CBMT-15. MET INHIBITION DRIVES PGC1A DEPENDENT METABOLIC REPROGRAMMING AND ELICITS UNIQUE METABOLIC VULNERABILITIES IN GLIOBLASTOMA

Abstract The receptor kinase, c-MET, has emerged as a target for glioblastoma therapy. However, treatment resistance evolves inevitably. By performing a global metabolite screen with metabolite set enrichment coupled with transcriptome and gene set enrichment analysis and proteomic screening, we have identified substantial reprogramming of tumor metabolism, involving oxidative phosphorylation and fatty acid oxidation (FAO) with a substantial accumulation of acyl-carnitines accompanied by an increase of PGC1a in response to genetic (shRNA and CRISPR/Cas9) and pharmacological (crizotinib) inhibition of c-MET. Extracellular flux and carbon tracing analyses (U-13C-Glucose and U-13C-Glutamine) demonstrated enhanced oxidative metabolism, which was driven by FAO and supported by increased anaplerosis of glucose carbons. These findings were observed in concert with increased number and fusion of mitochondria and production of reactive oxygen species (ROS). Genetic interference with PGC1a rescued this oxidative phenotype driven by c-MET inhibition. Silencing and chromatin immunoprecipitation experiments demonstrated that CREB regulates the expression of PGC1a in the context of c-MET inhibition. Interference with both oxidative phosphorylation (metformin, oligomycin) and beta-oxidation of fatty acids (etomoxir) enhanced the anti-tumor efficacy of c-MET inhibition. Moreover, based on a high-throughput drug screen, we show that gamitrinib along with c-MET inhibition results in synergistic cell death. Finally, utilizing patient-derived xenograft models, we provide evidence that the combination treatments (crizotinib+etomoxir and crizotinib+gamitrinib) were significantly more efficacious than single treatment without induction of toxicity. Collectively, we have unraveled the mechanistic underpinnings of c-MET inhibitor treatment and identified novel combination therapies that may enhance the therapeutic efficacy of c-MET inhibition.

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Identifying Personalized Metabolic Signatures in Breast Cancer

Metabolites ◽

10.3390/metabo11010020 ◽

2020 ◽

Vol 11 (1) ◽

pp. 20

Author(s):

Priyanka Baloni ◽

Wikum Dinalankara ◽

John C. Earls ◽

Theo A. Knijnenburg ◽

Donald Geman ◽

...

Keyword(s):

Drug Targets ◽

Metabolic Networks ◽

Target Genes ◽

Enrichment Analysis ◽

Metabolic Reprogramming ◽

The Cancer Genome Atlas ◽

Estrogen Metabolism ◽

Acid Oxidation ◽

A Genome ◽

Context Specific

Cancer cells are adept at reprogramming energy metabolism, and the precise manifestation of this metabolic reprogramming exhibits heterogeneity across individuals (and from cell to cell). In this study, we analyzed the metabolic differences between interpersonal heterogeneous cancer phenotypes. We used divergence analysis on gene expression data of 1156 breast normal and tumor samples from The Cancer Genome Atlas (TCGA) and integrated this information with a genome-scale reconstruction of human metabolism to generate personalized, context-specific metabolic networks. Using this approach, we classified the samples into four distinct groups based on their metabolic profiles. Enrichment analysis of the subsystems indicated that amino acid metabolism, fatty acid oxidation, citric acid cycle, androgen and estrogen metabolism, and reactive oxygen species (ROS) detoxification distinguished these four groups. Additionally, we developed a workflow to identify potential drugs that can selectively target genes associated with the reactions of interest. MG-132 (a proteasome inhibitor) and OSU-03012 (a celecoxib derivative) were the top-ranking drugs identified from our analysis and known to have anti-tumor activity. Our approach has the potential to provide mechanistic insights into cancer-specific metabolic dependencies, ultimately enabling the identification of potential drug targets for each patient independently, contributing to a rational personalized medicine approach.

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The Oncogenic Roles of PTTG1 and PTTG2 Genes and Pseudogene PTTG3P in Head and Neck Squamous Cell Carcinomas

Diagnostics ◽

10.3390/diagnostics10080606 ◽

2020 ◽

Vol 10 (8) ◽

pp. 606 ◽

Cited By ~ 1

Author(s):

Inga Grzechowiak ◽

Justyna Graś ◽

Dominika Szymańska ◽

Martyna Biernacka ◽

Kacper Guglas ◽

...

Keyword(s):

Dna Repair ◽

Oxidative Phosphorylation ◽

Head And Neck ◽

Squamous Cell ◽

Enrichment Analysis ◽

Tp53 Gene ◽

Squamous Cell Carcinomas ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Expression Levels

Background: Head and neck squamous cell carcinomas are a group of heterogeneous diseases that occur in the mouth, pharynx and larynx and are characterized by poor prognosis. A low overall survival rate leads to a need to develop biomarkers for early head and neck squamous cell carcinomas detection, accurate prognosis and appropriate selection of therapy. Therefore, in this paper, we investigate the biological role of the PTTG3P pseudogene and associated genes PTTG1 and PTTG2 and their potential use as biomarkers. Methods: Based on TCGA data and the UALCAN database, PTTG3P, PTTG1 and PTTG2 expression profiles and clinicopathological features with TP53 gene status as well as expression levels of correlated genes were analyzed in patients’ tissue samples. The selected genes were classified according to their biological function using the PANTHER tool. Gene Set Enrichment Analysis software was used for functional enrichment analysis. All statistical analyses were performed using GraphPad Prism 5. Results: In head and neck squamous cell carcinomas, significant up-regulation of the PTTG3P pseudogene, PTTG1 and PTTG2 genes’ expression between normal and cancer samples were observed. Moreover, the expression of PTTG3P, PTTG1 and PTTG2 depends on the type of mutation in TP53 gene, and they correlate with genes from p53 pathway. PTTG3P expression was significantly correlated with PTTG1 as well as PTTG2, as was PTTG1 expression with PTTG2. Significant differences between expression levels of PTTG3P, PTTG1 and PTTG2 in head and neck squamous cell carcinomas patients were also observed in clinicopathological contexts. The contexts taken into consideration included: T-stage for PTTG3P; grade for PTTG3, PTTG1 and PTTG2; perineural invasion and lymph node neck dissection for PTTG1 and HPV p16 status for PTTG3P, PTTG1 and PTTG2. A significantly longer disease-free survival for patients with low expressions of PTTG3P and PTTG2, as compared to high expression groups, was also observed. Gene Set Enrichment Analysis indicated that the PTTG3 high-expressing group of patients have the most deregulated genes connected with DNA repair, oxidative phosphorylation and peroxisome pathways. For PTTG1, altered genes are from DNA repair groups, Myc targets, E2F targets and oxidative phosphorylation pathways, while for PTTG2, changes in E2F targets, G2M checkpoints and oxidative phosphorylation pathways are indicated. Conclusions: PTTG3P and PTTG2 can be used as a prognostic biomarker in head and neck squamous cell carcinomas diagnostics. Moreover, patients with high expressions of PTTG3P, PTTG1 or PTTG2 have worse outcomes due to upregulation of oncogenic pathways and more aggressive phenotypes.

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PI3K Pathway Inhibition with NVP-BEZ235 Hinders Glycolytic Metabolism in Glioblastoma Multiforme Cells

Cells ◽

10.3390/cells10113065 ◽

2021 ◽

Vol 10 (11) ◽

pp. 3065

Author(s):

Shreya Udawant ◽

Carl Litif ◽

Alma Lopez ◽

Bonnie Gunn ◽

Erin Schuenzel ◽

...

Keyword(s):

Glioblastoma Multiforme ◽

Enrichment Analysis ◽

Pi3k Pathway ◽

Gene Set Enrichment Analysis ◽

Metabolic Reprogramming ◽

Clinical Samples ◽

Rna Seq ◽

Bioinformatics Analyses ◽

Dual Inhibitor ◽

The Impact

Glioblastoma (GBM) is the most lethal primary brain cancer that lacks effective molecular targeted therapies. The PI3K/AKT/mTOR pathway is activated in 90% of all Glioblastoma multiforme (GBM) tumors. To gain insight into the impact of the PI3K pathway on GBM metabolism, we treated U87MG GBM cells with NVP-BEZ235 (PI3K and mTOR a dual inhibitor) and identified differentially expressed genes with RNA-seq analysis. RNA-seq identified 7803 differentially regulated genes in response to NVP-BEZ235. Gene Set Enrichment Analysis (GSEA) identified two glycolysis-related gene sets that were significantly enriched (p < 0.05) in control samples compared to NVP-BEZ235-treated samples. We validated the inhibition of glycolytic genes by NVP-BEZ235 and examined the impact of the FOXO1 inhibitor (AS1842856) on these genes in a set of GBM cell lines. FOXO1 inhibition alone was associated with reduced LDHA expression, but not ENO1 or PKM2. Bioinformatics analyses revealed that PI3K-impacted glycolytic genes were over-expressed and co-expressed in GBM clinical samples. The elevated expression of PI3K-impacted glycolytic genes was associated with poor prognosis in GBM based on Kaplan–Meier survival analyses. Our results suggest novel insights into hallmark metabolic reprogramming associated with the PI3K-mTOR dual inhibition.

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65 Placental Function at Term is Altered in Broodmares Fed with Cereals from Mid Gestation

Reproduction Fertility and Development ◽

10.1071/rdv30n1ab65 ◽

2018 ◽

Vol 30 (1) ◽

pp. 171

Author(s):

M. Robles ◽

P. Peugnet ◽

C. Dubois ◽

F. Piumi ◽

L. Jouneau ◽

...

Keyword(s):

Random Effect ◽

Area Under The Curve ◽

Enrichment Analysis ◽

Mixed Linear Model ◽

Tolerance Test ◽

Gene Set Enrichment Analysis ◽

Acid Oxidation ◽

Placental Function ◽

Insulin Resistant ◽

Gene Sets

Recent data obtained in our laboratory suggest that feeding pregnant broodmares with cereal concentrates may affect both mare and foal metabolism in the short and long term. Here, we investigated feto-placental biometry and placental function at term in mares fed with cereals and forage or forage only. Twenty-two multiparous mares inseminated with the same stallion were allocated to 1 of 2 groups from 7 months of gestation: group F (n = 10) were fed forage only, whereas group B (n = 12) received forage and cracked barley until foaling. At 3 and 9 months of gestation, a glucose tolerance test (IVGTT) was performed to evaluate the insulin resistance of pregnant mares. At birth, placentas and foals were weighed and measured. Placental samples were collected above the umbilical cord insertion and snap frozen. An RNA sequencing (RNAseq) analysis was performed on 9 placentas of each group. After normalization, gene levels were analysed using the DESEqn 2 package of R software (https://www.r-project.org/). Enrichment of gene sets was analysed using the Gene Set Enrichment Analysis (GSEA) software using the Kyoto Encyclopaedia of Genes and Genomes (KEGG) and Gene Ontology [GO, biological processes (bp), molecular function (mf) and cellular components (cc)] databases. Gene analysis statistical results were considered significant for P-values < 0.05 after false rate discovery (fdr) correction. The IVGTT results were analysed using a type 3 ANOVA on a mixed linear model with group as fixed effect and age of the mare as random effect. At 3 months of gestation, maternal glucose metabolism was not different between groups. At 9 months, B mares had a higher insulin area under the curve (AUC) after glucose injection than F mares (P < 0.01), without any difference in glucose AUC, suggesting that B mares were more insulin resistant than F mares. At birth, no difference was observed for feto-placental biometry between groups. Gene-level analysis could not discern differences in gene expression between groups after fdr correction. The GSEA analysis, however, showed that 8 gene sets were down-regulated in C placentas (2 KEGG, 2 GObp, 3 GOmf, 1 GOcc) and 193 gene sets were up-regulated (15 KEGG, 144 GObp, 12 GOmf, 22 GOcc) in B placentas. The down-regulated gene sets were involved in neutral amino acids and anion transport, fatty acid oxidation, acetyl coA synthesis, cholesterol and folate degradation, and the up-regulated gene sets were involved in RNA expression, inflammation (activation and recruitment of immune cells, MAPK signalling, complement and coagulation cascades, pro-inflammatory cytokine production and signalling) and in vascularisation (vasculogenesis, angiogenesis and smooth muscle cells development). The results are consistent with the altered function observed in term placentas of women who suffer from gestational diabetes. In conclusion, feeding pregnant mares with cereal from mid gestation alters the placental function at term. The authors thank the GeT platform (Toulouse, France) for the sequencing of the samples.

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Prognostic significance and oncogene function of cathepsin A in hepatocellular carcinoma

Scientific Reports ◽

10.1038/s41598-021-93998-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Huaxiang Wang ◽

Fengfeng Xu ◽

Fang Yang ◽

Lizhi Lv ◽

Yi Jiang

Keyword(s):

Hepatocellular Carcinoma ◽

Oxidative Phosphorylation ◽

Prognostic Significance ◽

Enrichment Analysis ◽

Normal Liver ◽

Diagnostic Value ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Clinical Value ◽

Lysosomal Protease

AbstractCathepsin A (CTSA) is a lysosomal protease that regulates galactoside metabolism. The previous study has shown CTSA is abnormally expressed in various types of cancer. However, rarely the previous study has addressed the role of CTSA in hepatocellular carcinoma (HCC) and its prognostic value. To study the clinical value and potential function of CTSA in HCC, datasets from the Cancer Genome Atlas (TCGA) database and a 136 HCC patient cohort were analyzed. CTSA expression was found to be significantly higher in HCC patients compared with normal liver tissues, which was supported by immunohistochemistry (IHC) validation. Both gene ontology (GO) and The Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses demonstrated that CTSA co-expressed genes were involved in ATP hydrolysis coupled proton transport, carbohydrate metabolic process, lysosome organization, oxidative phosphorylation, other glycan degradation, etc. Survival analysis showed a significant reduction both in overall survival (OS) and recurrence-free survival (RFS) of patients with high CTSA expression from both the TCGA HCC cohort and 136 patients with the HCC cohort. Furthermore, CTSA overexpression has diagnostic value in distinguishing between HCC and normal liver tissue [Area under curve (AUC) = 0.864]. Moreover, Gene set enrichment analysis (GSEA) showed that CTSA expression correlated with the oxidative phosphorylation, proteasome, and lysosome, etc. in HCC tissues. These findings demonstrate that CTSA may as a potential diagnostic and prognostic biomarker in HCC.

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Distinctive Cellular and Metabolic Reprogramming in Porcine Lung Mononuclear Phagocytes Infected With Type 1 PRRSV Strains

Frontiers in Immunology ◽

10.3389/fimmu.2020.588411 ◽

2020 ◽

Vol 11 ◽

Author(s):

Elisa Crisci ◽

Marco Moroldo ◽

Thien-Phong Vu Manh ◽

Ammara Mohammad ◽

Laurent Jourdren ◽

...

Keyword(s):

Expression Profiles ◽

Enrichment Analysis ◽

Cellular Reprogramming ◽

Mononuclear Phagocytes ◽

Gene Set Enrichment Analysis ◽

Metabolic Reprogramming ◽

Specific Expression ◽

Data Set

Porcine reproductive and respiratory syndrome (PRRS) has an extensive impact on pig production. The causative virus (PRRSV) is divided into two species, PRRSV-1 (European origin) and PRRSV-2 (North American origin). Within PRRSV-1, PRRSV-1.3 strains, such as Lena, are more pathogenic than PRRSV-1.1 strains, such as Flanders 13 (FL13). To date, the molecular interactions of PRRSV with primary lung mononuclear phagocyte (MNP) subtypes, including conventional dendritic cells types 1 (cDC1) and 2 (cDC2), monocyte-derived DCs (moDC), and pulmonary intravascular macrophages (PIM), have not been thoroughly investigated. Here, we analyze the transcriptome profiles of in vivo FL13-infected parenchymal MNP subpopulations and of in vitro FL13- and Lena-infected parenchymal MNP. The cell-specific expression profiles of in vivo sorted cells correlated with their murine counterparts (AM, cDC1, cDC2, moDC) with the exception of PIM. Both in vivo and in vitro, FL13 infection altered the expression of a low number of host genes, and in vitro infection with Lena confirmed the higher ability of this strain to modulate host response. Machine learning (ML) and gene set enrichment analysis (GSEA) unraveled additional relevant genes and pathways modulated by FL13 infection that were not identified by conventional analyses. GSEA increased the cellular pathways enriched in the FL13 data set, but ML allowed a more complete comprehension of functional profiles during FL13 in vitro infection. Data indicates that cellular reprogramming differs upon Lena and FL13 infection and that the latter might keep antiviral and inflammatory macrophage/DC functions silent. Although the slow replication kinetics of FL13 likely contribute to differences in cellular gene expression, the data suggest distinct mechanisms of interaction of the two viruses with the innate immune system during early infection.

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OS9.5 Evidence that adult glioblastoma adapts to standard therapy though chromatin remodeling

Neuro-Oncology ◽

10.1093/neuonc/noz126.063 ◽

2019 ◽

Vol 21 (Supplement_3) ◽

pp. iii19-iii19

Author(s):

N Rippaus ◽

J Manning ◽

A Droop ◽

M Al-Jabri ◽

M Care ◽

...

Keyword(s):

Gene Expression ◽

Chromatin Remodeling ◽

Standard Therapy ◽

Single Cells ◽

Treatment Resistance ◽

Enrichment Analysis ◽

Post Treatment ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Differential Gene

Abstract BACKGROUND Glioblastoma (GBM) tumours recur following standard treatment in almost all cases. We use ‘omics technologies to simultaneously profile pairs of primary and matched recurrent GBM to specifically identify and characterise the cells that resisted treatment, with the aim of determining how to more effectively kill them. MATERIAL AND METHODS We have analysed high coverage RNAseq data from pairs of GBM tumours: primary de novo tumour and matched local recurrence from patients that underwent standard therapy. Our original cohort constituted 23 pairs and our validation cohort was an additional 22 pairs. We also cultured two plates of spheroids directly from a patient’s GBM, treating one with radiation and temozolomide. We monitored growth and captured and sequenced RNA from single cells at two time-points: one week post-treatment when the deviation between untreated and treated spheroid growth curves was most pronounced; and three weeks post-treatment when the growth rate of treated spheroids had recovered. We investigated differential gene expression between primary and recurrent pairs, and single cells pre- and post-treatment, and performed a bespoke per patient gene set enrichment analysis. RESULTS Differential gene expression analysis in 23 tumour pairs indicated a treatment-induced shift in cell states linked to normal neurogenesis and prompted us to develop a novel gene set enrichment analysis approach to identify gene regulatory factors that may orchestrate such a shift. This revealed the significant and universal dysregulation of genes, through therapy, that are targeted by a specific chromatin remodeling machinery. This finding was validated in an independent cohort of 22 further GBM pairs. To understand the therapeutic potential of this finding we must determine whether genes are dysregulated through therapy owing to a) their fixed expression in inherently treatment resistance cells in the primary tumour which get selected during therapy to increase the signal of that profile, or b) changes in expression during the process of cells acquiring treatment resistance. To inspect this, we analysed single cell gene expression data from GBM spheroids pre- and post-treatment. We found that there was significant dysregulation of the genes associated with the chromatin remodeling complex but only at the three-week post-treatment time-point. CONCLUSION Our results indicate that GBM cells are being transcriptionally reprogrammed in response to treatment; the mechanism of which may represent a therapeutic opportunity.

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Identifying personalized metabolic signatures in breast cancer

10.20944/preprints202011.0474.v1 ◽

2020 ◽

Author(s):

Priyanka Baloni ◽

Wikum Dinalankara ◽

John C. Earls ◽

Theo A. Knijnenburg ◽

Donald Geman ◽

...

Keyword(s):

Drug Targets ◽

Metabolic Networks ◽

Target Genes ◽

Enrichment Analysis ◽

Metabolic Reprogramming ◽

The Cancer Genome Atlas ◽

Estrogen Metabolism ◽

Acid Oxidation ◽

A Genome ◽

Context Specific

Cancer cells are adept at reprogramming energy metabolism and the precise manifestation of this metabolic reprogramming exhibits heterogeneity across individuals (and from cell to cell). In this study, we analyzed the metabolic differences between interpersonal heterogeneous cancer phenotypes. We used divergence analysis on gene expression data of 1156 breast normal and tumor samples from The Cancer Genome Atlas (TCGA) and integrated this information with a genome-scale reconstruction of human metabolism to generate personalized, context-specific metabolic networks. Using this approach, we classified the samples into four distinct groups based on their metabolic profiles. Enrichment analysis of the subsystems indicated that amino acid metabolism, fatty acid oxidation, citric acid cycle, androgen and estrogen metabolism and ROS detoxification distinguished these four groups. Additionally, we developed a workflow to identify potential drugs that can selectively target genes associated with the reactions of interest. MG-132 (a proteasome inhibitor) and OSU-03012 (a celecoxib derivative) were the top-ranking drugs identified from our analysis and known to have anti-tumor activity. Our approach has the potential to provide mechanistic insights into cancer-specific metabolic dependencies, ultimately enabling the identification of potential drug targets for each patient independently, contributing to a rational personalized medicine approach.

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Chromatin remodelling to facilitate treatment resistance in glioblastoma

Neuro-Oncology ◽

10.1093/neuonc/noz167.027 ◽

2019 ◽

Vol 21 (Supplement_4) ◽

pp. iv7-iv7

Author(s):

Alexander-F Bruns ◽

Nora Rippaus ◽

Alastair Droop ◽

Muna Al-Jabri ◽

Matthew Care ◽

...

Keyword(s):

Standard Treatment ◽

Clonal Evolution ◽

Differential Expression Analysis ◽

Treatment Resistance ◽

Enrichment Analysis ◽

Resistance Mechanisms ◽

Chromatin Remodelling ◽

Gene Set Enrichment Analysis ◽

Multiple Treatment ◽

Therapeutic Opportunity

Abstract Recent findings from our group, and the wider community, show that standard treatment does not impose an apparent bottleneck on the clonal evolution of adult glioblastoma (GBM), implying a lack of direct therapeutic opportunity. This does not negate the possibility that multiple treatment-resistance mechanisms co-exist in tumours, repeated across patients, making a combination of targeted therapies a potentially effective approach. We investigated whether treatment resistance may be driven by selection of cellular properties conferred above the level of the genome. Differential expression analysis was performed on 23 pairs of primary and recurrent tumours from patients who received standard treatment and had a local recurrence treated by surgery and second line chemotherapy. This revealed a treatment-induced shift in cell states linked to normal neurodevelopment. The latter is orchestrated by cascades of transcription factors. We, therefore, applied a bespoke gene set enrichment analysis to our paired expression data to investigate whether any factors were implicated in co-regulation of the genes that were altered through therapy. This identified a specific chromatin remodelling machinery, instrumental in normal neurogenesis. We validated our results in an independent cohort of 22 paired GBM samples. Our results suggest that the chromatin remodelling machinery is responsible for determining transcriptional hierarchies in GBM, shown elsewhere to have different treatment sensitivities such that their relative abundances are altered through treatment.

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Aurora kinase A inhibition reverses the Warburg effect and elicits unique metabolic vulnerabilities in glioblastoma

Nature Communications ◽

10.1038/s41467-021-25501-x ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Trang T. T. Nguyen ◽

Enyuan Shang ◽

Chang Shu ◽

Sungsoo Kim ◽

Angeliki Mela ◽

...

Keyword(s):

Aurora Kinase ◽

Critical Issue ◽

Metabolic Reprogramming ◽

Acid Oxidation ◽

Peroxisome Proliferator ◽

Novel Therapy ◽

Peroxisome Proliferator Activated Receptor ◽

Aurora Kinase A ◽

Extracellular Flux ◽

Kinase A

AbstractAurora kinase A (AURKA) has emerged as a drug target for glioblastoma (GBM). However, resistance to therapy remains a critical issue. By integration of transcriptome, chromatin immunoprecipitation sequencing (CHIP-seq), Assay for Transposase-Accessible Chromatin sequencing (ATAC-seq), proteomic and metabolite screening followed by carbon tracing and extracellular flux analyses we show that genetic and pharmacological AURKA inhibition elicits metabolic reprogramming mediated by inhibition of MYC targets and concomitant activation of Peroxisome Proliferator Activated Receptor Alpha (PPARA) signaling. While glycolysis is suppressed by AURKA inhibition, we note an increase in the oxygen consumption rate fueled by enhanced fatty acid oxidation (FAO), which was accompanied by an increase of Peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α). Combining AURKA inhibitors with inhibitors of FAO extends overall survival in orthotopic GBM PDX models. Taken together, these data suggest that simultaneous targeting of oxidative metabolism and AURKAi might be a potential novel therapy against recalcitrant malignancies.

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