Single Cell Proteomics for Molecular Targets in Lung Cancer: High-Dimensional Data Acquisition and Analysis

  • Zheng Wang
  • Xiaoju Zhang
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 1068)


In the proteomic and genomic era, lung cancer researchers are increasingly under challenge with traditional protein analyzing tools. High output, multiplexed analytical procedures are in demand for disclosing the post-translational modification, molecular interactions and signaling pathways of proteins precisely, specifically, dynamically and systematically, as well as for identifying novel proteins and their functions. This could be better realized by single-cell proteomic methods than conventional proteomic methods. Using single-cell proteomic tools including flow cytometry, mass cytometry, microfluidics and chip technologies, chemical cytometry, single-cell western blotting, the quantity and functions of proteins are analyzed simultaneously. Aside from deciphering disease mechanisms, single-cell proteomic techniques facilitate the identification and screening of biomarkers, molecular targets and promising compounds as well. This review summarized single-cell proteomic tools and their use in lung cancer.


Lung cancer Mass spectrometry Single nucleotide polymorphism Biomarker 


  1. 1.
    Siegel RL, Miller KD, Jemal A (2017) Cancer statistics, 2017. CA Cancer J Clin 67(1):7–30CrossRefGoogle Scholar
  2. 2.
    Greenhalgh J, Dwan K, Boland A, Bates V, Vecchio F, Dundar Y, Jain P, Green JA (2016) First-line treatment of advanced epidermal growth factor receptor (EGFR) mutation positive non-squamous non-small cell lung cancer. Cochrane Database Syst Rev 5:CD010383Google Scholar
  3. 3.
    Sabari JK, Lok BH, Laird JH, Poirier JT, Rudin CM (2017) Unravelling the biology of SCLC: implications for therapy. Nat Rev Clin Oncol 14(9):549–561CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Cohen AA, Geva-Zatorsky N, Eden E, Frenkel-Morgenstern M, Issaeva I, Sigal A et al (2008) Dynamic proteomics of individual cancer cells in response to a drug. Science 322:1511–1516CrossRefPubMedGoogle Scholar
  5. 5.
    Zimmer A, Amar-Farkash S, Danon T, Alon U (2017) Dynamic proteomics reveals bimodal protein dynamics of cancer cells in response to HSP90 inhibitor. BMC Syst Biol 11(1):33CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Fujii K, Nakamura H, Nishimura T (2017) Recent mass spectrometry-based proteomics for biomarker discovery in lung cancer, COPD, and asthma. Expert Rev Proteomics 14(4):373–386CrossRefPubMedGoogle Scholar
  7. 7.
    Birse CE, Lagier RJ, FitzHugh W, Pass HI, Rom WN, Edell ES et al (2015) Blood-based lung cancer biomarkers identified through proteomic discovery in cancer tissues, cell lines and conditioned medium. Clin Proteomics 12(1):18CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Li L, Wei Y, To L, Zhu CQ, Tong J, Pham NA et al (2014) Integrated omic analysis of lung cancer reveals metabolism proteome signatures with prognostic impact. Nat Commun 5:5469CrossRefPubMedGoogle Scholar
  9. 9.
    Bharti A, Ma PC, Salgia R (2007) Biomarker discovery in lung cancer-promises and challenges of clinical proteomics. Mass Spectrom Rev 26(3):451–466CrossRefPubMedGoogle Scholar
  10. 10.
    Ocak S, Chaurand P, Massion PP (2009) Mass spectrometry-based proteomic profiling of lung cancer. Proc Am Thorac Soc 6(2):159–170CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Soo RA, Adjei AA (2017) Predicting clinical outcomes using proteomics in non-small cell lung cancer-the past, present, and future. J Thorac Oncol 12(4):602–606CrossRefPubMedGoogle Scholar
  12. 12.
    Yanagisawa K, Shyr Y, Xu BJ, Massion PP, Larsen PH, White BC et al (2003) Proteomic patterns of tumour subsets in non-small-cell lung cancer. Lancet 362:433–439CrossRefPubMedGoogle Scholar
  13. 13.
    Ostroff RM, Bigbee WL, Franklin W, Gold L, Mehan M, Miller YE et al (2010) Unlocking biomarker discovery: large scale application of aptamer proteomic technology for early detection of lung cancer. PLoS One 5(12):e15003CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Jung YJ, Katilius E, Ostroff RM, Kim Y, Seok M, Lee S, Jang S, Kim WS, Choi CM (2017) Development of a protein biomarker panel to detect non-small-cell lung cancer in Korea. Clin Lung Cancer 18(2):e99–e107CrossRefPubMedGoogle Scholar
  15. 15.
    Codreanu SG, Hoeksema MD, Slebos RJC, Zimmerman LJ, Rahman SMJ, Li M, Chen SC, Chen H, Eisenberg R, Liebler DC, Massion PP (2017) Identification of proteomic features to distinguish benign pulmonary nodules from lung adenocarcinoma. J Proteome Res 16(9):3266–3276CrossRefPubMedGoogle Scholar
  16. 16.
    Solanki HS, Advani J, Khan AA, Radhakrishnan A, Sahasrabuddhe NA, Pinto SM et al (2017) Chronic cigarette smoke mediated global changes in lung mucoepidermoid cells: a phosphoproteomic analysis. OMICS 21(8):474–487CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    López-Sánchez LM, Jurado-Gámez B, Feu-Collado N, Valverde A, Cañas A, Fernández-Rueda JL, Aranda E, Rodríguez-Ariza A (2017) Exhaled breath condensate biomarkers for the early diagnosis of lung cancer using proteomics. Am J Physiol Lung Cell Mol Physiol ajplung.00119.2017. [Epub ahead of print]
  18. 18.
    Gocheva V, Naba A, Bhutkar A, Guardia T, Miller KM, Li CM, Dayton TL, Sanchez-Rivera FJ, Kim-Kiselak C, Jailkhani N, Winslow MM, Del Rosario A, Hynes RO, Jacks T (2017) Quantitative proteomics identify Tenascin-C as a promoter of lung cancer progression and contributor to a signature prognostic of patient survival. Proc Natl Acad Sci U S A 114(28):E5625–E5634CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Yanagisawa K, Tomida S, Shimada Y, Yatabe Y, Mitsudomi T, Takahashi T (2007) A 25-signal proteomic signature and outcome for patients with resected non-small-cell lung cancer. J Natl Cancer Inst 99:858–867CrossRefPubMedGoogle Scholar
  20. 20.
    Taguchi F, Solomon B, Gregorc V, Rodr H, Gray R, Kasahara K et al (2007) 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 99:838–846CrossRefPubMedGoogle Scholar
  21. 21.
    Salmon S, Chen H, Chen S, Herbst R, Tsao A, Tran H et al (2009) Classification by mass spectrometry can accurately and reliably predict outcome in patients with nonsmall cell lung cancer treated with erlotinib-containing regimen. J Thorac Oncol 4(6):689–696CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Gregorc V, Novello S, Lazzari C, Barni S, Aieta M, Mencoboni M et al (2014) Predictive value of a proteomic signature in patients with non-small-cell lung cancer treated with second-line erlotinib or chemotherapy (PROSE): a biomarker-stratified, randomised phase 3 trial. Lancet Oncol 15:713–721CrossRefPubMedGoogle Scholar
  23. 23.
    Grossi F, Rijavec E, Genova C, Barletta G, Biello F, Maggioni C et al (2017) Serum proteomic test in advanced non-squamous non-small cell lung cancer treated in first line with standard chemotherapy. Br J Cancer 116(1):36–43CrossRefPubMedGoogle Scholar
  24. 24.
    Lara PN Jr, Moon J, Hesketh PJ, Redman MW, Williamson SK, Akerley WL 3rd, Hirsch FR, Mack PC, Gandara DR (2016) SWOG S0709: Randomized phase II trial of erlotinib versus erlotinib plus carboplatin/paclitaxel in patients with advanced non-small cell lung cancer and impaired performance status as selected by a serum proteomics assay. J Thorac Oncol 11(3):420–425CrossRefPubMedGoogle Scholar
  25. 25.
    Paul D, Chanukuppa V, Reddy PJ, Taunk K, Adhav R, Srivastava S, Santra MK, Rapole S (2016) Global proteomic profiling identifies etoposide chemoresistance markers in non-small cell lung carcinoma. J Proteome 138:95–105CrossRefGoogle Scholar
  26. 26.
    Rovithi M, Lind JS, Pham TV, Voortman J, Knol JC, Verheul HM, Smit EF, Jimenez CR (2016) Response and toxicity prediction by MALDI-TOF-MS serum peptide profiling in patients with non-small cell lung cancer. Proteomics Clin Appl 10(7):743–749CrossRefPubMedGoogle Scholar
  27. 27.
    Nyberg F, Ogiwara A, Harbron CG, Kawakami T, Nagasaka K, Takami S et al (2011) Proteomic biomarkers for acute interstitial lung disease in gefitinib-treated Japanese lung cancer patients. PLoS One 6(7):e22062CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Peters S, Stahel RA, Dafni U, Ponce Aix S, Massutí B, Gautschi O et al (2017) Randomized phase III trial of erlotinib versus docetaxel in patients with advanced squamous cell non-small cell lung cancer failing first-line platinum-based doublet chemotherapy stratified by VeriStrat good versus VeriStrat poor. The European Thoracic Oncology Platform (ETOP) EMPHASIS-lung Trial. J Thorac Oncol 12(4):752–762CrossRefPubMedGoogle Scholar
  29. 29.
    Gadgeel S, Goss G, Soria JC, Felip E, Georgoulias V, Lu S et al (2017) Evaluation of the VeriStrat serum protein test in patients with advanced squamous cell carcinoma of the lung treated with second-line afatinib or erlotinib in the phase III LUX-Lung 8 study. Lung Cancer 109:101–108CrossRefPubMedGoogle Scholar
  30. 30.
    Tan YH, Lee KH, Lin T, Sun YC, Hsieh-Li HM, Juan HF, Wang YC (2008) Cytotoxicity and proteomics analyses of OSU03013 in lung cancer. Clin Cancer Res 14(6):1823–1830CrossRefPubMedGoogle Scholar
  31. 31.
    Li Y, Zhang B, Wang X, Yan H, Chen G, Zhang X (2011) Proteomic analysis of apoptosis induction in human lung cancer cells by recombinant MVL. Amino Acids 41(4):923–932CrossRefPubMedGoogle Scholar
  32. 32.
    Labots M, Schütte LM, van der Mijn JC, Pham TV, Jiménez CR, Verheul HM (2014) Mass spectrometry-based serum and plasma peptidome profiling for prediction of treatment outcome in patients with solid malignancies. Oncologist 19(10):1028–1039CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Cheung CHY, Juan HF (2017) Quantitative proteomics in lung cancer. J Biomed Sci 24:37CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Yang L, Tang C, Xu B, Wang W, Li J, Li X, Qin H, Gao H, He K, Song S, Liu X (2015) Classification of epidermal growth factor receptor gene mutation status using serum proteomic profiling predicts tumor response in patients with stage IIIB or IV non-small-cell lung cancer. PLoS One 10(6):e0128970CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Heath JR, Ribas A, Mischel PS (2016) Single cell analytic tools for drug discovery and development. Nat Rev Drug Discov 15(3):204–216CrossRefPubMedGoogle Scholar
  36. 36.
    Gavasso S, Gullaksen S, Skavland J, Gjertsen BT (2016) Single-cell proteomics: potential implications for cancer diagnostics. Expert Rev Mol Diagn 16(5):579–589CrossRefPubMedGoogle Scholar
  37. 37.
    Lu Y, Yang L, Wei W, Shi Q (2017) Microchip-based single-cell functional proteomics for biomedical applications. Lab Chip 17(7):1250–1263CrossRefPubMedPubMedCentralGoogle Scholar
  38. 38.
    Wei W, Shin YS, Ma C, Wang J, Elitas M, Fan R, Heath JR (2013) Microchip platforms for multiplex single-cell functional proteomics with applications to immunology and cancer research. Genome Med 5(8):75CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    Beck TN, Chikwem AJ, Solanki NR, Golemis EA (2014) Bioinformatic approaches to augment study of epithelial-to-mesenchymal transition in lung cancer. Physiol Genomics 46(19):699–724CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Marrugal Á, Ojeda L, Paz-Ares L, Molina-Pinelo S, Ferrer I (2016) Proteomic-based approaches for the study of cytokines in lung cancer. Dis Markers 2016:2138627CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    Herzenberg LA, Parks D, Sahaf B, Perez O, Roederer M, Herzenberg LA (2002) The history of the fluorescence activated cell sorter and flow cytometry: a view from Stanford. Clin Chem 48:1819–1827PubMedGoogle Scholar
  42. 42.
    Lamoreaux L, Roederer M, Koup R (2006) Intracellular cytokine optimization and standard operating procedure. Nat Protoc 1:1507–1516CrossRefPubMedGoogle Scholar
  43. 43.
    Leelatian N, Doxie DB, Greenplate AR, Mobley BC, Lehman JM, Sinnaeve J et al (2017) Single cell analysis of human tissues and solid tumors with mass cytometry. Cytometry B Clin Cytom 92(1):68–78CrossRefPubMedGoogle Scholar
  44. 44.
    Lin CC, Huang WL, Su WP, Chen HH, Lai WW, Yan JJ, Su WC (2010) Single cell phospho-specific flow cytometry can detect dynamic changes of phospho-Stat1 level in lung cancer cells. Cytometry A 77(11):1008–1019CrossRefPubMedGoogle Scholar
  45. 45.
    Skavland J, Jorgensen KM, Hadziavdic K, Hovland R, Jonassen I, Bruserud O, Gjertsen BT (2011) Specific cellular signal transduction responses to in vivo combination therapy with ATRA, valproic acid and theophylline in acute myeloid leukemia. Blood Cancer J 1(2):e4CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Kotecha N, Flores NJ, Irish JM, Simonds EF, Sakai DS, Archambeault S, Diaz-Flores E, Coram M, Shannon KM, Nolan GP, Loh ML (2008) Single-cell profiling identifies aberrant STAT5 activation in myeloid malignancies with specific clinical and biologic correlates. Cancer Cell 14(4):335–343CrossRefPubMedPubMedCentralGoogle Scholar
  47. 47.
    Lu Y, Liang H, Yu T, Xie J, Chen S, Dong H, Sinko PJ, Lian S, Xu J, Wang J, Yu S, Shao J, Yuan B, Wang L, Jia L (2015) Isolation and characterization of living circulating tumor cells in patients by immunomagnetic negative enrichment coupled with flow cytometry. Cancer 121(17):3036–3045CrossRefPubMedGoogle Scholar
  48. 48.
    Mesri M, Birse C, Heidbrink J, McKinnon K, Brand E, Bermingham CL, Feild B, Fitzhugh W, He T, Ruben S, Moore PA (2013) Identification and characterization of angiogenesis targets through proteomic profiling of endothelial cells in human cancer tissues. PLoS One 8(11):e78885CrossRefPubMedPubMedCentralGoogle Scholar
  49. 49.
    Diercks AH, Ozinsky A, Hansen CL, Spotts JM, Rodriguez DJ, Aderem A (2009) A microfluidic device for multiplexed protein detection in nano-liter volumes. Anal Biochem 386:30–35CrossRefPubMedGoogle Scholar
  50. 50.
    Shrestha B, Vertes A (2009) In situ metabolic profiling of single cells by laser ablation electrospray ionization mass spectrometry. Anal Chem 81:8265–8271CrossRefPubMedGoogle Scholar
  51. 51.
    Bandura DR, Baranov VI, Ornatsky OI, Antonov A, Kinach R, Lou X, Pavlov S, Vorobiev S, Dick JE, Tanner SD (2009) Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry. Anal Chem 81(16):6813–6822CrossRefPubMedGoogle Scholar
  52. 52.
    Gullaksen SE, Skavland J, Gavasso S, Tosevski V, Warzocha K, Dumrese C et al (2017) Single cell immune profiling by mass cytometry of newly diagnosed chronic phase chronic myeloid leukemia treated with nilotinib. Haematologica 102(8):1361–1367CrossRefPubMedPubMedCentralGoogle Scholar
  53. 53.
    Levine JH, Simonds EF, Bendall SC, Davis KL, Amir e-AD, Tadmor MD et al (2015) Data-driven phenotypic dissection of AML reveals progenitor-like cells that correlate with prognosis. Cell 162(1):184–197CrossRefPubMedPubMedCentralGoogle Scholar
  54. 54.
    Giesen C, Wang HA, Schapiro D, Zivanovic N, Jacobs A, Hattendorf B (2014) Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry. Nat Methods 11(4):417–422CrossRefPubMedGoogle Scholar
  55. 55.
    Rahman AH, Lavin Y, Kobayashi S, Leader A, Merad M (2017) High-dimensional single cell mapping of cerium distribution in the lung immune microenvironment of an active smoker. Cytometry B Clin Cytom [Epub ahead of print]
  56. 56.
    Brodie TM, Tosevski V (2017) High-dimensional single-cell analysis with mass cytometry. Curr Protoc Immunol 118:5.11.1–5.11.25CrossRefGoogle Scholar
  57. 57.
    Schuffler PJ, Schapiro D, Giesen C, Wang HA, Bodenmiller B, Buhmann JM (2015) Automatic single cell segmentation on highly multiplexed tissue images. Cytometry A 87(10):936–942CrossRefPubMedGoogle Scholar
  58. 58.
    Angelo M, Bendall SC, Finck R, Hale MB, Hitzman C, Borowsky AD, Levenson RM, Lowe JB, Liu SD, Zhao S et al (2014) Multiplexed ion beam imaging of human breast tumors. Nat Med 20:436–442CrossRefPubMedPubMedCentralGoogle Scholar
  59. 59.
    Rost S, Giltnane J, Bordeaux JM, Hitzman C, Koeppen H, Liu SD (2017 Aug) Multiplexed ion beam imaging analysis for quantitation of protein expresssion in cancer tissue sections. Lab Investig 97(8):992–1003CrossRefPubMedGoogle Scholar
  60. 60.
    Roth C, Stückrath I, Pantel K, Izbicki JR, Tachezy M, Schwarzenbach H (2012) Low levels of cell-free circulating miR-361-3p and miR-625* as blood-based markers for discriminating malignant from benign lung tumors. PLoS One 7(6):e38248CrossRefPubMedPubMedCentralGoogle Scholar
  61. 61.
    Sun J, Michael Masterman-Smith M, Graham NA (2010) A microfluidic platform for systems pathology: multiparameter single-cell signaling measurements of clinical brain tumor specimens. Cancer Res 70(15):6128–6138CrossRefPubMedPubMedCentralGoogle Scholar
  62. 62.
    Huang L, Michael SA, Chen Y, Wu H (2017) Current advances in highly multiplexed antibody-based single-cell proteomic measurements. Chem Asian J 12(14):1680–1691CrossRefPubMedGoogle Scholar
  63. 63.
    Khoo BL, Warkiani ME, Tan DS, Bhagat AA, Irwin D, Lau DP, Lim AS, Lim KH, Krisna SS, Lim WT, Yap YS, Lee SC, Soo RA, Han J, Lim CT (2014) Clinical validation of an ultra high-throughput spiral microfluidics for the detection and enrichment of viable circulating tumor cells. PLoS One 9(7):e99409CrossRefPubMedPubMedCentralGoogle Scholar
  64. 64.
    Fan B, Li X, Chen D, Peng H, Wang J, Chen J (2016) Development of microfluidic systems enabling high-throughput single-cell protein characterization. Sensors (Basel) 16(2):232CrossRefGoogle Scholar
  65. 65.
    Yu J, Zhou J, Sutherland A, Wei W, Shin YS, Xue M, Heath JR (2014) Microfluidics-based single-cell functional proteomics for fundamental and applied biomedical applications. Annu Rev Anal Chem 7:275–295CrossRefGoogle Scholar
  66. 66.
    Chen H, Lau MC, Wong MT, Newell EW, Poidinger M, Chen J (2016) Cytofkit: a bioconductor package for an integrated mass cytometry data analysis pipeline. PLoS Comput Biol 12(9):e1005112CrossRefPubMedPubMedCentralGoogle Scholar
  67. 67.
    Cohen D, Dickerson JA, Whitmore CD, Turner EH, Palcic MM, Hindsgaul O, Dovichi NJ (2008) Chemical cytometry: fluorescence-based single-cell analysis. Annu Rev Anal Chem 1:165–190CrossRefGoogle Scholar
  68. 68.
    Xu F, Zhao H, Feng X, Chen L, Chen D, Zhang Y, Nan F, Liu J, Liu BF (2014) Single-cell chemical proteomics with an activity based probe: identification of low-copy membrane proteins on primary neurons. Angew Chem Int Ed Engl 53(26):6730–6733CrossRefPubMedGoogle Scholar
  69. 69.
    Yan H, Zhang B, Wu H (2008) Chemical cytometry on microfluidic chips. Electrophoresis 29(9):1775–1786CrossRefPubMedGoogle Scholar
  70. 70.
    Kleparnik K (2015) Recent advances in combination of capillary electrophoresis with mass spectrometry: methodology and theory. Electrophoresis 36(1):159–178CrossRefPubMedGoogle Scholar
  71. 71.
    Mainz ER, Dobes NC, Allbritton NL (2015) Pronase E-based generation of fluorescent peptide fragments: tracking intracellular peptide fate in single cells. Anal Chem 87(15):7987–7995CrossRefPubMedPubMedCentralGoogle Scholar
  72. 72.
    Sun L, Zhu G, Yan X et al (2014) Capillary zone electrophoresis for analysis of complex proteomes using an electrokinetically pumped sheath flow nanospray interface. Proteomics 14(4–5):622–628CrossRefPubMedGoogle Scholar
  73. 73.
    Jung HJ (2017) Chemical proteomic approaches targeting cancer stem cells: a review of current literature. Cancer Genomics Proteomics 14(5):315–327PubMedGoogle Scholar
  74. 74.
    Kang CC, Yamauchi KA, Vlassakis J, Sinkala E, Duncombe TA, Herr AE (2016) Single cell-resolution western blotting. Nat Protoc 11(8):1508–1530CrossRefPubMedPubMedCentralGoogle Scholar
  75. 75.
    Hughes AJ, Spelke DP, Xu Z, Kang CC, Schaffer DV, Herr AE (2014) Single-cell western blotting. Nat Methods 11(7):749–755CrossRefPubMedPubMedCentralGoogle Scholar
  76. 76.
    Streets AM, Huang Y (2014) Microfluidics for biological measurements with single-molecule resolution. Curr Opin Biotechnol 25:69–77CrossRefPubMedGoogle Scholar
  77. 77.
    Spitzer MH, Nolan GP (2016) Mass cytometry: single cells, many features. Cell 165(4):780–791CrossRefPubMedPubMedCentralGoogle Scholar
  78. 78.
    Amann JM, Chaurand P, Gonzalez A, Mobley JA, Massion PP, Carbone DP, Caprioli RM (2006) Selective profiling of proteins in lung cancer cells from fine-needle aspirates by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Clin Cancer Res 12:5142–5150CrossRefPubMedGoogle Scholar
  79. 79.
    Hmmier A, O’Brien ME, Lynch V, Clynes M, Morgan R, Dowling P (2017) Proteomic analysis of bronchoalveolar lavage fluid (BALF) from lung cancer patients using label-free mass spectrometry. BBA Clin 7:97–104CrossRefPubMedPubMedCentralGoogle Scholar
  80. 80.
    Carvalho AS, Cuco CM, Lavareda C, Miguel F, Ventura M, Almeida S et al (2017) Bronchoalveolar lavage proteomics in patients with suspected lung cancer. Sci Rep 7:42190CrossRefPubMedPubMedCentralGoogle Scholar
  81. 81.
    Fahrmann JF, Grapov DD, Wanichthanarak K, DeFelice BC, Salemi MR, Rom WN, Gandara DR, Phinney BS, Fiehn O, Pass H, Miyamoto S (2017) Integrated metabolomics and proteomics highlight altered nicotinamide- and polyamine pathways in lung adenocarcinoma. Carcinogenesis. pii: bgw205. [Epub ahead of print]
  82. 82.
    Shen Q, Cheng F, Song H, Lu W, Zhao J, An X, Liu M, Chen G, Zhao Z, Zhang J (2017) Proteome-scale investigation of protein allosteric regulation perturbed by somatic mutations in 7000 cancer genomes. Am J Hum Genet 100(1):5–20CrossRefPubMedGoogle Scholar
  83. 83.
    Backes C, Ludwig N, Leidinger P, Huwer H, Tenzer S, Fehlmann T, Franke A, Meese E, Lenhof HP, Keller A (2016) Paired proteomics, transcriptomics and miRNomics in non-small cell lung cancers: known and novel signaling cascades. Oncotarget 7(44):71514–71525CrossRefPubMedPubMedCentralGoogle Scholar
  84. 84.
    Xue M, Wei W, Su Y, Kim J, Shin YS, Mai WX, Nathanson DA, Heath JR (2015) Chemical methods for the simultaneous quantitation of metabolites and proteins from single cells. J Am Chem Soc 137(12):4066–4069CrossRefPubMedPubMedCentralGoogle Scholar
  85. 85.
    Wiwie C, Baumbach J, Röttger R (2015) Comparing the performance of biomedical clustering methods. Nat Methods 12:1033–1038CrossRefPubMedGoogle Scholar
  86. 86.
    Weber LM, Robinson MD (2016) Comparison of clustering methods for high-dimensional single-cell flow and mass cytometry data. Cytometry A 89(12):1084–1096CrossRefPubMedGoogle Scholar
  87. 87.
    Shi L, Zhu B, Xu M, Wang X (2017) Selection of AECOPD-specific immunomodulatory biomarkers by integrating genomics and proteomics with clinical informatics. Cell Biol Toxicol
  88. 88.
    Hwang M, Park HH, Choi H, Lee KY, Lee YJ, Koh SH (2017) Effects of aspirin and clopidogrel on neural stem cells. Cell Biol Toxicol
  89. 89.
    Chu MP, Kriangkum J, Venner CP, Sandhu I, Hewitt J, Belch AR, Pilarski LM (2017 Apr) Addressing heterogeneity of individual blood cancers: the need for single cell analysis. Cell Biol Toxicol 33(2):83–97. Scholar
  90. 90.
    Wang W, Zhu B, Wang X (2017 Oct) Dynamic phenotypes: illustrating a single-cell odyssey. Cell Biol Toxicol 33(5):423–427. Scholar
  91. 91.
    Chen C, Shi L, Li Y, Wang X, Yang S (2016 Jun) Disease-specific dynamic biomarkers selected by integrating inflammatory mediators with clinical informatics in ARDS patients with severe pneumonia. Cell Biol Toxicol 32(3):169–184. Scholar
  92. 92.
    Gu J, Wang X (2016 Feb) New future of cell biology and toxicology: thinking deeper. Cell Biol Toxicol 32(1):1–3. Scholar
  93. 93.
    Amodio G, Sasso E, D’Ambrosio C, Scaloni A, Moltedo O, Franceschelli S, Zambrano N, Remondelli P (2016 Aug) Identification of a microRNA (miR-663a) induced by ER stress and its target gene PLOD3 by a combined microRNome and proteome approach. Cell Biol Toxicol 32(4):285–303. Scholar
  94. 94.
    Wang X (2016 Oct) New biomarkers and therapeutics can be discovered during COPD-lung cancer transition. Cell Biol Toxicol 32(5):359–361. Scholar
  95. 95.
    Zhu D, Liu Z, Pan Z, Qian M, Wang L, Zhu T, Xue Y, Wu D (2016 Aug) A new method for classifying different phenotypes of kidney transplantation. Cell Biol Toxicol 32(4):323–332. Scholar
  96. 96.
    Xu M, Wang X (2017 Aug) Critical roles of mucin-1 in sensitivity of lung cancer cells to tumor necrosis factor-alpha and dexamethasone. Cell Biol Toxicol 33(4):361–371. Scholar
  97. 97.
    Wang W, Gao D, Wang X (2017) Can single-cell RNA sequencing crack the mystery of cells? Cell Biol Toxicol [Epub ahead of print]
  98. 98.
    Wang X (2016 Aug) CBT profiles of cabozantinib approved for advanced renal cell carcinomas. Cell Biol Toxicol 32(4):259–261. Scholar
  99. 99.
    Bao L, Zhang Y, Wang J, Wang H, Dong N, Su X, Xu M, Wang X (2016 Oct) Variations of chromosome 2 gene expressions among patients with lung cancer or non-cancer. Cell Biol Toxicol 32(5):419–435. Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Zheng Wang
    • 1
  • Xiaoju Zhang
    • 1
    • 2
  1. 1.Department of Respiratory and Critical Care MedicineZhengzhou University People’s HospitalZhengzhouChina
  2. 2.Biomedical Research CenterZhengzhou University People’s HospitalZhengzhouChina

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