Deciphering oxygen distribution and hypoxia profiles in the tumor microenvironment: a data-driven mechanistic modeling approach.

OBJECTIVE: The distribution of hypoxia within tissues plays a critical role in tumor diagnosis and prognosis. Recognizing the significance of tumor oxygenation and hypoxia gradients, we introduce mathematical frameworks grounded in mechanistic modeling approaches for their quantitative assessment within a tumor microenvironment. By utilizing known blood vasculature, we aim to predict hypoxia levels across different tumor types. APPROACH: Our approach offers a computational method to measure and predict hypoxia using known blood vasculature. By formulating a reaction-diffusion model for oxygen distribution, we derive the corresponding hypoxia profile. Main Results: The framework successfully replicates observed inter- and intra-tumor heterogeneity in experimentally obtained hypoxia profiles across various tumor types (breast, ovarian, pancreatic). Additionally, we propose a data-driven method to deduce partial differential equation (PDE) models with spatially dependent parameters, which allows us to comprehend the variability of hypoxia profiles within tissues. The versatility of our framework lies in capturing diverse and dynamic behaviors of tumor oxygenation, as well as categorizing states of vascularization based on the dynamics of oxygen molecules, as identified by the model parameters. SIGNIFICANCE: The proposed data-informed mechanistic method quantitatively assesses hypoxia in the tumor microenvironment by integrating diverse histopathological data and making predictions across different types of data. The framework contributes valuable insights from both modeling and biological perspectives, advancing our comprehension of spatio-temporal dynamics of tumor oxygenation.

Multi-Level Control of the ATM/ATR-CHK1 Axis by the Transcription Factor E4F1 in Triple-Negative Breast Cancer.

E4F1 is essential for early embryonic mouse development and for controlling the balance between proliferation and survival of actively dividing cells. We previously reported that E4F1 is essential for the survival of murine p53-deficient cancer cells by controlling the expression of genes involved in mitochondria functions and metabolism, and in cell-cycle checkpoints, including CHEK1, a major component of the DNA damage and replication stress responses. Here, combining ChIP-Seq and RNA-Seq approaches, we identified the transcriptional program directly controlled by E4F1 in Human Triple-Negative Breast Cancer cells (TNBC). E4F1 binds and regulates a limited list of direct target genes (57 genes) in these cells, including the human CHEK1 gene and, surprisingly, also two other genes encoding post-transcriptional regulators of the ATM/ATR-CHK1 axis, namely, the TTT complex component TTI2 and the phosphatase PPP5C, that are essential for the folding and stability, and the signaling of ATM/ATR kinases, respectively. Importantly, E4F1 also binds the promoter of these genes in vivo in Primary Derived Xenograft (PDX) of human TNBC. Consequently, the protein levels and signaling of CHK1 but also of ATM/ATR kinases are strongly downregulated in E4F1-depleted TNBC cells resulting in a deficiency of the DNA damage and replicative stress response in these cells. The E4F1-depleted cells fail to arrest into S-phase upon treatment with the replication-stalling agent Gemcitabine, and are highly sensitized to this drug, as well as to other DNA-damaging agents, such as Cisplatin. Altogether, our data indicate that in breast cancer cells the ATM/ATR-CHK1 signaling pathway and DNA damage-stress response are tightly controlled at the transcriptional and post-transcriptional level by E4F1.

Computational Model of Heterogeneity in Melanoma: Designing Therapies and Predicting Outcomes.

Cutaneous melanoma is a highly invasive tumor and, despite the development of recent therapies, most patients with advanced metastatic melanoma have a poor clinical outcome. The most frequent mutations in melanoma affect the BRAF oncogene, a protein kinase of the MAPK signaling pathway. Therapies targeting both BRAF and MEK are effective for only 50% of patients and, almost systematically, generate drug resistance. Genetic and non-genetic mechanisms associated with the strong heterogeneity and plasticity of melanoma cells have been suggested to favor drug resistance but are still poorly understood. Recently, we have introduced a novel mathematical formalism allowing the representation of the relation between tumor heterogeneity and drug resistance and proposed several models for the development of resistance of melanoma treated with BRAF/MEK inhibitors. In this paper, we further investigate this relationship by using a new computational model that copes with multiple cell states identified by single cell mRNA sequencing data in melanoma treated with BRAF/MEK inhibitors. We use this model to predict the outcome of different therapeutic strategies. The reference therapy, referred to as "continuous" consists in applying one or several drugs without disruption. In "combination therapy", several drugs are used sequentially. In "adaptive therapy" drug application is interrupted when the tumor size is below a lower threshold and resumed when the size goes over an upper threshold. We show that, counter-intuitively, the optimal protocol in combination therapy of BRAF/MEK inhibitors with a hypothetical drug targeting cell states that develop later during the tumor response to kinase inhibitors, is to treat first with this hypothetical drug. Also, even though there is little difference in the timing of emergence of the resistance between continuous and adaptive therapies, the spatial distribution of the different melanoma subpopulations is more zonated in the case of adaptive therapy.

Meeting report of the 4th biennial Metabolism and Cancer symposium.

The 4th International meeting Metabolism and Cancer initially programed to take place in Bordeaux (France) was held virtually on May 27-29, 2021. The three-day event was followed by around 600 participants daily from 47 countries around the world. The meeting hosted 21 speakers including selected talks and a keynote lecture from the Nobel Prize winner Sir Peter J. Ratcliffe (Oxford, UK). Presentations and discussions were divided in four scientific sessions: (a) Redox and energy metabolism (b) Redox and hypoxia (c) Metabolic profiling and epigenetic control and (d) Signalling, fuelling and metabolism in cancer and a general public session on cancer and nutrition. This report summarises the presentations and outcomes of the 4th annual Metabolism and Cancer symposium. We provide here a summary of the scientific highlights of this exciting meeting.

The multifunctional protein E4F1 links P53 to lipid metabolism in adipocytes.

Growing evidence supports the importance of the p53 tumor suppressor in metabolism but the mechanisms underlying p53-mediated control of metabolism remain poorly understood. Here, we identify the multifunctional E4F1 protein as a key regulator of p53 metabolic functions in adipocytes. While E4F1 expression is upregulated during obesity, E4f1 inactivation in mouse adipose tissue results in a lean phenotype associated with insulin resistance and protection against induced obesity. Adipocytes lacking E4F1 activate a p53-dependent transcriptional program involved in lipid metabolism. The direct interaction between E4F1 and p53 and their co-recruitment to the Steaoryl-CoA Desaturase-1 locus play an important role to regulate monounsaturated fatty acids synthesis in adipocytes. Consistent with the role of this E4F1-p53-Steaoryl-CoA Desaturase-1 axis in adipocytes, p53 inactivation or diet complementation with oleate partly restore adiposity and improve insulin sensitivity in E4F1-deficient mice. Altogether, our findings identify a crosstalk between E4F1 and p53 in the control of lipid metabolism in adipocytes that is relevant to obesity and insulin resistance.

High Resolution Episcopic Microscopy for Qualitative and Quantitative Data in Phenotyping Altered Embryos and Adult Mice Using the New "Histo3D" System.

3D imaging in animal models, during development or in adults, facilitates the identification of structural morphological changes that cannot be achieved with traditional 2D histological staining. Through the reconstruction of whole embryos or a region-of-interest, specific changes are better delimited and can be easily quantified. We focused here on high-resolution episcopic microscopy (HREM), and its potential for visualizing and quantifying the organ systems of normal and genetically altered embryos and adult organisms. Although the technique is based on episcopic images, these are of high resolution and are close to histological quality. The images reflect the tissue structure and densities revealed by histology, albeit in a grayscale color map. HREM technology permits researchers to take advantage of serial 2D aligned stacks of images to perform 3D reconstructions. Three-dimensional visualization allows for an appreciation of topology and morphology that is difficult to achieve with classical histological studies. The nature of the data lends itself to novel forms of computational analysis that permit the accurate quantitation and comparison of individual embryos in a manner that is impossible with histology. Here, we have developed a new HREM prototype consisting of the assembly of a Leica Biosystems Nanocut rotary microtome with optics and a camera. We describe some examples of applications in the prenatal and adult lifestage of the mouse to show the added value of HREM for phenotyping experimental cohorts to compare and quantify structure volumes. At prenatal stages, segmentations and 3D reconstructions allowed the quantification of neural tissue and ventricular system volumes of normal brains at E14.5 and E16.5 stages. 3D representations of normal cranial and peripheric nerves at E15.5 and of the normal urogenital system from stages E11.5 to E14.5 were also performed. We also present a methodology to quantify the volume of the atherosclerotic plaques of ApoEtm1Unc/tm1Unc mutant mice and illustrate a 3D reconstruction of knee ligaments in adult mice.

Mitochondrial metabolism supports resistance to IDH mutant inhibitors in acute myeloid leukemia.

Mutations in IDH induce epigenetic and transcriptional reprogramming, differentiation bias, and susceptibility to mitochondrial inhibitors in cancer cells. Here, we first show that cell lines, PDXs, and patients with acute myeloid leukemia (AML) harboring an IDH mutation displayed an enhanced mitochondrial oxidative metabolism. Along with an increase in TCA cycle intermediates, this AML-specific metabolic behavior mechanistically occurred through the increase in electron transport chain complex I activity, mitochondrial respiration, and methylation-driven CEBPα-induced fatty acid ß-oxidation of IDH1 mutant cells. While IDH1 mutant inhibitor reduced 2-HG oncometabolite and CEBPα methylation, it failed to reverse FAO and OxPHOS. These mitochondrial activities were maintained through the inhibition of Akt and enhanced activation of peroxisome proliferator-activated receptor-γ coactivator-1 PGC1α upon IDH1 mutant inhibitor. Accordingly, OxPHOS inhibitors improved anti-AML efficacy of IDH mutant inhibitors in vivo. This work provides a scientific rationale for combinatory mitochondrial-targeted therapies to treat IDH mutant AML patients, especially those unresponsive to or relapsing from IDH mutant inhibitors.

DEXOM: Diversity-based enumeration of optimal context-specific metabolic networks.

The correct identification of metabolic activity in tissues or cells under different conditions can be extremely elusive due to mechanisms such as post-transcriptional modification of enzymes or different rates in protein degradation, making difficult to perform predictions on the basis of gene expression alone. Context-specific metabolic network reconstruction can overcome some of these limitations by leveraging the integration of multi-omics data into genome-scale metabolic networks (GSMN). Using the experimental information, context-specific models are reconstructed by extracting from the generic GSMN the sub-network most consistent with the data, subject to biochemical constraints. One advantage is that these context-specific models have more predictive power since they are tailored to the specific tissue, cell or condition, containing only the reactions predicted to be active in such context. However, an important limitation is that there are usually many different sub-networks that optimally fit the experimental data. This set of optimal networks represent alternative explanations of the possible metabolic state. Ignoring the set of possible solutions reduces the ability to obtain relevant information about the metabolism and may bias the interpretation of the true metabolic states. In this work we formalize the problem of enumerating optimal metabolic networks and we introduce DEXOM, an unified approach for diversity-based enumeration of context-specific metabolic networks. We developed different strategies for this purpose and we performed an exhaustive analysis using simulated and real data. In order to analyze the extent to which these results are biologically meaningful, we used the alternative solutions obtained with the different methods to measure: 1) the improvement of in silico predictions of essential genes in Saccharomyces cerevisiae using ensembles of metabolic network; and 2) the detection of alternative enriched pathways in different human cancer cell lines. We also provide DEXOM as an open-source library compatible with COBRA Toolbox 3.0, available at https://github.com/MetExplore/dexom.

The p53 Pathway and Metabolism: The Tree That Hides the Forest.

The p53 pathway is functionally inactivated in most, if not all, human cancers. The p53 protein is a central effector of numerous stress-related molecular cascades. p53 controls a safeguard mechanism that prevents accumulation of abnormal cells and their transformation by regulating DNA repair, cell cycle progression, cell death, or senescence. The multiple cellular processes regulated by p53 were more recently extended to the control of metabolism and many studies support the notion that perturbations of p53-associated metabolic activities are linked to cancer development, as well as to other pathophysiological conditions including aging, type II diabetes, and liver disease. Although much less documented than p53 metabolic activities, converging lines of evidence indicate that other key components of this tumor suppressor pathway are also involved in cellular metabolism through p53-dependent as well as p53-independent mechanisms. Thus, at least from a metabolic standpoint, the p53 pathway must be considered as a non-linear pathway, but the complex metabolic network controlled by these p53 regulators and the mechanisms by which their activities are coordinated with p53 metabolic functions remain poorly understood. In this review, we highlight some of the metabolic pathways controlled by several central components of the p53 pathway and their role in tissue homeostasis, metabolic diseases, and cancer.

Targeting MDM2-dependent serine metabolism as a therapeutic strategy for liposarcoma.

Well-differentiated and dedifferentiated liposarcomas (LPSs) are characterized by a systematic amplification of the MDM2 oncogene, which encodes a key negative regulator of the p53 pathway. The molecular mechanisms underlying MDM2 overexpression while sparing wild-type p53 in LPS remain poorly understood. Here, we show that the p53-independent metabolic functions of chromatin-bound MDM2 are exacerbated in LPS and mediate an addiction to serine metabolism that sustains nucleotide synthesis and tumor growth. Treatment of LPS cells with Nutlin-3A, a pharmacological inhibitor of the MDM2-p53 interaction, stabilized p53 but unexpectedly enhanced MDM2-mediated control of serine metabolism by increasing its recruitment to chromatin, likely explaining the poor clinical efficacy of this class of MDM2 inhibitors. In contrast, genetic or pharmacological inhibition of chromatin-bound MDM2 by SP141, a distinct MDM2 inhibitor triggering its degradation, or interfering with de novo serine synthesis, impaired LPS growth both in vitro and in clinically relevant patient-derived xenograft models. Our data indicate that targeting MDM2 functions in serine metabolism represents a potential therapeutic strategy for LPS.

Simultaneous Measurement of Metabolite Concentration and Isotope Incorporation by Mass Spectrometry.

Studies of the topology, functioning, and regulation of metabolic systems are based on two main types of information that can be measured by mass spectrometry: the (absolute or relative) concentration of metabolites and their isotope incorporation in 13C-labeling experiments. These data are currently obtained from two independent experiments because the 13C-labeled internal standard (IS) used to determine the concentration of a given metabolite overlaps the 13C-mass fractions from which its 13C-isotopologue distribution (CID) is quantified. Here, we developed a generic method with a dedicated processing workflow to obtain these two sets of information simultaneously in a unique sample collected from a single cultivation, thereby reducing by a factor of 2 both the number of cultivations to perform and the number of samples to collect, prepare, and analyze. The proposed approach is based on an IS labeled with other isotope(s) that can be resolved from the 13C-mass fractions of interest. As proof-of-principle, we analyzed amino acids using a doubly labeled 15N13C-cell extract as IS. Extensive evaluation of the proposed approach shows a similar accuracy and precision compared to state-of-the-art approaches. We demonstrate the value of this approach by investigating the dynamic response of amino acids metabolism in mammalian cells upon activation of the protein kinase R (PKR)-like endoplasmic reticulum kinase (PERK), a key component of the unfolded protein response. Integration of metabolite concentrations and isotopic profiles reveals a reduced de novo biosynthesis of amino acids upon PERK activation. The proposed approach is generic and can be applied to other (micro)organisms, analytical platforms, isotopic tracers, or classes of metabolites.

Metabolic functions of the tumor suppressor p53: Implications in normal physiology, metabolic disorders, and cancer.

BACKGROUND: The TP53 gene is one of the most commonly inactivated tumor suppressors in human cancers. p53 functions during cancer progression have been linked to a variety of transcriptional and non-transcriptional activities that lead to the tight control of cell proliferation, senescence, DNA repair, and cell death. However, converging evidence indicates that p53 also plays a major role in metabolism in both normal and cancer cells. SCOPE OF REVIEW: We provide an overview of the current knowledge on the metabolic activities of wild type (WT) p53 and highlight some of the mechanisms by which p53 contributes to whole body energy homeostasis. We will also pinpoint some evidences suggesting that deregulation of p53-associated metabolic activities leads to human pathologies beyond cancer, including obesity, diabetes, liver, and cardiovascular diseases. MAJOR CONCLUSIONS: p53 is activated when cells are metabolically challenged but the origin, duration, and intensity of these stresses will dictate the outcome of the p53 response. p53 plays pivotal roles both upstream and downstream of several key metabolic regulators and is involved in multiple feedback-loops that ensure proper cellular homeostasis. The physiological roles of p53 in metabolism involve complex mechanisms of regulation implicating both cell autonomous effects as well as autocrine loops. However, the mechanisms by which p53 coordinates metabolism at the organismal level remain poorly understood. Perturbations of p53-regulated metabolic activities contribute to various metabolic disorders and are pivotal during cancer progression.

Spatio-Genetic and phenotypic modelling elucidates resistance and re-sensitisation to treatment in heterogeneous melanoma.

Although novel targeted therapies have significantly improved the overall survival of patients with advanced melanoma, understanding and combatting drug resistance remains a major clinical challenge. Using partial differential equations, we describe the evolution of a cellular population through time, space, and phenotype dimensions, in the presence of various drug species. We then use this framework to explore models in which resistance is attained by either mutations (irreversible) or plasticity (reversible). Numerical results suggest that punctuated evolutionary assumptions are more consistent with results obtained from murine melanoma models than gradual evolution. Furthermore, in the context of an evolving tumour cell population, sequencing the treatment, for instance applying immunotherapy before BRAF inhibitors, can increase treatment effectiveness. However, drug strategies which showed success within a spatially homogeneous tumour environment were unsuccessful under heterogeneous conditions, suggesting that spatio-environmental heterogeneity may be the greatest challenge to tumour therapies. Plastic metabolic models are additionally capable of reproducing the characteristic resistant tumour volume curves and predicting re-sensitisation to secondary waves of treatment observed in patient derived xenograft (PDX) melanomas treated with MEK and BRAF inhibitors. Nevertheless, secondary relapse due to a pre-adapted subpopulation, remaining after the first wave of treatment, results in a more rapid development of resistance. Our model provides a framework through which tumour resistance can be understood and would suggest that carefully phased treatments may be able to overcome the development of long-term resistance in melanoma.

Mitochondrial MDM2 Regulates Respiratory Complex I Activity Independently of p53.

Accumulating evidence indicates that the MDM2 oncoprotein promotes tumorigenesis beyond its canonical negative effects on the p53 tumor suppressor, but these p53-independent functions remain poorly understood. Here, we show that a fraction of endogenous MDM2 is actively imported in mitochondria to control respiration and mitochondrial dynamics independently of p53. Mitochondrial MDM2 represses the transcription of NADH-dehydrogenase 6 (MT-ND6) in vitro and in vivo, impinging on respiratory complex I activity and enhancing mitochondrial ROS production. Recruitment of MDM2 to mitochondria increases during oxidative stress and hypoxia. Accordingly, mice lacking MDM2 in skeletal muscles exhibit higher MT-ND6 levels, enhanced complex I activity, and increased muscular endurance in mild hypoxic conditions. Furthermore, increased mitochondrial MDM2 levels enhance the migratory and invasive properties of cancer cells. Collectively, these data uncover a previously unsuspected function of the MDM2 oncoprotein in mitochondria that play critical roles in skeletal muscle physiology and may contribute to tumor progression.

Chromatin-bound MDM2, a new player in metabolism.

The oncoprotein MDM2 is recognized as a major negative regulator of the p53 tumor suppressor but growing evidence indicates that its oncogenic activities extend beyond p53. We show that MDM2 is recruited to chromatin independently of p53 to regulate a transcriptional program implicated in amino acid metabolism and redox homeostasis.

E4F1-mediated control of pyruvate dehydrogenase activity is essential for skin homeostasis.

The multifunctional protein E4 transcription factor 1 (E4F1) is an essential regulator of epidermal stem cell (ESC) maintenance. Here, we found that E4F1 transcriptionally regulates a metabolic program involved in pyruvate metabolism that is required to maintain skin homeostasis. E4F1 deficiency in basal keratinocytes resulted in deregulated expression of dihydrolipoamide acetyltransferase (Dlat), a gene encoding the E2 subunit of the mitochondrial pyruvate dehydrogenase (PDH) complex. Accordingly, E4f1 knock-out (KO) keratinocytes exhibited impaired PDH activity and a redirection of the glycolytic flux toward lactate production. The metabolic reprogramming of E4f1 KO keratinocytes associated with remodeling of their microenvironment and alterations of the basement membrane, led to ESC mislocalization and exhaustion of the ESC pool. ShRNA-mediated depletion of Dlat in primary keratinocytes recapitulated defects observed upon E4f1 inactivation, including increased lactate secretion, enhanced activity of extracellular matrix remodeling enzymes, and impaired clonogenic potential. Altogether, our data reveal a central role for Dlat in the metabolic program regulated by E4F1 in basal keratinocytes and illustrate the importance of PDH activity in skin homeostasis.

E4F1 controls a transcriptional program essential for pyruvate dehydrogenase activity.

The mitochondrial pyruvate dehydrogenase (PDH) complex (PDC) acts as a central metabolic node that mediates pyruvate oxidation and fuels the tricarboxylic acid cycle to meet energy demand. Here, we reveal another level of regulation of the pyruvate oxidation pathway in mammals implicating the E4 transcription factor 1 (E4F1). E4F1 controls a set of four genes [dihydrolipoamide acetlytransferase (Dlat), dihydrolipoyl dehydrogenase (Dld), mitochondrial pyruvate carrier 1 (Mpc1), and solute carrier family 25 member 19 (Slc25a19)] involved in pyruvate oxidation and reported to be individually mutated in human metabolic syndromes. E4F1 dysfunction results in 80% decrease of PDH activity and alterations of pyruvate metabolism. Genetic inactivation of murine E4f1 in striated muscles results in viable animals that show low muscle PDH activity, severe endurance defects, and chronic lactic acidemia, recapitulating some clinical symptoms described in PDC-deficient patients. These phenotypes were attenuated by pharmacological stimulation of PDH or by a ketogenic diet, two treatments used for PDH deficiencies. Taken together, these data identify E4F1 as a master regulator of the PDC.

Chromatin-Bound MDM2 Regulates Serine Metabolism and Redox Homeostasis Independently of p53.

The mouse double minute 2 (MDM2) oncoprotein is recognized as a major negative regulator of the p53 tumor suppressor, but growing evidence indicates that its oncogenic activities extend beyond p53. Here, we show that MDM2 is recruited to chromatin independently of p53 to regulate a transcriptional program implicated in amino acid metabolism and redox homeostasis. Identification of MDM2 target genes at the whole-genome level highlights an important role for ATF3/4 transcription factors in tethering MDM2 to chromatin. MDM2 recruitment to chromatin is a tightly regulated process that occurs during oxidative stress and serine/glycine deprivation and is modulated by the pyruvate kinase M2 (PKM2) metabolic enzyme. Depletion of endogenous MDM2 in p53-deficient cells impairs serine/glycine metabolism, the NAD(+)/NADH ratio, and glutathione (GSH) recycling, impacting their redox state and tumorigenic potential. Collectively, our data illustrate a previously unsuspected function of chromatin-bound MDM2 in cancer cell metabolism.