Conventional Msbased Proteomics Technologies

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The discovery, identification, and validation of proteins associated with a particular disease state is a difficult and laborious task. This process often requires hundreds, if not thousands, of samples to be analyzed. As mentioned earlier, the predominant proteomic method of disease biomarker discovery in use today is a combination of 2D-PAGE and MS [10]. In this method, proteins from two distinct samples (i.e., diseased vs. normal, treated vs. control, etc.) are analyzed via 2D-PAGE and their protein expression patterns compared. Protein spots of interest are excised from the gel, proteolytically or chemically digested, and the resultant peptides analyzed by MS to identify the protein. As a separation technique, 2D-PAGE provides excellent resolution of complex protein mixtures. The method, however, is limited by its laboriousness, the low sensitivity of conventional stains, and its inability to resolve proteins with extreme molecular weights, hydrophobicity, and isoelectric points. Regardless of the limitations of 2D-PAGE, it has proven to be a vital tool in proteomics.

An excellent example of the use of 2D-PAGE MS analysis for the discovery of potential cancer-related biomarkers is illustrated in the study by Chen et al. [11], who analyzed 93 lung adenocarcinomas and 10 uninvolved lung samples (Figure 4.1). After measuring and comparing the relative abundances of the individual protein spots, those that showed a difference in relative intensity were identified via peptide mapping using MALDI-MS or ESI-MS/MS.

FIGURE 4.1 (A) 2D-PAGE gel separation of proteins identified with silver staining from a stage I lung adenocarcinoma. The proteins are separated by isoelectric point (pi) in the first dimension and by molecular weight (MW) in the second dimension. (B-F) The outlined areas of part A showing proteins significantly increased in lung adenocarcinoma. (Reprinted from Chen et al. [11], used with permission from the American Association of Cancer Research.)

FIGURE 4.1 (A) 2D-PAGE gel separation of proteins identified with silver staining from a stage I lung adenocarcinoma. The proteins are separated by isoelectric point (pi) in the first dimension and by molecular weight (MW) in the second dimension. (B-F) The outlined areas of part A showing proteins significantly increased in lung adenocarcinoma. (Reprinted from Chen et al. [11], used with permission from the American Association of Cancer Research.)

Several candidate tumor markers were identified to be upregulated (1.4- to 10.6-fold) in lung adenocarcinomas when compared with normal lung tissue. Among these, the antioxidant enzyme AOE372, cytosolic inorganic pyrophosphatase (PPase), mu-class glutathione transferase 4 (GSTM4), and ubiquitin carboxy-terminal hydrolase L1 (UCHL1) were increased 10.6-, 7.6-, 4.0-, and 3.5-fold, respectively. The frequency of elevated expression of these proteins in lung adenocarcinomas was found to range from 35.5% to 96.8% among the 93 tumors examined. GSTM4 was the most consistently over-expressed protein, being upregulated in 96.8% of the tumors. Correlations were observed between overexpression of some proteins and specific clin-icopathological variables, including tumor differentiation (AOE372), tumor subhistology (PPase), and a positive smoking history (PPase and UCHL1). In addition, the increased abundance of both AOE372 and UCHL1 correlated with the upregulation of these genes at the mRNA level.

Identification of Clinically Useful Biomarkers

In the design of studies aimed to discover and ultimately use a clinically useful biomarker, a set of characteristics that define the acquisition and measurement of the biomarker needs to be established. For a biomarker to have the greatest impact it should be present within an easily obtainable sample, such as urine or blood. If a biomarker is only assayable within a sample that requires a biopsy to be recovered, it is likely to only be interrogated as a secondary screen to confirm the original diagnosis. Second, the assay to clinically measure and validate the overall positive predictive value (PPV) of the biomarker must be capable of screening thousands of samples in a high throughput manner. In an attempt to fulfill the first criterium, a major focus in proteomics is in the discovery of biomarkers within serum. The second criterium is absolutely necessary for the analysis of serum due to the wide variability in the protein content of serum from different individuals. Thousands of samples need to be assayed to ensure that the potential biomarker is indeed related to the pathophysiology or pathohistology of the disease state and is not simply a function of the variability within the serum of patients due to differences in diet, genetic background, lifestyle, etc. At first glance, serum presents many beneficial attributes for proteomic investigation, since it has a high protein content (i.e., 60-80 mg/mL), with many of these proteins being secreted and shed from cells and tissues [12]. Serum, however, is one of the most difficult proteome samples to characterize adequately. Unfortunately, serum proteins are present across an extraordinary dynamic range of concentration that is likely to span more than 10 orders of magnitude [13]. This large dynamic range exceeds the analytical capabilities of traditional proteomic methods, making the detection of lower abundance serum proteins extremely challenging. The protein

Plasma Protein Pie Chart
FIGURE 4.2 Pie chart representing the relative contribution of proteins within plasma. Twenty-two proteins constitute approximately 99% of the protein content of plasma.

content of serum is dominated by a handful of proteins, such as albumin, transferrin, haptoglobulin, immunoglobulins, and lipoproteins [14]. Indeed, only 10 proteins constitute 90% of the protein content of serum. Of the remaining 10%, 12 proteins make up 90% of this remaining total. In fact, only 1% of the entire protein content of serum is made up of proteins that are considered to be in low abundance and of great interest in proteomic studies in search of potential biomarkers (Figure 4.2).

SURFACE-ENHANCED LASER-DESORPTION/IONIZATION TIME-OF-FLIGHT MASS SPECTROMETRY

A major development in the use of MS as a diagnostic instrument has been fueled by the development of surface-enhanced laser-desorption/ionization time-of-flight MS (SELDI-TOF) [15]. Whereas HPLC-MS combines elution chromatography with MS, SELDI-TOF MS uses retention chromatography. Chromatographic surfaces arrayed on the surface of protein chips are used to retain proteins from complex mixtures according to some physicochemical property of the protein, such as hydrophobicity, charge, specific affinity, etc. After the protein mixture has been deposited on the protein-chip surface, it is washed and an energy-absorbing molecule (i.e., matrix) is applied. The proteins are then ionized and desorbed from the protein-chip surface using a nitrogen laser, and their molecular masses are measured by TOF MS.

The SELDI-TOF MS format enables proteins from a variety of complex biological specimens, such as serum, plasma, intestinal fluid, urine, cell lysates, and cellular secretion products, to be profiled in a high throughput manner [16]. In most cases biofluids can be added directly to the protein chip without the need for extensive sample processing steps prior to analysis. The sensitivity of the TOF MS enables protein profiles to be generated from as little as a single microliter of serum, and have been generated from as few as 25-50 cells [17]. SELDI-TOF MS has proved to be useful in the discovery of potential diagnostic markers and patterns for prostate [18], bladder [19], breast [20], and ovarian cancers [21]. While SELDI-TOF MS has been used primarily for the analysis of crude biological fluids, and its greatest potential is within the field of diagnostic medicine, it can also be used for more targeted studies, such as the characterization of phosphoproteins [22], glycoproteins [23], and protein-DNA interactions [24].

The SELDI-TOF MS Components

The most popular MS instrument to perform SELDI-TOF MS analysis is the PBS-II, manufactured by Ciphergen Biosystems Inc. [16]. The SELDI-TOF MS instrument is composed of three major components: the ProteinChip® arrays, the mass analyzer, and the data-analysis software.

Protein Chip Arrays

The ProteinChip arrays are the unique components that distinguish SELDI-TOF MS technology from other MS-based systems. The protein-chip arrays are composed of different chromatographic surfaces spotted onto a 10-mm-wide x 80-mm-long protein chip that is made of aluminum. Each chromato-graphic spot is 2 mm in diameter, and each protein chip contains either 8 or 16 of these spots. The chromatographic surfaces are designed to capture proteins based on either a chemical (anionic, cationic, hydrophobic, hydrophilic, metal ion, etc.) or biochemical (immobilized antibody, receptor, DNA, enzyme, etc.) interaction, as shown in Figure 4.3. Typically, chemically active surfaces retain whole classes of proteins, whereas biochemical surfaces are used to target a single protein of interest through a specific interaction with an affinity reagent, such as an antibody. The selectivity of the chemically active surfaces is illustrated in Figure 4.3B, which shows the protein profiles of a cell lysate using the different surfaces. Different surfaces retain different proteins, and these differences depend, for example, on the pH of the sample, when anion and cation exchange surfaces are used. While the chemically treated ProteinChip arrays are commercially available, the biochemical surfaces are generally custom-made by using an open preactivated platform, to which a bait molecule of choice, such as an antibody, is immobilized. Any crude extract or sample can be applied to the surface thus retaining those target proteins that interact with the bait molecule.

Anionic Cationtc Hydrophobie Meint Ion HydrophUlc

Anionic Cationtc Hydrophobie Meint Ion HydrophUlc

Antibody-Antigen Receptor-Ligand DNA-Protein Activated Snrface

Hydrophobie

IMAC-Cn

Cationic Exchange, pH 4 _ Cationtc Exchange, pH 7 Anionic Exchange, pH 9

Anionic Exchange, pH 5

20,000

FIGURE 4.3 The variety of ProteinChipw arrays available for sample preparation. (A) The upper arrays represent chemically modified chromatographic surfaces, while the bottom arrays are biochemically modified surfaces. Chemically modified surfaces are used to retain a group of proteins, while biochemically modified surfaces are typically used to isolate a specific protein or functional class of proteins. (B) Protein profile of a cell lysate on different ProteinChip surfaces. As shown in the figure for a selection of protein chips, the individual surfaces retain different groups of proteins, depending on their physiochemical properties. The proteins retained are also dependent on the pH of the sample for the cation and anion exchange surfaces.

Antibody-Antigen Receptor-Ligand DNA-Protein Activated Snrface

Hydrophobie

IMAC-Cn

FIGURE 4.3 The variety of ProteinChipw arrays available for sample preparation. (A) The upper arrays represent chemically modified chromatographic surfaces, while the bottom arrays are biochemically modified surfaces. Chemically modified surfaces are used to retain a group of proteins, while biochemically modified surfaces are typically used to isolate a specific protein or functional class of proteins. (B) Protein profile of a cell lysate on different ProteinChip surfaces. As shown in the figure for a selection of protein chips, the individual surfaces retain different groups of proteins, depending on their physiochemical properties. The proteins retained are also dependent on the pH of the sample for the cation and anion exchange surfaces.

The Mass Analyzer

The mass analyzer is a relatively simple TOF MS equipped with a pulsed UV nitrogen laser, as shown in Figure 4.4. While the acronym SELDI has become almost synonymous with this technology, in principle it is really a form of MALDI. Upon laser activation, samples become irradiated, causing the sample to be desorbed and ionized, analogous to the MALDI process. The ionized molecules are accelerated through the spectrometer under vacuum (the so-called TOF tube) toward an ion detector. The mass-to-charge ratio (m/z) of each species is recorded based on the time each species requires to pass through the TOF tube (i.e., its time-of-flight). The design of the mass analyzer is somewhat rudimentary when compared to higher-performance mass spectrometers, but the SELDI-TOF MS does have reasonably high sensitivity. While time-lag focusing is used to increase data resolution and mass accuracy,

FIGURE 4.4 Schematic diagram of the SELDI Ciphergen mass spectrometer. After sample preparation, the ProteinChip arrays are analyzed by a laser-desorption/ionization (LDI) time-of-flight mass spectrometer (TOF MS). The TOF MS measures the molecular weights of the various proteins that are retained on the array. For comparison purposes, the software associated with the SELDI Ciphergen instrument is capable of displaying the resultant data as either a spectral, map, or gel view.

FIGURE 4.4 Schematic diagram of the SELDI Ciphergen mass spectrometer. After sample preparation, the ProteinChip arrays are analyzed by a laser-desorption/ionization (LDI) time-of-flight mass spectrometer (TOF MS). The TOF MS measures the molecular weights of the various proteins that are retained on the array. For comparison purposes, the software associated with the SELDI Ciphergen instrument is capable of displaying the resultant data as either a spectral, map, or gel view.

the achievable mass accuracy is much less than that afforded using more conventional, high-resolution TOF MS instrumentation [25].

The Software

One of the original intents was to use SELDI-TOF MS to identify differences in the protein expression profiles of two or more distinct biological samples, such as diseased vs. healthy, treated vs. control, differentiated vs. immature, etc. [16,25]. Accordingly, the samples being analyzed are often quite complex, particularly in the field of biomarker discovery, in which clinical samples such as serum are measured. The resulting MS spectrum shows the relative abundance versus the m/z ratios of the detected proteins, as shown in Figure 4.5. To simplify the visual output, the spectrum can be displayed as a trace view, gel view, or map view. The recognition of peaks that show differences in intensity is simplified by converting the MS peak trace into a simulated 1D gel electrophoresis display (i.e., the gel view). The software also can be used to compare the displays and identify unique mass-spectral peaks or those that show a significant abundance difference in one of the samples via cluster

The Ipmn Spectrum

FIGURE 4.5 Representative spectrum examples of SELDI analysis of pancreatic juice samples bound to IMAC-3 cupper ProteinChip array. A peak of ~ 16,570 Da (arrow) was present in the four pancreatic juice samples from patients with pancreatic adenocarcinoma (PC4, PC8, PC18, PC24) but absent in the four patients with other pancreatic diseases (IPMN; islet cell tumor (ICT); serous cystadenoma (SC)). (Reprinted from Rosty et al. [26], used with permission from the American Association of Cancer Research.)

FIGURE 4.5 Representative spectrum examples of SELDI analysis of pancreatic juice samples bound to IMAC-3 cupper ProteinChip array. A peak of ~ 16,570 Da (arrow) was present in the four pancreatic juice samples from patients with pancreatic adenocarcinoma (PC4, PC8, PC18, PC24) but absent in the four patients with other pancreatic diseases (IPMN; islet cell tumor (ICT); serous cystadenoma (SC)). (Reprinted from Rosty et al. [26], used with permission from the American Association of Cancer Research.)

analysis. As described later in this chapter, significant software developments, both by the manufacture and independent laboratories, have enabled SELDI-TOF MS spectral data to be analyzed as a pattern rather than as individual peaks. It has been the analysis of the proteomic patterns that has propelled the use of SELDI-TOF MS as a potentially revolutionary diagnostic tool.

Protein Identification by SELDI-TOF MS

Essentially the SELDI-TOF MS spectrum is a low-resolution profile of molecular species that were retained on the protein-chip surface. The resolution, mass accuracy, and lack of MS/MS capabilities of the mass analyzer makes direct protein identification from complex mixtures extremely challenging, unless a protein of interest is selectively targeted using an affinity-based surface. So what is the value of the results? The value lies in the ability to obtain and compare spectra from a significant number of samples in a relatively short time period, with very little sample preparation or sophisticated chromatography. For example, a single operator can acquire mass spectra of >250 different samples in a single day. Ideally the ability to compare this number of samples will reveal a reliable biomarker signal that is unique to a particular disease state.

Once a signal that is consistently unique to a particular disease state has been recognized in a statistically empowered sample set, the next phase is to identify the potential biomarker. Due to the low-mass accuracy of the TOF MS used to acquire the proteomic spectrum, direct identification is generally impossible; however, invaluable information can be garnered from the SELDI analysis to design the necessary purification strategy. Matching its m/z recorded by SELDI-TOF MS with that measured during the purification process provides an assay to follow the purification of the potential biomarker. The purification strategy can be based on any type of chromatography; however, the type of protein chip that the protein(s) of interest binds to provides a useful starting point in the design of a purification scheme. Once isolated to a reasonable level of purity, high-resolution MS with tandem MS capabilities can then be used to identify the potential biomarker. A simpler approach would be to identify the differentially expressed proteins that are captured directly on the chip. In this procedure, the peak of interest is selected for tandem MS analysis directly off the protein chip without the need to isolate it from its complex matrix (i.e., serum). This procedure would be much easier, faster, and less costly. Fortunately, new ion sources are available that allow the protein chips to be analyzed using a hybrid triple quadrupole TOF MS (Qq-TOF MS). The aim is to use this high-resolution MS/MS capable instrument to directly identify peptides desorbed and ionized directly off the protein chip surface. While in theory this seems to be a reasonable approach, in practice this method is still unproved as being routine with clinical samples.

In some cases, however, investigators have been fortuitous in the identification of potential biomarkers using the SELDI-TOF MS. A good example of this is the recognition and eventual identification of abiomarker for pancreatic cancer by Rosty et al. [26]. This group's focus was on the identification of a reliable biomarker for pancreatic cancer, the fourth leading cause of cancer death in both men and women in the United States [27]. Few if any patients with pancreatic cancer are cured without resection, and unfortunately only 10-15% of patients are resectable at the time of diagnosis [28]. Current methods for diagnosing pancreatic cancer at an early stage are relatively ineffective. Their study used the SELDI-TOF MS method essentially as described earlier to analyze and compare the proteomic profiles of 15 pancreatic-juice samples from patients with pancreatic adenocarcinoma to those obtained from seven fluid samples acquired from patients with other pancreatic diseases. No samples were obtained from normal control patients, since all of the samples were collected from patients undergoing pancreatectomy. A peak with a molecular weight of ~ 16,570 Da was present in higher intensity in the pancreatic juice samples obtained from patients with pancreatic adenocarcinoma, as shown in Figure 4.6.

FIGURE 4.6 Disease diagnostics using proteomic patterns. The sample drawn from the patient is applied to a protein chip, which is made up of a specific chromatographic surface. After several washing steps and the application of an energy-absorbing molecule, the species that are retained on the surface of the chip are analyzed via mass spectrometry. The pattern of peaks within the spectrum is analyzed using sophisticated bioinformatic software to diagnose the source of the biological sample.

FIGURE 4.6 Disease diagnostics using proteomic patterns. The sample drawn from the patient is applied to a protein chip, which is made up of a specific chromatographic surface. After several washing steps and the application of an energy-absorbing molecule, the species that are retained on the surface of the chip are analyzed via mass spectrometry. The pattern of peaks within the spectrum is analyzed using sophisticated bioinformatic software to diagnose the source of the biological sample.

To identify this 16,572.9-Da protein, the investigators searched this mass against the masses of the proteins listed within the SWISS-PROT and TrEMBL protein databases. The mass approximately matched that of the secreted form of the human pancreatic-associated protein 1 (PAP-I), which has a calculated mass of 16,566.5 Da, and is known to originate within the pancreas. The match between the calculated mass of PAP-I and the experimentally determined mass was within the margin of error of the SELDI-TOF MS mass-measurement accuracy (i.e., ~1000 ppm). Due to the degeneracy of protein masses within the human databases, the identity of the peak at 16,572.9 Da required confirmation. To confirm the identification of this peak, the investigators performed a SELDI immunoassay by coupling an anti-hepatocarcinoma-intestine-pancreas (HIP)/PAP-I polyclonal antibody to a biochemically activated protein-chip surface and applying 12 of the different pancreatic-juice samples used in the original screening. Six of the samples were those in which the 16,572.9-Da peak was present, and six were those in which it was absent. The specific peak at mass 16,569.2 was present in all of the six samples that showed this peak in the original screening and not detected in the six samples that did not display the peak in the original screening. This peak was not detected in the control spots using an irrelevant antibody. Using this information, the investigators proceeded to develop an enzyme-linked immunosorbant assay (ELISA) to measure the levels of HIP and PAP-I in the pancreatic juice and serum of additional patients, providing a potentially simple, noninvasive diagnostic assay for early-stage pancreatic cancer. While this group was somewhat fortuitous, in that the mass of their proposed biomarker obtained from the initial screening matched that of a pancreatic-related protein, it still shows a useful example of the need of classic biochemistry techniques to identify the peaks that are seen within a SELDI-TOF MS profile.

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