Abstract FNC, 2'-deoxy-2'-β-fluoro-4'-azidocytidine, is a novel cytidine analogue, that has shown strong antiproliferative activity in human lymphoma, lung adenocarcinoma and acute myeloid leukemia. In this study, we investigated the effects of FNC on mantle cell [40]lymphoma (MCL) and the underlying mechanisms. In in vitro experiments, cell viability was detected by the CCK8 assay, and cell cycle progression and apoptosis were assessed by flow cytometry, and the expression of relative apoptosis proteins were detected by Western Blot. The in vivo antitumor effect of FNC was investigated in a SCID xenograft model. Finally, the mechanisms of action of FNC were assessed using a whole human genome expression profile chip. The data showed that FNC inhibited cell growth in a dose- and time-dependent manner, and FNC could induce apoptosis by the death recepter pathways in JeKo-1 cells and arrest the cell cycle in the G1/S or G2/M phase. Notably, FNC showed in vivo efficacy in mice bearing JeKo-1 xenograft tumors. Gene expression profile analysis revealed that the differentially expressed genes were mainly focused on the immune system process, cellular process and death. These findings implied that FNC may be a valuable therapeutic in mantle cell [41]lymphoma and provided an experimental basis for the early clinical application of FNC. Introduction Mantle cell lymphoma (MCL), a B-cell neoplasm, constitutes 6% of the total non-Hodgkin lymphoma (NHL) population[[42]1]. Presently, MCL is a very dangerous disease clinically because it possesses characteristics of both indolent and aggressive lymphomas, and has a more aggressive disease course[[43]2]. The genetic hallmark of MCL is the chromosomal translocation t(11; 14) (q13; q32), which leads to the overexpression of the cell cycle regulatory protein cyclin D1[[44]3]. Despite this common genetic lesion, the clinical behavior and biology of mantle cell lymphoma are highly variable[[45]4]. MCL is responsive to various initial therapies, but relatively short-term remissions are achieved with conventional chemotherapy regimens. Virtually all patients are destined to relapse, and it remains an incurable disease with a rather short median survival of 3–5 years[[46]5–[47]7]. Both high-dose chemotherapy and stem cell transplant cannot change its natural processes. Currently, there is no curative therapy available for refractory MCL[[48]8]. Although using combination regimens has proven to be effective clinically, the development of chemoresistance and side effects in tumor cells is the main obstacle to treatment success. Therefore, there is an urgent need to develop new and more effective anticancer medications for MCL. Cytotoxic nucleoside analogs were among the first chemotherapeutic agents used in cancer treatment[[49]9]. Nucleoside analogs, including purine and pyrimidine nucleoside derivatives, such as cytarabine, gemcitabine and fludarabine, have been widely used for the treatment of tumors and malignant blood diseases[[50]10–[51]12]. Because of similar chemical construction to normal metabolic nucleotides, this family of compounds behaves as antimetabolites, compete with the cellular endogenous deoxynucleotides and interact with many intracellular targets to induce cytotoxicity[[52]13]. Nucleoside drugs can exert cytotoxic activity by incorporation into and altering the DNA and RNA macromolecules themselves, eventually modifying the metabolism of physiological nucleosides[[53]14]. Better understanding of the molecular mechanisms of the anticancer nucleoside activity may uncover more therapeutic strategies and improve their antitumor efficacy. FNC, 2'-deoxy-2'-beta-fluoro-4'-azidocytidine, is a novel pyrimidine analog. Presently, a patent application has been submitted for FNC as an invention (patent number: ZL201010506595.X). Previous research has demonstrated that FNC has a significant inhibitory effect on the proliferation of several non-Hodgkin's lymphoma (NHL) cell lines. Similar effects were also seen in various human cancer cell lines, such as lung adenocarcinoma and acute myeloid leukemia[[54]15]. Furthermore, FNC could remarkably inhibit the adhesion, migration and invasion of Raji and JeKo-1 cell lines[[55]16]. Based on our previous work, the mantle cell lymphoma cell line JeKo-1 was chosen to further study the effects of FNC on the proliferation of MCL and its molecular mechanism, providing an experimental basis for the early clinical application of FNC. Materials and methods Cells and reagents The MCL JeKo-1 cell line was purchased from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). The cells were grown in RPMI-1640 medium supplemented with 20% fetal bovine serum and penicillin (100 U/ml)/streptomycin (100μg/ml) at 37°C with 5% CO[2]. The FNC was provided by Professor Junbiao Chang (Zhengzhou University, Zhengzhou, China), and the cytarabine hydrochloride for injection was commercially available (Ara-C; Sinopharm A-Think Pharmaceuticals co., Ltd, China). For in vitro experiments, FNC and Ara-C were dissolved in sterile phosphate-buffered saline (PBS) as a stock solution and then were diluted with culture medium to the desired concentration. For in vivo experiments, FNC and Ara-C were dissolved in 0.9% sodium chloride. Cell proliferation analysis Cell viability was determined using the Cell Counting kit-8 (Dojindo Company, Japan)[[56]17]. Briefly, 2×10^4 JeKo-1 cells were incubated in a 96-well plate in the absence or presence of various concentrations of FNC and Ara-C. After treatment for the indicated times (24, 48, and 72 h), 20 μL of CCK-8 reagent was added to each well, and the plate was incubated at 37°C for 3 h. The number of cells was measured with a microplate reader at a test wavelength of 450 nm. Each experiment was performed in triplicate and was repeated at least three times. Cell cycle analysis The cell cycle distribution was analyzed by flow cytometry using a cell cycle kit purchased from Br-green Biotechnology (Hubei, China). Exponentially growing JeKo-1 cells (5×10^5 cells/ml) were treated with different concentrations of FNC (0.0–1.0 μM) for 48 h and then were collected and washed with PBS buffer, fixed in ice-cold ethanol (100%) to a final concentration of 70% and incubated at 4°C overnight. The fixed cells were washed with PBS and incubated with 100 μl of RNase A for 30 min at 37°C, and then 400 μl of propidium iodide (PI) solution was added to the suspension. After staining with PI for 30 min in the dark at room temperature, the samples were analyzed using a Becton Dickson flow cytometer, and the cell cycle profile was analyzed by ModFit LT software (Verity Software House, Topsham, ME, USA). Each assay was repeated three times. Apoptosis analysis The Annexin V-FITC apoptosis detection kit (Keygenbio, Nanjing, China) was used to detect the fraction of apoptotic JeKo-1 cells. Briefly, 5×10^5 cells per well were exposed to various concentrations of FNC (0, 0.0625, 0.125, 0.25 and 1μM) and were incubated for 48 h. The treated cells were harvested and rinsed with PBS, and then were resuspended in 500 μL of Binding Buffer, followed by the addition of 5 μl of Annexin V-FITC and 5 μL of propidium iodide. After incubation for 15 min at room temperature in the dark, the samples were analyzed by flow cytometry (BD FACS Calibur). Each assay was repeated three times. Western blot analysis Jeko-1 cells were lysed with RIPA cell lysis buffer that contained 1% protease inhibitor cocktail. Total proteins were extracted and separated by 8%-15% SDS-PAGE, and transferred on a poly vinylidene fluoride (PVDF) membrane. The membranes were blocked in 5% skim milk for 1h at room temperature, and then probed with the appropriate primary antibodies at 4°C overnight. After washing in TBST (3×10 min), membranes were incubated with horseradish-peroxidase-conjugated secondary antibody at 37°C for 2h. Then the membrane preparations were washed three times as above. Protein bands were detected with the ECL chemiluminescence Kit. Blots were stripped and photographed and the signal intensity of each band was determined using Image J software. In vivo tumor xenograft model SCID mice inoculated with JeKo-1 cells were used for the evaluation of the function FNC in MCL. Our study was approved by the Animal Ethics Committee of Zhengzhou University. All animals were treated according to the procedures outlined in the Guide for the Care and Use of Laboratory Animals (P. R. China), and all efforts were made to minimize suffering to animals Fifty male SPF-SCID/Beige mice (5–6 weeks old; weighing 18–20 g) (Vital River Laboratory, Beijing, China), were maintained in a specific pathogen free (SPF) environment with a 12 h light/dark cycle at 20−25°C with a relative humidity of 40−70% and received sterilized food and water freely available. The mice were irradiated by X-ray before the inoculation experiment. Next, 200 μL of the tumor cell suspension containing 2×10^7 cells was injected subcutaneously into the right subaxillary region of SCID mice. Fifteen days later, the average tumor volume reached 200 mm^3. The tumor-bearing mice were then randomly divided into five groups, and each group had ten mice: negative control group (0.9% sodium chloride injection), positive control group (cytarabine, 36 mg/kg), and low-dose (1 mg/kg), medium-dose (2 mg/kg) and high–dose (3 mg/kg) FNC groups. After treatment started, the general condition, change in tumor growth and weight of the SCID mice were observed every other day, and tumor size was measured using a Vernier caliper. Tumor volumes were calculated as described, V (mm^3) = length (mm) × (width (mm))^2 × 0.5. The mice were injected with drugs via the caudal vein at the same time every day. All injections were performed using sterile technique with efforts made to minimize trauma to the animals. After 8 days of treatment, the mice were weighed and euthanized using CO2 inhalation. The tumors were harvested and weighed, and the tumor growth inhibitory rate was calculated. The tumor inhibition rate (TIR%) in the treated versus control mice was expressed as follows: TIR% = (mean tumor weight of the control group—mean tumor weight of the treated group)/(mean tumor weight of the control group)×100%. All of the tumor tissue samples were immediately snap-frozen in liquid nitrogen. The liver and kidney of animals were collected and fixed in 4% buffered paraformaldehyde and paraffin-embedded for hematoxylin and eosin (HE) staining. Gene expression profiling Total RNA extracted from xenograft tumor tissues of the 3 mg/kg FNC and negative control groups were subjected to gene expression profile analysis. Each group has three biological repetitions. The microarray assay was conducted by Shanghai Bio Corporation (Shanghai, China). The expression profiling of all of the samples was tested using the Agilent Whole Human Genome Oligo Microarray (4×44K; Agilent Technologies, Palo Alto, CA), which represents >41,000 human genes and transcripts. After applying the SAS platform online analysis system to analyze the chip results, genes with more than 2-fold changes in the expression level were selected for further analysis. Semi-quantitative RT-PCR Semi-quantitative determination of E2F1,CDKN1A,MKI67,CCND1 and Raf1 gene expression was assessed and compared with the results of the gene expression profile chip. Total RNA was extracted from the tumor tissues of 3 mg/kg FNC and negative control groups using Trizol (ComWin, Beijing, China). Next, 1 μg of RNA was used to synthesize cDNA using ReverTra Ace (Toyobo, Japan) according to the manufacturer’s protocol. The primers used for RT-PCR are presented in [57]Table 1. Human GAPDH was used as an internal control to normalize the mRNA levels. PCR amplification was carried out in a 50-μl reaction mixture with 25 μl of 2×Taq Master Mix (ComWin, Beijing, China), 19 μl of ddH2O, 2 μl (10μM) each of forward and reverse primers and 2 μl of cDNA. The PCR conditions included an initial denaturation at 94°C for 2 min followed by 40 amplification cycles consisting of denaturation for 30 sec at 94°C, annealing for 30 sec at 60°C and extension for 30 sec at 72°C, followed by a final extension for 2 min at 72°C. The annealing temperature was 60°C for GAPDH. PCR products were fractionated on 2% agarose gels and were photographed with a UV gel imaging system (Kodak, USA) using ImageJ software to analyze the gray values. Each assay was repeated three times. Table 1. RT-PCR primers sequences and fragment. Symbol Sequence (5′→3′) Product size (bp) GAPDH forward: 5’-CAGGAGGCATTGCTGATGAT-3’ 138 reverse: 5’-GAAGGCTGGGGCTCATTT-3’ CDKN1A forward:5′-CCTGGCACCTCACCTGCTCTGCTG-3′ 280 reverse: 5′-GCAGAAGATGTAGAGCGGGCCTTT-3′ E2F1 forward: 5′-CATCCAGCTCATTGCCAAGAAG-3′ 391 reverse:5′-GATCCCACCTACGGTCTCCTCA-3′ MKI67 forward:5′-ATTGAACCTGCGGAAGAGCTGA-3′ 105 reverse: 5′-GGAGCGCAGGGATATTCCCTTA-3′ CCND1 forward:5'-AGGAACAGAAGTGCGAGGAGG-3′ 192 reverse: 5'-GGATGGAGTTGTCGGTGTAGATG-3′ Raf1 forward: 5'-TCTACACCTCACGCCTTCACC-3′ 142 reverse: 5'-CATCCTCAATCATCCTGCTGTCC-3′ [58]Open in a new tab Statistical analysis The IBM SPSS 21.0 software was used. The results were presented as the means±SD. Differences between groups were evaluated by t-test. A P value < 0.05 was considered to be statistically significant. In the gene chip analysis, differentially expressed genes were mainly subjected to fold change analysis, hierarchical clustering analysis, principal component analysis, GO enrichment analysis and pathway enrichment analysis. Results FNC inhibits the growth of JeKo-1 cells in a dose- and time-dependent manner The inhibitory effect on cell growth of JeKo-1 was measured by the CCK-8 assay in five treated or untreated groups (0.00032,0.0016,0.008,0.04,0.2 μM and control) for three different treatment times (24 h, 48 h and 72 h), and cytarabine was used as a positive control drug. Here, we showed that FNC significantly inhibited the growth of JeKo-1 cells in a dose- and time-dependent manner ([59]Fig 1). The IC[50] values of FNC treatment were 0.29 μM,0.18 μM,0.097 μM at 24 h,48 h and 72 h, respectively. We also found that cytarabine inhibited the proliferation of JeKo-1 cells in a dose- and time-dependent manner. The IC[50] values of cytarabine treatment were 0.48 μM,0.30 μM,0.11 μM at 24 h,48 h and 72 h, respectively. Fig 1. Anti-proliferative activity of FNC on JeKo-1 cells. [60]Fig 1 [61]Open in a new tab Detected by CCK-8 assay after 24, 48 and 72 h treatment. Values are Means±SD (means of three independent experiments). FNC shows a dose-and time-dependent anti-proliferative activity in JeKo-1 cells. FNC induces cell cycle arrest in the G1/S or G2/M phase The possible effect of FNC on cell cycle progression in JeKo-1 cells was assessed by flow cytometry. The cells were treated with FNC (0, 0.0625, 0.125, 0.25,and 1 μM) for 48 h. The cell cycle distribution was not the same in different concentrations of FNC ([62]Fig 2A and 2B). FNC (0.0625,0.125,1 μM) treatment significantly increased the proportion of JeKo-1 cells in the G0/G1 phase and G2/M phase compared with the control cells(52.0±1.51%,52.0±2.12% and 57.8±2.40% vs. 44.3±1.78%, p<0.05; 2.0±1.02%,12.0±2.33% and 13.6±1.35% vs. 0.0, p<0.05). At a concentration of 0.25 μmol/L, FNC induced arrest in the S phase in JeKo-1 cells (75.0±1.36% vs. 55.7±3.55%, p<0.05). Taken together, our results showed that FNC could cause cell cycle arrest at any one phase, and FNC is a cell cycle-nonspecific agent (CCNSA). Fig 2. Effects of FNC on cell cycle distribution and apoptosis. [63]Fig 2 [64]Open in a new tab (A)FNC induces G1/S or G2/M phase cell cycle arrest. JeKo-1 cells were incubated with 0, 0.0625, 0.125, 0.25, 1 μmol/L FNC for 48 h. The cell cycle distribution was determined via flow cytometry. Data are representative of one of three similar experiments. (C)JeKo-1 cells were treated with 0, 0.0625, 0.125, 0.25, 1 μmol/L FNC for 48 h and harvested. Flow cytometry was performed to observe apoptosis rates. Data are representative of one of three similar experiments. (B and D) Quantified histograms display the effect of FNC on JeKo-1 cells cycle distribution and apoptosis. Data are expressed as means ± SD for 3 independent experiments. * P<0.05 versus the control. FNC induces the apoptosis of JeKo-1 cells To further investigate whether the growth inhibition was due to apoptosis, JeKo-1 cells were incubated with FNC (0, 0.0625, 0.125, 0.25 and 1 μM) for 48 h and then were analyzed by flow cytometry. As shown in [65]Fig 2C and 2D, the percentages of apoptotic cells were significantly increased by FNC treatment in a dose-dependent manner (P<0.05). The percentage of cells undergoing apoptosis was determined by the sum of the cells in early and late apoptosis. Jeko-1 cells were treated with FNC (0, 0.0625, 0.125, 0.25 and1 μM) for 48 h followed by Western blotting analysis of protein expression. Following FNC treatment, Fas, FasL and TNF-α expression significant increased ([66]Fig 3). Fig 3. Effect of FNC treatment on Fas, FasL, TNF-α protein expression in Jeko-1 cells. [67]Fig 3 [68]Open in a new tab (A) Western blot of proteins extracted from Jeko-1 cells following 48h treatment with FNC (0μM, 0.0625μM, 0.125μM, 0.25μM and 1.000μM). A representative result of 3 independent experiments is shown. (B) The Fas/GAPDH, FasL/GAPDH and TNF-α/GAPDH ratio is displayed as Mean±SD. * P<0.05 versus the control. FNC inhibits tumor growth in SCID mice To evaluate the antitumor activity of FNC in vivo, JeKo-1-bearing SCID/Beige mice were injected with FNC via the caudal vein. When administered at a dose of 1, 2 or 3 mg/kg for eight consecutive days, the inhibitory rates were 37.9%,75.8% and 82.1%, respectively. At the end of the experiment, tumor volume was 1857.73 ± 326.51 mm^3 in the control group, while tumor volume in the treatment groups was 1089.35± 267.14 mm^3, 452.65 ± 96.38 mm^3 and 274.40± 77.26 mm^3 at FNC doses of 1 mg/kg, 2 mg/kg and 3 mg/kg, respectively. The tumor volume in cytarabine group was 553.61 ± 123.85 mm^3. Our results showed that the tumor growth in the FNC-treated group was markedly inhibited compared with that of the negative control group, and FNC significantly suppressed tumor growth in a dose-dependent manner ([69]Fig 4A and 4B). Furthermore, the inhibitory rate of cytarabine (36 mg/kg) was 65%. In addition, the body weight of mice had significantly decreased at a dose of 3 mg/kg FNC and 36 mg/kg cytarabine ([70]Fig 4C). In the positive control group, two mice died during the treatment. Otherwise, the low- and medium-dose FNC groups did not cause significant body weight loss compared with the negative control group. Histopathological examination of the liver and kidney revealed no signs of toxicity to the organ tissues ([71]Fig 5). Fig 4. FNC significantly inhibited the growth of human JeKo-1 xenografts in vivo. [72]Fig 4 [73]Open in a new tab (A)Graphs represent the average weight of tumors from every group. (B)shows the average proliferation index(proliferation index% = (tumor weight of drug group/tumor weight of negative control group)×100%]. (C) Graphs represent the average body weight, the body weights were measured after treatment. Tumor weights and body weights are presented as means±SD. * P<0.05 versus the control. Fig 5. Histopathological examination of liver and kidney in FNC treated mice. [74]Fig 5 [75]Open in a new tab When the mice were euthanized, liver and kidney were collected and fixed in 4% buffered paraformaldehyde and paraffin embedded for H&E staining. Pictures were original captured at 100× magnification. Microarray analysis of gene expression in xenograft tissue To obtain more comprehensive insight into the mechanisms by which FNC exerts its anti-tumor effects, we carried out a microarray study of xenograft tissue following exposure to FNC[[76]18;[77]19]. The gene expression profiles of the medicine group (3 mg/kg FNC) were compared with that of the negative control group using the Agilent Whole Human Genome Oligo Microarray (4×44K). The report of total RNA sample quality certification are showed in [78]S1 Table and [79]S1 Fig. The sample we use is uniform and comparable([80]S2 Fig). Our experimental design is reasonable and the biology repeatability is good([81]S3 Fig). The genes were filtered by the setting criterion of p<0.05,fold change≥2 (up-regulated) or≤0.5 (down-regulated) and mean = 7 (significant differences are reflected in the three biological repetitions) as significantly differentially expressed genes. First, we found that there were 606 genes that were significantly different between the 3.0mg/kg FNC and vehicle control group. As shown in [82]Fig 6A and 6B, 448 genes were up-regulated (74%), and 158 genes were down-regulated (26%). [83]S2 and [84]S3 Tables shows the most significant difference gene in up-regulated and down-regulated genes respectively. By pathway enrichment analysis([85]http://cgap.nci.nih.gov/Pathways/BioCarta Pathways), we found that the differentially expressed genes were mainly involved in cell cycle and immunity based on the Biocarta database. [86]Fig 7 shows the top 10 significantly enriched pathway terms. Many factors, including IL2RG,JAK3,IL7R,TNF,BIRC3,PML and CCND2, were involved in those pathways([87]S4 Table). GO analysis was also performed([88]http://geneontology.org/), and the enriched GO-terms (Enrichment test p value = 0) in the ontology classification “Biological Process” were selected and are presented in [89]Table 2. The results showed that “cellular process” contained the greatest number of genes among the GO-terms; thus, we analyzed the main GO terms of cellular process (Enrichment test p value≤0.001) and present them in [90]Table 3. Furthermore, we identified genes related to cell proliferation, cell cycle and apoptosis, respectively, as shown in Tables [91]4, [92]5, [93]6 and [94]7. Fig 6. Gene expression profiling analysis of differential expression genes in xenograft tissue with and without FNC treatment. [95]Fig 6 [96]Open in a new tab Red color represents the up-regulated genes, and green color represents the down-regulated genes. (A)Hierarchical clustering(p≤0.05, fc≥2 or fc≤0.5, mean = 7). (B)Volcano plot. The x axis represents the differential expression profiles with the fold-induction ratios in a log2 scale, and the y axis represents the P value of T-test in a log10 scale. Differentially expressed genes are established at Fold change ≥2 and P < 0.05. Fig 7. Pie chart of pathway enrichment. [97]Fig 7 [98]Open in a new tab We screen out the top 10 significant enrichment pathway terms based on Biocarta. The percentage of each pathway is shown. Table 2. Table analysis of GO enrichment. GOID Name P Hits GO:0002376 immune system process 0 94 GO:0009987 cellular process 0 352 GO:0016265 death 0 65 GO:0032501 multicellular organismal process 0 159 GO:0032502 developmental process 0 145 GO:0050896 response to stimulus 0 163 GO:0051704 multi-organism process 0 44 GO:0065007 biological regulation 0 250 GO:0048518 positive regulation of biological process 0 111 GO:0048519 negative regulation of biological process 0 94 GO:0050789 regulation of biological process 0 229 [99]Open in a new tab Hits: Number of genes included in the go term. Table 3. The main GO terms of cellular process. GOID Name P Hits GO:0001775 cell activation 0 39 GO:0007154 cell communication 0 148 GO:0007155 cell adhesion 7.00E-04 38 GO:0008219 cell death 0 65 GO:0008283 cell proliferation 0 55 GO:0048522 positive regulation of cellular process 0 97 GO:0048523 negative regulation of cellular process 3.00E-04 79 GO:0050794 regulation of cellular process 0 216 [100]Open in a new tab Table 4. Positive regulation of cell proliferation. InputId GeneId foldchange Symbol InputId GeneId foldchange Symbol A_23_P109988 942 2.01 CD86 A_23_P55099 5578 2.80 PRKCA A_23_P137196 3597 3.31 IL13RA1 A_23_P57364 7032 2.52 TFF2 A_23_P138760 23529 2.36 CLCF1 A_23_P59210 1026 2.45 CDKN1A A_23_P14774 1512 2.02 CTSH A_23_P86390 8829 2.20 NRP1 A_23_P167328 952 0.32 CD38 A_24_P173823 5087 2.13 PBX1 A_23_P17998 3280 2.27 HES1 A_24_P245298 8742 2.40 TNFSF12 A_23_P208493 10288 2.10 LILRB2 A_24_P302584 6664 0.48 SOX11 A_23_P28857 55423 3.97 SIRPG A_24_P407645 6693 0.44 SPN A_23_P327380 8626 2.78 TP63 A_24_P938293 3280 2.25 HES1 A_23_P372874 6284 2.03 S100A13 A_32_P65616 5617 3.84 PRL A_23_P52017 259266 0.44 ASPM [101]Open in a new tab Table 5. Negative regulation of cell proliferation. InputId GeneId foldchange Symbol InputId GeneId foldchange Symbol A_23_P109143 5621 2.04 PRNP A_23_P59210 1026 2.45 CDKN1A A_23_P164650 348 2.40 APOE A_23_P76364 928 0.46 CD9 A_23_P168882 94241 4.27 TP53INP1 A_24_P103469 7940 4.35 LST1 A_23_P1962 5920 2.40 RARRES3 A_24_P12651 23087 2.31 TRIM35 A_23_P208493 10288 2.10 LILRB2 A_24_P207139 5371 2.18 PML A_23_P211207 104 0.27 ADARB1 A_24_P228130 414062 0.29 CCL3L3 A_23_P259490 10608 3.06 MXD4 A_24_P234732 10608 2.92 MXD4 A_23_P28857 55423 3.97 SIRPG A_24_P302584 6664 0.48 SOX11 A_23_P321920 414062 0.49 CCL3L3 A_24_P379104 11040 2.10 PIM2 A_23_P376488 7124 3.99 TNF A_24_P407645 6693 0.44 SPN A_23_P423695 10608 3.47 MXD4 A_24_P94916 7940 4.75 LST1 A_23_P55099 5578 2.80 PRKCA [102]Open in a new tab Table 6. Cell cycle arrest related genes covered in GO. InputId GeneId foldchange Symbol A_23_P109143 5621 2.04 PRNP A_23_P168882 94241 4.27 TP53INP1 A_23_P314760 51422 2.02 PRKAG2 A_23_P35082 83667 2.58 SESN2 A_23_P361448 143686 2.37 SESN3 A_23_P436259 2081 2.45 ERN1 A_23_P59210 1026 2.45 CDKN1A A_24_P207139 5371 2.18 PML A_24_P921823 6934 0.40 TCF7L2 [103]Open in a new tab Table 7. Genes related to apoptosis. GoId Name InputId Geneid foldchange Symbol GO:0045768 positive regulation of anti-apoptosis A_23_P59210 1026 2.45 CDKN1A GO:0060561 apoptosis involved in morphogenesis A_24_P20719 5371 2.18 PML [104]Open in a new tab Verification of the microarray data by RT-PCR Selected genes with altered expression levels by microarray analysis were confirmed by RT-PCR. The mRNA expression of E2F1,MKI67,CCND1 and Raf1 detected by RT-PCR were down-regulated, and the mRNA expression of CDKN1A was up-regulated ([105]Fig 8). The results showed acceptable consistency between the results of RT-PCR and microarray data. Fig 8. Verification of microarray data by RT-PCR. [106]Fig 8 [107]Open in a new tab (A) Electrophoresis image of agarose gel. GAPDH was used as an internal control. The pictures shown are representatives of 3 independent experiments. (B)Gene expression levels of 5 selected genes. The right panel of each gene shows the gene expression levels as detected by RT-PCR, and the left panel of each gene shows the gene array data. It shows that the result of RT-PCR was consistent with the microarray results. Discussion MCL is considered one of the most aggressive lymphomas with poor responses to conventional chemotherapy and a relatively short survival[[108]20]. Therefore, novel, more effective and less toxic anti-carcinogens are needed to improve the curative effect on MCL. In the current study, we first demonstrated that FNC efficiently inhibited the proliferation of Jeko-1 cells both in vitro and in vivo and investigated the possible mechanism. In vitro, FNC markedly inhibited the growth of JeKo-1 cells in a dose- and time-dependent manner. Moreover, compared with the positive control drug (cytarabine), the dose of FNC was smaller. In vivo, we used the human-derived MCL cell line JeKo-1 with SCID mice to establish a xenograft model, and the tumor formation rate was 100%. The in vivo experiment further revealed that FNC significantly suppressed tumor growth in a dose-dependent manner. This finding was of particular importance because it was the first time that FNC was shown to inhibit JeKo-1 tumor growth in vivo. Both the inhibitory rates of FNC in the medium- and high-dose groups were higher than those of the positive control group. Of importance, cytarabine treatment caused the most significant body weight loss, and two mice died during the cytarabine treatment, while FNC was well-tolerated in xenograft mice. These results suggested that FNC might be a potential anti-MCL candidate for clinical applications. Recently, remarkable advances have been made in the anti-MCL mechanisms of drugs[[109]21]. Among them, inhibiting proliferation, inducing apoptosis and cell cycle arrest are the main anti-tumor mechanisms[[110]22]. Because defects in apoptosis and cell cycle regulation are primary events in MCL, we investigated the effect of FNC treatment on cell cycle and apoptosis. Our results demonstrated that FNC could induce G1/S or G2/M phase cell cycle arrest, and FNC is a cell cycle-nonspecific agent. Furthermore, FNC significantly induced apoptosis in the JeKo-1 cell line. Obviously, regulating the cell cycle and inducing apoptosis may be one of the important antitumor mechanisms of FNC. Cell cycle is the basic feature of life activities regulated by a variety of proteases. Cyclin-CDK complexes which directly involved in regulating different cell cycle transitions include CDK4(6)/cyclinD, CDK2/cyclinE, CDK2/cyclinA and CDK1/cyclinB. CyclinD binding to CDK4 and CDK6 plays important roles in the G1 phase. CDK2/cyclinE induces the transition of G1 to S phase. After CyclinA binding to CDK2 and CDK1 respectively, cells complete S phase transformation, proceed to M phase. CDK1/cyclinB controls the access and adjustment of the M phase. Our results show that FNC causes cell cycle arrest of different periods concentration-dependently, which may be related to the concentration-dependent regulation of FNC on cell cycle checkpoint activation. Apoptosis plays an important role in development of tumor. There are two major apoptosis pathways: the cell death receptor-mediated extrinsic pathway and the mitochondrial-mediated intrinsic pathway. According to the results of gene chip, Fas, Fasl and TNF-α were chosen to observe the effect of FNC on Jeko-1 cells. Death receptors are transmembrane proteins belonging to tumor necrosis factor receptor (TNFR) gene superfamily. Fas and TNFRs are the most important among these receptors. Upon ligand binding, these receptors gather and activate adapter proteins, lead to the activation of downstream caspases and finally induce apoptosis. Death ligands include TNF-α, FasL and tumor necrosis factor related apoptosis inducing ligand (TRAIL). FAS is an important death receptor on cell surface which binds its ligand FASL and activates the process of transmitting signals to induce the target cell apoptosis. TNF-α is a kind of cytokines with many biological effects. TNF is triggered by two kinds of TNF receptor (TNFR) on the cell surface. The major signaling pathways include apoptosis mediated by caspase family, transcription factor NF-κB mediated by adapter protein TRAF, and the activation of JNK protein kinase. We found that FNC treatment significantly increased the protein expression of Fas, FasL and TNF-α. These results indicate that FNC induces apoptosis in Jeko-1 cells via the cell death receptor-mediated extrinsic pathway. In this study, we compared the gene-expression profiles with and without FNC treatment and searched for genes that were markedly upregulated or downregulated by FNC treatment. 448 genes were found to reveal significantly higher expression levels, and 158 genes had significantly lower expression levels in the FNC (3.0 mg/kg) group than in the negative control group. Pathway analysis of the microarray data revealed that the most significant pathways were involved in the immune system and cell cycle. The most significantly enriched terms such as “immune system process”, “cellular process” and “death” were selected by GO enrichment analysis. Therefore, FNC may affect the occurrence and development of tumors through multiple molecular pathways. According to the results of gene expression profile chip analysis, genes such as CDKN1A, PML, TP53INP1, TNF, SPN and LST1 are associated with cell growth; PRNP, TP53INP1, PRKAG2, SESN2, SESN3, ERN1, CDKN1A, PML and TCF7L2 are involved in cell cycle arrest; and genes such as CDKN1A, PML, BIRC3, CASP10 and TNF play a role in apoptosis. Particularly, two tumorigenesis-related genes, PML and CDKN1A, are related to all three biological processes. Accordingly, we can infer that PML and CDKN1A are critical genes in these pathways. As is well known, CDKN1A (also known as p21) is a cyclin-dependent kinase inhibitor[[111]23]. P21 together with P53 make up the cell cycle G1 check point, and p21 also plays a regulatory role in S phase DNA damage repair and DNA replication[[112]24]. In addition to its role in cell cycle control, CDKN1A is involved in the regulation of cellular senescence, gene transcription and apoptosis[[113]25]. In addition, previous studies have reported that PML functions as an important tumor suppressor, and PML regulates numerous fundamental processes, such as apoptosis, cellular proliferation and cell cycle regulation[[114]26]. Furthermore, PML plays a role in a significantly enriched pathway-regulation of transcriptional activity by PML, and this pathway can regulate the expression of CDKN1A through the P53 pathway. Thus, one possible anti-tumor mechanism of FNC was found to be associated with the regulation of transcriptional activity by the PML pathway. Apart from that, many of the significantly enriched pathways found in this study were already reported to be involved in the immune system process. This finding suggests that modulating the immune system may be another important anti-tumor mechanism of FNC, and we will investigate it further. In conclusion, for the first time, we revealed that FNC could inhibit JeKo-1 cell proliferation and tumor growth in vitro and in vivo. Our in vitro experiments suggest that the underlying mechanisms may be, at least in part, because FNC can cause cell cycle arrest in the G1/S or G2/M phase and induces apoptosis. Therefore, detailed elucidation of the pathways and the respective targets of FNC involved in the cell cycle and apoptosis are critical for its potential application in cancer therapy. In the present study, we first compared the gene-expression profiles with and without FNC treatment to provide a comprehensive analysis of its antitumor mechanisms. Within our observation, FNC regulated many biological process involved in tumors, such as the immune system process, cell proliferation, cell cycle and apoptosis. One possible anti-tumor mechanism of FNC was found to be associated with the regulation of transcriptional activity by the PML pathway. This study shows the potential of FNC as a therapeutic agent for mantle cell lymphoma. Supporting information S1 Fig. Electrophoresis image. (TIF) [115]Click here for additional data file.^ (2.1MB, tif) S2 Fig. Box blot. The central line represents the median of the data. The box represents an interval that contains 50% of the data. This range is called the IQR(Inter Quantile Range). The upper and lower edges of each box represent the 75th and 25th percentile, respectively. It shows that all data concentrate in the middle area and there is no discrete distribution data. The sample is uniform and comparable. (TIF) [116]Click here for additional data file.^ (124.5KB, tif) S3 Fig. PCA(Principal Component Analysis). The distance between the points on the image shows the similarity between samples. It is observed that the distance of three biological repetition in negative control group is very close to each other and so is the drug group. It shows that the biology repeatability is good and the experimental design is reasonable. (TIF) [117]Click here for additional data file.^ (671.1KB, tif) S1 Table. The report of total RNA sample quality certification. (DOC) [118]Click here for additional data file.^ (29.5KB, doc) S2 Table. The most significant difference gene in up-regulated genes. (DOC) [119]Click here for additional data file.^ (31.5KB, doc) S3 Table. The most significant difference gene in down-regulated genes. (DOC) [120]Click here for additional data file.^ (32KB, doc) S4 Table. Differentially expressed genes in the main pathways. (DOC) [121]Click here for additional data file.^ (38.5KB, doc) Data Availability All relevant data are within the paper and its Supporting Information files. Funding Statement This work was supported by the National Natural Science Foundation of China (NO. 21172202 for Junbiao Chang), the Science and technology research Key project of Henan Province(NO. 142102310085 for Yan Zhang). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. References