615
Views
12
CrossRef citations to date
0
Altmetric
Review

Advances in mass spectrometry-based cancer research and analysis: from cancer proteomics to clinical diagnostics

, &
Pages 593-607 | Received 11 Feb 2016, Accepted 21 Apr 2016, Published online: 06 May 2016

References

  • Cox J, Mann M. Quantitative, high-resolution proteomics for data-driven systems biology. Annu Rev Biochem. 2011;80:273–299.
  • Altelaar AF, Heck AJ. Trends in ultrasensitive proteomics. Curr Opin Chem Biol. 2012;16(1–2):206–213.
  • Smith LM, Kelleher NL. Proteoform: a single term describing protein complexity. Nat Methods. 2013;10(3):186–187.
  • Motoyama A, Yates JR 3rd. Multidimensional LC separations in shotgun proteomics. Anal Chem. 2008;80(19):7187–7193.
  • Ntai I, LeDuc RD, Fellers RT, et al. Integrated bottom-up and top-down proteomics of patient-derived breast Tumor Xenografts. Mol Cell Proteomics: MCP. 2016;15(1):45–56.
  • Timms JF, Cutillas PR. Overview of quantitative LC-MS techniques for proteomics and activitomics. Methods Mol Biol. 2010;658:19–45.
  • Silva JC, Denny R, Dorschel CA, et al. Quantitative proteomic analysis by accurate mass retention time pairs. Anal Chem. 2005;77(7):2187–2200.
  • Thompson A, Schafer J, Kuhn K, et al. Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS. Anal Chem. 2003;75(8):1895–1904.
  • Ross PL, Huang YN, Marchese JN, et al. Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol Cell Proteomics: MCP. 2004;3(12):1154–1169.
  • Hsu JL, Huang SY, Chow NH, et al. Stable-isotope dimethyl labeling for quantitative proteomics. Anal Chem. 2003;75(24):6843–6852.
  • Ong SE, Blagoev B, Kratchmarova I, et al. Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol Cell Proteomics: MCP. 2002;1(5):376–386.
  • Geiger T, Cox J, Ostasiewicz P, et al. Super-SILAC mix for quantitative proteomics of human tumor tissue. Nat Methods. 2010;7(5):383–385.
  • Iglesias-Gato D, Wikstrom P, Tyanova S, et al. The proteome of primary prostate cancer. Eur Urol. 2015;69(5):942–952.
  • Wisniewski JR, Dus-Szachniewicz K, Ostasiewicz P, et al. Absolute proteome analysis of colorectal mucosa, adenoma, and cancer reveals drastic changes in fatty acid metabolism and plasma membrane transporters. J Proteome Res. 2015;14(9):4005–4018.
  • Bischoff R, Permentier H, Guryev V, et al. Genomic variability and protein species - improving sequence coverage for proteogenomics. J Proteomics. 2015;134:25–36.
  • Menschaert G, Fenyo D. Proteogenomics from a bioinformatics angle: A growing field. Mass Spectrom Rev. 2015 Dec 15. doi:10.1002/mas.21483.
  • Zhang B, Wang J, Wang X, et al. Proteogenomic characterization of human colon and rectal cancer. Nature. 2014;513(7518):382–387.
  • Jmeian Y, El Rassi Z. Liquid-phase-based separation systems for depletion, prefractionation and enrichment of proteins in biological fluids for in-depth proteomics analysis. Electrophoresis. 2009;30(1):249–261.
  • Righetti PG, Boschetti E, Lomas L, et al. Protein equalizer technology: the quest for a “democratic proteome”. Proteomics. 2006;6(14):3980–3992.
  • Yang ZP, Hancock WS. Monitoring glycosylation pattern changes of glycoproteins using multi-lectin affinity chromatography. J Chromatogr. 2005;1070(1–2):57–64.
  • Engholm-Keller K, Larsen MR. Titanium dioxide as chemo-affinity chromatographic sorbent of biomolecular compounds–applications in acidic modification-specific proteomics. J Proteomics. 2011;75(2):317–328.
  • Selvaraju S, Rassi ZE. Liquid-phase-based separation systems for depletion, prefractionation and enrichment of proteins in biological fluids and matrices for in-depth proteomics analysis–an update covering the period 2008-2011. Electrophoresis. 2012;33(1):74–88.
  • Puangpila C, Mayadunne E, El Rassi Z. Liquid phase based separation systems for depletion, prefractionation, and enrichment of proteins in biological fluids and matrices for in-depth proteomics analysis-An update covering the period 2011-2014. Electrophoresis. 2015;36(1):238–252.
  • Britton D, Zen Y, Quaglia A, et al. Quantification of pancreatic cancer proteome and phosphorylome: indicates molecular events likely contributing to cancer and activity of drug targets. PLoS One. 2014;9(3):e90948.
  • Wilkes EH, Terfve C, Gribben JG, et al. Empirical inference of circuitry and plasticity in a kinase signaling network. Proc Natl Acad Sci U S A. 2015;112(25):7719–7724.
  • Zhao J, Simeone DM, Heidt D, et al. Comparative serum glycoproteomics using lectin selected sialic acid glycoproteins with mass spectrometric analysis: application to pancreatic cancer serum. J Proteome Res. 2006;5(7):1792–1802.
  • Zeng X, Hood BL, Sun M, et al. Lung cancer serum biomarker discovery using glycoprotein capture and liquid chromatography mass spectrometry. J Proteome Res. 2010;9(12):6440–6449.
  • Chen J, Xi J, Tian Y, et al. Identification, prioritization, and evaluation of glycoproteins for aggressive prostate cancer using quantitative glycoproteomics and antibody-based assays on tissue specimens. Proteomics. 2013;13(15):2268–2277.
  • Deeb SJ, Cox J, Schmidt-Supprian M, et al. N-linked glycosylation enrichment for in-depth cell surface proteomics of diffuse large B-cell lymphoma subtypes. Mol Cell Proteomics: MCP. 2014;13(1):240–251.
  • Findeisen P, Neumaier M. Functional protease profiling for diagnosis of malignant disease. Proteomics Clin Appl. 2012;6(1–2):60–78.
  • Hunt DF, Henderson RA, Shabanowitz J, et al. Characterization of peptides bound to the class I MHC molecule HLA-A2.1 by mass spectrometry. Science. 1992;255(5049):1261–1263.
  • Caron E, Kowalewski DJ, Chiek Koh C, et al. Analysis of Major Histocompatibility Complex (MHC) immunopeptidomes using mass spectrometry. Mol Cell Proteomics: MCP. 2015;14(12):3105–3117.
  • Berlin C, Kowalewski DJ, Schuster H, et al. Mapping the HLA ligandome landscape of acute myeloid leukemia: a targeted approach toward peptide-based immunotherapy. Leukemia. 2015;29(3):647–659.
  • Couzin-Frankel J. Breakthrough of the year 2013. Cancer immunother Sci. 2013;342(6165):1432–1433.
  • Gika HG, Wilson ID, Theodoridis GA. LC-MS-based holistic metabolic profiling. Problems, limitations, advantages, and future perspectives. J Chromatogr B Analyt Technol Biomed Life Sci. 2014;966:1–6.
  • Sreekumar A, Poisson LM, Rajendiran TM, et al. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature. 2009;457(7231):910–914.
  • Ritchie SA, Akita H, Takemasa I, et al. Metabolic system alterations in pancreatic cancer patient serum: potential for early detection. BMC Cancer. 2013;13:416.
  • Losman JA, Looper RE, Koivunen P, et al. (R)-2-hydroxyglutarate is sufficient to promote leukemogenesis and its effects are reversible. Science. 2013;339(6127):1621–1625.
  • Wang H, Shi T, Qian WJ, et al. The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification. Expert Rev Proteomics. 2016;13(1):99–114.
  • Flatley B, Malone P, Cramer R. MALDI mass spectrometry in prostate cancer biomarker discovery. Biochim Biophys Acta. 2014;1844(5):940–949.
  • Indovina P, Marcelli E, Pentimalli F, et al. Mass spectrometry-based proteomics: the road to lung cancer biomarker discovery. Mass Spectrom Rev. 2013;32(2):129–142.
  • Timms JF, Menon U, Devetyarov D, et al. Early detection of ovarian cancer in samples Pre-diagnosis using CA125 and MALDI-MS peaks. Cancer Genomics Proteomics. 2011;8(6):289–305.
  • Tiss A, Timms JF, Smith C, et al. Highly accurate detection of ovarian cancer using CA125 but limited improvement with serum matrix-assisted laser desorption/ionization time-of-flight mass spectrometry profiling. Int J Gyn Cancer: Off J Int Gyn Cancer Soc. 2010;20(9):1518–1524.
  • Ludwig JA, Weinstein JN. Biomarkers in cancer staging, prognosis and treatment selection. Nat Rev Cancer. 2005;5(11):845–856.
  • Banks RE, Stanley AJ, Cairns DA, et al. Influences of blood sample processing on low-molecular-weight proteome identified by surface-enhanced laser desorption/ionization mass spectrometry. Clin Chem. 2005;51(9):1637–1649.
  • Findeisen P, Sismanidis D, Riedl M, et al. Preanalytical impact of sample handling on proteome profiling experiments with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Clin Chem. 2005;51(12):2409–2411.
  • Diamandis EP. Serum proteomic profiling by matrix-assisted laser desorption-ionization time-of-flight mass spectrometry for cancer diagnosis: next steps. Cancer Res. 2006;66(11):5540–5541.
  • Timms JF, Arslan-Low E, Gentry-Maharaj A, et al. Preanalytic influence of sample handling on SELDI-TOF serum protein profiles. Clin Chem. 2007;53(4):645–656.
  • Tuck MK, Chan DW, Chia D, et al. Standard operating procedures for serum and plasma collection: early detection research network consensus statement standard operating procedure integration working group. J Proteome Res. 2009;8(1):113–117.
  • Tiss A, Smith C, Camuzeaux S, et al. Serum peptide profiling using MALDI mass spectrometry: avoiding the pitfalls of coated magnetic beads using well-established ZipTip technology. Proteomics. 2007;7(Suppl 1):77–89.
  • Mustafa D, Kros JM, Luider T. Combining laser capture microdissection and proteomics techniques. Methods Mol Biol. 2008;428:159–178.
  • Gustafsson OJ, Arentz G, Hoffmann P. Proteomic developments in the analysis of formalin-fixed tissue. Biochim Biophys Acta. 2015;1854(6):559–580.
  • Tonack S, Jenkinson C, Cox T, et al. iTRAQ reveals candidate pancreatic cancer serum biomarkers: influence of obstructive jaundice on their performance. Br J Cancer. 2013;108(9):1846–1853.
  • Tonry CL, Doherty D, O’Shea C, et al. Discovery and longitudinal evaluation of candidate protein biomarkers for disease recurrence in prostate cancer. J Proteome Res. 2015;14(7):2769–2783.
  • Jenkinson C, Elliott V, Evans A, et al. Decreased serum thrombospondin-1 levels in pancreatic cancer patients up to 24 months prior to clinical diagnosis: association with diabetes mellitus. Clin Cancer Res. 2015;22(7):1734–1743.
  • Mallett S, Timmer A, Sauerbrei W, et al. Reporting of prognostic studies of tumour markers: a review of published articles in relation to REMARK guidelines. Br J Cancer. 2010;102(1):173–180.
  • Glasziou P, Altman DG, Bossuyt P, et al. Reducing waste from incomplete or unusable reports of biomedical research. Lancet. 2014;383(9913):267–276.
  • Petricoin EF, Liotta LA. SELDI-TOF-based serum proteomic pattern diagnostics for early detection of cancer. Curr Opin Biotechnol. 2004;15(1):24–30.
  • Hortin GL. The MALDI-TOF mass spectrometric view of the plasma proteome and peptidome. Clin Chem. 2006;52(7):1223–1237.
  • Albalat A, Husi H, Stalmach A, et al. Classical MALDI-MS versus CE-based ESI-MS proteomic profiling in urine for clinical applications. Bioanalysis. 2014;6(2):247–266.
  • Petricoin EF, Ardekani AM, Hitt BA, et al. Use of proteomic patterns in serum to identify ovarian cancer. Lancet. 2002;359(9306):572–577.
  • Li J, Zhang Z, Rosenzweig J, et al. Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer. Clin Chem. 2002;48(8):1296–1304.
  • Poon TC, Yip TT, Chan AT, et al. Comprehensive proteomic profiling identifies serum proteomic signatures for detection of hepatocellular carcinoma and its subtypes. Clin Chem. 2003;49(5):752–760.
  • Mobley JA, Lam YW, Lau KM, et al. Monitoring the serological proteome: the latest modality in prostate cancer detection. J Urol. 2004;172(1):331–337.
  • Theodorescu D, Wittke S, Ross MM, et al. Discovery and validation of new protein biomarkers for urothelial cancer: a prospective analysis. Lancet Oncol. 2006;7(3):230–240.
  • Zhang X, Wang B, Zhang XS, et al. Serum diagnosis of diffuse large B-cell lymphomas and further identification of response to therapy using SELDI-TOF-MS and tree analysis patterning. BMC Cancer. 2007;7:235.
  • Taguchi F, Solomon B, Gregorc V, et al. Mass spectrometry to classify non-small-cell lung cancer patients for clinical outcome after treatment with epidermal growth factor receptor tyrosine kinase inhibitors: a multicohort cross-institutional study. J Natl Cancer Inst. 2007;99(11):838–846.
  • Metzger J, Negm AA, Plentz RR, et al. Urine proteomic analysis differentiates cholangiocarcinoma from primary sclerosing cholangitis and other benign biliary disorders. Gut. 2013;62(1):122–130.
  • Diamandis EP. Analysis of serum proteomic patterns for early cancer diagnosis: drawing attention to potential problems. J Natl Cancer Inst. 2004;96(5):353–356.
  • Baggerly KA, Morris JS, Edmonson SR, et al. Signal in noise: evaluating reported reproducibility of serum proteomic tests for ovarian cancer. J Natl Cancer Inst. 2005;97(4):307–309.
  • Tiss A, Smith C, Menon U, et al. A well-characterised peak identification list of MALDI MS profile peaks for human blood serum. Proteomics. 2010;10(18):3388–3392.
  • Villanueva J, Shaffer DR, Philip J, et al. Differential exoprotease activities confer tumor-specific serum peptidome patterns. J Clin Invest. 2006;116(1):271–284.
  • Davis MT, Auger P, Spahr C, et al. Cancer biomarker discovery via low molecular weight serum proteome profiling - where is the tumor? Proteomics Clin Appl. 2007;1(12):1545–1558.
  • Skytt A, Thysell E, Stattin P, et al. SELDI-TOF MS versus prostate specific antigen analysis of prospective plasma samples in a nested case-control study of prostate cancer. Int J Cancer. 2007;121(3):615–620.
  • Timms JF, Cramer R, Camuzeaux S, et al. Peptides generated ex vivo from serum proteins by tumor-specific exopeptidases are not useful biomarkers in ovarian cancer. Clin Chem. 2010;56(2):262–271.
  • Zhang Z, Bast RC Jr., Yu Y, et al. Three biomarkers identified from serum proteomic analysis for the detection of early stage ovarian cancer. Cancer Res. 2004;64(16):5882–5890.
  • Sardana G, Jung K, Stephan C, et al. Proteomic analysis of conditioned media from the PC3, LNCaP, and 22Rv1 prostate cancer cell lines: discovery and validation of candidate prostate cancer biomarkers. J Proteome Res. 2008;7(8):3329–3338.
  • Sinclair J, Metodieva G, Dafou D, et al. Profiling signatures of ovarian cancer tumour suppression using 2D-DIGE and 2D-LC-MS/MS with tandem mass tagging. J Proteomics. 2011;74(4):451–465.
  • Mathivanan S, Ji H, Tauro BJ, et al. Identifying mutated proteins secreted by colon cancer cell lines using mass spectrometry. J Proteomics. 2012;76(Spec No.):141–149.
  • Zawadzka AM, Schilling B, Cusack MP, et al. Phosphoprotein secretome of tumor cells as a source of candidates for breast cancer biomarkers in plasma. Mol Cell Proteomics: MCP. 2014;13(4):1034–1049.
  • Karagiannis GS, Pavlou MP, Saraon P, et al. In-depth proteomic delineation of the colorectal cancer exoproteome: mechanistic insight and identification of potential biomarkers. J Proteomics. 2014;103:121–136.
  • Teng PN, Wang G, Hood BL, et al. Identification of candidate circulating cisplatin-resistant biomarkers from epithelial ovarian carcinoma cell secretomes. Br J Cancer. 2014;110(1):123–132.
  • Lin Q, Lim HS, Lin HL, et al. Analysis of colorectal cancer glyco-secretome identifies laminin beta-1 (LAMB1) as a potential serological biomarker for colorectal cancer. Proteomics. 2015;15(22):3905–3920.
  • Barderas R, Mendes M, Torres S, et al. In-depth characterization of the secretome of colorectal cancer metastatic cells identifies key proteins in cell adhesion, migration, and invasion. Mol Cell Proteomics: MCP. 2013;12(6):1602–1620.
  • Lawrenson K, Mhawech-Fauceglia P, Worthington J, et al. Identification of novel candidate biomarkers of epithelial ovarian cancer by profiling the Secretomes of three-dimensional genetic models of ovarian carcinogenesis. Int J Cancer. 2015;137(8):1806–1817.
  • Faca VM, Song KS, Wang H, et al. A mouse to human search for plasma proteome changes associated with pancreatic tumor development. PLoS Med. 2008;5(6):e123.
  • Greening DW, Gopal SK, Mathias RA, et al. Emerging roles of exosomes during epithelial-mesenchymal transition and cancer progression. Semin Cell Dev Biol. 2015;40:60–71.
  • Melo SA, Luecke LB, Kahlert C, et al. Glypican-1 identifies cancer exosomes and detects early pancreatic cancer. Nature. 2015;523(7559):177–182.
  • Purvine S, Eppel JT, Yi EC, et al. Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics. 2003;3(6):847–850.
  • Venable JD, Dong MQ, Wohlschlegel J, et al. Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra. Nat Methods. 2004;1(1):39–45.
  • Chakraborty AB, Berger SJ, Gebler JC. Use of an integrated MS–multiplexed MS/MS data acquisition strategy for high-coverage peptide mapping studies. Rapid Commun Mass Spectrom: RCM. 2007;21(5):730–744.
  • Gillet LC, Navarro P, Tate S, et al. Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis. Mol Cell Proteomics: MCP. 2012;11(6):O111–016717.
  • Law KP, Lim YP. Recent advances in mass spectrometry: data independent analysis and hyper reaction monitoring. Expert Rev Proteomics. 2013;10(6):551–566.
  • Li GZ, Vissers JP, Silva JC, et al. Database searching and accounting of multiplexed precursor and product ion spectra from the data independent analysis of simple and complex peptide mixtures. Proteomics. 2009;9(6):1696–1719.
  • Silva JC, Gorenstein MV, Li GZ, et al. Absolute quantification of proteins by LCMSE: a virtue of parallel MS acquisition. Mol Cell Proteomics: MCP. 2006;5(1):144–156.
  • Liu Y, Huttenhain R, Collins B, et al. Mass spectrometric protein maps for biomarker discovery and clinical research. Expert Rev Mol Diagn. 2013;13(8):811–825.
  • Sajic T, Liu Y, Aebersold R. Using data-independent, high-resolution mass spectrometry in protein biomarker research: perspectives and clinical applications. Proteomics Clin Appl. 2015;9(3–4):307–321.
  • Janvilisri T, Leelawat K, Roytrakul S, et al. Novel serum biomarkers to differentiate cholangiocarcinoma from benign biliary tract diseases using a proteomic approach. Dis Markers. 2015;2015:105358.
  • Ansari D, Andersson R, Bauden MP, et al. Protein deep sequencing applied to biobank samples from patients with pancreatic cancer. J Cancer Res Clin Oncol. 2015;141(2):369–380.
  • Guo T, Kouvonen P, Koh CC, et al. Rapid mass spectrometric conversion of tissue biopsy samples into permanent quantitative digital proteome maps. Nat Med. 2015;21(4):407–413.
  • Liu Y, Chen J, Sethi A, et al. Glycoproteomic analysis of prostate cancer tissues by SWATH mass spectrometry discovers N-acylethanolamine acid amidase and protein tyrosine kinase 7 as signatures for tumor aggressiveness. Mol Cell Proteomics. 2014;13(7):1753–1768.
  • Hou G, Lou X, Sun Y, et al. Biomarker discovery and verification of esophageal squamous cell carcinoma using integration of SWATH/MRM. J Proteome Res. 2015;14(9):3793–3803.
  • Picotti P, Aebersold R. Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions. Nat Methods. 2012;9(6):555–566.
  • Gallien S, Bourmaud A, Kim SY, et al. Technical considerations for large-scale parallel reaction monitoring analysis. J Proteomics. 2014;100:147–159.
  • Peterson AC, Russell JD, Bailey DJ, et al. Parallel reaction monitoring for high resolution and high mass accuracy quantitative, targeted proteomics. Mol Cell Proteomics. 2012;11(11):1475–1488.
  • Tang HY, Beer LA, Tanyi JL, et al. Protein isoform-specific validation defines multiple chloride intracellular channel and tropomyosin isoforms as serological biomarkers of ovarian cancer. J Proteomics. 2013;89:165–178.
  • Ohmine K, Kawaguchi K, Ohtsuki S, et al. Quantitative targeted proteomics of pancreatic cancer: deoxycytidine kinase protein level correlates to progression-free survival of patients receiving gemcitabine treatment. Mol Pharm. 2015;12(9):3282–3291.
  • Rodriguez H, Rivers R, Kinsinger C, et al. Reconstructing the pipeline by introducing multiplexed multiple reaction monitoring mass spectrometry for cancer biomarker verification: an NCI-CPTC initiative perspective. Proteomics Clin Appl. 2010;4(12):904–914.
  • Kennedy JJ, Abbatiello SE, Kim K, et al. Demonstrating the feasibility of large-scale development of standardized assays to quantify human proteins. Nat Methods. 2014;11(2):149–155.
  • Li XJ, Hayward C, Fong PY, et al. A blood-based proteomic classifier for the molecular characterization of pulmonary nodules. Sci Transl Med. 2013;5(207):207ra142.
  • Vachani A, Hammoud Z, Springmeyer S, et al. Clinical utility of a plasma protein classifier for indeterminate lung nodules. Lung. 2015;193(6):1023–1027.
  • Li QK, Chen L, Ao MH, et al. Serum fucosylated prostate-specific antigen (PSA) improves the differentiation of aggressive from non-aggressive prostate cancers. Theranostics. 2015;5(3):267–276.
  • Kiernan UA, Tubbs KA, Gruber K, et al. High-throughput protein characterization using mass spectrometric immunoassay. Anal Biochem. 2002;301(1):49–56.
  • Anderson NL, Anderson NG, Haines LR, et al. Mass spectrometric quantitation of peptides and proteins using stable isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA). J Proteome Res. 2004;3(2):235–244.
  • Weiss F, van den Berg BH, Planatscher H, et al. Catch and measure-mass spectrometry-based immunoassays in biomarker research. Biochim Biophys Acta. 2014;1844(5):927–932.
  • Oran PE, Trenchevska O, Nedelkov D, et al. Parallel workflow for high-throughput (>1,000 samples/day) quantitative analysis of human insulin-like growth factor 1 using mass spectrometric immunoassay. PLoS One. 2014;9(3):e92801.
  • Schober Y, Guenther S, Spengler B, et al. Single cell matrix-assisted laser desorption/ionization mass spectrometry imaging. Anal Chem. 2012;84(15):6293–6297.
  • Rompp A, Guenther S, Schober Y, et al. Histology by mass spectrometry: label-free tissue characterization obtained from high-accuracy bioanalytical imaging. Angew Chemie Int Ed. 2010;49(22):3834–3838.
  • Jungmann JH, Smith DF, MacAleese L, et al. Biological tissue imaging with a position and time sensitive pixelated detector. J Am Soc Mass Spectrom. 2012;23(10):1679–1688.
  • Jarmusch AK, Pirro V, Baird Z, et al., Lipid and metabolite profiles of human brain tumors by desorption electrospray ionization-MS. Proc Natl Acad Sci U S A. 2016;113:1486–1491.
  • Fletcher JS, Vickerman JC, Winograd N. Label free biochemical 2D and 3D imaging using secondary ion mass spectrometry. Curr Opin Chem Biol. 2011;15(5):733–740.
  • Eikel D, Vavrek M, Smith S, et al. Liquid extraction surface analysis mass spectrometry (LESA-MS) as a novel profiling tool for drug distribution and metabolism analysis: the terfenadine example. Rapid Commun Mass Spectrom: RCM. 2011;25(23):3587–3596.
  • Li Y, Shrestha B, Vertes A. Atmospheric pressure infrared MALDI imaging mass spectrometry for plant metabolomics. Anal Chem. 2008;80(2):407–420.
  • Bartels B, Svatos A. Spatially resolved in vivo plant metabolomics by laser ablation-based mass spectrometry imaging (MSI) techniques: LDI-MSI and LAESI. Front Plant Sci. 2015;6:471.
  • Huang MZ, Jhang SS, Shiea J. Electrospray laser desorption ionization (ELDI) mass spectrometry for molecular imaging of small molecules on tissues. Methods Mol Biol. 2015;1203:107–116.
  • Barry JA, Groseclose MR, Robichaud G, et al. Assessing drug and metabolite detection in liver tissue by UV-MALDI and IR-MALDESI mass spectrometry imaging coupled to FT-ICR MS. Int J Mass Spectrom. 2015;377:448–155.
  • Bhandari DR, Schott M, Rompp A, et al. Metabolite localization by atmospheric pressure high-resolution scanning microprobe matrix-assisted laser desorption/ionization mass spectrometry imaging in whole-body sections and individual organs of the rove beetle Paederus riparius. Anal Bioanal Chem. 2015;407(8):2189–2201.
  • Balluff B, Frese CK, Maier SK, et al. De novo discovery of phenotypic intratumour heterogeneity using imaging mass spectrometry. J Pathol. 2015;235(1):3–13.
  • Calligaris D, Feldman DR, Norton I, et al. MALDI mass spectrometry imaging analysis of pituitary adenomas for near-real-time tumor delineation. Proc Natl Acad Sci U S A. 2015;112(32):9978–9983.
  • Jones EA, Schmitz N, Waaijer CJ, et al. Imaging mass spectrometry-based molecular histology differentiates microscopically identical and heterogeneous tumors. J Proteome Res. 2013;12(4):1847–1855.
  • Willems SM, van Remoortere A, van Zeijl R, et al. Imaging mass spectrometry of myxoid sarcomas identifies proteins and lipids specific to tumour type and grade, and reveals biochemical intratumour heterogeneity. J Pathol. 2010;222(4):400–409.
  • Grüer BM, Winkelmann I, Feuchtinger A, et al. Modeling therapy response and spatial tissue distribution of erlotinib in pancreatic cancer. Mol Cancer Ther. 2016.2016 Jan 28. doi:10.1158/1535-7163.MCT-15-0165.
  • Buck A, Halbritter S, Spath C, et al. Distribution and quantification of irinotecan and its active metabolite SN-38 in colon cancer murine model systems using MALDI MSI. Anal Bioanal Chem. 2015;407(8):2107–2116.
  • Mascini NE, Eijkel GB, ter Brugge P, et al. The use of mass spectrometry imaging to predict treatment response of patient-derived xenograft models of triple-negative breast cancer. J Proteome Res. 2015;14(2):1069–1075.
  • Gemoll T, Strohkamp S, Schillo K, et al. MALDI-imaging reveals thymosin beta-4 as an independent prognostic marker for colorectal cancer. Oncotarget. 2015;6(41):43869–43880.
  • Jones EE, Powers TW, Neely BA, et al. MALDI imaging mass spectrometry profiling of proteins and lipids in clear cell renal cell carcinoma. Proteomics. 2014;14(7–8):924–935.
  • Wang S, Chen X, Luan H, et al. Matrix-assisted laser desorption/ionization mass spectrometry imaging of cell cultures for the lipidomic analysis of potential lipid markers in human breast cancer invasion. Rapid Commun Mass Spectrom. 2016;30(4):533–542.
  • Dekker TJ, Balluff BD, Jones EA, et al. Multicenter matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) identifies proteomic differences in breast-cancer-associated stroma. J Proteome Res. 2014;13(11):4730–4738.
  • Jiang L, Chughtai K, Purvine SO, et al. MALDI-mass spectrometric imaging revealing hypoxia-driven lipids and proteins in a breast tumor model. Anal Chem. 2015;87(12):5947–5956.
  • Flatley B, Quaye C, Johnson E, et al. Distribution analysis of the putative cancer marker S100A4 across invasive squamous cell carcinoma penile tissue. EuPA Open Proteomics. 2015;7:1–10.
  • Cole LM, Clench MR. Mass spectrometry imaging tools in oncology. Biomark Med. 2015;9(9):863–868.
  • Kriegsmann J, Kriegsmann M, Casadonte R. MALDI TOF imaging mass spectrometry in clinical pathology: a valuable tool for cancer diagnostics (review). Int J Oncol. 2015;46(3):893–906.
  • McDonnell LA, Corthals GL, Willems SM, et al. Peptide and protein imaging mass spectrometry in cancer research. J Proteomics. 2010;73(10):1921–1944.
  • Schäfer K-C, Dénes J, Albrecht K, et al. In Vivo, In situ tissue analysis using rapid evaporative ionization mass spectrometry. Angew Chemie Int Ed. 2009;48(44):8240–8242.
  • Dixon RB, Bereman MS, Muddiman DC, et al. Remote mass spectrometric sampling of electrospray- and desorption electrospray-generated ions using an air ejector. J Am Soc Mass Spectrom. 2007;18(10):1844–1847.
  • Iorio E, Mezzanzanica D, Alberti P, et al. Alterations of choline phospholipid metabolism in ovarian tumor progression. Cancer Res. 2005;65(20):9369–9376.
  • Balog J, Sasi-Szabo L, Kinross J, et al. Intraoperative tissue identification using rapid evaporative ionization mass spectrometry. Sci Transl Med. 2013;5(194):194ra193.
  • Wong S. “Intelligent knife” tells surgeon if tissue is cancerous. London: Imperial College London; 2013.
  • Gallagher J. Cancer surgery: tumour ‘sniffing’ surgical knife designed. BBC News. 2013.
  • Nicholson J. iKnife: a surgical revolution: sniffing out cancer. Kent: Telegraph Media Group Limited; 2014.
  • REIMS research system with iKnife sampling device. Milford (MA): Waters; 2015.
  • Wong S. Waters corporation acquires iKnife technology. London: Imperial College London; 2014.
  • Strittmatter N, Jones EA, Veselkov KA, et al. Analysis of intact bacteria using rapid evaporative ionisation mass spectrometry. Chem Communications. 2013;49(55):6188–6190.
  • Strittmatter N, Rebec M, Jones EA, et al. Characterization and identification of clinically relevant microorganisms using rapid evaporative ionization mass spectrometry. Anal Chem. 2014;86(13):6555–6562.
  • Golf O, Strittmatter N, Karancsi T, et al. Rapid evaporative ionization mass spectrometry imaging platform for direct mapping from bulk tissue and bacterial growth media. Anal Chem. 2015;87(5):2527–2534.
  • Sachfer KC, Szaniszlo T, Gunther S, et al. In situ, real-time identification of biological tissues by ultraviolet and infrared laser desorption ionization mass spectrometry. Anal Chem. 2011;83(5):1632–1640.
  • Schafer KC, Balog J, Szaniszlo T, et al. Real time analysis of brain tissue by direct combination of ultrasonic surgical aspiration and sonic spray mass spectrometry. Anal Chem. 2011;83(20):7729–7735.
  • Clark AE, Kaleta EJ, Arora A, et al. Matrix-assisted laser desorption ionization-time of flight mass spectrometry: a fundamental shift in the routine practice of clinical microbiology. Clin Microbiol Rev. 2013;26(3):547–603.
  • Xiao D, Zhang HF, He LH, et al. High natural variability bacteria identification and typing: Helicobacter pylori analysis based on peptide mass fingerprinting. J Proteomics. 2014;98:112–122.
  • Levine JH, Simonds EF, Bendall SC, et al. Data-driven phenotypic dissection of AML reveals progenitor-like cells that correlate with prognosis. Cell. 2015;162(1):184–197.
  • Amal H, Leja M, Funka K, et al. Breath testing as potential colorectal cancer screening tool. Int J Cancer. 2016;138(1):229–236.
  • Arasaradnam RP, McFarlane MJ, Ryan-Fisher C, et al. Detection of Colorectal Cancer (CRC) by Urinary volatile organic compound analysis. PLoS One. 2014;9(9).:e108750.
  • Li J, Peng YL, Liu Y, et al. Investigation of potential breath biomarkers for the early diagnosis of breast cancer using gas chromatography-mass spectrometry. Clinica Chimica Acta. 2014;436:59–67.
  • Phillips M, Bauer TL, Cataneo RN, et al. Blinded validation of breath biomarkers of lung cancer, a potential ancillary to chest CT screening. PLoS One. 2015;10(12):.e0142484.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.