Cyclin-dependent kinases are involved in the regulation of cancer-initiating processes like cell cycle progression, transcription, and DNA repair. In hematological neoplasms, these enzymes are often overexpressed, resulting in increased cell proliferation and cancer progression. Early (pre-)clinical data using cyclin-dependent kinase inhibitors are promising but identifying the right drug for each subgroup and patient is challenging. Certain chromosomal abnormalities and signaling molecule activities are considered as potential biomarkers. We therefore summarized relevant studies investigating cyclin-dependent kinase inhibitors in hematological malignancies and further discuss molecular mechanisms of resistance and other open questions.Genetically altered stem or progenitor cells feature gross chromosomal abnormalities, inducing modified ability of self-renewal and abnormal hematopoiesis. Cyclin-dependent kinases (CDK) regulate cell cycle progression, transcription, DNA repair and are aberrantly expressed in hematopoietic malignancies. Incorporation of CDK inhibitors (CDKIs) into the existing therapeutic regimens therefore constitutes a promising strategy. However, the complex molecular heterogeneity and different clinical presentation is challenging for selecting the right target and defining the ideal combination to mediate long-term disease control. Preclinical and early clinical data suggest that specific CDKIs have activity in selected patients, dependent on the existing rearrangements and mutations, potentially acting as biomarkers. Indeed, CDK6, expressed in hematopoietic cells, is a direct target of MLL fusion proteins often observed in acute leukemia and thus contributes to leukemogenesis. The high frequency of aberrancies in the retinoblastoma pathway additionally warrants application of CDKIs in hematopoietic neoplasms. In this review, we describe the preclinical and clinical advances recently made in the use of CDKIs. These include the FDA-approved CDK4/6 inhibitors, traditional and novel pan-CDKIs, as well as dual kinase inhibitors. We additionally provide an overview on molecular mechanisms of response vs. resistance and discuss open questions. Despite the clinical implementation of novel treatments like kinase inhibitors, hypomethylating agents or pathway modulators during the last decades, several hematological malignancies still face a poor prognosis. Relapsed or refractory courses are particularly difficult to manage, often exhibiting multiple drug resistances and intimidating survival rates ,2,3,4. TCell cycle regulation is a key mechanism to prevent malignant cell proliferation and uncontrolled cell division. Aleem and Arceci reviewed the roles of CDKs in controlling cell cycle and development of hematological malignancies in detail . Here, wINK4A, the most frequently deleted locus in human cancer. Translocations of the MLL gene locus are common in acute myeloid leukemia (AML) and account for most infant ALL cases. CDK6 is a direct target of MLL fusion proteins and thus activated. Finally, CDK6 can be activated by FLT3-ITD-mediated down-regulation of cyclins D2 and D3. Besides CDK6, other CDKs are also involved in leukemogenesis. For example, the AML driver mutation FLT3-ITD is an activator of CDK1. Further, mutations and deletions of the cyclin C and CDK19 locus on 6q21 result in altered Notch1 regulation especially in T-ALL . Be. Be40]. ML cells .T315I mutated CML, via reducing proliferation and inducing G1 arrest. This is of importance because tyrosine kinase inhibitor resistance is frequently observed in this CML subtype, leading to challenging clinical problems [Although there is a clear connection between BCR-ABL1 fusion and cell cycle regulation, only very limited data is available for the evaluation of CDKIs in chronic myeloid leukemia (CML). Rangatia and Bonnet have shown that lack of BCR-ABL1 leads to G1 phase arrest and a decrease in cyclin D1. Physiological CDKIs p21 and p27 subsequently exhibited increased gene expression . Schneewproblems . In ALL,problems ,44. Incrproblems ,46. In mproblems ,47.FOXO3A can additionally control p27 gene expression. However, it was not influenced in palbociclib-resistant cells; ruling out the possibility of FOXO3A directly induced p27 downregulation. Palbociclib-sensitive cell lines exhibited a similar drop in p27 gene expression, while protein abundance remained stable. Hence, the p27-downregulating effect is rather due to posttranslational modification than reduced p27 gene expression  is another CDK4/6 inhibitor that demonstrated significant anti-proliferative and apoptosis-inducing effects in AML and B-ALL cell lines and primary samples, probably mediated via G1 arrest and senescence . A recenNOTCH1-mutant and wildtype T-ALL and found both subtypes sensitive to the inhibitor. The combination with glucocorticoid dexamethasone and mTOR inhibitor everolimus acted synergistically in vitro and in vivo. In contrast, antagonistic effects were observed with several drugs used in T-ALL standard chemotherapy including methotrexate, mercaptopurine, asparaginase, or doxorubicin [Pikman et al. investigated ribociclib in orubicin .CD25 and RUNX1 expression upon CDK6 inhibition and that CD25 ablation results in T-ALL leukemogenesis. They further showed that CD25 mediates the therapeutic response to ribociclib, suggesting CD25 deletion as a potential mechanism of resistance to CDK6 inhibitors as well as predictive marker for ribociclib response  has been more widely evaluated in lymphoma. Here, inhibited proliferation and induced apoptosis was reported in germinal center-derived B-cell lymphoma cell lines, but not in activated B-cell like diffuse large B-cell lymphoma cell lines . In a clMLL-rearranged AML cell lines and xenografts [Further preclinical studies found abemaciclib effective in nografts  as well nografts . Nakatannografts . Moleculnografts .The novel CDK4/6 inhibitor lerociclib (G1T38) was capable of decreasing Rb phosphorylation and induced G1 cell cycle arrest in leukemia and lymphoma cell lines in vitro. Of note, lerociclib demonstrated a superior efficacy compared to palbociclib and did not induce severe neutropenia in an estrogen receptor positive breast cancer dog animal model, which is a common side effect of CDK4/6 inhibitors. Using mouse xenograft models, the authors further demonstrated that lerociclib accumulated within the tumor but not in plasma, implying less severe effects on myeloid progenitor cells compared to palbociclib therapy. Indeed, plasma concentrations after palbociclib treatment were significantly higher than the concentration needed to inhibit cell proliferation in several cell lines. In contrast, after lerociclib treatment, plasma concentrations dropped faster. The authors thus claim that palbociclib-induced neutropenia is a product of CDK4/6 inhibition in the bone marrow, preventing proliferation of healthy bone marrow cells .CDK4/6 inhibitors including the novel promising molecule lerociclib are without doubt the most intensively researched group of CDKIs in both, solid and hematological malignancies. While palbociclib, ribociclib, and abemaciclib already obtained FDA approval for breast cancer, current preclinical and clinical studies for leukemia and lymphoma also focus on inhibitors targeting other CDKs.MLL in acute leukemias, are also part of the super elongation complex, thus mis-localizing CDK9 to HOX gene promoters and inducing abnormal CDK9 expression, cell growth, and proliferation [CDKs 7, 8, and 9 are novel emerging targets in preclinical research. Indeed, recent data reveal anti-leukemic activity upon inhibition of these transcriptional regulators. CDK9 is a global transcriptional regulator and part of the super elongation complex controlling RNA polymerase II phosphorylation and elongation. AFF family members, which are frequently fused to feration . Anotherferation .So far, AZD4573 is the only selective CDK9 inhibitor invested clinically in hematological malignancies. A preclinical study on different hematological neoplasms proved significant induction of apoptosis via MCL-1 suppression in vitro and in vivo . The samMCL1 gene expression after CDK9 inhibition while fludarabine had the opposite effect. Combined application of CDKI-73 and fludarabine downregulated RNA polymerase II mediated genes MCL1, XIAP, CCND1, and CCND2. Of note, synergistic effects were also observed under CD40L-expressing pro-survival co-culture conditions with initial fludarabine resistance [The non-selective CDK9 inhibitor CDKI-73 proved anti-proliferative and pro-apoptotic capacity in chronic lymphoblastic leukemia (CLL) , diffusesistance . In diffsistance . The samsistance . Many mosistance ,69,70,71CDK8 regulates transcription as part of the mediator complex or by phosphorylation of transcription factors . In primRUNX1/ETO rearranged cell line [First CDK7 inhibitors are also arising and are being tested in AML cell lines. The CDK7/12/13 inhibitor THZ1 showed anti-proliferative effects and induced apoptosis in a ell line . A preclell line .SY-1365, which is under clinical investigation for solid tumors, decreased MCL-1 protein levels and induced transcriptional changes mainly of oncogenic transcription factor genes and members of cell cycle and DNA damage repair related pathways. Of note, this inhibitor was more effective in cells with low BCL-XL expression. When combined with BCL-2 inhibitor venetoclax, antitumor effects were synergistically increased in vitro and in vivo . FinallyCollectively, CDK7/8/9 inhibitors hold promise for being implemented in trials because of their unique ability to modify transcriptional processes and regulate apoptosis. Other approaches featuring down-regulation of these kinases are less specific, resulting in a broader spectrum of mechanistic actions to be dealt with.Flavopiridol  is a first generation pan CDK inhibitor, targeting CDKs 1, 2, 4, 6, 7, and 9. It induces cell cycle arrest in ALL and AML cell lines as well as leukemia and lymphoma animal models ,80. PrecClinical efficacy was observed in hematological neoplasms including CLL and AML, especially in AML as part of the FLAM regimen (flavopiridol followed by cytarabine and mitoxanthrone) ,84. ClinSeveral mechanisms of resistance have been described for flavopiridol . MahoneyMLL rearrangement, primary patient cells, and in vivo models [Dinaciclib (SCH727965) is now widely evaluated in hematological malignancies. By inhibiting CDKs 1, 2, 5, and 9, dinaciclib reduces cell viability, induces apoptosis and cell cycle arrest in ALL and AML cell lines, also with o models ,90,91,92In CLL, dinaciclib downregulates MCL-1 gene and protein expression and potently induces apoptosis in patient-derived cells . InteresIn mantle cell lymphoma, Höring et al. pursued a combined MCL-1 inhibiting and NOXA stabilizing approach using dinaciclib and fatty acid synthase inhibitor orlistat. They observed synergistically-induced NOXA-dependent apoptosis in mantle cell lymphoma cell lines and primary samples along with tumor growth inhibition in vivo . In advaFurther preclinical evaluation detected increased doxorubicin response rates in myeloma cell lines after low dose dinaciclib treatment, boosting growth inhibition and promoting senescence . InteresFurther pan CDK inhibitors are now also tested in the clinical setting. Besides the CDKs targeted by dinaciclib , AT7519M also inhibits CDK4, still inducing apoptosis in vitro and in vivo and reducing proliferation in myeloma and CLL ,104. TwoMCL-1 and c-Myc downregulation was only reached in an intermittent drug administration schedule that should be considered in clinical practice [Voruciclib (P1446A), a CDK1/2/4/5/6/8/9 inhibitor, was evaluated in a phase I study recruiting follicular lymphoma, mantle cell lymphoma, marginal zone lymphoma, small lymphocytic lymphoma, CLL, diffuse large B-cell lymphoma, and AML patients after demonstrating significant potential in preclinical studies ,107. Compractice .The CDK1/4/9 inhibitor P276-00 showed promising in vitro and in vivo results in AML , myelomaINK4C as a potential tumor suppressor gene in Hodgkin lymphoma [INK4A expression has been observed in Reed–Sternberg cells of Hodgkin lymphoma cases [Roniciclib (BAY1000394) targets the same CDKs as flavopiridol  and achieved SD in three out of seven patients with lymphoid neoplasms . Of notelymphoma . Finallyma cases .Due to its variety in mechanistic pathways, pan CDK inhibition offers a broad range of possibilities to target virtually every hematological subtype. Most progress has been made for dinaciclib, which is already investigated in clinical trials; however, results are ambiguous. Chemical modifications or combinatorial schedules might be beneficial to increase the therapeutic outcome.Developing resistance to CDKI monotherapy is frequently seen in both preclinical and clinical studies. Hence, novel approaches are being evaluated, including dual kinase inhibitors. In the AML setting, most inhibitors target one or more CDKs and FLT3. AMG925 and FN-1501 inhibit FLT3 in combination with CDK4 and CDK2/4/6, respectively. Both drugs significantly induced apoptosis and anti-leukemic effects as well as ERK/AKT/Rb dephosphorylation in vitro and in vivo ,118.TG02, a pan CDK and FLT3 inhibitor, further targets JAK2. This inhibition promoted G1 arrest, apoptosis, and tumor regression in AML cell lines, in vivo models, and primary samples ,120,121.Additionally in myeloma, pan CDK/JAK/Src/AMPK/GSK3β inhibitor RGB-286638 achieved cytotoxicity in vitro and prolonged animal survival . BesidesStructural similarity of CDK ATP binding sites is a major challenge in the design and development of selective inhibitors. Proteolysis-targeting chimeras (PROTACs) are a novel approach of CDK elimination. These synthetic molecules comprise a ligand for the protein of interest, for example, CDK6, and another ligand which recruits E3 ligases. E3 ligases then induce ubiquitination and proteasomal degradation of the target structure. In a recent study of De Dominici et al. investigating BCR-ABL1-positive ALL, PROTAC YX-2-107 was designed to bind CDK4/6, reducing CDK6 enzymatic activity and inducing degradation in vitro. Further, S phase transition was suppressed and Rb and FOXM1 dephosphorylation was observed. In vivo, PROTAC YX-2-107 achieved a comparable or better reduced leukemia burden in PDX mice compared to palbociclib . AnotherNovel and innovative strategies like dual kinase inhibition or PROTAC design are important steps towards an improved targeted therapy. Further preclinical studies in syngeneic and xenograft models are needed to identify candidates with a high likelihood of proving beneficial in a clinical setting.A major challenge for receiving long-term disease free-survival in hematological diseases is successful targeting of the malignant niche in the bone marrow. The latter is a complex microenvironment in which hematopoietic stem cells interact with multiple non-hematopoietic cell types. Just like normal stem cells, leukemia stem cells, hosted in the stem cell niche, undergo self-renewal, can efflux drugs, and have a quiescent cell cycle status, which makes them difficult to target. Especially CDK6 plays a critical role in hematopoietic stem cell differentiation . A compaIschemia-like conditions are the driving force of leukemia stem cell refractoriness to classical drugs as well as targeted agents, such as imatinib mesylate . Though The field of hematological neoplasms is very heterogeneous with each entity featuring individual characteristics and challenges. However, most of them are still difficult to treat, indicated by high relapse rates, intimidating prognoses, and lack of durable curative therapies. CDKs and their regulating cyclins are of major importance for the tumorigenic potential of developing leukemia or lymphoma cells and frequently dysregulated in those malignancies. Modulation of CDK expression and activity thus represents a promising strategy to target aberrant cell cycle progression and proliferation in hematological tumor cells.The results of extensive preclinical evaluations are promising, with several clinical studies currently testing CDKIs in most hematological malignancies. CDK4/6Is palbociclib, abemaciclib, and ribociclib are already FDA-approved for solid neoplasms, raising hopes for a subsequent clinical implementation in hematological malignancies in the near future. Interestingly, clinical trials have mainly been finished for lymphoma  and CLL patients while data on acute leukemias are lagging behind. Published results indicate that combined therapy with other small molecule inhibitors like ibrutinib or bortezomib as well as inhibitors of anti-apoptotic proteins may have the capacity to circumvent CDKI resistance development. Importantly, most clinical studies so far have been conducted in heavily pretreated relapsed/refractory patient cohorts, highlighting the potential of CDK targeting for hematological malignancy management. Another open question that must be addressed in future studies is why inhibitors of the same class result in highly variable response rates in the same entity. This underlines the importance of further investigation on biomarkers, resistance mechanisms, and exact modes of action.This is an exciting period potentially improving the therapeutic outcome of leukemia and lymphoma patients; however, there are still unanswered questions and several issues to be addressed. Clinical data on acute leukemias are still missing while results in other entities are ambiguous or obtained from rather small cohorts. Appropriate combination partners need to be identified, ideal application sequences and dosages are to be evaluated, and biomarkers are necessary to offer a useful and potent CDKI-based therapy for the special needs of every molecular subgroup in a variety of hematological entities.


In many human cancers, the rate of cell growth depends crucially on the size of the tumor cell population. Low, zero, or negative growth at low population densities is known as the Allee effect; this effect has been studied extensively in ecology, but so far lacks a good explanation in the cancer setting. Here, we formulate and analyze an individual-based model of cancer, in which cell division rates are increased by the local concentration of an autocrine growth factor produced by the cancer cells themselves. We show, analytically and by simulation, that autocrine signaling suffices to cause both strong and weak Allee effects. Whether low cell densities lead to negative (strong effect) or reduced (weak effect) growth rate depends directly on the ratio of cell death to proliferation, and indirectly on cellular dispersal. Our model is consistent with experimental observations from three patient-derived brain tumor cell lines grown at different densities. We propose that further studying and quantifying population-wide feedback, impacting cell growth, will be central for advancing our understanding of cancer dynamics and treatment, potentially exploiting Allee effects for therapy. A common feature of tumor growth is the production, by the cancer cells themselves, of hormones known as growth factors that increase the rate of cell division. This type of signalling makes the growth rate of the tumor depend on the population size in a non-linear manner, and the growth rate might become low or negative for small population sizes. This is known as the Allee effect which has been studied extensively in ecology. We have developed a computational model that can explain the Allee effect in terms of growth factor signalling, and show by mathematical analysis of the model that the magnitude of the Allee effect depends on the ratio of cell death to proliferation, as well as the properties of the growth factor. In addition we show that the model is consistent with experimental observations from three different cell lines derived from the brain tumor glioblastoma. Our findings indicate that the Allee effect can be exploited in order to improve the treatment of glioblastoma patients. Cancer growth is increasingly understood as an ecosystem, in which the different cellular components not only grow, but also interact. Such cellular interactions were originally proposed by Laird  and the One such nonlinear growth behavior, with strong empirical support, is the Allee effect. A central idea in ecological population dynamics, the Allee effect denotes a per-capita growth rate that is reduced at low population densities . There iin vitro conditions in the lab at limiting densities . We. WeAIC=2el error . We thusA > μ implying a weak Allee effect, whereas for U3123MG we have μ > A which corresponds to a strong Allee effect. These differences can also been seen in When comparing the optimal parameters for the cell lines we note that for U3013MG and U3289MG we have We have proposed a mathematical model to explain the Allee effect, a phenomenon observed in many experimental datasets of cancer cell population dynamics. Our model, which posits that autocrine secreted growth factors increase the rate of cell division, yields population dynamics that can exhibit a weak or strong Allee effect depending on the relationships between the model parameters. Fitting the model to a dataset of three patient-derived glioma cell lines showed that a parameter setting with an Allee effect provided the best fit.α and EGF [Due to the large heterogeneity between patient-derived cell lines coupled to the experimental difficulties of measuring growth factor production and decay, we chose an approach where we used the IB-model as a means of showing that an Allee effects is possible. This observation was confirmed by our experimental data, but parametrizations of individual experiments remain difficult. Additional experiments to measure, e.g. the rate of growth factor production and its precise impact on cell division would be needed, as these two parameters are not identifiable in the ODE model. The situation is further complicated by the fact that several distinct growth factors have been identified as autocrine signals in glioblastoma, e.g. TGF- and EGF .In recent years many studies have focused on the Allee effect in cancer, either in an effort to understand its origin or to investigate how the effect can be therapeutically exploited . For exaemergence of Allee effects based on a feasible bio-physical mechanism such as secretion and uptake of growth-stimulating molecules. Thus, our integrative framework here complements these results by directly showing that autocrine signalling induced, and density-dependent feedback, can have detrimental effects on the per-capita growth rate of the cell population. We showed that this type of interaction is plausible to generate an Alee effect, integrating an analytical framework with agent based modeling and novel experimental results.Neither of the above mentioned results were directly linked to production and consumption of secreted factors. Böttger et al.  approachβ, EGF) and is beyond the scope of this paper.We provide a mechanistic explanation for a density-dependent proliferation rate in terms of local growth factor concentration. Mathematical analysis of the individual-based model allowed for the derivation of an ODE-model whose coefficients depend on the IB-model parameters. Our ODE-model was fitted to experimental data, and we found that a model which included an Allee effect best explained the empirical observations, in accordance with a previously observed weak Allee effect in breast cancer cell populations . These aAnother way of testing the hypothesis put forth is to investigate the impact of local cell density on the rate of cell division on the cell lines considered in this study. Given microscopy time-lapse data it should possible to estimate the impact of neighbouring cells on the rate of division. An inferred rate of division as an increasing function of the number of neighbouring cells would lend strong support to a localised interaction (e.g. a diffusing GF) as the potential origin of the Allee effect.In light of cancer therapy, a strong Allee effect would be more beneficial for the ability to control a tumor, since the strong effect leads to population extinction at critically low population densities. Such conditions are typically present after therapeutic interventions (e.g. surgery and radiotherapy). If the population dynamics could be tipped towards a strong Allee effect during therapy, similar to an extinction threshold , one couIn conclusion, our findings provide a general model for the population dynamics of cancer cells driven by autocrine signaling. We provide a possible mechanistic explanation for the ubiquitous Allee effect. Further, our findings warrant more research into the therapeutic benefits of altering the effects of autocrine signaling to understand and achieve tumor control.S1 Supplementary MethodsFig A: The confluence plotted against the cell count for a single well across all time points. Fig B: The mean squared displacement as a function of time averaged across all cells in a single well. The dashed line shows the best fit for a line with intercept y = 0. The slope of the line equals 4D, where D is the diffusion coefficient of the cells.(PDF)Click here for additional data file.


CDKN2A variants are associated with an increased risk of pancreatic ductal adenocarcinoma (PDAC). CDKN2A variants of uncertain significance (VUSs) are reported in up to 4.3% of patients with PDAC and result in significant uncertainty for patients and their family members as an unknown fraction are functionally deleterious, and therefore, likely pathogenic. Functional characterization of CDKN2A VUSs is needed to reclassify variants and inform clinical management. Twenty-nine germline CDKN2A VUSs previously reported in patients with PDAC or in ClinVar were evaluated using a validated in vitro cell proliferation assay. Twelve of the 29 CDKN2A VUSs were functionally deleterious (11 VUSs) or potentially functionally deleterious (1 VUS) and were reclassified as likely pathogenic variants. Thus, over 40% of CDKN2A VUSs identified in patients with PDAC are functionally deleterious and likely pathogenic. When incorporating VUSs found to be functionally deleterious, and reclassified as likely pathogenic, the prevalence of pathogenic/likely pathogenic CDKN2A in patients with PDAC reported in the published literature is increased to up to 4.1% of patients, depending on family history. Therefore, CDKN2A VUSs may play a significant, unappreciated role in risk of pancreatic cancer. These findings have significant implications for the counselling and care of patients and their relatives.Pathogenic germline  ATM, BRCA1, BRCA2, CDKN2A, CPA1, CPB1, MLH1, MSH2, MSH6, PALB2, PMS2, PRSS1, and STK11, has the potential to reduce mortality through detection of early, potentially curable, PDAC and its precursor lesions  during a median follow-up 53 months  is a lethal cancer with a median survival of less than 6 months and a 5-year survival rate of only 10% . Surveil lesions . The Int lesions . Similar3 months . Importa3 months . Further3 months . Consequ3 months .CDKN2A gene encodes two proteins, p16INK4a and p14ARF. p16INK4a inhibits CDK4 activity, is a regulator of cell cycle progression, and a tumor suppressor gene (CDKN2A that affect p16INK4a (hereafter referred to CDKN2A variants) can be classified as either pathogenic, benign, or variants of uncertain significance (VUSs) based on American College of Medical Genetics (ACMG) guidelines  p16INK4a, but do not inhibit cell proliferation, indicating that additional functions not assessed in vitro CDK4 binding are important for cellular function  was not detectable in PANC-1 cells by western blot  is a human PDAC cell line with a homozygous deletion of CDKN2A . Consistern blot . Stable ern blot . Convers control .CDKN2A VUSs, we next determined cell proliferation values for an additional six known pathogenic and six known benign variants in our assay. Known pathogenic and benign variants are likely functionally deleterious and functionally neutral, respectively, in our assay and were used as benchmarks for interpretation of CDKN2A VUSs. The mean cell proliferation value for all pathogenic variants assayed was 0.90 (range: 0.84–1.03), while the mean cell proliferation value for all benign variants assayed was 0.26 (range: 0.14–0.48)  . Importa14–0.48) .CDKN2A VUSs. These VUSs were selected because they were either reported in previously published studies in patients with PDAC and/or were reported in ClinVar  using two additional PDAC cell lines with homozygous deletions of CDKN2A: MIA PaCa-2  and AsPC-1   . Westernell line . Importaell line . In MIA ell line . In AsPCell line . Importaell line . When coell line .As reintroduction of CDKN2A into cancer cells lacking CDKN2A delays cell cycle progression, we determined the percent of variant-expressing PANC-1 cells in G1, G2/M, and S phases of the cell cycle . The perCDKN2A VUSs assayed had previously reported functional data available  of the 17 CDKN2A VUSs identified in a study of 638 patients with familial pancreatic cancer  in patients with familial pancreatic cancer, 0.9% (95% CI: 0.5–1.8%) in patients with PDAC positive family history of PDAC , and 0.1% (95% CI: 0.02–0.3%) in PDAC patients unselected for family history. When incorporating functionally deleterious VUSs we have reclassified as likely pathogenic variants with known pathogenic variants in CDKN2A, the cumulative prevalence of pathogenic and likely pathogenic CDKN2A variants in these studies increased from 2.5% to 4.1% (95% CI: 2.8–5.9%) in patients with familial pancreatic cancer, from 1.7% to 2.7% (95% CI: 1.9–3.9%) in patients with PDAC who had a positive for a family history of the disease , and from 0.7% to 1.0% (95% CI: 0.6–1.7%) in PDAC patients unselected for family history.As we assayed all CDKN2A VUSs are identified in up to 4.3% patients with PDAC and are the cause of significant clinical uncertainty. Individuals with a CDKN2A VUS are not currently eligible for surveillance unless they meet other family history criteria. We used a cell proliferation assay to functionally characterize germline CDKN2A VUSs identified in patients with PDAC and/or reported in ClinVar and provide evidence to reclassify variants into clinically actionable strata.Germline CDKN2A variants previously classified as VUS were functionally deleterious in our assay and could be reclassified as likely pathogenic variants . When considering CDKN2A VUS identified in patients with PDAC, our results suggest that the prevalence of CDKN2A VUSs that are functionally deleterious is up to 1.6% in patients with PDAC, depending on family history. It should be noted, however, that we characterized only missense CDKN2A VUS in our assay. Functional characterization of other types of CDKN2A VUS, such as synonymous variants, in-frame indels, and non-coding variants, would refine these estimates.We found that over 40% of CDKN2A VUSs that are functionally deleterious in patients with PDAC reported in previously published literature. Overlap of patient cohorts between these studies may affect estimates of prevalence. Regardless, we can conclude that functionally deleterious CDKN2A VUSs are likely to play a significant and previously unappreciated role in risk of PDAC, particularly for patients with a family history of the disease. Studies to define age-specific penetrance estimates for individuals with a pathogenic germline CDKN2A variant, including functionally deleterious variants previously classified as VUSs, are necessary and will inform genetic counselling, surveillance, and early detection efforts.Furthermore, we determined the prevalence of germline VUS functional characterizations were generally consistent when using PANC-1, MIA PaCA-2, and AsPC-1 cells in our cell proliferation assay. Specifically, no variant found to be functionally deleterious or potentially functionally deleterious when assayed with one cell line, had a functionally neutral or potentially functionally neutral classification when assayed with another cell line. Furthermore, PDAC cell lines had different genetic alterations and degrees of ploidy  indicatiCDKN2A variants classified as pathogenic, functionally deleterious, or potentially functionally deleterious do not control progression through the cell cycle.Consistent with our functional classifications, we found that benchmark pathogenic variants and VUSs classified as functionally deleterious or potentially functionally deleterious had a significantly lower percent of cells in G1 phase and a significantly higher percent of cells in G2/M phase of the cell cycle compared to either benchmark benign variants or VUSs classified as functionally benign or potentially functionally benign. These data suggest that expression of CDKN2A VUSs with previously published data. In general, our assay results were consistent with previous reports. However, assay results for two VUSs, p.Gly67Arg and p.Glu69Gly, were inconsistent with previously reported partial reduction in CDK4 binding. There are several explanations for these observations. First, our assay is of broad cellular function, specifically cell proliferation, and therefore, may encompass functions other than CDK4 binding. Second, it is possible that overexpression of CDKN2A variants with partial loss-of-function may be obscured in our assay by non-physiological levels of expression. Future studies to correlate CDK4 binding with pathogenicity and to develop of functional assays that utilize endogenous promoters and enhancers would provide further clarity.We were also able to compare our assay results for five CDKN2A VUSs identified in patients with PDAC or reported in ClinVar using a validated functional assay. We found that over 40% of CDKN2A VUS assayed were, in fact, functionally deleterious and as a result can be reclassified as likely pathogenic using ACMG guidelines. This finding may have significant implications for the management of patients with PDAC, and their relatives found to have a CDKN2A VUS.In conclusion, we functionally characterized and reclassified 29 PANC-1 , MIA PaCa-2 , and AsPC-1 , and the human embryonic kidney cell line 293T  were purchased from American Type Culture Collection . PANC-1, MIA PaCa-2, and 293T cells were maintained in Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine serum. AsPC-1 cells were maintained in RPMI-1640 supplemented with 10% fetal bovine serum. Cell line authentication and mycoplasma testing of PDAC cell lines was performed using GenePrint 10 System  and a PCR-based MycoDtect kit , respectively, by the Genetics Resource Core Facility of The Johns Hopkins University School of Medicine, Baltimore, MD.INK4A at a 1:1000 dilution . Western blotting data and images presented are representative of at least three independent experiments.Western blots were performed as previously described with the following modifications : (1) antCDKN2A and CDKN2A-L78Hfs*41 cDNAs were subcloned into the pLJM1-Empty from pHAGE-CDKN2A and pHAGE-CDKN2A-L78Hfs*41, respectively, using the Q5 High-Fidelity PCR kit  as previously described  and Sanger sequencing . Restriction enzyme, EcoRI-HF digest was performed with CutSmart Buffer  at 37°C for 15 min. Expression constructs for each assayed CDKN2A variant were produced from the pLJM1-CDKN2A using the Q5 Site-Directed Mutagenesis kit . Primers used to generate each CDKN2A variant expression plasmids are given in CDKN2A VUS was confirmed using Sanger sequencing . The manufacturer’s protocol was followed unless otherwise specified.pHAGE-CDKN2A  and pHAGE-CDKN2A-L78Hfs*41  created by Gordon Mills & Kenneth Scott , and pLJescribed . PrimersCDKN2A cDNA (WT or variant) and the lentiviral packaging vectors, psPAX2  and pCMV-VSV-G , created by Didier Trono and Bob Weinberg, respectively  or selected variants were generated by lentiviral transduction. Briefly, 1 × 105 cells were cultured in media supplemented with 10 µg/ml polybrene and transduced with 10 TUs/ml lentivirus particles. Cells were then centrifuged at 1200× g for 1 hr. After 48 hr of culture at 37°C and 5% CO2, transduced cells were selected by culture in media containing 3 µg/ml puromycin for PANC-1 cells and 1 µg/ml puromycin for MIA PaCa-2 and AsPC-1 cells for 7 days.PANC-1, MIA PaCa-2, and AsPC-1 cells stably expressing WT CDKN2A  and cell numbers were counted using a TC20 Automated Cell Counter  on day 7 for MIAPaCa-2 cells, and day 14 for PANC-1 and AsPC-1 cells. Cell numbers were normalized to empty vector transduced cells to give a relative cell proliferation value. Assays to determine the functional effect of CDKN2A variants were repeated in triplicate. Mean cell proliferation value and standard deviation (s.d.) were calculated.1 × 10CDKN2A VUSs were functionally characterized into four categories: (1) deleterious, (2) potentially deleterious, (3) potentially neutral, and (4) neutral, based on the results of the cell proliferation assay using previously described methodology  and the FxCycle Violet Ready Flow Reagent  according to the manufacturer’s protocols. Flow cytometry was performed on Cytek Aurora Flow Cytometry System  and the data analyzed to determine the percentage of cells in each phase of the cell cycle using the FlowJo software .CDKN2A variants were calculated using the modified Wald Method. A p-value less than 0.05 considered statistically significant.Statistical analyses were performed using JMP v.11  and Prism v.6 . Comparison of means used the Student’s t test. CIs for the prevalence of functionally deleterious  In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Decision letter after peer review:eLife. Your article has been reviewed by 2 reviewers, one of whom is member of our Board of Reviewing Editors and the evaluation has been overseen by Wafik El-Deiry as the Senior Editor. The reviewers have opted to remain anonymous.Thank you for resubmitting your work entitled "Functional CDKN2A assay identifies frequent deleterious alleles misclassified as variants of unknown significance" for further consideration by The manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below:Reviewer #1:The investigators postulated that some variants of uncertain significance (VUS) of CDKN2A have been misclassified, and that some proportion may be in fact be deleterious and possibly pathogenic in carcinogenesis of pancreatic ductal adenocarcinoma (PDAC). in vitro analysis of cell proliferation of 29 known VUSs was performed, and the authors report that >40% of these variants are functionally deleterious.CDKN2A encodes a tumor suppressor as well as an important regulator of progression through the cell cycle. It has been extensively studied in epithelial carcinomas, including pancreatic ductal adenocarcinomas (PDAC). The concept that a significant number of previously reported variants of this gene may not be as benign has important implications for understanding etiology and downstream molecular effects and tumoral progression of this cancer, especially in the albeit relatively small number of patients who harbor germline variants that may be important in driving pancreatic cancer development. The study is well-written and leverages an established and validated in vitro cell proliferation assay from this lab.1. The information redesignating 40% of the VUS as functionally deleterious and possibly pathogenic is applied to external datasets. Did the investigators gain access to the raw data from the authors of the cited published works, or were the reassignments based on available information that was published? It would be important to access and confirm the raw data.2. Application to an internal dataset of tumor samples would affirm the conclusions made from the in vitro validation steps.3. The use of only a single PDAC cell line is a limitation that tempers the conclusions of the study .The in vitro analysis should be performed on at least three cell lines to control for other differences between cell lines. This work would strengthen the argument, as the premise of the study is to extend the finding to in vivo/human PDAC, with implications that the reassigned germline VUSs are more pathogenic in humans than previously thought.Reviewer #2:The study provides evidence of functionality of mutations present in pancreatic cancer, a dismal condition predicted be the second cause of cancer death by 2030. Specifically, the authors showed that mutations in CDKN2A associated with increased risk of developing pancreatic cancer have lost the ability to control cell growth.The authors have functionally characterized CDKN2A mutations present in familial pancreatic cancer cases. The methodology used is for the most adequate to address the main goal of the study. Some of the deficiencies/weaknesses are associated with limitations of the pancreatic cancer model/methodologies and lack of side by side comparison with other known factors associated with increased risk of the disease as well as clinical correlations of these mutations.To fully support the authors conclusions, the authors should1) The Panc1 results should be repeated in two additional lines to avoid any cell line bias effect.2) The cell growth analysis should be confirmed using a cell cycle analysis to define if the mutants lack the ability to control G1 progression.3) The study should include side-by-side comparison with other know p16 mutations from familial cases. Reviewer #1:The investigators postulated that some variants of uncertain significance (VUS) of CDKN2A have been misclassified, and that some proportion may be in fact be deleterious and possibly pathogenic in carcinogenesis of pancreatic ductal adenocarcinoma (PDAC). in vitro analysis of cell proliferation of 29 known VUSs was performed, and the authors report that >40% of these variants are functionally deleterious.CDKN2A encodes a tumor suppressor as well as an important regulator of progression through the cell cycle. It has been extensively studied in epithelial carcinomas, including pancreatic ductal adenocarcinomas (PDAC). The concept that a significant number of previously reported variants of this gene may not be as benign has important implications for understanding etiology and downstream molecular effects and tumoral progression of this cancer, especially in the albeit relatively small number of patients who harbor germline variants that may be important in driving pancreatic cancer development. The study is well-written and leverages an established and validated in vitro cell proliferation assay from this lab.1. The information redesignating 40% of the VUS as functionally deleterious and possibly pathogenic is applied to external datasets. Did the investigators gain access to the raw data from the authors of the cited published works, or were the reassignments based on available information that was published? It would be important to access and confirm the raw data.We are happy to clarify. Several authors of this manuscript were also authors of the cited published works used to identify VUS for assay. These authors were extensively involved in the analysis and interpretation of these variant data. The cited studies included research next-generation sequencing (whole genome and gene-panel), Sanger sequencing, and CLIA approved clinical genetic testing that have high-confidence for single base substitution calls. As such, we are confident in the VUS calls used in this manuscript.2. Application to an internal dataset of tumor samples would affirm the conclusions made from the in vitro validation steps.CDKN2A loss-of-heterozygosity with retention of the deleterious variant (supporting evidence) or somatic loss of the deleterious variant (refuting evidence). However, even without tumor samples, we present additional experimental evidence to support our functional characterizations (see below).We thank the reviewer for their suggestion. We agree that analysis of tumor samples might provide additional evidence to validate functional characterizations. Unfortunately, only ~10% of patients with pancreatic ductal adenocarcinoma undergo resection and have tissue available for correlative studies. We were unable to identify any tumor tissue for patients with functionally deleterious or potentially functionally deleterious VUS where additional studies would be informative, for example, somatic 3. The use of only a single PDAC cell line is a limitation that tempers the conclusions of the study .The in vitro analysis should be performed on at least three cell lines to control for other differences between cell lines. This work would strengthen the argument, as the premise of the study is to extend the finding to in vivo/human PDAC, with implications that the reassigned germline VUSs are more pathogenic in humans than previously thought.CDKN2A variants  in two additional cell lines (MIA PaCa-2 and AsPC-1). Reassuringly, no VUS with a functionally deleterious or potentially functionally deleterious classification in one cell line had a functionally neutral or potentially functionally neutral classification in the other cell lines tested. Furthermore, cell cycle analysis to determine the distribution of cells in each stage of the cell cycle provides support for our functional classifications. These additional data indicate that our functional classifications are robust to cell lines specific effects included ploidy and genetic background.We are happy to provide the additional experimental data requested by the reviewer. We have now assayed selected Reviewer #2:The study provides evidence of functionality of mutations present in pancreatic cancer, a dismal condition predicted be the second cause of cancer death by 2030. Specifically, the authors showed that mutations in CDK2A associated with increased risk of developing pancreatic cancer have lost the ability to control cell growth.The authors have functionally characterized CDK2A mutations present in familial pancreatic cancer cases. The methodology used is for the most adequate to address the main goal of the study. Some of the deficiencies/weaknesses are associated with limitations of the pancreatic cancer model/methodologies and lack of side by side comparison with other known factors associated with increased risk of the disease as well as clinical correlations of these mutations.To fully support the authors conclusions, the authors should1) The Panc1 results should be repeated in two additional lines to avoid any cell line bias effect.CDKN2A variants  in two additional cell lines (MIA PaCa-2 and AsPC-1). Reassuringly, no VUS with a functionally deleterious or potentially functionally deleterious classification in one cell line had a functionally neutral or potentially functionally neutral classification in the other cell lines tested.We are happy to provide the additional experimental data requested by the reviewer. We have now assayed selected 2) The cell growth analysis should be confirmed using a cell cycle analysis to define if the mutants lack the ability to control G1 progression.We thank the reviewer for this suggestion. We have completed cell cycle analysis to determine the distribution of cells in each stage of the cell cycle for each assayed variant in PANC-1 cells. These data provide clear support for our functional classifications and indicate that expression of pathogenic or functionally deleterious variants do not inhibit cell cycle progression. Specifically, pathogenic and functionally deleterious variants had a lower percentage of cells in G1 phase and a higher percentage of cells in G2/M phase compared to benign and functionally neutral variants.3) The study should include side-by-side comparison with other know p16 mutations from familial cases.We are grateful for the opportunity to clarify. The majority of pathogenic germline variants tested in our assay were either identified in patients with familial pancreatic cancer (5 of 9 variants) or in patients with pancreatic adenocarcinoma (2 of 9). Furthermore, these variants were classified as pathogenic using American College of Medical Genetics variant interpretation guidelines. As such, our assay has broad applicability to patients with pancreatic cancer.


Obesity, a physiological situation where different proinflammatory cytokines and hormones are secreted, is a major risk factor for breast cancer. Mitochondrial functionality exhibits a relevant role in the tumorigenic potential of a cancer cell. In the present study, it has been examined the influence of an obesity-related inflammation ELIT treatment , which aims to stimulate the hormonal conditions of a postmenopausal obese woman on the mitochondrial functionality and invasiveness of MCF7 and T47D breast cancer cell lines, which display a different ratio of both estrogen receptor isoforms, ERα and ERβ. The results showed a decrease in mitochondrial functionality, with an increase in oxidative stress and invasiveness and motility, in the MCF7 cell line (high ERα/ERβ ratio) compared to a maintained status in the T47D cell line (low ERα/ERβ ratio) after ELIT treatment. In addition, breast cancer biopsies were analyzed, showing that breast tumors of obese patients present a high positive correlation between IL-6 receptor and ERβ and have an increased expression of cytokines, antioxidant enzymes, and mitochondrial biogenesis and dynamics genes. Altogether, giving special importance to ERβ in the pathology of obese patients with breast cancer is necessary, approaching to personalized medicine. Cancer, a pathology characterized by the excessive proliferation of tumor cells, is the second cause of death in the world, responsible for approximately 9.6 million deaths in 2018. In addition, breast cancer is a disease causing more than half a million deaths annually, projecting an increase in its incidence to a total of 3.2 million new cases per year in 2050 [Obesity is a chronic metabolic disease characterized by excess fat accumulation in the body, and its prevalence has increased markedly in the last two decades in the most developed countries . In obesThe cellular effects of estrogens are mediated by their binding to estrogen receptors (ER) alpha (ERα), beta(ERβ), and GPER. Although ERα and ERβ show homology in the DNA and ligand-binding domains, their activity and affinity for 17β-estradiol are different, with ERα having a higher affinity for it. In addition, the expression pattern of the receptors also varies according to the cell type ,9,10. ERAnother adipokine synthesized and secreted by adipocytes is leptin, whose circulating levels are directly correlated with the individual’s BMI . Leptin It is worth noting that obesity is considered an inducing factor of inflammation, where adipose tissue takes on the role of producer of cytokines and inflammatory proteins. However, the biochemical role between inflammation and cancer-inducing cellular modifications has not yet been elucidated . In thisThe expression of inflammatory cytokines, such as interleukin-6 (IL6) and Tumor necrosis factor alpha (TNFα), have been related to an increase in invasiveness and a poor prognosis in breast cancer . IL6 is Mitochondria is a cellular organelle that is highly influenced in response to estrogens, and it is the main source of reactive oxygen species (ROS), playing an important role in tumor processes, as well as in proliferation and apoptosis ,21,22. TMitochondrial function depends on mitochondria morphology, changes in shape, number, and location, which can translate into important functional modifications. Thus, mitochondrial biogenesis is the combination of both proliferation  and differentiation  processes , while mMitochondrial structure and function can be regulated by the activation of ERα and ERβ receptors by binding of 17β-estradiol ,26. RegaDysfunctional mitochondria play a relevant role in cancer and in the epithelial-to-mesenchymal transition (EMT) program in breast cancer . As a coThe aim of the present work was to study mitochondrial functionality and invasiveness, analyzing mitochondrial biogenesis and dynamics processes, as well as oxidative stress and inflammatory status and motility, in cell lines with different estrogen receptors ratio, exposed to a treatment consisting of 17β-estradiol, leptin, IL-6, and TNFα simulating circulating hormonal conditions in a postmenopausal obese woman ,32,33 LiSpecific reagents 17β-estradiol, leptin, interleukin-6, and TNF-α were purchased from Sigma-Aldrich . Dulbecco’s modified Eagle’s medium without phenol red was purchased from GIBCO , Fetal Bovine Serum, and antibiotics solution (penicillin and streptomycin) from Biological Industries . Routine chemicals were supplied by Sigma-Aldrich , Panreac , and Bio-Rad Laboratories .2. To avoid phenol red estrogenic effect, cells were seeded in 6-well or 96-well plates in phenol red-free DMEM containing 10% FBS and 1% antibiotics 24 h prior to treatment. Cells were treated, at 70–80% confluence, with vehicle (0.1% DMSO) or ELIT treatment  for 24 or 48 h.MCF7 and T47D breast cancer cell lines were purchased from American Type Culture Collection ATCC  and maintained in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% Foetal bovine serum (FBS) and 1% antibiotics (penicillin and streptomycin) at 37 °C with 5% CO4 cells/well for MCF7 and 3.2 × 104 cells/well for T47D cell line) and treated with ELIT for 48 h. Hydrogen peroxide production was determined by Amplex® Red Hydrogen Peroxide/Peroxidase Assay Kit, following the manufacturer’s protocol, as described previously [® Red reagent, following the manufacturer’s protocol, as described previously [Cells were seeded in 96-well plates  and treated with ELIT for 48 h. Cells were stained with 250 nM of Nonyl Acridine Orange (NAO) to measure cardiolipin content as previously described [Cells were seeded in 96-well plates  in 6-well plates and treated with ELIT for 24 h. Total RNA from cultured cells or breast cancer human biopsies (25 mg) was isolated using TRI Reagent , following the manufacturer’s protocol, and then quantified using a BioSpec-nano spectrophotometer  set at 260 nm and 280 nm, getting 260/280 nm ratio. Samples were retrotranscribed to cDNA, and PCR reactions were carried out as previously reported [Cells were seeded . Membranes were blocked in 5% non-fat powdered milk in TBS with 0.05% Tween for 1 h. Antisera against OXPHOS complexes , SOD-1 , SOD-2 , CAT , GRd , 4-HNE , COXIV , PGC1α , and GAPDH  were used as primary antibodies. Protein bands were visualized as described previously by [After 48 h of ELIT treatment, cells were harvested as described previously by Torrens-Mas . Proteinously by .For 4-hydroxy-2-nonenal (4-HNE) adducts analysis, as lipid oxidative damage marker, 20 μg of total protein from cell lysate, processed as previously described by Pons et al. .6 cells/well for T47D cell line and 8.5 × 105 cells/well for MCF7 cell line. Wound healing assay was performed as previously described by Torrens-Mas et al. [Cells were seeded in six-well plates at a density of 1 × 10s et al. . The are5 cells/well for MCF7 and 5 × 105 cells/well for T47D. After 24 h, cells were treated with ELIT treatment for 24 h. Then, cells were incubated with MitoTracker™ Green 0.5 µM  for 1 h and LysoTracker™ Red 0.5 µM  for 20 min, both at 37 °C in the dark. For DNA staining, cells were incubated with 1/200 dilution of 1 μg/mL Hoechst 33342  for 5 min at 37 °C in the dark.Cells were seeded on a glass coverslip inside 6-well plates at a density of 2 × 10The fluorescence was monitored with a Leica TCS-SPE Confocal Microscope, using 63× immersion oil (147 N.A.) objective lens. Fluorescence excitation/emission was 490/516 nm for MitoTracker Green, 577/590 for LysoTracker Red, and 350/455 nm for Hoechst 33342.Mitochondrial Roundness was analyzed in ImageJ software with Mito-Morphology Macro designed by Ruben K. Dagda at the University of Pittsburgh (2010). This macro is currently maintained and supported by grants NIH/NINDS R01NS105783-01 grant and by NIH/NIGMS R25 1R25-OD023795-01.3 cells/well for MCF7 and 9.600 cells/well for T47D into XFe96 well cell culture plates and incubated overnight to allow attachment at 37 °C in 5% CO2. After 24 h, cells were incubated with vehicle or ELIT treatment. After 48 h of incubation, cells were maintained in 200 μL/well of XF assay media at 37 °C, in a non-CO2 incubator for 1 h. During the incubation time, mitochondrial complex inhibitors  were preloaded for OCR measurements, in XF assay media into the injection ports in the XFe96 sensor cartridge.Real-time oxygen consumption rates (OCRs) were determined for MCF7 and T47D cells using the Seahorse Extracellular Flux (XFe96) analyzer . Cells were seeded at a density of 4.8 × 102).Human breast cancer biopsies were obtained from 33 women, ages between 45–90 years. Samples of these patients were obtained from the Biological Specimen Bank of Son Llàtzer Hospital and as specified by and with the necessary permission granted from the Balearic Island Bioethics Committee. Tumor samples were collected immediately after tumor removal and were frozen in isopentane for analysis as described by Sastre-Serra et al. . Writtent-test with statistical significance was set at p < 0.05 (*). The statistical differences in human samples were analyzed using Pearson’s correlation with statistical significance was set at p < 0.01 (**) and p < 0.05 (*).The statistical analyses were performed with the Statistical Programme for the Social Sciences software for Windows . Data are presented as mean ± standard error of the mean (SEM). The statistical differences in cell lines between vehicle- and ELIT-treated cells were analyzed using a Student’s IL6, IL6R, CXCL8, PTGS2, TNF, and STAT3) showed a statistically significant increase in both MCF7 and T47D cell lines after 24 h of ELIT (17β-estradiol (10 nM), leptin (100 ng/mL), interleukin-6 (50 ng/mL), and TNFα (10 ng/mL)) treatment. In contrast, PPARG anti-inflammatory gene had decreased expression in the MCF7 cell line, and TGFB anti-inflammatory gene showed a statistically significant increase in the T47D cell line.To confirm the obesity-related inflammation treatment effectivity, mRNA expression of main inflammatory genes was determined. As shown in 2O2 production increased in both cell lines (+100% in MCF7 and +34% in T47D cells). However, cardiolipin content, as an indicator of mitochondrial inner membrane quantity, decreased in MCF7 treated cells. Moreover, as shown in As shown in SOD2  showed a high increase in both cell lines; in addition, a decrease in SOD1 (copper/zinc superoxide dismutase) was observed. However, ELIT-treated MCF7 cells showed a general decrease in catalase (CAT) and glutathione reductase (GSR). Nevertheless, in the T47D cell line, ELIT treatment increased GSR and nuclear factor erythroid 2-related factor 2 (NFE2L2) expression, as shown in The mRNA expression of antioxidant enzymes was analyzed  in both Main antioxidant protein expression levels were determined  after 48ESRRA) and Twinkle (TWNK) were found in ELIT-treated cells versus non-treated cells. Moreover, uncoupling proteins 2 and 5  mRNA expression was analyzed, and a decrease in UCP2 expression in both cell lines was accompanied by a decrease in uncoupling protein 5 expression in the MCF7 cell line.Mitochondrial biogenesis genes were also checked, as shown in Mitochondrial biogenesis master regulator PPARGC1A protein levels increased after ELIT treatment in the MCF7 cell line. However, to check the effect of ELIT treatment on the mitochondrial respiratory chain (OXPHOS), protein levels of these OXPHOS complexes were analyzed. As seen in To further investigate mitochondrial function, the oxygen consumption rate (OCR) was determined. As shown in MFN1, MFN2, OMA1, OPA1 showed decreased levels in the MCF7 cell line, whereas, in the T47D cell line, ELIT treatment increased expression of MFN1, MFN2, and OMA1. Fission-related mitochondrial genes presented a different pattern expression between cell lines, with a statistically significant increase in FIS1 mRNA expression in the T47D cell line after ELIT treatment.As shown in On the one hand, mitochondrial networking was modified after 24 h-ELIT treatment in both MCF7 and T47D cell lines. However, as shown in CDH1) expression was decreased in MCF7 cells after 24 h ELIT treatment, but Matrix Metalloproteinase 9 (MMP9) expression increased three times with respect to vehicle-treated cells. In contrast, CDH1 expression increased in the T47D cell line after treatment. In addition to these results, a wound-healing assay was performed. As shown in As shown in ESR1) mRNA expression was decreased in both cell lines after 24 h-ELIT treatment. However, estrogen receptor beta (ESR2) and GPER (GPER1) mRNA expression only shown a decrease in the MCF7 cell line, maintaining its expression in the T47D cell line.To observe the effects of obesity-related inflammation treatment over estrogen receptors alpha (ERα), beta (ERβ), and GPER in MCF7 and T47D breast cancer cell lines, mRNA expression was analyzed. As shown in CXCR8, CXCL8, TNF, SLC25A14, NRF1, NFE2L2, PPARGC1A, and FIS1 were significantly and positively correlated with IL6R expression in the nw group. CXCR8, TNF, SLC25A14, NRF1, NFE2L2, and PPARGC1A were significantly and positively correlated with IL6R expression in the ow group. CXCR8, CXCL8, TNF, PTGS2, ESR2, GPX1, SOD1, SLC25A14, NRF1, NFE2L2, PPARGC1A, SIRT1, FIS1, and OMA1 were significantly and positively correlated with IL6R expression in the ow group.ESR1 and ESR2 gene expression correlations are shown in IL6, CXCL8, SOD1, and SSBP1 were significantly and negatively correlated with ESR1 expression; instead, SIRT3 was significantly and positively correlated. On the other hand, IL6R, CXCR8, GPX1, SLC25A14, NRF1, PPARGC1A, SIRT1, and OMA1 were significantly and positively correlated with ESR2 expression.Moreover, In this study, the effects of obesity related-inflammation on mitochondrial functionality in breast cancer cell lines and breast tumors, focusing on estrogen receptors ratio, were analyzed. Moreover, invasiveness in this situation was also analyzed. We demonstrated that ERβ, in an inflammatory and obesity condition, maintains mitochondrial functionality and avoids invasiveness in breast cancer cell lines. Moreover, we found a strong correlation between interleukin-6 receptor gene expression and inflammation, mitochondrial functionality, and oxidative stress markers, as well as with estrogen receptor beta, in breast cancer human samples in different BMI situations. Obesity stimulates the adipose tissues to release inflammatory mediators such as tumor necrosis factor α and interleukin 6, predisposing them to a proinflammatory state and oxidative stress ,39. ThesPrevious studies in our group and other research groups have shown the independent effects of 17β-estradiol or leptin on oxidative stress and mitochondrial biogenesis and dynamics ,42,43,442O2 and superoxide anion, as similarly described by some authors [In this study, MCF7 and T47D cell lines have been treated with an ELIT inflammatory cocktail with the aim of generates an inflammation situation (IL6 and TNFα) in the presence of Leptin and 17β-estradiol levels, simulating the physiological condition of postmenopausal obese women. In this way, an increase in reactive oxygen species has been observed in both cell lines; however, in the T47D cell line, a lower increase in the production of hydrogen peroxide and levels of superoxide anion was observed. These data make more sense when studying the oxidative damage present in both cell lines, where a significant increase was only observed in the MCF7 cell line. On the other hand, it seems that the T47D treated cell line does not present differences compared to the control group, despite presenting higher levels of H authors ,45,46.NFE2L2, a transcription factor that controls mainly antioxidant enzymes expression, and glutathione reductase, which recycles glutathione, was also increased, avoiding a high increase in free radical levels in low ERα/ERβ ratio T47D cell line. In addition, it should be noted that those tumors with a high correlation between IL6R and ESR2 gene expression presented an increase in antioxidant enzymes, thus could palliate levels of free radicals, which can ultimately diminish oxidative damage.Oxidative stress is generated in breast cancer, and in many other pathologies, in two main ways. The first one, as observed in the high ERα/ERβ ratio MCF7 cell line after ELIt treatment, is a decrease in the expression of the antioxidant enzymes. It was observed that all antioxidant enzymes had decreased their gene or protein expression in the MCF7 cell line, except the SOD2 enzyme that had increased expression in both MCF7 and T47D cell lines. It has been described that SOD2 plays a role as a free radical detector, increasing gene and/or protein expression in order to alleviate oxidative damage [The other pathway that increases oxidative stress is the poor maintenance of a functional mitochondrial pool . To achiESRRA) and Twinkle (TWNK). ESRRA belongs to a superfamily of nuclear receptors independent of estrogen activation. Its expression is induced and activated by PGC1α, and the two factors together are capable of binding to response elements and promoting the initiation and elongation of the transcription of metabolic and mitochondrial target genes [However, the T47D cell line, with high levels of ERβ, had mitochondrial dynamics elevated, maintaining a more functional pool of mitochondria. In the case of mitochondrial biogenesis, it should be noted that there are two genes that presented a very significant elevation, estrogen-related receptor alpha (et genes . Twinkleet genes . In factet genes . Taking into account that patients with tumors with low ERα/ERβ ratios have a worse response to chemical agents oxidative damage inductors , we obseIn addition to mitochondrial biogenesis and dynamics, our study reveals an oxygen consumption rate decreased in the MCF7 cell line that supports all the results commented above. It is worth noting that ELIT treatment decreases basal respiration, maximal respiratory capacity, ATP-linked respiration as much as proton leak in the MCF7 cell line. Proton leak decrease is in concordance with low uncoupling proteins mRNA expression levels found in the MCF7 cell line after ELIT treatment. UCPs, which promote proton leak across the inner mitochondrial membrane, have emerged as essential regulators of mitochondrial membrane potential, respiratory activity, and ROS generation . As seenOxidative stress, inflammation, and poor mitochondrial network observed in MCF7 cell lines after ELIT treatment leads to a worse situation, and some authors have described a relationship between this situation and metastasis . Our resAs mentioned above, the MCF7 cell line has a higher ERα/ERβ ratio, and the T47D cell line has a lower ratio. ELIT-treatment decreases estrogen receptor alpha mRNA expression in both MCF7 and T47D cell lines, as shown in results. However, estrogen receptor beta mRNA expression only decreases in the MCF7 cell line but not in the T47D cell line. This fact supports that all the results showed in our study could be through estrogen receptor beta T47D cell lines maintenance, giving to this receptor subtype the protective role that previously some studies have been described ,39. The presence of estrogen receptor beta allows maintaining a more functional mitochondrial pool, with active mitochondrial biogenesis and dynamics, which means less production of reactive oxygen species and better mitochondrial metabolism in an obesity-related inflammation condition. In addition, antioxidant enzymes are active, preventing oxidative damage and, at least in part, invasiveness.This study could be important to remark the importance of estrogen receptor beta and mitochondria as an important organelle in the development and prognosis of breast cancer in obese patients. Likewise, more studies are necessary in order to clarify the estrogen receptor beta mechanism in breast cancer and establish it as a clinical biomarker, as is the estrogen receptor alpha.


Pediatric high-grade glioma (pHGG) is a major contributor to cancer-related death in children. In vitro and in vivo disease models reflecting the intimate connection between developmental context and pathogenesis of pHGG are essential to advance understanding and identify therapeutic vulnerabilities. Here we report establishment of 21 patient-derived pHGG orthotopic xenograft (PDOX) models and eight matched cell lines from diverse groups of pHGG. These models recapitulate histopathology, DNA methylation signatures, mutations and gene expression patterns of the patient tumors from which they were derived, and include rare subgroups not well-represented by existing models. We deploy 16 new and existing cell lines for high-throughput screening (HTS). In vitro HTS results predict variable in vivo response to PI3K/mTOR and MEK pathway inhibitors. These unique new models and an online interactive data portal for exploration of associated detailed molecular characterization and HTS chemical sensitivity data provide a rich resource for pediatric brain tumor research. Patient-derived xenografts provide a resource for basic and translational cancer research. Here, the authors generate multiple pediatric high-grade glioma xenografts, use omics technologies to show that they are representative of primary tumours and use them to assess therapeutic response. Pediatric diffuse high-grade gliomas (pHGG) comprise approximately 20% of all childhood brain tumors. This heterogeneous group of tumors carries a devastating prognosis, with 70–90% of patients dying within 2 years of their diagnosis1. Genome-wide analyses have transformed our understanding of pHGGs to illuminate distinct molecular features compared to adult HGG, including a close association between tumor location, patient age, and recurrent mutations that indicates an intimate connection between pHGG pathogenesis and developmental context3. For example, histone H3K27M mutations, which are rare in other tumor types, occur in approximately 80% of diffuse intrinsic pontine gliomas (DIPG) and other diffuse HGGs in midline structures such as the thalamus7. This striking association has redefined the diagnosis of these tumors, with the 2016 World Health Organization Classification of Tumors of the Central Nervous System (CNS) now incorporating molecular-based criteria to define diffuse midline glioma—H3K27M mutant (DMG-K27M) as a distinct diagnostic entity8. H3K27M mutations most frequently occur in 2 of the 15 genes that encode histone H3, with H3F3A encoding H3.3 K27M and HIST1H3B encoding H3.1 K27M in approximately 75% and 25% of H3 mutant DIPG, respectively2. Activating mutations in the gene encoding the BMP receptor ACVR1 are found almost exclusively in DIPG and preferentially co-occur with H3.1 K27M mutations, generally in younger patients, demonstrating an even more restricted association with developmental context12. In contrast, histone H3.3 G34R/V mutations are found in approximately 15% of cerebral cortical HGG, with patient age ranging from older adolescents through young adulthood7.Brain tumors are the predominant cause of cancer-related morbidity and mortality in childrenTP53 or CDKN2A, mutations in epigenetic regulators such as ATRX, and others12. Different subclasses of pHGG are readily detected through comparisons of genome-wide DNA methylation profiles, which may reflect both the developmental origins of the tumors and the consequences of tumorigenic mutations13. This epigenetic characterization allows a refined molecular classification of CNS tumors and is increasingly being incorporated into clinical practice.Variable combinations of additional mutations also contribute to intertumoral heterogeneity, including mutations activating the receptor tyrosine kinase–RAS–PI3-kinase pathway, alterations inactivating tumor suppressors 14. In vitro and in vivo models that recapitulate the complexity and heterogeneity of pHGG are essential to advance our understanding and identify therapeutic vulnerabilities of these deadly childhood brain tumors.Despite rapid advances in the characterization of the genomic and epigenetic landscape of pHGG, effective therapeutic approaches are still lacking for almost all pHGG patientsHere, we report the establishment of a unique collection of 21 patient-derived orthotopic xenograft (PDOX) models and 8 new pHGG cell lines recapitulating molecular signatures of the primary tumors from which they were derived and representing a broad spectrum of the heterogeneity found in pHGG. We use a total of 14 pHGG cell lines and two control cell lines for high-throughput screening (HTS) to identify drug sensitivity and validate the in vitro heterogeneity of response for two drugs in vivo. Detailed molecular characterization of these novel models and the results from HTS chemical sensitivity studies on the large cell line panel are available through an interactive online data portal providing a rich resource to the pediatric brain tumor research community.We generated a unique resource of 21 pHGG PDOX by implanting dissociated tumor cells from surgical or autopsy samples into the brains of immunodeficient mice. Patient age at diagnosis ranged from 4 to 19 years, with a median age of 12 years and a median survival of 12 months (Supplementary Data t-distributed stochastic neighbor embedding (t-SNE) analysis of methylation profiles from these samples and a reference set including samples from diverse brain tumor subgroups13, all PDOX models and cell lines clearly grouped with glioblastoma or glioma, distinct from embryonal or ependymal tumors. , 10 glioblastoma, IDH wild type, including three H3.3 G34 mutant (GBM G34), four subclass midline (GBM Mid), one subclass RTK II (pedRTKII), and two subclass RTKIII (pedRTKIII). Three tumors did not directly match the reference clusters, but were closest to GBM Mid, pedRTKII, or PXA  or whole-exome sequencing (WES) on all PDOX, matched patient tumors and derived cell lines. Somatic mutations and potentially pathogenic germline mutations were identified for tumors with matched germline samples for 16/21 lines, and potentially pathogenic non-silent mutations were annotated for tumors without available matched germline  showed upregulation of genes associated with cell cycle progression (adj. p < 2.2e−16) and downregulation of genes associated with inflammatory response (adj. p < 2.2e−16) in PDOX (Supplementary Data p < 2.2e−16). Cell lines, which represent extensive passaging in neural stem cell growth media, also showed strong fidelity with the matched PDOX models from which they were derived   that supports interactive exploration of all molecular data. Within this rich open-access portal, detailed information can be viewed or downloaded for each individual model, summarizing clinical, molecular, and histopathological features  , was the most active drug (highest median AUC) in this subset and was more selective for pHGG models compared to iAstro and HABS. The CDK9 inhibitor CDK9-IN-2 (ref. 23) had lower AUC values compared to THZ1, but also showed selectivity for most pHGG models relative to control cell lines. CDK7 and CDK9 are key regulators of transcription initiation and elongation, respectively, supporting the concept of targeting transcriptional dependencies in tumor cells24. In contrast, the pan-BET inhibitor JQ1 (ref. 26), which also impacts transcription regulation, was much weaker than the CDK7 and CDK9 inhibitors, and was equally or more cytotoxic to control cell lines  as predicted by a previous study27. Consistent with previous reports that evaluated broad-spectrum HDAC inhibitors29, panobinostat showed strong efficacy in vitro. However, CUDC-907, a dual-acting inhibitor of class I PI3K and HDAC30, had higher median AUC and was slightly more selective for pHGG models. The proteasome inhibitor marizomib is being evaluated in a phase I combination study with panobinostat in DIPG (NCT04341311)15. This drug had the largest interquartile range of AUC values in the subset and induced significant cytotoxicity in iAstro cells   and MEK (trametinib) were selective for the same three DIPG pHGG models over other cell lines Fig. . However32. We also tested two other alkylating agents, streptozocin and nimustine33, and both were ineffective in our pHGG models (Supplementary Data The WEE1 inhibitor MK-1775 (adavosertib), which is being evaluated clinically with radiotherapy in pHGG (NCT01922076), showed low efficacy in our panel. Likewise, the alkylating agent temozolomide (TMZ), a standard of care in adult gliomas, was ineffective in our tumor models, consistent with the lack of clinical response to TMZ in pHGGFinally, to better explore patterns of drug sensitivity across the cell lines in our panel, we performed unsupervised clustering of cell lines (columns) and compounds (rows) with all 93 compounds  and mirdametinib (PD0325901), which target PI3K/mTOR and MEK, respectively, and have superior blood–brain barrier penetration and exposure37, to validate the effects of pathway inhibition for in vitro/in vivo comparisons.We sought to determine if sensitivity differences between tumor cell lines detected by HTS translated into in vivo effects in orthotopic brain tumors. For these studies, we chose PI3K/mTOR and MEK pathway inhibitors because responses in different pHGG lines varied and target engagement can be reliably detected in tumor tissue. HTS results showed that the PI3K/mTOR inhibitor omipalisib was active in most pHGG models but varied in potency. In contrast, the MEK inhibitor trametinib showed weak activity in many tumor cells Fig. . While t39. We conducted in vitro quantitative synergy assays in seven cell lines and analyzed results using the Bivariate Response to Additive Interacting Doses (BRAID) response surface model40. BRAID κ denotes the type of interaction , whereas BRAID IAE50 computes the degree to which a combination achieves a minimal efficacy within a defined concentration range . Higher IAE50 means that the combination is more efficacious. The combination of paxalisib and mirdametinib exerted synergistic growth inhibition (κ > 0) in three pHGG cell lines  and iAstro controls, but not in SJ-DIPGX7c, SJ-HGGX42c, SJ-HGGX6c, or HA-bs controls , synergy made a major contribution in the case of SJ-DIPGX37c and SJ-DIPGX29c, as indicated by the curvature of the 50% (black) and 90% (white) cell viability isoboles. In contrast, the IAE50 value for SJ-DIPGX7c was driven solely by paxalisib: the 50% and 90% isoboles run parallel to the y-axis because mirdametinib exerts little cytotoxicity on its own and fails to potentiate the activity of paxalisib. While the synergy is highest in iAstro (κ = 8.8), as evidenced by the clear shift in the 50% isobole with increasing mirdametinib concentrations, both drugs are weakly cytotoxic on their own and their interaction is insufficient to induce high combined efficacy (IAE50 = 1.0).Numerous studies have shown extensive cross-talk between these pathways and promise for enhanced efficacy of combined inhibition approachesTP53-related pathways , whereas mirdametinib induced a stronger response (EC50 = 1 μM) in DIPGX37c, which has PIK3R1 and PPM1D mutations and did little in SJ-DIPGX7c, which has PIK3CA and TP53 mutations . We examined the plasma and brain pharmacokinetics of mirdametinib and paxalisib in normal mice to assess the possibility that the enhanced combinatorial effects were due to drug–drug interaction. While both agents had slightly increased plasma AUCs in combination , mRNA expression profiles, and DNA methylome signatures of the primary tumors from which they were derived.pHGG remains largely incurable despite decades of clinical trials. Worldwide efforts in studying the molecular basis of this group of tumors has revolutionized understanding and revealed subgroups based on spatiotemporal tumor occurrence and striking molecular heterogeneity that has been further subdivided by DNA methylation signatures and inter- and intra-tumoral heterogeneity of mutated genes. Relevant in vitro and in vivo disease models that are founded in the correct developmental origins, recapitulate genetic and epigenetic signatures and represent the significant heterogeneity of pHGG are essential to further our understanding of mechanisms driving tumorigenesis and to identify therapeutic vulnerabilities. Although a growing number of DIPG cell lines have been established and characterized50. Indeed, there were a few differences between patient tumor, PDOX, and cell line, such as NTRK1 mutation detected in the autopsy sample of SJ-DIPGX37, but not the associated PDOX or cell line, or MYCN amplification present in SJ-DMGX40 PDOX, but not in the matched patient tumor  analyses showed no substantial drug–drug interaction changing drug exposures, so the enhanced effects are likely to represent the result of combined pathway inhibition. However, levels of mirdametinib used to effectively block signaling in our study were significantly higher than those observed in humans following exposure at the current clinical dosing of 4 mg twice daily54. Given the compelling survival advantage and observed in vivo toxicity, there is a rationale to consider local delivery of PI3K/mTOR and MEK inhibitors to these tumors to avoid systemic toxicities and reach the necessary levels of drug activity.Understanding how disease heterogeneity contributes to therapeutic response is the foundation of precision medicine. The panel of 14 pHGG cell lines and two astrocyte controls revealed substantial variation in efficacy and potency across the collection of compounds representing multiple MOA. We further investigated inhibitors of PI3K/mTOR and MEK pathways in two PDOX models with differing responses as test cases to determine how well results of in vitro screening were predictive of in vivo response. Myriad mutations in pHGG and other cancers converge on these two signaling pathways, and there are multiple examples of pathway cross-talk that compromise the efficacy of single-agent approaches that inhibit only one of these two regulatory cascadesIt is promising that the majority of compounds screened in our study showed substantially greater efficacy across all of the tumor models tested when compared to temozolomide, which is still frequently used in treating pHGG. Further studies are needed to understand the intrinsic differences in sensitivity between tumors to ultimately achieve the promise of personalized medicine. While we did not observe a simple predictive relationship between DNA methylation subgroup and compounds inhibiting a particular MOA, our results showed efficacy of inhibitors of transcription and translation across all pHGG subgroups Fig. . ImportaPatient material: Genomic analyses of patient material and use of patient tumor samples to establish xenografts and cell lines were performed with informed consent and approval from the Institutional Review Board of St. Jude Children’s Research Hospital. Written informed consent was obtained from patients and/or legal guardians for use of tissue for research. This study complies with the Declaration of Helsinki and all other relevant ethical regulations.All reagants used for this study are listed in Supplementary Table N-acetyl cysteine and 0.012 mg of DNase through a 15–30 min digestion at 37 °C. The cells were washed in Neurobasal™ media, counted, and resuspended in Matrigel . Intracranial implantation of 2 × 105–1 × 106 cells in matrigel into CD-1 nude mice was completed as described55. In brief, intracranial injections for tumor implantations were performed by designated surgeons, under general anesthesia and with analgesics for 1 week. The head of the anesthetized mouse  was held by ear bars on a stereotaxic equipment . A standard 2 × 2 mm bore hole was created with a dental drill and the dura was cut completely from the surface of the exposed brain. Cells in Matrigel were injected with a sterile glass Hamilton syringe bearing a 26G unbeveled needle 2.5 mm below the cortex surface. The wound was sealed with two Relex clips . Mice were monitored until awake. The drinking water contained 115 μg/ml ibuprofen and Baytril (3.5 ml of 2.27% stock/500 ml water) for a week. Mice were observed and monitored daily for neurological and health symptoms and euthanized at a humane endpoint. PDOX tumors were dissected from moribund mice, dissociated, and passaged into 5–10 recipient mice, or cryopreserved in either Millipore or Sigma cell freezing medium  and ThermoFisher Knock-Out DMEM/F12  supplemented with 20 ng/ml of human recombinant EGF, 20 ng/ml of human recombinant bFGF, 10 ng/ml of human recombinant PDGF-AA and -BB, 1% of Glutamax, 1% of sodium pyruvate, 1% of NEAA, 10 mM of HEPES, 2 μg/ml of heparin and 1× Primocin. In the first passage, the Miltenyi Biotec Mouse Cell Depletion Kit was used, and removal of residual mouse cells was verified by demonstrating successful PCR amplification with humans, but not mouse-specific, primer sets for 56 at 37 °C, 5% CO2, and 5% of O2. Doubling times were computed using http://www.doubling-time.com/compute.php.The cell lines were either maintained in suspension culture as tumorspheres or on human ESC-qualified Geltrex artificial extracellular matrix-coated tissue culture surface20 were generous gifts from Dr. Michelle Monje. Normal cell type references were human neural stem cells induced from H9 ES cells , human iPSC-derived astrocytes (Tempo Bioscience), and human brainstem astrocytes .SU-DIPG-IV, SU-DIPG-VI, SU-DIPG-XIII, SU-DIPG-XVII, SUDIPG-XIX, and SU-DIPG-XXIMolecular fingerprinting for PDOXs and cell lines was performed with Promega PowerPlex® 16 HS or PowerPlex Fusion® System .12 were assessed for quality control and pre-processed using the minfi package in R57. Low-quality samples were excluded from the downstream analysis based on mean probe detection with p value > 0.01. Relevant tumor subgroups were selected from the reference cohort. Subgroups with more than 30 cases were randomly downsampled to 30 cases. Methylation probes were filtered based on the following criteria: detection p > 0.01 in >50% of the cohort, non-specificity based on a published list from ref. 58, and probes residing on sex chromosomes. The data then underwent single-sample Noob normalization to derive beta values, with the top 35,060 most variable probes (probe s.d. > 0.25) selected for downstream analysis. Distances between samples were calculated based on Pearson’s distance and then visualized with the t-SNE algorithm (Rtsne package v.0.11).DNA methylation profiles were evaluated using Illumina Infinium Methylation EPIC BeadChip arrays according to the manufacturer’s instructions. Raw IDAT files from pHGG patient tumors, PDOXs, and cell lines as well as a published reference cohort from ref. n = 34). CNAs were then detected as significant positive or negative deviations, which encompassed more than 50% of the chromosomal arm, from the genomic baseline.Copy-number alteration (CNA) analysis was done using the conumee package (v 1.18.0) with default parameters. Probe intensities were normalized against a reference set of normal brain tissues profiled by Methylation EPIC array  and blinded to the origin and genetic alterations of the PDOXs.59. In brief, tissues were fixed in 4% paraformaldehyde at pH 7.4, embedded in paraffin, and cut into 5 μm sections. For DAB staining, antigen retrieval was performed by boiling in 0.01 M citrate buffer (pH 6.0) for 10 min. Endogenous hydrogen peroxidase activity was blocked by 0.6% hydrogen peroxide in TBS (pH 7.6) for 30 min, and IHC followed instructions from the VECTASTAIN Elite ABC kit. Antibodies and dilution factors are listed below and in Supplementary Table PDGFRA (4q12) and MYCN (2p24) was detected by interphase fluorescence in situ hybridization in a Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory in St. Jude Children’s Research Hospital with probes developed in-house using the following BAC clones: PDGFRA (RP11-231C18 + RP11-601I15) with 4p12 control (CTD-2057N12 + CTD-2588A19) and MYCN (RP11-355H10 + RP11-348M12) with 2q35 control (RP11-296A19 + RP11-384O8).Immunohistochemistry (IHC) was performed as previously describedPrimary antibodies used were Akt rabbit pAb, dilution ratio 1:1000 for Western ; Phospho-Akt (Ser473) rabbit pAb, dilution ratio 1:1000 for Western, 1:50 for IHC ; p44/42 MAPK (Erk1/2) rabbit pAb, dilution ratio 1:1000 for Western ; Phospho-p44/42 MAPK (Erk1/2) (Thr202/Tyr204) rabbit pAb, dilution ratio 1:1000 for IHC and Western ; Phospho-Histone H3 (Ser10) rabbit pAb, dilution ratio 1:200 for IHC ; Cleaved Caspase-3 Antibody rabbit mAb, dilution ratio 1:500 for IHC ; and Anti-ATRX rabbit pAb, dilution ratio 1:600 for IHC . The secondary antibodies were anti-rabbit biotinylated secondary antibody, dilution ratio 1:200 for IHC ; Rabbit IgG HRP linked whole Ab, dilution ratio 1:10,000 for Western (MilliporeSigma GENA934-100UL); and Mouse IgG HRP-linked whole Ab Cytiva, NXA931, dilution ratio 1:10,000 for Western (MilliporeSigma GENXA931-1ML).62. For PDOX samples, mapped reads were cleansed of mouse read contamination by XenoCP63. For patient tumors and PDOX samples with matched germline samples, somatic mutations including SNVs and Indels were called and classified62. Briefly, the putative somatic calls were called with Bambino in the paired tumor/normal mode and normal only modes, then further filtered to ensure the high sequence level supports including (1) strong enrichment in tumor sample compared with normal samples, using Fisher exact test; (2) supporting reads in tumors in both orientations of mated pairs (≥3 unique reads); (3) low read allele frequency in normal samples (≤0.05). Additional filters are included to remove the somatic mutations due to the paralogous mapping, sequence misalignment, or sequencing artifacts due to homopolymers, or low-quality base pairs. Non-silent mutations including missense, nonsense, in-frame insertion, in-frame deletion, frameshift, and splice mutations were reported. Potentially pathogenic germline variants were reported based on these filters: (1) non-synonymous mutations with variant allele frequency (VAF) > 0.2 and coverage > 10×; (2) minor allele frequency (MAF) in general populations <1e−3 in ExAC;64 and (3) REVEL score > 0.5 (ref. 65), if available, for missense mutations. For patient tumors and PDOX samples without matched germline samples, variants were called and annotated by Bambino and Medal Ceremony67; variants meeting these criteria were reported as potentially pathogenic variants: (1) any “Gold” variants annotated by Medal Ceremony with alternative allele count > 4; (2) non-Gold but non-silent variants with VAF > 0.3, alternative allele count > 4, and MAF in general populations < 1e−3 in ExAC64, 1000 Genomes, and NHLBI. Mutations in pHGG signature gene list  and four PDOX samples from earlier passages . Differential expression analyses were carried out on 16 one-to-one matched pairs of PDOXs from the most recent passages and the patient samples from which they were derived using edgeR (v 3.28.0) and limma (v 3.42.0) following the RNAseq123 workflow71. Subsequent gene set enrichment analyses were conducted using a hypergeometric test against hallmark gene sets downloaded from MSigDB v 5.2 (ref. 72). Fusion genes were detected using CICERO73.Paired-end RNA sequencing (RNA-seq) was conducted on Illumina HiSeq platform with 100-bp read length or 125-bp read length. Paired-end reads from RNA-seq were mapped by BWA and STAR to multiple reference files such that the best alignments are selected to be included in the bam fileGrowth curves for each cell line were established in 384-well plates (Corning 3707 or 3765) coated with 40 µl of 1% Geltrex matrix with varying cell numbers to determine optimal seeding density for 7-day treatments (Supplementary Table 2 and humidified)  that was integrated into an automated HTS system . All compounds were transferred with a pin tool  and tested in triplicate, and drug exposure time was 7 days except for the fast-growing iAstro cells (shortened to 3 days). Media and drug was not changed during the 7-day incubation to avoid logistical difficulties including cell loss with media change. At the end of the experiment, the assay plates were equilibrated to room temperature for 20 min. Cell viability was measured using CellTiter-Glo® . Luminescent signal was read with an EnVision® multimode plate reader . Screening experiments were processed, and the results visualized using two in-house developed programs: RISE (Robust Investigation of Screening Experiments) and AssayExplorer.The assay plates were loaded into an automated cell culture compatible LiCONiC incubator  values for each compound at each concentration were log2 transformed, normalized to obtain % activity using the following equation: 100 × [(mean(negctrl) – compound)/(mean (negctrl) – mean (posctrl))], and then pooled from replicate experiments prior to fitting. Here, negctrl and posctrl refer to the negative (DMSO) and positive controls (staurosporine) on each plate.drc74 package in R . Both a three-parameter  and a four-parameter model  were fit using the sigmoidal function LL2.4. The hill slope was constrained to be between −10 and 0, and EC50 was constrained to be between 10−11 and 10−4 (which roughly equated to the drug concentration range tested in these experiments). For the three-parameter model, yFin, the maximum response of the dose–response curve, was constrained to be between zero and the maximum of the median activities calculated at each concentration overall pooled measurements. For the four-parameter model, y0 and yFin were both constrained to be between the minimum and the maximum of the median activities calculated at each concentration overall pooled measurements. The model with the lowest corrected Akaike information criterion (AICc) was selected as the best fit model.Dose–response curves were fit using the −11 and 10−4 M. In the event of a failure to fit a sigmoidal dose–response curve, the smooth.spline option in R was used to fit a curve that could be used to determine AUC.Area under the curve (AUC) was calculated from the fitted curve using the trapezoid rule in the concentration range 10z′ statistic was calculated using the following formula: 1 − ((3 × s.d. (negctrl)) + (3 × s.d. (posctrl)))/abs (mean (negctrl) – mean (posctrl)).The 40. Raw RLU values were processed as described above for the single-agent experiments, except no log2 transformation was applied.Drug combination experiments were analyzed using the BRAID response surface modelPaxalisib (GDC0084) and mirdametinib (PD0325901) were formulated at 1.8 or 2.5 mg/ml, respectively, in 1% methylcellulose and 1% Tween 80 with sonication. The combination was co-formulated and administered as a single gavage.59. In brief, the tumor tissue was homogenized in cold RIPA buffer with protease and phosphatase inhibitor cocktails on ice. The protein concentrations were determined with the BCA method. The samples were denatured with the NuPAGE sample-reducing agent and LDS sample buffer at 70 °C for 15 min. The proteins were separated by NuPAGE precast gels and blotted on the nitrocellulose membrane. Antibodies including the dilution ratios and reagents are listed in the key resource Supplementary Table SJ-DIPGX37 or SJ-DIPGX7 tumors were implanted in the brain and treated when mice showed decreased activity consistent with large tumors and confirmed visualization of brain tumors by MRI. Mice were dosed by oral gavage, QD, for 5 days with mirdametinib (17 mg/kg), paxalisib (12 mg/kg), mirdametinib and paxalisib , or vehicle. Two hours after the last dose, mice were perfused with phosphate-buffered saline (PBS) to remove blood, a small piece of tumor was grossly dissected and snap-frozen for western blot analysis, and the remainder of the tumor and brain was processed for FFPE histology and IHC. Long-term treatment at these doses caused toxicity manifested as loss of >20% of body weight. To identify doses tolerated for longer treatment needed for survival studies, we treated CD-1 nude mice without tumors in one of seven arms: (1) vehicle; (2) paxalisib at 8 mg/kg; (3) paxalisib at 12 mg/kg; (4) mirdametinib at 14 mg/kg; (5) mirdametinib at 17 mg/kg; (6) paxalisib at 8 mg/kg + mirdametinib at 14 mg/kg, or (7) paxalisib at 12 mg/kg and mirdametinib at 17 mg/kg. Three mice per arm were treated for five consecutive days, and then the brains were collected 2 h after the final dose for pharmacodynamic analysis of pathway inhibition (pAKT and pERK) by western blotting. An additional three mice per arm were treated on cycles of 5 days on, 2 days off for three cycles. Body weight and behavioral changes were monitored daily. Paxalisib (8 mg/kg) and mirdametinib (14 mg/kg) alone and in combination were tolerated without loss of >20% body weight, so these doses were selected for a survival study. Western blots for pharmacodynamic studies were performed as previously described5 cells in 7.5 µl of Matrigel/mouse were implanted into brains of 24 mice. The details of implantation were previously described in this Methods section and in a previous publication55. Bioluminescence imaging (BLI) was monitored weekly, and 50 days after implantation when all mice reached a threshold BLI total flux >2 × 105, they were randomized into four treatment groups (6 mice per group) and treated with vehicle, paxalisib (8 mg/kg), mirdametinib (14 mg/kg) or paxalisib + mirdametinib QD, 5 days on and 2/3 days off. Mice were euthanized when they reached moribund status.Cryopreserved SJ-DIPGX37 PDOX cells were thawed, and 2.4 × 1075. Additional details are presented in Supplementary Note The plasma and brain PK of mirdametinib and paxalisib was studied in non-tumor-bearing mice to determine potential for a PK drug–drug interaction (DDI). Mice were dosed mirdametinib and paxalisib daily, either alone or in combination, for up to 5 days. Blood samples were obtained from the retro-orbital plexus under anesthesia or by cardiac puncture upon termination. Brains were harvested after cardiac puncture and aortic perfusion with PBS. Samples were stored at −80 °C until analysis with qualified LC-MS/MS methods. Plasma concentration-time (Ct) data were analyzed using nonlinear mixed effects modeling implemented in Monolix 2019R2 . To enhance modeling precision and power, additional paxalisib plasma Ct data from a separate DDI study with another targeted compound was added to the analysis. Combination status was tested as a covariate upon the apparent clearance (CL/F) of each compound using the likelihood ratio test. Brain concentrations were log transformed and analyzed using two-way ANOVA with sample time and combination status as factors. Practically impactful interactions were defined as a ≥twofold change in the parameters of interest, consistent with the conventionally accepted threshold for preclinical and DDI studiesFurther information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Reporting Summary