A Reagent Resource to Identify Proteins and Peptides of Interest for the Cancer Community
2006; Elsevier BV; Volume: 5; Issue: 10 Linguagem: Inglês
10.1074/mcp.t600020-mcp200
ISSN1535-9484
AutoresBrian B. Haab, Amanda G. Paulovich, N. Leigh Anderson, Adam M. Clark, Gregory J. Downing, Henning Hermjakob, Joshua LaBaer, Mathias Uhlén,
Tópico(s)Advanced Proteomics Techniques and Applications
ResumoOn the basis of discussions with representatives from all sectors of the cancer research community, the National Cancer Institute (NCI) recognizes the immense opportunities to apply proteomics technologies to further cancer research. Validated and well characterized affinity capture reagents (e.g. antibodies, aptamers, and affibodies) will play a key role in proteomics research platforms for the prevention, early detection, treatment, and monitoring of cancer. To discuss ways to develop new resources and optimize current opportunities in this area, the NCI convened the "Proteomic Technologies Reagents Resource Workshop" in Chicago, IL on December 12–13, 2005. The workshop brought together leading scientists in proteomics research to discuss model systems for evaluating and delivering resources for reagents to support MS and affinity capture platforms. Speakers discussed issues and identified action items related to an overall vision for and proposed models for a shared proteomics reagents resource, applications of affinity capture methods in cancer research, quality control and validation of affinity capture reagents, considerations for target selection, and construction of a reagents database. The meeting also featured presentations and discussion from leading private sector investigators on state-of-the-art technologies and capabilities to meet the user community's needs. This workshop was developed as a component of the NCI's Clinical Proteomics Technologies Initiative for Cancer, a coordinated initiative that includes the establishment of reagent resources for the scientific community. This workshop report explores various approaches to develop a framework that will most effectively fulfill the needs of the NCI and the cancer research community. On the basis of discussions with representatives from all sectors of the cancer research community, the National Cancer Institute (NCI) recognizes the immense opportunities to apply proteomics technologies to further cancer research. Validated and well characterized affinity capture reagents (e.g. antibodies, aptamers, and affibodies) will play a key role in proteomics research platforms for the prevention, early detection, treatment, and monitoring of cancer. To discuss ways to develop new resources and optimize current opportunities in this area, the NCI convened the "Proteomic Technologies Reagents Resource Workshop" in Chicago, IL on December 12–13, 2005. The workshop brought together leading scientists in proteomics research to discuss model systems for evaluating and delivering resources for reagents to support MS and affinity capture platforms. Speakers discussed issues and identified action items related to an overall vision for and proposed models for a shared proteomics reagents resource, applications of affinity capture methods in cancer research, quality control and validation of affinity capture reagents, considerations for target selection, and construction of a reagents database. The meeting also featured presentations and discussion from leading private sector investigators on state-of-the-art technologies and capabilities to meet the user community's needs. This workshop was developed as a component of the NCI's Clinical Proteomics Technologies Initiative for Cancer, a coordinated initiative that includes the establishment of reagent resources for the scientific community. This workshop report explores various approaches to develop a framework that will most effectively fulfill the needs of the NCI and the cancer research community. Cancer is a leading cause of death worldwide, and the evolving nature of tumors challenges investigators who wish to understand the myriad molecular processes that govern tumor formation. Tumors often metastasize before they can be detected, making them difficult to effectively diagnose early, treat, and control. One potential solution to this problem is to develop clinical protein-based systems that can detect and monitor cancer processes. To be clinically useful, however, these high throughput proteomics technologies must identify low abundance proteins linked to cancer processes, be sufficiently specific and sensitive to support diagnostic monitoring applications, and be reproducible and scalable for clinical use. The National Cancer Institute (NCI) 1The abbreviations used are: NCI, National Cancer Institute; ATCC, American Type Culture Collection: a non-profit repository and worldwide distributor of various cell lines and primary cell types used for cell biology research; CPTI, Clinical Proteomics Technologies Initiative for Cancer: an initiative launched by the National Cancer Institute to accelerate advances in the prevention, diagnosis, and treatment of cancer through the use of proteomics technologies; HPA, Human Protein Atlas: an initiative funded by the Knut and Alice Wallenberg Foundation designed to allow the systematic exploration of the human proteome through affinity (antibody) proteomics, combining high throughput generation of affinity-purified (monospecific) antibodies with protein profiling using tissue arrays; HPR, Human Proteome Resource: located in Stockholm and Uppsala, Sweden, the HPR Center oversees the HPA and produces specific antibodies to human target proteins using a high throughput method involving the cloning and protein expression of protein epitope signature tags; IHC, immunohistochemistry; IP, intellectual property; PrEST, protein epitope signature tag: PrESTs are made in vitro from predicted coding regions of the human genome and are used to generate antibodies as part of an affinity-based proteomics strategy; SISCAPA, stable isotope standards and capture by anti-peptide antibodies: a methodology for quantitating peptides in complex digests using anti-peptide antibody chromatography and electrospray mass spectrometry; SOP, standard operating procedure: a set of instructions that serve as a guideline for those features of operations that lend themselves to a definite or standardized procedure without loss of effectiveness; XML, extensible markup language: a subset of standard generalized markup language, XML is a way to represent data that facilitates data sharing across different systems. convened the "Proteomic Technologies Reagents Resource Workshop" in Chicago, IL on December 12–13, 2005 to identify the cancer research community's expressed needs for validated and well characterized affinity capture reagents (e.g. antibodies, aptamers, and affibodies) to advance proteomics research platforms for the prevention, early detection, treatment, and monitoring of cancer. The workshop brought together leading scientists in proteomics research to discuss model systems for evaluating and delivering affinity reagents to the research community to support proteomics-based research. This workshop represented the latest effort in an ongoing dialogue between the NCI and the scientific community to enhance the applications of these technologies in discovery and translational research (1Proteomic Technologies for Early Cancer Detection Chantilly, VA. National Cancer Institute, Bethesda, MDApril 22–23, 2003Google Scholar, 2Clinical Proteomics and Biomarker Discovery in Cancer Research Bethesda, MD. National Cancer Institute, Bethesda, MDSeptember 24, 2004Google Scholar, 3Clinical Proteomics and Biomarker Discovery in Cancer Research (2), Menlo Park, CA. National Cancer Institute, Bethesda, MDNovember 5, 2004Google Scholar, 4Proteomic Technologies Informatics Workshop, Seattle, WA. National Cancer Institute, Bethesda, MDFebruary 8–9, 2005Google Scholar). On the basis of discussions with representatives from all sectors of the cancer research community, the NCI recognizes the immense opportunities to apply proteomics technologies to mission-critical problems in cancer research. In particular, the Institute addressed the community's concerns for access to affordable, well characterized, highly validated affinity reagents. A community resource that supports such reagents would accelerate biomarker discovery, cancer diagnostics development, and therapeutics monitoring. Based on these community needs, the Workshop Steering Committee invited speakers and guests to participate in discussions on a variety of topics, including the following. •A vision for a shared proteomics reagents resource•Opportunities to advance proteomics technologies for cancer research•Proposed models for an antibody reagent resource•Applications of affinity capture methods in cancer research•Affinity capture reagents and quality control/validation•Target selection•Database development•Next steps toward building a shared resource The meeting included presentations and discussions from leading industry representatives and academic investigators on state-of-the-art technologies and capabilities to meet the user community's needs. This workshop was developed as a component of the NCI's Clinical Proteomics Technologies Initiative for Cancer (CPTI; proteomics.cancer.gov), a coordinated initiative intended to evaluate, optimize, and advance proteomics technologies, informatics, and reagents to improve reliability and analytical validation (for a perspective on a proteomics initiative that incorporates a reagents resource, see Aebersold et al. (5Aebersold R. Anderson L. Caprioli R. Druker B. Hartwell L. Smith R. Perspective: a program to improve protein biomarker discovery for cancer.J. Proteome. Res. 2005; 4: 1104-1109Crossref PubMed Scopus (129) Google Scholar)). Launched in 2006, the CPTI is a 5-year, 104 million-dollar initiative comprised of three core technology development programs: the Clinical Proteomic Technology Assessment for Cancer, the Advanced Proteomic Technologies and Computational Sciences programs, and the Proteomic Technologies Reagents and Resources Core. Together these three programs are designed to increase the reliability and reproducibility of proteomics research results, thereby enabling these technologies to be translated ultimately to the clinical setting. The Clinical Proteomic Technology Assessment for Cancer and Advanced Proteomic Technologies and Computational Sciences programs are intended to fund research teams to rigorously assess and optimize current proteomics platforms and to push the envelope for innovative technologies and data analysis schemes, respectively. By contrast, the Proteomic Technologies Reagents and Resources Core will serve the broader biomedical and life science communities by organizing tools and reagents and enabling technologies to support protein/peptide measurement technology development efforts. These highly purified, standardized, and characterized reagents will be used to support improved approaches to sample preparation, fractionation, separation, detection, and quantitation for proteomics research. The CPTI is not itself a cancer biomarker discovery initiative but rather a technology-focused initiative designed to address current difficulties with the reproducibility of measurements, or the analytical validation, of proteomics platforms. In the absence of reliable measurements, it is difficult (if not impossible) to enable subsequent clinical validation of candidate biomarkers discovered using proteomics technologies. Such candidate biomarkers are only as reliable as the tools used to measure them. Reproducible proteomics research results will rely on high quality, well characterized, and easily accessible reagents, particularly affinity capture reagents such as antibodies. Optimized reagents will require detailed performance measurements across multiple platforms. This report will examine various aspects of affinity capture reagents and resources that will help fulfill the needs of the NCI and clinical proteomics researchers and enable the greatest impact on the cancer research community. The mapping of the human genome and advances in proteomics technologies have spurred interest in the application of molecular diagnostics (e.g. DNA- and protein-based biomarkers) to detect, diagnose, and treat various cancers. Successful utilization of DNA-based diagnostics in the treatment of cancer has been demonstrated by targeted antitumor agents such as trastuzumab (6Bartlett J.M. Pharmacodiagnostic testing in breast cancer: focus on HER2 and trastuzumab therapy.Am. J. Pharmacogenomics. 2005; 5: 303-315Crossref PubMed Scopus (28) Google Scholar), imatinib mesylate (7Deninger M.W. Druker B.J. Specific targeted therapy of chronic myelogenous leukemia with imatinib.Pharmacol. Rev. 2003; 55: 401-423Crossref PubMed Scopus (281) Google Scholar), erlotinib (8Comis R.L. The current situation: erlotinib (Tarceva) and gefitinib (Iressa) in non-small cell lung cancer.Oncologist. 2005; 10: 467-470Crossref PubMed Scopus (63) Google Scholar), and gefitinib (8Comis R.L. The current situation: erlotinib (Tarceva) and gefitinib (Iressa) in non-small cell lung cancer.Oncologist. 2005; 10: 467-470Crossref PubMed Scopus (63) Google Scholar). However, measurement of DNA-based molecular markers requires invasive sampling of tumor tissue, thus limiting approaches for targeted diagnostic and therapeutic applications of these markers. Hence despite these success stories, applications of DNA-based biomarkers of cancer to the prevention, early detection, treatment, and monitoring of disease have been limited to date. In contrast, circulating protein-based biomarkers offer a minimally invasive option to aid in the early detection of disease. Although molecular diagnostics represent critical elements for personalized disease screening and treatment, the successful translation of a diagnostic biomarker from discovery to routine clinical application remains relatively rare. The clinical value of a diagnostic tool is grounded in its robustness and reliability; the ability to measure a disease marker accurately (e.g. with high sensitivity and specificity), reproducibly, and rapidly ultimately determines the commercial application of the marker. Large scale assays and bibliometric searches have identified hundreds of candidate biomarkers for various cancers, creating a plethora of preliminary genomics and proteomics data. Sifting through this vast amount of information to test priority candidates requires sophisticated, selective, and high throughput molecular methodologies that include well characterized and validated assays and reagents. Profiling of differentially expressed proteins in normal and malignant tissues will support the development of a catalog of candidate biomarkers for various disease states (9Hudelist G. Singer C.F. Kubista E. Czerwenka K. Use of high-throughput arrays for profiling differentially expressed proteins in normal and malignant tissues.Anti-Cancer Drugs. 2005; 16: 683-689Crossref PubMed Scopus (16) Google Scholar, 10Patwardhan A.J. Strittmatter E.F. Camp II, D.G. Smith R.D. Pallavicini M.G. Comparison of normal and breast cancer cell lines using proteome, genome, and interactome data.J. Proteome Res. 2005; 4: 1952-1960Crossref PubMed Scopus (31) Google Scholar). Proteomics technologies enable the identification and measurement of these potential biomarkers of disease in serum, plasma (11Berhane B.T. Zong C. Liem D.A. Huang A. Le S. Edmondson R.D. Jones R.C. Qiao X. Whitelegge J.P. Ping P. Vondriska T.M. Cardiovascular-related proteins identified in human plasma by the HUPO Plasma Proteome Project pilot phase.Proteomics. 2005; 5: 3520-3530Crossref PubMed Scopus (78) Google Scholar), urine (12Grossman H.B. Soloway M. Messing E. Katz G. Stein B. Kassabian V. Shen Y. Surveillance for recurrent bladder cancer using a point-of-care proteomic assay.J. Am. Med. Assoc. 2006; 295: 299-305Crossref PubMed Scopus (217) Google Scholar), tissue (13Zhuang Z. Huang S. Kowalak J.A. Shi Y. Lei J. Furuta M. Lee Y.S. Lubensky I.A. Rodgers G.P. Cornelius A.S. Weil R.J. Teh B.T. Vortmeyer A.O. From tissue phenotype to proteotype: sensitive protein identification in microdissected tumor tissue.Int. J. Oncol. 2006; 28: 103-110PubMed Google Scholar), and tumor interstitial fluid (14Celis J.E. Gromov P. Cabezon T. Moreira J.M. Ambartsumian N. Sandelin K. Rank F. Gromova I. Characterization of the interstitial fluid perfusing the breast tumor microenvironment: a novel resource for biomarker and therapeutic target discovery.Mol. Cell. Proteomics. 2004; 3: 327-344Abstract Full Text Full Text PDF PubMed Scopus (268) Google Scholar). Combinatorial proteomics applications contribute to the understanding of the functional organization of the human proteome through characterizations and measurements of protein abundance, post-translational modifications, protein-protein interactions (15Stelzl U. Worm U. Lalowski M. Haenig C. Brembeck F.H. Goehler H. Stroedicke M. Zenkner M. Schoenherr A. Koeppen S. Timm J. Mintzlaff S. Abraham C. Bock N. Kietzmann S. Goedde A. Toksoz E. Droege A. Krobitsch S. Korn B. Birchmeier W. Lehrach H. Wanker E.E. A human protein-protein interaction network: a resource for annotating the proteome.Cell. 2005; 122: 957-968Abstract Full Text Full Text PDF PubMed Scopus (1858) Google Scholar), and correlation of disease phenotype with protein profiles (13Zhuang Z. Huang S. Kowalak J.A. Shi Y. Lei J. Furuta M. Lee Y.S. Lubensky I.A. Rodgers G.P. Cornelius A.S. Weil R.J. Teh B.T. Vortmeyer A.O. From tissue phenotype to proteotype: sensitive protein identification in microdissected tumor tissue.Int. J. Oncol. 2006; 28: 103-110PubMed Google Scholar). Applied clinical proteomics technologies offer a strong potential for early cancer detection and a strategy to evaluate tumor progression, response to treatment, metastasis (16Everley P.A. Zetter B.R. Proteomics in tumor progression and metastasis.Ann. N. Y. Acad. Sci. 2005; 1059: 1-10Crossref PubMed Scopus (14) Google Scholar), and recurrence (12Grossman H.B. Soloway M. Messing E. Katz G. Stein B. Kassabian V. Shen Y. Surveillance for recurrent bladder cancer using a point-of-care proteomic assay.J. Am. Med. Assoc. 2006; 295: 299-305Crossref PubMed Scopus (217) Google Scholar). However, reliably measuring the concentrations of these candidate cancer proteins at low levels (ng/ml to pg/ml) in plasma and other body fluids presents a bottleneck in the development of protein-based molecular diagnostics. Protein-based tests require precise, high throughput measurements enabled by highly characterized, validated affinity reagents. Yet biologically available proteins and potential biomarkers are being reported at a rate that outpaces the production and characterization of antibodies using conventional methodologies (17Chambers R.S. High-throughput antibody production.Curr. Opin. Chem. Biol. 2005; 9: 46-50Crossref PubMed Scopus (28) Google Scholar). Low throughput screening methods for monoclonal antibodies, arguably the optimal reagent of choice for proteomics analyses, have pushed the development of a number of automated, higher throughput approaches for antibody production (17Chambers R.S. High-throughput antibody production.Curr. Opin. Chem. Biol. 2005; 9: 46-50Crossref PubMed Scopus (28) Google Scholar, 18De Masi F. Chiarella P. Wilhelm H. Massimi M. Bullard B. Ansorge W. Sawyer A. High throughput production of mouse monoclonal antibodies using antigen microarrays.Proteomics. 2005; 5: 4070-4081Crossref PubMed Scopus (69) Google Scholar, 19Nilsson P. Paavilainen L. Larsson K. Odling J. Sundberg M. Andersson A.C. Kampf C. Persson A. Al-Khalili Szigyarto C. Ottosson J. Bjorling E. Hober S. Wernerus H. Wester K. Ponten F. Uhlen M. Towards a human proteome atlas: high-throughput generation of mono-specific antibodies for tissue profiling.Proteomics. 2005; 5: 4327-4337Crossref PubMed Scopus (205) Google Scholar, 20Angenendt P. Wilde J. Kijanka G. Baars S. Cahill D.J. Kreutzberger J. Lehrach H. Konthur Z. Glokler J. Seeing better through MIST: evaluation of monoclonal recombinant antibody fragments on microarrays.Anal. Chem. 2004; 76: 2916-2921Crossref PubMed Scopus (41) Google Scholar). As these techniques become more refined, reagent production should increase, making the characterization and analytical validation of these reagents increasingly crucial for broad application in proteomics. Well characterized and validated affinity capture reagents will be valuable and integral components in the development of advanced proteomics technology platforms. Innovative antibody-based methods to improve protein measurements, such as stable isotope standards and capture by anti-peptide antibodies (SISCAPA), are already being applied in mass spectrometry platforms to quantify peptides in complex mixtures (21Anderson N.L. Anderson N.G. Haines L.R. Hardie D.B. Olafson R.W. Pearson T.W. Mass spectrometric quantitation of peptides and proteins using Stable Isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA).J. Proteome Res. 2004; 3: 235-244Crossref PubMed Scopus (692) Google Scholar). Additionally the combination of microarray technology and proteomics reagents has led to the development of "proteome chips," which offer the potential for the multiplexed analysis of hundreds to thousands of proteins in parallel (22Ng J.H. Ilag L.L. Biomedical applications of protein chips.J. Cell. Mol. Med. 2002; 6: 329-340Crossref PubMed Scopus (28) Google Scholar, 23Zhu H. Bilgin M. Bangham R. Hall D. Casamayor A. Bertone P. Lan N. Jansen R. Bidlingmaier S. Houfek T. Mitchell T. Miller P. Dean R.A. Gerstein M. Snyder M. Global analysis of protein activities using proteome chips.Science. 2001; 293: 2101-2105Crossref PubMed Scopus (1928) Google Scholar). These chips represent a promising application for large scale, cost-effective screening for numerous proteomics applications, including identifying protein-drug and protein-lipid interactions and post-translational modifications (24Ptacek J. Devgan G. Michaud G. Zhu H. Zhu X. Fasolo J. Guo H. Jona G. Breitkreutz A. Sopko R. McCartney R.R. Schmidt M.C. Rachidi N. Lee S.J. Mah A.S. Meng L. Stark M.J. Stern D.F. De Virgilio C. Tyers M. Andrews B. Gerstein M. Schweitzer B. Predki P.F. Snyder M. Global analysis of protein phosphorylation in yeast.Nature. 2005; 438: 679-684Crossref PubMed Scopus (816) Google Scholar). Although antibodies are currently the most mature reagents for large scale applications, variability in design and production parameters and a shortage of economical, renewable capture reagents such as monoclonal antibodies have hampered extensive technological development and assessment of this platform. The development of affinity capture assays capable of surpassing the current validation standard, ELISA, is both costly and labor-intensive. Equally daunting is the reality that commercially available antibodies are often poorly annotated and are not validated for specific applications, leaving researchers guessing as to whether a particular antibody is appropriate to their research needs and resulting in a needless waste of time, money, and effort. The widespread availability of well characterized affinity reagents will greatly accelerate biomarker discovery and validation by facilitating time- and resource-intensive development of immunoassays to measure specific biomarker candidates. The field of proteomics and protein-based diagnostics has reached a stage for rapid advancement; tremendous opportunity exists to develop useful, meaningful resources to support future technology development and commercialization. A centralized (virtual) repository of affinity reagents with publicly available characterization/validation data will help to ensure reliable results and facilitate interlaboratory data comparison. Such a resource will greatly accelerate the development of proteomics technology platforms to identify protein biomarkers for the early detection of cancer and serve the greater research community as a hub to communicate and disseminate data and information. The workshop participants agreed that, to maximize impact, a shared reagents resource should 1) serve the broader scientific community; 2) coordinate efforts in characterization, validation, annotation, and database development; and 3) incorporate novel, inexpensive, scalable, high throughput technologies for future expansion to target the entire human proteome. These focal points advocate that the NCI and other funding institutions should use available resources to strike a balance between characterizing existing capture reagents, coordinating target selection for new reagents, and supporting advances in technology that will accelerate the production of new reagents. The current challenges that cancer investigators face with respect to affinity capture reagents may be illustrated by the case of monoclonal antibodies, currently the most mature affinity capture methodology. Numerous antibodies and commercial pipelines for antibody production are currently in place. However, the majority of antibodies are poorly characterized and not adequately validated for the variety of applications of interest to the research community (Table I). As such, the user must navigate through an increasingly complex marketplace to determine whether data are available on the binding characteristics of an antibody and whether the antibody is suitable for a specific application. For example, a query of Biocompare, an on-line search tool for scientific products and resources, for monoclonal antibodies to "p53" returns more than 1300 choices representing more than 50 vendors. These antibodies vary widely in application, design controls, validation parameters, supporting documentation, and cost. Conversely a search for emerging candidate biomarkers, such as "CA27.29," a recently identified candidate biomarker for breast cancer (251997 update of recommendations for the use of tumor markers in breast and colorectal cancer. Adopted on November 7, 1997, by the American Society of Clinical Oncology.J. Clin. Oncol. 1998; 16 ([No authors listed]): 793-795Crossref PubMed Scopus (143) Google Scholar), yields no results. Additionally a query for "CA15.3" identifies several vendors with available monoclonal antibodies to this candidate breast cancer marker, whereas a syntactical change to "CA 15.3" returns no results.Table IApplication-independent validation methods for antibodies (adapted from Uhlen et al. (26Uhlen M. Bjorling E. Agaton C. Szigyarto C.A. Amini B. Andersen E. Andersson A.C. Angelidou P. Asplund A. Asplund C. Berglund L. Bergstrom K. Brumer H. Cerjan D. Ekstrom M. Elobeid A. Eriksson C. Fagerberg L. Falk R. Fall J. Forsberg M. Bjorklund M.G. Gumbel K. Halimi A. Hallin I. Hamsten C. Hansson M. Hedhammar M. Hercules G. Kampf C. Larsson K. Lindskog M. Lodewyckx W. Lund J. Lundeberg J. Magnusson K. Malm E. Nilsson P. Odling J. Oksvold P. Olsson I. Oster E. Ottosson J. Paavilainen L. Persson A. Rimini R. Rockberg J. Runeson M. Sivertsson A. Skollermo A. Steen J. Stenvall M. Sterky F. Stromberg S. Sundberg M. Tegel H. Tourle S. Wahlund E. Walden A. Wan J. Wernerus H. Westberg J. Wester K. Wrethagen U. Xu L.L. Hober S. Ponten F. A human protein atlas for normal and cancer tissues based on antibody proteomics.Mol. Cell. Proteomics. 2005; 4: 1920-1932Abstract Full Text Full Text PDF PubMed Scopus (1015) Google Scholar))MethodDescriptionExamplesAdvantagesDisadvantagesAntigen-basedAssays based on the antigen used for immunizationELISA, protein arrays, Biacore SPR, antigen adsorptionCan be combined with affinity-based validationsNeed for pure and well characterized antigen; the binding to peptides or protein fragments might not be relevant for "real" applicationsTarget-basedAnalysis of native or partially denatured protein from natural sources (such as cell lysates)Western blot, immunohistochemistry, immunocaptureDoes not require the antigen used for immunizationIn the absence of the purified target, it is difficult to determine whether the antibody is binding to the target; usually relies on denatured targetsRNA-basedComparison of expression levels at the protein and RNA levelsTranscript profiling, in situ hybridizationsA huge set of data already publicly availableDifficult to know whether RNA levels correlate with protein levelsGenetics-basedThe use of genetic mutants or recombinant constructions to validate the targetTransgenetics, RNAi, GFP fusions (subcellular localization)If protein levels are observed to be increasing with an antibody or decreasing with an RNAi, then one can be relatively certain that the antibody is binding to the target.GFP fusions may be subject to artifactsDNA-basedBioinformatics analysis using predictive algorithms (as compared with experimental data)Signal peptide, transmembrane regions, localization signalsNo experimental evidence neededCan only be used as supportive evidence; must be complemented with experimental dataAffinity-basedDetermination of the kinetic parameters for the antibodyBiacore SPR, competition assaysGives binding parametersUsually done on antigens from "non-natural" sourcesEpitope-basedComparison of two or more antibodies directed to different parts of the same targetAntibodies to PrESTs or synthetic peptidesThe ultimate validation because identical patterns in various assays give strong support for specificity and lack of cross-reactivityRequires two independent antibodies to each target and also requires knowledge about the respective epitopes Open table in a new tab This example identifies several needs of the cancer research community. First, a set of well characterized and validated capture reagents with readily accessible supporting data will conserve resources by enabling investigators to rapidly determine reagent suitability for specific applications. Second, identifying the gaps in reagent needs will support the development of well characterized antibodies to prospective and emerging targets for which there is no established commercial market. Third, appropriate anno
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