Breast cancer (BC) is the most common malignancy among women. Emerging studies have demonstrated that circular RNA (circRNA) zinc finger RNA binding protein (circZFR) serves as a crucial regulator in many human cancers. However, the role and mechanism of circZFR in BC tumorigenesis remain unclear.The levels of circZFR, miR-578 and hypoxia-inducible factor 1α (HIF1A) were detected by quantitative real-time polymerase chain reaction (qRT-PCR) or western blot. Cell viability, colony formation, apoptosis, migration and invasion capacities in vitro were determined by using the Cell Counting Kit-8 (CCK-8), standard colony formation, flow cytometry and transwell assays, respectively. Glucose uptake, lactate product and adenosine triphosphate (ATP) levels of cells in vitro were measured using the commercial human assay kits. Targeted relationships among circZFR, miR-578 and HIF1A in BC cell lines were verified by dual-luciferase reporter and RNA pulldown assays. Animal studies were performed to assess the effect of circZFR on tumor growth in vivo.Our data indicated that circZFR was overexpressed in BC tissues and cells, and the increased circZFR level predicted poor prognosis of BC patients. CircZFR silencing or miR-578 overexpression repressed BC cell viability, colony formation, migration, invasion, and glycolysis and enhanced cell apoptosis in vitro. CircZFR silencing also hampered tumor growth in vivo. Mechanistically, circZFR acted as a sponge of miR-578, and circZFR silencing hindered BC cell malignant behaviors by miR-578. HIF1A was a functional target of miR-578 in regulating BC cell viability, colony formation, migration, invasion, glycolysis and apoptosis in vitro. Furthermore, circZFR modulated HIF1A expression through sponging miR-578.Our findings first identified that the silencing of circZFR suppressed BC malignant progression in vitro via the regulation of the miR-578/HIF1A axis, providing evidence for the crucial involvement of circZFR in BC pathogenesis. Breast cancer (BC) remains the most commonly diagnosed cancer and the leading cause of cancer-associated death among females in 2018 . TherefoCircular RNAs (circRNAs) are covalently closed, endogenous RNAs that have crucial non-coding functions in human physiologic and pathologic processes . Work inMiRNAs modulate gene expression but are frequently dysregulated in human cancers, including BC . Danza eHere, we undertook to examine the biological effect of circZFR in the malignant progression of BC in vitro and in vivo. We identified that circZFR, a prominently up-regulated circRNA in BC, controlled BC progression in vitro via targeting the miR-578/hypoxia-inducible factor 1α (HIF1A) axis.In this study, we enrolled 70 BC patients admitted to The First Affiliated Hospital of Zhengzhou University from April 2013 to June 2014. The clinicopathological features of these patients were provided in Table ®HTB-22), BT-549 (ATCC®HTB-122), MDA-MB-231 (ATCC®HTB-26) and MDA-MB-453  were cultured in RPMI-1640 medium, supplemented with 10% fetal calf serum (FCS) and 1% antibiotic solution . The immortalized MCF10A cell line  was maintained in Dulbecco’s modified Eagle’s medium/Nutrient Mixture F-12 (DMEM/F-12) with 10% FCS, 20 ng/mL epidermal growth factor, 0.5 μg/mL hydrocortisone and 5 μg/mL insulin . All cells were cultured in a 5% CO2 incubator at 37 °C.BC cell lines MCF7  synthesis was done using total RNA (100 ng) isolated by Isogen  from tissues and cell lines. The levels of circZFR and HIF1A were quantified using the TaqMan Gene Expression Assays with the indicated primers, and mature miRNAs were assayed using the TaqMan MicroRNA Assays with TaqMan-specific primer probes as recommended by the manufacturers . qRT-PCR was run in triplicate on the iCycler iQ5 device  using the PCR conditions as previously reported . Resultst method . Primer t method .CircZFR knockdown in MCF7 and BT-549 cell lines was achieved by the transduction of corresponding lentiviruses expressing three different sequence shRNAs specific to circZFR (sh-circZFR#1 (sh-circZFR), sh-circZFR#2 and sh-circZFR#3, Fulengen, Guangzhou, China), and nontarget shRNA lentiviruses (sh-NC) were used as the negative control. Vector-transduced cells were selected by puromycin  at a final concentration of 2.5 μg/mL at least 72 h. MiR-578 overexpression and knockdown cell lines were generated using the synthetic miR-578 mimic  and inhibitor , respectively, with a corresponding nontarget oligonucleotide  as the negative control. To elevate HIF1A expression in BC cell lines, a recombinant overexpressing plasmid for HIF1A  or negative control plasmid  was transiently transfected into cell lines using Lipofectamine 3000 reagent  as per the manufacturers’ protocols. Each experiment was performed in triplicate.+/PI−) and late (Annexin V+/PI+) apoptotic cells. All experiments were done in triplicate.sh-circZFR-infected or sh-NC-transduced cell lines were transfected with or without anti-NC or anti-miR-578, and MCF7 and BT-549 cell lines were carried out the indicated transfections, followed by the incubation for 24 h at 37 °C. Cell viability assay was done using the Cell Counting Kit-8  assay as per the manufacturer’s guidance. Cell colony formation was tested using standard colony formation protocols as previously reported . Cell apCell migration and invasion were detected by the transwell assay using modified Boyden chambers in 24-transwell plates . Chambers of cell invasion assays consisted of Matrigel-precoated membrane inserts (Corning). After transfection, BC cell lines were seeded into the top chamber of a 24-transwell insert, and medium containing 15% FCS was used as a chemoattractant in the lower chamber. 24 h later, the well was stained with 1% crystal violet (Solarbio), and the number of cells that had migrated or invaded to the basal side of the membrane was counted under a microscope  at 100× magnification. Each experiment was performed in triplicate.The Colorimetric Glucose Uptake Assay Kit, L-Lactate Assay Kit and ATP Assay Kit  were used to determine the levels of glucose uptake, lactate product and ATP, according to the recommendations of manufacturers. Briefly, the lysates of transfected cells were prepared using the Assay buffer and incubated with standard protocols for the indicated time point, followed by the measurement of the absorbance with a microplate reader (Invitrogen) at OD 412 nm for glucose uptake, 450 nm for lactate product and 570 nm for ATP level. All assays were done in triplicate.6 sh-NC-infected or sh-circZFR-transduced BT-549 cell line was subcutaneously injected into the dorsal flank of the mice. One week later, tumor size was measured every week with callipers and tumor volume was calculated using the following formula: volume = 0.5 × length × (width)2. All mice were sacrificed at 35 days after implantation, and tumor tissues were collected for weight.The xenograft models were constructed to assess the role of circZFR on tumor growth in vivo. Animal studies were implemented in accordance with a protocol approved by the Ethics Committee on Animal Use and Care of the First Affiliated Hospital of Zhengzhou University. Twelve 6–8 weeks BALB/c female mice  were used and randomly divided into two groups (n = 6 per group): sh-NC and sh-circZFR. Approximately 5 × 10https://circinteractome.nia.nih.gov/index.html) and CircBANK (http://www.circbank.cn/searchCirc.html). The putative targets of miR-578 were predicted by TargetScan v.7 online software (http://www.targetscan.org/vert_71/).Analysis for the targeted miRNAs of circZFR was performed using the online web CircInteractome  to construct corresponding wild-type reporters (circZFR-WT and HIF1A-3′UTR-WT). The TaKaRa MutanBest Kit was used to construct the corresponding mutations (circZFR-MUT and HIF1A-3′UTR-MUT) as per the insturctions of manufacturers . Each reporter construct (200 ng) and 30 nM of miR-578 mimic or miR-NC mimic were cotransfected into BC cell lines. Cell line extracts were prepared with RIPA buffer (TaKaRa) 24 h post-transfection, and the ratio of Renilla to firefly luciferase was detected using the Promega Dual-luciferase Assay. In RNA pulldown assays, cell lysates were incubated with the biotin-labeled miR-578 mimic  or nontarget control sequence  for 4 h at 4 °C before adding to the streptavidin beads (Sigma-Aldrich) for 2 h. The beads were collected, and total RNA was extracted for circZFR quantification. Each experiment was performed in triplicate.Western blot was used to determine the expression of HIF1A using standard protocols. The preparation of cell line extracts was done using RIPA buffer with proteinase inhibitors . Proteins (50 μg) were resolved on a 10% SDS–polyacrylamide gel, electrophoretically blotted onto nitrocellulose membranes  and probed with antibody against HIF1A  or GAPDH . Following the incubation with horseradish peroxidase-coupled IgG secondary antibody , the signals were visualized by Cheniluminescence  as recommended by the manufacturers. All experiments were done in triplicate.t test, Mann–Whitney U test or analysis of variance (ANOVA) with SPSS version 19.0 software . For survival analysis, the Kaplan–Meier survival curve and log-rank test were used. Correlations among circZFR, miR-578 and HIF1A expression levels in BC tissues were determined by the Spearman correlation test. All tests were considered statistically significant at p-value < 0.05.Data were shown as the mean ± standard deviation from at least three independent assays. Pairwise comparisons were done using a two-tailed Student’s As demonstrated by qRT-PCR, circZFR was significantly up-regulated in BC tissues and cell lines compared with their counterparts Fig. a, b. To To study the biological role of circZFR in BC progression, the loss-of-function experiments were carried out using shRNAs against circZFR . In contrast to the negative control, the transfection of the three shRNAs prominently reduced circZFR expression in both MCF7 and BT-549 cell lines  was identified within the 3′UTR of HIF1A Fig. a. When wWe then examine whether circZFR influenced HIF1A expression in BC cell lines. As expected, in comparison to their counterparts, HIF1A expression was remarkably down-regulated by circZFR silencing at both mRNA and protein levels in the two BC cell lines, and this effect was significantly abrogated by anti-miR-578 introduction  and BT-549 (B) cells.Additional file 2: Supplement material 2. The detailed quantification of the western blot analysis.


BRCA1 or BRCA2 genes. Mutations in these genes can increase the risk of developing breast, ovarian, and other types of cancer. Olaparib is the first clinically approved drug that specifically targets a vulnerability of cancers with these mutations. Genetic alterations in cancer tumors can affect response to treatment in cancer patients. Cancer models such as cell lines, which are cancer cells derived from patients and have been grown in the laboratory over time, can be used to identify these alterations which may contribute to sensitivity or resistance to treatment. We analyzed data from two independent groups of cancer cell lines and identified alterations in additional genes  that potentially increase sensitivity to olaparib. Further experimental and clinical investigations are required to validate our findings.Olaparib is an oral medication typically used to treat certain advanced ovarian and breast cancers with mutations in BRCA1/2 mutation carriers. Identification of additional biomarkers can help expand the population of patients most likely to benefit from olaparib treatment. To identify candidate markers of olaparib response we analyzed genomic and in vitro olaparib response data from two independent groups of cancer cell lines. Using pan-cancer cell lines (n = 896) from the Genomics of Drug Sensitivity in Cancer database, we applied linear regression methods to identify statistically significant gene predictors of olaparib response based on mRNA expression. We then analyzed whole exome sequencing and mRNA gene expression data from our collection of 18 HGSOC cell lines previously classified as sensitive, intermediate, or resistant based on in vitro olaparib response for mutations, copy number variation and differential expression of candidate olaparib response genes. We identify genes previously associated with olaparib response , and discover novel candidate olaparib sensitivity genes with known functions including interaction with PARP1  and involvement in homologous recombination DNA repair (ELP4). Further investigations at experimental and clinical levels are required to validate novel candidates, and ultimately determine their efficacy as potential biomarkers of olaparib sensitivity.The benefit of PARP inhibitor olaparib in relapsed and advanced high-grade serous ovarian carcinoma (HGSOC) is well established especially in  BRCA1/2-mutated, homologous recombination (HR) DNA repair deficient, tumor cells by blocking PARP-mediated DNA repair and promoting DNA replication stress through trapped PARP-DNA complexes leading to chromosomal instability, cell cycle arrest and ultimately apoptosis -ribose) polymerase (PARP) inhibitor to be clinically approved as maintenance therapy for treatment of advanced or recurrent ovarian cancer. It inhibits PARP1 and PARP2 which are involved in the base excision repair (BER) pathway important for repair of damaged bases and single-strand DNA breaks (SSB). The antitumor activity of olaparib is based on the synthetic lethality relationship between PARP and BRCA1/2 where loss of BRCA1/2 function or PARP inhibition alone is compatible with cell survival, but the combination of BRCA1/2 inactivation and PARP inhibition leads to cell death  and resistant  cell lines, respectively. Similarly, MYC (33.2%), MECOM (27.8%), and KRAS (9.4%) are amplified in EOC cases of the TCGA PanCancer Atlas . CC. CCn = 5er Atlas ,48 datasTP53 and BRCA1/2 in these cell lines were rediscovered [TP53. OV4485 and OV4453 harbor pathogenic variants in BRCA1  and BRCA2  of germline origin  were found to have mutational signature 3.Finally, analysis of single base substitution (SBS) mutational signatures in the 18 HGSOC cell lines revealed that cell lines exhibit multiple COSMIC  mutational signatures. The dominant signatures are 1 and 3, which are associated with aging and HR repair deficiency, respectively . These aTo validate the findings from GDSC pan-cancer cell lines in HGSOC cell lines, all 1214 candidate genes, from univariate and multivariate analyses, were investigated for mutations, CNVs, or whether they were differentially expressed between sensitive and resistant HGSOC cell lines . A totalSome validated genes were found to have relevant known functions, such as interactions with PARP1 and involvement in HR, and were prioritized. Genomic alterations involving candidate olaparib response genes identified in olaparib-sensitive or -resistant HGSOC cell lines suggests a role for these candidate genes in olaparib response. Known functions of these validated candidate genes could provide clues for plausible mechanisms by which they mediate olaparib sensitivity or resistance. Key candidate genes with relevant functions and altered in the HGSOC cell lines are presented below. PUM3 were found in 2 resistant and 1 intermediate HGSOC cell lines (PUM3 mRNA compared to sensitive and intermediate cell lines (PUM3 mRNA expression in olaparib response with high expression associated with increased sensitivity (from GDSC cell lines) and low expression associated with resistance (from HGSOC cell lines). However, some sensitive cell lines also have low expression of PUM3 suggesting that PUM3 expression alone is not the single predictor of olaparib response. Investigating the HGSOC cell lines for genomic alterations involving ELP4 revealed rare potentially deleterious, heterozygous, missense variants of ELP4 (p.Arg317Cys) as well as ELP6 (p.Gln151Arg) in TOV2978G . This suggests that a subset of PUM3-expressing EOC cases, distinct from BRCA1/2 mutation carriers, may benefit from olaparib treatment.The key candidate genes described above were investigated for mutations, copy number variation, and mRNA expression in patient tumor samples where data for these types of alterations were available . In totaPUM3, EEF1A1) and emerging HR genes .The analyses of pan-cancer cell lines in the GDSC database to identify genes whose mRNA expression was significantly associated with sensitivity or resistance to olaparib revealed novel candidate genes with relevant functions. The major findings from this analysis that were successfully validated in the HGSOC cell lines can be classified into two groups of genes: PARP1 interactors  binds to mRNA and regulates translation using its highly conserved PuF domains. A Puf domain consists of 35 to 39 amino acids capable of associating with the 3′-untranslated region (3′-UTR) of target mRNAs and interacts with other regulatory proteins to promote mRNA degradation and repression of translation [Caenorhabditis elegans, led to the development of germ cell tumors [PUM3 expression has been reported to be positively associated with breast cancer progression. High expression of PUM3 was observed in 70% of breast cancer biopsies comprising diverse histological subtypes compared to normal breast tissues, ductal carcinoma in situ, and adjacent noncancerous tissues [PUM3 by siRNA sensitizes cells to the DNA topoisomerase I (TOP1) inhibitor camptothecin and UV treatment, while cells constitutively overexpressing PUM3 are rendered resistant to genotoxic exposure [PUM3 gene silencing or deletion on in vitro response to PARPi treatment has not been reported. Our results show that PUM3 mRNA expression is associated with increased sensitivity to olaparib. This supports the hypothesis that PUM3-mediated inhibition of PARylation by PARP1 may support olaparib-mediated catalytic inhibition of PARP1 and sensitize cells. However, it is not known if PUM3 can contribute to PARP trapping which is considered the major part of PARPi cytotoxicity. PARP1 is the most active target of olaparib . Therefoer types . PUM3  of olaparib and programmed cell death ligand 1 (PDL-1) inhibitor durvalumab (Imfinzi) in platinum-sensitive relapsed germline BRCA1/2-mutated ovarian cancer is an example [BRCA1/2-mutated, HR-deficient HGSOC is associated with increased neoantigens, tumor-infiltrating lymphocytes (TILs) and favorable prognosis than HR-proficient HGSOC [ll lines B. The in 1 cells . IFNG exectively . While i example . BRCA1/2nt HGSOC . ELP4 and ELP5 at mRNA level is associated with increased sensitivity to olaparib in GDSC pan-cancer cell lines. An HGSOC cell line (TOV2978G) with intermediate response to olaparib has rare, potentially damaging heterozygous variants in ELP4 (p.Arg317Cys) and ELP6 (p.Gln151Arg). ELP4, ELP5, and ELP6 are subunits of the RNA polymerase II elongator complex [BRCA1/2 mutations although it does not express BRCA1 mRNA or protein [ELP4 was discovered as a novel HR repair gene through coevolution analysis of 600 species and functional experiments, and was found to have coevolved with BRCA1 and BARD1 in plants and mammals [ELP4 was experimentally associated with the HR repair pathway using two systems. Knockdown of ELP4 function led to a significant reduction in brood size of C. elegans following exposure to ionizing radiation. Defective HR repair pathway can cause germline radiation sensitivity [ELP4 significantly reduced HR efficiency in the osteosarcoma cell line U2OS [ELP4 in HR is not known. Since ELP4/5/6 form a discrete subcomplex and share a RecA ATPase-like protein domain [Expression of  complex . TOV2978 mammals . ELP4 wasitivity . Using tine U2OS . Howevern domain ,53 that PUM3, EEF1A1, and ELP4, identified from our bioinformatics analysis of cell lines could be considered top priorities for further investigations based on support of their molecular functions as reported in the literature. Biological assessment of these candidates using more recently developed preclinical ovarian cancer cell models such as patient-derived organoids and patient-derived xenografts, may yield more accurate information regarding their role in conferring PARPi sensitivity as these models mimic the three-dimensional environment of patient tumor samples. Despite the utility of cell lines for drug development and biomarker discovery there are some limitations of these models. These may include selection of cells in vitro that harbor molecular genetic abnormalities that may not recapitulate the microenvironment and exposure to chemotherapeutic drugs of in vivo settings. Our collection of HGSOC cell lines, derived from long-term passages of ovarian cancer specimens, have been extensively characterized demonstrating that their molecular genetic features are consistent with those found in the original cancer specimens and some have retained the capacity to propagate as three-dimensional structures in vitro and in vivo ,29,30,49EEF1A1 in olaparib-sensitive HGSOC cell lines provides a clue that expression of at least one of our key candidate genes may be influenced by chemotherapy. EEF1A1 expression is lower in TOV3041G, derived from a post-chemo case  in the HGSOC cell line TOV2978G likely contributes to its sensitivity to carboplatin even though TOV2978G was not found to express BRCA1 mRNA or protein [Chemotherapy can drive genomic alterations and gene expression in tumor cells that could lead to resistance, and the cell lines derived from these tumors retain these alterations. Information about the chemotherapy status of the GDSC cell lines is not available via the GDSC database. Therefore, we could not systematically investigate whether alterations in our candidate genes were enriched in cell lines derived from cases that had chemotherapy compared to cell lines derived from cases without prior exposure to chemotherapy. However, this information is available for the HGSOC cell lines and mRNA expression of emo case , as compR repair  and in tPUM3 and EEF1A1 which are known to interact with PARP1, and ELP4 a recently discovered HR gene.Our findings associate several genes with olaparib response. We identify known olaparib response genes in relevant pathways such as DNA repair and cell cycle control but also discover novel genes that have not been previously associated with olaparib response such as 50) data for over 300 drugs and compounds [50. Dose response curves were fitted to fluorescence signal intensities using a non-linear mixed effects model [ftp://ftp.sanger.ac.uk/pub4/cancerrxgene/releases/release-7.0/v17.3_fitted_dose_response.xlsx, accessed on 8 July 2018. GDSC cell lines analysed in this study are presented in GDSC is a pharmacogenomic database (cancerrxgene.org) providing genomic data for over 1000 cell lines derived from diverse human cancers, and drug response  , and Genanalysis . This fo50 as response and z-score expression for all genes as predictors with tissue of origin, microsatellite instability (MSI) status , BRCA1/2 mutation status , first two principal components  and test (40%) sets, ensuring that these partitions were balanced to have similar proportions of cell lines from each tissue type. A linear regression model with elastic net regularization was fit using natural log ICmponents  of gene 2) of the variation in natural log IC50 with RMSE = 0.898 and mean absolute error (MAE) = 0.734. Genes with coefficients greater or equal to zero were considered significant gene predictors. Data partitioning, model fitting and evaluation, and visualization were done in R using caret [The performance of the elastic net multivariate model was evaluated on the test data partition . This mong caret , glmnet,50 as response and z-score of gene expression as a predictor, keeping the same additional predictor variables as the multivariate approach. Correction for multiple testing was done using False Discovery Rate (FDR), genes with FDR-adjusted p-values less than 0.05 were considered significant gene predictors. This was done in R using functions lm and p.adjust from stats package.Multiple ordinary least squares (OLS) linear regression models, for one gene at a time, were also done with natural log ICIn vitro olaparib response of 18 spontaneously immortalized human HGSOC cell lines  or BRCA2 (OV4453) [These cell lines have been previously characterized at genetic and molecular levels ,29,30,49Exome sequencing of the cell lines was done using the Illumina HiSeq 2000 platform, following target enrichment with the Roche Nimblegen SeqCap EZ exome v3 kit, at the McGill University and Genome Quebec Innovation Centre . Sequencing was paired-end with average read length of 100 bases. Sequencing adapters were trimmed and trailing low quality (Phred33 score >= Q30) bases were removed using Trimmomatic  . Target regions were grouped into bins of 267 bp size, on average, according to default settings and read depth for these bins were computed. Off-target coverage was also determined for each cell line. Read depth for each sample is median-centered, across bins, and corrected for GC content and repetitive sequence biases. Corrected bin-level coverage was compared to a neutral (or flat) reference which assumes all target and off-target regions are equally covered and diploid. Bin-level copy number ratios were aggregated into segments using the default circular binary segmentation algorithm with low-coverage and outlier bins filtered out. Genes involved in CNV segments were selected using the genemetrics command with minimum absolute log2 copy ratio threshold (−t) of 0.4  and minimum number of bins (−m) per gene of 5. Amplifications and deletions were defined by log2 copy ratio thresholds of 1 and −1, respectively.CNVkit  version n = 5) was compared to the mean expression level in resistant cell lines (n = 4). The lmFit function was used to fit robust linear models to the data and calculate mean expression. A moderated t-test was used to compare the expression between resistant and sensitive groups using the eBayes function. Resulting p-values were adjusted for multiple testing using false discovery rate (FDR). Significant differentially expressed genes were defined by FDR-adjusted p-value < = 0.05, and absolute log2 fold change >= 1.5. Gene expression profiling was done for all 18 HGSOC cell lines using the Clariom™ S human array. Normalization was done using Signal Space Transformation-Robust Multi array Average (SST-RMA) method. Normalized expression values per gene were converted to z-scores (mean-centred expression divided by standard deviation). Differential gene expression analysis was done using the linear models for microarray data (LIMMA ) packageSNVs that pass confidence filtering and are present at MAF of 0.1% or less in gnomAD database, or confirmed somatic in COSMIC were considered somatic variants and selected for mutational signature analysis. Mutational signatures  were derPUM3, EEF1A1) or involvement in HR (ELP4). We present these results to encourage further experimental and clinical research into olaparib, and other PARPi, focusing on PUM3, EEF1A1 and ELP4 to investigate whether genomic and molecular alterations in these genes affect olaparib response in vitro, elucidate molecular mechanisms by which these genes contribute to olaparib response, and assess the potential utility of genomic alterations in these genes, in relation to BRCA1/2 mutations and HR deficiency, for identifying patients most likely to benefit from olaparib treatment.These results implicate new genes as potential biomarkers of olaparib response from genomic data analyses of two independent groups of cancer cell lines. Using statistical methods we identify significant predictors of olaparib response based on gene expression, successfully validate some of these candidate genes by identifying genomic alterations  in olaparib-sensitive, -intermediate or -resistant HGSOC cell lines, and further highlight that promising validated genes have known relevant functions including interaction with PARP1 (


Background: Drug resistance to chemotherapeutic drugs or targeted medicines is an obstacle encountered in the treatment of non-small-cell lung cancer (NSCLC). However, the mechanisms of competing endogenous RNA (ceRNA) on the drug resistance in NSCLC are rarely reported. In this paper, the comprehensive expression profiles of lncRNAs and mRNAs in drug-resistant NSCLC cells were obtained by RNA sequencing.Methods: The dysregulated lncRNAs, miRNAs and mRNAs in drug-resistant NSCLC cell lines were identified by RNA-sequencing and bioinformatics methods.Results: A total of 39 dysregulated lncRNAs and 650 dysregulated mRNAs were identified between drug-resistant NSCLC cell lines and their parental cell lines. Additionally, 33 lncRNA-miRNA-mRNA pathways in the ceRNA network in drug-resistant NSCLC were constructed through bioinformatics methods and ceRNA regulatory rules. These comprised 12 dysregulated lncRNAs, five dysregulated miRNAs, and eight dysregulated mRNAs. In addition, lncRNA ATP2B1/miR-222-5p/TAB2 and lncRNA HUWE1/miR-222-5p/TAB2 were identified as potential ceRNA networks involved in drug resistance to NSCLC.Conclusions: The current study provides a promising therapeutic strategy against the lncRNA-miRNA-mRNA ceRNA regulatory network for NSCLC treatment and deepens our comprehension of the ceRNA regulatory mechanisms related to drug resistance to NSCLC. Non-small-cell lung cancer (NSCLC) accounts for approximately 85% of lung cancer, which is one of the most common malignant cancers in the world, and is characterized by high morbidity and mortality Various studies have proposed that somatic activating mutations, dysregulation of drug transport, and disorders of cell apoptosis pathways or cell cycle regulation are common mechanisms of drug resistance The competing endogenous RNA (ceRNA) mechanism stated that the transcripts of non-coding RNAs like long non-coding RNAs (lncRNAs), can act as natural microRNAs (miRNAs) sponges through competitively binding to miRNA response elements (MREs) on target mRNAs to inhibit their functions To explore the potential mechanisms of ceRNAs in NSCLC drug resistance, we detected the expression levels of lncRNAs, miRNAs and mRNAs in the drug-resistant NSCLC cell lines (A549/DDP and HCC827/GR) and their parent cell lines (A549 and HCC827) by RNA sequencing. We then carried out a comprehensive analysis of the dysregulated lncRNAs, miRNAs, and mRNAs using bioinformatics methods. Finally, based on the bioinformatics results and the ceRNA regulatory rules, a lncRNA-miRNA-mRNA network was constructed among the dysregulated lncRNAs, miRNAs, and mRNAs. This paper might provide new insights into the mechanisms of drug resistance and might have certain clinical significance for further research in this area.A549 cells were obtained from Shanghai Meixuan Biological science and technology LTD, and HCC827 cells were kindly provided by Stem Cell Bank, Chinese Academy of Sciences. A549 and HCC827 cells were grown in RPMI-1640  supplemented with 10% fetal bovine serum  and penicillin/streptomycin. The cisplatin-resistant A549/DDP cells and the gefitinib-resistant HCC827/GR cells were generated by gradient dose treatment for almost six months. Drugs were added to maintain resistance and were withdrawn one week before the experiment.Total RNA from the cell lines was extracted by Trizol reagent  according to the instruction. The quantity and purity of total RNA were measured by Bioanalyzer 2100 and RNA 6000 Nano LabChip Kit  with a RIN number ≥8.First, ribosomal RNA was depleted from approximately 10 μg of total RNA by the Epicentre Ribo-Zero Gold Kit . And then, the rRNA-depleted RNA was broken into small pieces using divalent cations under an elevated temperature and then reverse-transcribed to create the final cDNA library by the mRNA-Seq sample preparation kit . Then, paired-end sequencing (300 ± 50 bp) was performed on Illumina X10  according to the vendor's recommended protocol.http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). The reads of each sample were mapped to the human genome by Bowtie 2 Adaptor contamination, low-quality bases, and undetermined bases were removed using Cutadapt, and the quality of sequencing was verified by FastQC  score P ≤0.05 using R package-Ballgown The expression values of lncRNAs and mRNAs were calculated as FPKM (fragments per kilobase per million) by StringTie -ΔΔCT methods were employed to analysis the relative expression levels of lncRNAs. The primer sequences were listed in Table Quantitative real-time PCR (qRT-PCR) was performed on Applied Biosystems QuantStudio 5 . Total RNA was extracted from A549, A549/DDP by Trizol  and reversely transcribed into cDNA by First Strand cDNA Synthesis Kit . The 2cis-target genes of the dysregulated lncRNAs 100 kbp upstream and downstream of the chromosome were picked using a Python script. The neighboring genes were then performed for gene ontology (GO) analysis and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis. Significance is expressed as a P-value < 0.05.To clarify the potential functional roles of the dysregulated lncRNAs, the First, starBase v3.0 https://cancergenome.nih.gov/). The optimal cut-off point for the expression of all RNAs in the ceRNA regulatory network was divided into high-risk and low-risk groups using the “cutp” function from R package-survMisc. Survival analysis of all RNAs in the ceRNA network was calculated by Kaplan-Meier analysis, which was performed using R package-survival. P < 0.05 was considered statistically significant.The data from the lung adenocarcinoma patients were downloaded from the database of The Cancer Genome Atlas . SiRNAs were purchased from Shanghai GenePharma Co., Ltd . The sense sequence of siTAB2 is 5'-GCUGGGUAUCUCAGUUUAATT-3' and the antisense sequence of siTAB2 is 5'-UUAAACUGAGAUACCCAGCTT-3'. The sense sequence of negative control (siNC) is 5'-UUCUCCGAACGUGUCACGUTT-3'and the antisense sequence of siNC is 5'-ACGUGACACGUUCGGAGAATT-3'. Cells were transfected for at least 24 h before the subsequent experiments.A549/DDP cells were seeded in plates and transfected with 40 nM siRNAs using jetPRIMETM Imaging System .A549/DDP cells were seeded in 6-well plates at a density of 300,000 cells/well and then transfected with 40 nM siNC or siTAB2 after 24h of cultivation. After 48h of transfection, the cells were lysed using RIPA lysis buffer with protease inhibitor. Total protein (20 μg) was separated on 10% SDS-PAGE, transferred to PVDF membranes (Millipore) and immunoblotted with a rabbit polyclonal antibody against TAB2  or GAPDH . Bands were detected by ChemiDoc® .Growth inhibition assay was assessed by measuring thiazolyl blue (MTT). A549/DDP cells were seeded in 96-well plates at a density of 4,000 cells/well and then transfected with 40 nM siNC or siTAB2 after 24h of cultivation. Different concentrations of DDP were added to the cells after 24h of transfection, and each group was set in triplicate. After 48h of treatment with DDP, 15μL 5mg/ mL MTT  was added into the wells and cultured at 37 °C for 4 h. The medium was removed and 100μL DMSO was added into the wells. The plate was shocked and the absorbance was measured at 570 nm using PerkinElmer Multimode Plate Reader EnVisionP ≤ 0.05 were chosen as lncRNAs candidates. Venn analysis displayed that there were 39 dysregulated lncRNAs, including 19 up-regulated lncRNAs and 20 down-regulated lncRNAs  and their parent cell lines (A549 and HCC827) on an Illumina X10. The global lncRNA abundances on different chromosomes were visualized based on sample expression and class code expression by mapping all lncRNA transcripts to a human reference genome  and their parent cell lines (A549 and HCC827) with a fold change ≥ 2.0 or ≤ 0.5 and To further understand the roles of the dysregulated lncRNAs, miRNAs, and mRNAs in drug-resistant NSCLC cell lines and to clarify the relationships among them, a lncRNA-miRNA-mRNA-related ceRNA regulatory network was done in drug-resistant NSCLC cell lines. The dysregulated miRNA expression levels in the drug-resistant NSCLC cell lines (A549/DDP and HCC827/GR) and their parent cell lines (A549 and HCC827) are described in our previous study First, starBase v3.0 and miRcode were employed to analyze the relationships between the dysregulated lncRNAs and miRNAs. Second, miRanda, miRcode, and TargetScan were employed to decode the relationships between the dysregulated miRNAs and mRNAs. And the ceRNA network was constructed in drug-resistant NSCLC cell lines by incorporating 12 lncRNAs (10 up-regulated and two down-regulated), five miRNAs (two up-regulated and three down-regulated), and eight mRNAs (five up-regulated and three down-regulated), according to the ceRNA regulatory mechanism and the change trend of lncRNAs, miRNAs and mRNAs. This was visualized using Cytoscape 3.6.1 (Fig. P < 0.05; Fig. TCGA data for lung adenocarcinoma were employed to identify the prognostic characteristics of the promising lncRNAs, miRNAs, and mRNAs in the ceRNA regulatory network. As a result, four lncRNAs and one mRNA were found to be significantly related to overall survival (P-value < 0.05 (Fig. To further confirm the possible interaction of lncRNAs, miRNAs, and mRNAs in the constructed ceRNA network, correlation analysis based on TCGA data was conducted between the expression levels of 12 lncRNAs and their paired mRNAs in lung cancer. It was shown that lncRNA ATP2B1 and TAB2, and lncRNA HUWE1 and TAB2 had a direct linear correlation with the correlation coefficient ≥ 0.3 and .05 Fig. . CombineTo further investigate the roles of TAB2 in the sensitivity of drug-resistant NSCLC cell lines, A549/DDP cells were then transfected with siNC or siTAB2. After 48h, the mRNA and protein levels of TAB2 were reduced as shown in Fig. Drug resistance to chemotherapeutic drugs or targeted medicines is an obstacle encountered in NSCLC treatment Most lncRNAs and miRNAs may function as one member of the ceRNA regulatory networks. In fact, several reports have suggested that the ceRNA networks are related to the occurrence and progression of tumors, such as hepatocellular carcinoma There have been a few reports suggesting that miR-222-5p and TAB2 are related to the occurrence and progression of tumors or drug resistance. MiR-222-5p has been reported to be involved in triple-negative breast cancer The mechanisms behind resistance to chemotherapeutic drugs or targeted medicines may differ greatly, but it is anticipated that some overlapping mechanisms between these two distinct types of drug resistance may exist. For example, ECM, which plays a vital role in biological processes such as cell proliferation, differentiation, and adhesion To our knowledge, this is the first report to construct and analyse the ceRNA network of lncRNAs, miRNAs and mRNAs in NSCLC drug resistance to chemotherapeutic drugs or targeted medicines. However, there are some limitations to our study. For example, the validation of potential lncRNAs, miRNAs, and mRNAs in drug resistance of NSCLC were not performed, and the mechanism of the ceRNA network was not confirmed by luciferase reporter assay or RNA immunoprecipitation assays.In conclusion, we provide here a comprehensive expression profile of lncRNAs, miRNAs, and mRNAs. We also constructed a lncRNA-miRNA-mRNA ceRNA regulatory network for drug resistance to chemotherapeutic drugs or targeted medicines in NSCLC. In addition, we found that lncRNA ATP2B1/miR-222-5p/TAB2 and lncRNA HUWE1/miR-222-5p/TAB2 are potential ceRNA regulatory networks in NSCLC drug resistance according to TCGA data and bioinformatics analysis. These results revealed that the lncRNA-miRNA-mRNA ceRNA regulatory network might play a vital role in drug resistance to NSCLC and might be a promising therapeutic strategy for further study. These results will deepen our comprehension of the ceRNA mechanisms involved in drug resistance to NSCLC.Supplementary table.Click here for additional data file.


Karenia brevis and Ostreopsis ovata blooms induces respiratory distress among others. The biogenics hypothesis, however, suggests that regular airborne exposure to natural products is health promoting via a downregulation of the mechanistic target of rapamycin (mTOR) pathway. Until now, little scientific evidence supported this hypothesis. The current explorative in vitro study investigated both health-affecting and potential health-promoting mechanisms of airborne phycotoxin exposure, by analyzing cell viability effects via cytotoxicity assays and effects on the mTOR pathway via western blotting. To that end, A549 and BEAS-2B lung cells were exposed to increasing concentrations (ng·L−1–mg·L−1) of (1) pure phycotoxins and (2) an extract of experimental aerosolized homoyessotoxin (hYTX). The lowest cell viability effect concentrations were found for the examined yessotoxins (YTXs). Contradictory to the other phycotoxins, these YTXs only induced a partial cell viability decrease at the highest test concentrations. Growth inhibition and apoptosis, both linked to mTOR pathway activity, may explain these effects, as both YTXs were shown to downregulate this pathway. This proof-of-principle study supports the biogenics hypothesis, as specific aerosolizable marine products  can downregulate the mTOR pathway.Respiratory exposure to marine phycotoxins is of increasing concern. Inhalation of sea spray aerosols (SSAs), during harmful  The (reported) occurrence of harmful algal bloom (HAB) effects to man and environment has increased over the last decades ,2. ToxinThroughout mankind’s history, exposure to seawater and coastal air has been linked to positive health effects. The first records of thalassotherapy date back to the ancient Egyptians, Greeks, and Romans ,9. FairlIn this explorative in vitro study, we aimed to investigate the potential effects of airborne exposure to aerosolizable marine phycotoxins. Adverse effects were evaluated through the assessment of cell viability effects using cytotoxicity assays. The potential downregulation of the mTOR pathway was evaluated via western blotting. Furthermore, given the importance of the mTOR pathway in both normal and cancer cells, we opted to incorporate both a normal (BEAS-2B) and adenocarcinoma (A549) human lung cell line in our study. We first studied the effects of pure phycotoxins. Next, we also examined the effects of homoyessotoxin (hYTX) in a more realistic SSA matrix; this treatment is further referred to as hYTX extract.Two different cell lines were used in this study: Adenocarcinoma alveolar  and normal bronchial  cells. The dose response curves (DRCs) for both cell lines derived from the different phycotoxins are plotted in −1. This was performed using only the A549 cells, as from previous experimental results, we would not expect a different outcome for the BEAS-2B cells. A comparison between these two starting cell densities  is made in −1) is smaller than the variability between successive experiments.To test the effect of the use of different starting cell densities, part of the MTT assays testing YTX were performed at 8000 cells·well−1), a much lower cell density and a high frequency of abnormal cell morphology is visible. In the mid-concentration range , somewhat intermediate results are observed, with a slightly lower cell density and a relatively lower amount of normal-shaped cells. These results are complementary with the western blot results (see discussion).Following every 43-h exposure period, the cell morphology and density were visually assessed and photographed at 100× magnification. In In exploratory immunoblotting experiments, only YTX exhibited an inhibitory effect on the phosphorylation of S6 ribosomal protein (S6RP), i.e., a downstream phosphorylation target of mTORC1. Therefore, all further experiments were conducted with YTX and analogues of YTX, like hYTX, using wide concentration ranges.−1) for all the examined markers. The downstream phosphorylation targets  showed a significant decrease in phosphorylation for both cell lines  while the phosphorylation of Akt only showed a significant increase for the BEAS-2B cells. An explanation for these variable Akt results is discussed below. Overall, the results are largely comparable for both cell lines and show an inhibitory effect of YTX on the mTOR pathway. This effect (at 1 µg YTX·L−1) is even more expressed than the inhibitory effects of the positive control treatment .In the first main experiment, the effects of YTX on both the A549 and BEAS-2B cell lines were examined. The differential phosphorylation for the examined markers of the mTOR pathway , S6RP, eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1)) are shown in −1 and only A549 cells were incorporated in this experiment. A representative example of one of the blots is shown, as a cropped non-edited version, in the −1) and the complex mixture of the hYTX extract, the results of this experiments are less pronounced. They, however, still support the previous experiments (see discussion).In a subsequent experiment, hYTX and hYTX extract (produced as described below) were dosed to the A549 cells . Due to Our results  indicate50 value was between 500 and 1000 µg·L−1. Wang et al. [−1) to OA and reported, using MTT cell viability assays, a 48-h EC50 value of 34 µg·L−1. Based on the cell morphology, they proposed apoptosis as the main cause for the negative cell viability effect. Botana et al. [50 values for YTX and hYTX of 3.2 and 0.62 µg·L−1, respectively. Depending on the exposure period they used in their experiments, the observed effects of YTXs were attributed to apoptosis or autophagy mechanisms [Few comparable in vitro experiments have been performed so far. To the best of our knowledge, there are at present no PbTx(-2) effect data for lung cells available in the literature. One of the few records concerning the cell viability effects of PbTx-2 was found for a leukemic T cell line (Jurkat cells). Although Walsh et al.  did not g et al.  exposed a et al.  performechanisms . In gene50 of 100–500 μg·kg−1) in mice following intraperitoneal injection [−1. A decreasing viability trend could, however, still be observed in the high concentration range for YTX and hYTX , protein levels, and T-lymphocytes, and activate different types of induced cell death [YTXs are, in terms of exposure via ingestion (food), considered as the least potent group of phycotoxins. No human intoxications have been reported so far . YTXs arnjection . The expand hYTX . If morell death . Based oll death  suggestell death  as the i−1) of pure YTX induced a significant downregulation of the phosphorylation of both downstream targets of mTORC1  for both the normal BEAS-2B and carcinoma A549 lung cell lines. Such an inhibitory effect of YTX on mTOR pathway activity was until now only described for human glioma cells exposed to much higher concentrations of 34 and 286 µg·L−1 [The results from the western blot experiments, summarized in 6 µg·L−1 . As discIn −1) of pure hYTX induced significant downregulation of S6RP phosphorylation (−1) of pure YTX in the previous experiment  [−1, calculated in the In this study, we aimed to investigate potential human health effects of airborne exposure to phycotoxins that can be present in SSAs. Until now, only a few brevetoxins (PbTxs) and ovatoxins have been detected and quantified in environmental SSAs. Reported PbTx air concentrations during HAB events of 0 ng·m−3 . Althougm−3 [−1)  that indYessotoxin (YTX) and homoyessotoxin (hYTX) were purchased as certified reference material (CRM) from the National Research Council Canada (NRC). All other toxins were analytical-grade products and dissolved, depending on their lipophilic properties, in 50% or 100% methanol or ethanol. Okadaic acid (OA) was purchased from LC Laboratories, domoic acid (DA) at Sigma-Aldrich , brevetoxin-2 (PbTx-2) from MARBIONC, and Torkinib (PP242)—a known mTOR kinase inhibitor—from MedChem Express .Protoceratium reticulatum (SCCAP K-1474) at a density of 106 cells·L−1. A prior chemical analysis, following the exact procedures described by Orellana et al. [−1 during 12 h. The detailed procedure to make extracts of SSA filter samples is described in the An experimentally produced SSA extract containing hYTX, in this manuscript referred to as hYTX extract, was generated using a marine aerosol reference tank (MART). This MART was constructed as described by Stokes et al. . The MARa et al. , showed −1 penicillin, and 100 µg·mL−1 streptomycin, at 5% CO2, 37 °C, and a relative humidity of 95% to 100%. Confluent cultures were sub-cultured, using 0.5% Trypsin–EDTA, and split two times per week in a 1/6 (BEAS-2B cells) or 1/8 ratio (A549 cells) or used in the experiments as explained below. Throughout our research, the passage number of all cultured lung cells never exceeded the value of 50.To assess the potential effects of airborne exposure to marine phycotoxins, two epithelial lung cell lines were used in a series of in vitro experiments: The adenocarcinoma alveolar basal A549 cell line and the normal bronchial BEAS-2B cell line. As inhibition or downregulation of the mTOR pathway has been associated with anti-cancer therapies and positive health effects, we opted to use both a normal (BEAS-2B) and adenocarcinoma (A549) human lung cell line in our study. As such, these cell lines served as models for  exposed lung tissues and, more generally, the lower respiratory tract. The choice to use cell lines originating from the lower respiratory tract is discussed in the −1 MTT dissolved in Dulbecco’s phosphate-buffered saline  with the additives as described above, but without phenol red and only 5% of FBS. The cell suspension was diluted and seeded in 96-well plates at 3000 cells per well in 75 µL of medium. Ten hours after incubation, adhered cells were exposed to phycotoxins , added as single substances in 25 µL of medium. Six replicates were used per concentration treatment. Negative, positive, and solvent control treatments were included in each experiment. For the negative control treatments, nothing was added to the medium, and for the positive control treatments, 3% SDS was added. The solvent control contained the same methanol or ethanol concentration as that used in the highest phycotoxin concentration treatments (maximum 2.9% ethanol). After a 43-h exposure period, the cell morphology and confluence were visually assessed and photographed  using ane D-PBS;  was adde−1 for the A549 and BEAS-2B cell line, respectively. Ten hours after incubation, phycotoxins  were added as single substances dissolved in 60 µL of methanol. Three replicates were used per phycotoxin treatment. Negative  and positive  control treatments were included in every experiment. No solvent control was tested as all treatments, including the negative control, contained the same methanol concentration .SDS-PAGE and western blotting were used to assess the mTOR pathway activity of exposed lung cells, allowing us to study the potential positive health effects of phycotoxins as suggested by the biogenics hypothesis. Since the phosphorylation of mTOR has been shown to be a less reliable marker ,35, we oAfter a 43-h exposure, protein cell extracts were prepared and analyzed with SDS-PAGE and western blotting procedures, as discussed in the 10) and 50% (EC50) decrease in cell viability were derived from the DRC models.The raw data of the MTT assays consisted of absorbance measurements. Using the RStudio software, cell viability dose response curve (DRC) models were fitted to these data. The exact procedure of how the raw absorbance data were transformed to cell viability values and how the final DRC models were made is explained in the p > 0.05). Subsequently, one-sample t-tests were performed to check for significant differences (p < 0.05) with the negative control (=0%).The raw data of the western blot analyses were image-derived chemiluminescent response values. We were specifically interested in the down or upregulation in the phosphorylation of the three target proteins. To that end, the ratio of the phospho-specific and respective non-phospho-specific signals was divided by the ratio of these measurements of the corresponding negative control (on the same blot) and subtracted with 1. In this way, for all treatments and examined proteins, a down (<0%) or upregulation (>0%) in phosphorylation, as compared to the negative control (=0%), was determined. Data within each treatment were checked for normality with a Shapiro–Wilk test (The raw data of the performed MTT and western blot experiments (Raw data—Van Acker (2020) Aerosolizable Marine Phycotoxins and Human Health Effects—In Vitro Support for the Biogenics Hypothesis.zip) are available on the marine data archive (MDA) of the Flanders Marine institute under “VLIZ External datasets— Public/UG/”.


Cancer cell lines are amongst the most important pre-clinical models. In the context of epithelial ovarian cancer, a highly heterogeneous disease with diverse subtypes, it is paramount to study a wide panel of models in order to draw a representative picture of the disease. As this lethal gynaecological malignancy has seen little improvement in overall survival in the last decade, it is all the more pressing to support future research with robust and diverse study models. Here, we describe ten novel spontaneously immortalized patient-derived ovarian cancer cell lines, detailing their respective mutational profiles and gene/biomarker expression patterns, as well as their in vitro and in vivo growth characteristics. Eight of the cell lines were classified as high-grade serous, while two were determined to be of the rarer mucinous and clear cell subtypes, respectively. Each of the ten cell lines presents a panel of characteristics reflective of diverse clinically relevant phenomena, including chemotherapeutic resistance, metastatic potential, and subtype-associated mutations and gene/protein expression profiles. Importantly, four cell lines formed subcutaneous tumors in mice, a key characteristic for pre-clinical drug testing. Our work thus contributes significantly to the available models for the study of ovarian cancer, supplying additional tools to better understand this complex disease. Ovarian cancer is the most lethal gynaecological cancer, and fifth leading cause of malignancy-related deaths in North American women . OvarianBRCA1 or BRCA2 mutation but also, to a lesser degree, germline mutations in RAD51C, RAD51D, PALB2, and FANCI, with a higher incidence in the HGSC subtype [BRCA1/2 mutations, HGSC tumors harbor a virtually ubiquitous somatic TP53 mutation (>95%), as well as less commonly mutated genes, including CSMD3, NF1, CDK12, and FAT3 [TP53-mutated, and instead show high-frequency mutually exclusive mutations in KRAS, BRAF, NRAS, or ERBB2 [PIK3CA, ARID1A, and KRAS mutations, amongst others, as well as a frequent loss of PTEN expression [KRAS mutation, in addition to TP53, BRAF, and CDKN2A alterations [ARID1A mutations, as well as moderately frequent mutations of PIK3CA, CTNNB1, and PTEN, usually presented as loss of expression or loss of heterozygosity, with some tumors rarely harboring a TP53 mutation [The most common risk factor for EOC is a family history of ovarian cancer. An estimated 25% of all ovarian cancer cases could be due to inherited genetic mutations, the most frequent being a germline  subtype ,9,10,11. subtype . Furtherand FAT3 ,14. LGSCor ERBB2 ,16,17. Cpression ,16,18,19erations ,16,20. Emutation ,16,21. Dmutation ,23,24. Amutation . Over thmutation ,29,30,31In this context, patient tumor-derived cell lines are efficient, inexpensive, and easy to maintain, and thus make for an attractive human pre-clinical cancer model ,33. OvarTP53-mutated, whereas the MC and CCC cell lines were TP53 wild-type but harbored KRAS mutations specific to their respective subtypes. Importantly, four of these cell lines form xenograft tumors in mice, a key characteristic for pre-clinical drug testing. These 10 new cell lines contribute significantly to the EOC cell lines available for research by their diversity and molecular characteristics.Here, we present 10 novel patient-derived EOC cell lines (from 10 different patients) and their generation, and describe their in vitro and in vivo growth characteristics, molecular biology, genetic mutation profiles, and histopathology. Eight of these cell lines were identified as HGSC cells, and two were found to be of the MC and CCC subtypes, respectively. All of the HGSC cell lines were The cell lines were derived from the samples of 10 patients  treated between 2001 and 2010, whose clinical characteristics are described in None of the patients harbored a somatic BRCA mutation. Patients 2085 and 2881 had a family history of breast cancer and malignant neoplasm of the urinary tract, respectively, whereas patients 2929 and 3392 had a previous personal history of colorectal cancer of the sigmoid junction and breast cancer, respectively. Histopathology indicated that 7 of the 10 primary tumors were of the HGSC subtype, one was of the MC subtype (2414), and one was of the CCC subtype (3392). As patient 3331 did not undergo surgery, histopathology was not possible, but cytology confirmed that the patient’s tumor was an adenocarcinoma (AC).Sampling that resulted in the described cell lines for each of the 10 patients was done between 2004 and 2007. This sampling coincided with initial debulking surgery in the case of 6 of the patients  or was done at a later point during laparotomy  or ascites collection  . Four ofNine of the ten cell lines displayed homogenous morphology after 60 passages, whereas one of the cell lines, OV3291, exhibited slowed growth after 50 passages and reached growth arrest before reaching 60 passages. This cell line was thus tested after reaching 30 passages, but before reaching passage 45. For the most part, the morphology of the cell lines exhibited the characteristic flattened cobblestone-like appearance of epithelial cells . Two of TP53 mutation; most (5/8) were missense mutations with amino acid substitutions  and a splicing variant mutation (OV2978). All of these TP53 mutations are described in the IARC TP53 database [TP53 mutations  and CCC (TOV3392D) cell lines analyzed but did not detect mutations in any of the other prevalently mutated genes in these subtypes, including PIK3CA, ARID1A, BRAF, PTEN, CTNNB1, PPP2R1A, and NRAS (TP53) and OV3291 (TP53 and CDK12) cell lines  and that the MC and CCC cell lines grouped in a separate cluster, confirming the distinct molecular identity of the derived cell lines a. Cell lp < 0.0001)  d. These Due to the selection pressure inherent in establishing immortalized cell lines, it is important to verify that the cell line obtained reflects the EOC subtype of the original tumor. Therefore, we performed specific protein biomarker analyses of tumor tissue samples and cell lines by immunohistochemistry (IHC) and Western blot (WB), respectively. The tumor tissue of origin of the corresponding patient was subjected to a hematoxylin and eosin (H&E) staining, followed by IHC stains for various described epithelial ovarian cancer biomarkers  Figure . The repPrevious work has shown the H&E and IHC staining of the tumor of origin for patients 3291 and 2978 , and an TP53 is mutated in more than 95% of cases, which is reflected at the expression level either by robust overexpression (missense mutation) or complete absence (null mutation) of the p53 protein [TP53 mutations , a known p53 target [CDKN1A in the wild-type TP53 cell lines  confirmed the epithelial origin of the patient tumors  and asso protein ,56,58. Autations , Table 3ll lines , Table 3ern blot . On the 3 target ,60, as oll lines .TP53 and CDK12 mutations, as well as by their proximal gene expression clustering  is solely expressed in the HGSC tumors . Howeverustering a. Intrigoteasome , ruling The Western blot analysis of the TOV2414 cell line, on the other hand, showed a lack of PAX8 expression . This diPrimary ovarian MC and colorectal metastases to the ovary overlap on many commonalities, making them difficult to differentiate ,61. MostOvarian CCC, on the other hand, is often confused with metastatic endometrial or renal clear cell carcinoma (RCCC), due to overlapping characteristics ,67,68,69CDKN2A mRNA (p16 protein)  , which iTumor expression of ER and PR was shown to help distinguish the different subtypes of EOC ,73. Our Collectively, our protein biomarker analysis together with our gene expression and mutational profiling demonstrate the suitability of our cell lines as pre-clinical models to specific EOC subtypes.Growth characteristics were assessed by measuring doubling times  and by lt-test, p = 0.0013) but were not significantly different when compared to each other . The confluence-based proliferation curves show that TOV2414 was the fastest-growing cell line, whereas OV2085 was the slowest , whereas TOV3392D and TOV2929D had the slowest migration velocity , showing little to no ability to migrate . OV3331 migrated visibly with low velocity (9.7 µm/h), whereas TOV2835EP, TOV2881EP, OV2978, TOV3121EP, and OV3291 demonstrated similar intermediate wound-healing efficacy (32.4–42.9 µm/h)  . The mig50) of 18.4 and 11.2 µM respectively, significantly higher than all the HGSC cell lines . This chemoresistance cannot be attributed to an inherent low growth characteristic of these cell lines, since they were found to have the fastest doubling time , significantly more sensitive than the other HGSC cell lines tested . On the other hand, TOV2835EP, TOV2929D, TOV3121EP, OV3291, and OV3331 exhibited intermediate sensitivity to carboplatin (IC50 between 1 and 5 µM)  . The senn = 5 mice per injection site for each cell line) , forcing ethical interruption of the experiment and sacrifice of the mice between 53 and 68 days post-injection. Of the other tumor-forming cell lines, OV2085 grew the fastest, followed by TOV2414 and OV3331, which reached a tumor volume of 500 mm3 after an average 65, 125, and 170 days, respectively  or intraperitoneally (IP) in NOD rag gamma (NRG) mice (ll line) . Four ofectively . None ofectively .Cell lines injected IP were tested for formation of ascites, tumors at site of injection, and metastases at abdominal organs. Only TOV2414 and TOV3392D formed peritoneal tumors at the site of injection. OV3331, OV2085, and TOV2929D formed medium to large metastases in most cases, whereas TOV2414, TOV2881EP, and TOV3392D formed very small metastases. OV3331, OV2085, TOV2881EP, and TOV2929D all formed large volumes of ascites, between 2 and 8.5 mL per mouse .Epithelial ovarian cancer is a highly heterogeneous disease that poses critical challenges when choosing appropriate pre-clinical models relevant in translational science. On one hand, EOC is classified into five main subtypes  with differences in morphology, etiology, pathogenesis, pathology, molecular biology, and prognosis ,20,21,44Despite their limitations, tumor-derived cell lines remain one of the most versatile pre-clinical models; they can be cultured two-dimensionally, as three-dimensional spheroids, and even in vivo as xenografts. However, concerns exist on the process of adaptation to in vitro cell culture conditions, which can be reflected on the success rate of cell line generation. The 10 novel EOC cell lines described in this publication were derived in the same time frame (2004–2011) as 16 others from our laboratory ,38,39, wTP53 mutation, and the two non-HGSC cell lines TOV2414 and TOV3392D did not. These data were confirmed by WB of whole cell lysates and IHC staining of the tumor of origin for each cell line, where cell lines with missense TP53 mutations had a robust p53 overexpression, and those with frameshift/splice TP53 mutations (null) did not express the p53 protein or mRNA. The two non-mutated cell lines, on the other hand, showed low or focal expression of p53 in IHC and moderate expression of the protein in WB. These are expected p53 phenotypes, as previously described [From the 10 novel patient-derived EOC cell lines described here, eight were identified as HGSC, one as MC, and one as CCC. Each cell line was successfully characterized as belonging to the subtype of the original patient sample by detailed protein biomarker  and mutaescribed . ConcordCDKN2A gene (p16 protein) [FAT3, CDK12, and CSMD3 genes [Further confirmation of the HGSC subtype involved the protein expression profiles of WT1, PAX8, and ER, ; the mRNprotein) ,72; and D3 genes . Most imD3 genes ,37,38,39D3 genes , the staOf the other HGSC cell lines, OV2085 and OV3331 are attractive pre-clinical models, in that they respectively show fast and slow in vivo growth when injected SC, and they both form IP tumors . These cCell lines OV2978 and OV3291 are derived from ascites, and are matched to their ovarian tumor cell lines derived from samples collected at the same time point for their corresponding patients . For theKRAS mutation, absence of SATB2 and focal expression of PAX8 [TP53 wild-type, harbours an uncommon but recurrent KRAS mutation, in addition to its cell population phenotype of clear cells and hobnail nuclei, as well as expression of Napsin A and absence of ER and PR, strongly confirming its CCC subtype rather than metastatic endometrial carcinoma [As for the MC cell line TOV2414, strong indicators for its ovarian mucinous subtype, aside from wild-type p53 and absence of WT1 expression, include the observed  of PAX8 ,55,62. Tarcinoma ,66,93,94arcinoma ,50,51,95Although several EOC cell lines were reported in the literature, a large number of these were insufficiently characterized, lacking important histological and molecular information. These include recently characterized ovarian cancer cell lines, where information regarding the tumor of origin, i.e., histology and protein biomarker analysis is not available for all the patients from which the cell lines were derived ,90,96. MTumor and ascites samples were obtained from patients from the Centre hospitalier de l’Université de Montréal (CHUM), Division of Gynaecologic Oncology, following informed consent. The stage was determined at the time of surgery by an on-site gynaecologic oncologist following the FIGO classification criteria . Histolo2, and 5% CO2 throughout the derivation process, following a previously established protocol [2, 5% CO2) and grown in complete OSE medium, consisting of OSE medium , 10% fetal bovine serum , 0.5 µg/mL amphotericin B (WISENT Inc.), and 50 µg/mL gentamycin sulfate  . Cells were passaged by trypsin 0.05%  digestion before reaching confluence, and culture medium was replaced weekly if cells were not passaged for more than seven days. All assays on these cell lines were conducted between passages 60 and 80, except in the case of OV3291, a non-immortalized cell line, which were conducted between passages 30 and 45.Ten cell lines were established from samples originating from ten patients: 2085, 2414, 2835, 2881, 2929, 2978, 3121, 3291, 3331, and 3392. All cell lines were kept in low oxygen conditions at 37 °C, 7% Ohttps://cesgq.com/). Alignment to the human genome NCBI37/hg19 was also performed by this facility to obtain BAM files of each of the 10 cell lines. BAM files were then uploaded into the public European Galaxy Network [TP53, BRCA1, BRCA2, NF1, GABRA6, RB1, CSMD3, CDK12, FAT3, ARID1A, BRAF, PTEN, PIK3CA, CTNNB1, PPP2R1A, NRAS, KRAS) was achieved using freebayes [Libraries for whole exome sequencing (WES) were prepared from 500 ng of DNA using the NimbleGen SeqCap EZ Human Exome Library v3.0 kit , followed by paired-end sequencing on the HiSeq 4000 , according to recommended protocols, at the Centre d’expertise et de services (CES) Génome Québec  according to manufacturer’s instructions. Then 2.8 µg of DNA target was hybridized on Clariom™ S Assay HT, human  and processed on the GeneTitan® Instrument  using the instrument’s Hyb-Wash-Scan automated workflow. Obtained CEL files were extracted and normalized using the Transcriptome Analysis Console (TAC) 4.0 software (Affymetrix). In this study, we performed subsequent gene expression analyses on the 10 cell lines described herein, as well as the matched TOV2978G and TOV3291G cell lines. For these 12 cell lines, unsupervised hierarchical clustering and principal component analysis (PCA) were performed using the TM4 MultiExperiment Viewer v3 software (MeV), a free, open-source tool for analyzing microarray data [RNA from 32 EOC cell lines, which includes 10 from this study and 22 previously characterized by our group ,37,38,39ray data .To demonstrate that the eight HGSC cell lines described here were clinically relevant, their microarray data (plus those from the two matched TOV2978G and TOV3291G cell lines) were compared to that of the publicly available Affymetrix U133a gene expression microarray data from 593 HGSC tumors from the TCGA cohort. The whole Affymetrix dataset was downloaded using the UCSC Xena Functional Genomics Explorer platform . To harmTissue sections (4 μm thick) were entirely stained with automated stain kit  Ventana were add® TGX™. Stain-Free 4–15% gradient Tris-glycine SDS-polyacrylamide 15-well gels (Bio-Rad Laboratories) and transferred onto 0.2 µm nitrocellulose membranes with the Trans-Blot Turbo transfer system (Bio-Rad Laboratories) using the mixed molecular weight program. Membranes were blocked with a PBS-Tween-milk solution  and incubated with primary antibodies  containing a protease and phosphatase inhibitor cocktail  on ice for three times 5 min, vortexing between each incubation. Protein concentration was measured by Bradford protein assay  using the GENESYS 10S US-Vis spectrophotometer . Then 30 µg of total protein extract were loaded and migrated at 100V in Mini PROTEANtibodies  overnigh2C and 1C respectively represent the later and earlier cell counts at two distinct time points, and Δt represents the elapsed time between cell counts 2C and 1C. Cell confluence was followed by live cell imaging using the IncuCyte® ZOOM System  and calculated using the IncuCyte® ZOOM 2016B software (Essen BioScience Inc.), where specific confluence masks were created for each individual cell line based on their morphologies , washed with PBS, and incubated in NCC. Scratches were monitored by live cell imaging using the IncuCyte® ZOOM System , and images were analyzed using the publicly available MRI Wound Healing Tool macro on ImageJ [Cells were seeded at confluence in a 96-well plate and incubated in NCC for 24 h. Wells were subsequently scratched using the IncuCyten ImageJ ,108. Resv/v methanol and 0.5% m/v methylene blue . Colonies were counted using a stereomicroscope, and the count for each concentration of treatment was reported as mean percent of control wells. Half maximal inhibitory concentration (IC50) values were calculated using the GraphPad Prism 7 software . Each individual experiment was performed in duplicate and repeated three times.Carboplatin sensitivity was determined by clonogenic survival assays, as previously described ,109. Celtm1Mom IL2rgtm1WjlRag1/SzJ  mice  at subcutaneous left gluteal injection (SC) or intraperitoneal (IP) sites, as previously described [6 cells in 100 µL of cold Dulbecco’s phosphate-buffered saline (D-PBS)  and 100 µL of either Matrigel® Matrix  for SC injections or D-PBS for IP injections. The mice were housed under sterile conditions in a laminar flow environment with unrestricted access to food and water. Formation of tumors, ascites, and metastases was evaluated twice a week for over 200 days. Animals were sacrificed before the mice reached certain limit points established by CIPA in accordance with guidelines by CCAC.All animal studies were approved by the Institutional Committee on Animal Protection (Comité institutionnel de protection des animaux-CIPA) protocol according to the Canadian Council on Animal Care (CCAC) (protocols C14008AMMs and C18010AMMs). Tumorigenic potential was assayed by injection of cells in NOD.Cg-escribed . A totalOur work reports ten novel immortalized EOC cell lines, providing well-characterized pre-clinical models for the benefit of the research, medical, and pharmaceutical communities, in order to advance therapeutic strategies for this deadly disease. Thorough analyses of protein biomarkers, somatic mutations, and gene expression demonstrate that each cell line represents critical aspects of the histological subtypes from which they were derived. These cell lines have diverse in vitro growth characteristics critical to cover the individual differences of EOC patients. Furthermore, some of the cell lines have the ability to grow as xenografts in mice, making pre-clinical in vivo experiments possible. These reliable and versatile models offer valuable tools for the study of ovarian cancer.


Osteosarcoma is a rare bone cancer that occurs primarily in children. The discovery of new treatments for osteosarcoma and other rare cancer types has been severely limited by access to patient samples to study these often-complex diseases. Here we capitalize on naturally-occurring cancers in pet dogs to study the biology of these rare cancers. Using living cells from canine and human patients to test thousands of drugs simultaneously, we identify a unique combination of drugs that disrupts protein degradation and protein trafficking in cancer cells. This drug combination represents a promising new treatment to treat both dogs and people with osteosarcoma.Background: Osteosarcoma is a rare but aggressive bone cancer that occurs primarily in children. Like other rare cancers, treatment advances for osteosarcoma have stagnated, with little improvement in survival for the past several decades. Developing new treatments has been hampered by extensive genomic heterogeneity and limited access to patient samples to study the biology of this complex disease. Methods: To overcome these barriers, we combined the power of comparative oncology with patient-derived models of cancer and high-throughput chemical screens in a cross-species drug discovery pipeline. Results: Coupling in vitro high-throughput drug screens on low-passage and established cell lines with in vivo validation in patient-derived xenografts we identify the proteasome and CRM1 nuclear export pathways as therapeutic sensitivities in osteosarcoma, with dual inhibition of these pathways inducing synergistic cytotoxicity. Conclusions: These collective efforts provide an experimental framework and set of new tools for osteosarcoma and other rare cancers to identify and study new therapeutic vulnerabilities. Osteosarcoma, the most common primary bone cancer, exemplifies the progress that needs to be made in the approach to discovering new therapies. As the third most common cancer of childhood, osteosarcoma is disproportionately lethal, and patients with advanced or metastatic disease have limited treatment options . Due to The story of osteosarcoma is the story of many cancers, especially uncommon ones: Alternative therapeutic approaches are urgently needed, but the path forward is not clear. How can we identify, design, and test new molecular therapies in a disease that is both rare and genetically diverse? Mouse models are a critical tool, but additional translational steps are needed. To complete these additional steps, we are able to look to pet dogs with spontaneous osteosarcoma. While there are approximately 800 cases of human osteosarcoma diagnosed each year, there are at least 30,000 cases of canine osteosarcoma diagnosed each year ,7. TreatWhile these common features of canine and human osteosarcoma are attractive, it is also important to clearly understand the differences in the biology of canine and human cancers. For example, while osteosarcomas in canines and humans are quite similar in terms of their clinical presentation, progression, host factors , and molecular profiles , thePatient-derived models of cancer, including low-passage cell lines , patientHere we combine the advantages of a comparative oncology approach  with patient-derived models to develop and refine a cross-species drug discovery pipeline. The pipeline uses patient samples from either pet dogs or humans to generate patient-matched, low-passage cell lines, and PDXs. Cell lines are used to perform high-throughput chemical screens, and top hits are validated in vitro using matched PDX models A. Using Osteosarcomas and other rare cancers suffer from a lack of access to patient-derived models for study. We reasoned that increased access to a larger patient population with nearly-identical biology could have significant benefits in identifying actionable pathways in osteosarcoma. To this end, we developed a cross-species pipeline that leverages the increased canine patient population and the extensive biological similarities between humans and pet dogs with naturally-occurring sarcomas. The pipeline uses patient tumor tissue from dogs or humans to create patient-derived xenografts (PDXs) that are grown and passaged in immunocompromised mice A. These We applied our pipeline to reveal novel therapeutic vulnerabilities at both the individual patient level and, more importantly, shared across osteosarcomas. To do this, we created matched cell lines from both dog (D418) and human (17-3X) PDXs. Both PDXs were confirmed as osteosarcoma by histopathology A,B. UsinUnlike standard-of-care therapies, analysis of small molecule sensitivities at the individual cell line level revealed heterogeneous responses across the panel of nine cell lines D. Most dGiven the extensive heterogeneity of response, we sought to identify novel compounds with efficacy across the entire panel of cell lines. Interestingly, the two most efficacious inhibitors, with an average of >95% killing for both inhibitors across all nine lines, were compounds that target the proteasome pathway E. Togeth2 = 0.54; p < 0.0001)  C. Also c 0.0001) D. For ex 0.0001) D. In add 0.0001) E. These  0.0001) E. Given  0.0001) F. A tota 0.0001) G,H. Cons 0.0001) I,J and D 0.0001) K,L, pinpOur in vitro small molecule screens pinpointed the proteasome and CRM1 nuclear export pathways as two promising therapeutic vulnerabilities for osteosarcoma. Consistent with this, CRM1 protein is highly expressed  and locaOur cross-species pipeline pinpointed both proteasome and CRM1 pathways as promising single-agent therapies to treat osteosarcoma. However, although CRM1 inhibition was effective across all four of the PDXs tested, the proteasome inhibitor, bortezomib, was only capable of inhibiting growth in one of the two treated PDXs when used as a single agent. Interestingly, these pathways are being targeted with combination therapy for synergistic benefit in several cancer types, including multiple myeloma , colorecIn the present study, we sought to combine the utility of comparative oncology with patient-derived models of cancer and high-throughput small molecule screens to create a cross-species, personalized medicine pipeline. We applied this pipeline to osteosarcoma, a painful bone cancer that occurs predominantly in adolescents and for which almost no treatment progress has been made in nearly four decades. Using our pipeline, we identified therapeutic vulnerabilities for osteosarcoma that are patient-specific, common across patients, and common across species. Among the common therapeutic sensitivities identified were the proteasome and CRM1 nuclear export pathways. Both of these pathways have been explored in depth as potential cancer monotherapies for a range of cancer types ,31, and The proteasome is a multi-subunit complex that degrades misfolded, damaged, or unused proteins. The proteasome regulates the turnover of thousands of proteins in the cell , and proInterestingly, the proteasome and CRM1 export pathways are functionally linked. Proteasome inhibition in colorectal cancer cells induces CRM1-dependent nuclear export of ubiquitinated proteins, and inhibition of CRM1 prevents this export, leading to cell cycle arrest and apoptosis . In addi2 in combination with fludarabine and cytarabine in pediatric patients with relapsed or refractory leukemia [Both of these targets/pathways are currently being explored as treatments for pediatric cancers, with promising tolerability and efficacy. In a phase I tolerability study, the CRM1 inhibitor selinexor was tolerable at doses as high as 55 mg/mleukemia . Likewisleukemia . Unlike leukemia ,44,45. Sleukemia ,47. IndeThe establishment of a cross-species drug discovery pipeline provides a robust platform to identify and validate potential new therapies and offers several advantages. First, it capitalizes on the expanded canine patient population with spontaneous disease, thereby substantially improving access to patient samples for the development of patient-derived models of cancer. This is particularly useful for studying rare cancers. Indeed, we established more than double the number of PDXs from canines than from humans. Second, combining low passage and established cell lines with high-throughput chemical screens enables interrogation of hundreds to thousands of compounds simultaneously, pinpointing both patient-specific and population-level therapeutic vulnerabilities. Third, the use of chemical screens with complete target and pathway annotation allows for identification of single agent- and target/pathways-level drug sensitivities. Fourth, the use of matched cell lines and PDXs from the same patient provides a robust system to validate top candidates. While the in vivo studies are a critical validation step in the pipeline, these studies are costly and time consuming. Future iterations of the pipeline that exploit continued improvement in patient-derived models, such as patient-derived organoids ,48,49, aCanine sarcoma tumor tissue samples were collected from University of Illinois at Urbana Collage of Veterinary Medicine  and Triangle Veterinary Referral Hospital  under Institutional Animal Care and Use committee (IACUC)-approved protocols. Human sarcoma tumor tissue samples were collected under a Duke IRB approved protocol (Pro00002435). All patients provided written informed consent to participate in the study. PDX models of the human and canine sarcoma were generated as described previously  and all Cell lines were generated from human and canine tumor samples. After washing in phosphate buffered saline (PBS), small pieces (<2 mm) of tumor tissue were mechanically homogenized. The homogenized tissue was then suspended in cell growth media and cultured in 12 well plates with DMEM + 10% FBS + 1% Penicillin/Streptomycin. To isolate tumor cells, growing colonies of cells were isolated by trypsinization using O rings and cultured in new 12 well plates. This process was repeated until a colony of cells that resembled pure tumor cells in morphology was established.For the cell lines generated from PDX, mouse cell contamination of the PDX cell lines were detected by PCR using human, canine, and mouse specific primers. Because mouse primers easily cross-react with canine and human gDNA, two different mouse primer sets were used. For human cell lines, human reverse (5′ TCC AGG TTT ATG GAG GGT TC), human forward (5′ TAG ACA TCG TAC TAC ACG ACA CG), mouse reverse (5′ CCC AAA GAA TCA GAA CAG ATG C) and mouse forward (5′ ATT ACA GCC GTA CTG CTC CTA T); for canine cell lines, canine reverse (5′ GTA AAG GCT GCC TGA GGA TAA G), canine forward (5′GGT CCA GGG AAG ATC AGA AAT G), mouse reverse (AGG TGT CAC CAG GAC AAA TG) and mouse forward (CTG CTT CGA GCC ATA GAA CTA A) primer sets were used.All PDX and patient-derived cell lines were authenticated using the Duke University DNA Analysis Facility cell line authentication service by analyzing DNA samples from each individual cell line for polymorphic short tandem repeat markers using the GenePrint 10 kit from Promega .All human  and canine  osteosarcoma cell lines were cultured in DMEM + 10% FBS + 1% Penicillin/Streptomycin. The NIH Approved Oncology set (119 compounds) and Selleck Bioactives collection (2100 compounds) were screened in the Duke Functional Genomics Shared Resource as described previously . Briefly3, mice were randomized (n = 5 mice for each treatment group and n = 5 for the control group) and 1 mg/kg bortezomib, 25 mg/kg alvespimycin and 5 mg/kg verdinexor intraperitoneal injections were initiated twice a week. Tumor volumes were measured three times a week using calipers, and 3.To validate in vitro drug screen results in vivo, 150 μL homogenized PDX tissue-PBS suspensions at 150 mg/mL concentration were injected subcutaneously into the right flanks of the 8 weeks old JAX NOD.CB17-PrkdcSCID-J mice. When the tumor volumes reached 100 mmhttps://hgserver1.amc.nl/cgi-bin/r2/main.cgi) with the “Kaplan Meier by gene expression” tool and the cutoff/modus set to “scan”.JMP from SAS software  was used for the high-throughput drug screen data analysis. Analysis of Means was used to identify the top drug candidates from the 119-compound drug screen and the 2100-compound screen. Tumor volumes were recorded in GraphPad Prism 6 software . Two-way ANOVA analysis was used to compare the tumor volumes among the control and treatment groups. Kaplan Meier curves for CRM1 expression were generated using the R2 genomics software (We demonstrate here the utility of combining patient-derived models of cancer with comparative oncology approaches to discover potential new therapies for osteosarcoma. The increased access to patient samples with biologically-similar disease not only means we can make discoveries in the lab faster, but we can also validate lead candidates in veterinary clinical trials at a fraction of the time and cost. Increasing collaboration between veterinarians, cancer researchers, and human physicians is needed to apply this pipeline and identify new therapies to treat osteosarcoma and other cancers across species.