To metabolomics and beyond: a technological portfolio to investigate cancer metabolism

Abstract

Tumour cells have exquisite flexibility in reprogramming their metabolism in order to support tumour initiation, progression, metastasis and resistance to therapies. These reprogrammed activities include a complete rewiring of the bioenergetic, biosynthetic and redox status to sustain the increased energetic demand of the cells. Over the last decades, the cancer metabolism field has seen an explosion of new biochemical technologies giving more tools than ever before to navigate this complexity. Within a cell or a tissue, the metabolites constitute the direct signature of the molecular phenotype and thus their profiling has concrete clinical applications in oncology. Metabolomics and fluxomics, are key technological approaches that mainly revolutionized the field enabling researchers to have both a qualitative and mechanistic model of the biochemical activities in cancer. Furthermore, the upgrade from bulk to single-cell analysis technologies provided unprecedented opportunity to investigate cancer biology at cellular resolution allowing an in depth quantitative analysis of complex and heterogenous diseases. More recently, the advent of functional genomic screening allowed the identification of molecular pathways, cellular processes, biomarkers and novel therapeutic targets that in concert with other technologies allow patient stratification and identification of new treatment regimens. This review is intended to be a guide for researchers to cancer metabolism, highlighting current and emerging technologies, emphasizing advantages, disadvantages and applications with the potential of leading the development of innovative anti-cancer therapies.

Fig. 1

Timeline of the milestone events for cancer metabolism. The first mass spectrum of a molecule was measured by Joseph J. Thomson in 1910. In 1931 Otto H. Warburg won the Nobel Prize in Physiology or Medicine for characterizing the respiratory enzyme. In 1938 Isidor I. Rabi detected the Nuclear magnetic resonance (NMR) for the first time in a beam of lithium chloride thus developing the methodology and further expanded in 1946 by Felix Bloch and Edward M. Purcell for use on liquids and solids. Gas chromatography (GC)-MS was described in 1959 and Liquid chromatography (LC)-MS was introduced in 1974. The discovery of oncogenes and tumour suppressor genes dates back to the 1980s. In 1994 Tsutomu Nomizu and colleagues realized the first single cells MS experiment, while in 1998 Steven Oliver firstly introduced the concept of metabolomics. 2004 is the year of Next-generation sequencing (NGS), 2006 of the Seahorse real-time cell metabolic analyser, 2007 of the first prototype of Cytometry by Time-of-flight (CyTOF) and of the first version of The Human metabolome database (HMDB). In 2009 there was the development of Single-cell RNA sequencing (scRNAseq), in 2016 of Single-cell metabolomics (SCM) and in 2017 of the In situ metabolomics. The first genome-wide functional screening was performed in 2014 and in 2020 Emmanuelle Charpentier and Jennifer Doudna were awarded the Nobel Prize in Chemistry for discovering the CRISPR/Cas9 system. In 2020 the flow-cytometry-based technologies Met-flow and SCENITH have been proposed. In 2022 the deregulation of cellular metabolism was eventually recognized core hallmark of cancer by Douglas Hanahan. This figure was created with Biorender.com

Fig. 2

a Mass spectrometry (MS)-metabolomic workflow. 1. Samples preparation consists of metabolism quenching and metabolites extraction. 2. Metabolites may need a separation step with Gas chromatography (GC), Liquid chromatography (LC), Capillary electrophoresis (CE) or can be directly ionized in the Direct infusion (DI) and in the Mass spectrometry imaging (MSI). 3. Different ionization techniques can be employed: Electron impact ionization (EI), Chemical ionization (CI), Atmospheric pressure chemical ionization (APCI), Electrospray ionization (ESI), Matrix-assisted laser desorption ionization (MALDI) and Direct real-time analysis (DART). 4. Single (MS) or tandem (MS/MS) mass analysers can be alternatively employed to separate ions according to their m/z: Quadrupole (Q), Quadrupole ion trap (QIT), Time-of-flight analyser (TOF), Fourier transform ion cyclotron resonance (FTICR), Orbitrap (OT). 5. Data processing includes conversion of m/z values, detection, filtering, normalization and identification. b Schematic depicting the most suitable techniques to separate metabolites with distinct polarity. This figure was created with Biorender.com

Fig. 3

a Fluxomics is the omics approach that gets closer to the phenotype. b Experimental workflow of a standard Metabolic flux analysis (MFA) experiment. The first step is the experimental design and the definition of the best tracer and metabolic model by in silico analysis. Cells or tissues are incubated with the tracer and samples are analysed by either MS or NMR. The isotope tracing is analysed considering the metabolites external rates and the statistical value. The results are thus integrated into the original metabolic model. This figure was created with Biorender.com

Fig. 4

a Key metabolic pathways governing cancer cell growth that can be measured by Extracellular flux analysis (EFA). b Glycolysis stress assay is performed by serial injections of Glucose, Oligomycin and 2-deoxyglucose (2-DG) to get as a read out glycolysis, glycolytic capacity, the glycolytic reserve and non-glycolytic acidification measurements. ECAR stands for extracellular acidification rate. c The Glycolytic rate assay reports multiple key parameters, such as basal glycolysis, compensatory glycolysis achieved by shutting down mitochondrial respiration with rotenone and antimycin A. Proton efflux rate (PER) is a quantitative measure of protons extruded into the extracellular medium during glycolysis. d In the Cell mito stress test, mitochondrial respiration is measured by quantifying the Oxygen consumption rate (OCR). Cells are sequentially exposed to oligomycin, Carbonyl cyanide 4-(trifluoromethoxy) phenylhydrazone (FCCP) and rotenone and antimycin A thus allowing the measurement of the basal and maximal respiration and spare respiratory capacity. e The Substrate oxidation stress test measures the contribution of Long-chain fatty acids (LCFAs), glucose/pyruvate and glutamine as primary substrates that fuel mitochondrial metabolism by using specific inhibitors in combination with a standard Cell mito stress assay. Etomoxir inhibits the Carnitine palmitoyl transferase 1a (CPT1a), UK5099 blocks glucose and/or pyruvate through inhibition of the Mitochondrial pyruvate carrier (MPC) and BPTES inhibits glutamine through Glutaminase-1 (GLS-1). This figure was created with Biorender.com

Fig. 5

Global overview of the cutting-edge techniques available to investigate the Tumour microenvironment (TME). a Single-cell RNA-sequencing (scRNAseq) representative workflow: individual cells are isolated, lysed and barcoded before retro-transcription, library amplification and sequencing. b Single-cell metabolomics (SCM) includes single cells isolation, sample processing, quenching of metabolism and metabolomics. c In the single-cell energetic metabolism by profiling translation inhibition (SCENITH) the sample is divided into 4 and either left untreated or treated with 2-deoxyglucose (2-DG), oligomycin and both inhibitors. The addition of puromycin allows protein synthesis quantification coupled with flow-cytometry phenotyping. d In Cytometry by Time-of-flight (CyTOF), the cells are labelled using stable heavy metals, nebulized, and vaporized to form ion clouds and analysed by a Time-of-flight (TOF)-MS. e With the In situ dehydrogenase activity assay, the activity of G6PD, GAPDH, LDH, IDH and SDH is coupled with immune-staining to distinguish single cells directly on a tissue slide. This figure was created with Biorender.com

Fig. 6

General workflow for screening using CRISPR/Cas9 libraries. The guide RNA (gRNA) library is synthetized after in silico optimization and cloned into plasmids for the amplification. A library of lentiviruses is then produced and used to infect the cells harbouring or not the Cas9 enzyme. A positive or a negative selection can be applied to identify specific phenotypes and next-generation sequencing is used to determine which genes are disrupted and which are not. This figure was created with Biorender.com