Metabolite systems profiling identifies exploitable weaknesses in retinoblastoma

Serum Metabolomics of Retinoblastoma: Assessing the Differential Serum Metabolic Signatures of Unilateral and Bilateral Patients

Retinoblastoma (Rb) is the most common pediatric eye cancer. To identify the biomarkers for early diagnosis and monitoring the progression of Rb in patients, mapping of the alterations in their metabolic profiles is essential. The present study aims at exploring the metabolic disparity in serum from Rb patients and controls using NMR-based metabolomics. A total of 72 metabolites, including carbohydrates, amino acids, and organic acids, were quantified in serum samples from 24 Rb patients and 26 controls. Distinct clusters of Rb patients and controls were obtained using the partial least-squares discriminant analysis (PLS-DA) model. Further, univariate and multivariate analyses of unilateral and bilateral Rb patients with respect to their age-matched controls depicted their distinct metabolic fingerprints. Metabolites including 2-phosphoglycerate, 4-aminobutyrate, proline, O-phosphocholine, O-phosphoethanolamine, and Sn-glycero-3-phosphocholine (Sn-GPC) showed significant perturbation in both unilateral and bilateral Rb patients. However, metabolic differences among the bilateral Rb cases were more pronounced than those in unilateral Rb cases with respect to controls. In addition to major discriminatory metabolites for Rb, unilateral and bilateral Rb cases showed specific metabolic changes, which might be the result of their differential genetic/somatic mutational backgrounds. This further suggests that the aberrant metabolic perturbation in bilateral patients signifies the severity of the disease in Rb patients. The present study demonstrated that identified serum metabolites have potential to serve as a noninvasive method for detection of Rb, discriminate bilateral from unilateral Rb patients, and aid in better understanding of the RB tumor biology.

Depleted hexokinase1 and lack of AMPKα activation favor OXPHOS-dependent energetics in retinoblastoma tumors

Lack of retinoblastoma (Rb) protein causes aggressive intraocular retinal tumors in children. Recently, Rb tumors have been shown to have a distinctly altered metabolic phenotype, such as reduced expression of glycolytic pathway proteins alongside altered pyruvate and fatty acid levels. In this study, we demonstrate that loss of hexokinase 1(HK1) in tumor cells rewires their metabolism allowing enhanced oxidative phosphorylation-dependent energy production. We show that rescuing HK1 or retinoblastoma protein 1 (RB1) in these Rb cells reduced cancer hallmarks such as proliferation, invasion, and spheroid formation and increased their sensitivity to chemotherapy drugs. Induction of HK1 was accompanied by a metabolic shift of the cells to glycolysis and a reduction in mitochondrial mass. Cytoplasmic HK1 bound Liver Kinase B1 and phosphorylated AMP-activated kinase-α (AMPKα Thr172), thereby reducing mitochondria-dependent energy production. We validated these findings in tumor samples from Rb patients compared to age-matched healthy retinae. HK1 or RB1 expression in Rb-/- cells led to a reduction in their respiratory capacity and glycolytic proton flux. HK1 overexpression reduced tumor burden in an intraocular tumor xenograft model. AMPKα activation by AICAR also enhanced the tumoricidal effects of the chemotherapeutic drug topotecan in vivo. Therefore, enhancing HK1 or AMPKα activity can reprogram cancer metabolism and sensitize Rb tumors to lower doses of existing treatments, a potential therapeutic modality for Rb.

Lipid Metabolic Reprogramming in Embryonal Neoplasms with MYCN Amplification

Tumor cells reprogram their metabolism, including glucose, glutamine, nucleotide, lipid, and amino acids to meet their enhanced energy demands, redox balance, and requirement of biosynthetic substrates for uncontrolled cell proliferation. Altered lipid metabolism in cancer provides lipids for rapid membrane biogenesis, generates the energy required for unrestricted cell proliferation, and some of the lipids act as signaling pathway mediators. In this review, we focus on the role of lipid metabolism in embryonal neoplasms with MYCN dysregulation. We specifically review lipid metabolic reactions in neuroblastoma, retinoblastoma, medulloblastoma, Wilms tumor, and rhabdomyosarcoma and the possibility of targeting lipid metabolism. Additionally, the regulation of lipid metabolism by the MYCN oncogene is discussed.

Emerging therapeutic targets for retinoblastoma

INTRODUCTION

Retinoblastoma (Rb) is an early childhood intraocular tumor of the retina and is managed by multimodal therapeutic approaches. Recent advanced targeted delivery of chemotherapeutic drugs to the eye has improved the possibility of globe salvage. However, enucleation is inevitable for advanced and recurrent Rb. The cumulative knowledge of identification of newer molecular biology tools, exosomal cargo, role of cancer stem cells (CSCs), and its microenvironment in the progression of the diseases warrants a relook at the traditional treatment protocol and explore the feasibility of targeted therapies.

AREAS COVERED

This review covers Rb pathobiology, novel molecular-targeted therapeutics, and strategies targeting Rb CSCs and provides an update on potential therapeutic targets such as second messengers and exosomal cargo.

EXPERT OPINION

The emergence of early diagnosis and multimodality treatment protocols have significantly improved the clinical outcome of children with advanced Rb; however, the problem of tumor recurrence has not yet been overcome. Improved understanding of the molecular pathways, identification, and characterization of CSCs opens up new targeted therapy approaches. The contemporary evidence from other fields shows promising evidence that combining conservative treatment modalities with targeting therapies specific for CSCs in clinical practice is essential for achieving high globe salvage rate in Rb patients.

Lack of Retinoblastoma Protein Shifts Tumor Metabolism from Glycolysis to OXPHOS and Allows the Use of Alternate Fuels

Mutations in the RB1 locus leading to a loss of functional Rb protein cause intraocular tumors, which uniquely affect children worldwide. These tumors demonstrate rapid proliferation, which has recently been shown to be associated with an altered metabolic signature. We found that retinoblastoma tumors and in-vitro models lack Hexokinase 1 (HK1) and exhibit elevated fatty acid oxidation. We show that ectopic expression of RB1 induces HK1 protein in Rb null cells, and both RB1 and HK1 can mediate a metabolic switch from OXPHOS to glycolysis with increased pyruvate levels, reduced ATP production and reduced mitochondrial mass. Further, cells lacking Rb or HK1 can flexibly utilize glutamine and fatty acids to enhance oxidative phosphorylation-dependent ATP generation, as revealed by metabolic and biochemical assays. Thus, loss of Rb and HK1 in retinoblastoma reprograms tumor metabolic circuits to enhance the glucose-independent TCA (tricarboxylic acid) cycle and the intermediate NAD+/NADH ratios, with a subsequent increase in fatty-acid derived L-carnitine to enhance mitochondrial OXPHOS for ATP production instead of glycolysis dependence. We also demonstrate that modulation of the Rb-regulated transcription factor E2F2 does not result in any of these metabolic perturbations. In conclusion, we demonstrate RB1 or HK1 as critical regulators of the cellular bioenergetic profile and identify the altered tumor metabolism as a potential therapeutic target for cancers lacking functional Rb protein.

Constraint-Based Reconstruction and Analyses of Metabolic Models: Open-Source Python Tools and Applications to Cancer

The influence of metabolism on signaling, epigenetic markers, and transcription is highly complex yet important for understanding cancer physiology. Despite the development of high-resolution multi-omics technologies, it is difficult to infer metabolic activity from these indirect measurements. Fortunately, genome-scale metabolic models and constraint-based modeling provide a systems biology framework to investigate the metabolic states and define the genotype-phenotype associations by integrations of multi-omics data. Constraint-Based Reconstruction and Analysis (COBRA) methods are used to build and simulate metabolic networks using mathematical representations of biochemical reactions, gene-protein reaction associations, and physiological and biochemical constraints. These methods have led to advancements in metabolic reconstruction, network analysis, perturbation studies as well as prediction of metabolic state. Most computational tools for performing these analyses are written for MATLAB, a proprietary software. In order to increase accessibility and handle more complex datasets and models, community efforts have started to develop similar open-source tools in Python. To date there is a comprehensive set of tools in Python to perform various flux analyses and visualizations; however, there are still missing algorithms in some key areas. This review summarizes the availability of Python software for several components of COBRA methods and their applications in cancer metabolism. These tools are evolving rapidly and should offer a readily accessible, versatile way to model the intricacies of cancer metabolism for identifying cancer-specific metabolic features that constitute potential drug targets.

Integrated Analysis of Cancer Tissue and Vitreous Humor from Retinoblastoma Eyes Reveals Unique Tumor-Specific Metabolic and Cellular Pathways in Advanced and Non-Advanced Tumors

Retinoblastoma (Rb) is a pediatric intraocular malignancy that is proposed to originate from maturing cone cell precursors in the developing retina. The molecular mechanisms underlying the biological and clinical behaviors are important to understand in order to improve the management of advanced-stage tumors. While the genetic causes of Rb are known, an integrated understanding of the gene expression and metabolic processes in tumors of human eyes is deficient. By integrating transcriptomic profiling from tumor tissues and metabolomics from tumorous eye vitreous humor samples (with healthy, age-matched pediatric retinae and vitreous samples as controls), we uncover unique functional associations between genes and metabolites. We found distinct gene expression patterns between clinically advanced and non-advanced Rb. Global metabolomic analysis of the vitreous humor of the same Rb eyes revealed distinctly altered metabolites, indicating how tumor metabolism has diverged from healthy pediatric retina. Several key enzymes that are related to cellular energy production, such as hexokinase 1, were found to be reduced in a manner corresponding to altered metabolites; notably, a reduction in pyruvate levels. Similarly, E2F2 was the most significantly elevated E2F family member in our cohort that is part of the cell cycle regulatory circuit. Ectopic expression of the wild-type RB1 gene in the Rb-null Y79 and WERI-Rb1 cells rescued hexokinase 1 expression, while E2F2 levels were repressed. In an additional set of Rb tumor samples and pediatric healthy controls, we further validated differences in the expression of HK1 and E2F2. Through an integrated omics analysis of the transcriptomics and metabolomics of Rb, we uncovered a significantly altered tumor-specific metabolic circuit that reduces its dependence on glycolytic pathways and is governed by Rb1 and HK1.

The regulatory landscape of retinoblastoma: a pathway analysis perspective

Retinoblastoma (Rb) is a rare intraocular tumour in early childhood, with an approximate incidence of 1 in 18 000 live births. Experimental studies for Rb are complex due to the challenges associated with obtaining a normal retina to contrast with diseased tissue. In this work, we reanalyse a dataset that contains normal retina samples. We identified the individual genes whose expression is different in Rb in contrast with normal tissue, determined the pathways whose global expression pattern is more distant from the global expression observed in normal tissue, and finally, we identified which transcription factors regulate the highest number of differentially expressed genes (DEGs) and proposed as transcriptional master regulators (TMRs). The enrichment of DEGs in the phototransduction and retrograde endocannabinoid signalling pathways could be associated with abnormal behaviour of the processes leading to cellular differentiation and cellular proliferation. On the other hand, the TMRs nuclear receptor subfamily 5 group A member 2 and hepatocyte nuclear factor 4 gamma are involved in hepatocyte differentiation. Therefore, the enrichment of aberrant expression in these transcription factors could suggest an abnormal retina development that could be involved in Rb origin and progression.

Leveraging genome-scale metabolic models for human health applications

Genome-scale metabolic modeling is a scalable and extensible computational method for analyzing and predicting biological function. With the ongoing improvements in computational methods and experimental capabilities, genome-scale metabolic models (GEMs) are demonstrating utility in addressing human health applications. The initial areas of highest impact are likely to be health applications where disease states involve metabolic changes. In this review, we focus on recent application of GEMs to studying cancer and the human microbiome by describing the enabling methodologies and outcomes of these studies. We conclude with proposing some areas of research that are likely to arise as a result of recent methodological advances.