Mass spectrometry-based clinical proteomics profiling: current status ...

0 downloads 0 Views 248KB Size Report
15 Slany A, Haudek VJ, Gundacker NC et al. Introducing a new parameter for quality control of proteome profiles: consideration of commonly expressed proteins ...

Editorial For reprint orders, please contact [email protected]

Mass spectrometry-based clinical proteomics profiling: current status and future directions Expert Rev. Proteomics 6(5), 457–459 (2009)

Peter Findeisen Author for correspondence

Institute for Clinical Chemistry, Medical Faculty Mannheim of the University of Heidelberg, University Hospital Mannheim, TheodorKutzer-Ufer 1–3, D-68167 Mannheim, Germany

Michael Neumaier Institute for Clinical Chemistry, Medical Faculty Mannheim of the University of Heidelberg, University Hospital Mannheim, TheodorKutzer-Ufer 1–3, D-68167 Mannheim, Germany

“…new approaches for the development of MS-based profiling are emerging that comprise the development of both powerful and robust fractionation strategies.” Biomarker discovery and validation is a central application in current proteomic research to improve the diagnosis, treatment monitoring and prognosis of many diseases, including cancer, and vascular, neurological and autoimmune disorders. Mass spectrometry (MS)-based proteomics is heralded to offer substantial advantages over traditional antibody-based clinical assays, namely greater specificity, cost–effectiveness, time–effectiveness and the potential to multiplex up to hundreds of peptides in a single assay. The clinical proteomics profiling approach was initially defined as the direct application of proteomics technologies in combination with informatics tools to discover disease-associated changes in patterns of peptide profiles for direct diagnostic purpose [1] . However, it became increasingly evident that respective peaks within the peptidomics profiles needed to be identified [2] . Over the past few years, tremendous progress in MS instrumentation has been achieved that has fueled progress in the field. Modern proteomics methods comprise a plethora of heterogeneous techniques allowing not only protein and peptide patterns to be analyzed, but also biomarkers to be identified and quantified of. The MS-based biomarker discovery can be grouped into three main strategies: • Protein profiling methods that do not directly result in the identification of proteins but, rather, generate ‘fingerprints’ that are compared between individuals or samples


• Non-gel-based methods that rely on liquid chromatography (LC) coupled to MS for both quantitation and identification of proteins • 2DE to quantitate relative protein levels, followed by MS to identify proteins of interest Owing to good reproducibility and high-throughput capability, only the first two workflows are applicable for clinical proteomics approaches. Until now, most of the proteomics profiling studies have been performed using SELDI- or MALDI-TOF MS. The crude clinical samples are fractionated using simple one-step affinity chromatography on activated solid phases before MS ana­lysis [3] . By contrast, only a few profiling studies have employed complex profiling strategies that couple LC [4] or capillary electrophoresis directly with MS [5] . These MS-based techniques can be applied easily to a variety of clinical specimens, including serum, plasma, urine or tissue samples. Specifically, the capillary electrophoresis MS ana­lysis of urine has evolved as one of the most attractive approaches in clinical proteomics that has advanced to be introduced for diagnostic testing in the near future [6] . However, the vast majority of all studies with serum and plasma specimens has serious shortcomings, and most of the results could not be validated independently [7] . This is owing to major obstacles that are related to the lack of standardization regarding preanalytical, analytical and postanalytical variabilities, thus, making it difficult to compare results from different profiling studies [8] .

© 2009 Expert Reviews Ltd

ISSN 1478-9450



Findeisen & Neumaier

Specifically, the preanalytical variabilities in sample handling and processing cause substantial changes of MS peptide profiles  [9] . Indeed, the powerful diagnostic performance of many proteomics profiling studies has shown to be related to undetected preanalytical bias [10,11] . However, the rigorous standardization that is necessary to keep the peptidomic profiles reproducible can hardly be integrated into routine laboratory testing, and it is highly questionable, if crude MS patterns will ever mature for diagnostic applications [12] . Finally, the wide dynamic range of protein abundance in clinical specimens, such as serum or plasma, is another hurdle of clinical proteomics approaches. Owing to the limited fractionation power of high-throughput sample-preparation procedures, such as solid-phase extraction protocols, the candidate biomarkers of most profiling studies represent merely fragments of highabundance proteins rather than specific disease-associated gene products [13] . To summarize the current status of clinical proteomics profiling, it has to be recognized that the majority of the published data are questionable at best and not in accordance with current recommendations [14] . The poor quality of many of the early ‘proof-of-principle’ studies was clearly damaging to the field, but the upside is that the requirements for standardization, as well as robustness of study designs, were recognized. Consequently, procedures for quality assessment of proteomics data have been suggested [15] . To increase independent reproducibility of published data the standards initiative of the Human Proteome Organization has released recommendations concerning minimal information about a proteomics experiment [16] . In addition, the National Cancer Institute has taken a lead role in this process and the Early Detection Research Network was initiated for streamlined discovery and evaluation of promising biomarkers and technologies. The difficulties to develop valid biomarkers may not be underestimated and efforts from an organized community that allow continuous progression from discovery to validation are a prerequisite of current research [17] . In addition to the improvement of existing approaches, new concepts are emerging that might alleviate current limitations in clinical proteomics profiling. The development of powerful fractionation strategies for targeted enrichment of biomarkers is straight forward for detecting low-abundance ‘real’ biomarkers among high-abundance proteins  [18] . Post-translational modifications of proteins, such as glycosylation, are known to play a major role in pathophysiological processes, and the selective enrichment of the informationrich glycoproteome effectively reduces the complexity of the analytes  [19] . By contrast, the simple depletion of high-abundance serum proteins to improve sensitivity is highly controversial, since biomarkers might be attached to carrier proteins, such as albumin  [20] , and are codepleted. The immuno-MS assays have comparable sensitivity to conventional ELISAs but specificity can clearly be improved [21] . However, the availability of appropriate antibodies is limiting to these approaches. Another unbiased fractionation strategy is the use of combinatorial ligand libraries to concentrate the low-abundance proteome [22] . This technique 458

is mainly used to exhaustively decipher different subcellular proteomes but the diagnostic applicability seems to be limited. The direct ana­lysis of tissue sections [23] and cellular sub­populations [24] can also circumvent sensitivity problems and preserves the spatial distribution of biomarkers; however, the standardization of these approaches remains a matter of debate. Recently, functional protease profiling has been proposed as a new diagnostic approach to alleviate current limitations of MS-based profiling [25] . The dysregulation of protease activity has been implicated in numerous diseases, including cancer. The spiking of exogenous reporter peptides into serum for characterization of protease activity offers substantial advantages over profiling of ‘native’ serum with respect to improved standardization [25–27] . Specifically, the reaction conditions for the proteolytic degradation of reporter peptides can easily be standardized, and reproducibility problems related to variations in sample collection, storage and handling are eliminated effectively [25] . Furthermore, such assays would allow amplification of the output signals, thus, potentially visualizing low-abundance proteases activity in a complex proteome background [26] . This approach is very similar to established diagnostic assays measuring the proteolytic activity of distinct enzymes, such as coagulation factors [28] . Although the preliminary data for MS-based protease profiling are very promising, the rigorous prospective and independent validation is lacking. Conclusion & outlook

The hype of clinical proteomics profiling triggered by early enthusiastic reports [29] has rapidly changed into suspicion [30] but may give way to cautious optimism. If current guidelines are implemented in the study design, MS-based clinical proteomics profiling is a solid and promising approach that offers several advantages over traditional laboratory ana­lyses, including multiplexing capability, unbiased detection of new biomarkers and the possibility of automation and high-throughput ana­lysis. However, new approaches for the development of MS-based profiling are emerging that comprise the development of both powerful and robust fractionation strategies. Besides the demands for ‘simple’ quantitation and identification of biomarkers, there is a growing need to elucidate the functionality of proteins. Modern proteomics methods will increasingly be challenged to detect different post-translational modifications, complex formations, spatial distributions and enzymatic activities of distinct proteins. The constantly growing progress in this field will, hopefully, introduce clinical proteomics profiling as a valuable diagnostic tool in the near future. Financial & competing interests disclosure

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of this manuscript. Expert Rev. Proteomics 6(5), (2009)

Mass spectrometry-based clinical proteomics profiling



McLerran D, Grizzle WE, Feng Z et al. SELDI-TOF MS whole serum proteomic profiling with imac surface does not reliably detect prostate cancer. Clin. Chem. 54(1), 53–60 (2008).


Sparbier K, Wenzel T, Dihazi H et al. Immuno-MALDI-TOF MS: new perspectives for clinical applications of mass spectrometry. Proteomics 9(6), 1442–1450 (2009).


Boschetti E, Righetti PG. The art of observing rare protein species in proteomes with peptide ligand libraries. Proteomics 9(6), 1492–1510 (2009).


Cornett D, Reyzer M, Chaurand P, Caprioli R. MALDI imaging mass spectrometry: molecular snapshots of biochemical systems. Nat. Methods 4(10), 828–833 (2007).


Borro M, Gentile G, Stigliano A, Misiti S, Toscano V, Simmaco M. Proteomic analysis of peripheral T lymphocytes, suitable circulating biosensors of strictly related diseases. Clin. Exp. Immunol. 150(3), 494–501 (2007).


Findeisen P, Post S, Wenz F, Neumaier M. Addition of exogenous reporter peptides to serum samples before mass spectrometrybased protease profiling provides advantages over profiling of endogenous peptides. Clin. Chem. 53(10), 1864–1866 (2007).


Villanueva J, Nazarian A, Lawlor K, Yi SS, Robbins RJ, Tempst P. A sequence-specific exopeptidase activity test (SSEAT) for ‘functional’ biomarker discovery. Mol. Cell. Proteomics 7(3), 509–518 (2008).


Pusch W, Flocco M, Leung SM, Thiele H, Kostrzewa M. Mass spectrometry-based clinical proteomics. Pharmacogenomics 4(4), 463–476 (2003).


Diamandis E. Serum proteomic profiling by matrix-assisted laser desorptionionization time-of-flight mass spectrometry for cancer diagnosis: next steps. Cancer Res. 66(11), 5540–5541 (2006).


Liebler DC. Summary of United States Human Proteome Organisation (HUPO) symposium entitled ‘Standardized clinical proteomics platforms’. Mol. Cell. Proteomics 8(5), 1165–1166 (2009).

Cazares L, Diaz J, Drake R, Semmes O. MALDI/SELDI protein profiling of serum for the identification of cancer biomarkers. In: Clinical Proteomics: Methods in Molecular Biology. Antonia V (Ed.). Springer, UK, 125–140 (2008).


Koomen J, Shih L, Coombes K et al. Plasma protein profiling for diagnosis of pancreatic cancer reveals the presence of host response proteins. Clin. Cancer Res. 11(3), 1110–1118 (2005).


Mischak H, Apweiler R, Banks R et al. Clinical proteomics: a need to define the field and to begin to set adequate standards. Proteomics Clin. Appl. 1(2), 148–156 (2007).


Slany A, Haudek VJ, Gundacker NC et al. Introducing a new parameter for quality control of proteome profiles: consideration of commonly expressed proteins. Electrophoresis 30(8), 1306–1328 (2009).


Taylor C, Paton N, Lilley K et al. The minimum information about a proteomics experiment (MIAPE). Nat. Biotechnol. 25(8), 887–893 (2007).









Qian WJ, Jacobs JM, Liu T, Camp DG, Smith RD. Advances and challenges in liquid chromatography-mass spectrometrybased proteomics profiling for clinical applications. Mol. Cell. Proteomics 5(10), 1727–1744 (2006). Weissinger E, Wittke S, Kaiser T et al. Proteomic patterns established with capillary electrophoresis and mass spectrometry for diagnostic purposes. Kidney Int. 65(6), 2426–2434 (2004). Decramer S, Gonzalez de Peredo A, Breuil B et al. Urine in clinical proteomics. Mol. Cell. Proteomics 7(10), 1850–1862 (2008). Callesen AK, Vach W, Jorgensen PE et al. Reproducibility of mass spectrometry based protein profiles for diagnosis of breast cancer across clinical studies: a systematic review. J. Proteome Res. 7(4), 1395–1402 (2008). Findeisen P, Neumaier M. Mass spectrometry based proteomics profiling as diagnostic tool in oncology: current status and future perspective. Clin. Chem. Lab. Med. 47(6), 666–684 (2009). Findeisen P, Sismanidis D, Riedl M, Costina V, Neumaier M. Preanalytical impact of sample handling on proteome profiling experiments with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Clin. Chem. 51(12), 2409–2411 (2005). McLerran D, Grizzle WE, Feng Z et al. Analytical validation of serum proteomic profiling for diagnosis of prostate cancer: sources of sample bias. Clin. Chem. 54(1), 44–52 (2008).



Hanash S. It takes a village to develop biomarkers. J. Proteome Res. 6(9), 3362 (2007).


Hoffman S, Won AJ, Echan L, Speicher D. Higher dimensional (Hi-D) separation strategies dramatically improve the potential for cancer biomarker detection in serum and plasma. J. Chromatogr. B 849(1–2), 43–52 (2007).


Findeisen P, Peccerella T, Post S, Wenz F, Neumaier M. Spiking of serum specimens with exogenous reporter peptides for mass spectrometry based protease profiling as diagnostic tool. Rapid Commun. Mass Spectrom. 22(8), 1223–1229 (2008).


Schiess R, Wollscheid B, Aebersold R. Targeted proteomic strategy for clinical biomarker discovery. Mol. Oncol. 3(1), 33–44 (2009).


Witt I. Test systems with synthetic peptide substrates in haemostaseology. Eur. J. Clin. Chem. Clin. Biochem. 29(6), 355–374 (1991).


Lopez M, Mikulskis A, Kuzdzal S et al. A novel, high-throughput workflow for discovery and identification of serum carrier protein-bound peptide biomarker candidates in ovarian cancer samples. Clin. Chem. 53(6), 1067–1074 (2007).


Petricoin E, Ardekani A, Hitt B et al. Use of proteomic patterns in serum to identify ovarian cancer. Lancet 359(9306), 572–577 (2002).


Diamandis E. Peptidomics for cancer diagnosis: present and future. J. Proteome Res. 5(9), 2079–2082 (2006).


Suggest Documents