A total of 8239 proteins were identified by LC–MS/MS, of which 718, 513, and 486 had significant changes, in abundance, in the Ri-1, U2904, and U2932 cell lines, respectively. We observed that changes in B-NHL proteome profiles induced by hypoxia and physioxia were quantitatively similar in each cell line; however, differentially abundant proteins (DAPs) were specific to a certain cell line. A significant downregulation of several ribosome proteins indicated a translational inhibition of new ribosome protein synthesis in hypoxia, what was confirmed in a pathway enrichment analysis. In addition, downregulated proteins highlighted the altered cell cycle, metabolism, and interferon signaling. As expected, the enrichment of upregulated proteins revealed terms related to metabolism, HIF1 signaling, and response to oxidative stress. In accordance to our results, physioxia induced weaker changes in the protein abundance when compared to those induced by hypoxia. Our data provide new evidence for understanding mechanisms by which DLBCL cells respond to a variable oxygen level. Furthermore, this study reveals multiple hypoxia-responsive proteins showing an altered abundance in hypoxic and physioxic DLBCL. It remains to be investigated whether changes in the proteomes of DLBCL under normoxia and physioxia have functional consequences on lymphoma development and progression.Hypoxia is a common feature in most tumors, including hematological malignancies. There is a lack of studies on hypoxia- and physioxia-induced global proteome changes in lymphoma. Here, we sought to explore how the proteome of diffuse large B-cell lymphoma (DLBCL) changes when cells are exposed to acute hypoxic stress (1% of O Lymphatic tissues show a lower concentration of oxygen than blood (0.6–2.8% of oxygen) ,2, whilell death . SurprisMammalian cells have historically grown and divided well in ambient air, thus culturing cells in a more physiologic setting concerning oxygen  has not received approval for many years. Meanwhile, with technological advances, data support that cells benefit from being cultured in physioxia. There is strong evidence that physioxia influences the growth ,7,8, difNon-Hodgkin’s B-cell lymphomas (B-NHLs) are a heterogeneous group of lymphoproliferative malignancies originating from the different stages of B-lymphocyte development and maturation . It was The majority of cancers undergo extensive cellular reprogramming to adapt to environmental challenges, such as hypoxia. Low oxygen pressure in the cancer microenvironment leads to the transcriptional induction of several genes, of which key regulators are the hypoxia-inducible transcriptional factors (HIFs) . The HIF2) and physioxic (5% O2) conditions with large-scale LC–MS/MS, and subsequent bioinformatics data analysis. We identified for the first time hundreds of hypoxia- and physioxia-responsive proteins, many of which have not been previously associated with hypoxia. Clearly, the observed response to hypoxia in DLBCL is highly complex and heterogenous, which was previously highlighted in work based on whole-genome sequencing data [Few previous works have been dedicated to describing the protein profile of B-NHLs, especially DLBCL ,29,30; hing data . At the ing data . Thus, tRi-1, U2904, and U2932 cell lines were obtained from the Leibniz Institute German Collection of Microorganisms and Cell Cultures . The characteristic of the cell lines are presented in 6 of cells were seeded on 75 cm2 flask and incubated for 72 h in Gibco™ RPMI 1640 medium with GlutaMAX  containing 10% heat-inactivated fetal bovine serum  in a humidified atmosphere in standard conditions. The viability of diffuse large B-cell lymphoma (DLBCL) cells was evaluated by Trypan blue dye exclusion assay on the Countess Automated Cell Counter (Thermo Fisher Scientific). Cells were routinely >95% viable.For the experiments, 1 × 106 of cells/mL were subjected to either physioxic  or hypoxic  treatment for 72 h using the multigas incubator . During incubation, the temperature of 37 °C and proper humidity were maintained. As a control, cell lines incubated in normoxia  were used. Four independent biological replicates were conducted for each condition for each cell line. All supplies and media were acclimated for at least 18 h in either hypoxia or physioxia, as previously suggested [Next, 3 × 10uggested .6 of cells were lysed in 150 µL of lysis buffer containing 100 mM of Tris-HCl, pH 8, 50 mM of dithiothreitol (DTT), and 2% of sodium dodecyl sulfate (SDS) for 5 min at 99 °C. Next, lysates were sonicated on the water at room temperature for 2 min and centrifuged at 10,000 RCF for 10 min, followed by transferring supernatant to the new tubes. The total protein concentration was measured in accordance with the tryptophan fluorescence (WF)-based assay [For the sample preparation, 1 × 10ed assay . Sample ed assay  with mined assay . Brieflyed assay  and conc6 and 105, respectively, while the dynamic exclusion was 25 s and 10 ppm. The mass spectrometry data were deposited to the ProteomeXchange Consortium via the PRIDE partner repository [Analysis of peptides was performed using a Q Exactive HF Mass Spectrometer (Thermo-Fisher Scientific). Moreover, 1 µg of total peptides was chromatographed on a 50 cm column with a 75 µm inner diameter packed C18 material . Next, peptide separation was carried out at 300 nL/min for 90 min with the use of two-step acetonitrile (ACN) gradient of 5–60% over the first 75 min and 60–95% for the following 15 min. The temperature of the column oven was 60 °C. The mass spectrometer operated in data-dependent mode. Survey scans were acquired at a resolution of 50,000 at m/z 400 with transient time 256 ms. Most abundant isotope patterns with charge ≥+2 from the survey scan (300–1650 m/z) were selected up to the top 15, with an isolation window of 1.6 m/z and fragmented by HCD with normalized collision energies of 25. The maximum ion injection times for the survey scan and the MS/MS scans were 20 and 60 ms, respectively. The ion target value for MS1 and MS2 scan modes was set to 3 × 10pository  with thep-values, and p < 0.05 was considered statistically significant. The following comparisons were performed: hypoxic cell lines versus corresponding normoxic cell lines, physioxic cell lines versus corresponding normoxic cell lines, and hypoxic cell lines versus corresponding physioxic cell lines to identify the hypoxia- and physioxia-related proteins. The ratio was calculated by (1) dividing the mean TPA values of the hypoxic/physioxic cell lines with the mean TPA values of the corresponding cell lines under normoxia; and (2) dividing the mean TPA values of the hypoxic cell lines with the mean TPA values of the corresponding cell lines under physioxia. The cutoff values of ±1.5-fold for up- and downregulated proteins between samples were established.MaxQuant (MQ) software  was used for spectra searching. A maximum of two missed cleavages was allowed. Carbamidomethylation of cysteines was set as a fixed modification. The minimum peptide length was specified to be seven amino acids. The initial maximal mass tolerance in MS mode was set to 7 ppm, while fragment mass tolerance was set to 20 ppm for HCD data. The maximum false peptide and protein discovery rate was set as 0.01. Specific protein concentrations were calculated by the “Total Protein Approach” (TPA)  using rap < 0.01 were shown. The Venn diagrams were created with the web tool from Bioinformatics and Evolutionary Genomics group [The differentially abundant proteins were analyzed by open-source bioinformatics software platform Cytoscape (version 3.8.2). Functional interaction network analysis was performed using ClueGO and CluePedia (version 2.5.7), STRING, and cytoHubba Cytoscape plugins ,41,42. Pcs group .We were interested in determining how hypoxia (1% of oxygen) and physioxia (5% of oxygen) differentially impacts the proteomes of DLBCL. We first cultured Ri-1, U2904, and U2932 cells under the hypoxic and the physioxic condition for 72 h. Cells maintained under the normoxic conditions served as a control. The experiment was performed in four biological replicates for each cell line in each condition. The findings of our comparative LC–MS/MS proteomic study are summarized in Importantly, principal component analysis (PCA) differentiated the cell lines treated under normoxia, physioxia, and hypoxia, and revealed similarity between Ri-1 and U2904 samples, especially under normoxia and physioxia B. In turp-values p < 0.05 under hypoxia and physioxia in comparisons to 21% of oxygen. Compared with the cells cultured under normoxic conditions, under hypoxia we identified 718, 513, and 486 of differentially abundant proteins (DAPs) in Ri-1, U2904, and U2932 cell lines, respectively. Thus, Ri-1 cell line appeared to be the most hypoxia-responsive with 11.45% of proteins with an altered abundance. U2904 and U2932 cells exhibited a relatively lower response to this treatment—the expression of 8.14% and 7.6% of proteins was significantly affected. Maximum alterations of over 195-fold decrease in protein abundance were found for AIM1 and CDK16 in hypoxic Ri-1 cells. In turn, the most upregulated protein in our dataset was RAB39B in hypoxic U2905 cells with a fold change of 30.06. For more details, see the complete lists of DAPs identified in each cell line  differences in the protein abundance and ell line . Next, well line A,D,G andell line B,E,H.Our data showed that the number of upregulated proteins was similar between the three cell lines, while the number of downregulated proteins was significantly higher in Ri-1 cells. Each cell line under physioxia exhibited weaker changes in the protein abundance when compared to those induced by hypoxia, and the percentage of DAPs was 5.3%, 4.37%, and 4.29% for U2904, Ri-1, and U2932, respectively. A full list of hypoxia, and physioxia-responsive proteins identified in each particular cell line is available as The numbers of DAPs overlapping in hypoxia and physioxia for each cell line separately are presented in the Venn diagram C,F,I. ThThen, we compared DAPs identified in each cell line, after hypoxic and physioxic treatment, and the analysis revealed that the response to increased oxygen is cell line specific. Among the differentially abundant proteins in hypoxia, 518, 382, and 315 proteins were specifically expressed in cell Ri-1, U2932, and U2904 cell lines, respectively B. In turOnly 19 of DAPs were common in the three compared groups, including TRUB2, SEC14L1, CLPTM1, PICALM, ALDH6A1, CCDC86, PPT1, AK4, MMAA, VIMP, HMGCL, GTPBP10, SGSH, EIF4A2, CFDP1, METTL17, KDM3A, DDX56, and PPP1R7. Under physioxia, 280, 227, 213 of DAPs were altered specifically in U2904, U2932, and Ri-1 cells respectively C. 40 of Next, we analyzed the cell lines proteomes under hypoxia versus corresponding cells cultured under physioxia. We identified the 320, 279, and 357 DAPs in Ri-1, U2904, and U2932 cells, respectively A–C. ImpoAs expected, the number of DAPs were significantly lower than the number of DAPs identified in the hypoxia compared to normoxia. The differences in the number of outliers identified in hypoxic cell lines ranged 55.43%, 42.59%, and 30.41% of the decrease in the number of DAPs in Ri-1, U2904, and U2932 cells, respectively. Regarding the fold change values of DAPs, these do not exceed a 10-fold increase in protein abundance in any cell line. CRYZ was the most upregulated protein in our dataset, with a fold change of 9.545 in U2904 cells. In turn, the highest fold decrease of 48.331 was noticed for LRRC15 in U2932 cells.Response to hypoxia, when compare with physioxia, is cell line-specific . 308, 257, and 221 of outliers were specifically expressed in U2932, Ri-1, and U2904 cell lines, respectively. In turn, only 35 DAPs were shared in hypoxia between Ri-1 and U2904 cells, while 26 and 21 DAPs were common for Ri-1 and U2932, and U2904 and U2932, respectively. Two altered proteins, KDM3A and MYO16, were identified in all cell lines under hypoxia. A complete list of hypoxia-responsive proteins identified in each cell line compared to physioxia is available as To find out which biological pathways are regulated preferentially in DLBCL cells by hypoxia and physioxia relative to normoxia, an enrichment analysis was performed with the use of Metascape. The enrichment was done for up- and downregulated proteins separately for each cell line . The top 20 clusters with their representative enriched terms (one per cluster) were presented for each experimental condition . As expeIn turn, pathway mapping shows a decrease in abundance of proteins mainly involved in the ribosome biogenesis, translation, and mitochondrial gene expression A–F. AddiRi-1 cell line with 718 DAPs was the most affected by hypoxia; thus, we decided to study the protein–protein interaction network on this representative. The up- and downregulated proteins were analyzed separately by the use of ClueGO application of Cytoscape (v.3.8.2) in accordance with Gene Ontology–Biological Processes to visualize the protein–protein interaction network A,B. For Six function cluster groups related to the response to hypoxia, amino acid metabolic process , histone demethylase activity, deoxyribonucleotide metabolic process, microtubule polymerization, as well as the oxidative phosphorylation were enriched from the upregulated proteins. Only two clusters related to the cellular response to hypoxia and amino acid metabolic process were functionally connected to each other  and the In turn, the PPIN between downregulated proteins was more complex, and five out of eight main clusters were functionally related. As expected, the proteins with a decreased abundance under hypoxia formed the following clusters: ribosome biogenesis (including 18 pathways), mitochondrial gene expression (13 pathways), cellular metabolic processing (16 pathways), and RNA processing (nine pathways). The other biological processes enriched by ClueGO were those associated with RNA modification, mitotic cell cycle, regulation of transcription, and nucleus organization. The eight pathways were represented by more than 200 proteins, including the cellular nitrogen compound metabolic process with 276 of proteins assigned. Moreover, 51, 92, 46, and 21 of the downregulated proteins were assigned to the pathway of ribosome biogenesis, RNA processing, translation, and mitochondrial gene expression, respectively. In the PPIN of downregulated DAPs, several proteins overlapped between the distinct pathways, as visualized in Since we were interested in pathways predominantly affected by hypoxia, we analyzed the translation pathway (R-HSA-72766) in hypoxic Ri-1 cells in more detail. DAPs belonging to the above pathway in accordance with the Metascape enrichment analysis were uploaded to STRING to create the PPIN, Finally, we used the cytoHubba plugin of Cytoscape to rank proteins in a network and find the hub proteins affected the most by hypoxia and physioxia. First, a STRING analysis was performed for DAPs identified in each cell line, and protein–protein interaction relationship network tables were downloaded and visualized using Cytoscape. Next, the hub proteins were identified in accordance with the degree algorithm of cytoHubba. The selected “hypoxic” hub proteins differed between cell lines, but some of them were overlapping including DDX56, MRTO4, RPF2, RSL24D1, and SDAD1 for Ri-1 and U2904 cells, or PWP1, shared between U2904 and U2932 cells. Interestingly, the vast majority of hub proteins are those downregulated in hypoxia. The PPIN between the top 20 hypoxia-responsive proteins are presented for each cell line in Furthermore, most of the Ri-1 hub proteins are related to ribosome biogenesis , and rRNA processing . CCNB1 and PLK1 were annotated to the cell cycle. U2904 hub proteins are involved in ribosome biogenesis , rRNA processing  and nucleotide binding . In turn, 13 of the U2932 hub proteins were involved in the cell cycle (mainly mitosis), e.g., CDCA5, CDC23, CDC45). Importantly, CHEK1 and RRM2 hubs were annotated to the p53 signaling pathway. For hypoxic Ri-1 and U2904 cells, most hub proteins are those related to ribosome biogenesis and rRNA processing. In turn, hub proteins selected among all DAPs identified in U2932 are mostly related to the cell cycle.Beyond the hypoxia-related hub proteins listed above, some targets identified in physioxia are worth highlighting. The Proteomic studies of hypoxia have been carried out extensively in recent years; however, the global effect of hypoxia-driven changes on lymphoma protein profiles remains largely undocumented. In this work, we present a report on global protein profiling in DLBCL cell lines exposed to long-term hypoxia (1%) and physioxia (5%). Since there are a lack of data explaining the role of hypoxia in lymphoma, we aimed to describe the complex molecular response of lymphoma cells to low oxygen concentrations. To the best of our knowledge, this study was the first to assess and compare DLBCL proteome changes under hypoxia, and physioxia. Recently, we better understood the need to study the realistic pattern of temporally variable oxygen exposure to the cells and tissues. In our work, the cells were incubated under constant hypoxia or physioxia for 72 h, while in cancer, the fluctuation in oxygen concentration occurred at irregular intervals with sporadic reoxygenation periods because of dysfunctional tumor vascularity and heterogenic blood supply . In addiLarge-scale LC–MS/MS proteomics was applied to comprehensively characterize the hypoxia- and physioxia-responsive proteins of three DLBCL cell lines: Ri-1, U2932, and U2904, when compared to normoxia. Additionally, we showed the differences in the obtained results when hypoxia was analyzed versus physioxia. In accordance with our results, the long-term increase of oxygen concentration affected the protein profiles in each cell line; however, the response to this treatment was cell line specific. Ri-1 and U2904 cell lines appeared to be the most hypoxia- and physioxia-responsive, respectively. Hypoxia significantly changed the abundance of 718 proteins in Ri-1 cells, while physioxia affected the expression of 280 proteins in U2932 cells compared to normoxia. The vast majority of DAPs were identified within the particular cells and only 19 and 2 of the DAPs were shared between cell lines exposed to hypoxia and physioxia, respectively. Most of these proteins have been recently recognized for their role in carcinogenesis and targeted cancer therapy, including, e.g., EIF4A2 , ALDH6A1Usually, in hypoxia and physioxia driven studies, cells are cultured at specific oxygen concentrations relative to normoxia. Since hypoxia is much closer to the physiologic range than normoxia, we analyzed the changes in the hypoxic proteomes of DLBCL cell lines when analyzed in comparison to physioxia. As expected, the lower quantitative changes in the proteomes of DLBCL cell lines were observed with a maximum decrease of 55% in the number of DAPs identified in Ri-1 cells. Notably, 47.81%, 31.18%, and 30.81% of DAPs identified in hypoxic Ri-1, U2904, and U2932 cells, respectively, were shared with DAPs identified in corresponding cell lines, when hypoxia compared to normoxia. Similar to previously performed comparisons, we observed that the response to hypoxic treatment is cell line-specific, and the majority of DAPs were found within the particular cells. Only two DAPs were shared in tree cell lines under hypoxia vs. physioxia: KDM3A, and MYO16, of which KDM3A was found to be the target of HIF-1α .Heterogeneity of cancers within response to hypoxia, which we reported here, was frequently underlined. Recently, Bhandari et al., based on whole genome sequencing data, quantified hypoxia in 1188 tumors spanning 27 cancer types . The autThe enrichment analysis was performed to annotate the pathways and biological function to DAPs, and subsequently to determine which of them are impaired under hypoxia and physioxia. Knowledge about the perturbed pathways and function can help to understand how DLBCL cells adapt to oxygen stress, and to potentially develop new treatment options. Translation and translational regulation are also pivotal for inducing adaptive stress responses of cancer cells to environmental hypoxia by regulation of gene expression . Cancer In our work, translational repression was functionally related to downregulation of mitochondrial function, as previously reported in DLBCL by Bhalla et al. in a transcriptomic study . MitochoOur results show that prolonged hypoxia significantly inhibited ribosome biogenesis in DLBCL cells. Ribosome, responsible for the translation of information contained in mRNA into the protein, is one of the most conservative structures throughout the evolution. However, its synthesis is one of the most complex biological processes . RibosomNearly 20 years ago, Koshiji et al. demonstrated that HIF-1α—rather than other hypoxia-associated genes—that induces the cell cycle arrest , which wHypoxia inducible factors (HIFs) perform master roles in the cellular response to hypoxia. HIFs regulate more than 100 genes in response to a decrease in oxygen . Under nIt is well established that hypoxia-inducible factors (HIFs) mediate metabolic reprogramming in response to hypoxia ,86. RebuThe oxygenation of tissues in vivo is more hypoxic compared to ambient air; however, knowledge of cancer cells responding to a physiological oxygen microenvironment remains a largely overlooked part of cancerogenesis. Here, we made an effort to present the global changes in B-cell proteomes under physioxia. Our data showed that the response of DLBCL cells to physioxia was more cell line specific when compared to hypoxia. The response to the oxidative stress pathway was only one pathway commonly upregulated in each cell line under physioxia.Interestingly, in our dataset, the enrichment analysis revealed an increase of SUMOylation of transcription factors pathway in Ri-1 cells. The upregulation of small ubiquitin-like modifier (SUMO) is a common posttranslational modification (PTM) in several tumors and is related to tumor development. Accordingly, a high level of SUMOylation was found to be required for cancer cells to survive external stresses, including oxygen deprivation . InteresFinally, in search for proteins of the core response to hypoxia and physioxia, a cytoHubba analysis was performed. Our results showed that hypoxic hub proteins were mostly downregulated. The notable hub proteins overlapping in Ri-1 and U2904 cells entirely included proteins involved in ribosome biogenesis . Concurrently, most of the hub proteins identified in Ri-1 and U2904 cells are related to ribosome biogenesis and rRNA processing, suggesting similarity of these two DLBCL cell lines in response to hypoxia. In turn, 13 of the U2932 hub proteins were involved in the cell cycle (mainly mitosis), e.g., CDCA5, CDC23, and CDC45. Importantly, CHEK1 and RRM2 hubs were annotated to the p53 signaling pathway. The selection of hub proteins, which are different for each cell line, additionally confirmed that the response to hypoxia and physioxia is cell line specific; however, the same molecular pathways are differentially regulated in the dataset, Ri-1, U2904, and U2932. DLBCLs are biologically highly heterogeneous tumors; thus, the reason behind the difference in hypoxic and physioxic proteomes of Ri-1, U2932, and U2904 cells, may be due to the metabolic differences between the three cell lines. Similarly, previous gene expression profiling studies revealed differences in several DLBCL cell lines, in their dependencies on metabolic pathways . NotablyTo summarize, this report is the first to investigate the influence of decreased oxygen concentration on the global proteomes of DLBCLB-NHL cell lines. Our proteomic data allowed us to define DLBCL phenotypes under hypoxia and physioxia, showing that hypoxia-related response in lymphoproliferative malignancies is complex and highly heterogeneous. However, we were able to indicate several pathways and notable proteins commonly affected by hypoxia in DLBCL. It remains to be investigated whether changes in the proteomes of DLBCL under normoxia and physioxia have functional consequences on lymphoma development and progression, with potential importance for the design of novel treatments. The functional significance of the identified hypoxia-responsive protein targets and pathways must be confirmed in the subsequent biochemical assays. Concurrently we established that the magnitude of hypoxia-driven global changes in the lymphoma proteomes depends on the oxygen concentration used for comparisons; thus, the selection of proper experimental conditions when studying hypoxia should be considered. Finally, given the importance and benefits of maintaining physiological oxygen levels, there is a need to establish more relevant oxygen concentration in vitro studies, especially in potentially life-saving therapies.


Eribulin has shown antitumour activity in some soft tissue sarcomas (STSs), but it has only been approved for advanced liposarcoma (LPS).In this study, we evaluated the effect of eribulin on proliferation, migration and invasion capabilities in LPS, leiomyosarcoma (LMS) and fibrosarcoma (FS) models, using both monolayer (2D) and three-dimensional (3D) spheroid cell cultures. Additionally, we explored combinations of eribulin with other drugs commonly used in the treatment of STS with the aim of increasing its antitumour activity.Eribulin showed activity inhibiting proliferation, 2D and 3D migration and invasion in most of the cell line models. Furthermore, we provide data that suggest, for the first time, a synergistic effect with ifosfamide in all models, and with pazopanib in LMS as well as in myxoid and pleomorphic LPS.Our results support the effect of eribulin on LPS, LMS and FS cell line models. The combination of eribulin with ifosfamide or pazopanib has shown in vitro synergy, which warrants further clinical research.The online version contains supplementary material available at 10.1186/s12935-021-02337-5. MDM2 and CDK4 genes [FUS and DDIT3 genes, and PLPS has no characteristic molecular alteration [Soft tissue sarcomas (STSs) represent approximately 1% of all adult cancers. This heterogeneous group of tumours is currently subclassified by the World Health Organization (WHO) into approximately 80 histological subtypes . WDLPS aK4 genes . MLPS isteration –7. FinalTreatment of advanced STS is mainly based on chemotherapy and other systemic treatments, although surgery and radiotherapy can also be used with palliative intention in some patients. Doxorubicin is usually administered as first-line treatment. Other drugs, such as ifosfamide, trabectedin, pazopanib, eribulin, gemcitabine (in combination) and dacarbazine are options for subsequent treatment lines . AdditioEribulin is an antitumour agent acting mainly as a microtubule dynamics inhibitor. Other mechanisms of action have also been proposed, such as vascular remodelling, reversion of the epithelial to mesenchymal transition (EMT) and suppression of migration and invasion –14. EribThe rarity of sarcomas makes it difficult to design clinical trials or make clinical decisions regarding specific subtypes. In this context, cellular models are a valuable approach, particularly for drug testing studies, which can provide useful preclinical data to help with the design of further clinical research. Most current studies are performed on monolayer two-dimensional (2D) cell models, which are still the most commonly used due to their high standardisation and cost effectiveness. However, they have a number of limitations, particularly important for drug studies. The main disadvantage is that cells are cultured on flat dishes, where there is no spatial complexity, and they are all equally exposed to compounds, which is not representative of a real cancer cell environment . This scIn this study, we explored the activity of eribulin in a STS cell line panel: LPS and LMS, which were the target of the phase III clinical trial, and FS, a rare sarcoma, in which eribulin was previously tested in vitro and in xenografts . We inveLIPODL221 (MLPS), LPS224 (DDLPS) and LPS246 (DDLPS) cell lines were obtained from the MD Anderson biobank core facility. SW872 (PLPS), SK-UT-1 (LMS), HT1080 (FS) and 93T449 (WDLPS) were kindly provided by Dr.Carnero from the Biomedicine Institute . The cell lines were tested routinely for mycoplasma, and authenticated by genetic profiling using polymorphic short tandem repeat loci from the Geneprint 10 kit .2. Cells were regularly tested for mycoplasma infection. All media and supplements were purchased from Sigma-Aldrich (USA).All culture media were supplemented with a concentration of 10% foetal bovine serum (v/v), 1% L-glutamine (v/v) and antibiotics (100 units/ml of penicillin and 100 µg/ml of streptomycin), all from Merck (Germany). SK-UT-1 (LMS), SW872 (PLPS), LIPODL221 (MLPS), LPS224 (DDLPS) and LPS246 (DDLPS) were cultured in DMEM, SW872 (PLPS) supplemented with 0.01% sodium pyruvate (PyrNa); and SK-UT-1 (LMS) supplemented with 0.01% non-essential amino acids (NEAA) + 0.001% 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) + 0.001% pyruvate. HT1080 (FS) and 93T449 (WDLPS) were grown in F-10 medium. Cultures were maintained at 37 ºC in a humid atmosphere and 5% COEribulin was kindly provided by Eisai Inc. (USA). Doxorubicin, ifosfamide, gemcitabine, trabectedin, pazopanib and palbociclib were obtained from Selleckchem (UK).The monolayer experiment cells were seeded in 96-well plates (MW96)  at a variable density, previously established for each cell line  round bottom plates The optimal spheroid size relies on the specific assay requirements, but is usually within a 200–500 µm diameter range We established a pre-set density for each cell line, to obtain a spheroid diameter around 300 µm at day 4, as previously described in ULA plates , 22. GroThe drug screening experiments were performed in MW96 plates. The design of the plate was as follows: all border wells contained phosphate buffered saline (PBS), to avoid evaporation issues. The rest of the plate contained the pre-set number of cells for each cell line and condition. With this design, 9 columns with 6 replicates each will be exposed to increasing concentrations of the explored drug, and one column will be used as control. For monolayer cultures, cells were exposed 24 h after seeding to 1:2 dilutions of drug concentrations  using non-linear regression with GraphPad Prism 7 software .We calculated 2D and 3D growth inhibitory concentration by 50% , and Matrigel coated inserts for invasion experiments . The insert was fixed and stained 24 h after seeding using the Diff-Quick method . Two different fields were photographed at 20 × magnification for the subsequent cell count using the ImageJ program .For the study of migration and invasion capacity in 3D, 4 day spheroids were placed on a previously solidified Matrigel layer for migration, or embedded in Matrigel for invasion assays.. The images were taken and quantified after 3 to 7 days using ImageJ (NIH).Two experiments were performed and the measures obtained in two fields are represented as a ratio with the non-treated control cells.50 value, 1.24 nM) over a period of three months.Eribulin-resistant cell line was established from 93T449 LPS cells by continuous exposure to eribulin  following manufacturer's instructions. Dots detection was performed with the GenePix 4100A Microarray scanner and quantified by GenePix Pro 7 Software System . The raw numerical intensity data were extracted and subjected to background subtraction before normalising the signal for each cytokine against the positive control signals in each array. Duplicate discordant results were eliminated for the analysis. A fold change over 2 times and pvalues < 0.05 were used as cutoff.http://bioconductor.org/packages/release/bioc/html/synergyfinder.html) [Drug combination studies were performed in pairs, combining eribulin with the other drugs. Treatment was established for 72 h, with a maximum concentration up to 10 mM  , 24.50 values of compounds [We used 4 available algorithms to test the synergy between drugs: the Bliss model (BLISS), Highest Single Agent (HSA), Loewe additivity model (LOEWE) and Zero Interaction Potency (ZIP) . The effompounds . A top d50 calculation was performed by non-linear interpolation using GraphPad Prism 7 software (GraphPad Software).The averages and standard deviations of the data, as well as the Student T tests, were performed using Microsoft Office Excel 2007 . As previously indicated, GIThe morphology of the cells is shown in Fig. 50 when grown in 3D conditions. Values in 2D were in the nanomolar range for all cell lines, and also for 4 of them in 3D conditions. The other 3 lines did not reach their GI50 values with a 100 nM exposure . HT1080 (FS) and SW872 (PLPS) keep similar values of sensitivity in both conditions, while the rest of the cells showed increases in their GIAdditionally, eribulin promoted morphological changes in all lines except LPS246 (DDLPS), changing their basal mesenchymal morphology to a more rounded one . Pazopanib and palbociclib presented a GICell cycle and apoptosis were also explored by DNA content quantification of cells. A general increase in the percentage of cells in sub G0 and S-phase was observed in all cell lines, indicating that eribulin treatment led to apoptosis and S-phase arrest. Regarding checkpoints, a decreased G0/G1-phase was observed, and G2/M-phase variations seemed to be dependent on the cell line .However, decreased migration and invasion was less visible in LPS cell lines, and not statistically significant. Some cells did not migrate or invade in basal conditions , whereas others , showed a high increase in their GIWe next sought to determine potential action modes for eribulin. To do so, we used 93T449 LMS cell line to generate an eribulin-resistant line through continuous drug exposure. An exploratory analysis of deregulated proteins included and enriched pathways, pointed candidate pathways to explore, as is protein metabolism  plus palbociclib, as possible agents for LPS.http://synergyfinder.org). First, the combination of eribulin and pazopanib was synergistic for SK-UT-1 (LMS), SW872 (PLPS) and LIPODL221 (MLPS) cell lines  with SynergyFinder  STS subtypes together. These entities are different from a histological and molecular point of view, and they do not necessarily share the same drug sensitivity .Cellular models are a useful tool with which to perform drug testing, especially in rare entities such as STS, given that they can serve as the basis for new clinical trial designs. Traditionally, the most commonly performed experiments have been based on cell proliferation or apoptosis in 2D conditions. Currently, we can analyse the effect of drug exposure on other aspects that are important for cancer progression, such as migration and invasion. Moreover, we already know that the classical monolayer culture, although it has a low cost and is easy to handle, does not reflect the architectural situation in the tumour. Spheroids are tridimensional structures that mimic the spatial architecture of tumour cells, and they more accurately represent the pattern of drug diffusion as it actually occurs in the tumour from the surrounding vasculature . AlthougEribulin has been previously studied in sarcomas in 2D culture models. There are positive data with preclinical models of Ewing's sarcoma, rhabdomyosarcomas and osteosarcoma cell lines . RegardiA modification of cell morphology was observed in the majority of cell lines, which is consistent with one of the mechanisms of action of eribulin. This mechanism involves the suppression of microtubule dynamics and EMT, which can prompt changes in cell morphology . These c50 values as the monolayer culture, the LPS and LMS models showed an increase in their GI50 values, primarily to nanomolar values, and even to a micromolar range in some cases. This increase could be due to the spheres’ architecture, given that HT-1080 had a less compact structure. A loose aggregate is more similar to a 2D culture, in which all cells are equally exposed to oxygen, nutrients and drugs. The rest of the cell lines, which had a more compact structure, were hindered by a diffusion gradient through the inner layers. They probably required a subsequent increase in the GI50 values, given that not all the cells were equally exposed.There have been few studies of the effect of eribulin on 3D STS cell models. A previous report with a 3D LM8 osteosarcoma model suggested an impact on proliferation . Eribuli50 values that would better represent the situation in the tumour [Additionally, in compact spheroids, only the outer ring proliferates, while the rest of the cells are quiescent, and some drugs need proliferation of cells for their activity. These findings could favour an increase in GIe tumour , 39. Dife tumour .Eribulin has been reported to affect migration and invasion of breast cancer cell lines in 2D conditions . It has LPS is one sarcoma subtype were eribulin has been approved and the understanding of resistance mechanisms is increasingly important. Some mechanisms has been already implicated, as the activation of PI3K . We haveOnce the effects of eribulin were observed, studying combinations of eribulin with other drugs commonly used in STS became an attractive option. Few combinations have been previously explored in STS cell line models , 43. RegSynergy indicates that 2 drugs combined exert a greater effect than that expected from the 2 drugs individually. In vitro studies are the basis for rational drug combination experiments, but they are not easy to evaluate and translate into clinical use . Many meWe found 2 interesting combinations. First, eribulin and pazopanib appeared to be synergistic for LMS, MLPS and PLPS, but not for other LPSs. Pazopanib is a potent and selective multitargeted receptor tyrosine kinase inhibitor that showed efficacy in a phase III trial in STS, and it is currently approved for the treatment of advanced STS (except LPS) pretreated with anthracyclines , 48. AddWe have proved eribulin’s effect on proliferation, migration and invasion in STS cell line models. The preclinical results we have obtained are sufficiently robust to consolidate its antitumour effect in this context. Additionally, the combination of eribulin with pazopanib or ifosfamide has a synergistic effect in STS, which warrants further clinical research.Additional file 1:Table S1. Detailed experimental conditions for employed cell lines, covering seeding densities and drug dose ranges for 2- and 3D conditions.Additional file 2: Figure S1. Eribulin dose response curves for cell lines studied. A representative experiment is shown for A) 2D and B) 3D culture conditions. Red line represents the value for GI50 values. C) GI50 Scatter plots. Cells haves been split in two plots according to their values for a better representation. In 3D experiments, only 4 cell lines are presented since the other 3 are over the tested drug range, and considered as resistant.A representative experiment is shown for A) 2D and B) 3D culture conditions. Red line represents the value for GI50 values. C) GI50 Scatter plots. Cells have been split in two plots according to their values for a better representation. In 3D experiments, only 4 cell lines are presented since the other 3 are over the tested drug range, and considered as resistant.Additional file 3: Figure S2. Eribulin effect on morphology. Phenotypical changes of cell lines exposed to eribulin for 72h.Additional file 4: Table S2. 2D GI50 values for studied drugs. The concentration value is displayed as mean ± standard deviation.Additional file 5: Figure S3. Effect of eribulin in Cell cycle. Bar plots show Cell cycle distribution for subG0, G0/G1, S and G2/M phases comparison in untreated and eribulin exposed cells. *p<0.05, **p<0.005.Additional file 6: Figure S4. Pathway enrichment analysis for disregulated processes between parental and resistant 93T449. NES: Normalized enrichment score; pval: p value.Additional file 7: Figure S5. Tidycomb Analysis. Eribulin combination with A. Ifosfamide, B. Pazopanib and C. Doxorubicin, on LMS and LPS cell lines. The area highlighted in red corresponds to the score values considered as indicators of synergy.


Acute myeloid leukemia (AML) is an aggressive and heterogeneous clonal hematologic malignancy for which novel therapeutic targets and strategies are required. Emerging evidence suggests that WTIP is a candidate tumor suppressor. However, the molecular mechanisms of WTIP in leukemogenesis have not been explored. Here, we report that WTIP expression is significantly reduced both in AML cell lines and clinical specimens compared with normal controls, and low levels of WTIP correlate with decreased overall survival in AML patients. Overexpression of WTIP inhibits cell proliferation and induces apoptosis both in vitro and in vivo. Mechanistic studies reveal that the apoptotic function of WTIP is mediated by upregulation and nuclear translocation of FOXO3a, a member of Forkhead box O (FOXO) transcription factors involved in tumor suppression. We further demonstrate that WTIP interacts with FOXO3a and transcriptionally activates FOXO3a. Upon transcriptional activation of FOXO3a, its downstream target PUMA is increased, leading to activation of the intrinsic apoptotic pathway. Collectively, our results suggest that WTIP is a tumor suppressor and a potential target for therapeutic intervention in AML. Acute myeloid leukemia (AML) is a highly heterogeneous clonal hematologic disease characterized by genetic and epigenetic alterations leading to the proliferation and expansion of abnormal myeloid stem/precursor cells in blood and bone marrow . AML is FOXO3a gene regulation remain elusive.Forkhead box O (FOXO) proteins, including FOXO1, FOXO3a, FOXO4, and FOXO6, are a group of transcriptional factors that can modulate the expression of genes involved in apoptosis, cell cycle arrest, DNA repair, oxidative stress, and other cellular functions –9. IncreWTIP is a candidate gene that maps to chromosome 19q13.11 [UBA2-WTIP in AML and found that it abrogates WTIP-mediated P-body formation [The 19q13.11 microdeletion syndrome is a clinically recognizable condition characterized by growth deficiency, microcephaly, ectodermal anomalies, and intellectual disability, suggesting missing of potentially key genes in this region –17. The 19q13.11 , 17. As 19q13.11 . In cerv19q13.11 . In our ormation . While oormation . These fIn this study, we revealed that WTIP expression is downregulated and significantly associated with poor prognosis in AML patients. Overexpression of WTIP inhibited cell proliferation and colony formation in AML cells. We further showed that WTIP overexpression was effective to induce apoptosis by upregulating FOXO3a and promoting its nuclear localization. Furthermore, we found that WTIP interacts with FOXO3a and transcriptionally activates FOXO3a mRNA expression. Upon transcriptional activation of FOXO3a, its downstream target p53 upregulated modulator of apoptosis (PUMA) is increased, leading to activation of the intrinsic apoptotic pathway. These results suggest that WTIP is a tumor suppressor and a potential target for therapeutic intervention in AML.Bone marrow samples were obtained from primary AML patients and healthy donors with informed consent in accordance with the Declaration of Helsinki. Studies were approved by the ethics committee of Zhejiang Provincial People’s Hospital, People’s Hospital of Hangzhou Medical College. KG1a, Kasumi-1, HL-60, MOLM-13, THP-1, U937 cells (human AML cell lines), HEK293 and HEK293T (human embryonic kidney cell line) were obtained from American Type Culture Collection . KG1a, Kasumi-1, HL-60, THP-1, and U937 cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum . MOLM-13 cells were cultured in an IMDM medium with 10% FBS. HEK293 and HEK293T cells were cultured in a DMEM medium with 10% FBS.Western blot analysis was performed as previously described . AntibodCells were plated on a 6-well plate and treated with doxycycline for 48 h. For flow-cytometry-based analysis, cells were harvested and incubated for 5 min with Annexin V-FITC/PI . The samples were analyzed using Beckman Coulter Navios Flow Cytometer .TM One Step Cloning Kit  as previously described [TM One Step Cloning Kit as previously described [The WTIP coding sequence with a 3×FLAG-tagged sequence was amplified from HEK293 cells, and then cloned into the pLVX-tre3G vector  or pCDH-MSCVMCS-EF1α-GFP+Puro  using Hieff Cloneescribed . The FOXescribed . The seqCells were fixed with 4% paraformaldehyde for 30 min, permeabilized with 0.1% Triton X-100 for 10 min and blocked with 5% BSA for 1 h, labeled with anti-WTIP and anti-FOXO3a antibodies overnight at 4 °C. After washing, cells were labeled with Alexa Fluor 488 and Alexa Fluor 594  for 1 h at room temperature. Cell nuclei were stained with DAPI . Samples were analyzed using Zeiss Confocal Laser Scanning Microscope 710 (Carl Zeiss MicroImaging GmbH).® Premix Ex Taq™ (TaKaRa). The sequences of primers for WTIP were forward, GGCATGTTACCACTGTGAGGACTG; and reverse, CGCAGGTGGCAACGACGAC. Primers for FOXO3a were forward, TGGCAAGCACAGAGTTGGATGAAG; and reverse, CATATCAGTCAGCCGTGGCAGTTC. Primers for p53 were forward, ACCGGCGCACAGAGGAAGAG; and reverse, GCCTCATTCAGCTCTCGGAACATC. Primers for PUMA were forward, CGGAGCAGCACCTGGAGTCG; and reverse, TTGAGGTCGTCCGCCATCCG. GAPDH was used as an internal control. Relative gene expression was calculated using the ΔΔCt-method.Total RNA was isolated by TRIzol Reagent  according to the manufacturer’s instructions. cDNA was synthesized by using PrimeScript™ RT reagent Kit . Real-time PCR was performed by using TB GreenCells were plated on a 6-well plate and treated with doxycycline for 48 h. Then cell lysates were prepared with RIPA lysis buffer . Primary antibodies or normal IgG were added to the cell lysates and incubated overnight at 4°C. The protein A magnetic beads  were added to the cell lysates incubated for 2 h at 4 °C. Beads were washed three times with PBST, boiled in Laemmli buffer at 95 °C for 5 min. The supernatant was subjected to western blotting.® Reporter System according to the manufacturer’s instructions.The promoter regions of human FOXO3a were amplified from human genomic DNA by PCR. Primers for FOXO3a promoter were forward, CTGCTCGTGGAAGGGAGGAG; and reverse, GGGGCAGCCCCCTCC. The reporters described here were derived from the pGL3-promoter luciferase vector . FOXO3a promoter was cloned into the pGL3-Basic vector for promoter activity analysis. HEK293T cells were grown in a 24-well plate were co-transfected with 200 ng of FOXO3a promoter vector, 20 ng of pSV-β-Galactosidase vector as an internal control, and 200 ng of WTIP full-length expression vector or control vector. The relative luciferase activity was analyzed 48 h after transfection by using the Promega E1960 Dual-LuciferaseSP siRNA/miRNA Transfection Reagent  following the recommended procedures. siRNAs for FOXO3a were designed .siRNA for FOXO3a was purchased from Ribobio . siRNA was transfected using RFect6 cells) into B-NSG mice . B-NSG mice were treated daily with doxycycline (2 μg/ml) by oral gavage, and tumor volumes were measured every 5 days for 20 days. Tumors were harvested on day 20 after treatment and immediately fixed in 4% paraformaldehyde. Tumor volume (V) was calculated by using the formula (L × S × S) × 0.5, where L and S were the long and short dimensions, respectively [KG1a and MOLM-13 cells transfected with WTIP or control vectors were injected subcutaneously . Statistical significance was calculated by Student’s PROGgeneV2 is a web tool that can be used to study prognostic implications of genes in various cancers . We initTo further investigate the functional role of WTIP in AML, we developed a doxycycline-inducible expression system for WTIP in KG1a and MOLM-13 cells. As determined by real-time PCR and western blot analysis, in the presence of doxycycline, robust induction of WTIP at both protein and mRNA levels was observed in KG1a and MOLM-13 cells transfected with WTIP vector compared with control vector cells Fig. . MTT andIn order to study the molecular mechanisms by which overexpression of WTIP inhibited cell proliferation, we investigated whether apoptosis is induced. Flow cytometry results showed that Annexin V-positive and PI-positive cell population was significantly higher in WTIP-overexpressing KG1a and MOLM-13 cells compared with control vector cells Fig. . WesternThe PUMA, a member of BH3-only Bcl-2 family proapoptotic protein, was identified as a critical mediator of AML cell apoptosis induced by anti-leukemic agents –28. It wPUMA was initially identified as a p53-inducible gene and activated in response to genotoxic stress, consequently mediating p53-dependent apoptosis , 31. In We then sought to determine whether FOXO3a is involved in PUMA-mediated apoptosis in AML cells. In the presence of doxycycline, we observed a robust induction of FOXO3a at both the protein and mRNA levels in KG1a and MOLM-13 cells transfected with WTIP vector Fig. . Next, KTo further explore the involvement of FOXO3a in WTIP-mediated upregulation of PUMA, KG1a and MOLM-13 cells were infected with two different siRNAs (siFOXO3a-1 and siFOXO3a-2) to knock down FOXO3a expression. KG1a and MOLM-13 cells transfected with either siFOXO3a-1 or siFOXO3a-2 showed effective knockdown of FOXO3a at the mRNA level compared with cells transfected with negative control siRNA (siNC) , and analyzed luciferase activity in the presence of WTIP or control vector in HEK293T cells. Co-transfection of FOXO3a-Luc reporter vector with WTIP vector increased luciferase activity in HEK293T cells compared with control vector cells (Fig. FOXO3a is transcriptionally regulated by WTIP.To determine whether WTIP can transcriptionally regulate lls Fig. . These r32, a key regulatory site for nuclear translocation [As FOXO3a exerts its transcriptional activity in the nucleus, we performed a confocal immunofluorescence assay to investigate the subcellular distribution of FOXO3a in KG1a and MOLM-13 cells transfected with WTIP vector. In the absence of doxycycline, low levels of FOXO3a were observed and it is mainly localized in the cytoplasm Fig. . In the location . The resTo explore the tumor-suppressive effects of WTIP in vivo, KG1a and MOLM-13 cells transfected with WTIP or control vectors were injected subcutaneously into B-NSG mice. The tumor volume in B-NSG mice subcutaneously injected with WTIP-overexpressing KG1a or MOLM-13 cells were significantly decreased compared with mice injected with control vector cells Fig. , suggestOver the past few decades, our understanding of the molecular pathogenesis of AML has been greatly advanced by genomics studies. Genetic abnormalities have been known to play an essential role in the pathogenesis of AML , 34. DelFOXO proteins have been shown to act as tumor suppressors in several cancers –9. PreviPUMA is of particular interest in the regulation of AML cell apoptosis , 27. In UBA2-WTIP in AML and found that it abrogates WTIP-mediated P-body formation [UBA2 gene mutation is associated with congenital dysplasia [We recently reported a novel fusion gene named ormation . As WTIPormation . Previouysplasia –42. Receysplasia –47. TherFOXO3a is a target gene of WTIP, and the apoptotic function of WTIP is mediated by upregulation and nuclear translocation of FOXO3a. Upon transcriptional activation of FOXO3a, its downstream target PUMA is increased, leading to activation of the intrinsic apoptotic pathway. Our results demonstrate that WTIP plays an important role in the regulation of cell proliferation and induction of apoptosis in AML. Restoring WTIP activity represents a plausible new therapeutic strategy in the treatment of AML.In conclusion, to our knowledge, this is the first study to elucidate the critical role of WTIP in AML. Our results demonstrate that WTIP expression is significantly reduced in AML, and low levels of WTIP are associated with decreased overall survival in AML patients. Overexpression of WTIP inhibits cell proliferation and colony formation by inducing apoptosis in AML cells. We further demonstrate that Reproducibility checklistSupplementary information


Animal cell-based expression platforms enable the production of complex biomolecules such as recombinant proteins and viral vectors. Although most biotherapeutics are produced in animal cell lines, production in human cell lines is expanding. One important advantage of using human cell lines is the increased potential that the resulting biotherapeutics would carry more “human-like” post-translational modifications. Among the human cell lines, HEK293 is widely utilized due to its high transfectivity, rapid growth rate, and ability to grow in a serum-free, suspension culture. In this review, we discuss the use of HEK293 cells and its subtypes in the production of biotherapeutics. We also compare their usage against other commonly used host cell lines in each category of biotherapeutics and summarise the factors influencing the choice of host cell lines used. Production of complex biopharmaceutical products rely heavily on mammalian cell lines, with most therapeutic biopharmaceuticals produced in the Chinese hamster ovary (CHO) cells . The useThe HEK293 cell line was established by transforming human embryonic kidney cells with sheared adenovirus type 5 DNA . Since tOther notable HEK293 derivatives commonly used in recombinant protein production include HEK293-E and HEK293-6E. HEK293-E was established by the expression of Epstein-Barr nuclear antigen 1 (EBNA-1), which allows for episomal replication of plasmids with oriP. Similarly, the HEK293-6E cell line was established by the expression of a truncated EBNA-1, lacking Gly-Gly-Ala domain. HEK293-6E showed improved transient gene expression and cell growth compared to HEK293-E .Eukaryotic expression systems are used to produce complex recombinant protein with complex PTMs for proper protein function. The use of the HEK293 host cell eliminates issues of potential immunogenicity due to the presence of non-human PTMs . Its easBecause of its ease of transfection, HEK293 is widely used for transient gene expression (TGE). Recombinant proteins can be produced quickly by transfecting HEK293 with readily available reagents such as calcium phosphate or polyethylenimine (PEI). Such transfection processes have been demonstrated in stirred-tank bioreactors and have proved to be a good method for the rapid production of recombinant proteins for lab to pre-clinical use . HEK293EStable producer cell lines are preferred for the large-scale production of recombinant proteins. The most recent HEK-produced recombinant protein therapeutic, NUWIQ®, was produced in HEK293F cells. NUWIQ® is a recombinant coagulation factor VIII (FVIII). It is produced by transfecting HEK293F cells with a B-domain deleted human FVIII expression construct. After stable transfectants were selected, clones exhibiting optimal production were selected for use .Protein production in producer cell lines can be increased by the use of gene amplification technology . Use of Host cells have a major impact on the glycosylation profile of the biotherapeutic produced . In the Amongst the mammalian expression platforms available in the biopharmaceutical industry, Chinese hamster ovary (CHO) cells are used to produce approximately 70% of recombinant biologics, especially monoclonal antibodies . CHO celCompared to HEK, CHO cells are not able to completely reproduce human glycostructures. This is because CHO cells do not express the enzymes β-galactoside α2,6-sialyltransferase, α1,3/4 fucosyl transferase or β-1,4-N-acetylglucosaminyltransferase III, which are expressed in human cell lines . In addiHEK293 is commonly used in the production of viral vectors. It is used in the production of adenoviral and adeno-associated viral vectors due to presence of the adenoviral E1A/B genes which provide helper functions during viral vector production. In retroviral vector production, HEK293T is used due to the expression of the SV40 large T-antigen in the cell line. Expression of the T-antigen allows plasmids which carry the SV40 origin of replication to undergo replication when transfected into the cell . It was Early viral vector production was challenging as production was performed by the transient transfection of adherent HEK293 cells in serum-containing media. Recent advancements in transient transfection technologies, cell line and media development have demonstrated that viral vector production can be performed using serum-free suspension-based transfection process in chemically defined cell culture medium. In addition, stable viral vector producer cell lines have been established. Together, these developments have enabled the scalable production of viral vectors in HEK293 cells.Retroviral vectors are enveloped, single-stranded RNA viruses. In this family of viruses, γ-retroviruses (γRV) based on the Murine Leukemia Virus and lentiviruses (LV) based on the Human Immunodeficiency Virus type 1, are commonly used in gene therapies . These rRetroviral vectors are one of the best tools for gene transfer due to its ability to transduce wide range of cell types . Retrovigag-pro-pol genes, and the envelope protein are stably expressed in separate expression casettes. γRV production is then achieved by transfection of the packaging cell line with a single vector construct carrying the transgene-of-interest, the Ψ packaging signal, and a modified long terminal repeat (LTR) species to further minimize risk of RCV formation . In γRV production, as the viral genes are non-cytotoxic, packaging cell lines have been developed to facilitate γRV production. In third generation γRV packaging cell lines, ormation .Gag-Pro-Pol which encodes viral structural proteins and enzymes; 2) Rev which expresses accessory proteins that is essential for viral genome nuclear exportation; 3) Env that encodes for the envelope glycoproteins which engage with cell receptors for cellular entry and; 4) Vector genome that carries the gene of interest  are non-enveloped, single-stranded DNA viruses which have shown safety and efficacy as gene therapy vectors . Since 2rep and cap genes; and 3) Cargo gene flanked by AAV ITR sequences (Recombinant AAVs (rAAVs) are typically produced via the transient-transfection of adherent HEK293 cells with three plasmids containing: 1) Adenoviral helper factors, E4, E2a, and VARNA; 2) Adeno-associated virus equences . HEK293 equences  which arequences . Althougequences , HEK293 rep, cap, and cargo genes  cells where gene expression is controlled by an inducible promoter. Scalable rAAV production is achieved simply by induction, without the use of helper viruses, transfection reagents or plasmids .Spodoptera frugiperda (Sf9) cells with three recombinant baculoviruses, a Rep-baculovirus, a Cap-baculovirus, and a Cargo ITR baculovirus, with the helper functions provided for by the baculovirus.While rAAVs are commonly produced in HEK293-based systems, baculovirus-based systems have been developed showing comparable rAAV titers. The use of the baculovirus expression vector system for rAAV production was first described in 2002  where rArep and cap genes  are non-enveloped, double-stranded DNA viruses. It was first used as a gene therapy vector as they possess high genomic capacity, high transduction efficiency and were non-integrating with high epichromosomal persistence . Howevertrans-complementation of viral vector genes in the production cell lines.The COVID-19 pandemic drove the rapid development of adenoviral vectored vaccines and their eventual emergency use . Of the First generation AdV vectors are produced by the substitution of the E1 and/or E3 regions with an expression cassette. E1 gene products which are necessary for viral production, are provided for in trans in production cell lines such as HEK293 or PER. C6. Products from the E3 gene region are not essential for viral replication and hence, does not need to be complemented. Due to the expression of other viral proteins, first-generation adenoviral vectors provoke an immune response. In the case of a vaccine, the immune response elicited is particularly advantageous .in vivo. In second generation AdV vectors, additional genes required for viral replication have been inactivated. Virus production is performed in cell lines expressing the E2 and/or E4 gene products. Finally, in the third class of “gutless adenovirus”, all viral genes have been removed except for the cis-acting DNA sequences required for viral DNA replication and packaging  are used in the LV-MAXFuture of viral vector production technologies leans towards development of stable cell lines for AAV, LV and yRV production. Such processes enable the production of viral vectors without the need to use costly reagents required for transfection. In stable producer cell lines, process developments in CHO resulted in a 10–20 fold improvement in glycoprotein production . Advance


HER2 affibody conjugate on the positive-HER2 cancer cell lines. Overexpression of human epidermal growth factor receptor 2 (HER2) causes cell transformation and development of various types of malignancies. Idarubicin is an effective anti-neoplastic drug but its specific delivery to the targeted cells is still a great challenge. Affibody as a cost-effective peptide molecule with low molecular weight has a high affinity for HER2 receptors. Breast and ovarian cancers as wide speared types of malignancies are associated with high expression of HER2. In the current study, we assessed the cytotoxic effects of idarubicin-ZHER2 affibody conjugate on the SK-BR-3, SK-OV-3, and MCF-7 cells with various levels of HER2 expression were evaluated by MTT assay following 48 hours of incubation.The cytotoxic effects of constructed idarubicin-ZHER2 affibody molecule showed a mild effect on the cell viability of all treated cells at its optimum concentration. The constructed Idarubicin-ZHER2 affibody conjugate decreased the viability of SK-OV-3 cells at its optimal concentration, more efficiently and specifically than other treated cells. Idarubicin showed a potent and dose-dependent cytotoxic effect against all treated cell lines while the SK-OV-3 cells were significantly more sensitive. The dimeric form of the ZHER2-affibody conjugate of idarubicin has a more specific cytotoxic effect compared with idarubicin alone against HER2-overexpressing ovarian cancerous cells. It appears the ZHER2-affibody conjugate of idarubicin has great potential to be implicated as an innovative anti-cancer agent in future clinical trials in patients with HER2-overexpressing ovarian cancer.The Z Ovarian cancer is one of the three major gynecologic malignancies and the most lethal among women worldwide . SurgeryHER2 has a great affinity for the HER2 receptor and previously has been used for the delivery of various anti-cancer drugs to HER2-overexpressed cancerous cell lines (HER2 affibody conjugate could be successfully used for specific ablation of HER2-overexpressed HN-5 cells originated from head and neck squamous cell carcinoma (HNSCC)  and breast cancer cells (SK-BR-3), were compared to MCF-7 as a low expressing HER2 cell line. One of the most substantial targets in human malignancy targeted therapy is EGFRs . This tyll lines -22. Our  (HNSCC) . In the Chemicals--2, 5-diphenyl tetrazolium bromide (MTT), and Dulbecco's modified Eagle's medium (DMEM) were purchased from Sigma-Aldrich . The human HER2-positive cell lines including ovarian carcinoma cell line (SK-OV-3), and breast cancer cell lines  were purchased from the National Cell Bank of Iran . All other chemicals were obtained from Merck .Idarubicin was purchased from Selleckchem . Sulfosuccinimidyl 4- cyclohexane-1-carboxylate (Sulfo-SMCC), HisPur™ Ni-NTA resin, imidazole, and β-D-1-thiogalactopyranoside (IPTG) were obtained from Thermo Fisher Scientific . Ethylenediaminetetraacetic acid (EDTA), ampicillin, phenylmethanesulfonyl fluoride (PMSF), 3Expression and Purification of Zher2Affibody HER2 gene was synthesized by de novo gene synthesis and one cysteine codon was also added to the 5΄ end of the gene (HER2 affibody gene was inserted into a Champion™ pET302/NT-His plasmid from Invitrogen™ (Thermo Fisher Scientific) and cloned in competent E. coli BL21 cells. ZHER2 Affibody was expressed, purified, and qualified as previously described elsewhere (HER2 affibody was performed on the HisPur™ Ni-NTA resin (Thermo Fisher Scientific) according to the manufacturer's protocol. Finally, protein fractions were examined using coomassie brilliant blue (CBB) staining following SDS-PAGE to confirm the purity of the prepared affibody. Finally, affibody-containing fractions were pooled and protein concentration was determined using Bradford reagent  cyclohexane-1-carboxylate (Sulfo-SMCC) as a heterobifunctional crosslinker as previously described (-1) at a 2-fold molar excess. The reaction mixture was incubated for 30 min at room temperature and then affibody solution was added to the mixture in a 1:1 molar ratio. After 30 min, unreacted cross-linker and unconjugated idarubicin molecules were separated from Idarubicin-ZHER2 affibody conjugate using a desalting column equilibrated with conjugation buffer. The product was concentrated using Amicon Ultra-15 centrifugal filter unit. Construction of idarubicin-ZHER2 affibody conjugate was confirmed using a UV-Vis spectrophotometer  and fluorescence spectrophotometer  as previously described (The idarubicin-Zescribed . The Sulescribed . Cell Viability Assay2). The cell viability was measured by MTT colorimetric assay. Briefly, the cells in the logarithmic growth phase were seeded at approximately 1×104 cells well−1 into flat-bottom 96-well plates . The cells were treated with various concentrations of idarubicin (0.001-0.1 µM), ZHER2 affibody (0.1-100 µM), and idarubicin-ZHER2 affibody conjugate (0.01-50 µM) for 48 hours in triplicate. Then, the culture medium was replaced with fresh medium and MTT solution was added and incubation continued for another 4.0 hours. After washing the cells three times with PBS the pure DMSO (200 μL) was added. The absorbance of each well was read at 570 nm using a microplate reader . The SK-BR-3 and MCF-7 cell lines were cultured in complete DMEM with high glucose, and the SK-OV-3 cell line was cultured in complete RPMI-1640 (with high glucose) under a humid atmosphere  supplemented with protease inhibitors. The cell lysate was centrifuged at 10,000 g for 15 min at 4°C and protein concentration of the supernatant was determined using a bicinchoninic acid (BCA) protein quantitation kit. The samples (50 μg each) were electrophoresed on 12% SDS-PAGE, and then were electro-transferred onto polyvinylidene difluoride (PVDF) membranes . After blocking with 5% skimmed milk-containing TBS-T solution  for 2 hr at room temperature, primary anti-HER2 antibody  was added and incubation was processed overnight at 4°C. After washing the blotted membrane three times with TBS-T and incubation with HRP-conjugated secondary antibody for 1 hr, protein bands were visualized with a Chemi-Doc gel documentation system  by enhanced chemiluminescence (ECL) kit . The intensity of bands was quantified by densitometry analysis of blots using Image J software and described as a ratio to β-actin expression.Western blot analysis was performed for comparison of HER2 expression in three investigated cancerous cell lines. The cells at a density of 5×10 Statistical AnalysisAll experiments were performed in triplicate. All data were processed using SPSS software version 15  and expressed as mean ± SEM. Data were analyzed by ANOVA to determine differences between experimental groups. A P-value <0.05 was considered as statistically significant. Affibody ZHER2 ExpressionE. coli as a bacterial host was used for cloning and expression of the engineered ZHER2 affibody gene. Affibody molecules were purified using Ni-affinity column chromatography and the purity of the product was assessed by the SDS-PAGE analysis. As shown in In the current study, BL21 (DE3) competent The protein bands were stained with Coomassie brilliant blue. A single sharp band with a molecular weight around 14 kDa confirmed the purity of the affibody product. HER2 Expression in Different Cancerous Cell LinesThe level of HER2 expression in three different cancerous cell lines was evaluated using western blot analysis. Our results indicated that the level of HER2 expression in SK-OV-3 cells was significantly higher than the other examined cell lines as shown in Over-expression of HER2 in SK-OV-3 and SK-BR-3 cells compared with MCF-7 cell line was verified using immunoblotting. As shown, SK-OV-3 and SK-BR-3 cell lines express HER2 at a higher level compared with MCF-7 cells with normal expression of HER2.Cytotoxic Effect of Idarubicin on the Cancerous Cell LinesTo our knowledge, there is no report about the cytotoxic effects of idarubicin either alone or with its conjugate with affibody on the SK-OV-3 cancerous cell line. In the current study, HER2-positive SK-OV-3 cells were treated with idarubicin at a concentration range between 0.001 to 0.1 µM and the cell viability was compared to SK-BR-3 and MCF-7 cell lines that were treated in a similar way . Based oCytotoxic Effect of Zher2 Affibody and Idarubicin-Zher2 Affibody Conjugate on the Treated Cancerous CellsHER2 affibody  was 45.98%, 90.01, and 94.81 compared to untreated control cells  of purified Zaffibody . After 4ol cells . The eleHER2 affibody was covalently bound to idarubicin through a heterobifunctional sulfo-SMCC crosslinker. The Sulfo-SMCC linker permits covalent conjugation of amine-containing (idarubicin) and sulfhydryl-containing (ZHER2 affibody) molecules. The formation of the immuno-conjugate was confirmed by UV-Vis and fluorescence spectrophotometry as previously described  which is one of the important and fascinating molecules in life sciences for therapeutic, diagnostic imaging, and biotechnological applications . Recentl et al. . They foHER2 affibody was expressed and purified on SDS-PAGE as shown in HER2 affibody showed a molecular weight of approximately 14 kDa which is consistent with the previously published results (HER2 affibody) molecules which can be confirmed by using UV-Vis and fluorescence spectroscopy as previously described elsewhere  as an FDA-approved therapeutic monoclonal antibody routinely used for the treatment of patients with HER2-positive breast tumors  of purified Zaffibody . Our rese tumors , 41, 42.-3 cells . They fot tumors . et al. confirmed that HER2 affibody-cisplatin containing liposomes (affisomes) could improve the therapeutic activity of cisplatin in a HER2-overexpressing tumor model  and sulfhydryl-containing (ZHER2 affibody) molecules. The formation of the immuno-conjugate was confirmed by UV-Vis and fluorescence spectrophotometry as previously described (HER2 affibody conjugate on the SK-OV-3 was significantly higher than the SK-BR-3 and MCF-7 cells (HER2 affibody conjugate on the cell viability of SK-OV-3 ovarian cancerous cells. Based on our results, we could propose the idarubicin-ZHER2 affibody conjugate as an anti-cancerous therapeutic agent should be more investigating for clinical trials in malignant patients with high expression of HER2 receptors, especially in ovarian cancer.Immuno-conjugates commonly are constructed from a targeting moiety, whole antibody molecule or its Fab domain, and a toxic part which is considered as promising therapeutic agents that have been attracted more attention in recent years for cancer therapy. Immuno-conjugate drugs are under active investigation for specific induction of apoptosis in malignant cells and some of them have been approved by the FDA for the treatment of cancer patients . Due to or model . In the escribed . Our res-7 cells . To our HER2 affibody on this cell line is not out of mind. Finally, it seems that by conjugation of idarubicin to ZHER2 affibody, the specificity of idarubicin for inhibition of SK-OV-3 proliferation can be improved by facilitating its delivery into targeted cells. More investigations are needed to verify the idarubicin-ZHER2 affibody conjugate as a potential candidate for the treatment of HER2-overexpression ovarian malignancies.Chemotherapeutic agents that are commonly used in the treatment of various human malignancies have several undesirable side effects. Approaches for specific delivery of antineoplastic drugs to malignant cells are seriously considered by drug discovery programs of pharmaceutical companies. In HER2-targeted therapy, as a new approach for the treatment of several human malignancies, therapeutic agents are directed toward HER2-positive cells by linking them to a peptide with a high affinity for the HER2 receptor. Idarubicin individually reduced the cell viability of all three examined cell lines in a dose-dependent manner but its effect on the SK-OV-3 cells was more potent. So, it seems idarubicin may be considered as a new medication for the treatment of ovarian tumors. On the other hand, and in regard to the higher expression of HER2 in SK-OV-3 cells, the more cytotoxic effect of Z


MET were present in three cell lines that all demonstrated increased MET phosphorylation in response to HGF and abrogation of MET phosphorylation in response to MET inhibitors. CDKN2A loss due to mutation or gene deletion, associated with poor outcomes in type 1 pRCC patients, was observed in all cell line models. Six cell lines formed tumor xenografts in athymic nude mice and thus provide in vivo models of type 1 pRCC. These type 1 pRCC cell lines provide a comprehensive representation of the genetic alterations associated with pRCC that will give insight into the biology of this disease and be ideal preclinical models for therapeutic studies.Renal cell carcinoma (RCC) is not a single disease but is made up of several different histologically defined subtypes that are associated with distinct genetic alterations which require subtype specific management and treatment. Papillary renal cell carcinoma (pRCC) is the second most common subtype after conventional/clear cell RCC (ccRCC), representing ~20% of cases, and is subcategorized into type 1 and type 2 pRCC. It is important for preclinical studies to have cell lines that accurately represent each specific RCC subtype. This study characterizes seven cell lines derived from both primary and metastatic sites of type 1 pRCC, including the first cell line derived from a hereditary papillary renal carcinoma (HPRC)‐associated tumor. Complete or partial gain of chromosome 7 was observed in all cell lines and other common gains of chromosomes 16, 17, or 20 were seen in several cell lines. Activating mutations of  These differences mean that each subtype may require specific management and treatment. Papillary renal cell carcinoma (pRCC) is the second most common subtype of RCC after conventional or clear cell renal cell carcinoma (ccRCC), accounting for ~20% of cases. Papillary RCC is further subcategorized into type 1 and type 2 pRCC. It is important for preclinical studies that cell line models which accurately represent each specific RCC subtype are produced and characterized.VHL tumor suppressor gene and loss of function of this gene in VHL renal tumors, as well as in a significant percentage of tumors from patients with sporadic ccRCC (ranging from 59% to 92%).MET oncogene in hereditary papillary renal carcinoma (HPRC), associated with type 1 pRCC, as well as germline inactivating mutations in the FH tumor suppressor gene in hereditary leiomyomatosis and renal cell carcinoma (HLRCC), often associated with an aggressive variant of type 2 pRCC.RCC, also referred to as kidney cancer, can occur as either a sporadic or inherited disease, and studies of familial kidney cancer syndromes have elucidated important genetic features of RCC. Investigations of the inherited von Hippel‐Lindau (VHL) clear cell RCC (ccRCC) predisposition syndrome led to the discovery of the MET gene) and 17 being most frequent, followed by gain of chromosomes 12, 16, and 20.MET gene occurs in approximately 13% of sporadic type 1 pRCC.BAP1) and that loss of CDKN2A (p16) associated with poorer patient outcome.Alongside these familial studies, analysis of large cohorts of sporadic pRCC, such as those performed by the Cancer Genome Atlas (TCGA), have provided further insights into the biology of these tumors that need to be reflected in cell line models.NF2 mutation that dysregulated the HIPPO pathway and created a targetable therapeutic susceptibility to dasatinib, thereby inhibiting the downstream effects of HIPPO pathway dysregulation.Cell line models provide an important tool for investigating the importance of these discoveries and a preclinical model for testing novel therapeutic agents that may target specific alterations within these tumors. The NCI has a long history of generating genetically defined cell line models from primary or metastatic kidney tumor tissue excised from patients with either sporadic or germline mutation associated RCCs.MET‐mutated HPRC patient. These cell line models provide examples of CDKN2A (p16) loss, BAP1, and KRAS mutation, and type 1 pRCC‐associated chromosomal copy number alterations that should enable the effective evaluation of precision therapies.This study characterizes the genetic and genomic alterations in seven type 1 pRCC cell lines derived from either primary kidney tumors or metastatic material excised from patients, including the first cell line derived from a germline 22.1All patients from which procured materials were acquired were evaluated and managed for clinical assessment and surgical resection or systematic therapy at the Hatfield Clinical Research Center, National Institutes of Health (NIH) as patients of the Urologic Oncology Branch of the National Cancer Institute (NCI). All patient recruitment and tissue procurement and use were approved by the Institutional Review Board of the National Cancer Institute on either the NCI‐97‐C‐0147 or NCI‐89‐C‐0086 protocols. All patients had provided written informed consent. Relevant clinical data was acquired where possible for all patients. Peripheral blood samples were obtained when possible for DNA extraction to provide germline DNA for each patient.2.23) and smeared across a 10 cm tissue culture dish or 75 cm2 flask and placed under 5 to 8 mL of DMEM media in sterile conditions. Ascites fluid was centrifuged at 4°C at 1000g for 5 minutes to produce a cell pellet which was mixed with a small volume of media (5‐8 mL) and placed in a tissue culture flask under sterile conditions. All cells were initially cultivated in DMEM medium containing 25 mM d‐glucose with 2 mM l‐glutamine  and supplemented with 10% fetal calf serum  and x1 Antibiotic‐Antimycotic solution (ThermoFisher Scientific Inc). Cell lines were propagated for over 20 passages to demonstrate immortalization with a passage being performed every 2 to 5 days. Once established, the Antibiotic‐Antimycotic solution was removed from the media to demonstrate that no infection was present within the cell line.All novel cell lines were established from either tumor tissue excised during surgery or from a cell pellet derived from ascites. Spontaneously immortal cell lines were generated using the protocols and techniques previously described.2.3All cell lines were evaluated by short tandem repeat (STR) analysis  to provide a distinct genetic fingerprint for each line . When po2.4MET (7q31), EGFR (7p11.2), and a probe for the centromere of chromosome 7 (CEP 7). FISH image analysis was performed using the Q‐FISH TM software (Leica).Metaphase spreads were prepared for each cell line and spreads were subsequently hybridized with custom chromosome‐specific fluorescence spectral karyotyping (SKY) probes, imaged, and analyzed using the SkyView software , as previously described.2.5Cell pellets were generated for each cell line from 80‐90% confluent 10 cm dishes and DNAs were extracted using a Promega Maxwell 16 System using the appropriate Maxwell 16 Cell DNA Purification Kit following manufacturers protocol . DNAs from the associated patient's blood samples were similarly extracted using a Promega Maxwell 16 Blood DNA Purification Kit following manufacturers protocol (Promega). Total RNA was extracted from each cells line using Trizol Reagent  and following the standard protocol. In brief, cell lines were grown in 10 cm dishes until they reached a confluency of approximately 80% to 90% and then washed once with 5 mL of sterile PBS and lysed using 1 mL of Trizol Reagent. Following the standard Trizol Reagent guanidinium thiocyanate‐phenol‐chloroform RNA extraction protocol, the resulting total RNA was re‐suspended in 50 μL of RNase‐Free water and stored at −80°C. DNA and RNA concentrations and purities were measured using a NanoDrop 2000 UV‐Vis Spectrophotometer (Thermo Fisher Scientific Inc).2.6RPPH1) on chromosome 14 and calculated using the ViiA7 software as comparative CT (ΔΔCT) values. The nonimmortalized normal kidney cell line, RPTEC, was designated to represent a normal chromosomal copy number with a value of 2. Taqman Copy Number Assay probes (Thermo Fisher Scientific Inc) were used to assess the gene copy number of the following genes: CDKN2A (Hs03714372_cn), MET (Hs01432482_cn), and EGFR (Hs00711969_cn).Copy number analysis was performed using 2 μL of dilute DNA (5 ng/μL), 5 μL of Taqman universal PCR master mix, 0.5 μL of Taqman Copy Number Assay probe (FAM), 0.5 μL of Taqman Copy Number Reference Assay (RNaseP) probe (VIC) and 2.0 μL of RNase‐Free Water to produce a 10 μL reaction volume for analysis by an ABI ViiA7 real‐time PCR system (Thermo Fisher Scientific Inc). Gene copy number was normalized to the Ribonuclease P RNA component H1 (H1RNA) gene (2.7CDKN2A (Hs00923894_m1), MET (Hs01565584_m1), EGFR (Hs01076078_m1), CD274 (PD‐L1) (Hs00204257_m1), and PDCD1LG2 (PD‐L2) (Hs00228839_m1).cDNA was synthesized from 2 μg of total mRNA from each cell line using the SuperScript VILO cDNA Synthesis Kit (Invitrogen) in a 20 μL volume. The cDNAs were diluted 10‐fold with 180 μL of RNase‐Free Water. RT‐PCR amplification was performed using 2 μL of dilute cDNA, 5 μL of Taqman universal PCR master mix, 0.5 μL of Taqman Gene Expression Assay probe, and 2.5 μL of RNase‐Free Water to produce a 10 μL reaction volume for analysis by an ABI ViiA7 real‐time PCR system (Thermo Fisher Scientific Inc). Expression levels were normalized to the control 18S rRNA gene (Hs99999901_m1) and calculated using the ViiA7 software as comparative CT (ΔΔCT) values. The nonimmortalized normal kidney cell line, RPTEC, was designated to represent the normal expression level with a value of 1. Taqman Gene Expression Assay probes (Thermo Fisher Scientific Inc) were used to assess the expression levels for several genes including, 2.8MET, CDKN2A, KRAS, CUL3, and BAP1 genes were validated by PCR using a Qiagen Taq PCR Core Kit  followed by bidirectional sequencing using the BigDye Terminator v.1.1 Cycle Sequencing Kit , in accordance with the manufacturer's specifications. Validations were compared to a control DNA sample derived from the peripheral blood leukocytes of a control patient. The entire mitochondrial genome was sequenced and analyzed as previously described.Cell line DNA was sequenced using the OncoVar assay that is a targeted hybrid capture sequencing analysis which detects genomic variants in a panel of 240 cancer‐related genes, including known pRCC associated genes, and was performed as previously published.2.9Analysis of the total and phospho‐MET levels in Triton X‐100 cell line extracts was performed by an electrochemiluminescent two site immunoassay using a SectorImager 2400 plate reader  as previously described.2.106 of cells were suspended in a 0.2 mL mixture of 50% PBS and 50% Matrigel Matrix  and subcutaneously injected into the flanks of 5 NCI Athymic NCr‐nu/nu mice (obtained from Charles River Frederick Research Model Facility) to evaluate the tumorigenic potential. All animal care protocols used had been approved by the Institutional Animal Care and Use Committee (IACUC) and were in accordance with National Cancer Institute guidelines.Approximately 1 × 1033.1MET oncogene identified a known pathogenic missense mutation, p.H1112R, thus confirming his diagnosis of HPRC , BRAF (7q34), and HGF (7q21.11) genes, but not EFGR (7p11.2) gene .Chromosome 17 and 16 are frequently gained in type 1 pRCC, but among our cell lines, only three consistently (>50% of spreads) gained whole copy number gains of chromosome 17  and four gained copies of chromosome 16  Figures .18 Not3.3MET p.H1112R mutation present in UOK345, UOK208 was found to have a known pathogenic MET mutation, p.V1088A, and UOK337 demonstrated a novel missense mutation, p.H1106Q. All of these mutations occur in the MET tyrosine kinase domain.CDKN2A tumor suppressor gene, a key component of cell cycle regulation  mRNA expression levels were reduced in comparison to the RPTEC normal control in most cell lines and only mildly elevated in UOK112 and comparable to RPTEC in UOK337 (PDCD1LG2) mRNA expression levels were similar to RPTEC normal control in most cells and elevated in a single cell line, UOK112 , and a breast cancer cell line, B5/589  that served as a positive control for MET expression. Adding hepatocyte growth factor (HGF), the ligand for the MET receptor, significantly increased phospho‐MET levels in the three cell lines with MET mutations as well as the B5/589 positive control, but the two cell lines with gain of the MET gene showed little response to HGF , two cell lines with high F Figure . The celF Figure . The eff3.62, while UOK342 xenografts grew rapidly producing 2000 mm2 tumors within ~40 days  analyses of papillary renal cell carcinoma (pRCC) provided an excellent characterization of the major genetic and genomic features of type 1 pRCC.All seven cell line models described herein were spontaneously immortalized from fresh patient tissues, requiring no additional genetic manipulation, and should provide the best representation of type 1 pRCC tumors. Five of the cell line models were derived from metastatic tissues, while the remaining two cell line models were derived from the primary kidney tissue in patients that also had synchronous metastatic disease. Thus, these cell line models may not be appropriate for investigating the biology behind the initiation of type 1 pRCC but rather can provide invaluable insights into the biology of metastatic type 1 pRCC and an excellent preclinical model for novel therapeutics for patients with advanced disease.MET, along with many other genes, but excluded EGFR. Similarly, UOK337 and UOK342 had gains of both complete copies of chromosome 7 and additional partial regions of chromosome 7q, leading to more increased copies of MET than EGFR. The gain of chromosome 7 could potentially affect many oncogenes including both MET and EGFR but the selective gain of MET and the correlated increased in MET mRNA expression, that was not observed in EGFR, suggests that MET gain is a key element in these cell lines.Chromosomal alterations are common in RCC and specific gains or losses are associated with different RCC subtypes. Type 1 pRCC is associated with gains of chromosomes 7, 16, and 17, all of which were represented in our type 1 pRCC cell line models. Classic gain of chromosome 7 was observed in 6 out of 7 cell lines. Notably, the UOK274 cell line had a partial gain of chromosome 7q that included MET to be the most commonly mutated gene in sporadic type 1 pRCC (~15%) and germline MET mutations are associated with HPRC, a disease defined by bilateral, multifocal type 1 pRCCs.MET gene, including the first cell line ever derived from a tumor excised from an HPRC patient (UOK345), and all cell lines demonstrated MET gain. This study showed phosphorylation of the mutant MET protein that could be further induced by adding the HGF ligand, and that this phosphorylation‐related activation can be abrogated using existing MET inhibitors, such as the investigation MET Kinase Inhibitor INC280 currently under clinical trial . Additionally, cell lines with wild‐type MET gain showed HGF‐independent phosphorylation of MET that could also be abrogated with MET inhibitors. Trials of small molecule inhibitors of MET, including foretinib and savolitinib, have demonstrated some efficacy in pRCC tumors. Foretinib was shown to produce a partial response in 5 out of 10 (50%) of germline MET mutation patients and 1 out of 5 (20%) of somatic MET mutation patients but only 1 out of 18 (5%) of patients with only a gain of chromosome 7.TCGA and previous studies have shown BAP1 mutated in UOK332 and CUL3 mutated in UOK345. In TCGA, mutation of the chromatin remodeling gene BAP1 and the NRF2/ARE (antioxidant responsive element) pathway gene CUL3 were observed in 5.6% and 4.1% of all pRCC respectively.KRAS gene, p.G12D and p.G12C respectively. Pathogenic mutation of KRAS was a rare event within the primary pRCC tumors investigated by the TCGA, present in only 2 out of 155 type 1 pRCC (1.3%) and 3 out of 67 type 2 pRCC (4.5%).Less frequently observed mutations in pRCC were also present in the new cell line models, with CDKN2A was shown by the TCGA to be associated with poor patient outcome and loss of CDKN2A was observed in all of our cell line models.CDKN2A loss in advanced disease by studying these cell line models could elucidate potential new therapies, such as targeting the cyclin dependent kinases 4 and 6 (CDK4 and CDK6) that are the inhibitor targets of the p16 protein encoded by CDKN2A.The presence of these less frequent events in our cell lines may reflect the aggressive nature of the tumors from which they were derived. The TCGA type 1 pRCC samples were largely lower stage tumors and these cell lines were all derived from patients with high stage, metastatic disease. In particular, loss of Finally, both in vitro and in vivo analysis of cell line models is essential to provide convincing data for the translation of potential new therapies into patients. Six of these cell lines were capable of producing xenograft tumors when injected into the flank of athymic nude mice, providing models for the vast array of genetic alterations that occur within type 1 pRCC and representing both primary and metastatic disease.VHL mutation, chromosome 3p loss or any other genomic alteration suggestive of ccRCC while demonstrating the gain of chromosomes 7 and 17 associated with pRCC.It is important to note that there are several models for pRCC currently available that have been characterized to varying degrees, including UOK112 and UOK342 that are characterized in this study. UOK112 was initially published over a decade ago with minimal genetic characterization and UOK342 was first published recently as an example of a pRCC cell line with a somatic NF2 mutation that responds to dasatinib treatment.Thus, these novel type 1 pRCC cell lines significantly increase the number of cell line models currently available for studying type 1 pRCC and provide a comprehensive representation of the genetic alterations associated with this cancer. These cell lines will give valuable insight into the biology of advanced type 1 pRCC tumors and provide an ideal preclinical model to investigate novel therapeutic approaches for pRCC that will hopefully provide the foundation for the development of effective forms of therapy for patients with metastatic disease.Appendix S1: Supporting InformationClick here for additional data file.