The cytotoxic activity of the obtained bicyclic derivatives was evaluated using human hepatocellular carcinoma (HCC), medulloblastoma (MB), and glioblastoma (GBM) cell lines. Chosen compounds were shown to notably reduce cell viability as compared to nonmalignant cells.A series of chiral sulfonamides containing the 2-azabicycloalkane scaffold were prepared from  Chromatographic separations were performed on silica gel 60 (70–230 mesh). Thin-layer chromatography was carried out using silica gel 60 precoated plates.Melting points were determined on the Schmelzpunkt Bestimmer Apotec melting point apparatus  using the standard open capillary. α radiation at 80(2) K. The Cambridge Crystallographic Data Centre (CCDC) reference numbers for 12a and 12d: CCDC 1992131 (12a) and 1992390 (12d) (eq = 1.2–1.5Ueq (parent C atom). Basic crystallographic data are presented in X-ray diffraction data for monocrystals were collected on an Xcalibur Ruby diffractometer  with MoKS,3R,4R)-2-[(S)-1-phenylethyl]-3-aminemethyl-2- azabicyclo[2.2.1]heptane 2 and -2-[(S)-1-phenylethyl]-4-amine-2- azabicyclo[3.2.1]octane 3, were prepared as described previously -3- hydroxymethyl-2-azabicyclo[2.2.1]heptane 4, as previously described octane (bridged azepane) counterparts. The scaffold of the latter can be regarded as less rigid; on the other hand, higher flexibility of the arm containing sulfonamide moiety in 2-azabicylo[2.2.1]heptane-derived compound 10 seems to be of importance as well. Among substituents present in the sulfonamide, biphenyl-containing methoxy group  or fluorine (10c) were found to be most active. For phenyl derivatives, the introduction of two –CF3 moieties resulted in enhanced activity and selectivity , while one trifluoromethyl group in the para position was not sufficient to increase the antiproliferative properties.Although the activities of the investigated sulfonamides varied from one cell line to another, certain regularities could be observed, which are important from the point of view of further developments. Comparison of activities exhibited by isomeric compounds Finally, dimeric species 12i and 13a were not particularly active, and even their toxicity for normal cell lines was higher than for malignant ones.10b, 10c, 10e, 10g, and 11e notably reduce cell viability on the D425 cell line  as compared to HUVEC cells. The D425 cell line is categorized as a group 3 medulloblastoma, with high MYC proto-oncogene amplification [10c (3.11-fold change), followed by compounds 10g and 11e . Thus, compounds 10c, 10g, and 11e showed the highest performance among the agents tested in this study. Although the safety margin seems to be too narrow and remains far below the >30-fold difference recommended for safety reasons [In this study, we evaluate the effect of chiral 2-azabicycloalkane-based sulfonamides on a variety of tumor cell lines, including HCC, MB, and GBM. Our results indicate that compounds fication . In D425 reasons , appropr


TMPRSS4 is a novel Type II transmembrane serine protease found at the surface of the cells and is involved in the development and cancer progression. However, TMPRSS4 functions in breast cancer remain poor understand. The present study investigated the function of TMPRSS4 in the breast cancer cells and the potential mechanistic action underling. The lentiviral vectors causing TMPRSS4 down-regulation and over-expression were established and transfected in MDA-MB-468 and MCF-7 cells, respectively. By using the CCK-8 assay, cell proliferation was analyzed. Moreover, western blot was used to detect the expression of certain proteins related to cell apoptosis (Bax and Bcl2) signaling pathway and telomere maintenance . Cell cycle and cell apoptosis were also analyzed by using the Flow cytometry analysis. TMPRSS4 expression was detected at the mRNA level and protein level by performing qPCR and western blot technique, respectively. TMPRSS4 expression is inhibited in stable transfected MDA-MB-468-shTMPRSS4 cells compared to the control MDA-MB-468-NC and its expression is up-regulated in stable transfected MCF-7-TMPTSS4 compared to its control MCF-7-NC. Moreover, TMPRSS4 silencing in breast cancer reduces cells proliferation by promoting cell cycle arrest in G2/M phase, cell apoptosis, and telomere maintenance impairment while the TMPRSS4 overexpression increases cells proliferation through cell apoptosis reduction and telomere maintenance reinforcement associated with insignificant change in cell cycle progression. TMPRSS4 plays important roles in cancer progression and may be considered as a good therapeutic target for cancer gene therapy especially breast cancer.  Breast cancer is the most common neoplasm diagnosis among women worldwide and is the leading cause of female cancer death . In 2015, 2.4 million incident cases and 523,000 death cases were estimated worldwide and the increase in the number is predicted in the future . The Cancer gene therapy (CGT) which is the modulation of genes implicated in cancer progression, is one of the new cancer treatment strategies developed and used nowadays . Moreover, the Type II Transmembrane serine proteases (TTPs) are a subfamily of serine proteases with a common proteolytic domain, a transmembrane domain, a short cytoplasmic domain and variable length stem region . TTPs are implicated in the regulation of cellular signaling, tumor initiation, and progression via itself deregulation . TMPRSS4 is a member of TTPs and is often overexpressed in many types of cancer tissues such as pancreatic, thyroid, colon, lung, gastric, breast and other cancer tissues, with a poor clinical prognostic . TMPRSS4 is implicated in cell mobility, invasion, proliferation and tumor metastasis . It has been reported that TMPRSS4 down-regulation suppressed cell proliferation rate , induced cell apoptosis , promotes cell cycle arrest , and cell migration and invasion . Moreover, telomeres are DNA proteins complexes found at the ends of eukaryotic chromosomes for the protection of these chromosomes ends from its recognition as chromosome breaks. Loss of telomere protection ( telomere maintenance) activates DNA damage like signaling response which can halt cell proliferation or promote cell death via induction of tumor suppressors P53 and p16 . However, the effect of TMPRSS4 on cell proliferation in relationship with telomere integrity remains unclear, especially in breast cancer. We undertook this study to confirm in breast cancer, the predicted roles of cell cycle and cell apoptosis in TMPRSS4 modulation mediated cell proliferation modulation found before in other types of cancer cell lines and to investigate the effect of TMPRSS4 modulation on cell proliferation in relationship with telomere integrity. From this study, we showed that cell apoptosis and telomeres are implicated in TMPRSS4 expression modulation induced modulation of cells proliferation while cell cycle is only implicated in TMPRSS4 expression silencing reduced cell proliferation in breast cancer. Cell line, cell culture, and reagents2 at 37oC in DMEM  containing 10% fetal bovine serum , 100 U/mL penicillin and 100 ug/mL streptomycin.MDA-MB-468 cells and MCF-7 cells were obtained from the key laboratory of Tumor Biological Behavior of Hubei Province and incubated under 5% COVector, transfection, and generation of stable cell linesHuman breast cancer cells MDA-MB-468 were stably transfected with TMPRSS4 down-regulating vectors PLKO.1-sh-TMPRSS4 versus PLKO.1-sh-NC. The full-length cDNA encoding TMPRSS4 was cloned into the lentiviral vector pHAGE-CMV-MCS-PGK-puro N-HA+C-Flag followed by its transfection in MCF-7 cells and the similar plasmid was used to establish a control clone (Bioeagle/Wuhan/China). Puromycin-resistant clones were selected at 5 ug/mL puromycin after two to three weeks post-transfection. The resultant stably transfected cell lines were respectively called MDA-MB-468-sh-TMPRS4 versus MDA-MB-468-sh-NC and MCF-7-TMPRSS4 versus MCF-7-NC. Quantitative PCR and western blot were used to analyze, in resultant stably transfected cell lines, the expression of TMPRSS4 at mRNA and protein level, respectively.Quantitative PCR (q-PCR) and RNA isolationoC. The resultants cDNA were amplified using the RevertAid™ First-Strand cDNA Synthesis kit . For the quantitative analysis, the glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as an internal control. The nucleotide sequence or specific primer for mRNA were designed as follows: TMPRSS4 Sense, 5′-CCGATGTGTTCAACTGGAAG-3′ and anti-sense, 5′-GAGAAAGTGAGTGG GAACTG-3′; GAPDH sense, 5’-GCACCGTCAAGGCTGAGAAC-3′ and anti-sense, 5’-TGGTGAAGACGCCAGTGGA-3’. After denaturation for 5 min at 950C, the reaction was conducted with 40 cycles of 45 sec at 94oC, for 45 sec at 55oC, 60 sec at 72oC and a final extension for 7 min at 72oC. The PCR products were identified using electrophoresis on 1.5% agarose gels containing 0.5% ethidium bromide (ED). The thermal amplification was performed on Mx3000P qPCR System  and the Mx3000P analysis program was used to analyze the results. All experiments were carried out in triplicate.Total RNA was isolated from the resultant stably transfected MDA-MB-468 and MCF-7 cell lines by using TRIzol reagent according to the manufacturer’s protocol, followed by measurement of the RNA concentration. cDNA was generated from extracted total RNA by using the HiScript qRT SuperMix , for 15 min at 50Western blot analysisoC overnight, followed by the incubation of Goat anti-rabbit or anti-mouse horseradish peroxidase-conjugated antibodies  for ,at least, 1 h at room temperature. Membranes were washed three to five times during 10 min per washing prior to each step. The primary antibodies used included: GAPDH , TMPRSS4 , Bax , Bcl2 , UBE2D3 , POT1 , TPP1 . The separated proteins bands were visualized using Enhanced chemiluminescence system ECL . The images were captured and analyzed (quantified) by respectively using ChemiDoc XRS + System  and Image J program. The resultant stably transfected MDA-MB-468 and MCF-7 cells were treated with RIPA lysis buffer  with an addition of 1xPMSF  and phosphatase inhibitor tablets . Same quantities of proteins (30 ug) were separated on 10-12.5% SDS page gels and transfected to polyvinylidene difluoride (PVDF) membrane with transfer buffer. After blocking in TBST supplemented with 5% skim milk powder at room temperature for 2 h, membranes were incubated with primary antibodies at 4Cell proliferation analysisoC for 90 min. The absorbance of each well was determined at 450 nm (A450 nm) with a microplate reader. Each test was repeated in four wells and performed daily for four days.The resultant stably transfected MDA-MB-468 and MCF-7 cells were seeded into the 96 wells plates at 3.103 cells per well in 100 µL DMEM culture medium. At real time post culture for each analysis , CCK-8 (10 μL) was added to each plate and re-incubated at 37Cell cycle assay5 /mL cells in 2 mL DMEM medium. At 3 days post-culture, cells were harvested, fixed in 70% ethanol for 30 min and stained with 500 μL of propidium iodure  for 30 min at 37oC. Samples were analyzed by flow cytometry . All experiments were performed three times.The resultant stably transfected MDA-MB-468 and MCF-7 cells were seeded into the six wells plates at the 10Cell apoptosis assay5 /mL cells in 2 mL DMEM medium. At 3 days post-culture, cells were collected and apoptosis tests were performing using FITC - Conjugated annexin V / Propidium iodide method  according to the manufacturer’s instructions. All tests were carried out in triplicate.The resultant stably transfected MDA-MB-468 and MCF-7 cells were seeded into the six wells plates at the 10Statistical AnalysisGraphPad Prism 5.0 was used for Statistical analysis. One way ANOVA was used for comparison of multiple groups with Turkey’s method and p-Value <0.05. Data are presented as the mean ± SD. Value of P<0.05 was considered to indicate a statistically significant difference.Effect of stable transfection in MDA-MB-468 and MCF-7 on normal TMPRSS4 expressionIn order to analyze the effect of TMPRSS4 down-regulating and up-regulating on normal TMPRSS4 expression in breast cancer, the MDA-MB-468 and MCF-7 breast cancer cell lines were respectively selected to perform the experiments based on the report of Li et al., (2017) where it has been shown that TMPRSS4 is highly expressed in MDA-MB-468 cells and lowly expressed in MFC-7 cell lines. For confirmation of efficient transfection, qPCR and western blot were respectively used and showed that stable transfection in MDA-MB-468 results to the reduction of TMPRSS4 mRNA  and TMPREffect of TMPRSS4 modulation on breast cancer cells proliferation.Cell proliferation was analyzed by utilizing the CCK-8 assay. The results showed that inhibition of TMPRSS4 expression in MDA-MB-468 cell lines reduced the cell proliferation kinetic  and signEffect of TMPRSS4 modulation on breast cancer cell cycleCells cycle was examined using flow cytometry (FACS) assay. The results revealed that silencing TMPRSS4 in MDA-MB-468 cells significantly induced cell cycle arrest in G2/M phase [25.63±0.32% versus 19.60±1.21%] and decrease of cell in S phase [ 30.27±0.66% versus 23.52±0.69%], at 72 h post-culture, in MDA-MB-468-sh-TMPRSS4 groups compare to control MDA-MB-468-sh-NC group  at 72 h Effect of TMPRSS4 modulation on breast cancer cells apoptosisCell apoptosis was investigated by performing flow cytometry assay and analyzing the expression of certain proteins (Bcl2 and Bax) related to cell apoptosis signaling pathway. The results showed that TMPRSS4 expression down-regulation increased the rate of apoptotic index in MDA-MB-468-sh-TMPRSS4 groups compared to control MDA-MB-468-sh-NC groups at 72 h post-culture [(26.29±0.62% versus 19.13±1.18%); . OtherwiEffect of TMPRSS4 modulation on telomere integrity in breast cancer cell linesWestern blot was performed to analyze telomere integrity through certain proteins  related to telomere functions. Our findings showed the impairment of expression related to telomere maintenance proteins. TMPRSS4 down-regulation in MDA-MB-468 cells inhibited, in MDA-MB-468-sh-TMPRSS4 groups versus control MDA-MB-468-sh-NC groups, the expression of POT1 and TPP1 and increase expression of UBE2D3 as the proteins positively and negatively related to telomere integrity, respectively . AdditioThe recent studies showed that TMPRSS4, which is kind of TTPs family and frequently overexpressed in the cancer cells , function as a cancer treatment target biomarker through the use of Cancer gene therapy (CGT) strategies. It has been reported that TMPRSS4 silencing reduced cancer proliferation and its overexpression induction increases cell proliferation in many kinds of cancer cell lines . In the present study, we used MDA-MB-468 triple negative breast cancer which overexpresses TMPRSS4 and MCF-7 triple positive breast cancer cell as a low expressed TMPRSS4 cancer cell  and found that induction of TMPRSS4 expression down-regulation by using down-regulating TMPRSS4 vector inhibited cell proliferation compared to transfected control and the induction of TMPRSS4 up-regulation promotes cell proliferation which confirms the several above mentioned former studies results . Moreover, the cell cycle is the well-established tumor suppressive mechanism which could be activated to reduce tumor progression and response of cancer to treatment . Regarding the effect of TMPRSS4 on cancer cell cycle, our results showed that TMPRSS4 silencing in MDA-MB-468 breast cancer promotes the cell cycle arrest in G2/M phase associated to the reduction of the cell cycle arrest in S phase while induction of the TMPRSS4 overexpression in MCF-7 breast cancer cell has no significant effect on cell cycle process. This difference results could be due to the expression of estrogen receptor in MFC-7 cell line. In a breast cancer cell, Estrogen Receptor status is inversely associated with a p53 expression which is implicated in cell cycle process perturbation. It has been reported that the sub-unit α of Estrogen receptor (estrogen receptor α) binds to and inactivates p53 . P53 induces the expression of p21WAF1/CIT1/Sdi1, an inhibitor of the cyclin-dependent kinases (CDKs)2,3,4 and 6 .This suggested that the expression of ER in the MCF-7 cell may lead to the lack of the p53 and unchanged of cell cycle process by TMPRSS4. Our findings are in correlation with the report of Jung  where it has been reported that TMPRSS4 inhibition reduces cell proliferation by down-regulating cyclin D1 and cyclin E1 expression as the genes related to the cell cycle signaling pathways , and with the report of Lee et al., (2016) which reported that TMPRSS4 overexpression promotes cell proliferation and induces a 1.89 fold increase of the cell cycle gene cyclin D1 promoter (-962/+134) activity. However, our results contradicted the previous studies which found that the TMPRSS4 silencing reduces cell proliferation with no changes in cell cycle phase  and the part of the finding of Lee et al., (2016), where it has been reported that, in prostate cancer cell lines, TMPRSS4 overexpression display smaller G0/G1 phase population and larger S phase population compared to control transfected Lee et al., (2016), suggesting that the effect of TMPRSS4 on cell proliferation in relationship with cell cycle is cancer cell type dependent and remains to be more investigated in the future. Otherwise, cell apoptosis is one of the key steps of cancer development and progression and also considered as an anticancer mechanism . The pro-apoptotic (Bax) and anti-apoptotic (Bcl2) proteins are key proteins in the signaling pathway of cell apoptosis and are also used as a therapeutic target for cancer treatment via apoptotic pathway affection . The present study investigated the link between TMPRSS4 and cell apoptosis in TMPRSS4 modulation mediated cell proliferation modulation and showed that TMPRSS4 silencing reduces cells proliferation by promoting cell apoptosis associated with inhibition of anti-apoptotic protein (Bcl2) and increase of pro-apoptotic (Bax) protein expression whereas TMPRSS4 overexpression induces cells proliferation by reducing cell apoptotic index through increase of anti-apoptotic protein (Bcl2) and decrease of pro-apoptotic protein (Bax) expression. These results confirm the finding of Fan  where it has been reported that TMPRSS4 modulation promotes cell proliferation modulation by modulating cell apoptosis through Bcl2 expression modulation  and the findings of Huang et al., (2014) showing that TMPRSS4 silencing reduced cell proliferation via increase of cell apoptosis. Moreover, the telomere is implicated in cancer development and treatment . The telosome and Ubiquitin Conjugated Enzyme (UBE2D3) are two kinds of factors implicated in the integrity of telomere . By investigating the relationship between TMPRSS4 and Telomere, we found that TMPRSS4 expression down-regulation reduce the telomere integrity via reduction of expression of POT1, TPP1 as the kind of telosome proteins, and up-regulation of UBE2D3 while TMPRSS4 overexpression reinforces its integrity. As it has been reported in our previous studies that UBE2D3 is negatively correlated with cell proliferation and telomere maintenance  and cell proliferation has been inhibited by affecting telomere integrity via silencing of POT1  and TPP1 , the present study suggest that TMPRSS4 modulation modulates cell proliferation by modulating telomere maintenance in breast cancer cells.In conclusion, our findings indicate that TMPRSS4 expression modulation modulates breast cancer cell proliferation by modulating cell apoptosis and telomere maintenance while cell cycle is only implicated in TMPRSS4 silencing mediated inhibition of breast cancer cells proliferation. This confirms the implication of TMPRSS4 in cancer progression and can make TMPRSS4 to be considered as a potential therapeutic target for Cancer Gene Therapy (CGT).


N-acetyltransferase 1 (NAT1), present in all tissues, is classically described as a phase-II xenobiotic metabolizing enzyme but can also catalyze the hydrolysis of acetyl-Coenzyme A (acetyl-CoA) in the absence of an arylamine substrate using folate as a cofactor. NAT1 activity varies inter-individually and has been shown to be overexpressed in estrogen receptor-positive (ER+) breast cancers. NAT1 has also been implicated in breast cancer progression however the exact role of NAT1 remains unknown. The objective of this study was to evaluate the effect of varying levels of NAT1 N-acetylation activity in MDA-MB-231 breast cancer cells on global cellular metabolism and to probe for unknown endogenous NAT1 substrates. Global, untargeted metabolomics was conducted via ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) on MDA-MB-231 breast cancer cell lines constructed with siRNA and CRISPR/Cas9 technologies to vary only in NAT1 N-acetylation activity. Many metabolites were differentially abundant in NAT1-modified cell lines compared to the Scrambled parental cell line. N-acetylasparagine and N-acetylputrescine abundances were strongly positively correlated  with NAT1 N-acetylation activity whereas saccharopine abundance was strongly inversely correlated (r = −0.876). Two of the most striking observations were a reduction in de novo pyrimidine biosynthesis and defective β-oxidation of fatty acids in the absence of NAT1. We have shown that NAT1 expression differentially affects cellular metabolism dependent on the level of expression. Our results support the hypothesis that NAT1 is not just a xenobiotic metabolizing enzyme and may have a role in endogenous cellular metabolism.Human arylamine  A better understanding of the role NAT1 has in breast cancer would aide in the development of novel treatment strategies and therapeutics.Breast cancer is a heterogeneous disease with many underlying genetic transformations that lead to a diseased state. According to the American Cancer Association, 30% of all new cancer cases in women in 2020 will be breast cancer and 1 in 8 women will develop breast cancer in their lifetimeN-acetyltransferase 1 (NAT1) is a phase-II xenobiotic metabolizing enzyme found in almost all tissues. NAT1 can additionally hydrolyze acetyl-Coenzyme A (acetyl-CoA) in the absence of an arylamine substrate using folate as a co-factor3. Many additional novel roles for NAT1 have recently been identified using breast cancer cell models including regulation of matrix metalloproteinase 9 (MMP9)4, providing protection against reactive oxygen species during glucose starvation5, and the loss of NAT1 leading to regulation of mitochondria through inhibition of the pyruvate dehydrogenase complex6. NAT1 expression varies inter-individually and has been shown to be elevated in several cancers including estrogen receptor-positive (ER+) breast cancers9. Additionally, multiple studies have shown that inhibition of NAT1, by both small molecule inhibition and siRNA methods, in breast cancer cells leads to decreased invasive ability and proliferation10 and decreased anchorage-independent colony formation11.Human arylamine 12). Differences in endogenous acetyl-CoA have been observed between MDA-MB-231 breast cancer cells expressing parental, increased, and decreased levels of human NAT113. A previous study investigating the polar metabolome of the same cells has also revealed differences in a number of metabolites, including amino acids and palmitoleic acid13. Given these data, we hypothesize differences in NAT1 activity may be contributing to downstream effects on metabolic pathways that utilize acetyl-CoA such as the TCA cycle and fatty acid synthesis and degradation.To date however, the exact mechanism by which NAT1 expression affects cancer risk and progression remains unclear  cell lines as well as a cell line that has only one copy of NAT1 knocked-out .As metabolic reprogramming is one of the hallmarks of cancer proposed by Hanahan and WeinbergScrambled), increased (Up), decreased , or knockout  human NAT1 N-acetylation activity  and no detectable (knockout) NAT1 activity  were included in this study  however the construction of the CRISPR 2–12 cell line has not been previously described. The CRISPR 2–12 cell line was constructed using the same methodology and guide RNA as the CRISPR 2–19 cell line described in Carlisle et al.19. All cell lines were authenticated by the ATCC Short Tandem Repeat (STR) profiling cell authentication service.Additionally, cell lines constructed using CRISPR/Cas9 technology, expressing approximately 50% of the NAT1 activity of the In vitro NAT1 N-acetylation activity was determined in each constructed cell line via high performance liquid chromatography (HPLC) using slight modifications of procedures previously described21. Briefly, cell lysate from each cell line was incubated with 1 mM acetyl-CoA and 300 μM p-aminobenzoic acid (PABA) at 37 °C for 10 minutes. Reactions were terminated with the addition of 1/10 reaction volume 1 M acetic acid. Reaction products were collected and analyzed using an Agilent Technologies 1260 Infinity high performance liquid chromatography using a LiChrospher 100 RP-18  column to determine the amount of acetylated product.(DMEM), with 10% fetal bovine serum, 1% glutamine, and 1% penicillin/streptomycin added. Cells were allowed to grow for three days in an incubator at 37 °C and 5% CO2.Cells were plated in triplicate per biological replicate at a density of 500,000 cells per 150 × 25 mm cell plate. All cell lines were cultured in high-glucose Dulbecco’s Modified Eagle Medium Cells were then harvested on ice by adding 5 mL 0.25% trypsin and scraping the cells from the plate. Three plates were combined to form one sample  to ensure there was enough cell mass for analysis. After harvesting the cells, cells were washed 3 times with ice-cold 1 x phosphate buffered saline (PBS). All supernatant was removed and the cryovials containing cell pellet samples were then flash frozen by placing in a pool of liquid nitrogen for 1 minute followed by immediate storage at −80 °C. Samples were then shipped on dry ice to Metabolon Inc.  for analysis.22.Following receipt by Metabolon, samples were inventoried and immediately stored at −80 °C until processing. Detailed sample preparation, quality assessment/quality control, ultrahigh performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), data extraction, compound identification, and metabolite quantification methods are described in detail elsewhereBiochemical data was normalized to total protein as determined by Bradford assay to account for differences in metabolite levels due to differences in the amount of material present in each sample. Data for each biochemical was rescaled to set the median equal to 1. Missing values were imputed with the minimum value.23. Data was approximately normally distributed after these transformations. Figure Q-values were then calculated from un-adjusted p-values for preserving the false discovery rate and to account for multiple comparisons24. Dunnett’s post-tests were utilized to compare all groups  to the Scrambled group for those metabolites with one-way ANOVA q ≤ 0.05. Q-values were also determined and reported for Dunnett’s post-tests.All statistical analyses were performed on median-scaled and log-transformed data using R: A Language and Environment for Statistical Computing version 3.3.113. Briefly, the mean abundance for each metabolite was calculated for each group. We then divided the mean of the comparison group  by the mean of the Scrambled group to give us fold-change relative to the Scrambled group. Fold-change and significance of between group differences in global metabolites were visualized using volcano plots. Additionally, abundance data were plotted as box-plots to visualize the distribution of each metabolite by groups. The Pearson correlation coefficient was calculated between NAT1 activity and relative metabolite abundance for all metabolites to generate hypotheses about potential unknown NAT1 substrates or products. Additionally, the correlation coefficient was calculated between carnitine and metabolites whose abundance was concordantly altered in the two NAT1 KO cell lines due to the large proportion of fatty acyl-CoA carnitine conjugates observed. Data was also plotted as a heatmap and hierarchal clustering was conducted using the weighted pair group method with arithmetic mean (WPGMA) method. Principal component analysis was conducted by singular value decomposition of the centered data matrix. The loadings of the first  and second  principal component were plotted. Pathway enrichment analysis was conducted for each group compared to Scrambled. The pathway analysis enrichment score was normalized to mean enrichment of random samples of the same size to determine the relative degree of enrichment.Fold-change was calculated as previously describedp-aminobenzoic acid (PABA) N-acetylation activity was measured in each of the six MDA-MB-231 cell lines. The Scrambled cell line had approximately the same activity as the Parent MDA-MB-231 cell line while the Up cell line had an approximate 700% increase in activity. Additionally, the Down and CRISPR 2-12 cell lines had approximately 65% and 50% of the activity of the Parent and Scrambled cell lines, respectively, while the CRISPR 2-19 and CRISPR 5-50 cell lines had no detectable (limit of detection = 0.05 nmoles acetylated PABA/min/mg) activity  between the six cell lines  were differentially abundant in the Down, Up, CRISPR 2-12, CRISPR 2-19, and CRISPR 5-50 groups, respectively, with a fold change of 2 or greater (in either direction) compared to the Scrambled cell line. Metabolites were further characterized by direction of fold-change compared to Scrambled  of the detected metabolites were found to significantly differ  utilized during the knockout of NAT1, the overlap in significant metabolites with a fold-change greater than or equal to 2 was compared between the two NAT1 KO cell lines and the oup Fig. . EighteeN-acetylasparagine, N-acetylputrescine, saccharopine, cytidine, 1-palmitoyl-2-alpha linolenoyl-GPC (16:0/18:3n3), isovalerylcarnitine (C5), cysteine sulfinic acid, and serotonin, were significantly associated with NAT1 PABA N-acetylation activity  value greater than 0.90 and are N-acetylated compounds, suggesting they may be products of N-acetylation by NAT1. Two of the metabolites significantly correlated with PABA N-acetylation, saccharopine  of all metabolites detected to be altered. Additionally, we expected very few, if any, differences in metabolite abundance between the two NAT1 KO cell lines since each cell line should have the exact same genome. Yet one of the most striking observations of this study is the differences in relative metabolite abundance between the two complete NAT1 KO cell lines. The hierarchical clustering, principal components analysis, and pathway enrichment analysis show there were significant differences between the two cell lines constructed using CRISPR/Cas9 guide RNA 2 and the cell line constructed using CRISPR/Cas9 guide RNA 5. Even though, in terms of NAT1 activity the CRISPR 2-19 and CRISPR 5-50, cell lines are highly similar, their metabolic profiles are extremely different. This suggests there may be additional genetic differences between the two cell lines. The observation of a large number of differentially abundant metabolites between each KO cell line compared to the Scrambled cell line and compared to each other could be because the cell lines have undergone additional unique mutations between them and/or because each CRISPR guide RNA used caused unique off-target effects in addition to targeting NAT1. To focus on metabolome differences associated with varying levels of NAT1 in breast cancer, we have focused our interpretation of this study to metabolites that agreed between the two CRISPR NAT1 KO cell lines  only genetically altered a single gene, NAT1, in each cell line, we expected only a small proportion of metabolites to be significantly different, due to the vast homeostasis mechanisms present32, is formed by carboxylating acetyl-CoA and is known to inhibit CPT1. Decreases in the level of a number of acylcarnitine species clearly indicate that the CPT1 step and subsequent mitochondrial metabolism of fatty acids are disturbed in NAT1 KO cells. We hypothesize the increase in acetyl-CoA observed when NAT1 is knocked out may lead to increased malonyl-CoA which inhibits CPT1 resulting in less acylcarnitines. In addition, 3 out of 18 metabolites that are concordantly increased in both KO cell lines belong to 3-hydroxy-fatty acids  , linolenoylcarnitine (C18:3), linoleoylcarnitine (C18:2), and myristoleoylcarnitine (C14:1)  have been reported to catabolize N-acetylasparagine, albeit at a much lower level than the prototypic ASPA substrate N-acetylaspartate49. Additionally, aminoacylase 1 deficiency (ACY1), a rare inborn error of metabolism disease, is diagnosed by increased N-acetylated amino acids in the urine, including N-acetylasparagine50 suggesting ACY1 can also metabolize N-acetylasparagine. Given the abundance distribution of N-acetylasparagine in our constructed cell lines, it is possible that L-asparagine is a substrate N-acetylated by NAT1 to form N-acetylasparagine but confirmation is needed.The strong positive association between the abundance of N-acetylputrescine and NAT1 N-acetylation activity in the 6 MDA-MB-231 cell lines is consistent with N-acetylputrescine as a product of NAT1 N-acetylation. Putrescine is known to be N-acetylated by spermidine/spermine N1-acetyltransferase 1 (SAT1) and spermidine/spermine N1-acetyltransferase 2 (SAT2) but with much lower affinity than for other SAT substrates such as spermidine51. Redundancy in non-homologous metabolic enzymes has been shown to occur53 and it is possible that NAT1 and the SATs may both N-acetylate putrescine.Similarly, the strong positive association between the abundance of 59. Our data indicates cell lines with higher levels of NAT1 activity have increased amounts of N-acetylated asparagine and putrescine while cell lines with decreased and knocked-out NAT1 activity have decreased amounts of N-acetylated asparagine and putrescine. We hypothesize this could lead to decreased asparagine and putrescine in cell lines with high NAT1 and increased asparagine and putrescine in cell lines with decreased and knocked-out levels of NAT1 relative to cell lines with basal NAT1 activity. However, we did not observe this differential distribution in our dataset. It has been shown that intracellular asparagine exchanges with extracellular amino acids to promote mTORC1 activation, protein and nucleotide synthesis and cell proliferation under normal growth (non-starvation) conditions55. Additionally, it has been reported that the invasiveness of a mouse breast cancer model could be modulated either by altering asparagine biosynthetic capacity or by modifying extracellular asparagine pools with decreases in asparagine leading to decreased metastatic burden54. Polyamines, such as putrescine, are known to facilitate the interactions of transcription factors, such as estrogen receptors with their specific response element and are involved in the proliferation of ER negative breast cancer tumor cells (reviewed in60). Additionally, an increase in intracellular polyamine concentrations has been associated with increased cell proliferation and has been linked to tumorigenesis65. Our data, interpreted in light of the results of previous studies, suggests that knockout NAT1 may increase cell growth capabilities due to higher levels of asparagine and putrescine however studies from our lab do not support this20. This may be because there are additional mechanisms in place regulating the amount of free asparagine and putrescine or other factors regulating growth that override an abundance of these metabolites.Both L-asparagine and putrescine have been implicated in the promotion of cell growth67. This observation may be connected to lysine’s role in carnitine biosynthesis33. Pathway analysis indicated pathways that directly involve acetyl-CoA such as the lysine degradation and tryptophan metabolism pathways were enriched for differences (Fig. The strong negative association between the abundance of saccharopine and NAT1 activity in the 6 MDA-MB-231 cell lines suggests saccharopine is a NAT1 substrate or located upstream of a NAT1 catalyzed reaction. Saccharopine is an intermediate in the main pathway responsible for the catabolism of lysineces Fig. . AdditioN-acetylation by NAT1 but further validation is required. These metabolites have recently been implicated in enhanced cell growth and metastatic potential in breast cancer models suggesting they may be the key to understanding how varying levels of NAT1 affect breast cancer progression. Furthermore, metabolites involved in fatty acid metabolism and pyrimidine biosynthesis showed strong concordant changes in both NAT1 KO cell lines suggesting NAT1 may have an essential role in these processes. Moreover, many of the pathways significantly enriched in pathway analysis are pathways where acetyl-CoA plays a role, adding further evidence for the connection between NAT1 and acetyl-CoA in metabolism.Our results support the hypothesis that NAT1 is not just a xenobiotic metabolizing enzyme and may have a role in endogenous cellular metabolism. Whether this is direct or through NAT1’s effect on acetyl-CoA remains unknown. We have shown that NAT1 expression differentially affects cellular metabolism dependent on the level of expression. Additionally, we have identified potential novel substrates and products of Supplementary information.Supplementary information2.


TP53, NOTCH1 and DNMT3 to be mutated in 84.6%, 69.2% and 30.0% of sensitive cell lines, and in 62.5%, 0% and 0% of resistant cell lines, respectively. An immunohistochemistry study showed that p-ERK and RelB were associated as potential biomarkers of tipifarnib sensitivity and resistance, respectively. Data from RNA-seq show that tipifarnib at IC50 after 72 h downregulated a great variety of pathways, including those controlling cell cycle, metabolism, and ribosomal and mitochondrial activity. This study establishes tipifarnib as a potential therapeutic option in T-cell leukemia and TCL. The mutational state of NOTCH1, p-ERK and RelB could serve as potential biomarkers of tipifarnib sensitivity and resistance.Patients diagnosed with T-cell leukemias and T-cell lymphomas (TCLs) still have a poor prognosis and an inadequate response to current therapies, highlighting the need for targeted treatments. We have analyzed the potential therapeutic value of the farnesyltransferase inhibitor, tipifarnib, in 25 TCL cell lines through the identification of genomic and/or immunohistochemical markers of tipifarnib sensitivity. More than half of the cell lines (60%) were considered to be sensitive. Tipifarnib reduced cell viability in these T-cell leukemia and TCL cell lines, induced apoptosis and modified the cell cycle. A mutational study showed  T-cell lymphoproliferative disorders are a very heterogeneous group of lymphoid neoplasms characterized by the clonal expansion of mature T-lymphocytes in bone marrow, blood or other tissues. They include peripheral T- cell lymphoma (PTCL) and T-cell acute lymphoblastic leukemia (T-ALL).1. It comprises a set of disorders that includes peripheral T-cell lymphoma not otherwise specified (PTCL-NOS), angioimmunoblastic T-cell lymphoma (AITL), anaplastic lymphoma kinase (ALK-) positive and ALK-negative forms of anaplastic large cell lymphoma (ALCL), and enteropathy-associated TCL2. Despite the subtypes being very different at the molecular level, their treatment is basically similar, consisting of CHOP  and Etopoxide, or a similar regimen. Therapeutic responses to this treatment show a current general 5-year survival rate of only 10–30% and a rapid progression in some subtypes5.PTCL accounts for about 10% of all non-Hodgkin lymphomas (NHLs)6. These results highlight the urgent need for alternative treatment strategies focusing on molecular characterization of individual cases that could identify potential candidates for targeted therapy.T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy characterized by an accumulation of immature T-cell lymphoblasts in bone marrow and peripheral blood. In contrast with PTCL, clinical progress has clearly improved in T-ALL; the 5-year survival rate is currently 65–70%8. The relatively poor prognosis for PTCL4 is ultimately the consequence of our insufficient knowledge about the molecular pathogenesis of these tumors and the limited availability of therapeutic tools8.The classification of T-cell lymphomas/leukemias is complex and requires the integration of information about clinical, pathological and genetic factors, morphology, immunohistochemistry (IHC), flow cytometry, cytogenetics, and molecular biology13, and, for a given gene, the distributions of the mutations and their relative prevalence are quite variable.Deregulated survival pathways and mutated genes have been partially characterized in PTCL. Genetic alterations affecting TCR signaling operate as a common pathogenic mechanism in several TCL entities. Mutations in genes related to TCR co-stimulation and signaling were recently reported in a range of TCL entities, such as cutaneous T-cell lymphoma (CTCL), PTCL-NOS, AITL and ATLL (adult T-cell lymphoma/leukemia). Nonetheless, mutations in specific genes have a variable frequency in distinct entitiesJAK1, JAK3, PTEN, IL7R and NRAS signaling proteins15. Other common oncogenic lesions are the loss of the CDKN2A (p16) locus and aberrant NOTCH1 signaling18. Activating mutations in JAK1, JAK3 or IL7R lead to activation of the JAK/STAT pathway, resulting in the stimulation of proliferation and survival pathways in the leukemic cells and thereby the development of T-ALL20.The mutational landscape of T-ALL has recently been elucidated too. A variety of somatic mutations was described like, 21. Mutations in RAS family genes induce constitutive activation of RAS-mitogen-activated protein kinase (MAPK), which activates several downstream effectors that play a role regulating a variety of cell functions, including cell growth, survival and differentiation. In view of these findings and the molecular landscape of PTCL and T-ALL, we were prompted to investigate the Ras mutations and MAPK pathway activation further. Farnesyltransferase inhibitors (FTIs) were designed to disrupt Ras farnesylation and the membrane localization necessary for Ras function. This work and other studies have demonstrated activity in neoplasms lacking mutant Ras23, suggesting that it could inhibit farnesylation of multiple proteins, leading to the arrest of proliferation and the induction of apoptosis in a variety of preclinical models25.Aberrant activation of oncogenic Ras signal transduction is a very frequent finding in PTCL and T-ALL27 and leukemia22. A variety of phase II trial has shown that it improves early survival when administered as maintenance therapy in patients in remission28. Administered as a single-agent, tipifarnib can produce antitumor effect in pretreated patients29.Some phase I trials using tipifarnib have demonstrated its antineoplastic effects in solid tumors31 in a panel of 25 TCL and T-ALL cell lines, enabling us to determine the therapeutic value of tipifarnib in these cell lines, and to identify biomarkers that could predict the response to this drug and to measure the dynamic effects on cell viability, apoptosis, cell cycle and gene expression. These observations could facilitate the development of personalized therapy in patients with TCL and T-ALL. The selected panel of 25 cell lines includes cell lines derived from a wide array of T-cell lymphoproliferative disorders, including T-cell acute lymphoblastic leukemia (T-ALL), cutaneous T-cell lymphoma (CTCL), anaplastic large cell lymphoma (ALCL) and adult T-cell lymphoma/leukemia (ATLL).The present study evaluates the effect of inhibiting FTase with tipifarnib50 values. With this classification, we found 60% of cell lines were sensitive to tipifarnib after 96 h , TH2 (IL-4), Th17 (IL-17) and Treg (Foxp3) phenotypes by analyzing changes in the expression of their markers in eight cell lines: MOLT-14, RPMI-8402, SU-DHL-1, L-82, HPB-ALL, HUT-78, JURKAT and HH. Those cytokines that allow the characterization of inflammatory, non-inflammatory and regulatory subpopulations were measured . No phenotypic changes were observed when cells were cultured in the presence of tipifarnib at IC50 and 2x IC50 , the mutational state of NOTCH1, ERK activation , sex and cell subtype. In this case, the magnitude of the change represents a coefficient that increases with the IC50 value  of <0.25 was used33 to generate testable hypotheses. The results suggested that the TCR pathway, G protein-coupled receptor activity and G2/M checkpoints were correlated with highly sensitive cases, while NFkB activation by the TNFα, IFNγ and IFNα response, ribosome and p53 pathway were correlated with resistant cell lines   and RAS-GTPase activating protein (GAP) genes, respectively . The mutational state of the RAS, RAS-GEF and RAS-GAP genes was not associated with drug sensitivity .These results prompted us to focus our analysis on the RAS/MAPK pathway and other T-cell lymphoma pathways, such as TCR, JAK/STAT, NFAT and NFκB. We selected only cell lines with genomic data available from COSMIC or CCLE or generated by our group (Supplementary Table 05) Fig. . 52% andty Figs.  and 4e, To elucidate the consequences of farnesyltransferase inhibition in TCL and T-ALL cell lines, we performed RNA-seq in three highly sensitive cell lines . Differential gene expression was analyzed with and without tipifarnib. We detected 24 differentially expressed (DE) genes common to all three cell lines Fig. .Figure 5. Several of the downregulated genes are involved in the cell cycle: UNG prevents mutagenesis; UHRF1 regulates chromatin structure and gene expression; SSRP1 affects nucleosome disassembly and transcription elongation; MYBL2 influences cell-cycle progression; MCM2 and MCM3 are involved in replication. Other deregulated genes are closely related to enzymatic and mitochondrial activity . The heat shock response genes, HSPD1, HSPA9 and HSP90AB1, are other downregulated genes.Two of these upregulated genes are related to damage response and the prevention of infection by retroviruses 35, are shown in Fig. GSEA was performed under more stringent conditions  at clinically achievable concentrations .Here we report the effectiveness of the farnesyltransferase inhibitor tipifarnib in a panel of 25 TCL and T-ALL cell lines, integrating TP53, NOTCH1 and DNMT3A to be mutated in 84.6%, 69.2% and 30.0% of cells in sensitive cell lines, respectively, in contrast to resistant cell lines, in which the mutational frequencies were much lower   Figs. . The assNOTCH1 and the activation of ERK could serve as potential biomarkers of sensitivity to tipifarnib, and the positivity of RelB (by IHC) could be a biomarker of resistance to the drug. Other studied markers, such as CD30, showed no such significant associations  and three resistant (37.5%) cell lines harbored mutations in RAS genes (not significant (n.s.)); eight sensitive (61%) and three resistant (37.5%) cell lines harbored mutations in RAS-guanine nucleotide exchange factors (GEFs) (n.s.) and five sensitive (38%) and two resistant (25%) cell lines harbored mutations in RAS-GTPase-activating protein (GAP) genes (n.s.). The mutational state of the RAS, RAS-GEF and RAS-GAP genes was not associated with tipifarnib sensitivity. The mutational state of all the RAS-GEF genes was associated with ERK activation and RelB negativity .Given the association between ERK activation and tipifarnib sensitivity, we focused our attention on the RAS/MAPK pathway and other T-cell leukemia/lymphoma-related pathways, such as TCR, JAK/STAT, NFAT and NFκB, which are known to be involved in T-cell leukemia/lymphomaUnder basal conditions, RNAseq analysis of 25 cell lines indicated that the TCR pathway, G protein-coupled receptor activity and G2/M checkpoints were correlated with greater sensitivity to tipifarnib, while NFkB activation by TNFα, IFNγ and IFNα response, ribosome and p53 pathway were correlated with resistance. These results replicate and confirm our previous observations that associated mutational status and pathway activation with tipifarnib sensitivity.To improve our understanding of the biological mechanism of action of tipifarnib, we performed RNA-seq in three of the most sensitive cell lines . We detected more than 300 differentially expressed genes , which is a farnesylated small GTPase, a key protein in the Rheb-Notch-Rheb loop, that positively regulates mTOR signaling49.The mammalian target of rapamycin (mTOR) is another commonly activated pathway in TCL and T-ALLNOTCH1 and the activation of ERK could serve as potential biomarkers of tipifarnib sensitivity, and a high level of RelB expression could be a biomarker of resistance to the drug. These results require validation in clinical samples or PDXs.This study suggests that tipifarnib is a potential therapeutic option in T-cell lymphomas and T-cell acute lymphoblastic leukemia. The results of our study suggest that the mutational state of 8). All cell lines were purchased or authenticated before use and were tested for mycoplasma .We included 25 TCL and T-ALL cell lines representing tumor types such as T-cell acute lymphoblastic leukemia/lymphoma , anaplastic large cell lymphoma , cutaneous T-cell lymphoma , and adult T-cell lymphoblastic leukemia   and cultured with Roswell Park Memorial Institute (RPMI) 1640 Medium (Thermo Fisher Scientific) containing 10% fetal bovine serum (Gibco), except for the MJ cell line, which was cultured with Gibco Iscove’s Modified Dulbecco’s Media (IMDM) medium (Thermo Fisher Scientific) containing 20% fetal bovine serum.BE-13, DND-41, HD-MAR-2, HPB-ALL, HSB-2, JURKAT, KE-37, L-82, MHH-TALL-2, MOLT-14, MOLT-16, P12-ICHIKAWA, PF-382, RPMI-8402, SR-786 and TALL-1 were purchased from the DSMZ German Collection of Microorganisms and Cell Cultures. Except for HSB-2, they were cultured with Roswell Park Memorial Institute (RPMI) 1640 Medium containing different proportions of fetal bovine serum: 10% for DND-41, HD-MAR-2, HPB-ALL, JURKAT, KE-37, L-82, MOLT-14, MOLT-16, P12-ICHIKAWA, PF-382 and RPMI-8402; 20% for BE-13 and MHH-TALL-2; 15% for SR-786 and TALL-1. HSB-2 was cultured with Gibco Iscove’s Modified Dulbecco’s Media (IMDM) medium containing 10% fetal bovine serum.MyLa was purchased from the European Collection of Authenticated Cell Cultures (ECACC) and was cultured with Roswell Park Memorial Institute (RPMI) 1640 Medium containing 10% fetal bovine serum.2 incubators at 37 °C in an atmosphere containing 5% CO2.All cells were cultured in CO50  values were calculated. Tipifarnib was provided by Kura Oncology . Growth curves were derived and IC50 values determined using the Cell Titer-Glo Luminescent Cell Viability Assay from Promega  at 0, 24, 72 and 96 h. IC50 values were calculated with Graphpad Prism v5 .All cell lines were tested for tipifarnib sensitivity in two steps, for which purpose they were cultured in appropriate medium in T96 multi-well plates . Individual optimal cell line seeding densities were determined before deriving growth curves with increasing concentrations of tipifarnib  using DMSO as the vehicle for 96 h. Six replicates of all experiments were carried out, and IC2. Cells were maintained in standard conditions for 24 h, after which they were exposed to IC50 and 2x IC50 values of tipifarnib and DMSO as a vehicle for 96 h. The positive and negative controls for the next analysis were included. To identify dead and apoptotic cells, 100 μL of Annexin Red Working Solution were added to each 100 μL of cell suspension and samples were incubated for 15 min at 37 °C. Samples were washed and resuspended in Assay Buffer HSC and then 5 μL of 7-ADD were added. Samples were incubated at room temperature (RT) for 5 minutes in the dark before analysis by Fluorescence-Activated Cell Sorting (FACS). Double-positive cells (Annexin-V and 7-ADD) were considered in the late apoptotic stage or necrotic cells, whereas cells that were positive for Annexin-V but negative for 7-ADD were those in early-stage apoptosis; in this study, we were interested in these early apoptotic cells. To assess the effects on DNA synthesis, cells were grown in each appropriate medium and, after treatment with tipifarnib, incubated for a further 2 h with EdU (5-ethynyl-2′-deoxyuridine), which is a nucleoside analog of thymidine that is incorporated into the DNA during active DNA synthesis . Immediately afterwards, cells were prepared for cytometry following the manufacturer’s recommendations. To calculate the percentage blockade of tipifarnib in the G0 phase and to prevent these cell lines from entering the G2 phase of replication, the percentage inhibition of tipifarnib with respect to DMSO was measured.Three of the most sensitive cell lines were subjected to apoptosis and cell-cycle analysis. Flow cytometry assays were used for both analyses, using a Flow Cellect Annexin Red Kit  and a Click-iT Plus EdU Alexa Fluor 647 Flow Cytometry Assay Kit , following the manufacturers’ instructions. Cells were seeded in 12-well plates  and incubated for 24 h at 37 °C in a humidified atmosphere of 5% CO8, we obtained genomic data from genomic repositories from T-cell lymphoma/leukemia cell lines. Specifically, we combined genomic data from CCLE , COSMIC Cell Lines Project , EGAS00001000268 , exomes produced previously by our group . Variants were annotated using the Variant Effect Predictor . Known SNPs with an allelic frequency greater than 1% in public databases  were filtered out.As previously described by our groupet al.8, total RNA was extracted using TRIzol reagent (Invitrogen) according to the manufacturer’s protocol. Total RNA was assayed for quantity and quality using the Qubit RNA BR or HS Assay Kit on the Qubit 2.0 Fluorometer (Life Technologies), and the RNA 6000 Nano Assay on a Bioanalyzer 2100 (Agilent). The RNASeq libraries were prepared using TruSeq Stranded mRNA LT Sample Preparation Kit . Briefly, total RNA (500 ng) was enriched for the mRNA fraction and fragmented by divalent metal cations at high temperature . To achieve directionality, the second-strand cDNA synthesis was performed in the presence of dUTP. Mondejar et al.8 described how the blunt-ended double-stranded cDNA was 3′adenylated and Illumina indexed adapters were ligated. The ligation product was enriched over 15 PCR cycles and the final library was validated on an Agilent 2100 Bioanalyzer with the DNA 7500 assay (Agilent). Libraries were sequenced on HiSeq2000  in paired-end mode with a read length of 2 × 76 bp using a TruSeq SBS Kit v4 in a fraction of a sequencing v4 flow cell lane, following the manufacturer’s protocol. Image analysis, base calling and quality scoring of the run were processed using the manufacturer’s Real Time Analysis (RTA 1.18.66.3) software, followed by generation of FASTQ sequence files.As previously described by Mondejar 51 with ENCODE parameters for long RNA. Annotated genes (GENCODE version 27) were quantified using RSEM version 1.3.052 with default parameters. Differential expression was analyzed with limma-voom53 adjusted for sex, cell subtype and 18 other hidden factors detected by surrogate variable analysis (sva). The IC50 was considered as a continuous variable, and only genes with at least 1 cpm in 10 samples or more were selected for the analysis.RNA-seq was performed in 25 cell lines under basal culture conditions. RNA-seq paired-end reads were mapped against the human reference genome (GRCh38) using STAR version 2.5.3a50 and DMSO in three biological replicates. RNA-seq reads were mapped and genes were annotated as described above. Principal component analysis of the ‘rlog’-transformed expression data was done using the top 500 most variable genes with the ‘prcomp’ R function and ‘ggplot2’ R library. Two outlier samples belonging to DMSO_SUDHL1 and TIPI_SUDHL1 were removed. Differential expression was analyzed with DESeq2 version 1.1054 for each cell line separately. Heatmaps with the top 50 differentially expressed genes were generated with the ‘pheatmap’ R package. Gene set enrichment analysis (GSEA) was performed from a background of > 5000 gene sets of the Hallmark collection of the Molecular Signatures Database (MSigDB), curated  and Gene Ontology (GO) gene sets (C5 collection). Expression data have been deposited in the Sequence Read Archive (SRA) under BioProject accession reference PRJNA603759.To further elucidate the consequences of farnesyltransferase inhibition in TCL and T-ALL cell lines, RNA-seq was performed in three cell lines  treated with tipifarnib for 72 h at IC50 of tipifarnib and DMSO in plates of T12 wells . All experiments were done in triplicate.The expression of the markers IL-2, IL-4, IFN-g, IL-17, RORγT and Foxp3 was tested by FACS in eight cell lines , enabling possible changes in the TH1/TH2/Treg/Th17 phenotypes to be studied. Cell lines were incubated for 96 h at 1x and 2x the ICThe chi-square or Fisher exact test were used to determine the significance of associations between the presence or absence of markers and sensitivity. Estimates were considered statistically significant for two-tailed values of p < 0.05. All analyses were carried out using IBM SPSS for Windows version 20 .Supplementary Table Legends.Supplementary Tables.


Restoration of blood flow to ischaemic heart inflicts ischaemia/reperfusion (I/R) injury, which manifests in metabolic and morphological disorders. Klotho is a protein with antioxidative and antiapoptotic activity, and is involved in the regulation of inflammation and fibrosis. The aim of the current research was to determine the role of Klotho in the heart subjected to I/R injury, as well as to study Klotho as a potential cardioprotective agent. Human cardiomyocytes and Wistar rat hearts perfused using Langendorff method subjected to I/R have been used. Hemodynamic parameters of heart function, markers of I/R injury, and gene and protein expression of Klotho were measured. Human cardiomyocytes were also incubated in the presence of recombinant Klotho protein, and the viability of cells was measured. There was a higher expression of Klotho gene and protein synthesis in the cardiomyocytes subjected to I/R injury. The compensatory production and release of Klotho protein from cardiac tissue during I/R were also shown. The treatment of cardiomyocytes subjected to I/R with Klotho protein resulted in increased viability and metabolic activity of cells. Thus, Klotho contributes to compensatory mechanism during I/R, and could be used as a marker of injury and as a potential cardiopreventive/cardioprotective agent. The expression of Klotho gene is observed mainly in the kidneys and brain.The aim of this study was to investigate the role of Klotho protein in the heart tissue subjected to I/R injury, as well as to study Klotho as a potential cardioprotective agent.2In this study, animal tissues obtained from our other project were used. All animal procedures conformed to the Guide to the Care and Use of Experimental Animals published by the Polish Ministry of Science and Higher Education. This investigation was approved by the Ethics Committee for Experiments on Animals at the Ludwik Hirszfeld Institute of Immunology and Experimental Therapy Polish Academy of Sciences, Wroclaw, Poland (Resolution 14/2016 of 20 April 2016).2.12 atmosphere in Dulbecco's Modified Eagle's Medium (Sigma‐Aldrich) containing Cardiac Myocyte Growth Supplement (ScienCell Research Laboratories), 5% foetal bovine serum, 100 U/mL penicillin and 100 μg/mL streptomycin . Cells were passaged at 90% confluence using 0.25% trypsin‐EDTA (Sigma‐Aldrich).The primary human cardiac myocytes (HCM) were purchased from ScienCell Research Laboratories. The cells were cultured at 37°C in a water‐saturated, 5% CO2.22, 5 mmol/L KCl, 2.1 mmol/L MgCl2, 5.5 mmol/L glucose and 10 mmol/L taurine) containing additional 55 μmol/L CaCl2 and 0.75 mg/mL BSA. In an in vitro chemical ischaemia group, cells were incubated in HEPES buffer containing 4.4 mmol/L 2‐deoxyglucose (to inhibit glycolysis) and 4.0 mmol/L sodium cyanide (an inhibitor of cellular respiration).g, the buffer was removed and cells were incubated in aerobic conditions with HEPES buffer for 20 minutes at RT (reperfusion). After reperfusion, the buffer was removed by centrifugation at 1500 g for 5 minutes, and the cell pellet was homogenized. The cells from aerobic control group were incubated aerobically for 50 minutes in HEPES buffer at RT. In the Klotho experimental groups , the cells underwent experimental protocol in the presence of Klotho protein  during whole procedure. Myocytes from aerobic group subjected to Klotho protein were tested to check the cytotoxicity of Klotho.Cardiac myocytes in culture underwent in vitro chemical I/R in accordance with the guidelines for experimental models of myocardial ischaemia and infarction.2.3g for 5 minutes at 4°C and then were transferred into a fresh tube. The homogenates were stored at −80°C for further experiments.Cells underwent three cycles of freezing (in liquid nitrogen) and thawing (at 37°C) in the homogenization buffer . Then, myocytes were homogenized mechanically on ice (three times for 10 seconds) with a hand‐held homogenizer. Supernatants were obtained by centrifugation at 10 000 2.4−ΔCt. 2−ΔCt was equal to the relative transcriptional mRNA level of Klotho gene in cells that were exposed to aerobic conditions and cells subjected to I/R.Total RNA from HCM was isolated with TRIZOL reagent (Thermo Fisher Scientific) according to the manufacturer's instruction. Microultraviolet (UV) spectrophotometer  was used to evaluate the concentration and purity of RNA. Reverse transcription of pure RNA samples (200 ng) was conducted in order to prepare cDNA with iScript cDNA Synthesis Kit (Bio‐Rad) according to the instructions provided. Briefly, the reverse transcription was carried out at 42°C for 30 minutes and inactivated at 85°C for 5 minutes. The expression level of glucose‐6‐phosphate dehydrogenase (G6PD) was used as internal reference for Klotho. To analyse expression of Klotho gene in a ratio to G6PD gene, real‐time quantitative PCR (RT‐qPCR) and CFX96 Real‐Time System (Bio‐Rad) were used. Briefly, the final volume of the reaction mix was 30 μL and included iTag Universal Sybr Green Supermix with ROX (Bio‐Rad), forward and reverse primers , water and cDNA (40 ng). The primers for Klotho were designed by us and synthesized by TIB Molbiol . The sequences of primers 5′–3′ are as follows: Human Klotho F: AGGGTCCTAGGCTGGAATGT and Human Klotho R: CCTCAGGGACACAGGGTTTA. The amount of particular mRNAs relative to G6PD was calculated as 22.5Klotho protein concentration in cell homogenates was measured quantitatively using Sandwich Human Klotho ELISA Kit from Biorbyt (Biorbyt Ltd.), according to manufacturer's instruction. After resetting the blank well, the optical density (OD) (at 450 nm) of each well was measured by Spark multimode microplate reader (Tecan Trading AG). Klotho protein concentration was normalized to total protein concentration in cell homogenates and expressed in pg/μg protein. The concentration of Klotho was compared in cells that were exposed to aerobic conditions and cells subjected to I/R.2.65 cells/well. When the cell confluence reached approximately 90%, myocytes underwent in vitro chemical I/R injury in the cell culture plate  for 15 minutes in the dark and rinsed with PBS. ZOE Fluorescent Cell Imager (Bio‐Rad) was used to estimate the bright green fluorescence for Klotho and blue fluorescence for DAPI. Image J 1.52a software (NIH) was used to analyse the area of fluorescence of each image. The number of cells was assessed by measuring the fluorescence of cells’ nuclei stained by DAPI (blue fluorescence). The cell surface expression of Klotho was assessed by measuring the green fluorescence of fixed cells stained with anti‐Klotho antibodies and normalized to the number of cells (blue fluorescence). Data were collected from three independent images trials for each experiment and shown as AU. The cell surface expression of Klotho was compared in cells that were exposed to aerobic conditions and cells subjected to I/R.The cells were cultured in 24‐well cell culture plate (Greiner Bio‐One GmbH) at a density of 1 × 102.74 cells/well for 24 hours and then subjected to in vitro chemical I/R injury in the presence and absence of 1 µg/mL Klotho protein  was performed.2.84 cells/well for 24 hours and then subjected to in vitro chemical I/R injury in the presence and absence of 1 µg/mL Klotho protein  and the vital exclusion dye DAPI.2.92PO4, 1.2 mmol/L MgSO4, 3.0 mmol/L CaCl2, 25 mmol/L NaHCO3, 11 mmol/L glucose and 0.5 mmol/L EDTA, pH 7.4. Spontaneously beating isolated hearts were cannulated by the aorta on a Langendorf system (EMKA Technologies) and perfused at a constant pressure of 60 mm Hg with Krebs‐Henseleit Buffer at pH 7.4, at 37°C and gassed continuously with 5% CO2/95% O2. After stabilization, the hearts were subjected to protocol of global I/R injury. As haemodynamic end‐points of cardioprotection,To determine the expression of Klotho protein at the tissue level, isolated rat heart model was used. Ten‐ to 11‐week‐old male Wistar rats (250‐350 g) were treated with buprenorfin  and anaesthetized with sodium pentobarbital (0.5 mL/kg i.p.). The hearts were rapidly excised from animals and rinsed by immersion in ice‐cold Krebs‐Henseleit Buffer containing 118 mmol/L NaCl, 4.7 mmol/L KCl, 1.2 mmol/L KH2.10Hearts in I/R group were subjected to aerobic perfusion for 25 minutes. After oxygenation, the heart perfusion was stopped (by cessation of the buffer flow) and hearts underwent global no‐flow ischaemia for 22 minutes.2.11g at 4°C for 15 minutes, and the supernatant was collected and stored at − 80°C for further experiments.Hearts previously frozen at −80°C were crushed using a mortar and pestle in liquid nitrogen and then homogenized in ice‐cold homogenization buffer containing: 50 mmol/L Tris‐HCl (pH 7.4), 3.1 mmol/L sucrose, 1 mmol/L dithiothreitol, 10 mg/mL, leupeptin, 10 mg/mL soybean trypsin inhibitor, 2 mg/mL aprotinin and 0.1% Triton X‐100. The homogenate was centrifuged at 10 0002.12The expression of Klotho protein in the rat heart tissue was determined qualitatively by immunoblot and quantitatively by ELISA test in aerobic control and I/R groups. The content of Klotho protein in coronary effluents was determined by immunoblot. In the Western blot analysis, an aliquot of 20 μg of total proteins from heart homogenates and an aliquot of 40 μL of coronary effluents were separated on 10% SDS‐PAGE and then transferred onto nitrocellulose membrane (Bio‐Rad), which were then blocked with 5% BSA. Klotho protein was detected with rabbit anti‐Klotho polyclonal antibody 1:1000  and secondary goat anti‐rabbit IgG horseradish peroxidase conjugate antibody 1:5000 . The membranes were developed with the ClarityTM Western ECL substrate (Bio‐Rad) using the ChemiDocTM MP System. Target protein bands in coronary effluents were quantified using Quantity One Software (Bio‐Rad). 120‐130 kDa Recombinant Human Klotho  and 65‐70 kDa Recombinant Human Klotho  were used as positive controls. The content of Klotho protein in coronary effluents was expressed as AU and normalized to CF. For quantitative evaluation of Klotho protein in the heart tissue, Rat Klotho ELISA Kit (Cusabio Technology LLC) was used according to manufacturer's instruction. Each sample was assayed in duplicate. Klotho protein concentration was normalized to total protein concentration in tissue homogenates and expressed in pg/μg protein. The level of Klotho was compared in hearts that were exposed to aerobic conditions and hearts subjected to I/R.2.13To determine the activity of LDH in coronary effluents, Lactate Dehydrogenase Activity Assay Kit (Sigma‐Aldrich) according to manufacturer's instruction was used. LDH is a stable cytosolic enzyme that is released upon membrane damage/permeability or cell lysis and serves as a marker of cell damage. LDH level was normalized to CF and compared in coronary effluents of hearts that were exposed to aerobic conditions and hearts subjected to I/R.2.14To assess an influence of I/R injury on isolated rat hearts, the number of death cells using the CytoTox‐Glo™ Cytotoxicity Assay (Promega) according to manufacturer's instruction was tested. The measurement of extracellular activity of dead‐cell protease was performed in coronary effluents and normalized to CF. The number of death cells was compared in hearts that were exposed to aerobic conditions and hearts subjected to I/R.2.15Bradford method was used to determine protein concentration in the cardiac tissue and cell homogenates. BSA  served as the protein standard. For measuring total protein concentration, Bio‐Rad Protein Assay Dye Reagent (Bio‐Rad) and Spark multimode microplate reader (Tecan Trading AG) were used.2.16t test or Mann‐Whitney U test was used for comparison between two groups of measurement data. ANOVA or non‐parametric test with post hoc tests for multiple groups was used. Correlations were assessed using Pearson's or Spearman's test, as appropriate. Results were expressed as mean ± SEM, and a value of P < .05 was regarded as statistically significant.Experimental data were analysed using GraphPad Prism 6 software (GraphPad Software). Shapiro‐Wilk normality test or Kolmogorov‐Smirnov test was used to assess normality of variances changes. The Student's 33.1The analysis showed significantly higher expression of Klotho mRNA in myocytes subjected to I/R in comparison with aerobic control group Figure . Then, w3.2Cardiac mechanical function was decreased in hearts subjected to I/R in comparison with aerobically perfused hearts, showing increased heart injury Table . The rel3.3P < .05, r = −.7) and positively correlated with LDH level   Figure .3.4To check the potential cardioprotective effect of Klotho protein, HCM were subjected to I/R in the presence and absence of Klotho protein. The treatment of cardiomyocytes with recombinant human Klotho (1 µg/mL) resulted in increased viability of cells during I/R. To check the toxicity of Klotho protein on cardiomyocytes, cells from aerobic control group were incubated with Klotho. Supplementation of recombinant Klotho protein decreased the number of dead cells in I/R group in comparison with I/R group without Klotho addition and did not show toxicity in aerobic control group Figure .3.5To explore an impact of Klotho on the metabolic activity of cardiomyocytes, the vital inclusion dye FDA and the vital exclusion dye DAPI were used. Cells that stained with FDA and excluded DAPI were considered viable, whereas cells that excluded FDA and stained with DAPI were considered necrotic. I/R injury led to decreased metabolic activity of the cardiomyocytes. The treatment with Klotho protein (1 µg/mL) significantly increased metabolic activity of the cardiomyocytes that underwent I/R in comparison with Klotho untreated I/R group Figure .4As the discovery of Klotho, a significant amount of efforts has been devoted to characterize its protective role in oxidative stress, inflammation, fibrosis and apoptosis.There are 3 types of Klotho protein: membrane‐bound (135 kDa), shed and secreted. It is known that membrane proteases cut membrane‐bound Klotho to generate shed types of Klotho: full‐length 130 kDa molecule (the major product of shedding) and a fragment of molecular mass of about 68 kDa. The alternative transcriptional termination of Klotho gene leads to production of secreted Klotho (about 65 kDa). Soluble types of Klotho protein (shed and secreted) are found in the blood, urine and cerebrospinal fluid.A large number of studies over last decade have greatly enriched our knowledge of correlation between Klotho deficiency and risk of CVD.In our study, we showed that Klotho protein was intensively released from cardiac tissue subjected to ischaemic damage. Thus, we propose that enhanced expression of Klotho, its further release from cardiomyocytes into extracellular space and increased level in the body fluids may be useful as a marker of ischaemic heart injury. This hypothesis can be supported by the evidence of increased serum Klotho level in patients after heart failure.Research from the last few years showed protective effect of Klotho overexpression or administration during ischaemic injury of the brain and kidneys.5Our research showed that: (a) there is an increased compensative production of Klotho protein in the cardiomyocytes during I/R to protect ischaemic heart from further injury; (b) an enhanced production of Klotho during I/R and its release to extracellular space can be used as a marker of heart damage; and (c) Klotho administration protects the cardiomyocytes against I/R injury and improves their metabolism after ischaemic damage.In conclusion, this study confirmed the potential cardioprotective role of Klotho in the development of I/R injury. We propose that administration of Klotho protein into hearts may prevent the cardiomyocytes from the damage or reduce the area of injury. We strongly suggest that Klotho protein can be valuable both as a marker of injury and as a potential cardioprotective agent and contributes to compensatory mechanism which mitigates the initial damage under cardiac stress.We are also aware that further studies on the role of exogenous Klotho on cardioprotection on in vivo model are needed. So the next goal of our study is to check whether administration of Klotho before I/R or during I/R will be cardioprotective, and how this cardioprotection is induced.The authors confirm that there are no conflicts of interest.All authors participated in the design, interpretation of the studies, analysis of the data and review of the manuscript; AO, AKZ and IBL designed the research study; AO, AKZ, MB and IBL performed the research; AO and IBL analysed the data; AO wrote the paper; IBL made critical revision of the manuscript.


EZH2 and other members of the polycomb repressive complex and EZH2 inhibition in RMC tumor spheroids resulted in decreased viability. High throughput drug screening of both cell lines revealed several additional candidate compounds, including bortezomib that had both in vitro and in vivo antitumor activity. The activity of bortezomib was shown to be partially dependent on increased oxidative stress as addition of the N‐acetyl cysteine antioxidant reduced the effect on cell proliferation. Combining bortezomib and cisplatin further decreased cell viability both in vitro and in vivo that single agent bortezomib treatment. The UOK353 and UOK360 cell lines represent novel preclinical models for the development of effective forms of therapy for RMC patients.Renal medullary carcinoma (RMC) is a rare, aggressive disease that predominantly afflicts individuals of African or Mediterranean descent with sickle cell trait. RMC comprises 1% of all renal cell carcinoma diagnoses with a median overall survival of 13 months. Patients are typically young (median age—22) and male  and tumors are characterized by complete loss of expression of the SMARCB1 tumor suppressor protein. Due to the low incidence of RMC and the disease's aggressiveness, treatment decisions are often based on case reports. Thus, it is critical to develop preclinical models of RMC to better understand the pathogenesis of this disease and to identify effective forms of therapy. Two novel cell line models, UOK353 and UOK360, were derived from primary RMCs that both demonstrated the characteristic SMARCB1 loss. Both cell lines overexpressed  RCC consists of several distinct subtypes that vary in incidence and demonstrate associations with specific histologic, genetic, and clinical features. Renal medullary carcinoma (RMC) is a rare and aggressive subtype of RCC that predominantly afflicts individuals of African or Mediterranean decent with sickle cell trait.SMARCB1 in chromosome band 22q11.23, is a core subunit of the SWI/SNF chromatin remodeling complex. Loss destabilizes the complex and disrupts its equilibrium with the polycomb repressive complex 2 (PRC2) resulting in dysregulation of transcription activity.SMARCB1 gene.SMARCB1 mutant MRT mouse xenograft models have shown complete responses.A central feature of RMC is loss of expression of the SWI/SNF‐related matrix‐associated actin‐dependent regulator of chromatin subfamily B member 1 (SMARCB1) protein, also known as integrase interactor 1 (INI1), BRG1‐associated factor 47 (BAF47), or sucrose non‐fermenting 5 (SNF5).SMARCB1 loss and (2) high throughput drug screening. Both cell lines produced tumor xenografts in nude mice, with UOK360 more rapidly, providing models for both in vitro and in vivo analysis of potential therapeutic targets.We endeavored to establish new RMC cell lines in hopes of elucidating their biology and defining effective treatments. Herein we report the development of two patient tumor‐derived cell lines, UOK353 and UOK360, that resulted from spontaneous transformation and represent models for RMC. These cell lines allow the adoption of a two‐pronged approach to identification of potential therapeutics using (1) a targeted approach focused on exploiting 22.1Patients were evaluated and managed at the Hatfield Clinical Research Center, National Institutes of Health (NIH). Tumor tissues were obtained from biopsy or surgical resection and used for cell line production. Peripheral blood and tumor samples were obtained for DNA extraction. All patients signed the Urologic Oncology Branch protocol, NCI‐97‐C‐0147 that has been approved by the Institutional Review Board of the National Cancer Institute and that includes the production and use of cell line models. Informed consent was acquired only after the patient had fully understood what might be done with samples obtained from them and the implications of our research.2.2d‐glucose) DMEM medium supplemented with 10% fetal calf serum and 2 mM l‐glutamine. Short tandem repeat (STR)‐based DNA‐profiling was performed on the cell lines and the matched peripheral blood DNA to confirm the origins of both cell lines.Surgically resected tumor tissue from one patient and a tumor biopsy from a second patient were utilized to establish two cell lines, UOK353 and UOK360, in accordance with protocols and techniques previously described by the Urologic Oncology Branch.2.3FISH and SKY were performed on both UOK353 and UOK360, on interphase and metaphase spreads, respectively. Interphase cells were hybridized with a SMARCB1 break apart probe . Images were imaged on ×63 objective using a Leica Thunder Imager . Metaphase spreads (n = 25) were scored for chromosomal copy number and for structural aberrations as previously described.2.4SMARCB1 and TP53 genes identified by the OncoVar v.4 assay were validated by an orthogonal sequencing methodology to validate the accuracy of the mutation calling. Sanger sequencing was performed on PCR products generated using a Qiagen Taq PCR Core Kit  that were bidirectionally sequenced using the BigDye Terminator v.1.1 Cycle Sequencing Kit , in accordance with manufacturer's protocols. Sequence reactions were cleaned with Performa DTR Plates  and capillary electrophoresis was performed on an ABI 3730/ABI 3130xl Genetic Analyzer automated sequencing machine (Applied Biosystems). Sanger Sequencing was conducted at the CCR Genomics Core, NCI. Forward and reverse sequences were evaluated using Sequencher 5.4.6 .DNA was extracted from cell pellets, tumors, and peripheral blood leucocytes using a Promega Maxwell 16 Cell, Tissue, or Blood DNA Purification Kit . The UOK353 and UOK360 cell line DNAs were assessed using the OncoVar v.4 assay provided by Genetics Branch, National Cancer Institute (NCI). The assay performs hybrid capture sequencing analysis for genomic variants on a panel of cancer‐related genes, including the known kidney cancer associated genes.2.5SMARCB1 (Hs00992521_m1), SMARCA4 (Hs00946396_m1), and PBRM1 (Hs00217778_m1), components of the PRC2 complex—EZH2 (Hs01016789_m1), SUZ12 (Hs00248742_m1), and EED (Hs00537777_m1), and downstream expression markers of activation of the NRF2‐antioxidant response element (ARE) signaling pathway—NQO1 (Hs00168547_m1), HMOX1 (Hs01110250_m1), SQSTM1 (p62) (Hs01061917_g1), GCLC (Hs00155249_m1), and GCLM (Hs00978072_m1).Total RNA was extracted from cell lines grown in 10 cm dishes using Direct‐zol Miniprep , following a standard protocol. Cell lines were grown to a confluency of approximately 80%‐90%, washed with 5 mL of sterile PBS and lysed using 1 mL of Trizol reagent. Following the standard RNA extraction protocol, the RNA was resuspended in 50 μL of RNase‐free water and the RNA concentration was measured using a NanoDrop 2000 UV‐Vis Spectrophotometer (Thermo Fisher Scientific). For each cell line, cDNA was synthesized from 1 μg of total mRNA using the SuperScript VILO cDNA Synthesis Kit (Thermo Fisher Scientific) in a 20 μL volume. The cDNAs were diluted 10‐fold with 180 μL of RNase‐free water and 2 μL was used in 10 μL reaction volume for RT‐PCR amplification using an ABI ViiA7 real‐time PCR system (Thermo Fisher Scientific). Expression levels were normalized to the control 18S housekeeping gene (Hs99999901_s1) and calculated using the ViiA7 software as comparative CT (ΔΔCT) values. The non‐immortalized normal kidney cell line HRCE was designated to represent the normal expression level with a value of 1. TaqMan Gene Expression Assays (Thermo Fisher Scientific) were used to assess the expression levels of several genes, including components of the SWI/SNF complex—2.62PO4, 10 mM Tris pH 8, 0.1% mercaptoethanol). Protein concentration was quantified by the Bio‐Rad protein assay . Proteins (20 μg) were separated by electrophoresis on NuPage 4%‐20% Bis‐Tris gels  and transferred onto Immobilon‐P membranes  according to the manufacturers' directions. Western blot analyses of proteins were carried out by using anti‐Ku80 (C48E7) , anti‐BAF180 (ABE70) (Millipore Sigma), anti‐BRG1/SMARCA4 (SC‐17796) , anti‐BAF57/SMARCE1 (A300‐810A) , anti‐SNF5/ SMARCB1 (612111) , anti‐EZH2 (ab3748) , anti‐SUZ12 (ab126577) (Abcam), and anti‐EED (ab4469) (Abcam). The primary antibodies were detected using fluorescently labeled anti‐mouse and anti‐rabbit secondary antibodies at a dilution of 1:10 000 and obtained from Li‐Cor and were visualized by scanning the blots on a Li‐Cor Odyssey (Thermo Fisher Scientific).Sub‐confluent cells were trypsinized and washed once in PBS. Total proteins were extracted by solubilizing the cell pellets in urea buffer  at 48 hours posttreatment. The Cell Titer Glo assay was conducted according to the manufacturer's instructions.2.82 until formation was confirmed by eye under a microscope. UOK353 did not produce usably spheroids, only loose aggregates, and where not analyzed. However, UOK360 cells produced tight spheroids and these were evaluated with the positive control SMARCB1‐deficient MRT cell line G401. After spheroids had been determined to have formed, drugs were added at ×2 concentration to reach ×1. All drugs were incubated for 48 hours and evaluated using Cell Titer Glo3D. For GSK126, every 3‐4 days 100 μL of the 200 μL of media in each well was removed and replaced with 100 μL fresh media containing ×2 the desired drug concentration. Cell Titer Glo 3D assay was conducted according to the manufacturer's instructions.Cell lines were evaluated using several EZH2 inhibitors, GSK126, EPZ6438, and JQEZ5, but these agents require an extended time period to be effectively evaluated that is not compatible with 2D in vitro assays in these fast‐growing cell lines, so 3D spheroid viability assays were utilized.2.9Samples were treated with equimolar concentration of the indicated compounds and viability as determined by Cell Titer Glo was utilized as the endpoint. The combination index calculation was performed using CompuSyn software .2.106 UOK353 or 1‐3 × 106 UOK360 cells were suspended in a 0.2 mL mixture of 50% PBS and 50% Matrigel Matrix  and subcutaneously injected into 10 NCI Athymic NCr‐nu/nu mice (obtained from Charles River Frederick Research Model Facility) to evaluate the tumorigenic potential of these cell lines. 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 5 × 102.11Quantitative high throughput screening (qHTS) was conducted with the assistance of the National Center for Advancing Translational Sciences, NIH. Five hundred UOK353 or UOK360 cells were plated into white, solid‐bottom, 1536‐well tissue culture treated plates using a Multidrop Combi cassette dispenser. The cells were then treated with the compounds of the MIPE library. Viability was assessed using Cell Titer‐Glo assay (Promega) 48 hours posttreatment and luminescence was measured on a ViewLux plate reader .2.12Invasion assays were performed using the xCELLigence system as previously described2.13CellROX® green reagent is a cell‐permeant dye used for measuring oxidative stress in live cells (Thermo Fisher Scientific Inc.). The probe is weakly fluorescent while in a reduced state and exhibits bright green photostable fluorescence upon oxidation by ROS. Cells were evaluated at 48 hours posttreatment.33.1UOK353 was derived from a 42‐year‐old female, African‐American patient with sickle‐cell trait who initially presented with flank pain and was found to have a 4.1 cm right kidney mass and bulky retroperitoneal lymphadenopathy Figure . The patProcured tissue from the surgery‐resected primary renal tumor of the first patient and biopsy tissue from the second patient was used to derive two new, spontaneously immortal cell lines (grown for more than 20 passages), UOK353 and UOK360 respectively.3.2SMARCB1 gene (22q11.23) and FISH analysis using SMARCB1 break apart probes demonstrated that the break occurred within the SMARCB1 gene resulting in loss of activity  immunohistochemistry staining was observed in both patient tumors. The mechanisms of this loss were investigated with spectral karyotypic (SKY) and genomic analysis. SKY analysis of UOK353 revealed that the modal number of chromosomes was hypodiploid, with consistent loss of one copy of chromosomes 4, 9, and 15 Figure . Transloy Figure . The FISSMARCB1   at a known cancer mutation hotspot  Figure . In addit Figure .3.3SMARCB1 gene mRNA expression, relative to primary renal proximal tubule epithelial cells (RPTEC), and no detectable levels of SMARCB1/SNF5 protein by western blot analysis  have shown that the loss of SWI/SNF complex subunits, such as SMARCB1/SNF5, result in an up‐regulation and dependency upon an opposing chromatin remodeling complex, the polycomb repressive complex 2 (PRC2).s Figure . Howevers Figure ,B. Conves Figure . Due to 3.4In collaboration with the National Center for Advancing Translational Science (NCATS), a high throughput drug screen utilizing a library of FDA approved drugs and compounds currently undergoing clinical trials was performed on UOK353 and UOK360 cells in 2D culture. These screens identified several candidate drugs that were effective in both cell lines, including the toll‐like receptor 7/8/9 antagonist CPG‐52364, the neurokinin 3 receptor antagonist osanetant, and the histone deacetylase (HDAC) inhibitor panobinostat that were selected for confirmation Figure . Further3.5NQO1, HMOX1, SQSTM1, GCLC, and GCLM. Notably, both cell lines demonstrated extremely low basal expression levels for NQO1 and reduced expression of HMOX1, while other members of the NRF2‐ARE signaling pathway demonstrated expression comparable to RPTEC cells  when the tumor sizes were compared to vehicle after 21 days of treatment  with an improved suppression of the tumor growth rate compared to single agent treatment, but tumors were not eliminated  injection twice weekly with either 0.9% saline vehicle (n = 8), 1 mg/kg bortezomib (n = 7), 5 mg/kg cisplatin (n = 7), or a combination of bortezomib and cisplatin (n = 7) and followed for 21 days. Single agent treatment with bortezomib demonstrated little effect and with cisplatin slowed the rate of xenograft proliferation that reached statistical significance , having sickle cell trait, and presenting with metastatic disease disseminating from RMC tumors that demonstrated loss of SMARCB1 (SNF5/INI‐1) staining.These lines therefore provide the opportunity to identify new potential treatments for RMC by investigating potential targeted therapies or utilizing high throughput drug screens. Previous studies of malignant rhabdoid tumors (MRTs) with SMARCB1/SNF5 loss had shown that those tumors upregulate expression the PRC2 complex, containing the essential subunit EZH2, and develop a significant sensitivity EZH2 inhibitors such as EPZ‐6438 (tazemetostat).While the efficacy of EZH2 inhibitors in RMC is still unknown, several small‐scale studies have demonstrated a response with bortezomib or platinum‐based combination chemotherapies, such as MVAC .This study also identified a response in these cell line models to panobinostat, an HDAC inhibitor, that could affect the gene expression dysregulation resulting from loss of SMARCB1/SNF5. Panobinostat inhibited proliferation and may represent a potential component of a combination therapy rather than a single agent treatment but highlights the potential for using preclinical models for drug discovery.In summary, UOK353 and UOK360 represent two novel human cell line models for RMC and the first in vivo mouse xenograft models of RMC. These models will provide an invaluable tool for research and preclinical drug testing. Initial analysis of these models confirmed the potential for combination therapy of bortezomib and cisplatin in RMC and highlighted other potential therapeutic options for patients with advanced renal medullary carcinoma.The authors declare no conflicts of interest.Data S1: Supporting InformationClick here for additional data file.