff to compile gene expression datasets. Where genes were represented by multiple probes, the highest value probe was used for gene-level summaries . Illumina idat files are available for download (qimrberghofer.edu.au/q-cell/) and GenomeStudio-processed probe-level datasets . RNA was extracted from patient tumour tissue, adherent cell cultures and xenograft tumours using RNeasy mini kits (Qiagen). Biotinylated cRNA was prepared using TotalPrep RNA amplification kits (Ambion). Microarray hybridisation and Cy3-streptavidin labelling was performed according to recommended protocols (Illumina). BeadChips were imaged with an iScan beadchip reader (Illumina) running BeadStudio software (Illumina). Raw data was exported to GenomeStudio (Agilent) where it was quantile normalised and background subtracted. Illumina beadchips allow a detection http://mev.tm4.org) with gene sets reported for proneural, classical and mesenchymal GBM4, a Pearson distance metric and average linkage criteria, and also by gene set enrichment analysis54 (GSEAv2.2.4) in the pre-ranked mode using the proneural, classical and mesenchymal.rnk files in the Molecular Signatures Database v6.0. Gene ranking was according to z-scores for RNA expression determined by microarray analysis. Heatmaps were created using Excel.GBM molecular subtyping was performed by hierarchical cluster analysis using MeV (RNA was extracted from frozen cell pellets using a Qiagen AllPrep DNA/RNA Minikit (Cat No: 80204). RNA integrity was assessed using an Agilent RNA 6000 Eukaryote Total RNA kit (Cat. No: 5067–1511) and Bioanalyzer 2100 instrument. All RNA samples had an RNA Integrity Number (RIN) >9.0. RNA libraries were prepared using an Illumina TruSeq Stranded mRNA Library Preparation Kit Set A (Cat. No: RS-122-2101). RNA libraries were sequenced using an Illumina NexSeq® 500/550 High Output Kit v2 (150 cycles) (Cat. No: FC-404-2002) and NexSeq® 550 instrument.Paired-end fastq files had adapters trimmed and flanking “N” bases removed for each paired-end read using Cutadapt v1.18. Trimmed files were aligned to the human GRCh37_ICGC_standard_v2 reference using STAR v2.5.2a. Quality control was performed using RNA-SeQC v1.1.8. Expected read counts and FPKM were calculated using RSEM v1.2.30, with a forward probability of 0 as the reads were stranded and derived from reverse strand. Finally, expected counts and FPKM for both genes and isoforms, were matched to gene/transcript annotation information using in-house scripts to provide expected counts and FPKM summary files for each sample.TM TGXTM Precast Midi Protein Gels  and transferred onto Immun-Blot® PVDF Membrane (Bio-Rad). Membranes were blocked in 5% BSA/TBST, washed in TBST, and protein levels determined using the following antibodies: EGFR , c-myc , PTEN  and β-actin .Cells  were washed 3 × in ice-cold PBS, then lysed on ice with ice-cold RIPA buffer  containing cOmpleteTM, Mini, EDTA-free Protease Inhibitor Cocktail (Merck) and PhosSTOP (Merck). Cells were disrupted by repeated passage through a 27G needle and crude lysates centrifuged at 20,000 g for 15 mins at 4 °C. Supernatants were collected, and protein content determined by Bio-Rad Protein Assay. 80 μg of total protein was loaded for each cell line per lane and proteins separated on 8–16% Criterionhttps://www.nature.com/articles/ni.3693). Peptides were desalted and separated on a C18 analytical column (Waters) interfaced to an Orbitrap Elite mass spectrometer (Thermo Fisher Scientific). All raw files were searched against human proteome sequences from UniProt using the based label-free quantification algorithm in MaxQuant (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4159666/) (protein and peptide FDR = 0.01). Proteins of interest were extracted manually from the total list.GBM cell lines were grown as tumourspheres for three days. Cells were lysed in buffer containing 2% SDS, 100 mM Tris pH 7.6, protease and phosphatase inhibitors followed by precipitation with acetone. The protein precipitate was resuspended in 8 M urea, followed by reduction with DTT, alkylation with iodoacetamide and digested with trypsin using a standard protocol (Flow cytometry was performed with an LSR Fortessa (BD Biosciences) for data acquisition and fluorochrome-conjugated antibodies targeting CD133 , CD15 , CD44 , CD49f , EGFR , EGFRvIII , PDGFRα , EphA2 , EphA3 , EphA4 , FGFR1 , FGFR2 , FGFR3 , c-Met , Sox2 , Nestin , GFAP , β-III tubulin  and MBP . Cells were incubated with antibody on ice for 30 minutes in PBS containing 2% FBS. Where required, cells were fixed and permeabilised using Intracellular Fixation & Permeabilization Buffer (eBioscience) and stained with antibodies in 1 × Permeabilization Buffer. Data analysis was performed using Flowjo (Treestar) software.P < 0.05 was considered statistically significant.Unless otherwise noted, data are presented as the mean and standard error of the mean. GSEA reports normalised enrichment scores with the associated false discovery rate and familywise-error rate. https://www.addgene.org/Brett_Stringer/.All GBM cell lines are available to research groups with a standard materials transfer agreement and can be obtained by contacting the corresponding author or via the website, qimrberghofer.edu.au/q-cell/. Cell lines (not expressing luciferase) will be distributed from passage 10 onwards. Lentiviral plasmids can be obtained from Addgene at Supplementary Figures S1-4Supplementary Tables S1-2Dataset 1Dataset 2Dataset 3Dataset 4Dataset 5Dataset 6


Radiotherapy plays an important role in the multimodal treatment of breast cancer. The response of a breast tumour to radiation depends not only on its innate radiosensitivity but also on tumour repopulation by cells that have developed radioresistance. Development of effective cancer treatments will require further molecular dissection of the processes that contribute to resistance.Radioresistant cell lines were established by exposing MDA-MB-231, MCF-7 and ZR-751 parental cells to increasing weekly doses of radiation. The development of radioresistance was evaluated through proliferation and colony formation assays. Phenotypic characterisation included migration and invasion assays and immunohistochemistry. Transcriptomic data were also generated for preliminary hypothesis generation involving pathway-focused analyses.Proliferation and colony formation assays confirmed radioresistance. Radioresistant cells exhibited enhanced migration and invasion, with evidence of epithelial-to-mesenchymal-transition. Significantly, acquisition of radioresistance in MCF-7 and ZR-751 cell lines resulted in a loss of expression of both ERα and PgR and an increase in EGFR expression; based on transcriptomic data they changed subtype classification from their parental luminal A to HER2-overexpressing (MCF-7 RR) and normal-like (ZR-751 RR) subtypes, indicating the extent of phenotypic changes and cellular plasticity involved in this process. Radioresistant cell lines derived from ER+ cells also showed a shift from ER to EGFR signalling pathways with increased MAPK and PI3K activity.This is the first study to date that extensively describes the development and characterisation of three novel radioresistant breast cancer cell lines through both genetic and phenotypic analysis. More changes were identified between parental cells and their radioresistant derivatives in the ER+ (MCF-7 and ZR-751) compared with the ER- cell line (MDA-MB-231) model; however, multiple and likely interrelated mechanisms were identified that may contribute to the development of acquired resistance to radiotherapy.The online version of this article (10.1186/s13014-019-1268-2) contains supplementary material, which is available to authorized users. Radiotherapy (RT) is a commonly used adjuvant treatment modality for a variety of solid cancers. Up to 83% of breast cancer patients benefit from radiotherapy either with curative or palliative intent . MultiplImproved understanding of the mechanisms underlying acquired radioresistance and the development of strategies to circumvent this clinical problem are required. Previous studies have shown that multiple factors are implicated in the development of radioresistance, including deregulated signalling pathways , oncogenic miRNA overproduction, enhanced DNA damage responses, the presence of cancer stem cells, epithelial-to-mesenchymal transition (EMT) and alterations in cancer metabolism, along with the effect of the tumour microenvironment itself (including hypoxia) . Many stIn comparison to the investigation of chemoresistance, the mechanisms underlying radioresistance development are poorly understood, partly due to a lack of radioresistant model systems. The use of global approaches to investigate resistance mechanisms is gaining interest, as this allows for the study of multiple pathways simultaneously and provides an overview of complex biological systems and response to treatment . In this− 1 penicillin and 50 mg ml− 1 streptomycin and incubated at 37 °C in a humidified atmosphere with 5% CO2. Cell lines obtained from the American Type Culture Collection  were authenticated by short tandem repeat (STR) profiling performed at Health England . All cell line DNA samples tested matched 9 of 9 tested core alleles in DNA from known cell line samples confirming their identity. All experiments were performed using cells, maintained at low passage number from these frozen stocks.Cell culture reagents were obtained from Gibco Thermo Fisher Scientific , unless otherwise stated. Human breast cancer cell lines ZR-751, MCF-7 and MDA-MB-231 were cultured in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% foetal calf serum (FCS), 50 U mlCells were irradiated using a Faxitron cabinet X-ray system 43855D . Radioresistant cell lines  were developed from their respective parental cell lines  by weekly exposure to single fractions of radiation. An initial dose of 2 Gy was followed by weekly incremental doses of 0.5 Gy for 12 weeks. During this period cells received a total radiation dose of 57 Gy. Cells were subsequently maintained with further weekly doses of 5 Gy.2O and, when dry, 50 μl SRB dye ) was added to each well and incubated for 30 min. Plates were washed 4 times in 1% glacial acetic acid and, when dry, 150 μl of 10 mM Tris-NaOH buffer (pH 10.5) was added to each well. The plates were incubated on a shaker for 60 min. Optical density was measured at 540 nm using a Biohit BP800 spectrophotometer  and Wallac 1420 Manager program . The half maximal inhibitory concentrations  were calculated using the GraphPad prism 7 package.Cells were seeded into 96 well plates (500 cells/well) and incubated for 24 h. Cells were drug-treated or exposed to radiation and fixed between 24 and 144 h after treatment by the addition of 50 μl cold 25% trichloracetic acid  per well at 4 °C for 1 h. Plates were washed in H3 cells/plate) and incubated for 24 h before radiation treatment. Once visible colonies had formed (approximately 50 cells per colony) in the untreated control group (approximately 10–14 days post-seeding) the plates were washed twice in PBS before fixing the cells with the addition of 5 ml of 1,9-dimethyl-methylene blue zinc chloride double salt . After 45 min the plates were washed and allowed to air dry before colonies were counted. Analysis was performed by calculating plating efficiencies and survival fractions for control and treatment plates . TAnalysis of transcriptomic data from ER+ parental and RR cell lines in respect of the WNT signalling pathway was investigated due to its reputed role in EMT and radioresistance . The WNT50: MCF-7 13.36 μM, MCF-7 RR 6.43 μM) and a significant reduction in migration, with a dose of 5 μM decreasing the migratory potential of the RR cell line to parental levels . Western blotting and IHC showed that the RR phenotype in the cell lines derived from ER+ cells was characterised by the loss of ERα and PgR expression, along with a gain in total EGFR expression  of 67 breast cancer cell lines. The MDA-MB-231 parental and RR cell lines, both treated and untreated, clustered tightly with each other in the dendrogram branch enriched for the basal breast cancer subtype. Both treated and untreated MCF-7 and ZR-75-1 parental cell lines were classified as luminal A whereas their RR derivates clustered independently and were enriched for normal-like (ZR-751 RR) and HER2-overexpressing (MCF-7 RR) intrinsic subtypes /protein kinase B (AKT) cascade is frequently overactive in a wide range of cancers and can trigger a cascade of responses related to cell survival and metabolism , 67. It In breast and other cancers radiation-induced proliferation has been linked with activation of EGFR and downstream components of the mitogen-activated protein kinase (MAPK) cascade, including phospholipase-C, Ras, and Raf-1 –73 and cThe use of multiple techniques ranging from gene to protein to functional experiments, which led to the validation of our results through independent means, represents one of the main strengths of this study. Additionally, the development of ER+ and ER- RR cell lines allowed for comparisons to be made between different molecular breast cancer subtypes. The aim of our study was to characterise these RR cell lines and identify pathways that could be related to radioresistance, rather than focusing on the reversal of radioresistance itself. However, following our successful characterisation, we now aim to use these cell lines in future studies to target these identified pathways and to identify biomarkers (genetic and secretomic signatures) that could be used for determining radiosensitivity and for the assessment of a tumour’s response to radiotherapy.In this study we developed a novel model to help improve the understanding and characterisation of radioresistant breast cancer cells and identified several important and likely interrelated networks contributing to the development of radioresistance. ER+ derived RR cell lines were characterised by a shift towards a more invasive mesenchymal phenotype with changes in oestrogen regulation, gain of EGFR signalling and change in subtype classification. The ER- cell line possessed these characteristics at the outset and hence its phenotype changed relatively little with the development of radioresistance. Here we have begun to dissect the mechanisms and signalling pathways involved in the development of radioresistance. Models of resistant disease as developed and examined in this study will be instrumental in future research and will aid the development of new therapeutic strategies for patients that either fail to respond or develop recurrent disease.Additional file 1:Table S1. RIN values for all samples used in gene expression analysis. (XLSX 10 kb)Additional file 2:Table S2. Overview of samples  used in each experiment or analysis. (XLSX 15 kb)Additional file 3:Figure S1. Colony formation assay comparing MCF-7, MCF-7 RR and MCF-7 rr (radioresistant cell line not radiated for 6 months (24 passages)) cell lines. (TIF 51 kb)Additional file 4:Figure S2. ICC and IHC staining of EMT markers in ZR-751 parental and RR cell lines. (TIF 2384 kb)Additional file 5:Figure S3. ICC and IHC staining of EMT markers in MCF-7 parental and RR cell lines. (TIF 2391 kb)Additional file 6:Table S3. Gene lists from a published EMT signature [ignature  and WNT ignature  applied Additional file 7:Figure S4. ICC and IHC staining for signalling receptors in ZR-751 parental and RR cell lines. (TIF 2818 kb)Additional file 8:Figure S5. ICC and IHC staining for signalling receptors in MCF-7 parental and RR cell lines. (TIF 2708 kb)Additional file 9:Figure S6. (A) SRB at 72 h and (B) Scratch assay at 24 h showing the effects of gefitinib on ZR-751 and ZR-751 RR cell lines . (TIF 170 kb)Additional file 10:Figure S7. Gene expression heatmap based on Pearson correlation hierarchical clustering with average linkage using a published list of intrinsic subtype genes [genefu R package Single Sample Predictor (SSP) algorithm [pe genes . Intrinslgorithm ; red=hig


Despite the clear involvement of V-ATPases in cancer, the therapeutic use of V-ATPase-targeting small molecules has not reached human clinical trials to date. Thus, V-ATPases are emerging as important targets for the identification of potential novel therapeutic agents. We identified a bisbenzimidazole derivative (V) as an initial hit from a similarity search using four known V-ATPase inhibitors (I–IV). Based on the initial hit (V), we designed and synthesized a focused set of novel bisbenzimidazole analogs (2a–e). All newly prepared compounds have been screened for selected human breast cancer  and ovarian cancer  cell lines, along with the normal breast epithelial cell line, MCF10A. The bisbenzimidazole derivative (2e) is active against all cell lines tested. Remarkably, it demonstrated high cytotoxicity against the triple-negative breast cancer (TNBC) cell line, MDA-MB-468 (IC50 = 0.04 ± 0.02 μM). Additionally, it has been shown to inhibit the V-ATPase pump that is mainly responsible for acidification. To the best of our knowledge the bisbenzimidazole pharmacophore has been identified as the first V-ATPase inhibitor in its class. These results strongly suggest that the compound 2e could be further developed as a potential anticancer V-ATPase inhibitor for breast cancer treatment.The vacuolar (H The V-ATPase proton pump is a macromolecular complex composed of at least 14 subunits organized into two functional domains, V1 and V0. The domain V1 is responsible for ATP hydrolysis and V0 provides the transmembrane proton channel imidazol]-2′-yl)phenol (compound 1) with appropriate substituted alkyl halides in the presence of cesium carbonate in dimethyl formamide (DMF) at reflux temperature (2a–e) using methanol and chloroform (3:7). We quickly developed a fast and efficient synthetic procedure to prepare novel bisbenzimidazole analogs using the one pot procedure. A general synthesis of bisbenzimidazole derivatives (perature . The cru+)-ATPase in breast as well as ovarian cancer cell lines -6-(1-methyl-4-piperazyl)benzimidazole trihydrochloride (compound 6-(4-Methylpiperazin-1-yl)-2'-(4-((1-methylpiperidin-4-yl)oxy)phenyl)-1H,3'H-2,5'-bibenzo[d]imidazole (2a) Yield: 12%, brown solid powder. m.p.: 165–166 °C; 1H-NMR  δ 2.06–2.18 , 2.55 , 2.70 , 2.89-3.00 , 3.19–3.28 , 4.74 , 7.06-7.09 , 7.18 , 7.53 , 7.72 , 7.97 , 8.09 , 8.29 ; MS (ESI): m/z 522.6 [M + H]+; HRMS (ESI): m/z calcd for C31H35N7O [M + H]+ 522.2981; obsd 522.2971.N,N-Dimethyl-3-(4-(6-(4-methylpiperazin-1-yl)-1H,3'H-imidazol]-2'-yl)phenoxy)propan-1-amine (2b). Yield: 15%, brown solid powder. m.p.: 171–172 °C; 1H-NMR  δ 1.90 , 2.20 2), 2.24 , 2.44 , 3.08–3.16 , 3.36–4.02 , 4.09 , 6.91–6.95 , 7.12 , 7.36–7.49 , 7.58–7.72 , 7.95–8.03 , 8.14 , 8.20–8.33 , 12.60 , 12.96 ; MS (ESI): m/z 510.6 [M + H]+; HRMS (ESI): m/z calcd for C30H35N7O [M + H]+ 510.2984; obsd 510.2983.N,N-Dimethyl-2-(4-(6-(4-methylpiperazin-1-yl)-1H,3'H-imidazol]-2'-yl)phenoxy)ethanamine (2c). Yield: 13%, yellow solid powder. m.p.: 197–198 °C; 1H-NMR  δ 2.44 3), 2.65 , 3.10–3.13 , 3.34–3.39 , 4.13 , 6.91–6.93 , 7.12 , 7.38–7.46 , 7.65 , 7.98 , 8.15 , 8.27 , 12.60 , 12.96 ; MS (ESI): m/z 496.4 [M + H]+; HRMS (ESI): m/z calcd for C29H33N7O [M + H]+ 496.2825; obsd 496.2820.2'-(4-(2-Methoxyethoxy)phenyl)-6-(4-methylpiperazin-1-yl)-1H,3'H-2,5'-bibenzo[d]imidazole (2d). Yield: 22%; yellow solid powder; m.p.: 208–209 °C; 1H-NMR  δ 2.35 , 2.62–2.65 , 3.16–3.18 , 3.39 , 3.68–3.70 , 4.05–4.08 , 6.98–7.00 , 7.07 , 7.46 , 7.52 , 7.57–7.58 , 7.95 , 8.16 ; 13C-NMR  δ 44.59, 50.25, 54.68, 57.85, 67.05, 70.63, 100.75, 114.57, 114.90, 120.98, 121.65, 124.17, 128.10, 134.5, 138.0, 148.06, 152.24, 153.70, 160.79, 171.56; MS (ESI): m/z 483.5 [M + H]+; HRMS (ESI): m/z calcd for C28H30N6O2 [M + H]+ 483.2508; obsd 483.2498.2'-phenyl)-6-(4-methylpiperazin-1-yl)-1H,3'H-2,5'-bibenzo[d]imidazole (2e). Yield: 16%; pale yellow solid powder; m.p.: 247–248 °C; 1H-NMR  δ 0.98 3), 1.70 , 2.24 , 3.12–3.30 , 4.11 , 6.91-6.96 , 7.13 , 7.58-7.72 , 7.28–7.49 , 7.94–8.02 , 8.13 , 8.20–8.35 , 12.58 , 12.94 ; 13C-NMR  δ 28.74, 29.23, 44.55, 46.94, 50.28, 54.68, 65.24, 100.10, 114.59, 114.97, 121.02, 121.32, 124.21, 128.14, 148.08, 152.32, 153.92, 161.14; MS (ESI): m/z 509.7 [M + H]+; HRMS (ESI): m/z calcd for C31H36N6O [M + H]+ 509.3029; obsd 509.3028.V), and bisbenzimidazole analogs 2a–e in the selected human breast cancer cell lines MDA-MB-231 , MDA-MB-468 , MCF-7  and the normal breast epithelial cell line, MCF10A, and the ovarian cancer cell lines, A2780, Cis-A2780, and PA-1 . Human breast cancer cell lines and the human ovarian cancer cell line (PA-1) were purchased from ATCC . The cisplatin-sensitive human ovarian carcinoma cell line, A2780, was obtained from Sigma-Aldrich. The cisplatin-resistant human ovarian cell line, Cis-A2780, was produced in our laboratory, as described in the literature [v/v) heat-inactivated fetal bovine serum , 100 U/mL penicillin G and 100 U/mL streptomycin . Cultures were maintained at 37 °C in a humidified atmosphere containing 5% CO2 and were passaged by trypsinization after reaching 80–90% confluence.We studied the antiproliferative activity of an initial hit (compound terature . MDA-MB-3) were seeded into each well of 96-well plates and incubated overnight. Dimethyl Sulfoxide (DMSO) stock solutions of the compounds  were diluted in corresponding media and exposed to different concentrations for 48 h. All three independent experiments were performed in quadruplicates. Untreated cells were used as a negative control and data were presented as the mean ± standard deviation (S.D.). The absorbances at 492 nm were measured using a Microplate Reader . The compound concentration that inhibited cell growth by 50% of the untreated control (IC50) was calculated from the dose response curves constructed by plotting percentages of cell viability versus drug concentrations using nonlinear regression analysis by GraphPad Prism Software 7 .CellTiter 96 AQueous One Solution cell proliferation assay (MTS) ,30 was u6 cells per mL in the same buffer and placed on ice. H+ uptake was initiated by the addition of MDA-MB-231 cells  to pre-warmed HBSS (2.4 mL) containing AO  and placed in a cuvette. AO fluorescence was measured at an excitation wavelength of 495 nm and an emission wavelength of 540 nm using the LS-50B Luminescence Spectrometer . Nigericin  was added to collapse the pH gradient and unquench the AO fluorescence (See 1a and 1b). MDA-MB-231 cells  were treated with the standard V-ATPase inhibitor Baf A1 (1 μM), along with compounds V, 2d, and 2e (10 μM), for 20 min followed by addition of AO  for the proton pump activity . A decrease in the fluorescence intensities per min of Baf A1 and the potent compounds  was calculated and is expressed as a percentage of the control (mean ± SD of two independent experiments) (The proton pump activity was assessed by using the AO fluorescence quenching method . Bafilomriments) . V) as an initial hit compound. Synthesis and anticancer screening of a focused set of novel bisbenzimidazole derivatives indicated that they were potent against selected breast and ovarian cancer cell lines in vitro. The selected bisbenzimidazole analogs (2d and 2e) have demonstrated selective potency towards the TNBC cell line, MDA-MB-468. The compound 2e potently inhibited the proton pump activity, which is largely responsible for the acidification, and it showed selective anticancer activity. To the best of our knowledge, the bisbenzimidazole pharmacophore has been identified as the first V-ATPase inhibitor in its class. Together, our findings demonstrated that the bisbenzimidazole analog (2e) could be further developed as an anticancer vacuolar (H+)-ATPase inhibitor for the treatment of breast cancer.In conclusion, starting from the virtual screening practice using known small molecule V-ATPase inhibitors, we identified a bisbenzimidazole analog (


The prepared substances were screened for their in vitro antitumor activity on the osteosarcoma (HOS) and breast adenocarcinoma (MCF7) human cancer cell lines, where 2 showed moderate antitumor effect . The complex 2 was further tested on a panel of six others human cancer cell lines, including the malignant melanoma (G361), cervix carcinoma (HeLa), ovarian carcinoma (A2780), cisplatin-resistant ovarian carcinoma (A2780R), lung carcinoma (A549) and prostate adenocarcinoma (LNCaP). This substance was found to be moderate antitumor effective against G361 (IC50 = 17.3 μM), HeLa (IC50 = 31.8 μM) and A2780 (IC50 = 19.2 μM) cell lines. The complex 2 was also studied by NMR for its solution stability and by ESI-MS experiments for its ability to interact with biomolecules, such as cysteine, glutathione or guanosine 5'-monophosphate.The platinum(II) oxalato complexes [Pt(ox)( Platinum carboxylates represent a notable group of transition metal complexes, which have been used for the treatment of various types of cancer for many years ,2,3. Vari.e., N-donor ligands) and leaving  ligands is one of the crucial challenge of modern bioinorganic chemistry ; L1=2-chloro-N6-(2-methoxybenzyl)-9-isopropyladenine) and IC50(MCF7) = 3.6 µM ([Pt(ox)(L2)]; L2=2-chloro-N6--9-isopropyladenine). Utku et al. described the platinum(II) oxalato complexes with 2-phenylbenzimidazole ligand and their antibacterial and antifungal activity [et al. dealt with the [Pt(ox)(L3)]  and their cytotoxic effect against A549, B16-F1, B16-F10 and MDA-MB-231 cancer cells and BHK-21 and CHO non-cancer cells. The obtained results proved four reported oxalato complexes as less active against the named cancer cells (IC50(A549) = 12.6–60.6 µM, IC50(B16-F1) = 14.5–21.9 µM, IC50(B16-F10) = 16.6–38.0 µM, IC50(MDA-MB-231) = 16.6–25.1 µM) as compared with cisplatin (IC50(A549) = 2.7 µM, IC50(B16-F1) = 3.5 µM, IC50(B16-F10) = 4.2 µM, IC50(MDA-MB-231) = 1.4 µM)  (4Claza)2]+H}+ for 1), 678.9 m/z (3Braza)2]+H}+ for 2) and 679.0 m/z (4Braza)2]+H}+for 3), their adducts with different cations, namely 627.1 m/z (4Claza)2]+K}+ for 1), 611.1 m/z (4Claza)2]+Na}+ for 1), 716.9 m/z (3Braza)2]+K}+ for 2), 701.0 m/z (3Braza)2]+Na}+ for 2), 716.9 m/z (4Braza)2]+K}+ for 3) and 701.1 m/z (4Braza)2]+Na}+ for 3). The peak of the released N-donor ligand was found at 153.1 m/z , 197.0 m/z  and 197.1 m/z . The pseudomolecular peaks of the {[Pt(ox)(naza)2]−H}– species were detected by means of ESI− (electrospray ionization in the negative mode) mass spectrometry at 585.9 m/z (4Claza)2]−H}− for 1) and 676.0 m/z (3Braza)2]−H}– for 2, and: calc. 675.9; 85%; {[Pt(ox)(4Braza)2]–H}− for 3). The ESI- mass spectra of the studied compounds also contain the peaks whose mass correspond to the {[Pt(ox)(naza)]−H}− fragment (4Claza)]−H}− for 1; 478.1 m/z, calc. 477.9; 30%; {[Pt(ox)(3Braza)]−H}− for 2; 478.1 m/z, calc. 477.9; 65%; {[Pt(ox)(4Braza)]−H}− for 3) and {naza−H}− ligand .The platinum(II) oxalato complexes [Pt(ox)2] 1–3;  were pre1–3, as well as the starting compounds naza and K2[Pt(ox)2]∙2H2O, were studied by means of multinuclear and 2D NMR spectroscopy. All the 1H, 13C and 15N signals of free naza molecules were unambiguously detected in the spectra of corresponding platinum(II) complexes and assigned by means of the below-mentioned 2D NMR experiments. The significantly different 15N-NMR coordination shift values of the N1 (|Δδ| = 2.5–3.4 ppm) and N7 (|Δδ| = 114.0–115.1 ppm) atoms clearly proved the coordination of naza molecules through the N7 atoms. The 13C-NMR chemical shifts of the C11 and C12 atoms of the oxalate dianion (detected at 165.9–166.0 ppm) and the 195Pt chemical shifts, which equal −1770.1 (1), −1783.5 (2) and −1772.5 (3), correlate well with the values of the formerly reported platinum(II) oxalato complexes with 7-azaindole 2+ and/or cis-[Pt(OH)2(3Braza)2] in our case +H}+ species , which most probably contains a ring-opened product of the interaction with a monodentate bound oxalate dianion.ESI-MS was also used to study the ability of  mixture :1 v/v  complexes is based on the covalent binding of activated platinum(II) species to the nuclear DNA molecule of the tumour cells , which i1–3 were screened for their in vitro antitumor activity against two types of the human cancer cell lines - osteosarcoma (HOS) and breast adenocarcinoma (MCF7)  in the medium used. This compound showed the moderate in vitro anticancer activity, concretely 27.5 ± 3.4 μM against HOS and 18.3 ± 3.6 μM against MCF7 cells, which is comparable effect with that of cisplatin (IC50(HOS) = 25.4 ± 8.5 μM, IC50(MCF7) = 18.1 ± 5.1 μM)  > 50.0 μM, IC50(MCF7) > 50.0 μM). Nevertheless, it can be stated that the complex 2 exceeded the in vitro antitumor activity of oxaliplatin on HOS and MCF7 human cancer cell lines.The complexes a (MCF7) . In the  5.1 μM) . It has 2 was tested against next six human cancer cell lines, namely malignant melanoma (G361), cervix carcinoma (HeLa), ovarian carcinoma (A2780), cisplatin-resistant ovarian carcinoma (A2780R), lung carcinoma (A549) and prostate adenocarcinoma (LNCaP). It has been observed that its in vitro antitumor activity equals IC50 = 17.3 ± 3.1 μM , IC50 = 31.8 ± 6.2 μM , IC50 = 19.2 ± 3.7 μM  and IC50 > 50.0 μM  cell lines , 3-iodo-7-azaindole (3Iaza) and 5-bromo-7-azaindole (5Braza), which, similarly to 1 and 3, did not show any effect against both HOS and MCF7 cell lines up to the concentration of 10.0, 25.0, and 0.5 μM, respectively. Concerning all six platinum(II) oxalato complexes with different 7-azaindole derivatives together, it can be said that the biological activity, in terms of bioavailability, is strongly affected by the position of halogeno-substituent of the 7-azaindole moiety, because the solubility of the complexes with 3Claza, 3Braza and 3Iaza (10.0–50.0 μM) is significantly higher than that of the complexes involving the 7-azaindole derivatives substituted in the position 4 (4Claza and 4Braza) or 5 (5Braza), whose solubility did not exceed 1.0 μM in the medium used.As it is mentioned above, reported  analogou2[PtCl4]), potassium oxalate monohydrate (K2(ox)∙H2O), 4-chloro-7-azaindole (4Claza), 3-bromo-7-azaindole (3Braza), 4-bromo-7-azaindole (4Braza), cisplatin, oxaliplatin, cysteine (cys), reduced glutathione (GSH), guanosine 5'-monophosphate disodium salt (GMP) and solvents were purchased from Sigma-Aldrich Co.  and Acros Organics Co.  and used as received.Potassium tetrachloridoplatinate(II) .Electrospray ionization mass spectrometry (ESI-MS): Mass spectra were obtained on fresh methanol solutions and after 2 h and 12 h by an LCQ Fleet ion trap mass spectrometer using both the positive (ESI+) negative (ESI−) mode electrospray ionization technique . The 10 µM  solution of 2 in methanol was mixed together with the same volume of water , water solutions of the mixture of GSH (6 µM) and cys (260 µM) or water solution of GMP. 20 µL of the mixtures was analysed by means of flow injection analysis/mass spectrometry (FIA/ESI-MS) in both the positive and negative ionization modes 0 h, 2 h and 12 h after the preparation.NMR spectroscopy: 1H, 13C and 195Pt NMR spectra and two dimensional correlation 1H-1H gs-COSY, 1H-13C gs-HMQC, 1H-13C gs-HMBC and 1H-15N gs-HMBC experiments (DMF-7d solutions) were performed at 300 K on a Varian 400 device  at 400.00 MHz (1H), 100.58 MHz (13C), 86.00 MHz (195Pt) and 40.53 MHz (15N); gs = gradient selected, COSY = correlation spectroscopy, HMQC = heteronuclear multiple quantum coherence, HMBC = heteronuclear multiple bond coherence. 1H and 13C spectra were adjusted against SiMe4, while 195Pt spectra were calibrated against K2[PtCl6] in D2O found at 0 ppm. 1H-15N gs-HMBC experiments were obtained at natural abundance and calibrated against the residual signals of DMF . The splitting of proton resonances in the reported 1H-NMR spectra is defined as s = singlet, d = doublet, t = triplet, br = broad band, m = multiplet. The coordination shift  is calculated as Δδ = δcomplex − δligand. The stability studies of the DMF-7d and DMF-7d/H2O (9:1 v/v) solutions of 2 was carried out by means of 1H and 195Pt NMR after 1, 2, 3, 4 and 5 days of standing at laboratory temperature. 4Claza (for 1), 3Braza (for 2) or 4Braza (for 3) in 10 mL of hot (50 °C) ethanol was slowly poured into the solution of K2[Pt(ox)2]∙2H2O (0.5 mmol) in 10 mL of hot (50 °C) distilled water. The reaction mixtures were stirred at 50 °C for two days. The products, which formed, were filtered off, washed (5 mL of distilled water and 5 mL of ethanol) and dried at 40 °C platinum(II)Bis(4-chloro-7-azaindole)-κN7} Light grey solid; yield 80%; 1H-NMR : δ/Δδ = 13.41/1.34 , 8.71/0.49 , 7.98/0.30 , 7.37/0.17 , 6.79/0.21  ppm. 13C-NMR : δ/Δδ = 165.9 , 148.2/−1.6 (C-7a), 146.6/3.0 (CH-6), 138.4/3.8 (C-4), 129.3/1.9 (CH-2), 122.2/3.1 (C-3a), 117.5/1.9 (CH-5), 100.5/2.2 (CH-3) ppm. 15N-NMR : δ/Δδ = 145.6/3.4 (NH-1), 154.6/−114.6 (N-7) ppm. 195Pt NMR : δ = −1770.1 ppm. ESI MS (30 ev): m/z = 611.1 (M+Na), 585.9 (M−H), 434.0 (M−4Claza−H), 153.1 (4Claza+H), 151.0 (4Claza−H). Anal. Calc.: C, 32.7%; H, 1.7%; N, 9.5%. Found: C, 32.8%; H, 1.6%; N, 9.6%.2O,O’)platinum(II)Bis(3-bromo-7-azaindole)-κN7} Light grey solid; yield 75%; 1H-NMR : δ/Δδ = 13.49/1.32 , 8.82/0.48 , 8.11/0.23 , 8.09/0.31 , 7.31/0.10  ppm. 13C-NMR : δ/Δδ = 166.0 , 147.5/3.2 (CH-6), 147.0/−0.9 (C-7a), 130.6/4.0 (CH-4), 128.0/2.1 (CH-2), 122.6/3.3 (C-3a), 118.0/1.4 (CH-5), 89.3/1.6 (C-3) ppm. 15N-NMR : δ/Δδ = 143.5/2.5 (NH-1), 159.4/−115.1 (N-7). 195Pt NMR : δ = −1783.5 ppm. ESI MS (30 ev): m/z = 678.9 (M+H), 676.0 (M−H), 478.1 (M−3Braza−H), 197.1 (3Braza+H), 195.1 (3Braza–H). Anal. Calc.: C, 28.4%; H, 1.5%; N, 8.3%. Found: C, 28.4%; H, 1.5%; N, 8.3%.2O,O’)platinum(II)Bis(4-bromo-7-azaindole)-κN7} Light grey solid; yield 80%; 1H-NMR : δ/Δδ = 13.40/1.31 , 8.60/0.47 , 8.00/0.30 , 7.51/0.16 , 6.72/0.21  ppm. 13C-NMR : δ/Δδ = 165.9 , 147.3/−1.6 (C-7a), 146.3/2.9 (CH-6), 129.4/1.9 (CH-2), 128.0/4.1 (C-3a), 124.6/3.2 (C-4), 120.6/1.8 (CH-5), 102.1/2.2 (CH-3) ppm. 15N-NMR : δ/Δδ = 145.5/3.1 (NH-1), 155.4/−114.0 (N-7). 195Pt NMR : δ = −1772.5 ppm. ESI MS (30 ev): m/z = 679.0 (M+H), 676.0 (M−H), 478.1 (M−4Braza−H), 197.1 (4Braza+H), 195.1 (4Braza−H). Anal. Calc.: C, 28.4%; H, 1.5%; N, 8.3%. Found: C, 28.3%; H, 1.5%; N, 8.4%.Breast adenocarcinoma , osteosarcoma , malignant melanoma , cervix epitheloid carcinoma , A2780 ovarian carcinoma (ECACC No. 93112519), A2780R cisplatin-resistant ovarian carcinoma (ECACC No.93112517), lung carcinoma  and prostate adenocarcinoma  cancer cell lines were purchased from European Collection of Cell Cultures .In vitro cytotoxicity was determined by an MTT assay against MCF7 (the complexes 1–3), HOS (1–3), G361 (2), HeLa (2), A2780 (2), A2780R (2), A549 (2) and LNCaP (2) human cancer cell lines. The cells were maintained in a humidified incubator . The cells were treated with 1–3 or standards  at the 0.01, 0.1, 1.0, 5.0, 25.0 and 50 μM concentrations for 24 h, using multi-well culture plates of 96 wells. In parallel, the cells were treated with vehicle  and Triton X-100  to assess the minimal  and maximal  cell damage, respectively. The MTT assay was measured spectrophotometrically at 540 nm . The data were expressed as the percentage of viability, when 100% and 0% represent the treatments with DMF and Triton X-100, respectively. The cytotoxicity data from the cancer cell lines were acquired from three independent experiments (conducted in triplicate) using cells from different passages. The IC50 values (µM) were calculated from viability curves. The results are presented as arithmetic mean ± SD.p < 0.05 considered to be significant .The significance of the differences between the results was assessed by the ANOVA analysis, followed by Tukey’s post-hoc test for multiple comparisons, with naza)2] (1–3) and evaluates their in vitro cytotoxicity on the selected human cancer cell lines. The testing revealed the complex 2 (involving 3Braza) as in vitro antitumor active against HOS, MCF7, G361, HeLa and A2780 with IC50° 17–32 µM. Because the complex 2 differs from 1 (involving 3Claza) and 3 (involving 4Braza) in the nature or position of the 7-azaindole moiety substituent, it can be concluded that 3Braza represents a very perspective N-donor ligand, which could be used as a carrier ligand involved into platinum(II) complexes with different leaving group than oxalato one.This work describes three new platinum(II) oxalato complexes [Pt(ox)(


Squamous cell carcinomas (SCCs) account for the majority of cancer mortalities. Although TP63 is an established lineage-survival oncogene in SCCs, therapeutic strategies have not been developed to target TP63 or it’s downstream effectors. In this study we demonstrate that TP63 directly regulates NRG1 expression in human SCC cell lines and that NRG1 is a critical component of the TP63 transcriptional program. Notably, we show that squamous tumors are dependent NRG1 signaling in vivo, in both genetically engineered mouse models and human xenograft models, and demonstrate that inhibition of NRG1 induces keratinization and terminal squamous differentiation of tumor cells, blocking proliferation and inhibiting tumor growth. Together, our findings identify a lineage-specific function of NRG1 in SCCs of diverse anatomic origin. Within the past decade, lineage addiction has emerged as a common paradigm to explain how certain tumors depend on co-opted survival and self-renewal programs that drive the normal development of the tissues from which they arise . During TP63 is prevalent in SCCs, and TP63 expression is used to distinguish SCCs from other cancer subtypes in multiple tissues  share many common properties, including genetic and epigenetic alterations . The TP6 tissues . SCCs ar tissues . DespiteHere we show that NRG1 expression is directly regulated by TP63 in SCCs of various organs, and that co-expression of NRG1 and its receptor ERBB3 is prevalent in SCCs. Moreover, we find that many of the SCC models that co-express NRG1 and ERBB3 depend on NRG1 autocrine signaling in vivo, in contrast to non-squamous cancers that exhibit NRG1 autocrine signaling but are not dependent on it.NRG1 and TP63 expression significantly correlated in both esophageal and lung squamous cell carcinomas (LUSC) as determined from The Cancer Genome Atlas (TCGA) transcriptome data (TP63 isoforms (siTP63 # 14) or only the TA-TP63 isoforms (siTA-TP63 # 13) and assessing expression of both isoforms of the NRG1 EGF-like domain, NRG1α and NRG1β, by qPCR in the OE-21 and KYSE-140 SCC cell lines. Knockdown of just the TA isoforms modestly reduced NRG1 expression, whereas silencing of all isoforms robustly decreased NRG1 expression , which encompasses the TP63 binding motif, compared to the control locus at −21 kB  compared to control treatment, nearly doubling time to progression from 14 to 27 days (p<0.002)  . Progresp<0.002) .NRG1/ERBB3 co-expression in ovarian cancer. We tested the effect of anti-NRG1 on a panel of ovarian cancer cell lines and indeed proliferation of cell lines expressing both NRG1 and ERBB3 was inhibited by anti-NRG1 in vitro  as described . Cell liAll animal studies were approved by the Institutional Animal Care and Use Committee (IACUC) at Genentech . For cell line xenograft studies, tumor cells were subcutaneously inoculated into C.B-17 SCID beige mice (FaDu) or athymic nude mice (HCC95 and KYSE-180). Mice were randomized into treatment groups when tumor volumes reached ~200mm3. Antibodies were dosed once per week intraperitoneally (i.p.) at 20 mg/kg for three doses, and tumor volumes and body weights were measured twice a week. For RNAseq, histology and western blot, HCC95 tumors were collected 72 hr after the first or third dose. For patient-derived tumor xenografts, tumor fragments were subcutaneously implanted into Balb/C nude mice, which were randomized into treatment groups (n = 5) when tumor volumes reached 150–250 mm3. Dosing and measurements were performed as noted above for 3–4 weeks.CreERT2+; tdTomato; KrasG12Dwt/ki; PTENloxP/loxP squamous skin cancer mouse model (manuscript in preparation), was used following Genentech IACUC guidelines. At 10–15 weeks of age, mice were dosed once with Tamoxifen . Three days after a single tamoxifen dose, mice were divided into two groups with mice of similar proportion of age and sex, and dosed with anti-Ragweed or anti-NRG1 antibodies .The Lgr53). Percent tumor growth inhibition (TGI) was calculated relative to the average tumor volume of control (anti-Ragweed) mice. Kaplan-Meier analysis was used to determine progression-free survival for the skin GEMM SCC mice. Log-rank analysis was used for statistical analysis to compare treatment groups.A mixed-modeling approach was used to analyze tumor volumes for xenograft and PDX studies as explained earlier . Cubic rGGACAGCAGCAUUGAUCAAUU, AS = UUGAUCAAUGCUGCUGUCCUU), #2 ], and negative control non target control  were purchased from Dharmacon. RNA was isolated after 72 hr using a RNeasy Plus kit (Qiagen). cDNA was prepared using the Advantage RT for PCR kit (Clontech), and qPCR was performed using ABI master mix, and the results were validated by three independent experiments using the following Taqman assays (Life Technologies): TP63-all (Hs00978340_m1), TA-TP63-TA (Hs00186613_m1), deltaN-TP63 (Hs00978339_m1), NRG1a (Hs01103794_m1) and NRG1b (Hs00247624_m1).Cells were plated in medium without antibiotics and transfected with 5 nmol/L of siRNA using Dharmafect transfection reagent (Dharmacon). siRNAs for TA-TP63 (#13 = J-003330–13), all isoform-TP63 (#14 = J-003330–14), deltaN-TP63 [#1 . Proteins were separated by SDS-PAGE, transferred to nitrocellulose membrane and stained with the indicated antibodies. HCC95 tumors from the in vivo studies were processed similarly for analysis of pharmacodynamic and apoptotic markers. Antibodies: TP63 alpha , deltaNTP63 (Biolegend 619001), actin (BD Bioscience 612656), p-ERBB3 (CST 4791), ERBB3 (CST 12708), PARP (CST 9542) and Cleaved caspase-3 (CST 9664).5’-TTCAAAAGGGAGTGCCAACTTTTCC-3’, 5’-GGTGCCTCACCTTTCTTCTTCCTGTCC-3’) and −30 KB NRG1 promoter  from NRG1 transcript start site as described earlier . Cultures of 25 million cells were fixed and cross-linked with formaldehyde (1.1%) for 15 min at room temperature and stopped with glycine. The cell pellet was re-suspended in ChIP lysis buffers and sonicated using a Bioruptor sonicator (Diagenode) to produce chromatin fragments averaging 200–500 bp. Sheared chromatin was incubated overnight at 4°C with protein A-coated magnetic beads plus either anti-TP63 alpha (CST 13109), anti-deltaNTP63 (BioLegend 619001) or isotype control antibody. Beads were washed, DNA was eluted and crosslinks were reversed during an incubation overnight at 65°C. Samples were treated with iPure beads and DNA was purified. Quantitative PCR was performed using sybr green PCR master mix (Applied Biosystem) to assess enrichment at the NRG1 promoter. The results were validated by three independent experiments. The ChIP ratio was calculated as enrichment over noise, normalized to the input. Statistical significance was determined by one-way ANOVA. Primers used for CHIP PCR were −21 kB NRG1 promoter  antibody , incubated at a concentration of 1.0 ug/mL for 60 min at room temperature and binding was visualized using ABC-Peroxidase Elite followed by DAB chromagen and counter stained with Mayer’s hematoxylin. KRT10 expression was reviewed manually by a translational pathologist (JMG) and scored for the percentage of cells demonstrating moderate to strong immunoreactivity, excluding areas of necrosis (0–100%).RNA-seq libraries were prepared using TruSeq RNA Sample Preparation kit  and sequenced on Illumina HiSeq 2500 sequencers, yielding an average of 34 million single-end reads (50 bp) per sample. Reads were aligned to the human genome version NCBI GRCh37 using GSNAP. Expression counts per gene were obtained by counting the number of reads aligned concordantly within a pair and uniquely to each gene locus as defined by NCBI, Ensembl gene annotations, and RefSeq mRNA sequences. Differential gene expression analysis was performed using edgeR. Gene enrichment analysis was performed on the edgeR differential expression results using the Gsea Preranked tool available through the Broad’s GSEA application. DESeq was used to compute the variance stabilized expression values for plotting the expression heat maps.Graphical and statistical data were generated with Microsoft Excel or GraphPad Prism . Statistical significance of differences between the results was assessed using a standard 2-tailed t-test or one-way ANOVA using Prism. p<0.05 was considered statistically significant. In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been reviewed by three peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Kevin Struhl as the Senior Editor. The reviewers have opted to remain anonymous.Thank you for submitting your article "NRG1 is a critical component of the TP63 transcriptional program driving squamous cell cancers in multiple tissues" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:The reviewers believe that the findings are of potential significance and may have therapeutic implications. Although NRG1 has already been established as a TP63 target in breast cells and NRG1/ERBB signaling has already been reported to play a role in squamous cell carcinoma biology, a strength of the work is the use of human material, murine models and cancer cell lines as well as an antibody to block NRG, which suggests that blocking NRG may affect tumor maintenance. However, the reviewers request additional work to more clearly demonstrate the interaction of NRG and p63, to clarify the specificity of some of the reagents and to determine whether squamous differentiation is the basis of the observed findings.Essential revisions:1) The title is quite broad. The reviewers were unclear whether the findings are true in all squamous tissues or are specific for a particular squamous epithelium. This should be addressed, and the title should be changed to more accurately reflect the findings presented in the manuscript.2) Further evidence to support co-expression/co-localization of NRG and p63 in SCC would strengthen the manuscript.3) The use of the blocking antibody is powerful but the details of how specific this reagent is for NRG are lacking. Further evidence of specificity and/or the use of genetics to support the findings are necessary.4) The authors should clarify whether tumors regress or arrest after treatment with the antibody. A waterfall plot of all of the tumors would be helpful.5) Is there squamous differentiation in cell lines? This needs to be assessed. If so, it is surprising that this did not affect proliferation.6) Although several experimental models are used, it would be helpful to perform similar experiments in at least three cell lines or to determine whether there are specific squamous tissues in which these findings are most relevant.For your information, we have included the reviews below, as you might find them helpful when preparing the revised version of your manuscript.Reviewer #1:In this manuscript Jackson and co-workers investigated the role of p63-NRG in tumor cell proliferation and tumor maintenance. They found that p63 and NRG expression co-occurred in the TCGA lung and esophageal cancer datasets. They showed that suppressing p63 decreased NRG expression and was localized to the NRG. Using a NRG antibody they showed that there was a modest effect on cell proliferation but a stronger effect in some tumor models. They argue that the effects on tumors is due to SCC differentiation.Overall these experiments are well described and well controlled. The observations are timely and important and may have therapeutic implications. However, there are a few points that require some additional clarification.The authors argue that the NRG plays a key role in SCC or those that co-express NRG and p63. However, they do not show this directly. It would be helpful to perform experiments in a panel of cell lines in which these markers are noted so that the point can be made clear. This is particularly important since the authors show that some tumors don't respond to anti-NRG, suggesting that they don't co-express p63 and NRG but this is not shown.It is also not clear whether the tumors regress or simply arrest. It would be helpful to show a waterfall plot for each tumor.It is also not clear why squamous differentiation would not affect proliferation. Have the authors formally assessed whether there is evidence of squamous differentiation in the 2D cultures?Reviewer #2:The authors show that NRG1 is a transcriptional target of p63 and argue that anti-NRG1 could be an effective therapy for a wide variety of squamous cell carcinomas. This data is interesting; however, the authors use a very limited number of cell lines and in vivo models. To strengthen the manuscript, the authors should focus on one type of SCC with a more robust number of cell lines and in vivo models.Reviewer #3:In this manuscript Hedge et al. show that TP63 directly regulates NRG1 expression in squamous cell carcinoma (SCC) cell lines. In addition, they show that treatment with an anti-NRG1 antibody inhibits the growth of SCC xenograft models and provide evidence that inhibition of NRG1 induces keratinization and terminal squamous differentiation of tumor cells. Although the data are potentially interesting, there are some major issues with the experimental design, which include the following:1) All experiments aimed at elucidating NRG1 function utilize an NRG1 blocking antibody. However, the authors fail to demonstrate (e.g. by using genetic tools) that the phenotype observed in their model systems upon antibody treatment is specifically mediated by NRG1 inhibition.2) NRG1 has already been established as a TP63 target in breast cells and NRG1/ERBB signaling has already been reported to play a role in squamous cell carcinoma biology. The authors provide some evidence that NRG1 inhibition decreases SCC cell proliferation and promotes cell differentiation. This hypothesis should be further investigated in properly controlled in 3D cell culture models where the role of ERBB3 and ERBB4 signaling could also be addressed.3) In Figure 1, it would be important to perform double IHC/IF to demonstrate co-localization of deltaN-TP63 and NRG1 at the protein level in tumor cells within human SCC tissue samples.Nrg1/ErbB signaling in the treated in vivo models should be provided.4) In Figure 3, immunoblotting data documenting inhibition of 5) In Figure 4, data for anti-Ragweed control (3 dose) should be showed for all experiments. Essential revisions:1) The title is quite broad. The reviewers were unclear whether the findings are true in all squamous tissues or are specific for a particular squamous epithelium. This should be addressed, and the title should be changed to more accurately reflect the findings presented in the manuscript.We revised the title to better reflect the findings. The new title is “NRG1 is a Critical Regulator of Differentiation in TP63-driven Squamous Cell Carcinoma”.2) Further evidence to support co-expression/co-localization of NRG and p63 in SCC would strengthen the manuscript.This is a great suggestion to demonstrate the co-localization of NRG1/p63. Unfortunately, the available NRG1 antibodies do not work for immunofluorescence, IHC or even western blot. We have tested many different antibodies for NRG1 in the past and have found them to be non-selective. We always perform shRNA knockdown of NRG1 to validate any commercial antibodies and so far, we have not found one that shows a specific staining pattern. Moreover, the blocking antibodies used in this paper are also not suitable for those applications. However, we would like to bring to the reviewer’s attention that we have provided TP63, NRG1, ERBB3 and ERBB4 mRNA levels in a table format just below the in vitro growth assay in Figure 2.3) The use of the blocking antibody is powerful but the details of how specific this reagent is for NRG are lacking. Further evidence of specificity and/or the use of genetics to support the findings are necessary.Details on antibody selectivity can be found in our earlier publication . We have added a sentence pointing the readers to this publication for additional details on the antibody properties.4) The authors should clarify whether tumors regress or arrest after treatment with the antibody. A waterfall plot of all of the tumors would be helpful.We have included a waterfall plot of all tumors as a supplementary figure. The tumors indeed undergo stasis not regression, consistent with the role of NRG1 in regulating differentiation, not cell survival. As discussed in our final paragraph, EGFR and other signaling pathways also play an important role in driving these tumors and inhibition of NRG1 could drive deeper responses when combined with EGFR inhibition.5) Is there squamous differentiation in cell lines? This needs to be assessed. If so, it is surprising that this did not affect proliferation.We thank the reviewers for raising this critical question. We carried out qPCR analysis of four differentiation markers in three different squamous cell carcinoma lines treated with anti-NRG1 or control antibody in vitro. The result are provided in Figure 4—figure supplement 3. Consistent with our in vivo findings, the cell lines treated in vitro also showed significant increases in multiple differentiation markers. However, the magnitude of induction was much lower in vitro, consistent with the more modest effects on proliferation observed in vitro compared to the tumor growth inhibition in vivo.6) Although several experimental models are used, it would be helpful to perform similar experiments in at least three cell lines or to determine whether there are specific squamous tissues in which these findings are most relevant.We have conducted additional experiments as mentioned above with 3 cell lines; FaDu (Head and Neck), HCC95 (lung) and KYSE-180  squamous cell carcinomas. The induction of differentiation markers upon treatment was highest in the lung and esophageal lines.


NAC1 is a cancer-related transcription regulator protein that is overexpressed in various carcinomas, including ovarian, cervical, breast, and pancreatic carcinomas. NAC1 knock-down was previously shown to result in the apoptosis of ovarian cancer cell lines and to rescue their sensitivity to chemotherapy, suggesting that NAC1 may be a potential therapeutic target, but protein complex formation of intranuclear NAC1 in ovarian cancer cells remain poorly understood. In this study, analysis of ovarian cancer cell lysates by fast protein liquid chromatography on a sizing column showed that the NAC1 peak corresponded to an apparent molecular mass of 300–500 kDa, which is larger than the estimated molecular mass (58 kDa) of the protein. Liquid chromatography-tandem mass spectrometry analysis identified CARM1 as interacting with NAC1 in the protein complex. Furthermore, tissue microarray analysis revealed a significant correlation between CARM1 and NAC1 expression levels. Ovarian cancer patients expressing high levels of NAC1 and CARM1 exhibited poor prognosis after adjuvant chemotherapy. Collectively, our results demonstrate that high expression levels of NAC1 and its novel binding partner CARM1 may serve as an informative prognostic biomarker for predicting resistance to chemotherapy for ovarian cancer. Ovarian cancer is the most aggressive gynecological malignancy worldwide  and its NACC1 gene, is a nuclear protein that encompasses an N-terminal BTB/POZ  (hereafter abbreviated BTB) and a C-terminal BEN  domain. The BTB domain is a ∼100 amino acid highly conserved motif that mediates homodimerization and/or heterodimerization and interacts with other proteins SAM as a methyl donor. The analysis clearly showed that CARM1 methylates histone H3, but not GST or GST-NAC1  enzyme that is known to methylate histone H3 (H3R17me2a and H3R26me2a), and nonhistone substrates . We ther1 Figure . To deteP < 0.0001. The significant correlation of CARM1 and NAC1 expression levels implies that NAC1 functions synergistically with at least CARM1 to promote tumorigenesis in ovarian cancers.In an attempt to determine the expression levels of CARM1 and NAC1 in clinical specimens, we performed immunohistochemistry (IHC) for CARM1 and NAC1 in 84 ovarian carcinoma tissues. Both antibodies stained tumors more strongly than the surrounding benign tissues Figure . High exP = 0.0152 and P = 0.0091, respectively) , residual tumor ≥1 cm , and high NAC1/CARM1 expression  correlated with shorter progression-free and overall survival (Tables P = 0.0002) for shorter progression-free survival  for overall survival  Figure . UnivariThe knockdown of CARM1 as well as NAC1 using siRNA suppressed cell growth in the ovarian carcinoma cell lines A2780 and MDAH2774 Figure .The present study indicates that NAC1 forms 300–500 kDa protein complexes in ovarian cancer cells, comparable with that of HeLa cells . The moset al. reported that CARM1 overexpression was noted only in a small number (17%) of ovarian cancer patients -adenosyl-L-methionine  (for hot assay) or 20 µM S-adenosylmethionine (SAM) (for cold assay) in methylase activity buffer  was incubated for 60 min at 30° C. The reaction products were separated by 15% SDS-polyacrylamide gel electrophoresis, followed by Coomassie Brilliant Blue staining and autoradiography (for hot assay) or by Western blotting with anti-histone H3R17me2a (for cold assay).Reaction mixture (30 µl) containing 1 µg of different recombinant human histone H3, GST and GST-NAC1 (as substrates), the indicated immunoprecipitate (as enzyme), and 1 µL of 2 or docetaxel 70 mg/m2). All patients received 6-12 courses of this combination regimen. The Shimane University Institutional Review Board approved the acquisition of tumor tissues and written informed consent was obtained from all subjects.Formalin-fixed, paraffin-embedded tissue samples of 84 ovarian cancers, including 44 serous carcinomas, 10 mucinous carcinomas, 10 clear cell carcinomas, and 20 endometrioid carcinomas, were used in the present study. Diagnoses were based on conventional morphological examinations of sections stained with hematoxylin and eosin (H&E), and tumors were classified according to the WHO classification. Tumor staging was performed according to the International Federation of Gynecology and Obstetrics (FIGO) classification. Samples were obtained from the Department of Obstetrics and Gynecology at Shimane University Hospital. All patients were primarily treated with cytoreductive surgery and adjuvant platinum and taxane chemotherapy  and pathology technician (K. I.) and was based on a review of H&E slides. The immunohistochemistry method and the evaluation criteria were detailed in a previous study .t-test was used to examine the significance of differences in growth assay data. Chi-squared test or Fischer’s exact test was used for comparisons of categorical data. Data are presented as means ± SD. P < 0.05 was considered significant.Progression-free and overall survivals were calculated from the date of diagnosis to the date of first relapse or last follow-up. Age and performance status distributions were similar between patients expressing and not expressing NAC1 or CARM1. Data were plotted as Kaplan–Meier curves, and the significance of differences was determined using the log-rank test. A multivariate prognostic analysis was performed using a Cox proportional hazards model. Data were censored when patients were lost to the follow-up. Student’s


Escherichia coli at different antibiotic concentrations for ∼400 generations. Our results reveal fast evolution toward specialization following the first mutational step toward resistance, along with pervasive trade‐offs among different evolution doses. We found clear and regular fitness patterns of specialization, which converged rapidly from different initial starting points. These findings are consistent with a simple fitness peak shift model as described by the classical evolutionary ecology theory of adaptation across environmental gradients. We also found that the fitness costs of resistance tend to be compensated through time at low doses whereas they increase through time at higher doses. This cost evolution follows a linear trend with the log‐dose of antibiotic along the gradient. These results suggest a general explanation for the variability of the fitness costs of resistance and their evolution. Overall, these findings call for more realistic models of resistance management incorporating dose‐specialization.Antibiotic and pesticide resistance of pathogens are major and pressing worldwide issues. Resistance evolution is often considered in simplified ecological contexts: treated versus nontreated environments. In contrast, antibiotic usually present important dose gradients: from ecosystems to hospitals to polluted soils, in treated patients across tissues. However, we do not know whether adaptation to low or high doses involves different phenotypic traits, and whether these traits trade‐off with each other. In this study, we investigated the occurrence of such fitness trade‐offs along a dose gradient by evolving experimentally resistant lines of  The massive increase in use of antibiotics since 1950 has greatly improved standards of living in our societies but has led to an explosion in the number of resistant phenotypes in microorganisms   for ∼400 generations in order to “push” them close to their optimal phenotype. We started with a susceptible reference strain, or “SRef” strain, corresponding to the 10,000th (abbreviated 10 K) generation of Lenski's long‐term adaptation experiment (E. coli strain REL4536). First, we obtained a highly resistant reference strain (“RRef” strain) by screening twice SRef for antibiotic resistance . We then evolved two series of strains at the different Nal doses. In the first main series, six resistant lines per ED  were initiated from independent resistant mutants of SRef obtained after a screen at the same dose than the ED . These lines (hereafter “SRef lines”) provided a diversity of first mutational step and evolved from the screen at a given Nal dose. In the second series, two lines per ED  were initiated from the RRef strain. These lines (hereafter “RRef‐lines”) provided with replicated evolution of the same initial resistant mutant , corresponding to the 10,000th generation of Lenski's long‐term adaptation experiment to Davis minimal broth DM25 (Lenski and Travisano All lines were derived from the −7). They were obtained via an additional fluctuation assay  divided among the five evolution doses and the six control lines  evolving at dose 0. All lines were distributed into four 24‐wells lidded microplates with 1 mL medium per well, with the six Nal concentrations allocated in each plate. Inoculated wells were alternated with noninoculated wells following a checkered pattern, to control for contaminations. The plates were incubated at 37°C, 200 rpm in a water‐saturated atmosphere . Every 24 h, 10 μL of the cultured lines were transferred to new wells containing 1 mL of fresh medium and incubated in the same conditions. The protocol was applied for two months corresponding to ∼400 generations of evolution after what the lines were stored as glycerol stocks.gyrA gene at Tini and Tfin. This sequence covers most of the promoter and 32% of the gyrA gene and its complete quinolone resistance‐determining region . Sequencing was performed using Eurofins mwg operon . Mutations in gyrA gene were identified by comparing the mutant sequences to that of the SRef strain.All lines were sequenced at the ini and Tfin. The “fitness profile” of each line (YFP) across the dose gradient was determined by competitions against the RRef‐CFP strain in DM250 at the five measure doses . Ecotoxicological measures such as MIC (minimum inhibitory concentration) are often used to characterize resistance evolution. However, competitive fitness is better suited in our context, to quantify adaptation and the evolution of specialization. For instance, two lineages with similar MIC can have very different competitive abilities, below their common MIC. The measure dose 150 was preferred to dose 200 because the latter exhibited high growth inhibition of the RRef strain, such that fluorescence measurements were close to the detection limit. The fitness costs of resistance were measured from competitions in absence of Nal (dose 0) against the strain SRef‐CFP.Competitions experiments were performed from glycerol stocks at Tt0). Competitions were initiated by inoculating 2 μL of the competition mix into 200 μL of DM250 . Fluorescence signals were measured again after 24h of growth (t24) in the same conditions as the evolution experiment . Each competition was repeated at least four times at different dates. We assumed that fitness effects were transitive between genotypes competing in the same dose. Deviation from transitivity as measured in Gallet et al. (−3 at most in these experiments).Competition assays were performed in the following procedures. 1:1 volumic ratio competition mixes were prepared from saturated cultures. Fluorescence signals of these mixes were measured on a Tecan Infinite 200  prior to the competition .The selection coefficient per generation associated with each competition was estimated as:lineID, MD (six doses) and time (Tini and Tfin). Random effects included plate and date of the competition assay. The model was used to estimate the fitness values at Tini and Tfin, the fitness changes between Tini and Tfin (pairwise comparisons) of each line in each MD, and their standard errors (performed with mvt adjustments with the lsmeans R package), which are all represented in figures. Polynomial fits of the fitness profiles of evolved lines (from the fitness estimates at Tfin of the previous model) in each MD were performed as functions of the log‐ED of lines (nls function of the R Stats package). The fits were done for the SRef lines alone or for both the RRef and the SRef lines for the comparison of the final fitness profiles of lines evolved in the same ED but initiated from mutants screened at different doses.Fitness measures were analyzed in a linear‐mixed model  with fixed effects on P value = 0.773) nor between replicates   due to adaptation to experimental conditions . The last replicate differed only slightly from the three others due to a fitness jump at generation 400 . The global fitness trajectory of the control0K lines is consistent with that expected from the similar 400 generations evolution in DM25 in the LTEE  Fig. . This reE. coli, the DNA gyrase is the target of Nal and many of the known resistance mutations occur in the gyrA gene coding for the GyrA subunit of this enzyme  and some non‐gyrA mutations (four lines) were initially sampled across the sets of single resistant mutants screened at the doses 3, 8, and 20 .In  20 Fig. . Evoluti 20 Fig. . In all gyrA mutants 87Gly and 119Glu) went extinct early in the evolution experiment. One of the SRef‐lines evolving at ED20 proved to be initially polymorphic for the gyrA resistance mutation. This line was removed from later analysis in order to avoid confusion in the data interpretation. One of the two RRef‐lines evolving at Nal3 was contaminated at one point and removed from the experiment. In all other lines, no additional mutations than the ones detected at Tini were found in the gyrA sequence at Tfin. Among the four lines without gyrA mutations initially (hereafter “non‐gyrA” lines), only one line acquired a gyrA mutation (87Tyr) during the evolution experiment.Two SRef‐lines evolving at ED200 , all fitness profiles show a regular quadratic pattern with log‐ED. Fitted curves are shown on each panel and Table gyrA mutation show a large fitness lag compared to all other lines, at all MD. Given this large and consistent difference, these lines were not included in the fit of the average fitness profiles among ED represented on Figure gyrA mutations after the initial screen, despite that these mutations are frequent and provide a strong fitness benefit. The effect of the first mutational step is also visible on gyrA lines, but is very small. In several cases, lines with the same initial gyrA mutation tend to group together for a given ED and MD . Similarly, RRef lines , tend to group together as well. These effects remain, however, minor compared to the overall trend. Even the RRef lines, which had a quite different starting point than most lines, show a final pattern very consistent with the general trend of SRef lines  and generation 400 of evolution (Tfin) in the MD corresponding to its ED. SRef lines evolved at ED200 are not shown as their fitness were not measured at MD200 (see Methods). For all lines, the fitness change was positive or not significantly different from zero at the dose in which they evolved. Among gyrA lines, the trend shows striking regularity independently of the evolution dose and of the identity of the gyrA mutation carried initially , with a slope close to –1. The trend is also observed among non‐gyrA lines but with a different intercept  and similar slope of about –1. This pattern is expected when evolution corresponds to convergence to a fitness peak, as it indicates that the fitness changes entirely compensate initial maladaptation. This pattern excludes a strong role for “chance” or transient “historical” effects  and show an adaptation (or no change) in all MD, indicating that evolving at low dose increases fitness at high dose. A different pattern is observed for lines evolved at high doses. While they adapted to their ED, they consistently and regularly “deadapted” to low doses.Studying a large sample of mutants screened at different doses in the same system showed that little dose specialization occurred after a single mutational step  but higher for non‐gyrA mutations. They were also variable between single‐mutants and “double”‐mutants of ED100 and ED200, even when they carried the same gyrA mutation. The change in cost between Tini and Tfin is negatively correlated with the ED . The non‐gyrA lines (present only at ED3) have generally higher costs than the gyrA lines . Furthermore, phenotypes evolved at intermediate doses are better adapted to high doses than phenotypes evolved at low doses (consistent with a multiple hit effect). Additionally, long‐term selection at low doses will not result in high fitness  at high doses, and as a result, long‐term selection at high doses will not select for high‐fitness phenotypes at low doses. These conclusions have important implications for understanding and modeling the evolution of resistance in the field, under heterogeneous conditions.To our knowledge, no previous study has clearly established the pattern of dose‐specialization along a gradient so far. First, many studies have investigated the fitness of resistant mutants from field samples . After 400 generations of evolution at ED3, their fitness profiles are still largely different to those of the gyrA lines indicating a strong historical contingency between those “mutational modules” of resistance. Contrary to the specialization pattern, this divergence in fitness patterns between the gyrA and the non‐gyrA lines was already observed immediately after the first resistance screen and interpreted as the occurrence of selective covariances across traits in Harmand et al. gyrA and non‐gyrA resistant lines as good candidates to investigate the effects of historical contingency and selective covariances on long‐term adaptive trajectories.“Historical contingency” or “mutation‐order” effects have been widely discussed in the literature to describe the dependence of adaptive trajectories on initial conditions  often overlook the possibility that dose gradients may represent different phenotypic challenges, in addition to also representing different selection intensities. Our results show that this simplification is not warranted. They show that the evolution of resistance along antibiotic dose gradients is consistent with classic evolutionary models of adaptation on ecological gradients, where each environment corresponds to one fitness peak. The observed patterns of adaptation and maladaptation are also fully consistent with the occurrence of dose‐dependent optima and show pervasive trade‐offs across doses. Hence, our findings call for more realistic models of resistance evolution in heterogeneous dose conditions that include dose‐specialization. Such models are necessary to better evaluate the impact of low doses of antibiotics that are today ecologically widespread.The authors declare no conflict of interest.Associate Editor: K. LythgoeFig. S1. Selection coefficients of control lines evolved in the absence of antibiotic in competition against the non‐evolved wild‐type 10K‐YFP (or 10K‐CFP in the case of 0K‐YFP lines).Click here for additional data file.Fig. S2. Fitness change of the SRef lines during 400 generations of evolution in different evolution doses (colors) versus their fitness just after the screen of resistance in the different measure doses. Symbols indicate the gyrA mutations sequenced after evolution in each line while colors indicate the dose at which they were screened and evolved. Error bars represent standard errors of the mean and the fitness change estimated in the statistical model.Click here for additional data file.Figure S2bClick here for additional data file.Figure S2cClick here for additional data file.Figure S2dClick here for additional data file.Figure S2eClick here for additional data file.Fig. S3. Costs of resistance of the SRel lines evolved for 400 generations at five evolution doses of antibiotic. Symbols indicate the mutation detected in the gyrA sequence or the absence of mutation in the gyrA sequence while colors indicate the evolution dose. The dotted horizontal line at 0 corresponds to an equal fitness with the susceptible ancestor 10K, while negative values correspond to a lower fitness of resistant lines. Error bars represent standard errors among replicates.Click here for additional data file.


The data presented in this article are related to the research paper entitled “Increased expression of mitochondrial sodium-coupled ascorbic acid transporter-2 (mitSVCT2) as a central feature in breast cancer”, available in Free Radical Biology and Medicine Journal [1]. In this article, we examined the SVCT2 transporter expression in various breast cancer cell lines using RT-PCR and Western blot assays. In addition, we analyzed the subcellular localization of SVCT2 by immunofluorescence colocalization assays and cellular fractionation experiments. Finally, an analysis of different cancer tissue microarrays immunostained for SVCT2 and imaged by The Human Protein Atlas (https://www.proteinatlas.org) is presented. Analysis of SVCT2 expression by RT-PCR and Western blot in four breast cancer cell lines are shown . Immunof22.1l-glutamine, penicillin/streptomycin (100 U/ml) and fungizone.Breast adenocarcinoma cell lines ZR-75, MCF-7, MDA-231 and MDA-468 were grown in DMEM:F12 (1:1) medium. Colon carcinoma cell line CaCo-2 was grown in DMEM medium. Embryonic kidney cell line HEK-293 was grown in DMEM-high glucose medium. All media were supplemented with 10% fetal bovine serum, 1% nonessential amino acids, 1% 2.2PCR experiments were performed using the protocol described in Ref. 2.3Immunoblotting experiments were performed using the protocol described in Ref. 2.4Immunofluorescence experiments were performed using the protocol described in Ref. 2.5Cellular fractionation and mitochondria purification were performed using the protocol described in Ref.