The measurement of biological tissues’ dielectric properties plays a crucial role in determining the state of health, and recent studies have reported microwave biosensing to be an innovative method with great potential in this field. Research has been conducted from the tissue level to the cellular level but, to date, cellular adhesion has never been considered. In addition, conventional systems for diagnosing tumor aggressiveness, such as a biopsy, are rather expensive and invasive. Here, we propose a novel microwave approach for biosensing adherent cancer cells with different malignancy degrees. A circular patch resonator was designed adjusting its structure to a standard Petri dish and a network analyzer was employed. Then, the resonator was realized and used to test two groups of different cancer cell lines, based on various tumor types and aggressiveness: low- and high-aggressive osteosarcoma cell lines , and low- and high-aggressive breast cancer cell lines . The experimental results showed that the sensitivity of the sensor was high, in particular when measuring the resonant frequency. Finally, the sensor showed a good ability to distinguish low-metastatic and high-metastatic cells, paving the way to the development of more complex measurement systems for noninvasive tissue diagnosis. Recently, techniques for measuring materials’ dielectric properties have become a pivotal issue due to their impact on scientific research, for example, for industrial, communication, and environmental applications ,2,3,4,5.Microwave sensors offer the possibility of measuring living tissue’s dielectric properties through noninvasive scattering parameters . Changesin vitro conditions, paving the way for in vivo diagnostic applications.Early tumor detection is a critical part of cancer research for reducing the mortality rates of cancers. However, due to the complex and various signaling pathways involved in cancer development, there is currently a lack of knowledge on tumor behavior ,24,25. GIn this context, here, we propose a microwave-based biosensor for the noninvasive detection of cancer cell types with varying degrees of aggressiveness. The resonator was initially designed in the CST Microwave Studio software to properly match the structure of the Petri cell dish surface. This was followed by simulation analyses which were computed to study its response, testing the proposed biosensor in air and with a common basal medium for cellular growth. Finally, the sensor was realized and tested to discriminate between two pairs of adherent cancer cell lines with varying degrees of aggressiveness.®, 60 x 15 mm) dish surface. To this end, we modified a prototype previously realized [L = 100.00 mm) comprising a circular dielectric patch element at the center (r = 20.00 mm). The sensor was designed on a 0.76 mm Rogers RO4835 dielectric layer with a dielectric constant (subε) and a loss tangent (sub (δ)tan) of 3.66 and 0.0031, respectively. The total thickness of the probe was set to h = 0.83 mm. The circular shape of the patch was chosen to guarantee the maximum symmetry below the circular Petri dish surface. It should be noted that the patch radius and the position of the SubMiniature version A (SMA) connector were crucial parameters for the optimal working of the probe, considering their strict relation with the operative resonant frequency. Therefore, we chose a patch radius (r = 20.00 mm) smaller than that of the Petri dish (pr = 25.72 mm), and the coaxial waveguide connector was soldered at the border of the patch for a good impedance. Since we expected to use this sensor in an operating frequency range of 0.001–3.000 GHz, these choices represented the optimal compromise between the resonant frequency and sensor sensitivity within the above reported operating microwave range.In this work, we proposed a circular patch biosensor to detect four cancer cell lines with different origins and varying degrees of aggressiveness in adhesion on a standard Petri | corresponding with the associated resonant frequency (rf). The operating frequency was computed through the following equation [The working principle of the probe consists of the electromagnetic field propagation through the SMA connector, thus, exciting the sensor structure and the material under test (MUT) due to resonance. The reflection coefficient-based method was chosen to evaluate the sensor’s operation by studying the minimum of the scattering parameter |equation :(1)fr=k1k1,1) at 1.84 and the effective radius (er) of the patch at 20.36 mm, and by varying the effective dielectric permittivity (eε), of note, the resulting er is slightly larger than the designed one (r = 20.00 mm) for the influence of the fringing field at the edges. Since the effective dielectric constant eε is strictly related to the radiated material, in simulation analyses we calculated this parameter considering two conditions, one with only the contribution of the probe dielectric substrate in the air (e_εsub = 3.61) and one with the presence of a MUT, namely the Dulbecco’s modified Eagle medium (DMEM) for cell growth (e_εDMEM = 5.04). Based on the literature, the relative permittivity was set at 1.00 and 80.00 for the air and the medium, respectively [By setting the first zero of the derivative Bessel function of order one (ectively . The theairε = 1.00) and with the DMEM (DMEMε = 80.00). The tests were performed in the CST Microwave Studio software and the simulations showed that the sensor produced a different output for different MUT. Considering the operative frequency band of 0.001–3.000 GHz, both curves differed from each other in the minimum of reflection coefficient (11 (f)||Sair = −11.93 dB and |S11DMEM(f)| = −15.35 dB), as well as in resonant frequency (r_DMEMf = 1.916 GHz and r_airf = 2.175 GHz). These preliminary results suggested a possible two-fold sensitivity of the biosensor in terms of signal 11 (f)|min|S and resonant frequency shift. Of note, the simulation results agreed with the theoretical results in terms of resonant frequency with a relative error of 4.2% in air, i.e., without any MUT.®, Taiwan), following the previous design specifications. The SMA waveguide connected the probe with a vector network analyzer MiniVNA-TINY for measuring scattering parameters in the operating frequency range of 0.001–3.000 GHz. The system also comprised a USB serial port, supported by the software VNA/J [re VNA/J . A plexi2. After a series of preliminary experiments, we decided to test all the cell lines 24 h after plating, which was the time of optimal compromise between good cell adhesion and cell confluence. To this end, since the four cell lines have different growth rates, for each experiment, a specific number of cells  was plated at the “time-point 0” in 1.5 mL of DMEM in standard 60 mm Petri dishes in order to achieve a comparable number of cells (7.5 × 105 < x < 9 × 105) at the time of the measurements of the dielectric properties, confirmed by cell count at the end of the test. Representative images of the tested cell lines on the day of the experiments are shown in For this work, low-aggressive osteoblast-like osteosarcoma SaOS-2 cells , high-ag® Research® plus pipette 100–1000 μL), with an uncertainty lower than 0.25% for both systematic and random errors. Eight samples were tested for each of the five conditions (four cell lines and one control), and the experiments were performed on three different days. For each sample, one single measurement was performed with the use of the above-described set-up.To evaluate the sensor capability to distinguish cell types with varying degrees of aggressiveness, we performed cellular experiments involving two pairs of cancer cell lines, namely low-aggressive SaOS-2 and high-aggressive 143B osteosarcoma cells, and low-aggressive MCF7 and high-aggressive MDA-MB-231 breast cancer cell lines. In addition, DMEM was also tested as a control. The medium volume was set equal to 1.5 mL in all the conditions and was prepared by pouring the medium into each Petri dish with successive fillings of 750 μL with a precision pipette  when removing the dishes before each measurement and then still tested on the probe.11 (f)|.|S To increase the resolution of the acquired data as much as possible, we imposed a sampling frequency of 0.5 MHz in the range from 1900.0 to 2600.0 MHz. The reflection coefficient was fitted to a Lorentzian curve (Equation (2)) using a nonlinear least squares method [A is the minimum of the curve; cx is the center at the minimum of the Lorentz curve; and lx and hx are the lower and upper bounds placed at the half-height of the curve, respectively.For each of the eight samples of the five materials under test (MUTs), we acquired and analyzed the reflection coefficient s method :(2)L(x)=11 (f)||S, the correspondent resonant frequency rf, evaluated at cx, the full width at half maximum (FWHM) and the interpolation error in terms of square error. At this point, it should be noted that we decided to employ the FWHM instead of the Q factor [By the fitting, we assessed the minimum of Q factor ,45,46, sQ factor .Data analysis was performed with GraphPad Prism 6.0.11 (f)|min|S, rf, and FWHM; the MANOVA was also weighted by the sum of square residuals (fitting error) obtained by each Lorentzian curve interpolation procedure. The univariate differences in 11 (f)|, frmin|S, and FWHM, respectively, between tumor cell lines and between days were analyzed by two-way analysis of variance (ANOVA) weighted by the fitting error obtained for each fitting procedure, followed by multiple comparisons, adjusted by Bonferroni correction.. The statistical analysis was performed with Stata 17, and the differences were considered to be significant when the p-value was lower than 0.05. For all the measured parameters, the values are expressed as mean ± SD. The coefficient of variation (CV) was computed as the ratio between the SD and the mean value, and expressed as a percentage. The overall differences in the tumor cell lines, consideringalso the day of the experiment as an additional factor on, were assessed by multivariate analysis of variance (MANOVA) based on Wilk’s Lambda test statistics, including all the parameters obtained from the reflection coefficient, namely in vitro for their dielectric properties using the proposed sensor. In the present work, two pairs of cancer cell lines with varying degrees of aggressiveness were tested FWHM (CV = 6.6%) and 11 (f)|min|S (CV = 3.3%), and an extremely low variability in the resonant frequency (CV = 0.02%). In addition, the CV computed for the resonant frequency for the four cell lines resulted almost equal or even lower than that in the DMEM, while the CV computed for the cell lines for the two other parameters resulted higher than in the control medium. p < 0.0001) difference in factors for the joint variables. This outcome indicated that either tumor or days (or both) were significant for at least one of the dependent variables, highlighting that the two factors overall influenced the measurements.p < 0.0001) influence of the day factor on 11 (f)|min|S and FHWM, highlighting that the experimental day affected cell measurements. On the contrary, the frequency variable was significantly (p < 0.0001) affected by the cell line factor but not by the day factor. This in-depth analysis revealed that frequency represents the optimal parameter to investigate differences in cells’ dielectric properties, being also robust to changes in the experimental day. To determine whether the specific dependent variables were significantly influenced by the two factors, cell line and days, we employed the two-way ANOVA test considering each of the three variables of interest separately, and the results are presented in p < 0.0001) difference between the pure DMEM and each of the tested cell lines, showing that the sensor is capable of detecting adherent cells with respect to medium only, with the resonant frequency of the medium containing cancer cells being consistently lower than that of pure DMEM. p < 0.0001) difference between SaOS-2 and 143B cell lines and between MCF-7 and MDA-MB-231 cell lines, showing the potential ability of the sensor to discriminate cell aggressiveness. Interestingly, this was obtained even if the increase in aggressiveness was associated with a different behavior in the two cancer cell types. In particular, high-aggressive 143B osteosarcoma cells showed a decrease in the resonant frequency, while high-aggressive breast cancer cells showed an increase in rf. This outcome highlighted the high sensitivity of the biosensor in terms of frequency. With regard to the difference in aggressiveness within tumors from the same tissue of origin, post hoc tests revealed a highly significant |min|S and FWHM values for all the tested groups. The results also reflect the fact that these two parameters were affected by a higher measurement variance than that reported for the resonant frequency. r)| in correspondence with the associated resonant frequency, and the full width at half maximum (FWHM). It should be noted that the biological samples cannot be considered to be reproducible samples, and the culture medium was the only material that could be employed to test measurement repeatability. The experimental results obtained with a culture medium showed an acceptable variability for all the tested parameters, with coefficient of variation (CV) values always lower than 7%, on average. However, the coefficient of variation value computed for the resonant frequency was about two orders of magnitude lower, highlighting a higher accuracy in measuring this parameter. At the same time, the resonant frequency was more robust to the changes in material under test than the |S11(f)| and FWHM, since its CV values were almost constant for all the tested cell lines. These outcomes are in accordance with the theory underlying the probe design, in which the resonant frequency is the main parameter characterizing the probe response, followed by the FHWM and 11 (f)|.min|S Finally, the resonant frequency was also more robust to potential confounding of external factors, such as the day of the experiment. As a matter of fact, the experimental results showed a significant frequency shift among each of the tested cell lines and the culture medium, and between low-aggressive and high-aggressive osteosarcoma cell lines and between low-aggressive and high-aggressive breast cancer cell lines. Interestingly, a significant frequency shift was also reported between low-aggressive osteosarcoma and high-aggressive breast cancer cell lines and between low-aggressive breast cancer and high-aggressive osteosarcoma cell lines, highlighting the ability of the proposed sensor to discriminate cancer cell line aggressiveness regardless of cancer type. Indeed, even though this result could not be generalized to other malignant cell types, further studies could be conducted to determine whether specific changes occur in highly aggressive cells that directly affect their dielectric properties. In accordance with the accuracy and robustness outcomes, the experimental results showed that the measurements of min|S11(f)| and FWHM did not allow for a precise detection of cancer cell lines, either with respect to the medium, or among the different cells.The aim of this work was to design a new sensor to assess the aggressiveness of cultured cancer cell lines, i.e., when cell–cell interactions and cell–substrate adhesion play a crucial role in their growth . To thisAs previously stated, in this work, we focused on adherent cells, to consider the cell-to-cell and cell-to-substrate interactions, while others have focused on the detection of cells in suspension in their culture medium  even a sIndeed, technologies based on the use of biosensors are rapidly spreading in the field of clinical practice and medical diagnostics thanks to their unique features. In general, biosensors are simple and disposable, usually are cost-efficient and suitable for mass production, and are especially useful to discriminate between a healthy and pathological condition through a noninvasive approach. Many works in the literature have already demonstrated the efficacy and usefulness of biosensors in some human diseases with worldwide incidence and high morbidity and mortality, such as metabolic disorders (primarily diabetes), cardiovascular diseases, and cancer ,53,54,55Our study, although it cannot yet be translated into clinical practice, provides evidence for a future investigation that should be based on primary cells from cancer biopsies. The strength of our work relies on the feasibility to discriminate between low-aggressive and metastatic cancer cells using only the measurement of dielectric cell properties. Indeed, most of the biosensors used in cancer prognosis are able to specifically recognize a cancer biomarker . HoweverIn this study, we proposed an innovative circular biosensor for detecting different adherent cancer cells based on their malignancy degree. First, the probe was designed and realized based on the shape and dimensions of a Petri dish and the operating frequency range of a network analyzer. Then, the sensor was used to evaluate the dielectric properties of four cancer cell lines deriving from different tissues of origin and with varying degrees of aggressiveness, and then compared with a culture medium. The experimental results clearly showed that the resonant frequency was the best parameter to assess differences in the dielectric properties of cell lines, as it turned out to be the most accurate and robust to cell variability and to potential confounding of external factors, such as the day of the experiment.With regard to detecting the cells’ aggressiveness, the proposed sensor could discriminate between the medium alone and each tested cell line, and between low-aggressive versus high-aggressive cell lines, both within the same type of cancer and across the two types.In conclusion, in this work, we suggested a novel resonator to discriminate different cell types, as well as the metastatic grade of cancer cells. This microwave approach offers a potential tool to support conventional diagnostic methods or in the long-term applications, particularly, for early cancer diagnosis.


Recent research has indicated that cuprotosis, or copper induced cell death, is a novel type of cell death that could be utilized as a new weapon for cancer management. However, the characteristics and implications of such signatures in cancers, especially in clear cell renal cell cancer (ccRCC), remain elusive.Expression, methylation, mutation, clinical information, copy number variation, functional implication, and drug sensitivity data at the pan-cancer level were collected from The Cancer Genome Atlas. An unsupervised clustering algorithm was applied to decipher ccRCC heterogeneity. Immune microenvironment construction, immune therapy response, metabolic pattern, and cancer progression signature between subgroups were also investigated.Cuprotosis related genes were specifically downregulated in various cancer tissues compared with normal tissues and were correlated with hypermethylation and copy number variation. Cuprotosis scores were also dysregulated in tumor tissues, and we found that such a signature could positively regulate oxidative phosphorylation and Myc and negatively regulate epithelial mesenchymal translation and myogenesis pathways. CPCS1 (cuprotosis scores high) and CPCS2 (cuprotosis scores low) in ccRCC displayed distinctive clinical profiles and biological characteristics; the CPCS2 subtype had a higher clinical stage and a worse prognosis and might positively regulate cornification and epidermal cell differentiation to fuel cancer progression. CPCS2 also displayed a higher tumor mutation burden and low tumor stemness index, while it led to a low ICI therapy response and dysfunctional tumor immunity state. The genome-copy numbers of CPCS2, including arm- gain and arm- loss, were higher than those of CPCS1. The prognostic model constructed based on subgroup biomarkers exerted satisfactory performance in both the training and validation cohorts. In addition, overexpression of the copper death activator DLAT suppressed the malignant ability, including cell migration and proliferation, of renal cell lines in vitro and in vivo. Finally, activation of cuprotosis in tumors could enhance antitumor immunity through dsDNA-cGAS-STING signaling in ccRCC.The activation of cuprotosis might function as a promising approach among multiple cancers. The cuprotosis related signatures could reshape tumor immunity in the ccRCC microenvironment via cGAS-STING signal, thus activating tumor antigen-presenting process. Upregulation of DLAT expression in ccRCC cell lines could reactivate the copper death pattern and be treated as a suitable target for ccRCC.The online version contains supplementary material available at 10.1186/s13578-022-00948-7. Even equipped with advanced diagnostic and therapeutic approaches, cancer is still the leading disease that accounts for approximately 15% of all deaths worldwide , 3. HoweCopper induced cell death is a newly discovered type of cell death that is different from apoptosis, ferroptosis, pyroptosis and necroptosis. Copper is an important enzymatic cofactor in cellular processes, but even modest intracellular concentrations could be toxic, leading to cell death. It has been recognized that the demand for copper is elevated in tumor cells relative to most other tissues, and represents a metabolic vulnerability that can be exploited by limiting copper availability . GeneticIn this study, we conducted a characterization study of cuproptosis related genes by pan-cancer analysis and stratified ccRCC patients by integrating multiomics data, including prognostic analysis, gene mutation analysis, immune infiltration analysis, and drug sensitivity analysis, and constructed a reliable risk stratification model to predict the prognosis of ccRCC patients. In addition, we identified and confirmed a promising cuproptosis target DLAT, which could function as a new therapeutic target for ccRCC.http://xena.ucsc.edu/) [https://www.ebi.ac.uk/arrayexpress/), and different stage single cell sequence data of ccRCC patients were collected from GEO . Two ccRCC single cell sequence datasets, including GSE159115 and GSE171306, were also adopted. This study also utilized several public cancer datasets, including UALCAN , TIMER (https://cistrome.shinyapps.io/timer/), TIDE (http://tide.dfci.harvard.edu/), and MEXPRESS (https://mexpress.be/) [The workflow of this study is depicted in Additional file sc.edu/) . The extWe collected 10 cuproptosis related genes according to Tsvetkov et al. Additional file https://www.gsea-msigdb.org/gsea/index.jsp) and the ConsensusPathDB (http://cpdb.molgen.mpg.de/) database [R package DEseq2 was used to identify differentially expressed genes (DEGs) between subgroups; thresholds were set at adjusted p < 0.01, and the abstract log Foldchange > 2. After calculating the DEGs, R package ClusterProfiler was used to perform Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GEVA), aiming to explain the biological function and molecular mechanism between CPCS1 and CPCS2. All gmt files used for enrichment analysis were downloaded from the MSigDB (database –15.http://tide.dfci.harvard.edu/) algorithm was used to compare immunotherapy responses between subgroups [We utilized multiple immune cell infiltration algorithms including TIMER, CIBERSORT, QUANTISEQ, MCPCOUNTER, XCELL, and EPIC to calculate cellular components or immune cell enrichment scores in ccRCC tissues –19. In aubgroups .https://cloud.genepattern.org/gp/pages/index.jsf) algorithm based on Euclidean distance [Somatic data were analyzed and visualized via R package Maftools to compare mutational patterns between subgroups . Throughdistance , 24.https://www.cancerrxgene.org/) database. R package pRRophetic was utilized to estimate the half-maximal inhibitory concentration-IC50. In addition, CellMiner (https://discover.nci.nih.gov/cellminer/home.do) and CCLE (https://sites.broadinstitute.org/ccle) databases were also introduced to compare the different sensitivities between ccRCC cell lines [Each patient was assessed for their susceptibility to molecular drugs using the Genomics of Cancer Drug Sensitivity  algorithm was further performed to select crucial signatures. Finally, a risk scoring model was constructed using the best combination of prognostic genes to screen. The JAPAN-ccRCC cohort was used to validate our risk scoring model, and patients in both datasets were divided into high- and low-risk groups based on median risk scores.RT-qPCR and immunohistochemical (IHC) staining were performed to validate DLAT expression in paired tumor and adjacent renal tissue . Primer sequences for RT-qPCR were as follows: primer for DLAT , STING, TBK1, cGAS, IRF2 and GAPDH . Antibodies of DLAT (Cat no: 13426–1-AP), cGAS (Cat no: ab252416) and GAPDH (Cat no: ab8245) were purchased from ProteinTech and Abcam Group. Ltd. The detailed procedure referred to our previous researcher’s protocols –30.6 cells per site). The tumors were dissected and photographed after approximately 4 weeks (n = 5 per group). The tumors were dissected and photographed after approximately 4 weeks (n = 5 per group). Tumor volumes were measured after tumor resection. The detailed procedure of the in vivo experiments is described in our previous study [All the cell lines used in our study, including human and mouse normal renal epithelial cell lines HK-2 and CP-M062 and cancer cell lines , were purchased from the American Type Culture Collection (ATCC). Cell lines were cultured according to the instructions. The DLAT overexpression plasmid was chemically synthesized by Shanghai GeneChem Co., Ltd. 786–0 and OSRC-2 cells were cultured in 6-well culture dishes at 60% density and then infected with DLAT overexpression lentivirus and the negative control (NC) lentivirus. All transfections were supplied with 4ug/ml polybrene  and lasted for 12 h. Screening was conducted with 2ug/ml puromycin  for 3 days to acquire stably transfected cells. QT-PCR and Western blotting were applied to verify the overexpression efficiency of the lentivirus. CCK-8 (Cell Counting Kit-8) was used to detect the difference in cell viability between the negative control and DLAT-overexpression groups. Scratch assays and Transwell migration assays were used to evaluate cell migration ability. A colony-forming experiment was conducted to determine the reproductive ability in vitro. A nude mouse xenograft tumor model assay was applied to investigate the effect of DLAT overexpression in vivo. Nude mice were given xenografts of DLAT overexpression and control 786-O cells  was purchased from BioXcell (Clone RMP1–14). ELISA kits for mouse IL6, TNF-α, IFN-γ, CXCL10 and CXCL11, and cytotoxicity assays based lactate dehydrogenase (LDH) release were purchased form Thermofisher. The cGAMP Activity Assay Kit was obtained from BellBrook. Tumor cell growth was evaluated via IVIS at 12 and 24 days after tumor cell injection. The antibodies for fluorescent dye-conjugated of flow cytometry, including CD45-BV510 and CD8-APC-Cy7, CD3-PE-Cy7, were purchased from Biolegend and eBioscience. The detailed procedure of intracellular staining can be found in each protocol. Flow cytometry analysis was performed with a FACS LSRII or Fortessa X-20  and data were analyzed by FlowJo v.10 software .+ monocytes from health donor’s peripheral venous blood, which were cultured in RPMI-1650  and IL-4(10 ng/ml)), then stimulated by lipopolysaccharide, or LPS(1ug/ml). Before co-culture, ACHN were treated with DMSO or cuprotosis inducer reagents (Elesclomol + Cucl2) at concentration of 2 μmol/L for 3 days. Then DCs were co-cultured with tumor cells pre-treated with DMSO or cuprotosis inducer reagents at a 5:1 ration in the presence of IL-4 (10 ng/ml). After 2 days co-culture, DCs were harvested to perform Western blotting, qPCR, and ELISA to quantify different level of cGAS-STING signal and immune related molecules.The optimal concentration of cuprotosis inducer reagents (Elesclomol + Cucl2) for renal cancer cell lines were identified by LDH release assay results between CP-M062 and RENCA. Dendritic cells, or DCs, were a kind gift from Department of Immunology . In detail, DCs were derived from CD146 cells per mice), respectively. BALB/c mice inoculated with RENCA were observed after 12 days; then those mice were randomized divided into three groups receiving DMSO, cuprotosis inducer reagents at concentration of 2 and 5 μmol/L, and tumor was identified at 24 days by bioluminescent imaging by IVIS Lumina K series III . After the xenografts reached a size of approximately 45 mm3, C57BL/6 mice were randomized into four groups receiving DMSO, anti-PD-1mAB, cuprotosis inducer reagents, and combined therapy (anti-PD-1 + cuprotosis inducer reagents) by intraperitoneal , respectively. After one week, all mice treated with those agents were euthanized and peripheral blood were harvested to quantity the percentage of CD45 + CD8 + T cells among different groups by flow cytometry. All those procedures were approved by the Institutional Animal Care and Use Committee at Navel Medical University.Athymic nude mice  and C57BL/6 mice (5–6-week-old) were obtained from Model Organisms . Renal cancer cells, including ACHN and RENCA treated with DMSO, ICI, or cuprotosis inducer reagents (Elesclomol + Cucl2), were injected into right flank of mice . Differences between subgroups were compared by Kruskal–Wallis test and Wilcoxon test. Differences in clinical characteristics and inhibitor response between subgroups were compared by the chi-square test. Differences in prognosis, including overall survival (OS) and progression-free survival (PFS) were compared by Kaplan–Meier method and Log-rank test. Hazard ratio (HR) differences were calculated by univariate Cox regression and multiple Cox regression analyses. Two-way p-values were taken and P < 0.05 was considered statistically significant.Copper induced cell death has gradually become the focus of attention for cancer research. We first explored the expression pattern of copper induced cell death related genes across cancers. As shown in Fig. After exploring the fundamental reasons for copper induced cell death gene dysregulation, we analyzed the effect of these genes on cancer signaling pathways. GSEA analyses indicated that copper induced cell death genes were mainly positively related to the MYC, MTOR, G2M checkpoint and oxidative phosphorylation signaling pathways, but negatively correlated with epithelial mesenchymal transition (EMT), myogenesis and TNFA—NFκB , similar to ferroptosis in cancer and normal tissues . CPI indAs we found above, copper-induced cell death-related genes were protective factors for ccRCC, which was unique and different from other cancers. Thus, we investigated the characteristics of copper-induced cell death-related genes in ccRCC. The TCGA ccRCC samples were classified into several subtypes using an unsupervised clustering method based on the expression levels of copper-induced cell death-related genes. The optimal classification method was validated, and the PAC method was used to assess the robustness of the analysis. Consequently, the TCGA ccRCC dataset was divided into two subtypes, namely, copper-pattern cancer type 1 (CPCS1) and type 2 (CPCS2) Fig. A–D. AfteSince there were differences in the copper-induced cell death profiles and clinical characteristics between the subgroups, we next investigated the biological function and hallmarks of CPCS1 and CPCS2. GO analysis demonstrated that differentially expressed genes were mainly enriched in cornified envelope, blood microparticle and lipoprotein particle in cellular component; cornification, keratinization, and epidermal cell differentiation in biological process; and serine hydrolase activity, active ion transmembrane transporter activity and anion transmembrane activity in molecular function Fig. A–C. GSEAThe tumor microenvironment (TME) and metabolic pathways were compared between the CPCS1 and CPCS2 subtypes. The CSP2 subtype was significantly activated in exosome secretion, ferroptosis and extracellular vesicle biogenesis and was inhibited in m6A methylation modification Fig. E. The TMImmunotherapy has gradually become the main characteristic of ccRCC treatment in recent years. To define the effect of copper-induced death on immune profiling, we analysed the immune infiltration environment of the two subgroups using GSVA. Immune-related genes of the CPCS2 subtype showed an overall upwards-regulated trend compared with the CPCS1 subtype. The CSP2 subtype expressed higher levels of CCL5, CCL21, CCL26, CXCR4, CXCR5, CXCR10, IL10RB, LAG3, CD276, CD48, CD70 and TCFRSF8  and CPCS2 (copper-induced cell death signature scores low groups). The CSP2 subtype shared a higher tumor mutation burden and low tumor stemness index but led to a low ICI therapy response and tumor immunity dysfunction state. Notably, activation of copper-induced cell death may reshape tumor immunity in the ccRCC microenvironment by facilitating the antigen presentation process. In addition, the prognostic model constructed based on subgroup biomarkers exerted satisfactory performance in both the training and validation cohorts. Finally, DLAT, the core gene of copper-induced cell death, could reactivate the copper death pattern and might be a suitable target for ccRCC therapy.Immunotherapy has been confirmed to be effective in many cancers, including ccRCC. However, therapy resistance diminishes the efficacy of immunotherapy, which can be alleviated by combination therapy, such as targeted therapy and gut microbiota therapy. Among them, copper-induced cell death may collaborate with immunotherapy. Intratumor copper has been shown to influence PD-L1 expression in cancer cells, which suggests that leveraging copper chelation may improve immunotherapy. Wang reported that Cu-triggered hydroxyl radicals and GSH elimination synergized with radiation therapy, remarkably enhancing dendritic cell maturation and promoting antitumour CD8 + T-cell infiltration, thereby potentiating the development of checkpoint blockade immunotherapies against primary and metastatic tumors . Based oIn addition to immunotherapy responses, copper-induced cell death is associated with the dysregulation of many signaling pathways in cancers. Our study indicated that copper-induced cell death-related genes were enriched in RAS-MAPK activation, oxidative phosphorylation accumulation, EMT inhibition and MYC pathways. Consistent with our research, many studies have identified that high copper levels in tumors can regulate kinase activity, inhibit autophagy, and regulate fat metabolism. Pharmacologic copper-chelator treatment using tetrathiomolybdate resulted in decreased tumor burden and increased survival in preclinical murine models of BRAFV600E-driven melanoma , 49. ComFor the root cause, signaling pathway dysregulations often depend on genome mutations. For copper-induced cell death-related genes, we observed that all tested samples had at least one mutation site (729/729). CDKN2A and MTF1 hold the most frequent fractions among mutated genes 54% vs 14%). CDKN2A can form complexes with CDK4 kinase to inhibit cell cycle progression. Mutation or deletion of the CDKN2A gene will relieve the checkpoint function of the cell cycle, and the cells will acquire the ability to proliferate indefinitely. A significant correlation was observed between copper-induced cell death genes and the G2/M checkpoint pathway across cancers. MTF1, a classic metal-sensing transcription factor, promoted myogenesis in response to copper . MTF1 di% vs 14%.Based on multiomics data, our study provided clues for choosing clinical treatment options. The drug sensitivity profiles were investigated between subgroups and their matched cell lines. There were certain differences in the effective targets of CPCS1 and CPCS2 subtypes, which were VEGFR/PDGFR/MET and EGFR/SRC, respectively. In the era of targeted therapy and immunotherapy, the effectiveness of these targets can provide certain clinical guidance for immunotherapy. The CellMiner database provides potential therapeutic targets for the copper-induced death subtype. For instance, although CPCS2 was less sensitive to many molecular inhibitors, the ROCK inhibitor GSK269962A displayed a unique curative effect on copper-induced death desert type (CPCS2). ccRCC is often resistant to chemotherapy. Our data suggested that the combination of paclitaxel and immunotherapy may reactivate the responses of the CPCS2 subtype to paclitaxel. Elesclomol was able to target resistant cancer cells, including cisplatin and proteasome inhibitor resistance. Antiapoptotic inhibitors of the BCL-2 family synergize with tetrathiomolybdate to induce apoptosis in melanoma cells resistant to BRAF and MEK1/2 inhibitors . MoleculFurthermore, the best risk model RCC-CUPT4 was established using Cox regression analysis. The four most relevant genes were MGAM, PTPRB, PAGE2B and RTL1. A high RCC-CUPT4 score indicated poor outcomes of ccRCC. Previous studies have shown that MGAM is closely related to cancer immunotherapy responsiveness in non-small cell lung cancer . Recent Although our study conducted genomics analysis and cell line experiments of copper-induced death, there are certain limitations. Our main findings were confirmed by bioinformatics analysis, which requires further experimental validation. The drug susceptibility of the two subtypes was different, but it also needs to be verified by subsequent animal and clinical experiments. More importantly, the prognostic model may be affected by some confounding factors, and more datasets are needed for revision and refinement.In conclusion, prior to our study, a few reports identified molecular subtypes of ccRCC based on gene expression profiles or mutational signatures , 69–71. Additional file 1: Figure S1. Workflow of this study. Figure S2. Copper-induced cell death-related genes are dysregulated in multiple cancers. (A) The expression of FDX1 in cancer and normal tissues. (B) Mutation frequencies of copper-induced cell death-related genes in multiple cancers. (C) The correlations between overall survival and methylation levels of copper-induced cell death-related genes. Figure S3. The drug sensitivity assessment of several copper-induced cell death-related genes to molecular inhibitors in cancer cell lines. Figure S4. Pathway enrichment analysis of ccRCC subtypes. (A) GSEA pathway analysis of differentially expressed genes between the two subtypes. Heatmap of tumor microenvironment-related pathways (B) and metabolism-related pathway (C) enrichment scores between the two subtypes. Figure S5. Correlation of copper-induced cell death-related gene expression and IC50 of tested drugs obtained from the CellMiner and GDSC databases (A) Drug sensitivity values in the form of normalized AUC using the GDSC renal cancer cell database. (B) Drug sensitivity values in the form of normalized AUC using the CCLE database. Figure S6. Verification of the copper-induced death-related risk model in the JAPAN-KIRC cohort. (A) Risk score analysis of patients in the JAPAN-KIRC cohort. (B) Survival analysis for OS of the two risk signatures in the JAPAN-KIRC cohort. (C) The time-dependent ROC curves for the two risk signatures in the JAPAN-KIRC cohort. Figure S7. The functional verification of DLAT. (A) The expression of DLAT in renal cancer and normal tissues. (B) The expression of DLAT in renal cancer of different stages. (C) Immunohistochemical score of DLAT in cancer and normal kidney tissues. (D) Survival analysis for PFS of DLAT expression. (E) The association between DLAT mutation and immune cell infiltration in ccRCC. (F) The association between DLAT expression and immune signatures across cancers. Figure S8. Different fluorescence and Edu level, and downregulated cuproptosis state in ccRCC malignant cells. (A)Different fluorescence and DdU positive cells (B) between NC and cuproptosis inducer treated groups, respectively.  Umap showing the cuproptosis score at the single-cell level for ccRCC. Figure S9. Impact of cuproptosis in tumor immunity of ccRCC. (A) Correlation of cuproptosis and immune infiltration degree among TCGA-KIRC, JAPAN-KIRC and Cancer cell-KIRC cohorts. (B) Schematic diagram of the activation of tumor immunity in ccRCC through cuproptosis.Additional file 2: Table S1. List of copper-induced cell death-related genes. Table S2. Clinicopathological features of different subtypes in ccRCC.Additional file 3: Table S3. Recurrent amplification and deletion regions in the two subtypes calculated by GISTIC2.0.Additional file 4: Table S4. List of 138 kinds of small-molecule drugs that could be used as potential drugs for ccRCC.


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.