NUAK2 is amplified along with MDM4 in a subset of breast cancers, particularly the claudin-low subset, suggesting that this may predict vulnerability to GPX4 inhibitors. These findings identify a novel pathway regulating GPX4 expression as well as ferroptotic sensitivity with potential as a biomarker of breast cancer patients that might respond to GPX4 inhibition as a therapeutic strategy.Ferroptosis is a caspase-independent form of regulated cell death strongly linked to the accumulation of reactive lipid hydroperoxides. Lipid hydroperoxides are neutralized in cells by glutathione peroxidase 4 (GPX4) and inhibitors of GPX4 are potent ferroptosis inducers with therapeutic potential in cancer. Here we report that siRNA-mediated silencing of the AMPK-related kinase NUAK2 suppresses cell death by small-molecule inducers of ferroptosis but not apoptosis. Mechanistically we find that NUAK2 suppresses the expression of GPX4 at the RNA level and enhances ferroptosis triggered by GPX4 inhibitors in a manner independent of its kinase activity.  Ferroptosis is a form of iron-dependent cell death associated with the oxidation of membrane phospholipids containing unsaturated double bonds into reactive lipid hydroperoxides –4. The bACSL4 and the iron transporter TFRC  and pDONR223-NUAK2 WT (Addgene #23831) as the template. The reaction mixture was transformed into Stbl3 competent cells (ThermoFisher). Miniprep DNA isolated from spectinomycin-resistant colonies was sequenced to identify clones with the desired mutation. A homologous recombination reaction was then performed using LR Clonase II (Life Technologies #11791100) with the pENTR223-NUAK2 K81R vector and the blasticidin-resistant destination lentiviral vector pLX304-CMV-gateway-V5. The reaction mixture was transformed into Stbl3 competent cells. Ampicillin-resistant colonies were isolated and the mutation confirmed by DNA sequencing.To make the NUAK2NUAK1 , NUAK2 , TEAD4 , YAP1 , CCN1   and GPX4 . 36B4 was used as the normalizer .Total RNA was isolated using the RNeasy kit (Qiagen) and tested for quality on a Bioanalyzer (Agilent Technologies). RNA concentrations were determined with a NanoDrop spectrophotometer (ThermoFisher Scientific). RNA was reverse transcribed using Moloney murine leukemia virus reverse transcriptase (Ambion- ThermoFisher Scientific) and a mixture of anchored oligo-dT and random decamers (Integrated DNA Technologies). Two reverse-transcription reactions were performed for each sample using either 100 or 25 ng of input RNA. Aliquots of the cDNA were used to measure the expression levels of the genes with the primers, and Power SYBR Green master mix  on a 7900 HT sequence detection system . Cycling conditions were 95 °C, 15 min, followed by 40 (two-step) cycles . Ct (cycle threshold) values were converted to quantities (in arbitrary units) using a standard curve  established with a calibrator sample. The primers (5’ to 3’) used were as follows: Cells were seeded in 96-well plates  and treated with compounds 24 hours after plating. Compounds were purchased from Cayman Chemical except for RSL3, purchased from Selleckchem and staurosporine from LC labs. Cell viability was measured using CellTiter-Glo Luminescent Cell Viability Assay (Promega) according to the manufacturer’s instructions. Luminescence was measured on an EnSpire Alpha (Perkin Elmer) using the integrated software package. Data were normalized to vehicle-treated or sensitizing agent-alone controls and sigmoidal dose-response curves were fit using GraphPad Prism (Version 9).Total cellular glutathione was quantified using the GSH/GSSG-Glo kit (Promega) according to the instructions provided by the manufacturer. Drug-treated samples were normalized to parallel cell viability measurements using the CellTiter-Glo assay (Promega).Western membranes were blocked with 5% powdered milk in tris-buffered saline. Primary antibodies used were against NUAK2  (1:1000), GPX4  (1:1000), β-actin  (1:5000) or V5 epitope tag  Rabbit mAb #13202, used 1:2000). Secondary antibodies used were goat-antimouse horseradish peroxidase  and goat-antirabbit horseradish peroxidase . ImageJ (NIH) was used for the densitometric quantification. Full length original western blots are provided as supplementary materials.NUAK2 expression for the selected cell lines according to the Cancer Cell Line Encyclopedia RNAseq data set . Cell line HEC151 was excluded due to a mutation in NUAK2.100 bar-coded human cancer cell lines were grown as a pool and treated with 0, 10, 40, 110, 330, or 1000 nM ML162 or RSL3 for 48 hours and individual cell lines were quantified by bar code sequencing as described in . Activitt-tests (two-tailed) were used for statistical comparisons unless otherwise noted and the threshold for significance was p < 0.05. Data are reported as mean and standard deviation of the indicated number of independent experiments. No samples were excluded from analysis and individual samples are presented in each figure to allow visual confirmation of normality and variance between groups.Sample sizes were not determined based on pre-specified effect sizes. Student’s Supplemental FigsOriginal western blots


Improvement of efficacy of immune checkpoint blockade (ICB) remains a major clinical goal. Association of ICB with immunomodulatory epigenetic drugs is an option. However, epigenetic inhibitors show a heterogeneous landscape of activities. Analysis of transcriptional programs induced in neoplastic cells by distinct classes of epigenetic drugs may foster identification of the most promising agents.enhancer of zeste homolog 2 (GSK126). Modulatory effects of epigenetic drugs were evaluated at the gene and protein levels. Master molecules explaining changes in gene expression were identified by Upstream Regulator (UR) analysis. Gene set enrichment and IPA were used respectively to test modulation of guadecitabine-specific gene and UR signatures in baseline and on-treatment tumor biopsies from melanoma patients in the Phase Ib NIBIT-M4 Guadecitabine + Ipilimumab Trial. Prognostic significance of drug-specific immune-related genes was tested with Timer 2.0 in TCGA tumor datasets.Melanoma cell lines, characterized for mutational and differentiation profile, were treated with inhibitors of DNA methyltransferases (guadecitabine), histone deacetylases (givinostat), BET proteins (JQ1 and OTX-015), and Epigenetic drugs induced different profiles of gene expression in melanoma cell lines. Immune-related genes were frequently upregulated by guadecitabine, irrespective of the mutational and differentiation profiles of the melanoma cell lines, to a lesser extent by givinostat, but mostly downregulated by JQ1 and OTX-015. GSK126 was the least active drug. Quantitative western blot analysis confirmed drug-specific modulatory profiles. Most of the guadecitabine-specific signature genes were upregulated in on-treatment NIBIT-M4 tumor biopsies, but not in on-treatment lesions of patients treated only with ipilimumab. A guadecitabine-specific UR signature, containing activated molecules of the TLR, NF-kB, and IFN innate immunity pathways, was induced in drug-treated melanoma, mesothelioma and hepatocarcinoma cell lines and in a human melanoma xenograft model. Activation of guadecitabine-specific UR signature molecules in on-treatment tumor biopsies discriminated responding from non-responding NIBIT-M4 patients. Sixty-five % of the immune-related genes upregulated by guadecitabine were prognostically significant and conferred a reduced risk in the TCGA cutaneous melanoma dataset.The DNMT inhibitor guadecitabine emerged as the most promising immunomodulatory agent among those tested, supporting the rationale for usage of this class of epigenetic drugs in combinatorial immunotherapy approaches.The online version contains supplementary material available at 10.1186/s13046-022-02529-5. Immune checkpoint blockade (ICB) has transformed management of a wide range of solid tumors . AntibodTo shed light on the specificity of the immune-related transcriptional programs activated in tumor cells by distinct classes of epigenetic drugs, we carried out a comparative profiling of gene signatures induced by DNMT, HDAC, BET and EZH2 inhibitors in the melanoma context, a tumor type currently treated by immunotherapy. The selection of these epigenetic targets was based on an extensive literature search indicating that DNMT, HDAC, BET and EZH2 inhibitors are the most frequently tested drugs in pre-clinical models and in ongoing clinical trials of epigenetic immunomodulation in association with ICB –21. We fn = 14) were established, maintained and routinely tested for the absence of mycoplasma contamination by PCR, as previously described [n = 1) or metastases (n = 13), histopathological features of the corresponding primary melanoma, cell line authentication by STR profiling  and mutational profile by targeted next generation sequencing (NGS) are described in Suppl. Table Sn = 10 melanoma cell lines  with RPMI-1640 medium (Life Technologies Limited) supplemented with 4% FCS  without antibiotics. Since the activity of epigenetic drugs is coupled with cell proliferation [Melanoma cell lines were treated with DNMT inhibitors decitabine (Selleckchem) and guadecitabine (MedChemExpress), HDAC inhibitor givinostat , BET inhibitors JQ-1 (Selleckchem) and OTX015 (Selleckchem), EZH2 inhibitor GSK-126 (Selleckchem), and CDK4/6 inhibitor abemaciclib (Selleckchem). Susceptibility of ten melanoma cell lines to all the drugs (dose range: 7.8 to 3000 nM) was assessed by the 3- dimethylthiazol-2,5-diphenyltetrazolium bromide (MTT) assay at 96 h as described . Drug doferation , melanomNext generation sequencing (NGS) assays on cell line DNA were performed as described in RNA was extracted from melanoma cell lines using the TRIzol reagent (Thermo Fisher Scientific). Melanin removal was performed by the CTAB-UREA method . The samGenomic DNA was extracted from 9 melanoma cell lines treated or not with guadecitabine (at 1 μM), using QIAmp DNA Blood mini-Kit (Qiagen), and modified (500 ng) with sodium bisulfite using the EZ DNA Methylation-Gold Kit (Zymo Research). Details on qMSP and primers for the analysis of the methylation status of LINE-1, MAGE-A1 and NY-ESO-1 are described in SDS-PAGE was performed with 30 μg of protein lysate on 4–12% NuPAGE Bis-Tris (Thermo Fisher Scientific), in MOPS buffer as described in www.ingenuity.com) as described in Transcriptomic Analysis Console (TAC) software  and nSolver software 4.0 were used for analysis of Clariom S gene expression data and of NanoString data respectively, as described in p < 0.05) reduction in the extent of methylation of LINE-1 repetitive elements, chosen as a surrogate of the overall genomic DNA methylation, and in the levels of specific promoter methylation of cancer testis genes  by guadecitabine treatment  were selected for the initial gene modulation experiments assessed with Clariom S arrays. VRG100, isolated from an NRAS-mutant tumor, has a more undifferentiated/mesenchymal transcriptomic profile, as indicated by higher expression of genes as We used the NanoString Cancer Immune panel, containing 731 immune-related genes re-classified into 21 functional classes . Gene modulation was tested by the NanoString Cancer Immune panel and compared to the effects of single drugs  analysis, with IPA  and 9 inhibited URs (Z score < − 2) in at least 6 out of 10 cell lines, i.e. in more than 50% of cell lines Fig. A, in humThe NIBIT-M4 trial is the first completed clinical study testing the association of guadecitabine with ipilimumab in metastatic melanoma . To testWe then tested the hypothesis that the guadecitabine-specific UR signature molecules, identified as activated in-vitro in 6/10 or in 5/10 melanoma cell lines, could also be differentially activated in-vivo in on-treatment lesions from responding compared to non-responding NIBIT-M4 patients. To this end, we first run differential gene expression analysis in tumor biopsies in responding vs non-responding patients at each time point . Subsequently we used such differentially expressed genes for UR analysis by IPA. The results revealed progressive activation of several guadecitabine-specific UR signature molecules in on-treatment (w4 and w12) tumor biopsies from responding patients compared to non-responding patients Fig. A,B. ThreTaken together, these results strongly support the notion that genes in the guadecitabine-specific signature are modulated even in-vivo at tumor site in patients treated with this DNMT inhibitor. Moreover, the progressive activation of the UR signature in responding versus non-responding patients suggests that the clinical activity of guadecitabine in melanoma patients depends on the effective activation of innate immunity pathways.http://timer.comp-genomics.org). Sixty-five % of the genes in the guadecitabine signature were significant in a Cox proportional hazards model (Suppl. Table Sp < 0.05). In the JQ1 signature, 59% of genes were significant and conferred a reduced risk . However, the prognostically significant genes in the guadecitabine signature were upregulated by this DNMT inhibitor in melanoma cells, while the prognostically significant genes in the JQ1 signature were frequently downregulated by the BET inhibitor in melanoma cells , and their inhibitors (serpins), implicating epigenetic drugs in the regulation of different cancer-related processes, controlled by cathepsins, such as proliferation, angiogenesis, metastasis and invasion. These results extend previous knowledge on the non-immuno-related anti-tumor activities of epigenetic inhibitors, such as reactivation of tumor suppressor genes by demethylating agents , promotiTaken together, our study indicates that distinct epigenetic drugs may elicit specific immune-related transcriptional programs in melanoma cells. These results provide a pre-clinical rationale in favor of association of ICB with DNMT or HDAC inhibitors, rather than with BET or EZH2 inhibitors.The findings of this study support a mechanistic rationale for development of combinatorial immune intervention where boosting of NF-kB, TLR, Type I-III IFN and inflammation-related pathways by DNMT inhibitors as guadecitabine might cooperate with the rescue of adaptive immunity by immune checkpoint blockade.Additional file 1. Supplementary Methods.Additional file 2: Supplementary Figs. S1 to S21. Supplementary Fig. S1. Expression in ten melanoma cell lines of genes and gene families targeted by epigenetic drugs. Supplementary Fig. S2. Differentiation profile of melanoma cell lines. Supplementary Fig. S3. Susceptibility of ten melanoma cell lines to the anti-proliferative effects of epigenetic drugs. Supplementary Fig. S4. Methylation status of LINE-1, MAGE-A1 and NY-ESO-1 in 9 melanoma cell lines treated with guadecitabine. Supplementary Fig. S5. Volcano plot of differentially expressed genes in VRG100 and CST30 cell lines. Supplementary FigureS6. Whole genome gene modulation analysis by 4 epigenetic drugs in two melanoma cell lines. Supplementary Fig. S7. Edwards-VENN diagram analysis of significantly modulated genes by epigenetic drugs. Supplementary Fig. S8. Original and revised gene classification of the NanoString nCounter PanCancer Immune Profiling panel. Supplementary Fig. S9. Quantitative analysis of Nanostring data in ten melanoma cell lines treated with epigenetic drugs. Supplementary Fig. S10. Modulation of immune-related genes in melanoma cell lines by epigenetic drugs. Supplementary Fig. S11. Comparison of immune-related gene modulation by BET inhibitors JQ1 and OTX-015. Supplementary Fig. S12. Immune-related signature of epigenetic drugs in melanoma. Supplementary Fig. S13. Outline of the strategy for quantitative analysis and visualization of western blot data. Supplementary Fig. S14. Quantitative western blot analysis and visualization of the modulation of LMP7 by epigenetic drugs in 11 melanoma cell lines. Supplementary Fig. S15. Pipeline of data analysis based on Upstream Regulators (UR) identified by IPA. Supplementary Fig. S16. Classification of URs significantly modulated by at least two different drugs in melanoma cell line VRG100. Supplementary Fig. S17. Classification of URs significantly modulated by at least two different drugs in melanoma cell line CST30. Supplementary Fig. S18. Summary of the major functional networks linking relevant URs emerging from IPA Core Analysis in melanoma cell line VRG100. Supplementary Fig. S19. Comparison of URs activated by guadecitabine in-vitro and in-vivo. Supplementary Fig. S20. Comparison of URs activated by guadecitabine in melanoma cell line VRG100 vs a mesothelioma cell line vs hepatocarcinoma cell lines. Supplementary Fig. S21. Prognostic significance of selected genes in the guadecitabine signatures in 41 TCGA tumor types.Additional file 3 Supplementary Table S1. Origin of melanoma cell lines, histopathological features of the corresponding primary tumor, cell line authentication data by STR profiling, and mutational profile by NGS of 14 melanoma cell lines used in this study.Additional file 4: Supplementary Table S2. Drug doses used for experiments and effect of each drug at such dose in the MTT assay on each cell line.Additional file 5: Supplementary Table S3. Antibodies used in quantitative western blot analysis.Additional file 6: Supplementary Table S4. Modulation of immune-related genes belonging to 21 functional classes by epigenetic drugs. Sheets # to #21.Additional file 7: Supplementary Table S5. Immune-related gene modulation by epigenetic drugs and by combinatorial treatments.Additional file 8: Supplementary Table S6. Upstream Regulator analysis on differentially expressed genes in drug-treated vs untreated cell lines VRG100 and CST30.Additional file 9 Supplementary Table S7. Prognostic significance of genes in the guadecitabine and JQ1 immune-related signatures in the Cancer Genome Atlas (TCGA) melanoma dataset.


Patient-derived tumor models show promise for evaluating novel cancer treatments that could improve outcomes for African children diagnosed with EBV-associated endemic Burkitt lymphoma. MYC chromosomal translocation. Survival rates hover at 50% after conventional chemotherapies; therefore, clinically relevant models are necessary to test additional therapies. Hence, we established five patient-derived BL tumor cell lines and corresponding NSG-BL avatar mouse models. Transcriptomics confirmed that our BL lines maintained fidelity from patient tumors to NSG-BL tumors. However, we found significant variation in tumor growth and survival among NSG-BL avatars and in Epstein–Barr virus protein expression patterns. We tested rituximab responsiveness and found one NSG-BL model exhibiting direct sensitivity, characterized by apoptotic gene expression counterbalanced by unfolded protein response and mTOR pro-survival pathways. In rituximab-unresponsive tumors, we observed an IFN-α signature confirmed by the expression of IRF7 and ISG15. Our results demonstrate significant inter-patient tumor variation and heterogeneity, and that contemporary patient-derived BL cell lines and NSG-BL avatars are feasible tools to guide new therapeutic strategies and improve outcomes for these children.Endemic Burkitt lymphoma (BL) is a childhood cancer in sub-Saharan Africa characterized by Epstein–Barr virus and malaria-associated aberrant B-cell activation and  Plasmodium falciparum malaria endemicity and EBV infection in young children (Endemic Burkitt lymphoma (eBL) was first described over 60 yr ago in pediatric patients in Uganda  and was children . Epidemichildren . Conventchildren ; howeverchildren , with mochildren . Devisinchildren . HoweverMYC oncogene expression arising in the vast majority of cases from chromosomal translocations . These solid B-cell tumors appear to be relatively homogenous in their gene expression profiles, but have varied mutations associated with key oncogenes, driver mutations, and are more distinct based on the EBV status of the transformed B cells than on the geographic location of diagnosis  diagnosed outside of Africa is ∼30% EBV-associated and has a 10-fold lower incidence, in contrast to eBL tumors that are >90% EBV-associated . All BL iagnosis . Common eaminase . In addieaminase . EBV-asseaminase . TherefoMYC, and functional analysis of apoptosis-related proteins demonstrates that EBV suppresses apoptosis in multiple latency types including eBL , and latent membrane proteins (LMP1 and LMP2). However, EBV-associated tumors generally display more restricted latency programs as an immune evasion strategy , with eBding eBL . Currentding eBL . EmerginOne of the most promising new therapies for CD20-positive lymphomas is the chimeric anti-CD20 monoclonal antibody rituximab that was approved by the US FDA in 1997 . In combscid IL2rgnull (NSG) mice, are being used to explore cancer treatment efficacy, dosing, and toxicity  or patient-derived cell lines (PDC) implanted into immunodeficient mouse strains such as SCID or NOD-toxicity . These ptoxicity , which wtoxicity . Althougtoxicity , these tTo advance our understanding of inter-patient variation, we established five new patient-derived BL cell lines, compared them with long-established “old” BL cell lines, and then leveraged them to create PDC NSG-BL avatar mouse models. We then investigated inherent variation between the NSG-BL avatars and differences in response to rituximab. In parallel, we conducted comparative transcriptomic studies to further characterize tumors from pediatric Kenyan eBL patients, corresponding BL cell lines, and BL tumors grown in NSG mouse models.To generate new BL cell lines, we optimized previous protocols  with ourIGH or IGL/MYC translocations and EBV. All our BL cell lines had uniform diagnostic features such as CD20 and CD10 expression, although there were minor variations in the abundance of surface marker expression, as determined by flow cytometry  involving the immunoglobulin heavy chain gene (IGH), and one (BL720) had the t translocation juxtaposing MYC/lambda light chain (IGL)  and for the presence of ytometry . BL717 aytometry  and threytometry , thus suytometry . All fivin (IGL) .To detect EBV, we performed RNA in situ hybridization (RNA-ISH) for EBERs, the most abundant viral RNA in EBV-infected cells. We observed positive staining for EBERs in the nuclei of all five BL lines . The freOur tumors had varied sites of presentation (jaw/abdomen), EBV type (type 1/type 2), and patient outcomes (survivor/non-survivor) post-chemotherapy (CHOP only) , suggestWe performed bulk RNA-seq on our new BL lines, the originating eBL patient tumors, and standard “old” BL cell lines to investigate their variance and concordance. To compare the overall transcriptomes, we performed principal component analysis (PCA) comparing four eBL patient tumor biopsies (BL740 patient specimen was not available for sequencing), the corresponding BL cell lines, and commercially available BL cell lines  that were culture-adapted decades ago . The PCAPrincipal component analysis loading values for Fig 3A.Table S1 MYC, MS4A1(CD20), MME(CD10), MKI67(KI-67), and BCL6. Differential gene expression (DGE) analysis showed minimal gene expression differences , and no significant difference in the expression of BL marker genes in the BL cell lines compared with the patient tumors , as a result of direct rituximab activity, whereas the other four new BL cell lines were not affected . Furthermore, we tested rituximab with complement  and found that our new BL cell lines showed no effect, with minimal cell death for NSG-BL740 tumors (P = 0.1). Akata and Mutu displayed significantly increased cell death with complement , suggesting rituximab action is likely to be complement-mediated in these cell lines, unlike our new BL cell lines. We also observed greater variation in rituximab responses using our new BL cell lines, likely reflecting tumor heterogeneity, which has been lost in old culture-adapted BL cell lines.Rituximab’s efficacy is well documented in B-NHL and BL in the developed world , but theaffected . We also0 tumors ; P = 0.1P = 0.004) and rituximab with complement  (P = 0.05). As for the old cell lines, Akata appeared to lose MMP with rituximab and complement  but this was not statistically significant, whereas Mutu had a minimal, yet significant, effect for rituximab without and with complement . Taken together, these in vitro assays suggest that BL740 is partially sensitive to rituximab-mediated cell death and CDC, in the absence of cellular cytotoxicity (ADCC or ADCP).To further evaluate rituximab-induced cell death in selected BL cell lines, we measured intrinsic apoptosis determined by loss of mitochondrial membrane potential (MMP) . Cells w = 0.05) . BL725 a3), necrosis of tumor, or loss in body weight (>20%). The BL720 avatars were the only ones euthanized early because of heavy tumor burden . BL719 avatars showed the poorest survival but with low tumor weights and a low implantation rate (two of six mice) suggesting other pathologic mechanisms involved  compared with EBV type 1 tumors, with BL720 achieving the largest tumor sizes   .Rate of metastasis in new BL cell lines.Table S5 2) was >0.9 showing that very few genes were divergent between the eBL patient tumors and NSG-BL tumors  and quantified them using QuPath software . We deteIn addition, we observed immediate–early protein BZLF1 expression in about 8–30% of cells within tumors , which has the potential to convert EBV from latent to lytic cycle in productive versus abortive lytic cycles  and S6 . Regulat+ cells in rituximab-treated BL740 tumors compared with untreated mice. The greater ratio of mCD45+ cells to tumor cells in BL740 tumors could be due to the smaller size of the tumors compared with other NSG-BL tumors  gene expression was observed for BL720 and BL740 but not for BL717 or Daudi. We speculate that discordance in CD20 gene and protein expression is driven by transcriptional regulation , CAV1 (logFC = 2.09 and FDR = 2.92 × 10−9), ACVR1 (logFC = 2.8 and FDR = 1.50 × 10−13), BCL2L11 (logFC = 1 and FDR = 1.39 × 10−5), and CASP3 (logFC = 0.6 and FDR = 1.5 × 10−4) involved in apoptosis and regulating cell proliferation and down-regulation of BCL-2 (logFC = −0.8 and FDR = 4.11 × 10−6) . To further interrogate rituximab responsiveness pathways, we compared the expression profiles from rituximab and PBS-treated NSG-BL740 tumors. We identified 210 genes to be DE (logFC > 1.5 and FDR < 0.01) among the human transcriptome ( × 10−6) . To iden × 10−6) . BecauseDifferentially expressed genes between rituximab-treated and untreated BL740-NSG mouse tumors.Table S7 Gene set enrichment results of DEGs between rituximab-treated and untreated BL740-NSG mouse models.Table S8 TNFRSF13C, IRF7, and STAT3 for NSG-BL717 and NSG-BL720 compared with NSG-BL740 tumors. GSEA performed on the normalized expression values of the DEGs identified the enrichment of 23 genes  associated with the interferon-alpha (IFN-α) pathway in both NSG-BL717 and NSG-BL720 tumors compared with NSG-BL740 (Table S10). Apoptosis and the mTORC1 signal responses were inherently enriched in NSG-BL740 tumors compared with NSG-BL717 and NSG-BL720. By IHC, we confirmed key mediators in the type I IFN pathway, interferon-regulatory factor 7 (IRF7), and interferon-stimulated gene 15 (ISG15) expressed in NSG-BL717, NSG-BL720, and NSG-Daudi tumors but not NSG-BL740 (To gain more insights into the molecular mechanisms underlying differences between the rituximab-responsive NSG-BL740 and rituximab-unresponsive (NSG-BL717 and NSG-BL720) tumors, we performed differential expression analysis and identified 878 genes DE between NSG-BL717 compared with NSG-BL740 and 803 genes DE between NSG-BL720 compared with NSG-BL740 (Table S9). Of these DEGs, we observed up-regulation of B-cell survival genes such as SG-BL740 . NSG-MutDifferentially expressed genes between rituximab-treated BL717-NSG and rituximab-treated BL740-NSG.Table S9 Gene set enrichment results of DEGs between rituximab-treated BL717-NSG and rituximab-treated BL740-NSG mouse tumors.Table S10 It is estimated that 80% of cancer deaths occur in low- to middle-income countries, which has prompted numerous global oncology initiatives . In thisUsing expandable patient-derived BL cell lines, we successfully established five different NSG-BL models and observed significant variation in tumor growth kinetics on the same mouse background. Most of our NSG-BL tumor-bearing mice exhibit sufficiently long survival for repeated dosing to simulate cancer treatment regimens and to test mechanisms leading to tumor regression or resistance. In the case of NSG-BL719, tumors grew early, and remained small but led to the rapid death of the mice. BL719 tumors exhibiting rapid softening and tumor necrosis suggesting these factors contributed to pathology similar to tumor lysis syndrome. Because BL is one of the most rapidly growing human tumors, our median time from patient biopsy to establishing cell lines ∼3 wk, followed by ∼ 4 wk to generate NSG-BL tumors, makes this pipeline feasible for studying clinically actionable markers.Our NSG avatars include both EBV type 1 and type 2 tumors, which allowed us to further interrogate EBV latency. BL tumors endemic to Africa are classified as latency I, a more restricted pattern of antigen expression, expressing EBNA1 only , 1987. HWe recognize that the biology of EBV latent infection is complex. The expression of EBNA2 (and other EBNAs) in the absence of LMPs has been described in early infection , EBV inf+ B-cell lymphomas, was our first choice of drug to test with our new BL cell lines and NSG-BL avatars. Rituximab induces apoptotic activity in vitro and has been previously studied in standard BL cell lines Raji, Daudi, and Ramos (BCL2L11) and PUMA (BBC3) have been identified as key pro-apoptotic genes repressed in latency I BL tumors  cells. We chose the NSG-BL mouse model as a launching point for the next set of experiments using humanized NSG mice to interrogate NK  and T-ceNK cells  that mayMYC-induced stress leading to apoptosis. It could be argued that ATF2 enrichment in culture-adapted cell lines is due to the lack of protein turnover in downstream processes, thus resisting apoptosis. We also observed that genes associated with STK33 and HOXA9 up-regulation were relatively enriched in new BL cell lines. STK33 phosphorylates pro-apoptotic BAD (BCL-xL) and suppresses apoptosis via mitochondrial pathways  biology and eBL pathogenesis.Ethical approval was obtained from the Scientific and Ethics Review Unit (SERU) at the Kenya Medical Research Institute (KEMRI) and the Institutional Review Board at the University of Massachusetts Chan Medical School, Worcester, USA. Written informed consent was obtained from adults and from parents of minor study participants in accordance with the Declaration of Helsinki. Children diagnosed with cancer were enrolled at Jaramogi Oginga Odinga Teaching and Referral Hospital (JOOTRH) in Kisumu, Kenya. Two independent pathologists confirmed diagnosis by cytopathology and May–Grunwald–Giemsa staining. Patient BL tumor samples were further characterized by transcriptome and mutational profiling to confirm BL diagnosis .g for 5 min. The tumor cell pellets were resuspended in 1 ml RPMI containing CSA that interferes with IL-2 synthesis and thereby restricts the growth of T cells that could be cytotoxic to the B-cell tumors. This cell suspension was then divided into four wells of a 48-well non-tissue culture–treated plate , and 250 µl of RPMI+CSA media was added to each well for a total volume of 500 µl per well. Cells were incubated in 5% CO2 at 37°C for at least 5 d without being disturbed. After 5 d, cell cultures were visually inspected using an inverted microscope at 100× magnification (Nikon TMS) and supplemented with fresh media by gently pipetting to disperse any cell clumps. Half the contents of each well (250 µl) was transferred to an adjacent well in the plate to expand the cultures. An additional 250 µl of tumor cell growth media  was added to each well. The tumor cells were allowed to grow undisturbed at 37°C and 5% CO2 for another 7 d. Our patient-derived BL cell lines grew free in suspension as clumps of cells or as single cells that did not adhere to the culture plate . The FNA samples were gently passed through a 70-µm cell strainer, to dissociate any tumor clumps into a single-cell suspension. The tumor cells were washed once in RPMI media supplemented with 15% FBS, 1X Pen/Strep, and 5 µg/ml cyclosporine A (CSA), and spun at 300re plate . After 72 incubator following the established protocols.Standard BL-derived cell lines, established decades ago, Namalwa , Jijoye MYC rearrangement  for BL720 alone, because it failed to show translocation in t. This probe set detects rearrangement of the MYC locus at 8q24.2 without identification of the translocation partner.FISH analyses were performed at the Clinical Duke Cytogenetics Laboratory at Duke University Health Systems Clinical Laboratories and carried out on cell lines. The Vysis LSI IGH/MYC/CEP 8 Tri-Color Dual Fusion FISH Probe Kit  was used to detect the t  reciprocal translocation involving the IGH and MYC gene regions, and also a centromere enumeration probe  as a reference for the copy number of chromosome 8. For BL720, we also performed interphase FISH analysis using a break-apart probe to test for any angement . The 8q2For each patient-derived BL cell line established, we isolated DNA from the first passage preserved in RNAlater using the Monarch Genomic DNA Purification Kit (NEB). We used ddPCR to determine EBV load by amplifying EBV BALF5 and human β-actin gene, using primers and probes as previously described . This meEBV type was determined by ddPCR using primers and probes targeting the EBNA2 and EBNA3C genes. Namalwa and Jijoye cell line DNAs were used as EBV-type positive controls for EBV type 1 and type 2, respectively. We targeted two EBV type–specific genes to confirm the EBV type and to eliminate incorrect identification in case we had a cell line with an intertypic virus as previously reported . The EBVEBER in situ hybridization of cytospin-fixed cells was performed using the Novocastra Predilute EBER probe kit (Leica Biosystems) following the manufacturer’s protocol. In brief, cells were stained with the fluorescein EBER probe (ISH5687-A) followed by the BCIP/NBT detection kit (NCL-ISH-D). The specimen shows positive staining indicated by dark blue/black stain. Each run had a positive and a RNA negative control probe (ISH5950-A). We defined a case as EBER-positive when most (>50%) of the tumor cells had moderate-to-strong signals.3 pieces or a single-cell suspension, and either tumor fragments or cells (2.5 × 106) were transplanted subcutaneously to the right flank of NSG mice  neutral buffered formalin (Thermo Fisher Scientific), paraffin-embedded, and sectioned into 4-µm sections. They were deparaffinized in xylene and rehydrated serially in 100%, 95%, and 75% ethanol and water, respectively, and pretreated in a 10 mM citrate buffer, pH 6.0, for 20 min in a water bath (98°C) followed by cooling. Endogenous peroxidase was blocked in 0.3% hydrogen peroxide. Then, the sections were incubated with a 1:100 diluted primary antibody for 1 h at room temperature and washed, and the slide was incubated with an appropriate species-specific secondary antibody for 1 h at room temperature, followed by visualization using DAB (Liquid DAB+ Substrate/Chromogen System) according to the manufacturer’s recommendation , and counterstained with hematoxylin stain. To detect EBV protein expression in the mouse tumors, we stained for EBNA1 , BZLF1 , LMP1 , EBNA2 , EBNA3A , and EBNA3C . We also stained for cleaved caspase-3 , IRF7 , and ISG15 . Images were captured using NIS-Elements software . Patient melanoma tumors were obtained from the UMass Chan Medical School Cancer Avatar Institute (IRB ID: H00004721) and passaged in NSG mice to deplete the human leukocytes present within the tumor microenvironment . The patNSG mice .6 cells/ml and blocked using 5% normal human serum, before antibody staining. Cells were stained with antibodies for 30 min at 4°C and were fixed using BD Cytofix/Cytoperm (BD Biosciences) for surface staining, and intracellular staining was performed using the transcription factor buffer set  according to the manufacturer’s recommendation, only in the case of Ki-67. Cells were analyzed on a four-laser Cytek Aurora (Cytek Biosciences) by acquiring at least 100,000 events, and data analysis was done using FlowJo v10.0 (BD Biosciences). We used Zombie near IR (BioLegend) to gate on live cells for flow cytometry except in the case of Annexin V staining where we use 7-aminoactinomycin D (7AAD), a vital dye to assess cell death, instead. Our gating strategy includes gating on forward scatter versus side scatter, followed by gating for singlets, selecting for live cells and then focusing on our markers of interest. We employed fluorescence minus one to determine our gates in dot plots. Cell surface expression of tumor markers was detected by flow cytometry. Cells were resuspended in PBS containing 2% FBS. The cells were adjusted to 1 × 10Antibodies and reagents: The following antibodies were used for staining tumor cell lines and NSG-BL tumors via flow cytometry from BioLegend: BV510 anti-CD20 (clone 2H7), PE/Cy7 anti-CD10 (clone HI10a), AF647 anti-CD19 (clone HIB19), PE/Cy5 anti-human CD45 (clone HI30), BV605 anti-mouse CD45 (clone 30-F11), BV785 anti-mouse Ly6G (clone 1A8), AF700 anti-mouse F4/80 (clone BM8), and BV421 anti-Ki-67 (clone Ki-67).phs001282.v2.p1.Total RNA was extracted from the patient FNA samples, the resulting BL cell lines, and NSG-BL mouse tumors using the Monarch Total RNA extraction kit (New England Biolabs). Starting with 1–5 µg total RNA, we enriched mRNA molecules using oligo-dT magnetic beads to capture polyA-tailed mRNA molecules. We then proceeded to prepare strand-specific RNA-seq libraries following the NEBNext Ultra II Directional RNA Library Prep Kit for Illumina (NEB). Final library concentration and fragment size were confirmed with a Qubit 4 fluorometer (Thermo Fisher Scientific) and fragment analyzer (Agilent), respectively. These libraries were sequenced with paired-end reads (2 × 75 bp) on the NextSeq 550 system . Raw sequencing data files from this study are deposited in the NCBI’s database of Genotypes and Phenotypes (dbGaP) with accession number https://www.R-project.org/) (version 3.5.3). For each tumor type, we calculated correlation coefficients between primary BL tumor samples, cell lines, and DLBCL tumors using the 5,000 most variable genes, as these genes are the most likely to be biologically informative. To show that our BL tumors, newly derived BL cell lines, and the NSG-BL mouse models all have a BL-like gene expression profile, we compared our expression data with those of previously published BL tumors collected from Uganda (accession no.: PRJNA374464). We also downloaded previously published data from DLBCL patients  (dbGaP accession no.: phs000532.v2.p1), to discern any similarities to other GC B-cell lymphomas, apart from BL.DGE analysis was performed using standard methods. Briefly, sequenced reads were first checked for quality using FastQC  and sortHBA1, HBA2, HBB, and HBD. To control for multiple testing, we applied the Benjamini–Hochberg (BH) procedure with a threshold for statistical significance set at an adjusted P < 0.01 and FDR < 0.01. Batch effects and unwanted sources of variations related to different sequencing platforms were removed using sva  would indicate a gene set enrichment at the top of the ranked list; a negative ES indicates gene set enrichment at the bottom of the ranked list. Gene sets were considered significantly enriched in a group if FDR q <0.2.BL avatar. Eight- to 10-wk-old NOD-scid IL2rg null (NSG) mice (The Jackson Laboratory) were injected with BL cell lines (5–10 × 106 cells) subcutaneously into the right flank. We observed palpable tumors within 2–4 wk, depending on the growth rate of the BL cell line. Tumor volume was measured by calipers three times a week and calculated using the modified ellipsoid formula ½(Length*width2). Criteria for endpoints were tumor burden > 20% of body weight loss (BW), mean tumor volume > 4,000 mm3, and ulceration/necrosis of tumor. Tumor phenotype and EBV content were evaluated by in situ hybridization, immunohistochemistry, and flow cytometry. All animals were housed in a specific pathogen-free facility in microisolator cages and given autoclaved food and acidified autoclaved water. All animal procedures were done in accordance with the guidelines of the Institutional Animal Care and Use Committee of UMass Chan and conformed to the recommendations in the Guide for the Care and Use of Laboratory Animals .2 asphyxiation followed by cervical dislocation when the tumors exceeded 20% body weight, and were inactive or moribund. Tumor tissues were collected and placed in RNA later  for RNA-seq experiments or harvested and processed, so they could be analyzed by IHC and flow cytometry. Single-cell suspensions of tumor tissues were obtained by mincing tumor tissue using gentleMACS Dissociator (Miltenyi) along with DNase  and hyaluronidase .Age-matched mice with both male and female NSG mice were divided into two groups (five–six mice/group) and injected with BL cell lines, as explained above. NSG mice without tumor cell implantation were used as controls. As tumors became palpable, mice were randomized by body weight and injected intraperitoneally (IP) either with rituximab  in 200 µl of PBS or with 200 µl PBS only, every 3 d up to four injections mimicking human treatment regimen of four doses weekly (375 mg/m2). Mice were monitored for adverse clinical signs and euthanized by COBL cell lines were incubated with rituximab (10 µg/ml) for 24 h based on previous studies . Rituxim6 cells/ml. 100 μl of this cell suspension (1 × 105 cells) was then incubated with 2.5 µl of Annexin V-PE and 7AAD each, in the dark for 20 min. After incubation, cells were added to 400 µl of 1X Annexin V binding buffer and analyzed by flow cytometry. Isotype IgG antibody was tested as a negative control even though there was no difference between the media-only condition and IgG isotype.Externalization of phosphatidylserine, an early marker of apoptosis, was monitored by Annexin V-PE and 7AAD staining to measure cell death . BL cell lines treated with rituximab, in vitro, and BL tumor cells harvested from NSG-BL tumors treated with rituximab and PBS were first stained with human antibodies to CD20, CD19, and CD45, followed by Annexin V/7AAD staining. Briefly, the cells were first washed with ice-cold PBS and resuspended in 1X Annexin V binding buffer at 1 × 106 cells/ml in warm complete RPMI medium and stained with JC-1 dye at a final concentration of 2 µM for 30 min at 37°C, and analyzed by flow cytometry. Staurosporine (1 µM) was used as a positive control.Loss of MMP as a marker of apoptosis was assessed with JC-1 dye , a cationic carbocyanine dye that accumulates in mitochondria of cells in proportion to MMP. After treatment of the BL cell lines with rituximab in vitro, the cells were harvested, washed, and resuspended in 200 µl of warm medium and stained with JC-1 dye as per the manufacturer’s recommendations. Briefly, cells were resuspended at a density of 1 × 10Fragmentation of intracellular DNA is a late marker of apoptosis and was measured by TUNEL assay, using the APO-DIRECT Kit . Briefly, tumor cells treated with rituximab and PBS were fixed with 1% paraformaldehyde, washed, and stored in ice-cold 70% ethanol for at least 24 h before staining with 50 µl of DNA labeling solution, prepared as per the manufacturer’s instructions. After incubation for about 1 h with the DNA labeling solution, the cells were washed and analyzed by flow cytometry.t tests using the Mann–Whitney test, or for paired analyses, t test  or non-parametric Wilcoxon signed-rank test. Differences were considered significant if P-value was less than 0.05 .Statistical analyses were performed using GraphPad Prism 9 and in R version 4.0.3. Statistical analysis was performed by non-parametric BioRender.com.Schemas were created with phs001282.v2.p1.The raw data generated supporting the results of this article are available and can be accessed in NCBI  dbGaP (database of Genotypes and Phenotypes) with accession number


In vitro assays were used to assess the potency and inhibition of CDK4/6 enzymatic activity of GLR2007. Using in vivo assays, the distribution of radiolabeled GLR2007 in rats was determined through quantitative whole-body autoradiography. The antitumor efficacy of GLR2007 was evaluated in human GBM and breast cancer orthotopic mice xenograft models, and human lung, colorectal, and liver cancer in a subcutaneous xenograft model. In tumor cell line proliferation assays, GLR2007 inhibited proliferation at lower concentration values than abemaciclib in 19 of 20 GBM, five of seven breast, 20 of 21 lung, and 24 of 24 liver cancer cell lines. Total levels of radiolabeled GLR2007 in the brains of rats exceeded those in plasma by 2.3–4.5-fold from 2–6 hours after dosing. A xenograft model showed that, compared with vehicle control, 50 mg/kg GLR2007 induced 95.9% tumor growth inhibition (TGI) (P<0.001) in GBM orthotopic xenografts, 81.4% TGI (P=0.037) in breast cancer orthotopic xenografts, and 91.5% TGI (P<0.001) in colorectal cancer subcutaneous xenografts. These studies show possible BBB penetration of GLR2007 and demonstrate its potential as a CDK4/6 inhibitor for the treatment of solid tumors, including GBM.Cyclin-dependent kinases, CDK4 and CDK6, are essential in regulating the cell cycle, which is disrupted in cancers like isocitrate dehydrogenase wild-type glioblastoma (GBM). Currently marketed CDK4/6 inhibitors, including abemaciclib, have shown preclinical efficacy in solid tumors, but factors such as poor blood–brain barrier (BBB) penetration limit their efficacy in GBM. GLR2007 is an investigational CDK4/6 inhibitor with the potential for improved BBB penetration.  Within the CDK group of proteins, CDK1, CDK2, CDK4, and CDK6 are involved in cell proliferation, regulating the transitions between different cell cycle phases . DysreguPromising preclinical studies were followed by favorable clinical trial results, and four CDK4/6 inhibitors, palbociclib, abemaciclib, ribociclib, and trilaciclib are currently approved by the US Food and Drug Administration (FDA). The introduction of CDK4/6 inhibitors has been described as the most relevant advance in the management of HR-positive, Erb-B2 receptor tyrosine kinase 2 -negative metastatic breast cancer in recent years . PalbociConversely, there remains an urgent need for additional therapeutic options in the treatment of the most common malignant primary brain tumor, GBM, which accounts for nearly half of all central nervous system (CNS) tumors . The 5-yin vitro assays, in vivo whole-body autoradiography, and in vivo xenograft models of GBM and other solid tumor cancers.A challenge to the development of effective targeted molecular therapies for GBM is the presence of the highly selective semipermeable blood–brain barrier (BBB), which prevents nearly all large molecules (>400 Da) and 98% of small-molecule drugs from entering the CNS , 17. Add50) and inhibition constant (Ki). IC50 and Ki values were determined using the XLfit 205 model  curve-fitting add-on for Microsoft Excel .Inhibition of the catalytic activities of protein kinases, CDK4–cyclin D1 and CDK6–cyclin D1 , by GLR2007  and palbociclib  was assessed using a LANCE Ultra time-resolved fluorescence resonance energy transfer assay  according to the manufacturer’s instructions. GLR2007 was tested across a range of concentrations from 0.0017 nM to 100 nM. Palbociclib was tested across a range of concentrations from 0.0169 nM to 1000 nM. Results were calculated as half-maximal inhibitory concentration , abemaciclib , or vehicle control dimethyl sulfoxide were added to each well at a volume of 20 μL, and cells were incubated at 37°C for 72 hours. In the DAPI staining method, cells were washed using 1× phosphate-buffered saline , fixed with 4% formaldehyde, permeabilized with 0.2% Triton X-100 (Sigma-Aldrich), washed again, and stained with 1 μg/mL DAPI to visualize cell nuclei. Cells were washed with 1× PBS three times, and 100 μL 1× PBS was added to each well. Plates were scanned using an IN Cell Analyzer 2200  and the number of cells per well was recorded. In the CellTiter-Glo assay, 60 μL of CellTiter-Glo luminescent solution was added to each well after incubation with the test compounds, and the assay plate was scanned using a Tecan Infinite M1000 PRO microplate reader  to record luminescent signals. For both types of cell viability assay, dose-response curves for GLR2007 and abemaciclib were plotted, data fitted using a four-parameter logistic model in Prism 6.0 , and IC50 generated from each fitted curve.The effect of GLR2007 on cell proliferation was assessed in one mammary epithelial, 19 brain cancer, one neural, six breast cancer, 14 colon cancer, 29 liver cancer, and 21 lung cancer cell lines ; bile, urine, feces, and cage rinse/wash up to 72 hours after treatment were collected from eight bile duct cannulated (BDC) rats . Heart, lung, liver, spleen, kidneys, whole brain, stomach tract wall, intestinal tract wall, skeletal muscle, body fat, reproductive organs  were collected at 2, 6, 24, and 72 hours after treatment . The total radioactivity (TRA) of plasma, bile, urine, and cage rinse/wash samples was directly analyzed by liquid scintillation counting. Fecal and tissue homogenates and blood were combusted using a PerkinElmer Oxidizer (PerkinElmer Inc.), and the generated [14C]CO2 was captured in 14C scintillation cocktail , followed by analysis using a PerkinElmer Liquid Scintillation Counter (PerkinElmer Inc.). The TRA levels determined in bile, urine, feces, and cage rinse/wash were used to calculate the percentage of the administered dose excreted. Mean TRA values of whole brain and plasma at 2, 6, 24, and 72 hours were used to calculate the area under concentration–time curve from time zero to 72 hours (AUC0–72), using a noncompartmental model in Phoenix WinNonlin v6.3 software .To investigate the degree to which GLR2007 penetrated organs and tissues, and the levels of excretion of the compound, rats were dosed with radiolabeled GLR2007 and whole-body autoradiography was performed. Sprague Dawley rats  were maintained in humidity- and temperature-controlled conditions on a 12-hour light/dark cycle, with food  and water available ad libitum.The efficacy of GLR2007 was evaluated in human GBM and breast cancer orthotopic cell-line-derived xenografts in NOD/SCID mice  and BALB/c nude mice , and human lung, colorectal, and liver cancer subcutaneous cell-line-derived xenografts in BALB/c nude mice . Mice were maintained in humidity- and temperature-controlled conditions with food and water available 5 U87-luc tumor cells plus Matrigel  in a 4:1 ratio in PBS at the right frontal lobe. Tumor growth was quantified using intraperitoneal administration of 150 mg/kg luciferin to anesthetized mice, and tumor bioluminescence was measured using an IVIS Lumina II imaging system (PerkinElmer Inc.). In one study, mice were randomized at day 6 after tumor implantation (mean bioluminescence of 2.81×107 photons/sec), and in the other, mice were randomized at day 14 or day 15 (mean bioluminescence of 7.49×106 photons/sec).In a GBM orthotopic xenograft study, female BALB/c nude mice were inoculated intracranially at 6–8 weeks old with 3×107 MCF-7 tumor cells plus Matrigel in a 1:1 ratio in PBS at a mammary fat pad or in the right flank. Randomization was performed when the mean tumor volume reached 135–138 mm3.In two breast cancer orthotopic xenograft models, female NOD/SCID mice were subcutaneously implanted with an estrogen pellet  one day before tumor inoculation. Mice were inoculated at 6–7 weeks old with 2×106–1×107 tumor cells , or palbociclib  in vehicle control, or vehicle alone, by oral gavage . For comparison among three or more groups, a one-way ANOVA was performed. Multiple comparison procedures were applied after ANOVA when significant F-statistics (ratio of treatment variance to error variance) were obtained. Comparisons between groups were carried out using the Games test. P<0.05 was considered to be statistically significant. Survival times were analyzed using the Kaplan–Meier method, with curves constructed for each group and the log-rank (Mantel–Cox) test used to compare survival curves between groups. Body weight change was calculated based on the weight on the first day of dosing.Statistical analysis of differences in mean tumor volume among groups was conducted 50 . The IC50 value of GLR2007 showed a 33.1-fold difference, and the Ki value showed a 23.5-fold difference compared with these values in palbociclib. GLR2007 also demonstrated more potent inhibition of CDK6 enzymatic activity, compared with palbociclib , with the IC50 value of GLR2007 showing a 3.8-fold difference, and the Ki value a ~9.6-fold difference compared with these values in palbociclib.In CDK4 and CDK6 enzymatic activity assays, GLR2007 showed greater inhibition than palbociclib in IC50 fold-difference range = 0.03–6.77; median = 0.42; mean ± standard deviation (SD) = 0.70 ± 1.06). In blastoma cell lines, GLR2007 inhibited cell proliferation to an equal or greater extent than abemaciclib in 19 of 20 cell lines (95%)  = 0.65 ± 0.76). In the non-malignant MCF-10A mammary epithelial cell line, GLR2007 demonstrated less cell proliferation inhibition than abemaciclib .For cell proliferation assays, cell viability data following treatment with GLR2007 were obtained for 90 cell lines, and of these, data following treatment with abemaciclib were obtained for 86 cell lines   of radioactivity in blood, plasma, and all tested tissue was observed at 6 hours after treatment, except the stomach wall, in which Cmax was attained at 2 hours, and testis, epididymis, and kidney, which peaked at 24 hours. In whole-brain tissue, the Cmax value (1774 ± 239 ng eq/g) was 4.51-fold higher than in plasma (393 ± 46.1 ng eq/g)  was 3.97-fold higher than in plasma , and in male rats, the AUC0–72 h of whole-brain tissue  was 4.09-fold higher than in plasma (8213 h·ng eq/g).Following a single 6 mg/100 μCi/kg oral dose of [ng eq/g) Table 2.P values for TGI in this experiment (P=0.496) (P<0.0001) longer in mice treated with 50 mg/kg GLR2007, compared with vehicle controls . At equivalent doses (25 mg/kg), GLR2007 demonstrated noninferior TGI to abemaciclib and palbociclib in glioblastoma xenograft models  Table 1.P=0.037) in MCF-7 breast cancer xenografts, up to 68.9% (P<0.001) in NCI-H1975 NSCLC xenografts, up to 91.5% (P<0.001) in COLO 205 colorectal cancer xenografts, and up to 77.7% (P=0.003) in LI1088 liver cancer xenografts, compared with vehicle controls. At equivalent doses (25 mg/kg), GLR2007 demonstrated numerically greater TGI over abemaciclib and palbociclib in lung, colorectal, and liver cancer xenograft models, and over abemaciclib in breast cancer xenograft models  was 0.01 within 5 minutes after intravenous administration of 1 mg/kg , 26. Abehibitors , 27.Abemaciclib has previously demonstrated antitumor efficacy in orthotopic U87-MG GBM rat xenografts, increasing survival time by 37.4% compared to vehicle control . In thesIn conclusion, these studies suggest that GLR2007 may be as efficacious in the treatment of GBM and other advanced solid tumor cancers as the approved CDK4/6 inhibitors, supporting further investigation of GLR2007 through clinical trials. There is an ongoing debate about whether abemaciclib and palbociclib can penetrate the BBB. Previous preclinical studies have shown that abemaciclib and palbociclib penetrate the BBB and reach concentration levels in rodent brains that would be expected to inhibit the activity of CDK4/6 –23. HoweThe activity and efficacy of GLR2007 were established in tumor cell lines and mouse xenograft models . Moreover, although the relative distribution of GLR2007 to the brain is low compared to other tissues, this study shows the potential of BBB penetration and delivery to the CNS. These preclinical studies demonstrate the prospect of this novel investigational CDK4/6 inhibitor for the treatment of GBM and other advanced solid tumors. Ongoing clinical trials will establish whether these preclinical findings translate to clinical benefits for patients.in vitro data  and People’s Republic of China Ministry of Science and Technology ‘Regulations for the Administration of Affairs Concerning Experimental Animals’ (1988).LY contributed to editing the manuscript. ZY contributed to data analysis, study conduction, and editing the manuscript. YW contributed to interpretation of the study data and editing the manuscript. MM contributed to editing the manuscript. All authors contributed to the article and approved the submitted version.The study was funded by Gan and Lee Pharmaceuticals.The authors would like to thank Dr Naveen Samuel, Gan and Lee Pharmaceuticals, USA, for critical review, and acknowledge Dr Derah Saward-Arav, integrated medhealth communication (imc), UK, for medical writing support, funded by Gan and Lee Pharmaceuticals.All authors are employees of Gan and Lee Pharmaceuticals.The authors declare that this study received funding from Gan and Lee Pharmaceuticals. All authors were involved in the design of the study, collection, analysis, and interpretation of data, and in writing the manuscript.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


We analyzed the epigenomic consequences of rearrangements between the super-enhancers of the immunoglobulin heavy locus (IGH) and proto-oncogene CCND1 that are common in B cell malignancies. By integrating BLUEPRINT epigenomic data with DNA breakpoint detection, we characterized the normal chromatin landscape of the human IGH locus and its dynamics after pathological genomic rearrangement. We detected an H3K4me3 broad domain (BD) within the IGH locus of healthy B cells that was absent in samples with IGH-CCND1 translocations. The appearance of H3K4me3-BD over CCND1 in the latter was associated with overexpression and extensive chromatin accessibility of its gene body. We observed similar cancer-specific H3K4me3-BDs associated with hijacking of super-enhancers of other common oncogenes in B cell  and T cell malignancies . Our analysis suggests that H3K4me3-BDs can be created by super-enhancers and supports the new concept of epigenomic translocation, in which the relocation of H3K4me3-BDs from cell identity genes to oncogenes accompanies the translocation of super-enhancers.Chromosomal translocations are important drivers of haematological malignancies whereby proto-oncogenes are activated by juxtaposition with enhancers, often called  The human CH region encodes nine different Ig isotypes: IGHA2, IGHE, IGHG4, IGHG2, IGHA1, IGHG1, IGHG3, IGHD, and IGHM . Complex regulatory and genomic rearrangements in the IGH locus are required to ensure that Ig transcripts containing only one of each of these gene segments are expressed in each B cell at the correct stage of B cell differentiation. These natural processes predispose human Ig loci to inappropriate translocation events. As a result, these super-enhancer-rich regions are commonly hijacked in B cell malignancies, providing the optimal model in which to address whether H3K4me3-BDs are formed as a consequence of super-enhancer activity.The immunoglobulin (Ig) loci contain powerful super-enhancers to drive antibody formation and expression. The immunoglobulin heavy . We defined H3K4me3-BDs as domains with H3K4me3 >2 kb and compared them across different hematopoietic cell types . We observed shared H3K4me3-BDs in all of the cell types that were associated with basic cellular functions . Only a small proportion of detected H3K4me3-BDs were cell type–exclusive , identifying cell-identity genes  as reported by the other studies mentioned above. With recent studies observing increased interactions between H3K4me3-BD and super-enhancers . The cell type–exclusive H3K4me3-BDs  had proximal super-enhancer(s) more frequently than cell type–nonexclusive H3K4me3-BDs .H3K4me3-BDs have been defined in different ways, using size- and height-ranked . Howevernhancers , we alsoCCND1) at 11q13 and IGH at 14q32 (IGH-CCND1). To begin to understand how this translocation event leads to CCND1 activation, we characterized the epigenomic landscape in these two regions from healthy and malignant B cells. To precisely define the location and activity of the human IGH super-enhancers and promoters and the chromatin dynamics of the CCND1 locus in B cells, we used 108 chromatin state maps for different hematopoietic cell types built with over 700 ChIP-seq data sets from BLUEPRINT , Chr 14: 106,144,200–106,179,400 (Eα1), and Chr 14: 106,281,800–106,326,200 (Eμ). The Eμ enhancer showed dynamic changes associated with the B cell development stage. A larger region appears active in naive B cells before entering the germinal center (GC), whereas in post-GC B cells, the region of activity is reduced (class-switched memory B cells and plasma cells)  were found within Ca cells) . A simila cells) . None ofCCND1 is one of the most common IGH translocation partner genes in hematological malignancies, a hallmark of MCL  samples show a similar pattern to healthy B cells, with the Polycomb state domain upstream of the active promoter. DLBCL and BL samples show a narrow H3K4me3 active promoter but lack the upstream Polycomb domain. All MCL and some MM samples have a larger active promoter/enhancer region extending upstream of and downstream from the transcription start site, with most of the gene body containing H3K4me3 marks, a pattern that looks comparable to an H3K4me3-BD .We discovered a B cell–specific H3K4me3-BD at the genomic location, Chr 14: 106,346,800–106,387,800 (41 kb), overlapping the DGH locus . This elIGH translocations, we studied the MM cell line U266, in which the IGH super-enhancer Eα1 is inserted next to the CCND1 proto-oncogene . We confirmed two chromosomal breakpoints that occur in the IGHE and IGHA switch regions and result in the cut and paste of the IGH Eα1 super-enhancer into Chromosome 11, ∼12 kb upstream of CCND1 . This suggests that the inserted Eα1 super-enhancer has a bidirectional effect, generating an H3K4me3-BD over another adjacent gene.To further investigate the presence or absence of H3K4me3-BD as a result of oncogene . This ceof CCND1 . The vas66 cells . Importaene body . This ob samples , 2. This samples , as obse samples , as obseSupplemental Table S3). Two of the cell lines had an IGH-CCND1 rearrangement, including U266  and the MCL cell line Z-138. We observed the H3K4me3-BD and strong DNase I hypersensitivity signals encompassing the entire coding region of the CCND1 gene in both cell lines  and seven MM patients whose diagnostic samples were engrafted in murine models (patient-derived xenografts [PDXs]). Each cell line had a complex rearrangement identified by targeted sequencing of the IGH locus involving multiple proto-oncogenes . 10x Genome sequencing detected in patients P1 and P2 the second most common IGH translocation in MM, t, involving the transcription factor MAF. Patients P3 and P4 had IGH translocations t, involving FGFR3 and NSD2, with the remaining three patients (P5–P7) having no detectable translocation involving any of the Ig loci . No cell lines or patients had an IGH-CCND1 rearrangement detected by targeted or genome sequencing; therefore, as expected, we did not observe an aberrant H3K4me3-BD or an increase in mRNA transcript levels for CCND1 in these samples . We observed a Polycomb chromatin state over MYC, but the analysis of each histone modification separately identified an H3K4me3-BD over MYC in the two cell lines , possibly reflecting repression of one allele of MYC and activation of the other owing to being juxtaposed to an IGH super-enhancer (In the two cell lines and four of the patient samples (P1–P4), we observed an H3K4me3-BD over the coding region of  RNA-seq B. This wenhancer .MAF; however, we see overexpression of MAF in association with an H3K4me3-BD .In the remaining two patients , we were unable to detect a genomic rearrangement of a super-enhancer in close proximity to K4me3-BD B. These IGH super-enhancer. Although the chromatin state model  are also regulated by super-enhancers, undergo similar inherent somatic rearrangement events, and are involved in translocation events in T cell acute lymphoblastic leukemia (T-ALL) . The Polycomb chromatin state was observed in healthy early and late cortical T cells and CD4 and CD8A expressing T cells . To provide mechanistic data to support the generation of H3K4me3-BD by super-enhancer relocation, we used our previously CRISPR-Cas9 engineered T-ALL cell line PEER, which contains the same 12-bp insertion upstream of the TAL1 gene, resulting in TAL1 overexpression .Next, we wanted to assess whether de novo super-enhancers, generated by somatic nucleotide insertions, could also generate aberrant H3K4me3-BD. An aberrant H3K4me3-BD was observed across the e Jurkat C, where e Jurkat . No supepression . H3K4me3In summary, we found that the appearance of H3K4me3-BDs is associated with cancer-specific super-enhancer activation in both B cell– and T cell–derived hematological malignancies. Our data suggest that H3K4me3-BDs could be a signature of super-enhancer targets in general and a useful marker to identify deregulated genes affected by the hijacking of super-enhancers in cancer.CCND1 at 11q13 and the IGH locus at 14q32. We have shown that genomic relocation of the IGH Eɑ1 super-enhancer alters the location of an H3K4me3-BD in rearranged malignant B cells. The presence of broad H3K27ac domains over CCND1 have previously been associated with t translocations in MM cell lines including U266 . We also observed H3K4me3-BDs over additional proto-oncogenes rearranged in B cell and T cell malignancies, including the involvement of gene-specific and de novo super-enhancers. H3K4me3-BDs are associated with high levels of stable transcription of cell-identity and tumor suppressor genes  and chromatin remodelers (NSD2), it may not be surprising that the increased expression and presence of the translated protein could indirectly drive the appearance of H3K4me3-BD over other cancer-associated genes.We analyzed a total of 14 hemato-oncology samples, newly generated data for seven PDX samples, and seven patient-derived cell lines. Twelve of these cases were positive for a genomic abnormality involving hijacking of super-enhancers and proto-oncogene activation (the remaining two did not have these rearrangements). All 12 samples showed an H3K4me3-BD over the oncogene specific to a genomic rearrangement, confirming our hypothesis about the association of H3K4me3-BD and super-enhancers. In three of these 12 samples, additional H3K4me3-BDs were observed over other oncogenes not involved in a genomic rearrangement; however, there was no evidence of super-enhancer translocations at these loci. This could be because of unidentified chromosomal abnormalities involving other super-enhancers or by the existence of additional mechanisms associated with H3K4me3-BD formation. This is in agreement with our complementary publication by epigenomic translocation, a consequence of hijacking of super-enhancers. In this model, a super-enhancer-driven wild-type H3K4me3-BD “relocates” to a target proto-oncogene as the result of a genomic rearrangement, leading to oncogene activation , where the hijacked oncogene and super-enhancer reside . This data set was composed of 85 samples from healthy donors  and 23 samples from patients (16 primary and seven cell lines) with different B cell hematological malignancies. Five of these cell lines had DNase I hypersensitivity and RNA-seq data available . BLUEPRINT data were downloaded from ftp://ftp.ebi.ac.uk/pub/databases/blueprint/ paper_data_sets/chromatin_states_carrillo_build37 (ChIP-seq chromatin states) and ftp://ftp.ebi.ac.uk/pub/databases/blueprint/data/homo_sapiens/GRCh37 (DNase I hypersensitivity and RNA-seq). Early and late cortical T cell ChIP-seq chromatin states are accessible from GitHub (https://github.com/guillaumecharbonnier/mw-cieslak2019/tree/master/src/hub). Detailed laboratory methods and data processing of BLUEPRINT experiments are described elsewhere  were used  and CCND1 (promoter and Polycomb) loci was built using 15 BLUEPRINT B cell/plasma-cell samples derived from healthy donors . Epigenomic consensus of super-enhancers and H3K4me3-BDs at TRA/TRD and BCL11B loci was assembled using 17 BLUEPRINT T cell samples derived from healthy donors. MCL (JVM-2 and Z-138) and MM (U266) cell lines with known IGH-CCND1 rearrangements  were used to determine the relocated CCND1 H3K4me3-BD.Epigenomic annotation of IGH (overlapping the CH and IGH intronic region), TRA/TRD (constant and joining regions), and BCL11B (from the gene position up to ∼1 Mb downstream) loci. Promoters were determined as a segment >2.5 kb within the expected promoter positions of IGH (CH and intronic region) and CCND1 genes. H3K4me3-BDs were scanned at IGH CH, JH and DH, and CCND1, TRA/TRD, and BCL11B loci, with a minimum size of 15 kb. Polycomb at the CCND1 locus was obtained as regions upstream and overlapping with the promoter.Segmentation files of relevant samples were filtered for the subset of chromatin states  of interSupplemental Tables S2, S3). For this analysis, the proximity of H3K4me3-BDs (≥2 kb) to super-enhancers was compared (≥5 kb) to a control group of small promoters . Super-enhancers overlapping directly H3K4me3-BD and/or genes with H3K4me3-BD were excluded from the analysis. Also, promoters in genes with H3K4me3-BD in alternative transcription start sites were excluded. Genomic distances between H3K4me3-BD/promoters and super-enhancers up to 5 Mb were analyzed by 100-kb bins. Gene enrichment for biological processes was performed using R package clusterProfiler v3.18.0  were sequenced using targeted high-throughput sequencing covering the following genomic regions: (1) 4.2 Mb, extended coverage for chromosomal abnormality detection within IGH, IGK, IGL, and MYC (4.2 Mb); and (2) 0.6 Mb, exonic regions of 127 myeloma-specific genes for mutation analysis and 27 additional regions for efficient data normalization. GRCh37 human genome assembly was used for sequence mapping using BWA-MEM (v0.7.12). Chromosomal rearrangements were called using Manta v.0.29.6 .PDXs were generated by passaging primary patient CD138 + selected cells through the previously described SCID-rab myeloma mouse model . DetaileSupplemental Table S5) were manually inspected.DNA from seven PDX samples were sequenced using phased whole-genome sequencing (10x Genomics) at Hudson Alpha. Long ranger (10x Genomics) pipelines were used for data processing, including alignment to GRCh38 genome assembly and structural variant calling. Germline controls were used to distinguish somatic abnormalities, and chromosomal breakpoints of detected translocations , the model used in the BLUEPRINT data set . Additio2 expression calculated.RNA-seq was performed using 100 ng total RNA with genomic DNA removal using the TURBO DNA-free kit (Ambion). RNA was prepared using the TruSeq stranded total RNA Ribo-Zero gold kit (Illumina), and libraries were sequenced using 75-bp paired-end reads on a NextSeq 500 (Illumina). RNA-seq data were analyzed as previously reported . Brieflyhttps://www.ncbi.nlm.nih.gov/geo/) accession numbers GSE54379 and GSE65687, were used for histone modification analysis of three T-ALL cell lines KOPT-K1, DND-41, and Jurkat . Raw files were downloaded using the associated NCBI Sequence Read Archive  accession and converted to FASTQ files using NCBI fasterq-dump (SRA Toolkit v2.9.6-1). Appropriate sequencing runs were merged, and sequences were mapped to the GRCh37 genome assembly using BWA (v0.7.17), followed by processing to MACS2 (v2.2.5) (http://dcc.blueprint-epigenome.eu/). Histone marks H3K4me1, H3K4me3, H3K27me3, H3K27ac, and H3K36me3 in all three cell lines were used in this study, with the exception of H3K27me3 in Jurkat as this was not available.Publicly available ChIP-seq data, accessed under the NCBI Gene Expression Omnibus   peaks, uhttp://dcc.blueprint-epigenome.eu/#/md/methods). Prepared libraries were sequenced in paired-end 50 + 30 bp mode using the NextSeq 500/550 (Illumina) according to the manufacturer's instructions. FASTQ files were processed by BLUEPRINT pipeline as T-ALL cell lines above. Raw read counts were collected using the Genomic Analysis Toolkit v4.2  PEER cell lines were included. The genome editing method was published elsewhere . ChIP-sekit v4.2  in 200-bP-values < 0.05 were considered statistically significant. Figures involving data and annotation alignment to the human genome were generated using karyoploteR (v1.16.0) R package  under accession number PRJNA635269. All raw and processed ChIP-seq data for the KMS11 and MM1S myeloma cell lines, as well as the PEER T-ALL cell line, have been submitted to the NCBI Gene Expression Omnibus  under accession number GSE151556. All high-throughput sequencing data for the MM PDXs have been submitted to the European Genome-phenome Archive (https://ega-archive.org/) under accession number EGAS00001005684.The DNA sequencing data for the U266, KMS11, and MM1S myeloma cell lines generated in this study have been submitted to the NCBI BioProject database (


Objective: Erchen Decoction (ECD), a well-known traditional Chinese medicine, exerts metabolism-regulatory, immunoregulation, and anti-tumor effects. However, the action and pharmacological mechanism of ECD remain largely unclear. In the present study, we explored the effects and mechanisms of ECD in the treatment of CRC using network pharmacology, molecular docking, and systematic experimental validation.Methods: The active components of ECD were obtained from the TCMSP database and the potential targets of them were annotated by the STRING database. The CRC-related targets were identified from different databases . The interactive targets of ECD and CRC were screened and the protein-protein interaction (PPI) networks were constructed. Then, the hub interactive targets were calculated and visualized from the PPI network using the Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. In addition, the molecular docking was performed. Finally, systematic in vitro, in vivo and molecular biology experiments were performed to further explore the anti-tumor effects and underlying mechanisms of ECD in CRC.Results: A total of 116 active components and 246 targets of ECD were predicted based on the component-target network analysis. 2406 CRC-related targets were obtained from different databases and 140 intersective targets were identified between ECD and CRC. 12 hub molecules  were finally screened from PPI network. GO and KEGG pathway enrichment analyses demonstrated that the biological discrepancy was mainly focused on the tumorigenesis-, immune-, and mechanism-related pathways. Based on the experimental validation, ECD could suppress the proliferation of CRC cells by inhibiting cell cycle and promoting cell apoptosis. In addition, ECD could inhibit tumor growth in mice. Finally, the results of molecular biology experiments suggested ECD could regulate the transcriptional levels of several hub molecules during the development of CRC, including MAPKs, PPARs, TP53, and STATs.Conclusion: This study revealed the potential pharmacodynamic material basis and underlying molecular mechanisms of ECD in the treatment of CRC, providing a novel insight for us to find more effective anti-CRC drugs. Colorectal Cancer (CRC) is one of the most commonly diagnosed malignant tumors and is a leading cause of tumor-related mortality worldwide . In 2020In recent years, the value of Traditional Chinese medicine (TCM) in tumor treatment has been high-profile based on its low toxicity and multi-target activity . Severalin vitro and in vivo experiments were utilized to verify the above molecules screened by network pharmacology. This study will explore the function of ECD for CRC treatment, understand their underlying anti-tumor mechanisms, provide evidence for the application of ECD in tumor therapy, and open new horizons for therapeutic intervention in the future.TCM is characterized by multiple targets and network pharmacology is a systematic method that combines molecular biology, bioinformatics, and computer science into the pharmacological study of TCM to explore their underlying mechanisms . In thisGlycyrrhiza glabra”, “Citrus reticulata”, “Pinellia ternata” and “Poria cocos” were retrieved from the TCM Systems Pharmacology Database  (https://cn.string-db.org) (The keywords “msp.php) . Oral bi-db.org)  was used“Colorectal Cancer” was used as the keyword to search the CRC-related targets in the online Mendelian inheritance in man (OMIM) database , the datThe intersective targets were obtained between the ECD components and CRC disease targets. Then, these targets were imported into the STRING database, and the highest confidence was set as 0.9 to show the PPI network. PPI network was visualized in Cytoscape 3.9.1  softwareThe active components in ECD and the interaction targets were constructed to the active components-targets-CRC network using Cytoscape 3.9.1 software. In addition, the top five components in the Degree value of ECD were selected to proceed molecular docking.https://pubchem.ncbi.nlm.nih.gov/) (https://www.rcsb.org/) (via the DeepSite database (PubChem database (ih.gov/)  was applsb.org/) . The mecdatabase  and Autodatabase  was utildatabase .https://david.ncifcrf.gov/) (https://www.omicshare.com/tools) tools. The GO enrichment analysis includes biological processes (BP), cellular component (CC), and molecular function (MF).The GO  and KEGGrf.gov/)  and Omicrf.gov/)  (https:/Pinellia ternata (34.5%), Citrus reticulata (34.5%), Poria cocos (20.7%), and Glycyrrhiza glabra (10.3%). The ECD granules were dissolved to 0.2 g/ml in phosphate buffered saline (PBS) and filtered through a 0.22 μm pore size filter . Then the ECD filtrate was divided into several centrifuge tubes and stored at −20°C for future use.Granules of ECD were purchased from Guoyi hospital, Fujian University of TCM , composed of 2.The human colorectal cancer cell lines HT29, SW620, and DLD-1, were obtained from the American Type Culture Collection (ATCC). Consistent with the previous methods , all cel50) values of each cell line based on different concentrations and times of ECD treatment were determined using nonlinear regression. Finally, the cell viability of each cell line with low (IC25), medium (IC50), and high concentrations (IC75) of ECD treatment was also further tested in different periods.The working concentrations of ECD were diluted in complete medium to 0, 0.3125, 0.625, 1.25, 2.5, 5, 10, 20, 40, and 80 mg/ml. Three wells (repeats) were applied for each concentration and repeated at least 3 times. After the gradient concentrations of ECD treatments for 24 h, 48 h, or 72 h, cell viability assays were measured by Cell Counting Kit 8 . Then, the half-maximal inhibitory concentration .4 cells per well and cultured for 24 h. Cells were treated with the low (IC25), medium (IC50), and high concentrations (IC75) of ECD for 48 h. Then, 10 μM EdU  was added and incubated for 2 h. The remaining operations, including fixing, glycine incubating, and dilution, were performed based on the standard protocols in a light-repelled environment. The fluorescence images of these cells were captured under an inverted fluorescence microscope  and at least three random fields in each well were photographed.Three CRC cell lines were all plated on 6-well plates at 2 × 1025), medium (IC50), and high concentrations (IC75) of ECD for 48 h. For the cell cycle assay, the cells (at least 1 × 106) were fixed by 75% ethanol and stored at 4°C overnight. After washing twice with cold PBS, 300 μl PI/RNase staining  was added to each sample and incubated for 30 min at 37°C under protection from light. The cell cycle was then analyzed by flow cytometry . Similarly, for the cell apoptosis assay, both floating and attached cells in each well were harvested and washed twice with cold PBS. Then, cells were incubated with 3 μl FITC-Annexin V  and 5 μl PI  in 100 μl binding buffer at 37°C under protection from light. Next, 200 μl binding buffer was added to each sample, and cell apoptosis was also measured by flow cytometry.Three CRC cell lines were all plated and cultured on 6-well plates for 24 h and treated with the low . Seven days after cell injection, mice were randomly divided into four groups: control , ECD-L, ECD-M, and ECD-H . ECD was dissolved in a PBS solution and delivered daily by intragastric administration for 14 days. Then, tumor volumes were measured every 3 days and calculated by the formula: length × width2/2. At the end of the experiment, mice were sacrificed and tumors were photographed, weighed, and stored. H and E staining and Immunohistochemistry (IHC) of the paraffin-embedded tumor tissue sections were performed based on the standard protocols. Antibodies for IHC: p21  and p38 MAPK .Nude mice  were purchased from Shanghai Jihui Laboratory Animal Care Co., Ltd. (China). All animal experiments in this study were conducted based on the Community guidelines of the animal care and use and were approved by the Ethics Committee of Fujian University of Traditional Chinese Medicine (No. 3501020096434). For the construction of the subcutaneous xenograft mouse models, 3 × 10p < 0.05 was regarded as a statistically significant difference.All the statistical analysis was performed by the R (version: 3.4.0) and SPSS (version: 25) software for double checking in this study. All experiments were repeated more than three times, and the corresponding results were presented as means ± SD. Student t and one-way ANOVA tests were used to compare two or more groups. Categorical variables were analyzed by chi-square test. A schematic flow chart of the study was shown in 2406 CRC-related targets were obtained from four different databases, including OMIM, DisGeNet, GeneCards, and DrugBank. Besides, these targets from different databases were screened and deduplicated. A Venn diagram  was drawvia four algorithms and shown in To further explore the relationship among the 140 intersective target molecules, the PPI network was constructed by the STRING database, containing 132 nodes and 690 edges, as shown in To verify the correlation between ECD and CRC, molecular docking, a novel method, was performed by PyMOL software. The top five main active components were screened by Degree value, including Quercetin (Que), Naringenin (Nar), Licoarylcoumarin (Lic), Kaempferol (Kae), and Vestitol (Ves), displayed as 2D structure in To further explore the above molecules of the PPI network, a bubble diagram was drawn to show the results of GO and KEGG enrichment analysis concisely. The top 20 enrichment processes of GO enrichment analysis were shown in 50 values of each cell line suggest that ECD could significantly inhibit the proliferation of CRC cells in a time- and dose-dependent manner. Considering the time-preference effects of ECD, the compromised duration (48 h) has been chosen to conduct the follow-up experiments. In this study, the IC50 values for HT29, SW620, and DLD-1 cell lines were 14.80 ± 1.00 mg/ml, 14.37 ± 0.48 mg/ml and 15.19 ± 3.13 for 48 h. CCK-8 assay, colony formation assay, and EdU assays were utilized to investigate the effects of ECD on the proliferation of CRC cell lines. CCK-8 assays further showed the cytotoxicity of ECD in manners of dose- and time-dependence  were selected and treated with different working concentrations of ECD (0–80 mg/ml) for 24, 48, and 72 h respectively. As shown in pendence . ECD coupendence  and redupendence  in a dospendence . The mRNll lines . These rWith the increasing concentrations of ECD, the significant reductions in the number of CRC cell lines, abnormal cell morphology , and increasing floating cells and cell debris were observed from the light microscopy images . These fAccording to the results of network pharmacology, several key molecules  and pathways  were predicted to be underlying molecular mechanisms of ECD in CRC treatments. Surprisingly, the results of RT-PCR showed that ECD could regulate the transcriptional levels of MAPKs , PPARs , TP53, and STATs (STAT1 and STAT3) in each CRC cell line . After tin vivo, the HT29 cell xenograft tumor models were established. The results showed that ECD could significantly inhibit tumor growth in a dose-dependent manner  in TME . StudiesConsidering over-reliance on the public datasets and bioinformatics technology could destabilize the results, a systematic experimental validation was performed. In our study, ECD showed certain antiproliferative effects on CRC cells in manners of dose- and time-dependence by cell viability assay, colony formation assay, and EdU incorporation assay. In addition, our results indicated that ECD induced cell cycle arrest in the S phase of CRC cells, down-regulated the transcriptional levels of CDK1 and CDK6, and up-regulated the transcriptional levels of CDKN1A. Cyclin-dependent kinases (CDKs) are reported as cell cycle regulators and the abnormal activation of them can accelerate tumor cell proliferation . CDKN1A via the STAT3/Cyclin D1 pathway and it was the first study on the mechanism of ECD in the treatment of tumors (In spite of the fact that ECD has been widely used to treat many diseases in China, very few studies have been conducted to investigate its mechanisms of action. A previous study has shown that ECD provides therapeutic effects on obesity by regulating the gut microbiota in rats . The stuf tumors . In the f tumors . ConsistIn conclusion, based on previous studies, we have explored and supplemented several potential mechanisms of ECD in the treatment of CRC, providing biological evidence for the clinical application of ECD in tumor therapy. In addition, we also found that ECD may be related to the immunotherapy and targeted therapy for CRC based on our results . However