Very high risk neuroblastoma is characterised by increased MAPK signalling, and targeting MAPK signalling is a promising therapeutic strategy. We used a deeply characterised panel of neuroblastoma cell lines and found that the sensitivity to MEK inhibitors varied drastically between these cell lines. By generating quantitative perturbation data and mathematical modelling, we determined potential resistance mechanisms. We found that negative feedbacks within MAPK signalling and via the IGF receptor mediate re-activation of MAPK signalling upon treatment in resistant cell lines. By using cell-line specific models, we predict that combinations of MEK inhibitors with RAF or IGFR inhibitors can overcome resistance, and tested these predictions experimentally. In addition, phospho-proteomic profiling confirmed the cell-specific feedback effects and synergy of MEK and IGFR targeted treatment. Our study shows that a quantitative understanding of signalling and feedback mechanisms facilitated by models can help to develop and optimise therapeutic strategies. Our findings should be considered for the planning of future clinical trials introducing MEKi in the treatment of neuroblastoma. Only few targeted therapies are currently available to treat high-risk neuroblastoma. To address this issue we characterized the drug response of high risk neuroblastoma cell lines and correlated it with genomic and transcriptomic data. Particularly for MEK inhibition, we saw that our panel could be nicely separated into two groups of resistant and sensitive cell lines. Genomic and transcriptomic markers alone did not help to discriminate between responders and non-responders. We used signalling perturbation data to build cell line specific signalling models. Our models suggest that negative feedbacks within MAPK signalling lead to a stronger reactivation of MEK in MEKi resistant cell lines after MEK inhibition. Model analysis suggested that combining MEK inhibition with IGF1R or RAF inhibition could be an effective treatment and we characterised this combination using phosphoproteomics by mass-spectrometry and growth assays. Our study confirms the importance of quantitative understanding of signalling and may help plan future clinical trials involving MEK inhibition for the treatment of neuroblastoma. Neuroblastoma is the most common and devastating extracranial childhood solid tumour, accounting for 15% of all childhood cancer deaths. The 5-year survival rate is 75% overall, but it is below 45% for so-called high-risk neuroblastoma that represent about 40% of patients . TelomerThis makes RAS/MAPK pathway inhibition a promising treatment option for neuroblastoma, and ALK and MEK inhibitors are already being tested in early clinical trials . HoweverResistance to targeted therapies of signalling pathways are often mediated by feedbacks that re-wire or re-activate signalling. For example, resistance to PI3K/mTOR inhibition in breast cancer is often mediated by feedbacks that lead to activation of JAK/STAT signalling . SimilarWe report here how a more quantitative understanding of feedback mechanisms might help to optimise combinatorial treatment. We used a neuroblastoma cell line panel representing the class of very high-risk neuroblastoma, which we profiled for drug sensitivity, genomic and transcriptomic alterations. We observed strong differences in the sensitivity to MEK inhibition. To arrive at a mechanistic understanding of resistance to MEK inhibition, we generated systematic perturbation data and quantified signalling using data-driven models. By this we described qualitative and quantitative differences in feedback structures that might confer the observed robustness to MEK inhibition. We then identified potential combinations capable of sensitising highly resistant cell lines to MEK inhibition, and tested these combinations systematically.We collected a panel of 9 neuroblastoma cell lines  and performed molecular profiling of these cells , using live cell imaging and computing growth rates from confluency measurements . In thisTo get insights into the underlying mechanisms of resistance to the MEK inhibitor AZD6244, we selected 6 neuroblastoma cells lines that represented the spectrum of sensitivity to MEK inhibition . Using these cell lines, we performed perturbation experiments, in which we stimulated the cells by growth factors for 30 minutes, and additionally inhibited specific pathways for 90 minutes . After pWe designed the experiments such that they probe the AKT/mTOR and MAPK signalling pathways . SpecifiOverall, the perturbation experiments yielded 240 data points per cell line, which are visualised in a heatmap in To get further insights into this high-dimensional data set, we performed principal component analysis (PCA) on the perturbation data . The PCAWhen we applied hierarchical clustering on the cell line panel, SKNSH was clustered separately, suggesting that it has a very atypical response to the perturbations, with a generally very high response to all ligands, and an especially strong response to PDGF  bottom. To get further, more mechanistic, insights into potential resistance mechanisms, we used the perturbation data to parameterise signalling models. We applied our previously developed method that has been derived from Modular Response Analysis  to fit When starting with a canonical literature network see , we obtaAll extended models had similar, but different, parameters for the inhibitor strength. However, there is a strong interdependence of the inhibitor strength and link strength downstream of the inhibitor which render comparison between those link strengths in different cells difficult see . As all When inspecting the parameters for ligand-induced pathway activation, we noticed that they reflected a strong heterogeneity in ligand response between the cell lines. Reassuringly, they matched the expression of the corresponding receptors in many cases . The parIn contrast to the receptor-associated parameters, the strength of intra-cellular kinase paths are less variable, and most paths are comparable between cell lines . The mosApart from the RAF-mediated feedback, MAPK signalling is also controlled by receptor-mediated feedbacks. In the KELLY cell line, our modelling procedure extended the model by a negative feedback from S6K to IGFR that could then explain the strong accumulation of pMEK by IGF following AZD6244 treatment . ReceptoIn summary, the signalling parameters derived from the perturbation data by our models show that cell lines diverge in receptor expression and feedback regulation, with strong multi-layered feedbacks for some of the resistant cell lines.χ2 p<0.05), but did not improve the IMR32 model  that is more pronounced in the cell lines IMR32 and KELLY compared to the other cell lines modelled, including the most sensitive cell lines CHP212 and LAN6 . We also32 model . Interes32 model . This hiTo gain a more systematic understanding of the effect of MEK and IGFR inhibition on the signalling states of the cells, we generated deep (phospho-)proteomics profiles using tandem mass-tag (TMT) based mass spectrometry , 29. We When we investigated the phosphorylation of components of the MAPK pathway more closely, we found many RAF negative feedback/crosstalk sites to be down-regulated after MEK inhibition  in both cell lines . MEK1 S2Taken together, the proteomics data is coherent with the model that MAPK signalling in N206 is controlled by a dual feedback structure involving RAF and IGFR, whereas it is mainly controlled by a RAF-mediated feedback in IMR32. It furthermore supports the notion that treatment with MEK and IGFR inhibitors would show synergy in N206.Feedback regulation is often a central aspect for drug resistance that could be overcome by a vertical inhibition strategy, where an inhibition of an upstream node prevents pathway reactivation. Based on our models, we tested if the additional application of an inhibitor targeting the feedback nodes (RAF and IGFR) would sensitise resistant cells toward MEK inhibition . We quanWhen trying to overcome the model-derived strong ERK-RAF feedback found in all three cell lines with a combination of MEK and RAF inhibition we only found a synergistic effect for two of the three cell lines (N206 and KELLY), whereas IMR32 remained resistant and no synergy could be detected. We hypothesised that this observed resistance in IMR32 might be either because the vertical inhibition by MEKi and RAFi was molecularly not effective or that IMR32 might no longer depend on ERK signalling for survival and growth. To distinguish the former from the latter we decided to compare model simulation and measurements for perturbation effects of selected inhibitor combinations on pMEK and pERK in IMR32 and KELLY cells.Based on the model simulations, in both cell lines the vertical inhibition of MEK + RAF inhibitor was predicted to suppress MAPK signalling much stronger than MEK inhibitor alone or in combination with an ERK inhibitor. Moreover, the suppressive effect was predicted to be even more profound in IMR32 than in KELLY  left. WeAs both KELLY and N206 have strong multi-layered feedbacks , we alsoNeuroblastoma is a complex disease with distinct subtypes that display radically different outcomes, ranging from spontaneous regression in low-risk groups to only 50% survival of patients in the high risk neuroblastoma group. Mutations in RAS/MAPK signalling are a hallmark of high risk neuroblastoma, and also define a subgroup of patients with ultra-high-risk neuroblastoma and an even worse survival. Therefore targeted treatment might be a valid strategy to treat those patients. However, response to MEK inhibitors are very variable, and it is thus important to understand mechanisms of resistance and how to circumvent these.In this work, we explored how a more quantitative understanding of signalling can be used to design combinatorial treatments to counteract drug resistance. We used a panel of deeply profiled cell lines representing high risk neuroblastoma and showed that the response to MEK inhibitors is variable, with some cell lines responding at low doses in the nM range, whereas others are highly resistant. By using signalling perturbation-response data, we characterised the signalling network surrounding MAPK. Analysis of that perturbation data with the modelling framework of modular response analysis unveiled that MAPK signalling is controlled by a multi-layered feedback with variable strength. A central finding was that MEK-inhibitor sensitive cells are controlled by low feedbacks within the MAPK cascade, whereas a subset of resistant cell lines shows strong multi-layered feedbacks that may be causal for resistance. Simulation of cell-line specific models suggested that different combinations of inhibitors can be used to overcome resistance, and experiments could confirm these predictions in two out of three cell lines.Our work highlights that systematic perturbation data are a powerful source to probe intracellular signalling pathways. The connectivity of signalling pathways implies that minor quantitative alterations of the network can lead to many changes in response, not all of which alter the phenotype. In this work, we saw that multivariate analysis of the perturbation data alone was not fruitful to separate cell lines with respect to their drug sensitivity. In contrast, integration of data by models highlighted that variations of only a few links is enough to explain the differences between those cell lines. Modelling was therefore key to integrate the data and to unveil feedback loops as potential sources of resistance.In our work we used a maximum likelihood version of MRA, but there are multiple other methods that might be suited to reconstruct semi-quantitative signalling networks from perturbation data.  proposedDrug resistance to targeted therapies have been attributed to negative feedback loops in multiple tumours. Most importantly, sensitivity to MEK inhibitors is strongly influenced by a pathway-intrinsic feedback, where ERK phosphorylates RAF at multiple sites –17. ThisOur modelling analysis suggested that some neuroblastoma cell lines possess two major layers of feedback in MAPK signalling. One of these feedbacks is pathway-intrinsic (from ERK to RAF) and one is a feedback to the IGF receptor. Interestingly, different cell lines show different relative strength of feedbacks from ERK to RAF and IGFR, and simulations show that those require different strategies for vertical inhibition. For the cell line KELLY, modelling unveiled an extremely strong negative feedback from ERK to RAF. This suggests that a combination of MEK and RAF inhibitor will be more potent than a combination of MEK and IGFR inhibitor. In contrast, in the cell line N206, both feedbacks have similar strength, suggesting that both combinations might be potent. In line with these predictions, experiments showed that in KELLY indeed the combination of MEK and RAF inhibitors is much more potent to reduce growth compared to the combination of MEK and IGFR. In contrast, in N206 both combinations reduce growth.Our phospho-proteomics analysis shows that the combination of MEK and IFGR also has different effects in the two cell lines: Whereas it shows clearly synergistic effects of the combination in N206, there is no sign of synergy in IMR32. By aggregating the phosphoproteome to kinase activities using kinase enrichment scores, one can also get insights into the re-wiring of signalling after perturbation. In our case, it clearly shows how the re-activation of RAF after MEK inhibition is inhibited by the treatment with IGFR inhibitors, and IGFR and MEK inhibitors synergize in reducing AKT activity in N206. The phosphoproteome also showed that the dual treatment of IGFR and MEK manifests itself in synergistic downregulation of important proteins that are regulated by convergent signalling of MEK and AKT, such as MYCN and EIF4B.Interestingly, a third resistant cell line, IMR32, showed no response in growth to MEK inhibitor in vertical combination with either RAF and/or IGFR inhibitor on growth, even though it’s cellular ERK signalling was strongly responsive. This highlights that cancer cells might lose ERK-mediated cell cycle control, suggesting that coupling of cellular phenotype to signalling pathways is not necessarily strict , 41. To in vivo and whether they could explain relapses. Our description of the wiring of the RAS/MAPK pathway in neuroblastoma will support the design of clinical trials using combinatorial treatments to prevent or overcome therapy resistance. In addition, the framework described here could be used to analyse signalling in tumours of individual patients While it will be technically challenging to assess signalling network responses in tumour patients, ex vivo cultures—so-called avatars—could be an option createModrylation , i.e acthttps://www.genome.jp/kegg/pathway/hsa/hsa04010.html and https://www.genome.jp/kegg-bin/show_pathway?hsa04151) with intermediate nodes suppressed, the addition of the well documented ERK->RAF feedback and all receptors corresponding to RTK. Each cell line was fitted first on the literature network, then we extended the networks independently using a greedy hill climbing approach, until no significant link could be added. We then performed successive rounds of reduction to identify the non-significant links. Most removed links relate to receptor connections. Only three connections not related to receptors were removed during this procedure, each for one cell line only. To facilitate model comparison, these links were ultimately retained in the model, as otherwise the model parameters would not be comparable. Those models with final topology yielded similar values for the inhibition parameters so we generated new models with those parameters fixed to the mean value across all 6 models and re-fitted each cell line with inhibitor values fixed. With this fitting strategy the links between models became directly comparable as the non identifiability induced by the inhibitor parameters was removed  and blocked for 30 minutes in 1:1 PBS:Odyssey blocking buffer. The primary antibodies were incubated overnight at 4C one at a time and the corresponding secondary during the following day for 2h at room temperature in 1:1 PBST/Odyssey. We used the following primary antibodies: pIGF1R betaY1135/Y1136 1:1000 (CST 3024), pAKT S473 1:2000 (CST 4060), total MYCN 1:200 (Santa Cruz sc-53993) and pMEKS217/S221 1:1000 (CST 9154).Cells were grown to confluency for 3 days in full medium and treated with AEW541 10μM and/or AZD6244 10μM or control DMSO for 4h.For the proteomics and phosphoproteomics cells were grown to confluency for 3 days in full medium and treated with AEW541 106. The top 20 most intense precursor ions with charges from +2 to +6 were selected for fragmentation with an isolation window of 0.7 m/z. Fragmentation was done in an HCD cell with a normalised collision energy of 30% and analysed in the detector with a resolution of 45 000 (200 m/z), AGC target value of 105, maximum IT of 86 ms. We used the same parameters for phosphoproteome analysis with the exception of MS2 maximum IT that was set to 240 ms.We used an adapted version of the TMT workflow : samplesThe acquired raw files were analysed using MaxQuant v1.6.10.43 , with TMlimma package  A letter containing a detailed list of your responses to all review comments, and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. 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If you believe any reviews to be missing, please contact [LINK]Reviewer's Responses to QuestionsComments to the Authors:Please note here if the review is uploaded as an attachment.Reviewer #1: In this paper the authors investigate mechanisms of drug resistance in a panel of high risk neuroblastoma cells focusing on the ERK pathway that is frequently altered in high risk neuroblastoma. They use a combination of experimental perturbation data and an elegant mathematical method to reconstruct signaling networks in order to decipher molecular mechanisms of drug resistance. Surprisingly, rather that linked to genetic mutations drug resistance seems mediated by differential network topologies in particular different feedback loops. While not entirely new, this finding is an important contribution to the growing case that network adaptations can be responsible for drug resistance in cancer and that we need to look beyond genetic mutations. Overall, the paper is well conceived, and the combination of experimental work and mathematical modelling is convincing. I am happy to recommend publication, but have a few comments that should be addressed.Major commentsAs negative feedback loops are ultimately made responsible for the differences in drug resistance, it would strengthen these conclusions by showing more evidence of their direct involvement. For instance, one would expect phosphorylation sites to change that mediate these feedback in a manner that correlates with the feedback strengths. These data seem to be there, but summarizing them in a figure would make the message clearer. Also, mutants that break the feedback could be used to show that is really the feedback that mediates drug resistance.Fig. 6B. The authors claim a “strong synergistic effect of the combination of MEK and IGFR inhibitions on growth 291 in N206 but little in KELLY or IMR32.” This is not apparent from the figure. A formal measure of synergism should be used, such as the Chou-Talalay method or Loewe isoboles.Fig. 6D. These data are not very convincing. The triple drug combination does not seem to be more potent than the dual combinations. This figure need error bars and a proper statistical comparison.Minor commentsThe MYN amplification status of the cell lines should be reported.“A strong RAF-mediated feedback is a known resistance mechanism against MEK inhibitors , …” should also cite Sturm et al. 2010.“… a known nexus between AKT and MAPK signalling (?).” Please supply the citation.https://doi.org/10.1016/j.ccr.2014.07.015). However, here the authors associate the de-phosphorylation of this residue with lower MYCN protein levels. Would be worth discussing or mitigating this claim as it is only based on a correlation.MYCN phosphorylation on S62 has been linked to enhanced degradation using phosphosite mutants , at least for MEKi.- Supplementary Figure2: Which method was used to calculate the correlation? As mutation data are qualitative (or at least Boolean), Pearson’s correlation is maybe not the best method to apply here. The authors should add more details about this and perhaps try other methods, like non parametric tests, to infer association between IC50 and mutations.- Line 94-96: “To get insights into the underlying mechanisms of resistance to the MEK inhibitor AZD6244, we selected 6 neuroblastoma cells lines that represented the spectrum of sensitivity to MEK inhibition ”, the period at the end of the sentence is missing.- Page 9, line249: What does the (?) stand for?- In figure 5 part C legend: there is a typo on phosphopeptides- Supplementary Figure 3: Is it really adjusted p>0.95? In the text it is written 0.93 and 0.94 for 1000 most variable genes and GO signal transduction genes respectively. Please double check.- Supplementary Figure 4,5,9: color code is missing-Supplementary Figure 17: Gene-sets should be re-ordered according to the GeneRatio to better see the ranking.**********Have the authors made all data and (if applicable) computational code underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data and code underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data and code should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. 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Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript.If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. 27 Sep 2021AttachmentReviewer_response-2.pdfSubmitted filename: Click here for additional data file. 1 Oct 2021Dear Dr. Blüthgen,We are pleased to inform you that your manuscript 'Neuroblastoma signalling models unveil combination therapies targeting feedback-mediated resistance' has been provisionally accepted for publication in PLOS Computational Biology.Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. 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We examined the 12C radioresponse of five HNSCC cell lines, whose surviving fraction at 3.5 Gy ranged from average to resistant when compared with a larger panel of 38 cell lines to determine if 12C irradiation can overcome X-ray radioresistance and to identify biomarkers predictive of 12C radioresponse. Cells were irradiated with 12C using a SOBP with an average LET of 80 keV/μm . RBE values varied depending upon endpoint used. A 37 gene signature was able to place cells in their respective radiosensitivity cohort with an accuracy of 86%. Radioresistant cells were characterized by an enrichment of genes associated with radioresistance and survival mechanisms including but not limited to G2/M Checkpoint MTORC1, HIF1α, and PI3K/AKT/MTOR signaling. These data were used in conjunction with an in silico-based modeling approach to evaluate tumor control probability after 12C irradiation that compared clinically used treatment schedules with fixed RBE values vs. the RBEs determined for each cell line. Based on the above analysis, we present the framework of a strategy to utilize biological markers to predict which HNSCC patients would benefit the most from 12C radiotherapy. Head and neck squamous cell carcinoma (HNSCC) is the sixth most common malignancy worldwide. Thirty percent of patients will experience locoregional recurrence for which median survival is less than 1 year. Factors contributing to treatment failure include inherent resistance to X-rays and chemotherapy, hypoxia, epithelial to mesenchymal transition, and immune suppression. The unique properties of  The potential therapeutic advantage of particle radiotherapy was recognized in the 1940s and was based upon the physical properties of the energy deposition patterns of said particles. Since that time, particle therapy has continuously developed predominantly based upon advances in engineering, imaging, and physics. The first dedicated clinical heavy ion therapy center was opened in 1994, and this facility focused on the use of accelerated carbon ions because of the physical and biological advantages over photons and protons including steeper lateral dose penumbra at greater depths in the body, a higher LET which results in a higher relative biological effectiveness (RBE) and took into account the experience gained at the Lawrence Berkeley Laboratory where the initial results for the use of heavy charged particles as a cancer therapy took place  has been used against intracranial cancers, head and neck cancers, primary and metastatic lung cancers, gastrointestinal tumors, sarcomas, prostate cancer, breast cancer, and pediatric cancers at what has grown to become 12 carbon centers across the globe, although none currently exist in the USA. CIRT has been shown to exert a strong antitumor effect in tumors resistant to conventional photon therapy; however, some tumor sites have been less amenable to therapy over concerns for the response of adjacent normal tissues. Whereas, the efficacy of CIRT has been shown for nonsquamous tumors like mucosal melanomas , 6, aden12C ions against head and neck squamous cell carcinoma (HNSCC) of the oral cavity, larynx, pharynx, and nasopharynx in a fashion that is beneficial for sparing organs at risk such as tissues of the oral cavity, the spinal cord, or bony structures like the mandible and vertebrae has been considered and acted upon. For example, the multi-institutional in silico trial designated ROCOCO describes the benefits of particle therapy and in particular CIRT, in a trial of reirradiation for recurrent HNSCC  tumors. Furthermore, identification of patients as potentially radioresistant by omics or other analysis that requires tumor sampling, is less complicated in H&N cancers based upon ease of access to tumor tissue.p < 0.01) conferring a 9-fold greater risk of mortality at 2 years. Furthermore, using a battery of HNSCC cell lines, tumor growth and metastatic potential were determined in an orthotopic model of oral tongue cancer, including how TP53 mutations influence tumor growth and metastasis  supplemented with 10% Fetal Plus brand fetal bovine serum , penicillin/streptomycin solution . All cell lines were authenticated by genotyping and validated as negative for mycoplasma contamination by the Molecular Diagnostics Core Services at the Dana Farber Cancer Center, Boston, MA. All cell culture was conducted in incubators at 37°C in ambient 5% COAn expression microarray dataset (GEO accession number GSE 67614) that was generated from 102 tumor samples collected from patients treated with a consistent protocol of surgery followed by radiotherapy based upon a prospective trial that evaluated pathologic risk features, total combined treatment duration, and postoperative radiation therapy  was used137Cs-sourced irradiator or at the MD Anderson Cancer Center using the “NASAtron” 137Cs irradiator. Dosimetry for these sealed source irradiators was validated on an annual basis. Briefly, for the J. L. Shepherd, irradiator cells in culture were placed on a 360° platform revolving at 13 RPM, irradiated, removed from the irradiator, and immediately returned to the incubator. For the NASAtron irradiations, the source was vertically above the stage and there was no sample rotation. Both devices had dose rates of ~3.25 Gy/min.Photon irradiation was conducted at the University of Texas Southwestern Medical Center using a J. L. Shepherd sealed horizontal 12C irradiations took place at the Centro Nazionale di Adroterapia Oncologica (CNAO) facility in Pavia, Italy. Cells were irradiated in T12.5 cm flasks while immersed in a water bath at 37°C using CNAO’s clinical, therapeutic quality, pencil beam scanning 12C-ion beam. A spread-out Bragg peak (SOBP) was created to assure a homogenous ( ± 2.5%) physical dose. The beam quality has been previously characterized  Using 2% FBs for such a limited time had no effect on cell growth or radioresponse.Following incubation, cultures were rinsed with phosphate-buffered saline at a pH of 7.4 and fixed in a solution of 0.5% crystal violet and 10% methanol in water. After staining and drying, colonies were counted to determine the number of surviving cells following irradiation. Only colonies identified as having more than 50 cells per colony were scored as surviving, and the surviving fraction was determined by dividing the number of colonies by the product of the plating efficiency of the cell line multiplied by the number of cells seeded.d is the dose per fraction and a, b, and c are parameters determined using a curve fitting algorithm  Model as described in Equation 1 where lgorithm .The γ-ray survival assays were performed at least twice for each cell line. If the coefficient of variation at 2 Gy was greater than 25%, they were repeated.137Cs exposures (reference) to that same radiosensitivity value determined from 12C exposures (test) as in Equation 2.RBE values were calculated by comparing a radiosensitivity value from Radiosensitivity parameters included:10% was calculated using values generated with the RCR model as described in Equation 1.The dose at SFuation 3 .Here, D0, represents the linear portion of the RCR fit located at the distal end of the survival curve. D0 was calculated by plotting the linear portion of the RCR line of best fit in MATLAB and using a linear to calculate the slope. The relationship between the slope of the linear portion and D0 is given in Equation 4.The limiting slope, In vitro transcription was done to synthesize biotin-labeled cRNA using T7 RNA polymerase. The cRNA was column purified and then checked for size and yield using the Bio-Rad Experion system. A total of 1.5 µg of cRNA was hybridized for each array using the standard Illumina protocols with streptavidin-Cy3  being used for detection. Slides were scanned on an Illumina Beadstation. Summarized expression values for each probe sets were generated using BeadStudio 3.1 .The tumor data set was generated using Illumina Whole Genome HumanWG6 v2 arrays (GEO accession number GSE67614). The v3 Illumina Expression BeadChip was used to generate transcriptome profiles for the HNSCC cell lines. Each RNA sample with 0.5 µg of total RNA was amplified using the Illumina TotalPrep RNA amplification kit with biotin UTP (Enzo) labeling. The Illumina TotalPrep RNA amplification kit uses T7 oligo(dT) primer to generate single-stranded cDNA followed by a second-strand synthesis to generate double-stranded cDNA which is then column purified. The Illumina BeadChip expression data were background subtracted and quantile–quantile normalized across samples using the MBCB algorithm –29. Normp-values generated from an F-test using the R limma package. The top-ranked genes corresponded to those that significantly changed in more than one of the radiosensitivity groups. Feature selection was performed by incrementally expanding the gene list from 4 to 500 from the top of the gene ranking. Classification models were built using a support vector machine (SVM) algorithm and the models were validated using a 10-fold repeated cross-validation.The gene expression values from 38 HNSCC cell lines were ranked by p-values calculated from moderated t-test using the R limma package. The R limma analysis was performed to compare resistant cell lines vs. other cell lines or tumors where there was local recurrence (LR) vs. tumors where there was NED in patients treated with postoperative radiotherapy. A false-discovery rate (FDR) <0.4 was used as a cutoff for significantly enriched pathways and then interrogated against the GSEA Hallmark Pathways by Leading Edge Analysis for pathway enrichment using the metrics of p-value, FDR, and Normalized Enrichment Scores, whereas the IPA analysis focused on pathways were enriched based upon a Fisher’s test with a p-value of 0.05 used as a cutoff. Z-scores for these pathways were then calculated with negative scores representing downregulation and positive scores representing upregulation of a given pathway.Functional pathway analysis was performed using the Gene Set Enrichment Analysis (GSEA 4.0.1) and Ingenuity Pathways Analysis (IPA) online software packages. Genes were ranked by Equation 5 where Nvox is the number of voxels in an in silico tumor, iN is the number of cells in voxel i, and i,j S is the surviving fraction in voxel i at fraction j with dose d, oxygen partial pressure 2pO, and LET L.The calculation of tumor control probability (TCP) is adapted from Antonovic et al.  and is s3) was assumed to contain 108 cells distributed equally across the voxels in the in silico tumor simulation. The survival model utilized is the Repairable Conditionally Repairable (RCR) model which can account for changes in survival due to dose, LET, and partial oxygenation, as shown in Equation 6.A spherical tumor with a radius of 0.6203 cm  was determined based upon the fitted values for SF2 and SF3.5 from the survival curves. The cell lines were clustered into four groups based upon Euclidean distances using the SF3.5 values for each cell line as depicted in A collection of 38 HNSCC cell lines was tested for radioresponse To determine whether there were differences in gene expression underlying these radiosensitivity cohorts, an SVM model was trained using the most significantly changed genes. As depicted in Z-scores.GSEA and IPA were used to examine differences in Hallmark Pathways (GSEA) and canonical pathway signaling (IPA). As shown in These same pathways were then interrogated in a gene expression dataset derived from 102 flash-frozen HNSCC tumor specimens from patients treated by postoperative radiotherapy (PORT) using a consistent treatment protocol , 32, 33.12C radioresponse of five HNSCC cell lines whose SF3.5 ranged from average to resistant when compared with the larger panel of 38 cell lines to determine if 12C irradiation can overcome radioresistance. Radiation survival curves were generated using 137Cs as a low LET radiation and 12C ions were generated by the Carbon Therapy Center in Pavia, Italy (CNAO). The cell lines SqCC/Y1 and UMSCC1 were chosen to represent the range of SF3.5 in the MR group with an emphasis on the high end of response; HN31 represents the highest SF3.5 in the MS cohort; and HN5 and SCC9 represent the R cohort. Survival curves for these cell lines are seen in 12C ions was calculated at: 10% survival; by mean inactivation dose D0) for each cell line. Those values are found in Next, we examined the lgorithm ; D¯ us12C ions from the five HNSCC cell lines, TCP curves were generated based upon Antonovic etal. (12C) were based upon schedules used in recurrent H&N cancers treated at the Shanghai and Heidelberg Heavy Ion radiotherapy facilities  by reirradiation for recurrent HNSCC with CIRT developed little in the way of either acute or late severe (>Grade III) toxicity  using a 12C ions. Radioresistant HNSCC can be manifested via a number of mechanisms, the predominant mechanism being hypoxia, but resistance may also be through acquired mechanisms of enhanced DNA repair, abrogation of apoptosis or through the development of a tolerogenic immune environment. 12C ions—or for that matter other ions separately or in combination—should at least partially overcome these limitations.The comparable overall improvements in late normal tissue toxicities in H&N cancers treated with CIRT suggest the potential for overall improvements in outcome in primary and recurrent disease as well as the potential for dose escalation in tumors identified as radioresistant. Also, given the limitations of access, if patients with tumors that are radioresistant can be identified, the argument could be made to treat those patients where possible with via clonogenic survival. Basal gene expression analysis was then tested as a surrogate for clonogenic survival and found to be capable of segregating the most radioresistant cell lines from the other cell lines. Furthermore, the gene expression patterns in these radioresistant cell lines supported their classification as radioresistant. Besides identifying some of the more commonly identified genes and pathways associated with radioresistance, one of the more intriguing finds is the increased expression of the GAGE genes. These genes are not expressed in normal tissue with the exception of testes. In tumors, members of this family (GAGE1 and 2) are CD4+T cell antigens, attracting T cells into tumors. GAGE12 family members have been shown to increase both radio- and chemoresistance and metastasis  for dose equivalent, dose equivalent for 12C radiotherapy is described as GyEq, GyE, or GyRBE because there is no unit definition for dose equivalent in a deterministic setting. GyEq relies on the determination of the RBE for a given endpoint. The earliest determinations of RBE, still used today, were based upon cell survival in mostly rodent (CHO) cell lines and the human radioresistant salivary tumor cell line HSG, which was determined to be contaminated with HeLa cells (12C scattered beam at NIRS was normalized to the dose-averaged LET at 80 KeV/µm using their clinical neutron RBE of 3.0 as they were equally effective (12C RBE in a small cohort of moderate to radioresistant cell lines using multiple endpoints and then applied the survival and RBE values to model tumor control probability and asked whether individualization of RBE could be consequential when compared to a generic value.Assuming that one will be able to identify radioresistance so that patients could be triaged to receive La cells , 54. Theffective . This alffective , 30, 56.12C, because this is GyE and uses a more conventional fraction size, is comparable with the conventional 2 Gy/fraction regimen. The SabR approach with 12C ions may be more effective for carbon ions but suffers the same complications as a conventional SAbR approach within the radioresistant subset.12C physical dose and it is consequential in that it reflects the need to understand the intrinsic radioresistance for a given tumor. Those values of “underdosing” at a TCP of 70% are given in In 12C and because HNSCC outcomes have seen little improvement. At least for cell lines, gene expression was able to segregate radioresistant tumor cell lines from cell lines less resistant. One could argue that 38 cell lines do not bring enough diversity of radiosensitivity as the most radioresistant cell lines were few in number. Also, while there was overlap in the enrichment of specific pathways in common between cell lines and tumors that were treated with PORT, it is evident that much work is needed, irrespective of the gene expression analysis.In this manuscript, we have attempted to draw attention to the need for individualizing therapy based upon the intrinsic radioresponse of a tumor. Head and neck squamous cells were used because of the recent trials where HNSCC are being treated with 12C exposures. This exercise highlighted the potential for underdosing radioresistant tumors when generic rather than personalized RBEs were used, which would negate the impact of triaging patients with radioresistant tumors.Using five cell lines whose radiosensitivity ranged from moderate to resistant across the 38 cell line panel, the potential impact of intrinsic radiosensitivity was tested by determining TCP curves using various radiation regimens for both γ-ray and 12C ions with different dose and fractionation schedules and a realistic understanding of the impact of tumor hypoxia to challenge and ultimately improve upon the biophysical modeling of CIRT with the intent to ultimately personalize therapy.We understand that our TCP calculations reflect fully oxygenated tumors, did not reflect tumor response to varied LETs, etc., but our goal is more one of relative comparisons and not necessarily quantitative comparisons. What we require are data from actual tumors treated with curative intent using X-rays and The original contributions presented in the study are included in the article/supplementary materials. Further inquiries can be directed to the corresponding author.MS conceived of and carried out experiments, wrote the manuscript, and led the research program. AD conceived of and carried out experiments, edited the manuscript, and participated intellectually. AP was responsible for radiation physics, helped develop the beam configuration, and wrote a portion of the manuscript. DS was partly responsible for designing and carrying out experiments. MC was responsible for 12C dosimetry, developing the SOBP for CNAO, and all physics aspects of 12C irradiation. AF was the CNAO biology contact person. She helped facilitate experiments and helped with the design of our irradiation setup at CNAO. JY was responsible for collecting the panel of H&N tumor cell lines, designed and carried out experiments to determine the X-ray survival parameters for these cells, and provided DNA and RNA for omics analysis. EP carried out additional survival X-ray survival curves, plotted all data, and calculated survival fits and tumor control probability curves. BS conceived of and carried out both X-ray and 12C experiments. He was involved in the interpretation of data and wrote sections of this manuscript. LD was responsible for all omics analysis, interpretation of that data, and wrote sections of the manuscript. All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.Funds were provided through the Department of Radiation Oncology Seed Grant Program to MS as well as the David A. Pistenmaa M.D., Ph.D. Distinguished Chair in Radiation Oncology to MS. The funders were not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.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.


The annual number of cancer deaths continues increasing every day; thus, it is urgent to search for and find active, selective, and efficient anticancer drugs as soon as possible. Among the available anticancer drugs, almost all of them contain heterocyclic moiety in their chemical structure. Xanthone is a heterocyclic compound with a dibenzo-γ-pyrone framework and well-known to have “privileged structures” for anticancer activities against several cancer cell lines. The wide anticancer activity of xanthones is produced by caspase activation, RNA binding, DNA cross-linking, as well as P-gp, kinase, aromatase, and topoisomerase inhibition. This anticancer activity depends on the type, number, and position of the attached functional groups in the xanthone skeleton. This review discusses the recent advances in the anticancer activity of xanthone derivatives, both from natural products isolation and synthesis methods, as the anticancer agent through in vitro, in vivo, and clinical assays. Cancer is one of the most fatal diseases in the world. Cancer mainly occurs due to gene mutations, and the condition is worsened by other carcinogenic agents. Both gene mutations and carcinogenic agents then influence and change the cell functions and metabolism, and thereby, the replication and spread of cancer cells are uncontrolled. The cancer cells grow and multiplicate rapidly, thus crowding the other normal cells . In someThe research on anticancer drug design and development is an urgent need, because people are suffering and the number of death cases is unstoppable until active, selective, and efficient anticancer drugs are found ,6,7. CanGentiana lutea in 1821. Xanthone with an IUPAC name of 9H-xanthen-9-one is a heterocyclic compound with a dibenzo-γ-pyrone framework, with a basic molecular formula of C13H8O2 + and [M + 2]+ in 3:1 and 1:1 ratios, respectively. In contrast, elucidation of fluoro- and iodo-substituted xanthones from their MS spectrum is difficult, as both halogen atoms are only found as a single isotope. Therefore, fluoro- and bromo-substituents in xanthones can be observed using the 19F-NMR and 127I-NMR techniques, respectively xanthone structure seemed to be critical for the anticancer activity against these cell lines [In 2008, Varache-Lembège et al. synthesized several xanthone derivatives and evaluated their anticancer activity. Among the prepared xanthones, compound ectively . On the ll lines . It was ll lines .4 exhibited the best anticancer activity, as measured by inhibitory activity (3.57–20.1 µM) against the aforementioned cancer cells. For a specific MGC-803 cancer cell, compound 4 exhibited a time-and dose-dependent proliferation inhibition. For a concentration greater than 1.0 µM, MGC-803 cells viability decreased significantly, due to lower mitochondrial membrane potential and intracellular calcium leading to the apoptosis mechanism [In 2014, Yang et al. examined the anticancer activity of several synthetic compounds based on 1,3-dihydroxyxanthone against CNE, MGC-803, Bel-7402, and A549 cell lines. It was reported that mono- and dioxygen functional groups were pivotal for the inhibitory activity against protein kinases. The presence of the aminoalkoxy group showed the increment of anticancer activity, while the introduction of the bromoalkoxyl group did not improve the anticancer activity. When the terminal amino group was quaternary ammonium salt, the anticancer activity of xanthone became weaker, due to poor cytomembrane penetration. The different terminal amino substituents had different effects in the increment of anticancer activity with the order: diethylamino > dimethylamino > pyrrolidine > piperidine > morpholino. Compound echanism .5a gave the IC50 value of 25.7, 33.2, and >50.0 µM against ECA109, SGC7901, and GLC-82 cell lines, respectively. Meanwhile, compound 5b with aminoalkyl moiety gave lower IC50 values of 9.56, 13.3, and 16.1 µM against the same cancer cell lines, respectively. The presence of polar aminoalkyl moiety in compound 5b gave a higher hydrophilicity; thus, this compound could easily penetrate the cancer cell membrane, leading to anticancer activity enhancement. Additionally, the aminoalkyl moiety having a higher pKa value is easily protonated which generate a cationic charge in order to bind with the DNA through its phosphate groups. This phenomenon blocked the DNA replication which is related to the inhibitory activity against the evaluated cancer cell lines [6 was the most potent anticancer agent against the A375-C5, MCF-7, and NCI-H460 cell lines, with IC50 values of 32.2, 22.6, and 14.1 µM, respectively. They found that the effect of the growth inhibitory activity of the xanthone compound was not only affected by the nature and position of the substituent but also the enantioselective effect. The presence of aryl group on the stereogenic center of xanthone was found to enhance the inhibitory activity against cancer cell lines [R)-isomer of compound 7 gave lower IC50 value (IC50 = 24.0 µM) than the (S)-isomer (IC50 = 112 µM) against MCF-7 cancer cell line. This phenomenon was caused by a more stable complex conformation between the (R)-isomer with the DNA through crosslinking reactions than the (S)-isomer one [In 2014, Shen et al. synthesized several xanthones through the modification of the free hydroxyl group of xanthone with dimethylamine group. The inhibitory activity of these xanthones was tested against ECA109, SGC-7901, and GLC-82 cell lines. It was found that the presence of aminoalkyl moiety was critical to its anticancer activity, as well as DNA binding. Moreover, the addition of dimethylamino side-chain resulted in the enhancement of anticancer activity. Compound ll lines . On the omer one .8 exhibited the highest anticancer activity with the IC50 value of 6.18, 8.06, 4.76, 4.59, and 6.09 µM against PC-3, MDA-MB-231, AsPC-1, A549, and HCT-116 cell lines, respectively. Compound 8 promoted cell cycle arrest, induced cell apoptosis, and provided antiproliferative effect on cancer cell viability. The presence of the 4-methyl group was critical in the xanthone structure, as it exhibited a higher potent anticancer activity. In contrast, the presence of oxygen atoms on the side chain of xanthone reduced the growth inhibitory activity against these cancer cell lines. This effect may be generated from the possibility of hydrogen bonds formation with other biological macromolecules outside the active site of the protein target. Additionally, the steric effect of the substituent at the side chain may also contribute to a lower inhibitory activity [In 2016, Liu et al. synthesized xanthone derivatives bearing 3,6-disubstituted aminocarboxymethoxy moiety and evaluated them as the anticancer agent. Among the evaluated xanthones, compound activity . A similactivity .9 was found to give the most potent inhibition of the catalytic activity of topoisomerase IIα, as evaluated using DNA relaxation assay. Compound 9 inhibited DNA relaxation with the IC50 of 1.00 µM. Specifically, compound 9 acts at the DNA cleavage/ligation active side and compound 9 is able to inhibit the ability of DNA to stimulate the rate of ATP hydrolysis. Furthermore, the presence of primary and secondary amine side-chains is more important, rather than the number of primary amines in the chain, or their distance from the primary amine [Minniti et al. in 2017 investigated the anticancer activity of synthetic xanthone derivatives with various polyamine moieties, including spermine, spermidine, butanediamine, and propanediamine at C-3 position. It was reported that the presence of the secondary amine group in the side chain significantly affected the topoisomerase II-drug interaction. Compound ry amine .10 showed the highest anticancer activity against MDA-MB-231 cell line, with an IC50 value of 0.46 µM. The inhibitory activity of compound 10 against MDA-MB-231 cell line was found to be much stronger compared to DMXAA (IC50 = 48.0 µM). Additionally, compound 10 also showed potent inhibitory activity against MCF-7, HepG2, K562, and COLO-320 cell lines, with IC50 values of 3.40, 9.20, 13.4, and 10.5 µM, respectively. The inhibitory effect was found as the result of induced apoptosis of the evaluated cancer cell lines. The effect of the electron-withdrawing group introduced to the opposite aromatic ring of 1,3-dihydroxyxanthone derivatives increased the anticancer activity, while the electron-donating group showed the opposite effect. Remarkably, the xanthone derivatives showed an enhanced inhibitory activity when combined with DMXAA. This synergistic effect demonstrated a good approach for the design and development of more potent anticancer drugs [In 2017, Liu et al. examined the anticancer activity of synthetic xanthones against MCF-7, MDA-MB-231, HepG2, K562, and COLO-320 cell lines. Among the synthesized xanthones, compound er drugs .11a–b with fluoro substituents were active against A549 cells, whereas compounds 11c–d were inactive against this cancer cell line. The anticancer activity of compound 11a (IC50 = 29.9 µM) and compound 11b (IC50 = 24.9 µM) was stronger than cisplatin (IC50 = 32.4 µM) as the positive control. In contrast, the anticancer activity of non-fluorinated xanthones (IC50 = 6.14–14.0 µM) was stronger than that of fluorinated ones (IC50 = 27.2–37.4 µM) against SMMC-7721 cell line. The anticancer activity of non-fluorinated xanthones 11c–d (IC50 = 6.14–14.0 µM) was also stronger than cisplatin (IC50 = 26.3 µM) [In 2018, Zhou et al. synthesized several xanthone derivatives and evaluated their anticancer activity against A549 and SMMC-7721 cancer cell lines. Compounds 26.3 µM) .12 was reported as the best anticancer agent against MCF-7, TK-10, and UACC-62 cells with the IC50 values of 21.9, 34.3, and 20.0 µM, respectively. In addition, the compound 12 is considered to be safe for the anticancer application as no cytotoxic to the human lymphocytes (cell viability > 70%) is observed. The nature of substituents in oxygenated xanthone structure had a significant effect on its anticancer activity. For example, the 1,2-dihydroxyxanthone exhibited a weaker anticancer activity than 2-hydroxy-1-methoxyxanthone. Therefore, the suitable functional group should be considered to be a critical parameter in the design of oxygenated xanthone derivative, with high potential for anticancer activity [Recently, Pedro et al. synthesized oxygenated xanthones and evaluated their anticancer activity against MCF-7, TK-10, and UACC-62 cell lines. Additional oxygenated groups in the xanthone core gave a significant effect on the anticancer activity enhancement. Among several synthesized xanthone derivatives, compound activity .13) was one of the most active anticancer agents. The anticancer activity of compound 13 against WiDr cells gave an IC50 value of 37.8 µM. Furthermore, compound 13 was not toxic against Vero cell lines (IC50 = 2510 µM), giving a selectivity index (SI) of 66.4, which was higher than doxorubicin (49.4) [13 suppressed the mRNA cyclooxygenase-2 (COX-2) expression by 37%, with no inhibitory expression against vascular endothelial growth factor receptors. Therefore, it was concluded that compound 13 inhibited the COX-2 enzyme and started chronic inflammation in the cancer cells. A molecular docking study showed that compound 13 interacted with Tyr355 and Arg120 amino acid residues of COX-2 enzymes, yielding a binding energy of −77.0 kcal/mol [Our research group has been working on anticancer research employing xanthone derivatives since 2010. Several hydroxyxanthone derivatives including 2-hydroxyxanthone, 3-hydroxyxanthone, 1,3-dihydroxyxanthone, 1,6-dihydroxyxanthone, 3,4-dihydroxyxanthone, 3,6-dihydroxyxanthone, 1,3,6-trihydroxyxanthone, 1,5,6-trihydroxyxanthone, 3,4,6-trihydroxyxanthone, and 1,3,8-trihydroxyxanthone have been synthesized in 2010–2021 ,125,126.n (49.4) . From thkcal/mol .50 values of 206–666 µM. These IC50 values are lower than hydroxyl derivatives (786–828 µM) against the same HepG2 cancer cell line. Furthermore, the SI value of chlorinated-hydroxyxanthones was higher (5.31–22.0) than hydroxyxanthones (2.58–10.60) against HepG2 cells. On the other hand, 4-chloro-1,3-dihydroxyxanthone also gave a lower IC50 (12.5 µM) than 1,3-dihydroxyxanthone (68.0 µM) against the P388 cancer cell line. The 4,5,7-trichloro-1,3,6-trihydroxyxanthone gave a lower IC50 (5.21 µM) than 1,3,6-trihydroxyxanthone (23.5 µM) against P388 cells. Meanwhile, the 4-chloro-3,6-dihydroxyxanthone gave a lower IC50 (0.69 µM) than 3,6-dihydroxyxanthone (10.4 µM) against P388 cancer cells. The SI value of chlorinated-hydroxyxanthones were much higher (87.6–9200) than hydroxyxanthones (31.2–844) against P388 cell line. From the molecular docking study, it was found that chlorinated-hydroxyxanthones were able to inhibit the c-KIT protein through hydrogen bond interactions with Asp810, Cys809, Ile789, His790, and Leu644 [Anticancer activity of chlorinated-hydroxyxanthones has been evaluated against HepG2 and P388 cell lines. Chlorinated-hydroxyxanthones, i.e., 4-chloro-1,3-dihydroxyxanthone, 4,5,7-trichloro-1,3,6-trihydroxyxanthone and 4-chloro-3,6-dihydroxyxanthone are inactive against HepG2 cells with ICd Leu644 .14) gave no anticancer activity against HeLa (IC50 = 251 µM), T47D (IC50 = 1398 µM), and HepG2 (IC50 = 262 µM) cancer cell lines. In contrast, compound 14 gave moderate anticancer activity against P388 (IC50 = 5.21 µM) cancer cells. Furthermore, the IC50 value of compound 14 (IC50 = 15.9 µM) was lower than doxorubicin (IC50 = 25.4 µM) against Raji lymphoma cell line. The toxicity of compound 14 for Vero cell lines was reported to be in IC50 of 256 µM, yielding an SI value of 16.1. From the molecular docking study, compound 14 gave strong binding energy against Raf-1  and c-Jun-N-terminal protein kinase (c-JNK)  proteins. Compound 14 formed hydrogen bonds with Cys424, Lys431, Ser427, and Gly426. The number of the hydrogen bond interactions (4) of compound 14 with Raf-1 protein was much higher than for the native ligand (1 hydrogen bond with Cys424). Compound 14 generated additional hydrogen bonds with Met111, Glu109, and Ser34 (two hydrogen bonds) on the active site of c-JNK protein. The number of hydrogen bond interactions (4) of compound 14 with c-JNK protein was also higher than the native ligand (2 hydrogen bonds with Met111 and Glu109) [The 4,5,7-trichloro-1,3,6-trihydroxyxanthone ( Glu109) .14 and doxorubicin against Raji lymphoma cell line has also been studied. It is well-known that drug resistance can be overcome through drug combination as the mechanism of action of two/more drug compounds, which may be different from in their individual usage. Furthermore, a synergistic effect of two/more drugs could lower the dose and thus suppress the side effects to the human body [14 inhibited Raf-1 protein and activated c-JNK protein. Inhibition of Raf-1 protein led to a higher sensitivity of cancer cells to doxorubicin. On the other hand, the activation of c-JNK protein led to the translocation of pro-apoptotic protein Bax to cytoplasm and stimulated the apoptosis mechanism of cancer cells [The synergistic effect between compound man body . Combinaer cells .15a and 15b, have also been prepared from 2,4-dihydroxybenzoic acid. The compound 15a was synthesized through bromination reaction of 2,4-dihydroxybenzoic acid first, and then followed by a cyclization reaction with phloroglucinol. On the other hand, compound 15b was obtained from a bromination reaction of 1,3,6-trihydroxyxanthone. Both compounds gave moderate anticancer activity against P388 cell line, with IC50 and SI values of 6.34–10.7 µM and 43.2–74.4, respectively. The molecular docking study revealed that the anticancer activity of brominated-hydroxyxanthones was generated by hydrogen bonding interactions with His790, Cys809, Leu644, Ile789, and Asp810 on the active site of c-KIT protein [Two new brominated-hydroxyxanthones, i.e., compounds  protein .16), a famous glycosylated xanthone, was reported for its anticancer activity against colorectal cancer cells through the inhibition of bcr/abl gene expression, thus inducing cellular apoptosis. In 2013, Li et al. isolated mangiferin from mangosteen fruit, and evaluated its anticancer activity against MDA-MB-231 and BT-549 cell lines. Mangiferin exhibited poor anticancer activity against MDA-MB-231 and BT-549 cells, giving the IC50 of 299 and 274 μM, respectively. Mangiferin gave a lower expression of matrix metalloproteinase-7 (MMP-7), MMP-9, beta-catenin, and vimentin, and simultaneously gave a higher expression of E-cadherin, thus leading to the antiproliferative phenomenon [Glycosylated xanthones have also been evaluated as anticancer agents. Mangiferin  [Psorospermum febrifugum in Africa in 1980. This compound exhibited in vitro and in vivo anticancer activity against wild type and drug-resistant leukemia cells. Furthermore, good anticancer activity of psorospermin against breast and colorectal cancer cells has also been reported. The psorospermin acts as the anticancer agent through DNA intercalation between base pairs at positions 11 and 12, as well as guanine alkylation on the topoisomerase II protein with its epoxydihydrofuran moiety. The DNA alkylation on the active site of topoisomerase II protein leads to inactivation on the DNA replication of cancer cells [20) isolated from the dry latex of Garcinia hanburyi. It was reported that desoxymorellin gave IC50 values of 0.74, 0.77, and 1.15 µM against HeLa, K562, and K562/R cell lines, respectively, through the apoptosis induction mechanism [Prenylated xanthones are the most evaluated xanthones, due to their promising application as the anticancer agent. In general, prenylated xanthones exhibited higher anticancer activities than the other classes. Early in 1992, Sordat-Diserens et al. reported that compound 3.08 µM) . The anter cells . Anotherechanism ,137.Cratoxylum cochinchinense and evaluated its anticancer activity against NCI-H187. This compound showed a potential cytotoxic effect against NCI-H187 cancer cell line with an IC50 value of 1.45 µM. Remarkably, it showed no cytotoxic activity against KB and BC-549 cell lines, which indicated excellent selectivity against NCI-H187 cancer cells. It was proposed that the presence of geranyl moiety in the isolated compound corresponded to its strong anticancer activity [21), from the early ripe fruit of Garcinia mangostana. The anticancer activity of mangostenone C was evaluated against KB, BC-1, and NCI-H187 cells, giving IC50 values of 6.11, 7.70, and 8.11 µM, respectively. The anticancer activity of mangostenone C against NCI-H187 was still weaker, but comparable to α-mangostin (5.07 µM) and gartanin (IC50 = 2.72 µM). This finding means that the tetraoxygen framework exhibits stronger anticancer activity [In 2006, Laphookhieo et al. isolated a prenylated xanthone from the roots of activity . In the activity .50 of 0.38–4.45 µM [22) as the main component in gamboge, an orange-brownish resin exuded from the plant of Garcinia hanburryi, which is often used as traditional medicine for cancer treatment. The anticancer activity of gambogic amide was found to be related to the apoptotic activity against T17 cells with an IC50 of 5.00 nM. The T17 cell line was derived from the basal forebrain of SN56 cell; therefore, T17 cells were defined as TrkA stably transfected SN56 cells. The gambogic amide could selectively bind to TrKA, triggering its tyrosine phosphorylation, and preventing neuronal cell death. These phenomena yielded an agonist effect to nerve growth factor (NGF) thus giving potent neurotrophic activity. Moreover, gambogic amide could block apoptotic machinery independent of the Trk receptor, which led to its ability to trigger programmed cell death for the cancer cell lines [Gambogic acid is one of the most famous natural xanthones as an anticancer agent ,141. Gam–4.45 µM ,145,146.–4.45 µM . Gambogi–4.45 µM ,151,152.ll lines .Terminalia calcicola named as termicalcicolanones A (23) and B (24) have been reported in 2007. Termicalcicolanones A and B showed weak to moderate anticancer activity against A2780 cells, with IC50 values of 40.6 and 8.10 µM, respectively [25 gave the most promising inhibitory activity on the K-562 cell viability, with an IC50 value of 20.0 µM. Additionally, compound 25 gave a moderate inhibitory activity against HL-60 and BV-173, with an IC50 value of 7.00 and 14.0 µM, respectively. The inhibitory mechanism was suggested to come from the antiproliferative and apoptotic effects on the evaluated cancer cell lines [Two new xanthones isolated from ectively . With a ectively . A combiectively . In 2010ll lines .26) against LNCaP, 22Rv1, DU 145, and PC-3 cancer cell lines, with IC50 values of 5.90, 6.90, 22.5, and 12.7 µM, respectively. The α-mangostin could induce cancer cell apoptosis at a concentration equal to or higher than 15 µM. Meanwhile, α-mangostin can promote G0/G1 cell cycle arrest at a lower concentration (<15 µM) [50 values of 2.44–28.5 µM [In 2011, Johnson et al. evaluated the anticancer activity of pure α-mangostin ((<15 µM) . Other r–28.5 µM ,163,164.–28.5 µM ,165. Fur–28.5 µM ,166. A s–28.5 µM . The int–28.5 µM . Azevedo–28.5 µM . On the –28.5 µM .27), from the hull of mangosteen fruit. The γ-mangostin was one of the major xanthone components in the mangosteen fruit. The γ-mangostin was evaluated as the anticancer agent against HT-29 cells. Unfortunately, γ-mangostin was non-active against HT-29 cells (IC50 = 68.5 µM). This inhibitory activity occurred through the induced apoptosis mechanism [28 showed the most potent anticancer activity, with IC50 values of 14.3, 15.8, and 5.17 µM for A549, MDA-MB-435, and HCT-116, respectively. The inhibitory activity of compound 28 as an anticancer agent relies on topoisomerase I protein inhibition, which led to the DNA relaxation of cancer cells [In 2012, Chang and Yang isolated another natural xanthone, γ-mangostin , and garciniaxanthone E (31) exhibited strong anticancer activity against HL-60 cell line, with IC50 values of 2.80, 3.40, and 3.10 µM, respectively. Compound 29 and garciniaxanthone E had prenyl moiety at their structure which corresponded to a stronger anticancer activity against HL-60 cells, indicating that the prenyl groups play an important role in the growth inhibitory activity. The number of prenyl groups was also suggested to significantly increase the inhibitory activity of xanthone. However, the addition of prenyl groups at the side-chain as in garciniaxanthone E did not significantly affect its activity compared to compound 29. Garciniaxanthone E was also reported for its anticancer activity against breast, lung, liver, gastric, colorectal, and leukemia cancer cell lines through the activation of caspase proteins and inhibition of PG-E2 pathways [In 2012, Niu et al. isolated a bioactive compound-based xanthone derivative from the stem bark of pathways .32 showed the most promising anticancer activity. Compound 32 gave IC50 values of 8.90 and 4.50 µM against HeLa and MDA-MB-231 cell lines, respectively. The anticancer activity of compound 32 was twice as strong as doxorubicin and cisplatin as the positive standards. The presence of nonplanar geminal-diprenylated rings was suggested to enhance its inhibitory activity against the cancer cell lines [33 showed the highest anticancer activity, with IC50 values of 2.62, 2.10, and 16.4 µM against HepG2, A549, and U-251 cell lines, respectively. Moreover, compound 33 also showed inhibitory activity against serine/threonine protein kinase, nuclear factor kappa-B kinase subunit gamma (IKK-β), with an IC50 value of 8.02 µM. The introduction of hydrophobic moiety in the aza-caged xanthone structure leads to a stronger anticancer activity. Moreover, it was reported that the presence of substituent group with larger volume was preferred in the anticancer activity enhancement, due to preferable interaction with the putative receptors. Compound 33 exhibited the anticancer activity through the apoptosis induction mechanism [Lim et al., 2012 synthesized several xanthone derivatives owing to the prenyl group, and evaluated their anticancer activity against HeLa and MDA-MB-231 cell lines. Among the synthesized compounds, compound ll lines . In the echanism .34 was considered to give strong anticancer activity against HepG2 and A549 cell lines with IC50 values of 3.25 and 3.60 µM, respectively. Furthermore, compound 34 was also found to have good bioavailability, and it was orally active, as tested through an in vivo assay. Compound 34 was capable of giving the inhibition rate of 58% against tumor growth (hepatoma solidity/Heps) at 100 mg/kg daily oral dose for 4 days, which was much better compared to the natural product with a similar structure, gambogic acid. However, a further clinical evaluation has not been reported yet [In 2013, Zhang et al. synthesized a natural xanthone derived from Garcinia species and evaluated its anticancer activity against HepG2 and A549 cell lines. Compound rted yet .Garcinia achachairu were investigated as the anticancer agents against nasopharynx cancer cells . A new prenylated xanthone (35) showed a remarkable anticancer activity with the IC50 of 1.43, 0.73, and 2.23 µM against CNE-1, CNE-2, and SUNE1 cell lines, respectively. On the other hand, the anticancer activity of compound 36 was evaluated against U-251, MCF-7, NCI/ADR-RES, 786-0, NCI-H460, PC-3, HT-29, and HaCat cell lines, giving IC50 values of 11.2, 34.0, 8.61, 19.6, 56.2, 10.5, 58.1, and 30.6 µM, respectively, which was comparable to doxorubicin [Garcinia paucinervis plant, which yielded a new compound, paucinervin I (37). Paucinervin I showed strong anticancer activity against HL-60 cell line with the IC50 value of 1.30 µM. The anticancer activity of paucinervin I was stronger than 5-fluorouracil (IC50 = 2.37 µM). The presence of angular pyranoxanthone skeleton in paucinervin I compound seemed to play a pivotal role in its antiproliferative activity [38), from the pericarp of mangosteen fruits, and studied its anticancer activity against CNE-1, CNE-2, A549, H490, PC-3, SGC-7901, and U-87 cancer cell lines. The 7-O-demethyl mangostanin gave IC50 values of 3.35, 4.01, 4.84, 7.84, 6.21, 8.09, and 6.39 µM against CNE-1, CNE-2, A549, H490, PC-3, SGC-7901, and U-87 cancer cell lines, respectively. The 7-O-demethyl mangostanin gave a stronger anticancer activity when compared to the Hirsutanol A as the positive control (IC50 = 6.30–15.0 µM). The mechanism of action of 7-O-demethyl mangostanin was generated by the induction of the late and early-stage apoptosis of cancer cells [In 2015, several isolated xanthones from the branches of orubicin . The mecorubicin . In 2016activity . In 2017er cells .Garcinia paucinervis and evaluated their anticancer activity against HL-60, PC-3, and Caco-2 cell lines. The isolation process yielded two new xanthones, (-)paucinervin O (39) and pacinervin P (40). Compound 39 showed strong anticancer activity, with IC50 values of 0.87 and 2.06 µM against HL-60 and Caco-2 cells, respectively. Compound 39 owing a furan ring was found to be more active against three cancer cell lines compared to the compounds with a dihydrofuran ring. On the other hand, compound 40 gave a strong anticancer activity, with IC50 value of 4.66 µM against PC-3 cells [41 was found to give the strongest anticancer activity, with IC50 values of 18.6, 36.5, 52.8, and 69.6 µM against HepG2, Hep3B, SMMC-7721, and HuH-7, respectively. The mechanism of its anticancer activity was reported through interactions with caspase 3, caspase 9, and poly(adenosine diphosphate-ribose) polymerase (PARP) proteins, which participate in programmed cell death [In 2018, Jia et al. isolated xanthone derivatives from the stem of -3 cells . In 201942 with the ethylamino functional group at C-1 position was the most active anticancer agent. Compound 42 gave IC50 value of 1.90 µM, which was much lower than doxorubicin (12.0 µM) [43 showed the most promising anticancer activity. Compound 43 gave moderate to strong anticancer activity, with IC50 values of 7.90 and 3.90 µM for MCF-7 and MDA-MB-468 cells, respectively. Compound 43 showed no significant toxicity effect toward H9C2 cells (>25.0 µM), demonstrating that it could be applied as a potential candidate for an anticancer lead compound [Since a limited number of isolated and synthesized xanthone dimers and xantholignoids are found, both groups are rarely investigated as anticancer agents. On the other hand, thioxanthone is a xanthone derivative in which the oxygen atom of the pyran ring is replaced by a sulfur atom ,181. In 12.0 µM) . In 2015compound .44 showed the most potent anticancer activity, with an IC50 value of 6.10, 6.00, and 3.60 µM against MCF-7, NCI-H460, and A375-C5 cells, respectively. The anticancer activity was caused through the induced apoptosis mechanism. The modification of compound 44 to its hydrochloride salt form was found to enhance its solubility and bioavailability [45 and tested its cytotoxic anticancer activity against HT-29 cells. Compound 45 showed no anticancer activity (IC50 > 165 µM) against HT-29 cell lines. In contrast, UV light irradiation stimulated compound 45 to enhance its cytotoxic activity (IC50 = 65.5 µM). Moreover, compound 45 exhibited higher activity compared to the common chemotherapeutic agents, such as 5-fluorouracil (IC50 = 222 µM) and cisplatin (IC50 = 66.4 µM). Under UV light irradiation, compound 45 released CO2 and produced alkyl radicals, thus increasing its anticancer activity. Therefore, compound 45 has potential for its application as a theragnostic agent toward specific targeted cancer treatment [In 2016, Barbosa et al. examined the anticancer activity of synthetic thioxanthone derivatives against MCF-7, NCI-H460, and A375-C5 cell lines. Compound lability . In 2020reatment . The sumA molecular docking study of xanthone and thioxanthone derivatives against platelet-derived growth factor response (PDGFR) and epidermal growth factor receptor (EGFR) protein kinases has been evaluated in our previous study. It was found that hydroxyxanthones with halogen substituents gave stronger binding energies  than erlotinib  against EGFR protein. However, they gave weaker binding energies  than imatinib  against PDGFR protein. A similar hydrogen bond of Met769 with erlotinib was also found on the hydroxyxanthones with halogen substituents. Furthermore, the hydroxyxanthones with halogen substituents gave an additional hydrogen bond with Thr766; consequently, they gave stronger binding energy than imatinib against EGFR protein. Meanwhile, a similar hydrogen bond with Cys673 of imatinib was also found on the hydroxyxanthones with halogen substituents. However, the hydrogen bond between imatinib with Asp810 was not found in the hydroxyxanthones with halogen substituents; thus, it may be the reason why they gave weaker binding energy than imatinib against PDGFR protein . On the Rational design on the structure and anticancer activity of xanthone derivatives has been reported; however, a comprehensive and holistic point of view is still very limited. For example, it was reported that the hydroxyl group at C-1 position of xanthone was critical for the anticancer activity against MCF-7 . The 1-h50 of haloxanthones against HepG2 cancer cells can be predicted through log(IC50) = −1.198(qC7) + 9.274(qC8b) − 1.887(qC8) − 23.35(qO carbonyl) − 6.034 (R2 = 0.94), where qX represented the charge of atom X. On the other hand, it was found that IC50 of haloxanthones against MCF-7 cancer cells can be predicted through log(IC50) = 100(LUMO) + 0.36(DM) − 3.02(qC6) − 1.71(qC4) − 7.98(qC1) + 7.85 (R2 = 0.89), whereas LUMO and DM represent the lowest unoccupied molecular orbital and dipole moment, respectively [50 of xanthones as topoisomerase IIα inhibitors can be predicted through pIC50 = 2.19(DE) + 0.22(n(OH)) − 0.54(LogP) − 0.469(SIB) + 0.018(SSA) + 2.57 (R2 = 0.84), whereas DE, n(OH), LogP, SIB, and SSA represent dielectric energy, the group count of hydroxyl substituents, logarithm of the partition coefficient between n-octanol and water, shape index basic (order 3), and solvent-accessible surface area, respectively [Quantitative structure–activity relationship (QSAR) is a computational approach to rationalize the relationship between the chemical structure of drugs with their biological activity . A QSAR ectively . A QSAR ectively .50 value of xanthone derivatives against A549 cancer cell line can be predicted through log (IC50) = −39.0090(x1) − 0.8078(x2) − 1.0827(x3) − 0.0483(x4) + 0.5053(x5) − 0.0560 (R2 = 0.87), whereas x1 is a parameter of electronegativity contribution, x2 is the atom type count descriptor class, x3 is the number of carbon atoms connected with four single bonds, x4 is the number of C=C bonds, and x5 is the electrotopological state of methyl group. Meanwhile, the IC50 value of xanthone derivatives against HepG2 cancer cell line can be predicted through log IC50 = −0.6407(y1) − 0.0336(y2) − 0.1278(y3) + 0.2226(y4) + 0.5877(y5) + 0.5940 (R2 = 0.87), whereas y1 is electrotopological state of carbon atoms, y2 is the number of double bonds, y3 is the number of hydrogen bond acceptor atoms, y4 is electrotopological state of methine group, and y5 is the number of oxygen atoms. On the other hand, the IC50 value of xanthone derivatives against U251 cancer cell line can be predicted through log IC50 (µM) = 0.0948(z1) + 0.5217(z2) + 0.3687(z3) + 1.1313 (R2 = 0.86), whereas z1 is the electrotopological state of nitrogen atoms, z2 is the number of oxygen atoms, and z3 is the topological state of carbon atoms. However, a more comprehensive QSAR study involving all reported xanthone derivatives against a certain cancer cell is not available yet, as of today. Therefore, computational studies on this research are still open to be investigated by researchers in the future.A more comprehensive QSAR study on the anticancer activity of xanthone derivatives was investigated by Alam and Khan in 2018 . They evThe xanthone derivatives showed promising in vitro anticancer activity; thus, further investigation through in vivo and then clinical assays is required . The in Garcinia mangostana fruit rinds containing 81% of α-mangostin and 16% of γ-mangostin significantly reduced the tumor volume of HCT-116 on mice. The inhibitory activity was related to the induction of apoptosis and inhibition of cancer cells migration, invasion, and clonogenicity [It was reported that panaxanthone (a mixture of α-mangostin and γ-mangostin in 6:1 wt/wt) inhibited the DNA replication and induced the G1 phase cell cycle arrest of cancer cells . Subcutagenicity .max) was found to be at 1 h, with a decrement to 65% after 4 h. A similar result was reported in China for maximum α-mangostin concentration (4.20 µg/L) and Tmax (1 h) value in the human group (20 people) [max value was found to be at 2–4 h on average [A clinical study for mangosteen juice (containing 3.90 g/L of α-mangostin) to the human group (20 people) was conducted . It was  people) . In 2012 average . Faster 2 dose. At a higher dose, the DMXAA gave the side effects of visual disturbance, tremors, confusion, slurred speech, and anxiety [Detailed anticancer investigation on DMXAA has also been reported. The DMXAA leads to vascular collapse and tumor necrosis through tumor necrosis factor-α induction. Synergistic anticancer activity with chemotherapy agents such as doxorubicin, imatinib, erlotinib, and sunitinib, as well as with the cancer radiotherapy technique has been reported. DMXAA exhibited low toxicity to the normal cells with suitable pharmacokinetic parameters. Furthermore, the clinical trials of DMXAA as the anticancer agent have been evaluated in New Zealand and the United Kingdom. The phase I clinical trial of DMXAA to 63 patients gave no drug-related myelosuppression. The DMXAA was well tolerated up to 4900 mg/m anxiety . Unfortu anxiety . HoweverAs an isostere of xanthone, thioxanthones have similar structures and physicochemical properties to xanthone derivatives . NowadayThe most serious drawbacks for the utilization of xanthone derivatives as the anticancer agent are their poor solubility in water and their reactivity to be transformed into phase 2 conjugates form. Therefore, further technologies are critical to overcome these limitations ,211. It This review highlights the potential anticancer of xanthone derivatives, contributing to the design and develop of new drugs. Both isolated and synthesized xanthone derivatives have been proven to have promising anticancer activities against breast, hepatoma, cervix, colorectal, ovarian, lung, gastric, leukemia, skin, epidermoid nasopharynx, prostate, neuron, brain glioblastoma, and other cancer cells through in vitro assay. However, their further evaluation as anticancer agents through in vivo and clinical assays is still limited as of today. Furthermore, a comprehensive QSAR study for the better design of anticancer drugs based on the xanthone structure has not yet been established. These research gaps require extensive collaborations and contributions from researchers around the world to further develop active, selective, and efficient anticancer drugs based on xanthone derivatives.