Pathological implications of metabolic reprogramming and its therapeutic potential in medulloblastoma

Abstract

Tumor-specific alterations in metabolism have been recognized to sustain the production of ATP and macromolecules needed for cell growth, division and survival in many cancer types. However, metabolic heterogeneity poses a challenge for the establishment of effective anticancer therapies that exploit metabolic vulnerabilities. Medulloblastoma (MB) is one of the most heterogeneous malignant pediatric brain tumors, divided into four molecular subgroups (Wingless, Sonic Hedgehog, Group 3 and Group 4). Recent progresses in genomics, single-cell sequencing, and novel tumor models have updated the classification and stratification of MB, highlighting the complex intratumoral cellular diversity of this cancer. In this review, we emphasize the mechanisms through which MB cells rewire their metabolism and energy production networks to support and empower rapid growth, survival under stressful conditions, invasion, metastasis, and resistance to therapy. Additionally, we discuss the potential clinical benefits of currently available drugs that could target energy metabolism to suppress MB progression and increase the efficacy of the current MB therapies.

Keywords: OXPHOS (oxidative phosphorylation); ROS; glutamine/glutamate (GABA) cycle; metabolism; warburg effect.

FIGURE 1

Intrinsic and extrinsic factors affecting metabolic changes in MB subgroups (WNT, SHH, Group3, Group4). Tumor intrinsic factors include heterogeneous oncogenic signaling and/or genetic alterations in metabolic enzymes that modulate gene expression through a variety of mechanisms such as signal transduction and epigenetic reprogramming. Tumor extrinsic factors consist of microenvironmental availability of nutrients such as glutamine or amino acids, oxygen and changes in extracellular pH. Alterations in metabolism influence glycolysis, lipogenesis, OXPHOS, oxygen reactive species (ROS) production, glutamine-dependent signaling and tumor heterogeneity, giving rise to metabolic adaptations. Figure is created in “BioRender.com”.

FIGURE 2

Schematic representation of MYC-dependent metabolic reprogramming in MB. MYC overexpression or amplification (MYC^high) drives metabolic reprogramming, leading to increased survival and therapy resistance. MYC-dependent alterations lead to enhanced aerobic glycolysis (i.e., Warburg effect) by a multiple-layered regulation. Activation of MYC stimulates glucose uptake by increasing transcription levels of glucose transporter GLUT1. MYC-dependent upregulation of hexokinase 2 (HKII) and pyruvate dehydrogenase kinase 1 (PDK1) fuels glucose flux within the cell. MYC highly contributes to extracellular acidification by acting on lactate synthesis and secretion through lactate dehydrogenase A (LDHA) and monocarboxylate transporter 1 (MCT1) expression, thus influencing MB microenvironment. Pharmacological targeting of MYC-dependent key metabolic reactions could be effective towards high-risk MYC-driven MB. Figure is created in “BioRender.com”.

FIGURE 3

Schematic representation of the impact of hypoxia-associated metabolic adaptation in MB. Hypoxia is a major component of the tumor microenvironment that shapes tumor heterogeneity; the levels of oxygen in cancer cells decrease with increasing distance from the blood vessels. In hypoxic MB cells, hypoxia-inducible factor 1 alpha (HIF1α) supports the Warburg effect by upregulating the expression of genes involved in the glycolytic pathway, such as GLUT1, carbonic anhydrase IX (CAIX) and pyruvate dehydrogenase kinase 1 (PDK1). The use of PDK1 inhibitor OSU03012 induces mitochondrial-dependent apoptosis in MB. Moreover, hypoxic conditions were found to trigger upregulation of NOTCH, which correlates with a poor prognosis in MB. A connection between HIF1α and NOTCH signaling is also found, driving stemness and cancer stem cells (CSCs) expansion. Finally, hypoxia upregulates CD133 (staminal marker) expression in MB cells and contributes to therapy resistance (after both etoposide (Eto) and radiotherapy (X-ray) treatments) by attenuating DNA damage signaling. Figure is created in “BioRender.com”.

FIGURE 4

MB subgroup-specific alterations of metabolic pathways. Schematic representation of both metabolic pathways and genes that are found upregulated in MB subgroups. Metabolic inhibitors currently in preclinical (black) and clinical (red) development for oncology applications are listed in this scheme. Figure is created in “BioRender.com”.