Zusammenfassung
Metabolomik, die neueste unter den Omik-Wissenschaften, die auch Genomik, Transkriptomik und Proteomik umfassen, ist zu einer zuverlässigen Hochdurchsatztechnologie gereift. Die Kombination von Gaschromatographie mit Flugzeitmassenspektrometrie (GC-TOFMS) stellt ein geeignetes Verfahren zur Analyse des zentralen Metabolismus in frisch gefrorenen Tumorgewebeproben dar. Bioinformatische Methoden, u. a. das von uns entwickelte PROFILE-Clustering, erlauben eine integrierte Analyse und schnelle Interpretation von Metabolomikdaten im Kontext enzymatischer Reaktionen und Stoffwechselwege. Die hier vorgestellte Metabolomanalysen dreier solider Tumortypen zusammen mit den Ergebnissen anderer Autoren bestätigen die Eignung von Metaboliten als Biomarker und eröffnen verschiedene Möglichkeiten für die Translation in die Klinik.
Abstract
Metabolomics, the newest of the omics sciences that also include genomics, transcriptomics and proteomics, has matured into a reliable high-throughput technology. Gas chromatography combined with time-of-flight mass spectrometry (GC-TOFMS) is a suitable method to analyze the central metabolism in fresh frozen tumor tissue samples. Bioinformatics methods, including the PROFILE clustering developed by us, permit integrated analysis and fast interpretation of metabolomics data in the context of enzymatic reactions and metabolic pathways. The metabolome analyses of three solid tumor types presented here, together with the results of other authors, show that metabolites are suitable as biomarkers and provide diverse options for translation into the clinical setting.
Literatur
Andronesi OC, Loebel F, Bogner W et al (2016) Treatment response assessment in idh-mutant glioma patients by noninvasive 3d functional spectroscopic mapping of 2‑hydroxyglutarate. Clin Cancer Res 22:1632–1641
Budczies J (2015) Metabolomanalyse solider Tumore: Beiträge zur Bioinformatik und translationalen Tumorforschung. Habilitationsschrift. http://www.diss.fu-berlin.de/diss/receive/FUDISS_thesis_000000100842. Zugegriffen: 9. Aug 2016
Budczies J, Denkert C (2016) Tissue-based metabolomics to analyze the breast cancer metabolome. In: Cramer T, Schmitt C (Hrsg) Metabolism in cancer. Springer, Heidelberg
Budczies J, Brockmöller SF, Müller BM et al (2013) Comparative metabolomics of estrogen receptor positive and estrogen receptor negative breast cancer: alterations in glutamine and beta-alanine metabolism. J Proteomics 94:279–288
Budczies J, Denkert C, Müller BM et al (2010) Metatarget – extracting key enzymes of metabolic regulation from high-throughput metabolomics data using KEGG reaction information. German Conference on Bioinformatics 2010., S 103–112
Budczies J, Denkert C, Müller BM et al (2012) Remodeling of central metabolism in invasive breast cancer compared to normal breast tissue – a GC-TOFMS based metabolomics study. BMC Genomics 13:334
Budczies J, Kosztyla D, von Törne C et al (2014) Cancerclass: an R package for development and validation of diagnostic tests from high-dimensional molecular data. J Stat Softw 59:1–19
Budczies J, Pfitzner BM, Györffy B et al (2015) Glutamate enrichment as new diagnostic opportunity in breast cancer. Int J Cancer 136:1619–1628
Chaturvedi A, Araujo Cruz MM, Jyotsana N et al (2016) Enantiomer-specific and paracrine leukemogenicity of mutant idh metabolite 2‑hydroxyglutarate. Leukemia. doi:10.1038/leu.2016.71
Denkert C, Budczies J, Kind T et al (2006) Mass spectrometry-based metabolic profiling reveals different metabolite patterns in invasive ovarian carcinomas and ovarian borderline tumors. Cancer Res 66:10795–10804
Denkert C, Budczies J, Weichert W et al (2008) Metabolite profiling of human colon carcinoma – deregulation of TCA cycle and amino acid turnover. Mol Cancer 7:72
Fathi AT, Sadrzadeh H, Comander AH et al (2014) Isocitrate dehydrogenase 1 (IDH1) mutation in breast adenocarcinoma is associated with elevated levels of serum and urine 2‑hydroxyglutarate. Oncologist 19:602–607
Gross MI, Demo SD, Dennison JB et al (2014) Antitumor activity of the glutaminase inhibitor CB-839 in triple-negative breast cancer. Mol Cancer Ther 13:890–901
Kelly AD, Breitkopf SB, Yuan M et al (2011) Metabolomic profiling from formalin-fixed, paraffin-embedded tumor tissue using targeted LC-MS/MS: application in sarcoma. PLOS ONE 6:e25357
Kroemer G, Pouyssegur J (2008) Tumor cell metabolism: cancer’s Achilles’ heel. Cancer Cell 13:472–482
Mihály Z, Kormos M, Lánczky A et al (2013) A meta-analysis of gene expression-based biomarkers predicting outcome after tamoxifen treatment in breast cancer. Breast Cancer Res Treat 140:219–232
Morin A, Letouzé E, Gimenez-Roqueplo A et al (2014) Oncometabolites-driven tumorigenesis: from genetics to targeted therapy. Int J Cancer 135:2237–2248
Robinson MM, McBryant SJ, Tsukamoto T et al (2007) Novel mechanism of inhibition of rat kidney-type glutaminase by bis-2-(5-phenylacetamido-1,2,4-thiadiazol-2-yl)ethyl sulfide (BPTES). Biochem J 406:407–414
Schulze A, Harris AL (2012) How cancer metabolism is tuned for proliferation and vulnerable to disruption. Nature 491:364–373
Shulaev V (2006) Metabolomics technology and bioinformatics. Brief Bioinform 7:128–139
Sreekumar A, Poisson LM, Rajendiran TM et al (2009) Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature 457:910–914
Tang X, Lin C, Spasojevic I et al (2014) A joint analysis of metabolomics and genetics of breast cancer. Breast Cancer Res 16:415
Tennant DA, Durán RV, Gottlieb E (2010) Targeting metabolic transformation for cancer therapy. Nat Rev Cancer 10:267–277
Tennant DA, Durán RV, Boulahbel H et al (2009) Metabolic transformation in cancer. Carcinogenesis 30:1269–1280
Terunuma A, Putluri N, Mishra P et al (2014) Myc-driven accumulation of 2‑hydroxyglutarate is associated with breast cancer prognosis. J Clin Invest 124:398–412
Vander Heiden MG, Cantley LC, Thompson CB (2009) Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science 324:1029–1033
Wang J, Erickson JW, Fuji R et al (2010) Targeting mitochondrial glutaminase activity inhibits oncogenic transformation. Cancer Cell 18:207–219
Wishart DS, Jewison T, Guo AC et al (2013) HMDB 3.0 – the human metabolome database in 2013. Nucleic Acids Res 41:D801–D807
Wojakowska A, Marczak Ł, Jelonek K et al (2015) An optimized method of metabolite extraction from formalin-fixed paraffin-embedded tissue for GC-MS analysis. PLOS ONE 10:e0136902
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Interessenkonflikt
J. Budczies gibt an, dass kein Interessenkonflikt besteht.
Dieser Beitrag beinhaltet keine vom Autor durchgeführten Studien an Menschen oder Tieren.
The supplement containing this article is not sponsored by industry.
Rights and permissions
About this article
Cite this article
Budczies, J. Metabolomanalyse solider Tumoren. Pathologe 37 (Suppl 2), 204–209 (2016). https://doi.org/10.1007/s00292-016-0217-1
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00292-016-0217-1