Abstract
Progression from health to disease is accompanied by complex changes in protein expression in both the circulation and affected tissues. Large-scale comparative interrogation of the human proteome can offer insights into disease biology as well as lead to the discovery of new biomarkers for diagnostics, new targets for therapeutics, and can identify patients most likely to benefit from treatment. Although genomic studies provide an increasingly sharper understanding of basic biological and pathobiological processes, they ultimately only offer a prediction of relative disease risk, whereas proteins offer an immediate assessment of “real-time” health and disease status.
We have recently developed a new proteomic technology, based on modified aptamers, for biomarker discovery that is capable of simultaneously measuring more than a thousand proteins from small volumes of biological samples such as plasma, tissues, or cells. Our technology is enabled by SOMAmers (Slow Off-rate Modified Aptamers), a new class of protein binding reagents that contain chemically modified nucleotides that greatly expand the physicochemical diversity of nucleic acid-based ligands. Such modifications introduce functional groups that are absent in natural nucleic acids but are often found in protein–protein, small molecule–protein, and antibody–antigen interactions. The use of these modifications expands the range of possible targets for SELEX (Systematic Evolution of Ligands by EXponential Enrichment), results in improved binding properties, and facilitates selection of SOMAmers with slow dissociation rates.
Our assay works by transforming protein concentrations in a mixture into a corresponding DNA signature, which is then quantified on current commercial DNA microarray platforms. In essence, we take advantage of the dual nature of SOMAmers as both folded binding entities with defined shapes and unique nucleic acid sequences recognizable by specific hybridization probes. Currently, our assay is capable of simultaneously measuring 1,030 proteins, extending to sub-pM detection limits, an average dynamic range of each analyte in the assay of >3 logs, an overall dynamic range of at least 7 logs, and a throughput of one million analytes per week. Our collection includes SOMAmers that specifically recognize most of the complement cascade proteins. We have used this assay to identify potential biomarkers in a range of diseases such as malignancies, cardiovascular disorders, and inflammatory conditions. In this chapter, we describe the application of our technology to discovering large-scale protein expression changes associated with chronic kidney disease and non-small cell lung cancer. With this new proteomics technology—which is fast, economical, highly scalable, and flexible—we now have a powerful tool that enables whole-proteome proteomics, biomarker discovery, and advancing the next generation of evidence-based, “personalized” diagnostics and therapeutics.
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References
Biesecker G, Dihel L, Enney K, Bendele RA (1999) Derivation of RNA aptamer inhibitors of human complement C5. Immunopharmacology 42:219–230
Binz HK, Amstutz P, Pluckthun A (2005) Engineering novel binding proteins from nonimmunoglobulin domains. Nat Biotechnol 23:1257–1268
Bossuyt PMM (2011) The thin line between hope and hype in biomarker research. J Am Med Assoc 305:2229–2230
Bouchard PR, Hutabarat RM, Thompson KM (2010) Discovery and development of therapeutic aptamers. Annu Rev Pharmacol Toxicol 50:237–257
Diamandis EP (2010) Cancer biomarkers: can we turn recent failures into success? J Natl Cancer Inst 102:1462–1467
Ellington AD, Szostak JW (1990) In vitro selection of RNA molecules that bind specific ligands. Nature 346:818–822
Fassett RG, Venuthurupalli SK, Gobe GC, Coombes JS, Cooper MA, Hoy WE (2011) Biomarkers in chronic kidney disease: a review. Kidney Int 80:806–821
Floege J, Ostendorf T, Janssen U, Burg M, Radeke HH, Vargeese C, Gill SC, Green LS, Janjic N (1999) Novel approach to specific growth factor inhibition in vivo: antagonism of platelet-derived growth factor in glomerulonephritis by aptamers. Am J Pathol 154:169–179
Gold L, Ayers D, Bertino J, Bock C, Bock A, Brody EN, Carter J, Dalby AB, Eaton BE, Fitzwater T, Flather D, Forbes A, Foreman T, Fowler C, Gawande B, Goss M, Gunn M, Gupta S, Halladay D, Heil J, Heilig J, Hicke B, Husar G, Janjic N, Jarvis T, Jennings S, Katilius E, Keeney TR, Kim N, Koch TH, Kraemer S, Kroiss L, Le N, Levine D, Lindsey W, Lollo B, Mayfield W, Mehan M, Mehler R, Nelson SK, Nelson M, Nieuwlandt D, Nikrad M, Ochsner U, Ostroff RM, Otis M, Parker T, Pietrasiewicz S, Resnicow DI, Rohloff J, Sanders G, Sattin S, Schneider D, Singer B, Stanton M, Sterkel A, Stewart A, Stratford S, Vaught JD, Vrkljan M, Walker JJ, Watrobka M, Waugh S, Weiss A, Wilcox SK, Wolfson A, Wolk SK, Zhang C, Zichi D (2010) Aptamer-based multiplexed proteomic technology for biomarker discovery. PLoS One 5:e15004
Green LS, Jellinek D, Jenison R, Östman A, Heldin CH, Janjic N (1996) Inhibitory DNA ligands to platelet-derived growth factor B-chain. Biochemistry 35:14413–14424
Gupta S, Thirstrup D, Jarvis TC, Schneider DJ, Wilcox SK, Carter J, Zhang C, Gelinas A, Weiss A, Janjic N, Baird GS (2011) Rapid histochemistry using slow off-rate modified aptamers with anionic competition. Appl Immunohistochem Mol Morphol 19:273–278
Hori S, Gambhir SS (2011) Mathematical model identifies biomarker-based early cancer detection strategies and limitations. Sci Transl Med 3:109ra116 Hori et al. (2011) Mathematical model identifies biomarker-based early cancer detection strategies and limitations. Sci Transl Med 3:109ra116
Ioannidis JPA, Panagiotou OA (2011) Comparison of effect sizes associated with biomarkers reported in highly cited individual articles and in subsequent meta-analyses. J Am Med Assoc 305:2200–2210
Jemal A, Siegel R, Xu J, Ward E (2010) Cancer statistics 2010. CA Cancer J Clin 58:71–96
Kassis ES, Vaporciyan AA, Swisher SG, Correa AM, Bekele BN, Erasmus JJ, Hofstetter WL, Komaki R, Mehran RJ, Moran CA, Pisters KM, Rice DC, Walsh GL, Roth JA (2009) Application of the revised lung cancer staging system (IASLC Staging Project) to a cancer center population. J Thorac Cardiovasc Surg 138:412–418
Keefe AD, Pai S, Ellington A (2010) Aptamers as therapeutics. Nat Rev Drug Discov 9:537–550
Köhler G, Milstein C (1975) Continuous cultures of fused cells secreting antibody of predefined specificity. Nature 256:495–497
Levey AS, Atkins R, Coresh J, Cohen EP, Collins AJ, Eckardt KU, Nahas ME, Jaber BL, Jadoul M, Levin A, Powe NR, Rossert J, Wheeler DC, Lameire N, Eknoyan G (2007) Chronic kidney disease as a global public health problem: approaches and initiatives—a position statement from kidney disease improving global outcomes. Kidney Int 72:247–259
Lutz AM, Willmann JK, Cochran FV, Ray P, Gambhir SS (2008) Cancer screening: a mathematical model relating secreted blood biomarker levels to tumor sizes. PLoS Med 5:e170
Mehan MR, Ayers D, Thirstrup D, Xiong W, Zichi D, Ostroff RM, Brody EN, Walker, JJ, Gold L, Jarvis TC, Janjic N, Baird GS, Wilcox SK (2012) Protein signature of lung cancer tissues. PLoS ONE 7:e35157
Okada M, Nishio W, Sakamoto T, Uchino K, Yuki T, Nakagawa A, Tsubota N (2005) Effect of tumor size on prognosis in patients with non-small cell lung cancer: the role of segmentectomy as a type of lesser resection. J Thorac Cardiovasc Surg 129:87–93
Ostroff RM, Bigbee WL, Franklin W, Gold L, Mehan M, Miller YE, Pass HI, Rom WN, Siegfried JM, Stewart A, Walker JJ, Weissfeld JL, Williams S, Zichi D, Brody EN (2010a) Unlocking biomarker discovery: large scale application of aptamer proteomic technology for early detection of lung cancer. PLoS One 5:e15003
Ostroff R, Foreman T, Keeney TR, Stratford S, Walker JJ, Zichi D (2010b) The stability of the circulating human proteome to variations in sample collection and handling procedures measured with an aptamer-based proteomics array. J Proteomics 73:649–666
Pascual M, Steiger G, Estreicher J, Macon K, Volanakis JE, Schifferli JA (1988) Metabolism of complement factor D in renal failure. Kidney Int 34:529–536
Riemsdijk-van Overbeeke IC, Baan CC, Hesse CJ, Loonen EH, Niesters HG, Zietse R, Weimar W (2000) TNF-alpha: mRNA, plasma protein levels and soluble receptors in patients on chronic hemodialysis, on CAPD and with end-stage renal failure. Clin Nephrol 53:115–123
Stevens LA, Coresh J, Greene T, Levey AS (2006) Assessing kidney function—measured and estimated glomerular filtration rate. N Engl J Med 354:2473–2483
Tucker CE, Chen L-S, Judkins MB, Farmer JA, Gill SC, Drotel DW (1999) Detection and plasma pharmacokinetics of an anti-vascular endothelial growth factor oligonucleotide-aptamer (NX1838) in rhesus monkeys. J Chromatogr B 732:203–212
Tuerk C, Gold L (1990) Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase. Science 249:505–510
Vanholder R, Van Laecke S, Glorieux G (2008) The middle-molecule hypothesis 30 years after: lost and rediscovered in the universe of uremic toxicity? J Nephrol 21:146–160
Vaught JD, Bock C, Carter J, Fitzwater T, Otis M, Schneider D, Rolando J, Waugh S, Wilcox S, Eaton BE (2010) Expanding the chemistry of DNA for in vitro selection. J Am Chem Soc 132:4141–4151
Venturoli D, Rippe B (2005) Ficoll and dextran vs. globular proteins as probes for testing glomerular permselectivity: effects of molecular size, shape, charge, and deformability. Am J Physiol Renal Physiol 288:F605–F613
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Mehan, M.R. et al. (2013). Highly Multiplexed Proteomic Platform for Biomarker Discovery, Diagnostics, and Therapeutics. In: Lambris, J., Holers, V., Ricklin, D. (eds) Complement Therapeutics. Advances in Experimental Medicine and Biology, vol 735. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4118-2_20
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DOI: https://doi.org/10.1007/978-1-4614-4118-2_20
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