Despite an increasing number of drug treatment options for people with idiopathic generalized epilepsy (IGE), drug resistance remains a significant issue and the mechanisms underlying it remain poorly understood. Previous studies have largely focused on potential cellular or genetic explanations for drug resistance. However, epilepsy is understood to be a network disorder and there is a growing body of literature suggesting altered topology of large-scale resting networks in people with epilepsy compared with controls. We hypothesize that network alterations may also play a role in seizure control. The aim of this study was to compare resting state functional network structure between well-controlled IGE (WC-IGE), drug resistant IGE (DR-IGE) and healthy controls. Thirty-three participants with IGE (10 with WC-IGE and 23 with DR-IGE) and 34 controls were included. Resting state functional MRI networks were constructed using the Functional Connectivity Toolbox (CONN). Global graph theoretic network measures of average node strength , node strength distribution variance, characteristic path length, average clustering coefficient, small-world index and average betweenness centrality were computed. Graphs were constructed separately for positively weighted connections and for absolute values. Individual nodal values of strength and betweenness centrality were also measured and ‘hub nodes’ were compared between groups. Outcome measures were assessed across the three groups and between both groups with IGE and controls. The IGE group as a whole had a higher average node strength, characteristic path length and average betweenness centrality. There were no clear differences between groups according to seizure control. Outcome metrics were sensitive to whether negatively correlated connections were included in network construction. There were no clear differences in the location of ‘hub nodes’ between groups. The results suggest that, irrespective of seizure control, IGE interictal network topology is more regular and has a higher global connectivity compared to controls, with no alteration in hub node locations. These alterations may produce a resting state network that is more vulnerable to transitioning to the seizure state. It is possible that the lack of apparent influence of seizure control on network topology is limited by challenges in classifying drug response. It is also demonstrated that network topological features are influenced by the sign of connectivity weights and therefore future methodological work is warranted to account for anticorrelations in graph theoretic studies. Pegg et al. report that, irrespective of seizure control, network topology in idiopathic generalized epilepsy is more regular and has higher global connectivity, compared with controls.  However, such approaches have failed to fully explain the underlying mechanisms of drug resistance.,,Resting state brain networks may be examined using functional MRI (fMRI), whereby blood oxygen level dependent (BOLD) signal is statistically analysed to establish the extent of connectivity between regions. Graph theory provides a robust mathematical method to subsequently delineate and analyse network topology (structure). Within this framework, each brain area is termed a ‘node’ and the connections between nodes are termed ‘edges’. Edges may be weighted according to the strength of correlation of BOLD signal between nodes. Information regarding the presence and strength of pairs of connections within a network is contained within a connectivity matrix and from this, a range of network metrics and features can be determined .13,14 Ov,To our knowledge, analysing fMRI-derived functional connectivity from a global network perspective in IGE according to seizure control has not previously been considered. However, reduced connectivity in specific networks (cerebellar and default mode networks) in drug resistant IGE (DR-IGE) compared with well-controlled IGE (WC-IGE) has been described.,,Considering that network topology may play a role in seizure control in IGE, and that diverging findings in the literature of IGE network topology may be influenced by a lack of evaluation according to seizure control,Thirty-five participants with IGE were recruited from the Walton Centre NHS Foundation Trust and from Salford Royal NHS Foundation Trust. All participants with IGE had been diagnosed by an experienced epileptologist according to current International League Against Epilepsy (ILAE) criteria Informed, written consent was obtained for all participants according to the Declaration of Helsinki and this study was approved by the local ethics committee  images were obtained for each participant using a 3T GE Discovery MR 750 MR system. Scanning was performed supine in the head-first orientation. Participants were instructed to stay awake and to look at a white fixation cross on a black background. T1-weighted data were acquired using the following parameters: Pulse sequence = BRAVO; echo time (TE) = 3.22 ms; repetition time (TR) = 8.2 ms; field of view (FOV) = 24, TI = 450 ms; slice thickness = 1 mm; voxel size = 1 mm × 1 mm × 1 mm; 140 slices; flip angle = 12. RS-fMRI was obtained with a 6-minhttp://www.neuro.uni-jena.de/cat/. Last accessed 18/05/21). This spatially normalizes the T1-weighted image into the MNI space then segments it into skull-stripped brain. Following this, adaptive maximum a posteriori segmentationSpatial pre-processing was implemented in SPM12 using the standard SPM pipeline. Slice timing correction of the fMRI time series was performed using the first slice as the reference. Head motion and EPI distortion were corrected to the first functional volume. The estimated movement parameters  were saved and later included as covariates for each subject in the first level analysis to produce the connectivity matrix. Data were normalized into MNI  space using the ICBM 152 template of European brains,Spatially pre-processed data were next temporally pre-processed using the Functional Connectivity Toolbox (CONN).Weighted functional connectivity matrices were constructed using the CONN functional connectivity toolbox . Data wer = 0.1 to r = 0.8 seen in the literature.r = 0.25 was selected as it is a commonly used threshold.post hoc analysis explored the effects of altering the threshold by performing the analysis with thresholds of zero, r = 0.125, and r = 0.375. There is no optimal solution to handle negative values in graph theoretical analysis,,Weighted, undirected, graphs were subsequently constructed using a custom script implemented in Matlab.,Global measures of average node strength, node strength distribution variance, average clustering coefficient, characteristic path length, small-world index and average betweenness centrality were calculated. These metrics were chosen to provide a broad overview of network topology. Because clustering coefficient and characteristic path length are sensitive to degree, normalized metrics were calculated for each by dividing average clustering coefficient and characteristic path length by the mean of the clustering coefficient and characteristic path length distributions of 500 surrogate random networks respectively.As a post hoc analysis, strength and betweenness centrality were also calculated for each node individually using an edge threshold of 0.25. Subsequently, ‘hub nodes’ were identified for each participant. Nodes were considered as hubs if both strength and betweenness centrality were greater than one standard deviation above the corresponding mean network value.U- or Tukey test. This was Bonferroni corrected for multiple comparisons using a factor of six. In addition, both groups with epilepsy were combined into one cohort and global outcome metrics were compared with controls using an independent t-test, controlled for participant age.Demographic and outcome metric results were firstly assessed for normality . Next, potential differences in demographics and outcome metrics between the three groups were evaluated using Kruskal–Wallis tests or one-way analysis of covariance, as appropriate. Age and epilepsy duration were included as co-variates. Where differences were found, pairwise comparisons were evaluated using a Mann–Whitney U-test. Correction for multiple comparisons was implemented using the false discovery rate (FDR)q-value of 0.1. Following the identification of hub nodes, the total number of times a node was considered a hub in each group was calculated and displayed visually. The number of hub nodes in each group was compared using a Kruskal–Wallis test.Potential differences in connectivity between individual nodes in IGE compared with controls were evaluated by comparing the strength and betweenness centrality of each node, using a Mann–Whitney P < 0.05) a Mann–Whitney U-test was performed.An analysis to compare motion parameters between the participants with IGE and controls was performed. Normality of the data was tested first using a Lilliefors test and when significant . Pairwise comparisons found a difference in age between WC-IGE and controls (P = 0.014), with no significant differences between WC-IGE and DR-IGE (P = 0.094), DR-IGE and controls (P = 1.00), or between both IGE groups (combined) and controls (P = 0.066). Females comprised 59.7% of participants, with no significant difference across groups . Median duration of epilepsy was 14.5 years in DR-IGE and 6.5 years in WC-IGE. This difference was not statistically significant . The mean number of AEDs taken in the group with WC-IGE was 1.14 (range 1–2) and in the DR-IGE group was 1.9 (range 1–4). This difference was not statistically significant .Median age significantly differed between groups .There was no significant difference in average root mean square motion values between groups (Mann–Whitney P = 0.013). Pairwise comparisons identified a significantly higher average betweenness centrality in WC-IGE compared with controls (P = 0.048) and a possible trend towards a significantly higher average betweenness centrality in DR-IGE compared with controls (P = 0.057), with no difference between WC-IGE and DR-IGE (P = 1). There were no other differences in global metrics at the three-group level. When both IGE groups (WC-IGE and DR-IGE combined) were compared with controls, a higher average node strength . A trend toward a significantly higher characteristic path length . There were no differences in node strength distribution variance . The remaining outcome metrics did not significantly differ between the two groups .There was no correlation between age or epilepsy duration with any outcome metric  and positive edge values . As with the threshold level of 0.25, higher characteristic path length and greater average betweenness centrality were also found in networks constructed with an edge threshold of 0.375 . Additionally, small world index was lower in IGE than controls using a threshold of 0.375  and with positive edges without a threshold (P = 0.035). Clustering coefficient was higher in IGE compared with controls with a threshold of 0.375 . No other significant differences were found in other group comparisons. Full details of results across various thresholds can be found in When edge thresholds of zero, 0.125, and 0.375 were tested, the finding of a statistically higher average node strength in the IGE group (WC-IGE and DR-IGE combined) compared with controls was robust across all thresholds and for networks constructed with both absolute edge values . On inspection of plots of the frequency of hub nodes at each location, there were no clear group differences between the location of hub nodes  and has generally greater connectivity across the network nodes , without a clear difference in the location of hub nodes. Network topology did not vary according to seizure control.,,,A higher characteristic path length results in a more regular network topology.,The average node strength of a network reflects the strength of connections of each node across the network. Therefore, networks that have a higher average node strength perhaps reflect networks with generally greater connectivity. Similarly, networks with higher average betweenness centrality (a measure of the extent of ‘information flow’ within a network), may also reflect a greater resting state hyperexcitability of the epileptic brain.Post hoc analysis of global metrics using a range of edge thresholds showed that the results were robust for average node strength and for betweenness centrality at higher threshold values. The additional significant findings of increased clustering coefficient in IGE and lower small world index were also in support of a more regular network topology in IGE.When the results using different thresholds of edges are compared, it is evident that the choice of threshold can alter the results. There appears to be a relationship between higher threshold values and the detection of a greater number of statistically significant results. Thresholds are applied to edges with the aim of decreasing sensitivity to spurious connections, but the optimal method to achieve this aim is not known. It is important to note that networks with lower summed synchronization values will become relatively less dense than networks with higher overall synchronization values after thresholding.The additional findings depending on whether negatively correlated edges were discarded highlight that network topology is sensitive to the sign of the edge. As discussed above, the significance of anticorrelated networks and the extent to which they are influenced by pre-processing techniques are not fully elucidated. We suggest that by using absolute values, correlation values may be regarded as a reflection of the strength of neural connectivity, irrespective of the nature of the relationship. The similarity of results of both analyses suggests that the results are not confounded by taking into account negative correlations and in fact, their inclusion may improve sensitivity to the detection of network differences. How negative correlations may be mathematically accounted for in graph theoretic analysis is an important consideration for future graph theoretical studies.,et al.’s study, significance levels did not survive this correction. Notwithstanding the fact that the individual nodal comparisons did not survive correction for multiple comparisons in our study, there is no suggestion from our study or from these previous studies, that there are specific regions of altered resting state connectivity in IGE. Whilst corticothalamic regions have been implicated in seizure genesis, it is possible that in generalized seizure disorders, the precise area of network aberration from where a seizure is initiated may vary between, or within, individuals.Previous fMRI connectivity studies have reported widespread locations of specific nodes that display altered connectivity in IGE, with a similar location of hub nodes in IGE and controls.It is possible that differences in network features in the group with IGE compared with controls represent medication effects. Previous studies have described alterations in global efficiency (inverse of characteristic path length) with topiramate, but not with valproate, lamotrigine or levetiracetam.This study did not find any differences in network topology dependent upon seizure control. One limitation of this interpretation is the small sample size, particularly in the WC-IGE group, which may have been underpowered to detect a possible difference. The low number of participants recruited with WC-IGE reflects the fact that they are less likely to remain under long-term follow up. In addition to potential underpowering, a small sample size may also result in a type 1 error.,,A larger study may have also permitted the comparison of IGE subtypes. Although there is strong evidence to support that IGE syndromes share pathophysiological and genetic relationships,A further potential limitation relates to the difficulties in classifying response to AEDs; Patients may not be concordant with their antiepileptic medication and therefore may be inaccurately categorized as drug resistant. Alternatively, they may have unrecognized co-existent non-epileptic attacks, which could result in a seemingly higher seizure frequency. Conversely, there is evidence that some patients under-report seizures,A further limitation of this study is that interictal epileptiform discharges (IEDs) in the group with IGE may have confounded the results. IEDs are associated with co-localized BOLD activation, in addition to BOLD activation in distant areas.In summary, this study demonstrates that the network topology in IGE is more regular and has higher global connectivity, with no evidence of systematic alteration in the location of nodes with high connectivity. This was found to be the case irrespective of seizure control. We suggest that examining drug resistance from a network perspective warrants further exploration in a larger, longitudinal, multimodal study.Brain Communications online.S.S.K. acknowledges support from the UK Medical Research Council (MR/S00355X/1 and MR/K023152/1) and Epilepsy Research UK (1085). P.L. is supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London; Maudsley NHS Foundation Trust; King’s College London; Innovative Medicines Initiative 2 Joint Undertaking (Grant/Award number: 115902); European Union’s Horizon 2020 Research and Innovation Programme; EFPIA.The authors report no competing interests.fcab196_Supplementary_DataClick here for additional data file.


Acute exacerbation is the major cause of asthma morbidity, mortality, and health-care costs. Respiratory viral infections, particularly rhinovirus (RV) infections, are associated with the majority of asthma exacerbations. The risk for bronchoconstriction with RV is associated with allergic sensitization and type 2 airway inflammation. The efficacy of the humanized anti-IgE monoclonal antibody omalizumab in treating asthma and reducing the frequency and severity of RV-induced asthma exacerbation is well-known. Despite these clinical data, mechanistic details of omalizumab's effects on RV-induced asthma exacerbation have not been well-defined for years due to the lack of appropriate animal models. In this Perspective, we discuss potential IgE-dependent roles of mast cells and dendritic cells in asthma exacerbations. IL4, IL5, IL13; IL-13-regulated genes, POSTN, CLCA1, SERPINB2) and mast cell  genes in the airway epithelium (Asthma is a T helper cell 2 (Th2) cell-driven chronic inflammatory lung disease, characterized by airway inflammation, airway hyperresponsiveness (AHR), airway remodeling, and reversible airway obstruction , 2. The ithelium –38, consithelium , 40. Masithelium . RV can ithelium –44. Impoithelium –48 and rithelium , 49, 50.in vivo asthma models  on 40LB feeder cells showed that IgE-producing B cells swiftly exit GCs and differentiate into plasma cells (PCs) and that IgE-producing GC cells die by apoptosis  than of mIgG1 on germinal center (GC) B cells, and increased apoptosis of IgEpoptosis –91. A repoptosis . TherefoM to IgE . IgE proM to IgE , 95. T fM to IgE . RecentlM to IgE . The halM to IgE . Several2 heterotrimers. It has been known for long that levels of FcεRI expression on the cell surface correlates well-with serum levels of IgE . FcεRI expressed on mast cells and basophils is a heterotetramer of three subunits, an IgE-binding α subunit, a receptor-stabilizing and signal-amplifying β subunit, and signal-initiating disulfide-linked two γ subunits . IgE bins of IgE , 102. Ths of IgE , 104. Ths of IgE . Binding+ B cells where they are delivered to CD8α− conventional DCs (cDCs) which induce proliferation of CD4+ T cells  that binds to free human IgE and to membrane-bound form of IgE (mIgE) on the surface of B cells . Omalizu+ neutrophils and subsequent enhancement of FcεRI expression on lung cDCs. Meanwhile anti-SeV IgE antibodies are produced, and these IgE antibodies stimulate the lung cDCs to produce CCL28 via FcεRI. CCL28 recruits IL-13-producing Th2 and type 2 innate lymphoid cells (ILC2)  , 128. ThThe clinical observations described above, particularly efficacy of omalizumab in reducing asthma exacerbations , 129, stEarly studies of animal models of asthma mostly used chicken OVA as a model allergen. More recently, numerous studies used HDM for sensitization and challenge purposes, as up to 90% of asthmatics are sensitized with HDM. When mice were repeatedly exposed to intranasal injections of a single allergen such as HDM, ragweed and Aspergillus, tolerance was induced . In contIn typical airway inflammation experiments using HDM, mice are sensitized with a commercial HDM via the intranasal or intratracheal route and then challenged with the same allergen via the same route. One day or a few days after the last allergen challenge, bronchoalveolar lavage fluids (BALF) are collected. Leukocytes  and cytokines  in BALF and lungs are reported together with total or allergen-specific IgE and IgG and lung functions . Remodeling such as goblet cell metaplasia is also reported. Acute and chronic disease-mimicking procedures were developed. Involvement of specific molecules or cells in these airway inflammation models has been defined using pharmacological and immunological reagents as well as genetically engineered mice lacking these molecules or cell types. For example, antibodies against GM-CSF  or chemiW−sh/W−sh mice  levels, which can inhibit IgE-mediated mast cell activation (2 could be responsible for the dampening effect on AHR (W/Wv and KitW−sh/W−sh mice) and abnormal reconstitution of these mice with adoptively transferred mast cells  and by a Grant-in-Aid for Special Research in Subsidies for ordinary expenses of private schools from the Promotion and Mutual Aid Corporation for Private Schools of Japan.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.


G protein-coupled receptors (GPCRs) are the largest family of membrane proteins in the human body and are responsible for accurately transmitting extracellular information to cells. Arrestin is an important member of the GPCR signaling pathway. The main function of arrestin is to assist receptor desensitization, endocytosis and signal transduction. In these processes, the recognition and binding of arrestin to phosphorylated GPCRs is fundamental. However, the mechanism by which arrestin recognizes phosphorylated GPCRs is not fully understood. The GPCR phosphorylation recognition “bar code model” and “flute” model describe the basic process of receptor phosphorylation recognition in terms of receptor phosphorylation sites, arrestin structural changes and downstream signaling. These two models suggest that GPCR phosphorylation recognition is a process involving multiple factors. This process can be described by a “QR code” model in which ligands, GPCRs, G protein-coupled receptor kinase, arrestin, and phosphorylation sites work together to determine the biological functions of phosphorylated receptors.Video AbstractThe online version contains supplementary material available at 10.1186/s12964-022-00832-4. In heart failure, the release of a large amount of catecholamine and activation of the β2-adrenoceptor (β2-AR)-Gi pathway can inhibit the activity of AC and weaken β1-AR-Gs activation . Ac. Ac37]. n effect . Partialn effect , 45. Antn effect .Fig. 1ClHowever, the same ligand that plays a role of agonist in a response may become antagonist or inverse agonist in another response. This complicacy is the pluridimensional efficacy of a ligand . For invTopographically, according the variant of binding sites, the GPCR ligands are divided into orthosteric ligands and allosteric ligands  . The ligThe ligand is the initiating factor in GPCR signaling. The type and characteristics of a ligand will specifically change the structure of a GPCR, impacting the final biological results . The comBased on the homology of the GPCR sequence, receptors can be divided into class A (rhodopsin family), B (secretin family), C (glutamate family), the adhesin family, and class F (frizzled family) . This la1-AR to exert positive chronotropic and positive inotropic effects through the cAMP/PKA pathway. To avoid the overactivation of β1-AR, β1-AR is phosphorylated by GRK in a timely manner. β-Arrestin binds to phosphorylated β1-AR to assist receptor desensitization and endocytosis . Us. Us. proocytosis . As a procytosis .Fig. 4Fl2R C-termini with different phosphorylation sites and analyzed the binding ability, structural changes and functional differences in relation to β-arrestin1 [2Rpp-1, V2Rpp-3, V2Rpp-4, V2Rpp-6, and 7 short peptides were designed according to the 7 phosphorylation sites  at the C-terminus of V2R. The suffixed number represents the position of the C-terminal phosphorylation site. V2Rpp-1 not only activated β-arrestin but also recruited c-Raf-1 kinase to the V2Rpp-1-β-arrestin1 complex. The V2Rpp-3-β-arrestin1 complex interacted with MEK1. Both c-Raf-1 and MEK1 are effectors of V2R. V2Rpp-6,7 was mainly responsible for regulating the nuclear localization sequence (NLS) structure in the N-terminal domain of β-arrestin1. An analysis of the structure of V2Rpp-4 and β-arrestin1 showed that this complex causes the rearrangement of C-terminal pS357 and pT359 and causes β-arrestin1 and pT359 to form phospho interactions. In the study of V2R C-terminal phosphorylation sites, T359 was not included as one of the seven phosphorylation sites studied by the flute model [2R.Recently, Qing-Tao He et al. designed four Vrrestin1 . V2Rpp-1te model , 28, 31.te model , 30. ThiThe flute model is similar to the bar code model; however, the flute model not only enriches the bar code model theory but also explains the GPCR phosphorylation recognition theory from the perspective of structural changes.2R [There are more than 800 known GPCRs in the human body, but research on receptor phosphorylation recognition patterns has mainly focused on rhodopsin and V2R , 30, 97.2R . AT1-AA 2R .Table 1E1-AR. The β-adrenergic receptor agonist isoproterenol (ISO) activates receptors and signals via the Gs pathway [1-AR recruits β-arrestin and drives receptor desensitization and endocytosis [1-adrenergic receptor autoantibody (β1-AA) in patients with cardiovascular disease, although also an agonist of β1-AR, allows for sustained activation of β1-AR. Although it increases β1-AR phosphorylation, it inhibits the recruitment of the receptor to β-arrestin [1-AR phosphorylation site is not efficiently recognized by β-arrestin under the action of β1-AA. Carvedilol as a representative of β-blocker could biased active β1-AR-Gi-β-arrestin pathway. Activation of this pathway could then exert cardioprotective effects by transactivating the epidermal growth factor receptor (EGFR)- extracellular signal-regulated kinase (ERK) pathway [A similar phenomenon exists in the β pathway . Phosphoocytosis . Meanwhiarrestin . The rea pathway , 116. ThThis modulation is similar to a “QR” code Fig. , which pAccurately understanding the process of GPCR phosphorylation recognition will help to fully describe the way in which arrestin binds to receptors and its functional mechanism. It will also help us to better understand the physiological state of the body and provide potential targets and ideas for disease prevention and treatment. At present, research on the mode of GPCR phosphorylation recognition mainly focuses on the bar code model and the flute model , 62, 79.2R and rhodopsin, with V2R being the most studied receptor carried out [Analysis of the barcode model and the flute model revealed that the detection of the phosphorylation recognition process by these two models was mainly between GPCR and GRK or GPCR and arrestin , 29, witried out , 97. ButThe difference between the QR code model and the barcode model or the flute model is that the QR code model integrates the factors influencing the whole process from GPCR activation to arrestin function, such as ligands, GRK, etc. This model is developed on the existing theory and is based on the two existing recognition models. Based on our re-thinking on the recognition model of GPCR phosphorylation, we find both of the earlier models hold their own strengths, but limited. The barcode model and the flute model can determine the interactions between GPCR and GRK or arrestin with experimental precision, while the QR code model considers the receptor phosphorylation process macroscopically and is more theoretically oriented.2-AR in cardiomyocytes maintains cardiomyocyte beating without the involvement of ligands [1-AR is distributed in both cell and organelle membranes and both can signal through the cAMP-PKA pathway [We are also conscious of the fact that the QR code model still has limitations and does not fully explain some specific phenomena of the GPCR phosphorylation recognition process. (1) Phosphorylation of some receptors is not involved in receptor endocytosis. Human lutropin receptor belongs to the class A GPCRs . Althoug ligands , 121. (3 pathway , 123. Ho2-AR-β-arrestin pathway, enhanced skeletal muscle contractility in mice without causing skeletal muscle cell hypertrophy. This feature might have therapeutic value for patients with sarcopenia and frailty. Although clenbuterol, another agonist of β2-AR, also enhanced the contractility of skeletal muscle cells, it caused cell hypertrophy and caused side effects such as arrhythmia [GPCR signal recognition, including phosphorylation, is the basis for the development of biased drugs. The presentation of allosteric microprocessors theory elaborated the mechanism of GPCR biased signaling. In this theory, biased ligands, GPCRs, transducers such as GRKs, G proteins and arrestins interacted allosterically. Biased ligands transmitted distinct GPCRs structural information that was processed into distinct biological outputs . A biaserhythmia . Biased


Renilla luciferases. The QSAR model predicted a moderate to high likelihood of firefly luciferase inhibition for all of the 11 isoflavonoids investigated, and the in vitro assays confirmed this for seven of them: daidzein, genistein, glycitein, prunetin, biochanin A, calycosin, and formononetin. In contrast, none of the 11 isoflavonoids inhibited Renilla luciferase. Molecular docking calculations indicated that isoflavonoids interact favorably with the D-luciferin binding pocket of firefly luciferase. These data demonstrate the importance of reporter-enzyme inhibition when studying the effects of such compounds and suggest that this in vitro assay can be used to exclude false-positives due to firefly or Renilla luciferase inhibition, and to thus define the most appropriate reporter gene.Firefly luciferase is susceptible to inhibition and stabilization by compounds under investigation for biological activity and toxicity. This can lead to false-positive results in in vitro cell-based assays. However, firefly luciferase remains one of the most commonly used reporter genes. Here, we evaluated isoflavonoids for inhibition of firefly luciferase. These natural compounds are often studied using luciferase reporter-gene assays. We used a quantitative structure–activity relationship (QSAR) model to compare the results of in silico predictions with a newly developed in vitro assay that enables concomitant detection of inhibition of firefly and  Advances in high-throughput screening of compounds for biological activity have enabled the compilation of data from cell-based and biochemical assays on a myriad of biological targets for thousands of compounds, such as the US Federal Consortium on Toxicology in the 21st Century (Tox21 Consortium) program . The intLuciferase reporter-gene assays are a commonly used bioluminescence assay. The construct includes a promoter region of a gene of interest followed by a luciferase gene. When this is introduced into a cell, luciferase is expressed in quantities that are proportional to the promoter activity. The luciferase (and hence the promoter activity) can then be quantified by the measurement of the luminescence produced when the enzyme substrate is added. In this way, the transcriptional activity of the gene of interest  can be measured in response to the effects of different modulators of the relevant signaling pathways . The lucPhotinus pyralis (FLuc) is the most widely used luciferase for bioluminescence assays. FLuc requires ATP and oxygen, and it catalyzes the oxidation of D-luciferin to oxyluciferin, with concurrent emission of a photon. However, during testing of 360,000 compounds in a chemical library, FLuc was shown to be inhibited by ~12% [Luciferase from the firefly  by ~12% . They co by ~12% ,15. ParaRenilla reniformis (RLuc) is also used in reporter-gene assays, and frequently in combination with FLuc, to determine cytotoxicity while providing for normalization of the results. Such dual-luciferase assays are possible due to the different substrate requirements of FLuc and RLuc, and to the possibility to quench FLuc luminescence before adding the RLuc substrate, coelenterazine [Luciferase from the sea pansy terazine . RLuc isterazine . Howeverterazine .The effects of luciferase inhibition are not only seen in terms of the isolated enzyme or when it is in cell lysates, but also in assays with viable cells, where any inhibitor first needs to pass through the cell membrane, to enter the cell, as for reporter-gene assays . The potPredicting potential inhibition of FLuc  using different chemoinformatic approaches has been a relatively active field in recent years. This has led to the development of different freely available models that can be used when designing studies using FLuc as the reporter protein, such as Luciferase Advisor , ChemFLuHere, we have evaluated the potential of selected isoflavonoids (with some as known phytoestrogens) to inhibit FLuc and RLuc activities using in silico and in vitro approaches. As the importance of addressing such reporter-enzyme inhibition has been relatively neglected, our aim was also to highlight this aspect using a well-known group of natural products as examples.These isoflavonoids were selected based on their structures, to provide insight into their importance for luciferase inhibition. They were therefore sorted according to five structurally diverse groups, as shown in The predicted potentials were determined, for the positive control (resveratrol) and these selected isoflavonoids, to interfere with FLuc using the Tox21 Consortium QSAR model InterPred , which iFLuc and RLuc reporter-genes and is used in OECD TG 458 for compound testing for (anti)androgen activity [The inhibitory activities of these isoflavonoids on the FLuc and RLuc enzymes in vitro were determined in lysates of the AR-EcoScreen cell line. This cell line is stably transfected with the activity . Using AThese data confirmed FLuc inhibition in vitro for seven of the 11 isoflavonoids. At the lowest isoflavonoid concentration tested of 1 μM, biochanin A and formononetin significantly inhibited FLuc . For the intermediate isoflavonoid concentration of 10 μM, significant inhibition of FLuc was seen for glycitein, calycosin, and prunetin . Finally, daidzein and genistein showed significant inhibition of FLuc at 100 µM . Genistin, daidzin, glycitin, and S-equol were inactive against FLuc.50 values for FLuc inhibition were determined for all of the active isoflavonoids, along with the positive control, resveratrol, as given in 50 of 640 nM, while the IC50 for the resveratrol control was almost eight-fold higher at 4.94 µM. Similar FLuc inhibitory activities to resveratrol were seen for formononetin (3.88 µM) and calycosin (4.96 µM). The other active isoflavonoids had IC50 values >10 µM.The IC50 of 338.4 µM, with its dose–response curve shown in None of these isoflavonoids inhibited RLuc in vitro, as seen in To further rationalize these in vitro data, molecular docking of the isoflavonoids was carried out using the available crystal structures of FLuc and RLuc. Initially, the electrostatic properties of the FLuc binding site were analyzed. The pocket for the binding of ATP and the D-luciferin substrate is bent and is relatively narrow around the D-luciferin sub-pocket. It is also relatively hydrophilic and includes several hydrophobic amino acids . As expeIn docking experiments, the isoflavonoids showed highly comparable binding modes, and interacted exclusively with the FLuc D-luciferin binding pocket, with no indications of docking to the neighboring AMP sub-pocket. The initial docking experiments used a water-free FLuc binding site, and two orientations of the isoflavonoids were detected, with the main difference being the 180° rotation of the core bicyclic scaffold . To furtIn contrast, RLuc operates via a completely different reaction mechanism, which is also reflected by the different binding site characteristics, as it is larger and more elongated than for FLuc. The RLuc binding site consists largely of hydrophobic amino acids, e.g., Trp156, Phe180, Phe261, and Phe262 . This isWhen the isoflavonoids were docked into the RLuc binding site, the poses generated showed no uniformity and were scattered across many possible orientations. On the other hand, a very uniform binding pose was obtained for the ensemble of the docking solutions for FLuc . Even thWhen studying the influence of specific compounds on gene expression using reporter-gene assays, it is essential to evaluate beforehand any interference of these compounds in the assay system. In the present study, we tested 11 isoflavonoids for inhibition of FLuc and RLuc using different approaches, including QSAR modeling, cell-lysate in vitro luciferase inhibition assays, and in silico molecular docking.50 values determined in vitro indicated different activities for these isoflavonoids within the InterPred highest predicted FLuc inhibition class . The highest in silico probabilities of interference were for biochanin A, formononetin, and genistein, although genistein showed much weaker inhibitory activity in vitro compared to biochanin A and formononetin. Conversely, calycosin showed one of the lowest in silico likelihoods for this class , while it was a more potent inhibitor in vitro than some of the compounds with higher in silico likelihoods in this class. However, overall, InterPred performed well, as all of the isoflavonoids that were predicted to be in the highest likelihood of interference class indeed showed relevant inhibitory activity in vitro.The InterPred model for the prediction of FLuc interference is a newly developed QSAR model that builds on the data for in vitro FLuc inhibition assays from the Tox21 Consortium library. Although it was cross-validated and showed near-perfect performance on the training set , some discrepancies were observed between its predictions here and the in vitro results for FLuc inhibition by these isoflavonoids. The lowest likelihood of interference  was not predicted for any of these 11 isoflavonoids, although four were inactive at concentrations as high as 100 µM in the in vitro assays. On the other hand, the isoflavonoids that were predicted to have the highest likelihood of interference  were also seen as FLuc inhibitors in vitro. These isoflavonoids share structure similarities, and therefore the in silico predictions of interference were similar too. However, the ICFLuc) with 4-hydroxytamoxifen [As the purchase of the purified reporter protein for in vitro inhibition assay is relatively costly, it is necessary to develop cheaper alternative methods for the testing for inhibition in such reporter-gene assays. To some extent, this was addressed in the OECD test guidelines for such compounds. Thus, TG 455 suggests a protocol to test for false-positive results for human estrogen receptor-α agonism by blocking transcription of the reporter gene . Here, we achieved this in a rapid, technically simple, and cost-effective way using the AR-EcoScreen cell lysates. This cell line is included in OECD TG 458 and expresses both FLuc and RLuc . By usinted FLuc . The samntration , which chibitors . The depnt study . This unNone of the isoflavonoids studied here with this cell-lysate in vitro assay showed inhibition of RLuc. The FLuc inhibition of these isoflavonoids is evidently dictated by their structural properties, where some of the structural modifications significantly increased the inhibition of FLuc, such as O-methylation of the basic isoflavonoid structure on the A-ring , and more prominently, on the B-ring . These isoflavonoids have versatile biological activities, which have often been studied in reporter-gene assays with FLuc ,26,27,28These results from the cell-lysate in vitro assays were further supported by in silico molecular docking in the active sites of FLuc and RLuc. Taken together, the in silico docking analysis suggested that these isoflavonoids inhibit FLuc activity by interacting with its D-luciferin binding (sub-)pocket. The very uniform docking modes for these isoflavonoids suggested that their successful molecular recognition is defined by two hydrogen bonds between the ligand and the FLuc residues Thr343 and Ser347, along with several hydrophobic interactions. The proposed binding model also further rationalizes the lack of inhibitory activity of the remaining four isoflavonoids. Here, the inactive glucosides daidzin, genistin, and glycitin, contain a bulky glucose molecule that might hinder the formation of the hydrogen bond with Thr434. Furthermore, the absence of a carbonyl group in S-equol leads to the loss of the hydrogen bond with Ser347.There was also little influence of the luciferase crystal structures used on the obtained isoflavonoid docking poses. The three-dimensional structural alignments of the FLuc X-ray structures demonstrated that the luciferase binding sites remain relatively unperturbed after binding of chemically diverse native ligands. This, in turn, provides more confidence for the assumption that substantial rearrangement within the binding site is not likely to occur also for the newly discovered inhibitors. As these isoflavonoids docked exclusively into the D-luciferin binding pocket, we speculate that their inhibition mechanism is through competition with the native D-luciferin substrate. This appears to be in line with the previously reported increased responses of selected isoflavonoids , which cFinally, this molecular docking also provided plausible structure-based rationalizations for the observed selectivity of the studied isoflavonoids towards FLuc. Namely, the narrower D-luciferin binding pocket can more easily adopt a predominantly planar structure similar to these isoflavonoids, which also share some level of structural similarity to the native D-luciferin molecule. On the other hand, the broader RLuc binding site appears to be less favorable for the uniform and thermodynamically favorable bound ligand conformation.InterPred webserver  is a platform for the prediction of interference in cellular and biochemical assays that use fluorescence or luminescence as the detection technology . InterPrThe selected isoflavonoids were submitted to the InterPred model for luciferase interference in the SMILES format, as obtained from PubChem, and the structures were prepared for QSAR modeling by removal of hydrogens, salt fragments, metal disconnection, sanitization, desolvation, and stereochemistry processing, and computing of the one-dimensional, two-dimensional, and physicochemical descriptors .The results were returned in the form of likelihoods that were in the range of 0 to 1, with the associated standard deviations. Values closer to 1 define higher likelihoods that a compound will cause FLuc interference. The results from InterPred are also color-coded based on the numerical values of the likelihood of FLuc inhibition, as follows: green, likelihood < 0.25 ; yellow, 0.25 ≤ likelihood < 0.50; orange, 0.5 ≤ likelihood < 0.75 ; and red, likelihood ≥ 0.75 .50 values.Glycitein , prunetin , biochanin A , formononetin , and glycitin  were from Extrasynthese . Daidzien , genistein , daidzin , and genistin  were from Sigma-Aldrich . Calycosin  was from Phytolab , and S-equol  was from Toronto Research Chemicals . The FLuc positive control was resveratrol , and the RLuc positive control was H-89 . The isoflavonoids were dissolved in cell-grade dimethylsulfoxide  and serially diluted to prepare 100× stock solutions. All of the isoflavonoids were screened in the in vitro FLuc and RLuc inhibition assays at 1, 10, and 100 µM final concentrations. Dose–response curves were generated for the active isoflavonoids and for the positive controls to determine the ICThe AR-EcoScreen cell line was derived from a Chinese hamster ovary cell line that was stably transfected with the androgen receptor and the FLuc and Rluc reporter genes. These AR-EcoScreen cells are used for detection of androgen receptor agonist and antagonist activities (OECD TG 458), where the expression of FLuc is androgen-receptor-driven, while Rluc is expressed constitutively, to allow detection of cytotoxicity . The AR-6 cells into a 150 cm2 growth flask  diluted in DMSO was added at 10 nM final concentration. This was followed by another 24-h incubation, removal of medium, and addition of 9.4 mL reporter lysis buffer . The growth flask was then stored at −80 °C until use.Preparation of cell lysates for use in the luciferase inhibition assays was through seeding of 4–7 ×10The cell lysate was thawed at room temperature. Stock solutions of the isoflavonoids and positive controls were dissolved in DMSO and 10-fold serially diluted in the cell lysate to the final concentration with 1% DMSO. Twenty microliters of each isoflavonoid in the cell lysate were transferred to 96-well plates in triplicate and incubated for 30 min at room temperature. Then, 30 µL Luciferase Assay Reagent II  was added to each well, and the FLuc luminescence was measured using a microplate reader . The addition of 30 µL of Stop & Glo Reagent  followed, and the RLuc luminescence was recorded using the microplate reader .50), and for the relevant Figures and statistical analysis. Statistical significance as compared to the vehicle control, considered: *, p ≤ 0.05; **, p ≤ 0.01; and ****, p ≤ 0.0001, using one-way ANOVA, followed by post-hoc Dunnett’s tests.The data from the in vitro luciferase inhibition assays in the AR-EcoScreen cell lysate were processed by first subtracting the background value  and then normalization to the vehicle control (1% DMSO), and are expressed as means ± standard deviation of three independent repeats carried out as technical triplicates. GraphPad Prism 8.0  was used for the calculation of the inhibitory concentrations at 50% activity (ICMolecular docking of the isoflavonoids in the available X-ray structures of FLuc containing ligands PTC124-AMP (PDB: 3IES) , aspulviThe molecular docking into the RLuc crystal structure used the coelenteramide ligand (PDB:2PSJ) . The proThe results of the docking calculations are visualized in LigandScout . This prUsing a combination of in silico and in vitro approaches, we demonstrated that RLuc is an appropriate substitute for FLuc in the testing of isoflavonoids, as FLuc was very susceptible to inhibition by the isoflavonoids selected here. On the other hand, none of these isoflavonoids inhibited Rluc in the cell-lysate in vitro luciferase inhibition assay. Furthermore, this study outlines the need for the use of prior testing of reporter cell lysates in routine screening for luciferase inhibition by compounds under investigation, such as those described here , to exclude any interference in the assay system by such compounds in the reporter-gene assays.


Odobenus rosmarus divergens). The ability to track the trophic transfer of iPOC is critical to understanding its value in the food web, but prior methods have lacked the required source specificity. We analyzed the H-Print index, based on biomarkers of ice algae versus phytoplankton contributions to organic carbon in marine predators, in Pacific walrus livers collected in 2012, 2014 and 2016 from the Northern Bering Sea (NBS) and Chukchi Sea. We paired these measurements with stable nitrogen isotopes (δ15N) to estimate trophic position. We observed differences in the contribution of iPOC in Pacific walrus diet between regions, sexes, and age classes. Specifically, the contribution of iPOC to the diet of Pacific walruses was higher in the Chukchi Sea (52%) compared to the NBS (30%). This regional difference is consistent with longer annual sea ice persistence in the Chukchi Sea. Within the NBS, the contribution of iPOC to walrus spring diet was higher in females (~45%) compared to males (~30%) for each year (p < 0.001), likely due to specific foraging behavior of females to support energetic demands associated with pregnancy and lactation. Within the Chukchi Sea, the iPOC contribution was similar between males and females, yet higher in juveniles than in adults. Despite differences in the origin of organic carbon fueling the system (sea ice versus pelagic derived carbon), the trophic position of adult female Pacific walruses was similar between the NBS and Chukchi Sea , supporting similar diets (i.e. clams). Given the higher quality of organic carbon from ice algae, the retreat of seasonal sea ice in recent decades may create an additional vulnerability for female and juvenile Pacific walruses and should be considered in management of the species.The expected reduction of ice algae with declining sea ice may prove to be detrimental to the Pacific Arctic ecosystem. Benthic organisms that rely on sea ice organic carbon (iPOC) sustain benthic predators such as the Pacific walrus ( Odobenus rosmarus divergens) [O. r. divergens) to investigate how sea ice primary production is presently being incorporated in the upper trophic positions of this benthic-dominated system. Declining sea ice not only affects foraging behavior and access to foraging grounds of the Pacific walrus [Primary production in the Pacific Arctic region is partitioned between sympagic (sea ice) and pelagic (open water) sources . On the vergens) ,4. This vergens) . Ice algvergens) . Howeververgens) ,8. It isvergens) ,10. We sc walrus ,12, but O. r. rosmarus) population [The Pacific walrus serves as an interesting test case for several reasons including their benthic based diet, geographic range relative to sea ice areal coverage, the migratory behavior of this species, and their general reliance on sea ice as a physical habitat. Pacific walruses are generalists that consume a wide range of prey items –15. Theypulation .As an ice-obligate species , the geoMacoma) are historically prevalent in this region and areas of high biomass were determined to be significantly correlated with Pacific walrus foraging site selection [South of St. Lawrence Island, in the NBS, is an important wintering ground and breeding area for the Pacific walrus population ,26. The election . The oncelection , possiblelection ,31. Studelection . The NBSelection ,33.Walruses segregate into distinct groups where most adult males remain in Bristol Bay and the Russian Bering Sea coast while females, dependent calves and young walruses follow the ice edge north into the Chukchi Sea each spring where they stay until autumn ,25. Decl25 [25 is only produced in Arctic sea ice by four ice-associated diatom species [25 and serves as an additional suitable proxy for sea ice organic carbon [We measured highly branched isoprenoids (HBIs) lipids, which are biomarkers produced by diatoms with well-defined sea ice and phytoplankton sources –45 and t25 . IP25 is species ,47. HBI c carbon , and serc carbon ,50, the c carbon , and thec carbon ,51–53. Ic carbon . While tc carbon ,55. TherUnderstanding the ecological connections between the Pacific walrus and sea ice, and the associated potential threats owing to climate change, has been highlighted as an ongoing research imperative ,56,57. WThe geographic range of the Pacific walrus is confined to the shallow continental shelf of the Bering and Chukchi seas , with coWe used the Distributed Biological Observatory (DBO) sampling program to provide ecological context for the walrus tissue sampling. The DBO regions include five areas of high benthic biomass in the northern Bering and Chukchi sea, which in turn support higher trophic positions . Severalhttps://arctos.database.museum/home.cfm). Age class data were listed as unknown for all walruses sampled in 2012.Walrus liver tissues were collected and donated from subsistence hunting activities in the NBS during the start of the spring migration (April/May) in 2012, 2014 and 2016 . These hWalruses harvested from the summer (June/July) foraging grounds in the Chukchi Sea were collected by subsistence hunters from Peard Bay, Wainwright, and Utqiaġvik in 2012 and 2014 . Additiohttps://nsidc.org) Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Imager/Sounder (SSMIS), using a 15% threshold to determine the presence vs. absence of sea ice cover, following methods of Frey et al. [Annual sea ice persistence data were calculated using sea ice concentration data from the National Snow and Ice Data Center . The HBIs were identified by their mass ions and RI including IP25 (m/z 350.3), HBI II (m/z 348.3) and HBI III (m/z 346.3). A procedural blank was run every 9th sample.The extracts were analyzed using an Agilent 7890A gas chromatograph (GC) coupled with a 5975 series mass selective detector (MSD) using an Agilent HP-5ms column (30 m x 0.25 mm x 0.25 μm), following established methods . The ove25, HBI II and HBI III:We used the H-Print index  to provi2 = 0.97, p <0.01, df = 23 [Lower values are indicative of proportionally greater sympagic organic carbon and higher values are indicative of proportionally greater pelagic organic carbon. Sea ice organic carbon (iPOC), as a proportion of marine-origin carbon within samples, was estimated using a prior H-Print calibration determined from feeding experiments with known algal species (R df = 23 ).In contrast to the H-Print index, higher iPOC values reflect greater proportions of organic carbon derived from ice algae. We define iPOC values exceeding 50% as indication of elevated sea ice organic carbon in the animal’s diet.2) using the following equation:15N/14N. Accuracy of the data was assured by simultaneous combustion and analysis of the samples with an internal standard of acetanilide, run every 9 samples, which has a well-characterized isotopic composition. Precision was also assessed by analysis of this internal standard. Samples were analyzed on two separate dates and the precision of the acetanilide standard run simultaneously was ±0.21‰ on the first date (n = 5) and ±0.08‰ on the second date (n = 6). The mean δ15N value determined for acetanilide for both dates were within 0.12‰ of each other.Freeze-dried samples were homogenized with a mortar and pestle. 0.4–0.6 mg of tissue was weighed and introduced into tin capsules. The nitrogen stable isotope ratios were measured at the stable isotope facilities at the Chesapeake Biological Laboratory using a Costech elemental analyzer coupled to a ThermoFisher Delta V Isotope Ratio Mass Spectrometer operated in a continuous flow mode. Nitrogen isotope ratios are expressed relative to atmospheric nitrogen (Nwww.r-project.org). Data were normally distributed with equal variances. A significance level of α = 0.05 was used for all tests. We explored the regional influence of sympagic and pelagic HBIs graphically through non-metric multidimensional scaling (NMDS) ordination plots using the R package ‘vegan’ [25, HBI II and HBI III). We assigned sea ice organic carbon (iPOC), H-Print, and sea ice persistence as the environmental vectors . We conducted a two-way ANOVA test with sex and region as factors. Both factors and the interaction of the two were significant (p < 0.01). To account for this interaction, the means were adjusted by grouping sexes among each year and comparing iPOC values by region using the R package ‘lsmeans’, which were reported with standard error (SE). We then carried out planned comparisons using the Bonferroni correction for multiple comparisons to detect differences in mean iPOC values between regions, sex and years. Given the limited age class data associated with the walruses harvested in the NBS, the effect of age class on sea ice organic carbon estimates could only be adequately examined for the Chukchi Sea. The age class analysis was therefore conducted using a Welch two sample t-test to examine the difference between adults and calves.All analyses were conducted using R version 3.6.1  [δ15N values for Macoma calcarea collected from Hanna Shoal in 2012 [M. calcarea values were comparable between the two studies  to generate carbon versus nitrogen plots to examine basal food sources and consumers spatially. The δ13C values were excluded from our study owing to the influence of lipids in our samples and inability to correct for their presence [δ13C in the model, which is not used in the calculation of the TP estimates with one baseline and does not impact these values  and DBO 4  [M. calcarea and surface sediments. We also employed a one-way ANOVA test to explore the relationship between sex, region and nitrogen stable isotope values.Trophic positions were estimated with a Bayesian model approach from the nitrogen stable isotope values using the R package ‘tRophicPosition’, which uses Markov Chain Monte Carlo simulations . This Baonsumer) . For the in 2012  and from in 2012  to serve, n = 36 ; δ15NDBO.3 ± 0.8 ) and allpresence . Howevere values . To do t, n = 7) . Based oSea ice persistence progressively declined in the NBS throughout the study period from 170 days/year in 2012, to 126 days/year in 2014, and 109 days/year in 2016; an overall decline of 61 days (36%) . In contAssigned monthly mean sea ice concentration values ranged from 0–98% overall . In 2012p<0.01), as well as sex . The adjusted iPOC values (mean± SE) in livers were highest overall in the Chukchi Sea with mean female values of 46 ± 6% and male values 58 ± 6%. In the NBS, mean iPOC values for females were 45 ± 3% and 30 ± 3% for males  between males and females in the Chukchi Sea in both 2012 [35 ± 6%  and 36 ± 8% ; p < 0.001) .Pairwise planned comparisons confirmed sea ice organic carbon values were significantly higher in NBS females when compared to NBS males for all 3 years of this study (< 0.001)  in the C< 0.001) . When fa8 = -2.8, p<0.05). Sea ice organic carbon values in calves was 65% ± 25%  versus 42% ± 11% (n = 9) in adults  factors for δ15N values as determined by a two-way ANOVA test. The interaction of the two factors was not significant (p > 0.05). The pairwise comparisons show each group was significantly different, with the exception of Chukchi males versus females.Overall,  in 2016 . In the  in 2014 . For mal in 2014 . Sex andp<0.05).The TP estimates were similar between regions and sexes. Overall, TPs were minimally but statistically higher in the Chukchi Sea at 3.5 compared to 3.2 in the NBS . In the The higher contribution of sea ice organic carbon in the Pacific walrus tissues from the Chukchi Sea compared to the NBS Figs  and 5 arM. calcarea is a useful representative species for tracking sea ice organic carbon contributions to the Pacific walrus diet. While iPOC data in Tellinid clams are currently unavailable to correspond with the timing of the walrus harvests and samples used in this study, mean iPOC values from both regions in 2018 suggest a significant difference in their sea ice organic carbon content (~6% in the Bering Sea and ~40% in the Chukchi Sea) [As stated previously, Pacific walruses are central place foragers that primarily consume bivalves , which ochi Sea) . Given tchi Sea) , which achi Sea) . If the chi Sea) . HoweverWe found no significant relationship between the two sea ice parameters tested (monthly mean sea ice concentration and sea ice persistence) with iPOC values in Pacific walrus tissue. However, this may be unsurprising owing to the fact that this species migrates across a gradient of sub-Arctic to Arctic habitat with distinct sea ice conditions, while also coupling the benthic and pelagic oceanic realms along the way. These large-scale movements likely result in both horizontal and vertical habitat integration. This integration across the entire Pacific Arctic region over the course of a few months during the ice melt season is likely why our sea ice index did not robustly match iPOC values in the walrus liver tissues. The elevated sea ice organic carbon values measured in the Chukchi Sea walruses collected during open water periods (October) exemplify the nuances of analyzing associations with satellite-derived sea ice data. These walruses had a longer period of time to forage in the Chukchi Sea, consuming more of the prey that had previously assimilated sea ice organic carbon than those harvested earlier in the summer as the ice edge retreated. We conclude that direct associations between these biomarkers and sea ice data  in migratory consumers in this region may not always be possible and require further interpretation and perhaps paired with additional trophic markers .Despite the lack of association between the sea ice parameters and sea ice organic carbon, there were interesting patterns within a broader context when considering the sea ice persistence anomalies from 2012 and 2014. For 2012, the NBS was a cold year in which sea ice persistence was well above average . HoweverThe effects of declining sea ice on Pacific walruses may already be evident in the Bering Sea. Observations from the southwestern Bering Sea indicate that occupation of land haul-outs by males in this region may be shifting to northward locations in the Chukchi Sea on the Chukotka Peninsula . There hO. r. rosmarus) in the Canadian Arctic, coupled with measurements of δ13Cphe , suggested nearly exclusive sea ice-derived carbon as the base of the walrus diet at high-latitudes (89–98% iPOC) [In a recent similar study using HBIs in Atlantic walruses (8% iPOC) . These v8% iPOC) ,29.The contribution of sea ice derived organic carbon was higher in females than in males in the NBS, whereas there was no difference between sexes in the Chukchi Sea . This caSecond, to support lactation and pregnancy, females may show selective foraging on more lipid-rich food sources and increase their foraging effort to support the energetic demands during lactation . FemalesThe higher contribution of sea ice carbon in female walrus during the breeding period strongly suggest an elevated reliance of females to sea ice during this period compared to males. The results from Oxtoby et al.  suggesteδ15N values of bulk tissue in predators is a useful tool to estimate trophic position but is influenced by changes in δ15N values at the base of the food web, or baseline. Here, we estimated the trophic position of Pacific walruses taking in account regional values of the δ15N at the baseline (i.e. primary consumers), allowing comparison between the two regions. Trophic position estimates were similar between regions and sexes, with median values ranging from 3.1 to 3.5, which were in alignment with expected values . The mos  [δ15N values in walruses from Chukchi Sea compared to the Bering Sea, that could be driven by differences at the base of the food web, as we found no regional differences in TP when taking in account the δ15N baseline. The higher δ15N values at the base of the Chukchi sea food web can be a result of several processes. The food web in the Chukchi Sea becomes more complex than the NBS as a result of the Pacific water inflow system, where advective processes deliver substantial carbon sources that are in part degraded and deposited as currents move across the shelf [δ15N values in the baseline. The hydrography of the Chukchi Sea around Hanna Shoal has been shown to influence the benthic food web, with increased benthic-pelagic coupling under nutrient rich Anadyr water [δ15N signal in the water column, a process called “sedimentary isotope effect” [The ± 1.2 ‰) . We founhe shelf . With thyr water . As a re effect” ,94. This effect” . The adv effect” .Our study sought to reveal linkages between sea ice algae and Pacific walrus diets, as shifts in primary production driven by climate change will have cascading effects on the food web. HBI biomarkers revealed distinct differences in sea ice organic carbon between walruses sampled from 2012, 2014 and 2016 that varied between sex and region. Sea ice organic carbon was higher in walruses that migrated into the Chukchi Sea and were collected in the summer and autumn months compared to those harvested from St. Lawrence Island in the NBS in the spring. This regional distinction aligns with sea ice organic carbon levels measured in walrus prey items (benthic macrofauna), in addition to the general distribution of HBIs deposited on the seafloor throughout the Pacific Arctic . There wS1 TableMacoma calcarea, served as the benthic baseline. Sea ice organic carbon values for M. calcarea were taken from Koch et al. [The clam species, h et al.  and stabh et al.  and McTih et al. . FG is t(XLSX)Click here for additional data file.S2 Table25, HBI II and HBI III) was used to calculate the H-Print and iPOC values. Monthly mean sea ice concentrations were collected from the assigned DBO region and the month indicated. Sea ice persistence values are reported by year.Sample data includes location/region, year, month, sex, and age class of the specimen. Samples were assigned to either Distributed Biological Observatory (DBO) 1 or 4 for sea ice analysis purposes. The biomarker abundance data (IP(XLSX)Click here for additional data file.


PTEN loss is associated with p110β signaling dependency, leading to the clinical development of p110β-selective inhibitors. Here we use a panel pre-clinical models to reveal that PI3K isoform dependency is not governed by loss of PTEN and is impacted by feedback inhibition and concurrent PIK3CA/PIK3CB alterations. Furthermore, while pan-PI3K inhibition in PTEN-deficient tumors is efficacious, upregulation of Insulin Like Growth Factor 1 Receptor (IGF1R) promotes resistance. Importantly, we show that this resistance can be overcome through targeting AKT and we find that AKT inhibitors are superior to pan-PI3K inhibition in the context of PTEN loss. However, in the presence of wild-type PTEN and PIK3CA-activating mutations, p110α-dependent signaling is dominant and selectively inhibiting p110α is therapeutically superior to AKT inhibition. These discoveries reveal a more nuanced understanding of PI3K isoform dependency and unveil novel strategies to selectively target PI3K signaling nodes in a context-specific manner.Previous studies have suggested that  Understanding the mechanisms driving PI3K isoform dependency in prostate cancer can help the design of future clinical trials. Here, the authors show that gain-of-function mutations in PIK3CA or PIK3CB can confer PI3K p110 isoform dependency and that the direct inhibition of AKT may be superior to PI3K inhibition in PTEN-deficient prostate cancers. In hormone-regulated cancers such as prostate and breast cancer, activation of the PI3K pathway is often driven by mutations/amplification/overexpression of PIK3CA/PIK3CB, or loss of the tumor suppressor PTEN6. According to recent cancer genomic sequencing efforts, PIK3CA alterations are found in more than 30% of breast cancers, and PIK3CA/PIK3CB alterations are observed in 15% of prostate cancers6. Loss of PTEN occurs in approximately 40% of metastatic prostate cancers and represents the most common alteration in the PI3K pathway4. Previous studies using preclinical cell lines and xenograft models have shown that targeting PI3K activity could be a promising therapeutic strategy to treat tumors with PI3K pathway alterations8. However, early attempts to develop PI3K inhibitors did not advance clinically due to nonselective target inhibition, toxicity necessitating dose reductions, and the recently described concept of relief of feedback inhibition, all of which reduced efficacy10.The phosphoinositide 3-kinase (PI3K) pathway is one of the most altered oncogenic pathways in human cancerPIK3CA) and p110β (PIK3CB) are the dominantly expressed catalytic subunit isoforms11. Oncogenic activity of PI3K-altered tumors is often dependent on different p110 isoforms16. In breast cancer, activating PIK3CA mutations are dominant drivers of PI3K signaling whereas in PTEN-deficient prostate cancer, such activity is reported to be driven by p110β17. These findings subsequently propelled the development of the next generation of agents designed to target individual p110 isoforms in a selective manner20.The PI3K holoenzyme is composed of a catalytic subunit (p110) and a regulatory subunit . In epithelial lineages, p110α  for metastatic prostate cancer patients with tumors displaying loss of PTEN25. The results of this trial have led to the accrual of a phase III study that recently met its co-primary endpoint in PTEN-loss metastatic castration resistant prostate cancer (mCRPC) demonstrating a significant improvement in RPFS. Additionally, the recent phase III SOLAR1 trial reported a significant improvement in progression-free survival for breast cancer patients harboring PIK3CA mutations when treated with BYL719 (p110α inhibitor) plus fulvestrant (ER degrader)28. In prostate cancer, while previous studies suggest that loss of PTEN is associated with p110β dependency and early phase clinical trials have been developed to evaluate the efficacy of p110β-selective inhibitors in this context, several caveats to this approach remain. First, the original studies reporting that loss of PTEN promoted p110β dominant signaling were performed in a limited number of models. Secondly, investigators have shown that in the context of PTEN loss, inhibition of p110β leads to relief of feedback inhibition of the non-dominant p110 isoforms resulting in PI3K rebound signaling and diminished efficacy29. Despite these caveats, enthusiasm for p110 isoform-selective inhibitors for the management of PI3K pathway-altered prostate cancer continues, with the hope of maximizing efficacy and minimizing toxicity.Previous studies have documented a reciprocal negative feedback regulation between PI3K activity and hormone receptor (e.g. androgen receptor) signaling in hormone-dependent cancers including breast and prostate cancerPTEN status and PI3K alterations on p110 isoform dependency, further study the role of relief of feedback between p110 isoforms across the common PI3K pathway alterations and reveal a novel and actionable mechanism of resistance to PI3K inhibition.Here, we analyze a broad collection of prostate cancer models to identify the appropriate molecular context and therapeutic strategies to selectively target PI3K pathway-altered prostate cancers. We define the impact of PTEN, PIK3CA, PIK3CB, and PIK3R1) are seen in more than 50% metastatic castration-resistant prostate cancer (mCRPC)  display amplification, mutations, or mRNA upregulation in PIK3CA or PIK3CB  Fig. . Among t3CB Fig. . Additiohip Fig. . This hi30. We also analyzed two previously established prostate cancer cell lines, LNCaP (PTEN loss) and CWR22Pc (PIK3CA Q546R). These prostate cancer models harbor various alterations in the PI3K pathway and exhibit differential PI3K signaling activity, as shown by the levels of downstream AKT phosphorylation  established from metastatic tumor biopsies of mCRPC patientsion Fig. . FocusinPTEN-deficient prostate cancer has been reported to be dependent on p110β, but the models evaluated were limited in number15. Using our collection of PDOs, we first tested if their PI3K activity is dependent on p110α or p110β by treating them with a p110α-selective inhibitor (BYL719) or a p110β-selective inhibitor (AZD8186). We used both compounds at their on-target dosage that does not cross-inhibit other PI3K isoforms1. Surprisingly, despite their PTEN deficiency, MSK-PCa3, MSK-PCa11, and MSK-PCa8 showed selective sensitivity to p110α inhibition (BYL719) rather than p110β inhibition (AZD8186), while MSK-PCa1 displayed p110β dependency similar to LNCaP   using lentiviral transduction. Ectopic expression of mutant p110αE545K or p110βE1051K further enhanced baseline PI3K activity in both the PTEN-null  and PTEN wild-type (CWR22Pc) backgrounds  at its on-target or higher concentration dosing in in vitro growth assays  Fig. . Interesors Fig. . Based onds Fig. . These ring Fig. . LNCaP-pays Fig. . Importawth Fig. . Similaring Fig. . Additioion Fig. .Fig. 2AcPIK3CA/PIK3CB alterations involve amplification or mRNA upregulation of wild-type alleles, we evaluated if ectopic expression of wild-type PIK3CA impacted PI3K signaling. Indeed, overexpression of p110αWT in a PTEN deficient (p110β-dependent) pre-clinical model promoted PI3K signaling through p110α, impacting isoform selective signaling dependency. However, this effect was not as robust as the expression of constitutive activating PIK3CA mutations , reactivation of PI3K signaling occurred through p110α in MSKPCa1 and LNCaP , selective inhibition of p110α (BYL719) resulted in feedback activation of PI3K signaling through p110β  following p110α inhibition  a similar phenotype of residual rebound PI3K signaling is observed following combined p110α and p110β inhibition , while dual inhibition of both isoforms significantly reduced the level of pAKT  treatment, while dual inhibition of both isoforms significantly repressed pAKT level  when combined with p110α + p110β dual inhibition in MSK-PCa12  + AZD8186 (p110β inhibitor) was able to further decrease PI3K signaling and repress cell proliferation in MSK-PCa12  at 500 nM in vitro and at 50 mg/kg in vivo , AKT inhibition showed greater efficacy at suppressing cell growth than PI3K inhibition even when p110α activating mutations were present .Given the recent positive interim analysis of the phase III ipatasertib and abiraterone clinical trial in mCRPC patients with ion Fig. . Also, Aion Fig. . To direion Fig. . Howeverent Fig. . This asPTEN, inhibiting AKT may be more efficacious than targeting PI3K, as AKT inhibitors are effective independent of RTK levels or PIK3CA mutations. Conversely, in PIK3CA-mutant PTEN wild-type prostate and breast cancers, p110α inhibition provides superior antiproliferative effects. Furthermore, as we have previously published, due to reciprocal feedback inhibition between the PI3K and AR pathways, combined inhibition of these pathways is required in prostate cancer , BYL719, a p110α-selective inhibitor combined with fulvestrant significantly improved progression-free survival in ER-positive, PIK3CA-mutant breast cancers26. Because PIK3CA (p110α) and PIK3CB (p110β) are ubiquitously expressed in tumors of epithelial origin11, understanding p110α or p110β dependency across different genetic backgrounds is critical for selectively targeting the PI3K signaling axis in PI3K pathway-altered tumors.Targeting PI3K alterations to treat human malignancies has been proposed for more than a decade, yet previous clinical trials using PI3K pathway inhibitors against multiple human malignancies did not generate profound success due to significant toxicities and low efficacyPTEN loss-of-function alterations. Limited evidence suggesting that PI3K signaling in PTEN-deficient tumors is more dependent on p110β led to the development of several phase I clinical trials evaluating p110β-selective inhibitors in PTEN-deficient mCRPC patients28. Here we characterized an expanded cohort of patient-derived organoid (PDO) models that harbor loss of PTEN to define PI3K isoform dependency. Surprisingly, we found that PTEN-status is not the determinant driver of p110 isoform selectivity. While the mechanisms determining p110 isoform dominance in PTEN-deficient prostate cancer remain unknown, this finding has important clinical implications that loss of PTEN alone will not be a biomarker of p110β inhibition sensitivity.In metastatic prostate cancer, PI3K pathway alterations are seen in more than 50% of patients, among which more than 80% harbor PIK3CA/PIK3CB/PIK3R1 alterations in the setting of both PTEN wild-type and PTEN loss. Through the modeling of PIK3CA or PIK3CB alterations using multiple PDO and cell line models, we discovered that activating mutations of p110α or p110β can drive or shift isoform dependency. This finding indicates that p110 isoform-activating mutations could be a potential biomarker for the selection of an isoform-selective inhibitor, especially in the context of PIK3CA mutant, PTEN wild-type prostate cancer. Our results provide support for the development of clinical trials evaluating combined p110α (BYL719) and AR inhibition in patients with mCRPC harboring PIK3CA-mutant, PTEN wild-type cancers.This unexpected finding raises the question about what molecular mechanisms drive p110 isoform selectivity. Indeed, through our genomic analyses of mCRPC, we found frequent occurrence of PTEN-loss but not in the setting of wild-type PTEN. In prostate cancers harboring loss of PTEN, this feedback inhibition is reciprocal between the p110 isoforms and occurs in the context of p110α or p110β-dominant signaling. Although dual inhibition of p110α+p110β can efficiently block PI3K relief of feedback inhibition and achieve potent anti-tumor effect in some prostate cancers harboring loss of PTEN, we also identified that resistance to p110α+p110β inhibition can occur through IGF1R-mediated PI3K residual activity. While addition of an IGF1R inhibitor, linsitinib, restored p110α + p110β sensitivity in resistant lines, this combination is associated with significant toxicity limiting clinical development. Importantly, we show that the use of an AKT-selective inhibitor such as ipatasertib (GDC-0068) is not only able to overcome this resistance, but generally performs superior to pan-PI3K inhibition with lower toxicity across PTEN-deficient pre-clinical models. Moreover, these results are also supported by a recent phase II and phase III clinical trial for mCRPC patients in which treatment with ipatasertib plus abiraterone has achieved a significantly longer RPFS in PTEN-deficient patients25. Furthermore, in the metastatic breast cancer, PTEN alterations are shown to confer resistance to p110α-selective inhibition, demonstrating the need for an alternative strategy to target PI3K signaling33. Our results suggest AKT inhibitors may also be superior to pan-PI3K inhibition in breast and prostate cancers harboring loss of PTEN, however in the context of PIK3CA mutant PTEN wild-type cancers there is limited efficacy to AKT inhibition and targeting p110α is superior, secondary to dual suppression of downstream PI3K and MAPK signaling. Importantly, PIK3CA mutant PTEN wild-type prostate cancers should not be broadly grouped with PTEN loss cancers in future AKT inhibitor clinical trials. Taken together, as we gain further insights into the mechanisms driving p110 isoform dependency and validate isoform selective biomarkers, therapeutic trials may be developed to selectively target a specific isoform through a precision medicine approach.For the first time, we show that PI3K relief of feedback inhibition is robust and therapeutically meaningful in the context of 30. MSK-PCa11, MSK-PCa12, MSK-PCa15, and MSK-PCa16 were newly generated and can be obtained from Dr. Yu Chen’s group upon request. PDOs were maintained and cultured in standard organoid culture condition47. LNCaP (#ATCC® CRL-1740™) and DU145 (#ATCC® HTB-81™) were obtained from American Type Culture Collection . MCF7(#ATCC® HTB-22™), T47D (#ATCC® CRL-2865™), MDA-MB-453(#ATCC® HTB-131™), EFM19, CAL51 and BT20 (#ATCC® HTB-19™) cell lines were gifts from Dr. Guotai Xu (MSKCC). CWR22Pc was a gift from Marja T. Nevalainen , and CWR22Pc-EP was generated and maintained as previously described49. Cell lines were maintained in RPMI  or DMEM . Additional supplements for all cell lines were 10% FBS , PenStrep (1%), L-glutamine (1%), sodium pyruvate (1%), and HEPES pH=7.6 (1%). All cell lines and prostate cancer organoids used in our studies have tested negative for mycoplasma using the MycoProbe Mycoplasma Detection Kit (R&D Systems) within one month of initiating experiments. All cell lines and organoids were freshly thawed and only passaged to achieve the number of cells required for in vitro or in vivo experiments. Cell lines and organoids developed by our group were validated by STR genotyping protocols.Patient-derived organoids (PDOs)  were obtained from Dr. Yu Chen’s laboratory through collaboration. MSK-PCa1, MSK-PCa2, MSK-PCa3, and MSK-PCa8 were previously published by Dr. Yu Chen’s group3 cells in 100 μL media were seeded per well in a 96-well plate. Drugs were administered the next day to a total volume of 200 μL of media per well, and media and drugs were replaced every 48 h to maintain their efficacy. The number of viable cells was measured using CellTiter-Glo Luminescent Cell Viability Assay kit . Luminescence was detected using a Veritas Microplate Luminometer (Turner Biosystems). Luminescence signal representing relative number of cells was recorded as RLU (relative light units) according to manufacturer’s instruction. CellTiter-Glo 2.0 reagent was aliquoted into working solutions and stored at −80 °C, then at each assay time point, thawed to room temperature. Equal volume of reagent was added to wells of 96-well plates using a multi-channel pipette. Plates were incubated in room temperature on an orbital shaker for 10 m to stabilize the reaction. All cell proliferation assays were repeated in at least two independent biological replicates.5 × 10PIK3CA wild-type , PIK3CA mutant (E545K) , and PIK3CB wild-type . PIK3CB mutant (E1051K) was obtained through site-directed mutagenesis with plenti-PIK3CB vector. The PI3KCB cDNA mutant was generated following manufacture’s instruction using QuikChange II XL Site-Directed Mutagenesis Kit, 10 Rxn . Inducible PTEN expression lentivector was obtained as a gift from Dr. Wouter Karthaus (MSKCC). Doxycycline (500 ng/mL) was added to LNCaP-EV (empty vector) or LNCaP-PTEN cells for 8 h for PTEN induction. LNCaP-EV cells serve as control. All expression vectors were sequenced verified.pLenti-Lentiviral vector (pLenti-C-Myc-DDK-P2A-Neo)  was used to express 29. The PI3K p110α-selective inhibitor BYL719 was purchased from LC Laboratories (cat# A-4477). BYL719 was dissolved in 0.5% methyl cellulose and dosed at 25 mg/kg daily P.O. The PI3K p110β-selective inhibitor AZD8186 was kindly provided by Laboratory of Neal Rosen and purchased from SelleckChem (cat# S7694). AZD8186 was dissolved in 0.5% HPMC + 0.1% Tween80 and dosed at 75 mg/kg b.i.d P.O. Pan-PI3K inhibitor BKM120 was purchased from SelleckChem (cat# S2247). BKM120 was dissolved in 0.5% methyl cellulose and dosed at 50 mg/kg daily P.O. IGF1R/INSR inhibitor linsitinib was purchased from LC Laboratory (cat# L-5814). Linsitinib was dissolved in 25 mM Tartaric Acid and dosed at 40 mg/kg daily P.O. AKT inhibitor ipatasertib was provided by Genentech under an MTA and was dissolved in 0.5% Methylcellulose and 0.2% Tween-80 for in vivo study.The AR inhibitor MDV3100, enzalutamide, was synthesized by the MSKCC chemistry core. MDV3100 was used in our studies in vitro at a concentration of 10 mmol/L and in vivo with a dose of 10 mg/kg/day6 cells resuspended in 100 μL of 1:1 mix of growth media and matrigel  were engrafted or injected into 6 to 8-week-old CB17-SCID male mice (Taconic). Tumor volume was measured weekly with Peira TM900 (Peira Scientific Instruments) and was calculated using the formula: Volume 1⁄4 Length × Width × Height. A total of 5 mice (10 tumors) per group were used to assay tumor growth in vivo in response to treatment. Treatment was initiated when tumor volume reached ~200 mm3. All experiments were approved by our IACUC protocol 06-07-012.2 × 10Cell lysates were prepared in RIPA buffer supplemented with proteinase and phosphatase inhibitors. Proteins were resolved on NuPAGE Novex 4–12% Bis–Tris Protein Gels (Thermo Fisher Scientific) and transferred electronically onto a PVDF 0.45 mm membrane (Millipore). Membranes were blocked in 5% BSA diluted in Tris buffer saline plus 0.1% Tween 20 (TBST) for 1 h at room temperature and were incubated with primary antibodies in 5% BSA at 4 °C overnight. After 3 washes of 10 m in TBST, membranes were incubated with secondary antibodies in 5% BSA at room temperature. All immunoblots were performed with three independent biological repeats. Representative and consistent findings were shown.PTEN , phospho-PRAS40 (Thr246) , PRAS40 , phospho-IGF1R (Tyr1135/1136)/INSR (Tyr1150/1151) , phospho-IGF1R (Tyr1135) , IGF1R , INSR , phospho-p44/42 MAPK (Erk1/2) (Thr202/Tyr204) (D13.14.4E) XP , p44/42 MAPK (Erk1/2) (137F5) , phospho-MEK1/2 (Ser217/221) (41G9) , MEK1/2 (D1A5) , PI3K kinase P110α , PI3K kinase P110β , HSP90 , Cyclophilin B , DDK tag . All western blot antibodies were used at a 1:1000 dilution unless specificied.The following antibodies were used for Western blotting: AR , β-actin , phospho-AKT (Ser473) , phospho-AKT (Thr308) , AKT , phospho-S6 ribosomal protein , S6 (5G10) ribosomal protein , PTEN in PDOs, human prostate and breast cancer cell lines, sgRNA against human PTEN exon 1 was designed (https://zlab.bio/guide-design-resources/) and cloned into the LentiCRISPRv2 backbone . Lentiviruses for sgRNAs were generated in 293 T cells by standard methods using Lipofectamine 2000 . Cell lines were infected with lentivirus for 48 to 72 h and selected with puromycin (1 μg/mL) for 7 days. The target guides sequences are listed in Supplementary data To knock out 50. The target guides sequences are listed in Supplementary data The lentiviral  miR-E-based shRNA expression vectors were generously gifted by Dr. Johannes Zuber 51 and quantified into Transcripts Per Kilobase Million (TPM) using Cufflinks with upper quartile normalization (v2.1)52. Heatmaps analysis were generated using R-studio (package pheatmap 1.0.12). RTK normalized expression values are available in Supplementary data RNA was isolated from organoids with low passage number (less than 5) using Qiagen RNeasy kits. Library preparation and RNA sequencing were performed by MSKCC Genomics Core Laboratory using Illumina HiSeq with 50 or 75 bp paired-end reads and ∼30 million reads were generated for each sample. The reads were mapped human genome reference sequence GRC37/hg19) using STAR (v2.3)9 using SAll experiments involving animals were approved by MSKCC Animal Ethics Committee (Judith Farber).Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesMao_Supplementary Data 1Mao_Supplementary Data 2Mao_Supplementary Data 3Reporting summary