Monitoring cancer prognosis, diagnosis and treatment efficacy using metabolomics and lipidomics

IntroductionCellular metabolism is altered during cancer initiation and progression, which allows cancer cells to increase anabolic synthesis, avoid apoptosis and adapt to low nutrient and oxygen availability. The metabolic nature of cancer enables patient cancer status to be monitored by metabolomics and lipidomics. Additionally, monitoring metabolic status of patients or biological models can be used to greater understand the action of anticancer therapeutics.ObjectivesDiscuss how metabolomics and lipidomics can be used to (i) identify metabolic biomarkers of cancer and (ii) understand the mechanism-of-action of anticancer therapies. Discuss considerations that can maximize the clinical value of metabolic cancer biomarkers including case–control, prognostic and longitudinal study designs.MethodsA literature search of the current relevant primary research was performed.ResultsMetabolomics and lipidomics can identify metabolic signatures that associate with cancer diagnosis, prognosis and disease progression. Discriminatory metabolites were most commonly linked to lipid or energy metabolism. Case–control studies outnumbered prognostic and longitudinal approaches. Prognostic studies were able to correlate metabolic features with future cancer risk, whereas longitudinal studies were most effective for studying cancer progression. Metabolomics and lipidomics can help to understand the mechanism-of-action of anticancer therapeutics and mechanisms of drug resistance.ConclusionMetabolomics and lipidomics can be used to identify biomarkers associated with cancer and to better understand anticancer therapies.

[1]  Guowang Xu,et al.  Serum metabolic profiling study of lung cancer using ultra high performance liquid chromatography/quadrupole time-of-flight mass spectrometry. , 2014, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[2]  Yu Bai,et al.  Comprehensive lipid profiling of plasma in patients with benign breast tumor and breast cancer reveals novel biomarkers , 2015, Analytical and Bioanalytical Chemistry.

[3]  C. Heeschen,et al.  MYC/PGC-1α Balance Determines the Metabolic Phenotype and Plasticity of Pancreatic Cancer Stem Cells. , 2015, Cell metabolism.

[4]  Eugenia G. Giannopoulou,et al.  Vitamin C selectively kills KRAS and BRAF mutant colorectal cancer cells by targeting GAPDH , 2015, Science.

[5]  Theodoros N. Arvanitis,et al.  Dynamic range and mass accuracy of wide-scan direct infusion nanoelectrospray fourier transform ion cyclotron resonance mass spectrometry-based metabolomics increased by the spectral stitching method. , 2007, Analytical chemistry.

[6]  John C Lindon,et al.  Pharmacometabonomics as an effector for personalized medicine. , 2011, Pharmacogenomics.

[7]  Robert V Farese,et al.  Cellular fatty acid metabolism and cancer. , 2013, Cell metabolism.

[8]  John L Cleveland,et al.  Targeting lactate metabolism for cancer therapeutics. , 2013, Journal of Clinical Investigation.

[9]  Y. Lotan,et al.  Bladder Cancer Biomarker Discovery Using Global Metabolomic Profiling of Urine , 2014, PloS one.

[10]  L. Cantley,et al.  Understanding the Warburg Effect: The Metabolic Requirements of Cell Proliferation , 2009, Science.

[11]  R. Weinshilboum,et al.  Metabolomics: a global biochemical approach to drug response and disease. , 2008, Annual review of pharmacology and toxicology.

[12]  H. Boeing,et al.  Higher plasma levels of lysophosphatidylcholine 18:0 are related to a lower risk of common cancers in a prospective metabolomics study , 2016, BMC Medicine.

[13]  O. Warburg.  [Origin of cancer cells]. , 1956, Oncologia.

[14]  S. Im,et al.  An NMR metabolomics approach for the diagnosis of leptomeningeal carcinomatosis in lung adenocarcinoma cancer patients , 2015, International journal of cancer.

[15]  Wun-Jae Kim,et al.  Diagnosis of bladder cancer and prediction of survival by urinary metabolomics , 2014, Oncotarget.

[16]  U. Günther,et al.  Metabolic plasticity in CLL: adaptation to the hypoxic niche , 2015, Leukemia.

[17]  A. Harris,et al.  Acetyl-CoA Synthetase 2 Promotes Acetate Utilization and Maintains Cancer Cell Growth under Metabolic Stress , 2015, Cancer cell.

[18]  Christian M. Metallo,et al.  Mitochondria as biosynthetic factories for cancer proliferation , 2015, Cancer & metabolism.

[19]  K. Williams,et al.  ToF‐SIMS as a tool for metabolic profiling small biomolecules in cancer systems , 2013 .

[20]  Fei Li,et al.  Modulation of colon cancer by nutmeg. , 2015, Journal of proteome research.

[21]  M. Gottesman.  Mechanisms of cancer drug resistance. , 2002, Annual review of medicine.

[22]  G. Morgan,et al.  Proton NMR-Based Metabolite Analyses of Archived Serial Paired Serum and Urine Samples from Myeloma Patients at Different Stages of Disease Activity Identifies Acetylcarnitine as a Novel Marker of Active Disease , 2013, PloS one.

[23]  I. Pernicova,et al.  Metformin—mode of action and clinical implications for diabetes and cancer , 2014, Nature Reviews Endocrinology.

[24]  Mark R. Trusheim,et al.  Stratified medicine: strategic and economic implications of combining drugs and clinical biomarkers , 2007, Nature Reviews Drug Discovery.

[25]  Wei Jia,et al.  Metformin suppressed the proliferation of LoVo cells and induced a time-dependent metabolic and transcriptional alteration , 2015, Scientific Reports.

[26]  B. Faubert,et al.  Metabolic Heterogeneity in Human Lung Tumors , 2016, Cell.

[27]  A. Darzi,et al.  Intraoperative Tissue Identification Using Rapid Evaporative Ionization Mass Spectrometry , 2013, Science Translational Medicine.

[28]  H. Cooper,et al.  Liquid extraction surface analysis field asymmetric waveform ion mobility spectrometry mass spectrometry for the analysis of dried blood spots. , 2015, The Analyst.

[29]  E. Gottlieb,et al.  Succinate dehydrogenase and fumarate hydratase: linking mitochondrial dysfunction and cancer , 2006, Oncogene.

[30]  James B. Mitchell,et al.  13C-MR Spectroscopic Imaging with Hyperpolarized [1-13C]pyruvate Detects Early Response to Radiotherapy in SCC Tumors and HT-29 Tumors , 2015, Clinical Cancer Research.

[31]  D. Raftery,et al.  Targeted serum metabolite profiling and sequential metabolite ratio analysis for colorectal cancer progression monitoring , 2015, Analytical and Bioanalytical Chemistry.

[32]  Z. Takáts,et al.  In vivo, in situ tissue analysis using rapid evaporative ionization mass spectrometry. , 2009, Angewandte Chemie.

[33]  M. Bousamra,et al.  Breath carbonyl compounds as biomarkers of lung cancer. , 2015, Lung cancer.

[34]  Anastasia L. Sowers,et al.  Mass Spectrometry-Based Metabolomics Identifies Longitudinal Urinary Metabolite Profiles Predictive of Radiation-Induced Cancer. , 2016, Cancer research.

[35]  F. Clavel-Chapelon,et al.  Metabolomic profiles of hepatocellular carcinoma in a European prospective cohort , 2015, BMC Medicine.

[36]  M. Hidalgo,et al.  Metabolomic evaluation of Mitomycin C and rapamycin in a personalized treatment of pancreatic cancer , 2014, Pharmacology research & perspectives.

[37]  A. Mes-Masson,et al.  A targeted analysis identifies a high frequency of BRCA1 and BRCA2 mutation carriers in women with ovarian cancer from a founder population , 2015, Journal of Ovarian Research.

[38]  J. Menéndez,et al.  Fatty acid synthase and the lipogenic phenotype in cancer pathogenesis , 2007, Nature Reviews Cancer.

[39]  Cuthbert Dukes,et al.  Origin of Cancer , 1938 .

[40]  S. Taylor-Robinson,et al.  The promise of metabolic phenotyping in gastroenterology and hepatology , 2015, Nature Reviews Gastroenterology &Hepatology.

[41]  Xue Gu,et al.  Metabolic transformation of breast cancer in a MCF-7 xenograft mouse model and inhibitory effect of volatile oil from Saussurea lappa Decne treatment , 2014, Metabolomics.

[42]  Xin Lu,et al.  Integration of Metabolomics and Transcriptomics Reveals Major Metabolic Pathways and Potential Biomarker Involved in Prostate Cancer* , 2015, Molecular & Cellular Proteomics.

[43]  M. Maes,et al.  Cognitive remission: a novel objective for the treatment of major depression? , 2016, BMC Medicine.

[44]  J. Rabinowitz,et al.  Quantitative analysis of acetyl-CoA production in hypoxic cancer cells reveals substantial contribution from acetate , 2014, Cancer & Metabolism.

[45]  L. Béress,et al.  Head and neck cancer cells and xenografts are very sensitive to palytoxin: decrease of c-jun n-terminale kinase-3 expression enhances palytoxin toxicity , 2013, Molecular Cancer.

[46]  A. Harris,et al.  Neoadjuvant Window Studies of Metformin and Biomarker Development for Drugs Targeting Cancer Metabolism. , 2015, Journal of the National Cancer Institute. Monographs.

[47]  D. Albanes,et al.  Metabolomic analysis of prostate cancer risk in a prospective cohort: The alpha‐tocopherol, beta‐carotene cancer prevention (ATBC) study , 2015, International journal of cancer.

[48]  C. Barbas,et al.  To treat or not to treat: metabolomics reveals biomarkers for treatment indication in chronic lymphocytic leukaemia patients , 2015, Oncotarget.

[49]  E. Cuyás,et al.  Oncometabolic mutation IDH1 R132H confers a metformin-hypersensitive phenotype , 2015, Oncotarget.

[50]  K. Kaluarachchi,et al.  Pharmacologic inhibition of fatty acid oxidation sensitizes human leukemia cells to apoptosis induction. , 2010, The Journal of clinical investigation.

[51]  P. Morin,et al.  Investigating a signature of temozolomide resistance in GBM cell lines using metabolomics , 2015, Journal of Neuro-Oncology.

[52]  Guangjun Nie,et al.  Enhanced anti-tumor efficacy by co-delivery of doxorubicin and paclitaxel with amphiphilic methoxy PEG-PLGA copolymer nanoparticles. , 2011, Biomaterials.

[53]  Dan Gao,et al.  Metabolomics study on the antitumor effect of marine natural compound flexibilide in HCT-116 colon cancer cell line. , 2016, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[54]  Andrey Korshunov,et al.  Analysis of the IDH1 codon 132 mutation in brain tumors , 2008, Acta Neuropathologica.

[55]  F. Prósper,et al.  Multiple Myeloma Patients Have a Specific Serum Metabolomic Profile That Changes after Achieving Complete Remission , 2013, Clinical Cancer Research.

[56]  L. Poisson,et al.  A metabolomic approach to identifying platinum resistance in ovarian cancer , 2014, Journal of Ovarian Research.

[57]  Ning Li,et al.  Assessment of the Biological Effects of a Multifunctional Nano-Drug-Carrier and Its Encapsulated Drugs. , 2015, Journal of proteome research.

[58]  Ivano Bertini,et al.  Metabolomic NMR fingerprinting to identify and predict survival of patients with metastatic colorectal cancer. , 2012, Cancer research.

[59]  R. Price,et al.  Artemether-lumefantrine treatment of uncomplicated Plasmodium falciparum malaria: a systematic review and meta-analysis of day 7 lumefantrine concentrations and therapeutic response using individual patient data , 2015, BMC Medicine.

[60]  F. Ginhoux,et al.  Anticancer immunotherapy by CTLA-4 blockade relies on the gut microbiota , 2015, Science.

[61]  Theodoros N. Arvanitis,et al.  Diagnosing relapse in children's brain tumors using metabolite profiles. , 2014, Neuro-oncology.

[62]  Ge Zhang,et al.  Halofuginone inhibits colorectal cancer growth through suppression of Akt/mTORC1 signaling and glucose metabolism , 2015, Oncotarget.

[63]  J. Ricci,et al.  Cancer metabolism: current perspectives and future directions , 2012, Cell Death and Disease.

[64]  S. Linnarsson,et al.  Rewired Metabolism in Drug-resistant Leukemia Cells , 2015, The Journal of Biological Chemistry.

[65]  N. Hay,et al.  The pentose phosphate pathway and cancer. , 2014, Trends in biochemical sciences.

[66]  T. Bathen,et al.  Increased levels of choline metabolites are an early marker of docetaxel treatment response in BRCA1-mutated mouse mammary tumors: an assessment by ex vivo proton magnetic resonance spectroscopy , 2015, Journal of Translational Medicine.

[67]  L. Qiu,et al.  Lipid profiling for early diagnosis and progression of colorectal cancer using direct-infusion electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry. , 2013, Rapid communications in mass spectrometry : RCM.

[68]  R. Deberardinis,et al.  Metabolic pathways promoting cancer cell survival and growth , 2015, Nature Cell Biology.

[69]  A. McKenna,et al.  Widespread genetic heterogeneity in multiple myeloma: implications for targeted therapy. , 2014, Cancer cell.

[70]  J. A. Murray,et al.  Combined Bezafibrate and Medroxyprogesterone Acetate: Potential Novel Therapy for Acute Myeloid Leukaemia , 2009, PloS one.

[71]  Mikko I. Kettunen,et al.  Magnetic resonance imaging of tumor glycolysis using hyperpolarized 13C-labeled glucose , 2013, Nature Medicine.

[72]  H. Oberoi,et al.  Therapeutic and Nutraceutical Potential of Bioactive Compounds Extracted from Fruit Residues , 2015, Critical reviews in food science and nutrition.

[73]  Martin E. Fernandez-Zapico,et al.  Faculty Opinions recommendation of Elevation of circulating branched-chain amino acids is an early event in human pancreatic adenocarcinoma development. , 2015 .

[74]  J. Jara,et al.  Metformin and cancer: Between the bioenergetic disturbances and the antifolate activity. , 2015, Pharmacological research.

[75]  Bin Zhou,et al.  ¹H NMR-based metabolic profiling of human rectal cancer tissue , 2013, Molecular Cancer.

[76]  W. Hahn,et al.  Fatty acid synthase: a metabolic enzyme and candidate oncogene in prostate cancer. , 2009, Journal of the National Cancer Institute.

[77]  M. Haigis,et al.  Mitochondria and Cancer , 2016, Cell.

[78]  C. Barbas,et al.  Metabolomics in cancer biomarker discovery: current trends and future perspectives. , 2014, Journal of pharmaceutical and biomedical analysis.

[79]  T. Ashburn,et al.  Drug repositioning: identifying and developing new uses for existing drugs , 2004, Nature Reviews Drug Discovery.

[80]  D. Trede,et al.  Spatial Segmentation of MALDI FT-ICR MSI Data: A Powerful Tool to Explore the Head and Neck Tumor In Situ Lipidome , 2014, Journal of The American Society for Mass Spectrometry.

[81]  C. Thompson,et al.  Glutamine addiction: a new therapeutic target in cancer. , 2010, Trends in biochemical sciences.

[82]  N. Habermann,et al.  Aspirin Reduces Plasma Concentrations of the Oncometabolite 2-Hydroxyglutarate: Results of a Randomized, Double-Blind, Crossover Trial , 2015, Cancer Epidemiology, Biomarkers & Prevention.

[83]  M. Viant,et al.  Drug Redeployment to Kill Leukemia and Lymphoma Cells by Disrupting SCD1-Mediated Synthesis of Monounsaturated Fatty Acids. , 2015, Cancer research.

[84]  Wei Jia,et al.  The influence of gut microbiota on drug metabolism and toxicity , 2016, Expert opinion on drug metabolism & toxicology.

[85]  Yun Yen,et al.  Lowered circulating aspartate is a metabolic feature of human breast cancer , 2015, Oncotarget.

[86]  E. White,et al.  Hypoxic and Ras-transformed cells support growth by scavenging unsaturated fatty acids from lysophospholipids , 2013, Proceedings of the National Academy of Sciences.

[87]  V. Bae-Jump,et al.  Antiproliferative and metabolic effects of metformin in a preoperative window clinical trial for endometrial cancer , 2014, Cancer medicine.

[88]  J. W. Allwood,et al.  Optimization of parameters for the quantitative surface-enhanced Raman scattering detection of mephedrone using a fractional factorial design and a portable Raman spectrometer. , 2013, Analytical chemistry.

[89]  A. Kimmelman,et al.  Metabolic Dependencies in RAS-Driven Cancers , 2015, Clinical Cancer Research.

[90]  António S. Barros,et al.  NMR metabolomics of human lung tumours reveals distinct metabolic signatures for adenocarcinoma and squamous cell carcinoma. , 2015, Carcinogenesis.

[91]  T. Haferlach,et al.  IDH1 mutations are detected in 6.6% of 1414 AML patients and are associated with intermediate risk karyotype and unfavorable prognosis in adults younger than 60 years and unmutated NPM1 status. , 2010, Blood.

[92]  N. Urban,et al.  Identification of novel candidate plasma metabolite biomarkers for distinguishing serous ovarian carcinoma and benign serous ovarian tumors. , 2016, Gynecologic oncology.

[93]  H. Dienemann,et al.  Non-small cell lung cancer is characterized by dramatic changes in phospholipid profiles , 2015, International journal of cancer.

[94]  D. Wishart.  Is Cancer a Genetic Disease or a Metabolic Disease? , 2015, EBioMedicine.

[95]  E. Jobard,et al.  A serum metabolomic fingerprint of bevacizumab and temsirolimus combination as first-line treatment of metastatic renal cell carcinoma , 2015, British Journal of Cancer.

[96]  John C. Lindon,et al.  Metabonomics Techniques and Applications to Pharmaceutical Research & Development , 2006, Pharmaceutical Research.

[97]  R. Deberardinis,et al.  Beyond aerobic glycolysis: Transformed cells can engage in glutamine metabolism that exceeds the requirement for protein and nucleotide synthesis , 2007, Proceedings of the National Academy of Sciences.

[98]  N. Malats,et al.  Searching for urine biomarkers of bladder cancer recurrence using a liquid chromatography-mass spectrometry and capillary electrophoresis-mass spectrometry metabolomics approach. , 2013, Journal of chromatography. A.

[99]  Alexander G. Gray,et al.  Feasibility of detecting prostate cancer by ultraperformance liquid chromatography-mass spectrometry serum metabolomics. , 2014, Journal of proteome research.

[100]  Xiaohui Lin,et al.  Metabolomics Identifies Biomarker Pattern for Early Diagnosis of Hepatocellular Carcinoma: from Diethylnitrosamine Treated Rats to Patients , 2015, Scientific Reports.