Proteomics and diagnostics: Let's Get Specific, again

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Available online at www.sciencedirect.comsinof historical interest are antibodies; we shall try in this shortreview to compare binding specificity for both antibodiesan effecter of much of biology, often because of secretedproteins (such as growth factors) whose job is to moveextreme sensitivity and specificity.and aptamers and the ways in which proteomics might bescaled to deliver on the promise of high analyte density andthrough the blood to a nearby or distant site. In addition, avariety of proteins make their way into blood when somepathology causes localized cell death and the uninten-DOI 10.1016/j.cbpa.2008.01.016IntroductionSome years ago we published a short paper called LetsGet Specific [1] in which we tried to understand what wethought to be the extraordinary binding specificity ofaptamers [2,3]. We thought that elements of aptameraffinity and binding specificity were derived in part thelarge libraries used to find aptamers [often as many as 1015molecules for a SELEX experiment [4,5], and recentdevelopments [6]], as well as the structural possibilitiesexplored by single-stranded oligonucleotides. Morerecently we have focused our attention on the more generalnature of biochemical specificity, and we have wonderedabout the connection between reagent specificity andproteomics. When one considers proteomics, the reagentsProteomics and diagnostics: LetDom Zichi1, Bruce Eaton1,2, Britta SDNA array technology has changed all discussions aboutproteomics. Whole genome arrays allow unbiasedexperimentation, and the surprises that flow from thoseapproaches. Whole proteome proteomics is not possibletoday, and might never be possible unless experiments areguided by careful evaluation of reagent specificity. In this paperwe explore some possible ways to increase the content ofproteomic analysis.Addresses1 SomaLogic, 1775 38th Street, Boulder, CO 80301, USA2Department of Chemistry and Biochemistry, University of Colorado,Boulder, CO 80309, USA3Department of Molecular, Cellular and Developmental Biology,University of Colorado, Boulder, CO 80309, USACorresponding author: Zichi, Dom (, Eaton,Bruce (, Singer, Britta(, and Gold, Larry (,Current Opinion in Chemical Biology 2008, 12:7885This review comes from a themed issue onProteomics and GenomicsEdited by Natalie Ahn and Andrew H.-J. WangAvailable online 7th March 20081367-5931/$ see front matter# 2008 Elsevier Ltd. All rights reserved.A beautifully written (and referenced) recent review byBorrebaeck and Wingren [7] is aimed at a substantiallyCurrent Opinion in Chemical Biology 2008, 12:7885Get Specific, againger1 and Larry Gold1,3different question than we address in this article. Borre-baeck and Wingren have focused attention on theimpressive (and growing) list of improvements to variouscomponents of an antibody-based proteomic array. Ourfocus is on what specificity is possible with variousreagents, and to raise the possibility that array formatsmust solve any intrinsic limitations of those reagents.High analyte density is often abbreviated as content inthe case of nucleic acid arrays, content eventuallyincluded probes for entire genomes of viruses, bacteria,yeast, model organisms (flies, worms, and the mouse), andhumans. Using large arrays, scientists have utilizedmRNA and SNP profiling, along with epigenetic DNAmethylation, as genome-wide biomarker-discovery tech-nologies. All three platforms are possible because gen-ome-wide specific hybridization is possible that is, byjudicious use of proper probe lengths and appropriatebase composition along with the right temperature, bufferconditions, and hybridization time, specific sequencescan be recognized in the face of an entire genome.DNA chip technologies are remarkable as engineeringmarvels, but their discovery power flows from the highspecificity of nucleic acid hybridization. In fact, notsurprisingly, this same high specificity is the hallmarkof how nucleic acids perform their functions in biochem-istry. Remarkably, however, the array manufacturers havereached elegant solutions even as they built their contenton to compromised platforms. Probes bound to surfaces,be they beads (Luminex), slides (Agilent, Affymetrix,NimbleGen), or things in the middle (Illumina) presentless than perfect kinetics and slow approaches to equi-librium. These approaches are quite unlike hybridizationin solution as it was originally developed [8,9]. Only rarelydid platform builders include approaches that overcamethe slow kinetic approach to equilibrium (NanoGen,MetriGenix, PamGene, etc.), and those sensible plat-forms seem to have lost in the market place.Human diagnostics is better served by protein measure-ments than by nucleic acid measurements, and servedbest by protein measurements in blood samples (a matrixwith a vast number of proteins see below). Human bloodis an integrator of much of what happens in the body, andtional release of proteins. Since blood equilibrates quicklywith all human tissues, including brain, panels of proteinbiomarkers should become the earliest warnings one haswww.sciencedirect.comProteomics and diagnostics: Lets Get Specific, again Zichi et al. 79for the early stages of disease, even when a person isasymptomatic. Of course these same biomarkers can bepresent at vanishingly low concentrations and measuringthese low abundant proteins is the major hurdle proteo-mics must overcome.Of the approximately 23,000 human genes and their>100,000 encoded proteins (comprising splice variants,post-translationally modified proteins, and even more rareevents [10], we do not know how many proteins are foundin blood. Probably every human protein is present in bloodat a very low level (if only from cell death), and perhapsseveral thousand are present between the concentrations ofthe most abundant blood proteins (albumin at just under1 mM) down to protein concentrations at about 1 fM adynamic range of 12 logs or more! The problems in humanproteomics and diagnostics are to scale proteomics to highcontent to discover useful biomarkers and to make avail-able diagnostic products that utilize (smaller) panels ofproteins for specific medical purposes. That is, in the samespirit as made possible by nucleic acid array technologies,one must survey large fractions of the proteome content inan unbiased manner for novel biomarker discovery.One might think this is a simple task, given the stunningsuccess with nucleic acid arrays. The problem of course isthat typing nucleic acid complement sequences (probes) isa lot easier than understanding the biophysics of proteinrecognition biochemistry. Indeed, the allure of typingenthralled the antisense, ribozymes, and siRNA thera-peutic researchers with the hope that typing would be agreat way to identify new drugs. For proteomics the ideahas been to replace typing of nucleic acid complementswith typing orders to the antibody suppliers. However,when commercial antibodies are printed (as though theywere analogues of nucleic acid probes) and then testedwith various protein mixtures, performance (meaningspecificity) probably is not adequate. The purpose of thisreview is to discuss these attempts and the aptamer-basedalternatives, and to note the intrinsic kinetic problemsthat must be solved by proteomics.Reagent-free proteomicsWe mention briefly that reagent-free proteomics wouldbe a wonderful development, although it appears diffi-cult. Since 1975, with the publication of Pat OFarrellsextraordinary work on 2D gels [11], such reagent-freeproteomics has been possible. The quality of the first 2Dgels was amazingly high (something like 1100 proteinswere visible), major and minor proteins seemed to differquantitatively by three logs or so, and differently chargedspecies of the same molecular weight were not a majorsource of additional spots that cluttered the patterns. InPats thesis seminar he showed wild-type Escherichia coligels versus lactose-operon deletion gels, and the missingspots were a powerful demonstration of what might bedone, at least qualitatively.www.sciencedirect.comBlasting through many samples (tissue extracts or plasmaor serum, or urine, or whatever) with 2D gels had amoment (back in the day as our children say . . .).However, the problems with reproducibility and quanti-fication were serious, and the cost per analysis was high eventually people added MS to the methodology, and it isnow common for an entire 2D gel to be extracted (featureby feature) for MS analysis. Furthermore, the limitationsin protein number (content again) have never been solved Pat OFarrells number from E. coli really has remained,after a lot of work, about the number of protein spots onecan visualize, and the proteins observed are thus inevi-tably the most abundant proteins in the sample.Mass spectrometry (MS) has had a similar fate, so far.Even though the sensitivity of a great mass spectrometermight enable analysis of samples quite a bit lower thannmolar in a few microliters, when complex matrices areexplored the noise obscures all but the most abundantproteins. In fact, it appears that 2D gels and MS querymore or less the same most abundant proteins from withina complex sample. Clearly, the resolving power of 2D gelscoupled to MS in proteomics has yet to match what iscapable in DNA hybridization micro arrays.Reagent-dependent proteomics: antibodiesNo one really knows what fraction of the human pro-teome has been used to generate high quality antibodies[see the Human Protein Atlas (, [12]] or protein reagents with alternative frame-works [13]. The assumption has been that antibodyproduction could be scaled up to meet the need, andthat people would be able to print antibodies the sameway that people print nucleic acid probes.Just how specific are antibody reagents, and (thus) wouldan array of printed antibodies allow quantitative proteo-mics? Sadly we do not have a literature quite like thedefinitive literature for nucleic acid hybridization. TheTurner rules [14] and hundreds of other careful papers(e.g. [15,16,17] and many, many others) allow one tocalculate the likely interactions between two single-stranded oligonucleotides. Proteins are likely to interactwith other proteins with low affinity (comprising diffusionlimited association rates along with fast dissociationrates), but we have no rules. However, three independentlines of evidence suggest that proteins are sloppy in theirintermolecular interactions and that one ought to expectthe equivalent of error-prone DNA hybridization.First, phage display has been used to identify shortpeptides (many experiments were done with peptides10 amino acids in length) that will bind to a target protein[18,19]. Usually binding peptides are found, with Kdsbetween 1 mM and about 10 nM. The classic phagedisplay libraries in the early days contained roughly107 peptides, about the number present in the humanCurrent Opinion in Chemical Biology 2008, 12:7885proteome. Many peptides are found to bind weakly toalmost any target protein. Binding interactions of lowaffinity should be expected as noise in human biology.Second, intracellular protein-interaction maps have beenmade (and continue to be made) using some variant of theyeast two-hybrid system [20,21]. Again one fights noise whatever bait protein is used, many candidate proteinsemerge that interact weakly with the bait and are eithernoise or subtle reflections of meaningful biology it isvery difficult to tell which. Probably the ways that thetwo-hybrid system is tuned matters greatly if bothproteins are expressed at high intracellular levels, weakinteractions (probably reflecting mM Kds or even greater)are sufficient to activate transcription.Third, antibodies found in healthy people (these obser-vations are not about people who have known auto-immune disorders) react with roughly 28% of thehuman proteins [13]. This is an astonishing observation,and almost certainly most often reflects weak and unin-tended binding. That is, in the format employed, anti-bodies against other targets react with human proteins.But how could this be? Did not we learn that antibodiesare magic bullets? In fact, this platform is shown(Figure 1B below) and represents a particularly com-proteins. The slow effective dissociation rate results frommultivalent binding of antibodies to the wrong humanproteins.Antibody arrays: printed antibodies, reversearrays, and sandwich formatsThree kinds of protein-based proteomic arrays have beentried. The easy approach was to simply print antibodiesand see what would happen, and then to make evenbetter antibodies to see if performance was improved.These arrays are called antibody capture arrays and arecommercially available. When the difficulties of sensi-tivity and specificity with these arrays became clear,people tried reverse arrays in which, for example, plasmaor tissue homogenates were spotted directly on to asurface and probed with antibodies. For reasons visiblein Figure 1 reverse arrays may in fact be more specificthan antibody-capture arrays. Finally, people have triedvery hard to deploy antibody sandwiches onto an arrayformat.First, arrays of single antibodies are now available com-mercially (reviewed in Borrebaeck and Wingren, [7]).The content is impressive hundreds of antibodies areprobed (often) with a standard mixture of proteins and an80 Proteomics and Genomicshe c) And mpromised platform because of very slow effective dis-sociation rate constants for unintended non-targetFigure 1Specificity: A function of rebinding rates. In the binding reactions shown, tgreen or blue. Intrinsic on and off rates are identical in the examples. (Amixture of antigens. (B) Reverse arrays with homogenous antigen spots anexample tissue homogenate, probed with a single antibody. Intrinsic on andlimited on rates, with solution off rates). Rebinding rates (for cognate and incvery slow in (C).Current Opinion in Chemical Biology 2008, 12:7885unknown but similar mixture, with one mixture labeledwith one color dye and the other with another. While theBrown lab at Stanford was an early proponent of suchorrect interaction is blue with green. The wrong interactions are pink withtibody capture arrays, with single antibody in each spot, probed withixture of antibodies, for example plasma. (C) Mixed antigens spotted, foroff rates are identical in the examples (A), (B), and (C) (usually diffusionorrect interactions) are extremely fast in (B), somewhat slower in (A), andwww.sciencedirect.comProteomics and diagnostics: Lets Get Specific, again Zichi et al. 81experiments, using commercial antibodies [22], the stron-gest work thus far comes from Borrebaecks lab in Sweden[7]. Over several years that lab has developed surfacesfor printing antibodies, discovered which antibody frame-work was best at obtaining high quality antibodies withstable structures and good analyte recognition, and so on.The work is lovely. The use of such arrays becomesstraightforward. If, for example, a large number of plasmasamples from healthy women were mixed together andanother set of plasma samples from similar women withstage II ovarian cancer were compared on a large antibodyarray, any differences in the average protein concen-tration in the two sample sets would show up as a changein the ratio of dye #1 to dye #2 on a specific antibodyfeature. This now-standard experiment (patterned aftermRNA profiling arrays) has been reported several times[23,24,25], and soon will become a cottage industry. Wehope that data from antibody arrays will be confirmed byhigh quality ELISAs, used to probe the same plasmamixtures for that analyte (or, even better, each individualsample from the plasmas that made up each mixture [26]).The formalism is obvious oligonucleotide array (hybrid-ization) data are confirmed by something precise (QPCR)because even hybridization arrays (as specific as they are)do not guarantee that the measured oligonucleotide isthe intended oligonucleotide. The proteomics com-munity will learn about this problem, although slowly,exactly as the DNA-array community learned about theproblem.Figure 1A pictures the problem and suggests a key metricfor evaluating even very good antibody arrays. Putsimply, the burden of proof lies with the manufacturers,distributors, and academic scientists who claim highspecificity in array formats. The question is at leastpartially answered by spiking plasma samples withnon-human proteins at low concentrations to determinethe limit of detection and to measure background inunspiked plasma. We imagine that a set of (ten or so?)non-human proteins will become a standard specificitymetric so that various platforms and reagents may becompared. The severity of the problem goes beyondlimits of detection, of course. If an abundant protein inplasma binds inappropriately to an antibody selected fora non-abundant protein, the measured protein will not bethe intended analyte. This is a real issue if severalplasma proteins are 106 to 1012 times more abundant thanthe analyte of interest and those abundant proteins haveeven submicromolarKds for the capture antibodies aimedat the intended analyte, a significant fraction of the signalon that capture antibody will result from the wrongproteins, due only to equilibrium binding. Moreover,avidity/rebinding components can increase the noiseon an antibody array. Equilibrium binding for targetanalytes and all other proteins in a mixture is quite ahurdle to overcome in printed antibody arrays (and seenext paragraph).www.sciencedirect.comSecond, reverse-phase protein microarrays (RPAs) havebecome popular. A key reference is from the Petricoinand Liotta labs [27]. As shown in Figure 1C, multivalentrecognition in an RPA is unlikely a spotted tissue extractor plasma sample will have thousands of proteins, andstatistically it is unlikely that identical proteins will fallnear each other, and thus provide opportunities for multi-valent binding. However, in the review cited above, theauthors write that Currently the two biggest technicalchallenges facing this techniques are the need for specificantibodies and . . . We agree, but in fact this is just theequilibrium binding problem mentioned above, but noth-ing worse than that. Again, as previously mentioned,antibody specificity almost never is good enough to yieldbinding only to the intended analyte in the presence ofmany other vastly more abundant proteins. We believethis is inherent in the biochemistry of antibody CDRs(complementarity-determining regions) and cannot besolved easily even with recombinant antibody technol-ogy.There is, of course, an additional issue facing RPAs. Thespotted analytes are of uncertain protein state, fromnative to denatured and everything in between. Anti-bodies often are not well characterized with respect to thepreferred analyte structure, which could be an importantattribute in biology, and this must confound the use ofRPAs. The good news (and the bad) is that RPAs are easyto use, and thus another cottage industry has been born,but getting the right assay for the serious study of humanhealth is unlikely to be easy.Third, an enormous amount of time and money has beenspent trying to build arrays of antibody sandwiches. Weshow (Figure 2a) why sandwich assays won the battle forsingle analyte measurements for diagnostics specificity isthe product of the two specificities of the two antibodyreagents in a sandwich. If a capture antibody is bound byproteins other than the intended analyte, the secondantibody (which recognizes a different analyte epitope)will NOT also bind to the inappropriately capturedunwanted protein. One problem with adapting this sand-wich format for protein arrays is that any nonspecificallybound protein with a secondary antibody in the assay willnow signal for the wrong analyte (Figure 2b). As thesandwich array content grows, these nonspecific inter-actions will grow, limiting the practical size of this formatfor arrays of antibody sandwiches. The content limita-tions to sandwich arrays are depicted (Figure 2b) andargue powerfully that sandwich arrays will not be used fornovel biomarker discovery because they cannot scale tohigh content.So formats matter here (Figures 1 and 2). Forcing proteinprotein interactions as required to drive high contentproteomics arrays is in conflict with the rather delicatestructural integrity of these biopolymers. When proteinsCurrent Opinion in Chemical Biology 2008, 12:788582 Proteomics and GenomicsFigure 2within a printed feature are crowded they may denatureand further lose specificity. In addition, when the solublepartner is bivalent, weak binding might be sufficient forkinetic entrapment, which really is nothing more thanavidity (which is nothing more than artificially increasedrebinding rates or even multivalent binding caused bypacked proteins attached to the surface with close pack-ing). So these features substantial weak interactionsbetween many abundant proteins, along with bivalentprobes, must lead to measurements that are obscured bynoise.The take home message is clear: antibodies will bindmore specifically to protein analytes in solution or even inAntibody sandwich assays. (a) As shown, antibody sandwiches help with speare pink with green. The second antibody (dark green) provides additional srecognized by the second antibody. (b) The specificity is lost when many pro(red is the capture antibody, and brown is the secondary antibody) are addespecificity is lost.Current Opinion in Chemical Biology 2008, 12:7885cells or in blood than they will if they are used as captureantibodies or as antibody probes against printed humanproteins. Surprisingly, reverse arrays offer some advan-tages over antibody capture arrays, which we did notappreciate when we started writing this review.Reagent-dependent proteomics: aptamersOur colleagues and we have been working on aptamerarrays for almost two decades. We collectively come toproteomics from backgrounds in genetics, molecularbiology, biochemistry, and physical chemistry. For at leastten years we worked to format arrays of aptamers tomeasure proteins we even published a paper on a mixedsandwich protocol (using an aptamer and an antibody cificity. The correct interaction is blue with green. The wrong interactionspecificity and the incorrect interaction with the capture antibody is notteins are probed in the same assay. When antibodies to the pink antigend to the array, the wrong interaction in (a) will now generate signal[28]). Equilibrium binding assays led to comparable per-formance (and limitations) as those achieved by anti-bodies in any of the formats discussed above. Recently,we have been using kinetic manipulations so that mereequilibrium binding will not need to do the impossible to distinguish between the intended analyte and to notbind significantly to any abundant and inappropriateprotein.We have tried to solve the problems identified in thisreview article without using sandwich arrays (which prob-ably would not scale with aptamers any better than theyscale with antibodies, as in Figure 2). The principleobstacle we needed to overcome was to identify a secondspecificity element (beyond equilibrium binding) thatcould be built into the assay; at one point we workedvery hard on photo-crosslinking as the second specificityelement [29].We have had some success (Figure 3) at quantifying manyhuman proteins with aptamers that have both low Kds fortheir cognate proteins and higher Kds for the abundantproteins in plasma. In addition, we have been able toselect aptamers with very slow dissociation rates, some-thing we had tried to do unsuccessfully many times in thepast. These slow dissociation rates allow us to remove the(abundant) non-target proteins that would otherwise con-tribute to noise. Most importantly, we have been able toformat assays so that binding discrimination occurs insolution before array read-out.In Figure 3 we show some proteomic data, both for anaptamer-array with many proteins measured simul-taneously (Figure 3a), and spike-and-recovery exper-iments (Figure 3b) in 5% plasma (with an expectedneurotrophin-3 concentration of about 15 pM) and buf-fer. The significance of these data is that broad andquantitative measurements of (low) protein concen-trations are now available.The details of these experiments will be submittedshortly (personal communication from Dan Schneider,Sheri Wilcox, Jeff Carter, Marty Stanton, and many othersat SomaLogic). We continue to be instructed, intellec-tually, by the kinetic descriptions of John Hopfield fromdecades ago; his descriptions of the intrinsic problems ofProteomics and diagnostics: Lets Get Specific, again Zichi et al. 83Figure 3Multiplexed proteomics with aptamers work well. (a) Multiplexed readout of(blue) and 5% plasma (red) and measured on arrays.www.sciencedirect.comserum proteins with aptamers. (b) Neurotrophin-3 was spiked into bufferCurrent Opinion in Chemical Biology 2008, 12:788584 Proteomics and Genomicsspecific binding in a complex sample (cells or plasma or invitro) have much to say about sound experimentation[30,31].ConclusionsThis short review was intended at first to highlight theobvious: if one measures enough proteins in plasma inpeople with and without a variety of diseases, one oughtto be able to identify novel biomarkers that could be usedin small panels to facilitate appropriate evidence-basedmedical decisions for specific indications. Ultimately oneexpects that small specific proteomic panels will beaggregated into larger panels that enable more compre-hensive medical decisions to be made. This appears to usto be within reach [32].But as we wrote we came to the conclusion that novelbiomarker discovery is constrained by reagent limitations(with respect to limits of detection and content/scale) that is, old-fashioned biochemistry remains important.We find the work reviewed here (and also a lot we didnot review) to be stunning in its medical implications if(and only if) the reagents and/or platforms are up to thetask. We have tried to make clear what these old or newreagents must do for the dream to be realized. We areoptimists about the diagnostic and medical future throughproteomics.Conflicts of interest statementDr Eaton consults for SomaLogic. Drs Singer, Zichi, andGold are employees of SomaLogic.AcknowledgementsWe thank our colleagues at both SomaLogic and the University of Coloradofor hundreds of serious conversations.References and recommended readingPapers of particular interest, published within the period of review,have been highlighted as: of special interest of outstanding interest1.Eaton BE, Gold L, Zichi DA: Lets get specific: the relationshipbetween specificity and affinity. Chem Biol 1995, 2:633-638.Shows that the factors that contribute to high affinity are the same asthose that determine specificity.2. Tuerk C, Gold L: Systematic evolution of ligands by exponentialenrichment: RNA ligands to bacteriophage T4 DNApolymerase. Science 1990, 249:505-510.3. Ellington AD, Szostak JW: In vitro selection of RNA moleculesthat bind specific ligands. Nature 1990, 346:818-822.4. Schneider DJ, Feigon J, Hostomsky Z, Gold L: High-affinityssDNA inhibitors of the reverse transcriptase of type 1 humanimmunodeficiency virus. Biochemistry 1995, 34:9599-9610.5. Gold L: Oligonucleotides as research, diagnostic, andtherapeutic agents. J Biol Chem 1995, 270:13581-13584.6. Klussmann S: The Aptamer Handbook: Functional Oligonucleotides and their Applications Weinheim: Wiley-VCH;2006.An important collection of articles about aptamers that spans the rangefrom practical to theoretical.Current Opinion in Chemical Biology 2008, 12:78857.Borrebaeck CA, Wingren C: High-throughput proteomics usingantibody microarrays: an update. Expert Rev Mol Diagn 2007,7:673-686.A useful review of the state of the art of antibody microarrays.8. Nygaard AP, Hall BD: A method for the detection of RNADNAcomplexes. Biochem Biophys Res Commun 1963, 12:98-104.9. Gillespie D, Spiegelman S: A quantitative assay for DNARNAhybrids with DNA immobilized on a membrane. JMol Biol 1965,12:829-842.10.Birney E, Stamatoyannopoulos JA, Dutta A, Guigo R, Gingeras TR,Margulies EH, Weng Z, Snyder M, Dermitzakis ET, Thurman REet al.: Identification and analysis of functional elements in 1%of the human genome by the ENCODE pilot project.Nature 2007, 447:799-816.This work foreshadows the complete elucidation of the humantranscriptome, and leads to the possibility that far more of the genomethan expected appears as RNA one wonders if all such RNAs areimportant or represent noise from unavoidably sloppy DNA-dependentRNA polymerases.11. OFarrell PH: High resolution two-dimensional electrophoresisof proteins. J Biol Chem 1975, 250:4007-4021.12.Uhlen M: Mapping the human proteome using antibodies.Mol Cell Proteomics 2007, 6:1455-1456.A short overview of the HUPO Antibody Initiative and the Human ProteinAtlas program ( ME, Pozdnyakova I, Haines K, Mor G, Snyder M:Identification of differentially expressed proteins in ovariancancer using high-density protein microarrays.Proc Natl Acad Sci U S A 2007, 104:17494-17499.Uses protein microarrays to detect autoantibodies in sera to identifyproteins associated with ovarian cancer.14. Turner DH, Sugimoto N: RNA structure prediction. Annu RevBiophys Biophys Chem 1988, 17:167-192.15. SantaLucia J Jr: A unified view of polymer, dumbbell, andoligonucleotide DNA nearest-neighbor thermodynamics.Proc Natl Acad Sci U S A 1998, 95:1460-1465.16. MathewsDH, Sabina J, ZukerM, Turner DH:Expanded sequencedependence of thermodynamic parameters improvesprediction of RNA secondary structure. J Mol Biol 1999,288:911-940.17. Do CB, Woods DA, Batzoglou S: CONTRAfold: RNA secondarystructure prediction without physics-based models.Bioinformatics 2006, 22:e90-e98.18. Scott JK, Smith GP: Searching for peptide ligands with anepitope library. Science 1990, 249:386-390.19. Smith GP, Scott JK: Libraries of peptides and proteinsdisplayed on filamentous phage. Methods Enzymol 1993,217:228-257.20. Fields S, Song O: A novel genetic system to detectproteinprotein interactions. Nature 1989, 340:245-246.21. Young KH: Yeast two-hybrid: so many interactions, (in) so littletime. Biol Reprod 1998, 58:302-311.22. Marinelli RJ, Montgomery K, Liu CL, Shah NH, Prapong W,Nitzberg M, Zachariah ZK, Sherlock GJ, Natkunam Y, West RBet al.: The Stanford tissue microarray database. Nucleic AcidsRes 2007, 36:D871-D877.23. Wingren C, Ingvarsson J, Dexlin L, Szul D, Borrebaeck CA: Designof recombinant antibody microarrays for complex proteomeanalysis: choice of sample labeling-tag and solid support.Proteomics 2007, 7:3055-3065.24.Wingren C, Steinhauer C, Ingvarsson J, Persson E, Larsson K,Borrebaeck CA: Microarrays based on affinity-taggedsingle-chain Fv antibodies: sensitive detection ofanalyte in complex proteomes. Proteomics 2005,5:1281-1291.A description of the state of the art in recombinant antibody microarrays.25. Ellmark P, Ingvarsson J, Carlsson A, Lundin BS, Wingren C,Borrebaeck CA: Identification of protein expression signaturesassociated with Helicobacter pylori infection and gastricwww.sciencedirect.comadenocarcinoma using recombinant antibody microarrays.Mol Cell Proteomics 2006, 5:1638-1646.26. Mor G, Visintin I, Lai Y, Zhao H, Schwartz P, Rutherford T, Yue L,Bray-Ward P, Ward DC: Serum protein markers for earlydetection of ovarian cancer. Proc Natl Acad Sci U S A 2005,102:7677-7682.27.Gulmann C, Sheehan KM, Kay EW, Liotta LA, Petricoin EF 3rd:Array-based proteomics: mapping of protein circuitries fordiagnostics, prognostics, and therapy guidance in cancer.J Pathol 2006, 208:595-606.A description of the drawbacks and advantages of several formats ofmicroarrays used in proteomics.28. Drolet DW, Moon-McDermott L, Romig TS: An enzyme-linkedoligonucleotide assay. Nat Biotechnol 1996, 14:1021-1025.29.Petach H, Gold L: Dimensionality is the issue: use ofphotoaptamers in protein microarrays. Curr Opin Biotechnol2002, 13:309-314.Yet another discussion of obstacles on the path to high-densityproteomics.30.Hopfield JJ: Kinetic proofreading: a new mechanism forreducing errors in biosynthetic processes requiringhigh specificity. Proc Natl Acad Sci U S A 1974,71:4135-4139.One of our favorite papers of all time a clear exposition about thelimitations of equilibrium binding when searching for a needle in a hay-stack.31. Hopfield JJ, Yamane T, Yue V, Coutts SM: Directexperimental evidence for kinetic proofreading in aminoacylation of tRNAIle. Proc Natl Acad Sci U S A 1976,73:1164-1168.32.Kessler A: The End of Medicine: How Silicon Valley (and NakedMice) will Reboot your Doctor New York: Collins; 2006.An imaginative description of a better future for healthcare that dependson proteomic arrays and in vivo imaging.Proteomics and diagnostics: Lets Get Specific, again Zichi et al. Current Opinion in Chemical Biology 2008, 12:7885Proteomics and diagnostics: Let's Get Specific, againIntroductionReagent-free proteomicsReagent-dependent proteomics: antibodiesAntibody arrays: printed antibodies, reverse arrays, and sandwich formatsReagent-dependent proteomics: aptamersConclusionsConflicts of interest statementAcknowledgementsReferences and recommended reading