**5. Future trends**

#### **5.1 Immuno-SRM (SISCAPA)**

The comprehensive qualitative protein identification capability of the MudPIT approaches, can be extended to include relative quantitative features made possible with the use of multiplex stable isotope labelling strategies at the protein or peptide level. As already discussed, the quantitative capability will further minimize analytical systematic error and to better stratify patients in accordance to prostate pathophysiology analogous to that of the

chromatographic retention time window) while at the same time reducing their co-elution (improved separation efficiency). It is precisely these chromatographic characteristics that allowed the enhancement of the nano-electrospray ionization of the eluting peptides followed by their tandem mass spectrometry. The end result from this process was the generation of more information rich tandem mass spectra at improved S/N ratios, which

Consequently, the collective analytical attributes of this milestone 3-D MudPIT analysis study of BPH sera resulted in the identification of proteins differing by approximately 12 orders concentration range in terms of their native abundance levels in the naturally occurring serum matrix (as measured with bioassay technique such as ELISA). In addition to this extensive dynamic range coverage, the study identified 1955 proteins with a wide spectrum of biological and physico-chemical properties. A key component however to this proteome including the detection of secreted, tissue-specific proteins also found to be differentially expressed in the respective BPH tissue reported (S. D. Garbis et al., 2008). This constitutes a hallmark feature in the effective discovery of serum protein markers that reflect the pathophysiology of a specific organ tissue of interest. An additional performance characteristic of the 3-D study method is its accuracy and sensitivity in identifying close to 400 phosphoproteins of potential importance to cancer biology. The identification of the phosphorylated variant to a potential protein marker imparts an additional molecular feature in the more precise capturing of unique chemical signatures of disease. This is based on the notion that a phosphorylated motif may signify the induction or silencing of a potential physiologic protein target already discussed. The versatility and adaptability of the method's constituent techniques permit the incorporation of label-based or label-free strategies to impart a quantitative feature for the in-depth proteome analysis of any given

biological specimen derived from tissue, blood plasma or serum, and cell culture.

approaches such as those based on Immuno-MRM techniques discussed below.

**5. Future trends** 

**5.1 Immuno-SRM (SISCAPA)** 

The tissue-surrogate serum proteins detected in this study and other MudPIT studies allow for the un-biased and in-depth discovery of useful biomarkers without recourse to the targeted antibody capture approach, as is common the case. In contrast, the Medical Therapy of Prostatic Symptoms (MTOPS) clinical trial, attempted to characterize potential biomarkers that could stratify the BPH patients according to their response to medical therapy, by using the *a priori* use of the ELISA assay (Mullins et al., 2008). However, such an *a priori* approach bypassed the possibility in observing unexpected low-abundant tissue specific and secreted proteins that might play a significant role on the differential diagnosis between BPH and PCa. Conclusively, the MudPIT approach is definitely a forward trend in the establishment of novel proteins marker that can be validated with more targeted

The comprehensive qualitative protein identification capability of the MudPIT approaches, can be extended to include relative quantitative features made possible with the use of multiplex stable isotope labelling strategies at the protein or peptide level. As already discussed, the quantitative capability will further minimize analytical systematic error and to better stratify patients in accordance to prostate pathophysiology analogous to that of the

constitutes the ultimate objective for any effective MS based method.

BPH/PCa prostate tissue study reported by the authors. Such an approach can serve as part of a more systematic serum biomarker discovery study that can eventually lead to their validation over a very large number of specimens from healthy and diseased patient cohorts, typically exceeding 1000 for each group. So far, however, and despite the advancements made in analytical technologies, the discovery and validation of robust protein biomarkers with good specificity and sensitivity has been very disappointing. This low return on investment is due to several factors. One of them is due to the lack of functional or mechanistic utility of the candidate biomarkers. This lack of mechanistic relevance also applies to proteins that exhibit a significant differential expression between the healthy and disease samples. Another factor is associated with the large biological heterogeneity of the specimens tested. Unless the clinical samples have well defined inclusion and inclusion criteria along with effective sample procurement and handling protocols at statistically significant numbers to address a hypothesis at hand (i.e., power analysis), the analytical output will lack accuracy and precision to be of any value to the clinician (Adewale et al., 2008; Anderson, 2010; Barelli et al., 2007; Farrah et al., 2011). Another impediment is the lack of lower-cost and high-throughput validation protocols to compensate for the large number of samples that need to be analyzed. This is further compounded by the lack of antibodies for the vast majority of candidate proteins needed for the development of an ELISA kit, which is the only suitable bioassay for protein measurements in serum or plasma. Yet another limitation relates to the unreliability of a significant number of commercially available ELISA kits due to their lack of sufficient antibody validation in terms of their selectivity, cross-reactivity, linear dynamic range and sensitivity(Bordeaux et al., 2010; Stoevesandt & Taussig, 2007). An additional factor to the high failure rate of the effectiveness of the ELISA assay is that its development is principally based on recombinant protein standards that do not capture the level of complexity of the protein as it exists its *in vivo* modification status within the context of its biological matrix and also the level of protein purification is not high enough to compare to the behavior observed for the respective recombinant, highly purified, protein. Moreover, the ELISA assay is not conducive to multiplexing approaches that could have reduced some of the biological variation already discussed. This is where targeted tandem mass spectrometry methods can overcome these limitations (Gerber, Rush, Stemman, Kirschner, & Gygi, 2003; Jaffe et al., 2008). Examples of these methods include accurate inclusion mass spectrometry (AIMS) and quantitative selection reaction monitoring (Q-SRM). These more targeted MS methods specifically account for the amino-acid composition of surrogate tryptic peptides to which the selective monitoring of their precursor mass (i.e., with quadrupole mass filter), its fragmentation (i.e., CID, HCD, ETD), and subsequent product ions take place. This Selective towards one specific peptide MS precursor – product ion Reaction Monitoring (hence the term SRM) allows for its more full-time measurement and henceforth its enhanced detection in complex mixtures. The SRM detection is therefore based on the molecular signature (i.e. the unique amino acid composition of a peptide) traceable to an information rich, distinctively annotatable (i.e., *de novo* peptide sequencing), tandem (MS-MS) spectrum. Also, the intensity of the tandem spectrum traceable to one specific peptide depends on the relative or absolute concentration level of this peptide (Q-SRM). Such a level of selectivity and specificity is well beyond what can be attained with antibody capture technologies (i.e., ELISA assay)(Rissin et al., 2010). In addition, the detection of a biochemical assay is based on an absorption reading to a specific wavelength that is highly subject to background signal

The Discovery of Cancer Tissue Specific Proteins in Serum: Case Studies on Prostate Cancer 347

for both the enhanced measurement selectivity and dynamic range characteristics, the SRM technique can attain > 1-2 orders of magnitude greater sensitivity compared to the fluorescence ELISA assay. These SRM advantages can be extended when combined with various targeted protein or tryptic peptide isolation techniques such as biological antibody capture (i.e., monoclonal or polyclonal based Immuno-SRM) or chemical affinity capture (i.e. chemical ligands, peptide aptamers, etc.). In the case of the Immuno-SRM variant, it can be tailored to accommodate polyclonal antibodies for the immunoaffinity capture and enrichment of proteotypic peptides mixed with their stable isotope analogs as internal standards upstream to the SRM-MS detection phase. In this scenario, the proteins found in biological extracts are tryptic digested, the resulting tryptic peptides are then immunoaffinity isolated with the polyclonal antibodies, mixed with the specific stable isotope analogues and then analyzed with SRM-MS techniques. The stable isotope peptide analogues are used as internal standards to allow for absolute or relative quantification. This particular work-flow is referred to as Stable Isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA)(Anderson, Jackson, et al.,2009; Whiteaker et al., 2011; Whiteaker, Zhao, Anderson, & Paulovich, 2010). The principles of the SISCAPA – SRM MS work-flow allows for the simultaneous capturing and analysis of over 50 tryptic peptides, uniquely traceable to over 10 proteins (Kuzyk et al., 2009). With proper experimental design and the employment of effectively trained analysts, the SISCAPA has great potential in the highthroughput with high-confidence (> 90%) analysis of thousands of clinical serum or plasma specimens for the reliable verification and validation of protein biomarker panels as unique signatures of disease prediction, diagnosis, or treatment prognosis (Figure 6). The high analysis capacity afforded by the SISCAPA - SRM MS workflow can permit the implementation of double blind, randomized and placebo controlled clinical designs (i.e., to also include a statistically significant number of healthy volunteer with diseased patient cohorts) for the more robust and comprehensive validation of such biomarker panels. Another potential advancement achievable with the SISCAPA - SRM MS workflow can be for to supersede the other currently available protein verification assays such as the Western blot, qRT-PCR, protein chip arrays, etc. This is based on the notion that workflows such as that of the SISCAPA - SRM MS can match the selectivity, specificity and sensitivity achievable by the high-precision discovery MS methods such as those based on the 3-D MudPIT and iTRAQ 2DLC-MS techniques already discussed. This especially becomes true when the same tryptic peptides including those that have undergone *in vivo* modification

A crucial requirement in the ability to study the content of a biomedical specimen such as clinical tissue biopsies, cell cultures or blood plasma/serum for the presence of potentially significant biomarkers is analytical sensitivity. This especially becomes prudent when the staring amount of a given clinical specimen is small. Additionally, sensitivity becomes absolutely essential given that the concentration of clinically relevant proteins and their surrogate biomolecules is exceedingly small at the progression or initiation stages of carcinogenesis already discussed. When combined with selectivity, that is an affinity to preferentially analyze one specific biomolecular entity, the availability of high sensitivity allows the targeted analysis of a naturally low abundant disease marker in complex matrices such as those typically encountered in clinical specimens. It is these requirements that drive

constitute the analytes to be measured.

**5.2 Microfluidics and Lab-on-a-chip** 

interference due to cross-reactivity or non-specific binding effects. Another innate advantage to the SRM technique is their very large linear dynamic range that exceed 4 orders of magnitude thanks to the latest developments to MS analyzer and detector technology (Cox & Mann, 2011; Nilsson et al., 2010; Zhang et al., 2011). When one accounts

Fig. 4. Multistage, targeted proteomic pipeline for triage and verification of biomarker candidates. (a) Overview of the workflow used to triage and verify candidate biomarkers, showing the flux of candidates at each stage of the pipeline. (b) Required resources forimplementing the proteomic pipeline. The overall timeline includes time for data collection and analysis. For Q-SRM and immuno-SRM measurements, the overall timeline includes synthetic peptide quality control, development of SRM methods, acquisition of response curves and data analysis (but not the time required to generate antibodies, which can be interspersed with other activities). Instrument demands are summarized independently to provide an estimate of the required laboratory resources to carry out the study. Additional reagent costs (e.g., peptide standards and antibodies) are required for Q-SRM and immuno-SRM assays. Finally, the required personnel used in each phase of the study are denoted as full-time equivalents (Whiteaker, J.R., et al., *Nat. Biotech.* 2011).

for both the enhanced measurement selectivity and dynamic range characteristics, the SRM technique can attain > 1-2 orders of magnitude greater sensitivity compared to the fluorescence ELISA assay. These SRM advantages can be extended when combined with various targeted protein or tryptic peptide isolation techniques such as biological antibody capture (i.e., monoclonal or polyclonal based Immuno-SRM) or chemical affinity capture (i.e. chemical ligands, peptide aptamers, etc.). In the case of the Immuno-SRM variant, it can be tailored to accommodate polyclonal antibodies for the immunoaffinity capture and enrichment of proteotypic peptides mixed with their stable isotope analogs as internal standards upstream to the SRM-MS detection phase. In this scenario, the proteins found in biological extracts are tryptic digested, the resulting tryptic peptides are then immunoaffinity isolated with the polyclonal antibodies, mixed with the specific stable isotope analogues and then analyzed with SRM-MS techniques. The stable isotope peptide analogues are used as internal standards to allow for absolute or relative quantification. This particular work-flow is referred to as Stable Isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA)(Anderson, Jackson, et al.,2009; Whiteaker et al., 2011; Whiteaker, Zhao, Anderson, & Paulovich, 2010). The principles of the SISCAPA – SRM MS work-flow allows for the simultaneous capturing and analysis of over 50 tryptic peptides, uniquely traceable to over 10 proteins (Kuzyk et al., 2009). With proper experimental design and the employment of effectively trained analysts, the SISCAPA has great potential in the highthroughput with high-confidence (> 90%) analysis of thousands of clinical serum or plasma specimens for the reliable verification and validation of protein biomarker panels as unique signatures of disease prediction, diagnosis, or treatment prognosis (Figure 6). The high analysis capacity afforded by the SISCAPA - SRM MS workflow can permit the implementation of double blind, randomized and placebo controlled clinical designs (i.e., to also include a statistically significant number of healthy volunteer with diseased patient cohorts) for the more robust and comprehensive validation of such biomarker panels. Another potential advancement achievable with the SISCAPA - SRM MS workflow can be for to supersede the other currently available protein verification assays such as the Western blot, qRT-PCR, protein chip arrays, etc. This is based on the notion that workflows such as that of the SISCAPA - SRM MS can match the selectivity, specificity and sensitivity achievable by the high-precision discovery MS methods such as those based on the 3-D MudPIT and iTRAQ 2DLC-MS techniques already discussed. This especially becomes true when the same tryptic peptides including those that have undergone *in vivo* modification constitute the analytes to be measured.

#### **5.2 Microfluidics and Lab-on-a-chip**

346 Biomarker

interference due to cross-reactivity or non-specific binding effects. Another innate advantage to the SRM technique is their very large linear dynamic range that exceed 4 orders of magnitude thanks to the latest developments to MS analyzer and detector technology (Cox & Mann, 2011; Nilsson et al., 2010; Zhang et al., 2011). When one accounts

Fig. 4. Multistage, targeted proteomic pipeline for triage and verification of biomarker candidates. (a) Overview of the workflow used to triage and verify candidate biomarkers, showing the flux of candidates at each stage of the pipeline. (b) Required resources forimplementing the proteomic pipeline. The overall timeline includes time for data collection and analysis. For Q-SRM and immuno-SRM measurements, the overall timeline includes synthetic peptide quality control, development of SRM methods, acquisition of response curves and data analysis (but not the time required to generate antibodies, which

can be interspersed with other activities). Instrument demands are summarized

independently to provide an estimate of the required laboratory resources to carry out the study. Additional reagent costs (e.g., peptide standards and antibodies) are required for Q-SRM and immuno-SRM assays. Finally, the required personnel used in each phase of the study are denoted as full-time equivalents (Whiteaker, J.R., et al., *Nat. Biotech.* 2011).

A crucial requirement in the ability to study the content of a biomedical specimen such as clinical tissue biopsies, cell cultures or blood plasma/serum for the presence of potentially significant biomarkers is analytical sensitivity. This especially becomes prudent when the staring amount of a given clinical specimen is small. Additionally, sensitivity becomes absolutely essential given that the concentration of clinically relevant proteins and their surrogate biomolecules is exceedingly small at the progression or initiation stages of carcinogenesis already discussed. When combined with selectivity, that is an affinity to preferentially analyze one specific biomolecular entity, the availability of high sensitivity allows the targeted analysis of a naturally low abundant disease marker in complex matrices such as those typically encountered in clinical specimens. It is these requirements that drive

The Discovery of Cancer Tissue Specific Proteins in Serum: Case Studies on Prostate Cancer 349

decreased lateral diffusion thus increasing its mass density leading to improved MS-based measurement sensitivity (Figure 7)(Culbertson, Jacobson, & Michael Ramsey, 2002). Other physico-chemical parameters that also play a role in achieving ideal diffusional kinetic profiles for a given chromatographic process, include the geometry of the chambers, their material properties (i.e., porous vs. non-porous), the actual chemistry (i.e. ion-exchange, hydrophilic/hydrophobic interaction, etc.) and configuration (packed vs. open tubular) of the interactive binding sites, the chemical composition of the solution phase (i.e., affecting viscosity, ion charge and mobility, etc.)(Culbertson et al., 2005; Koster & Verpoorte, 2007). Concordantly, the lab chip devices can fully exploit the very high-speed (> 40 kHz) with high-resolution (>30,000 m/Δm) signal acquisition features of the current MS platforms retrofitted with on-line or off-line ionization interfaces, such as the ESI or MALDI type,

These design features were incorporated in the development and application of a lab chip device based on a TiO2–ZrO2 monolithic chemical affinity chromatography format for the more selective and sensitive analysis of phosphopeptides at higher loading capacities relative to other more mainstream approaches such as those based on micropipette tips (Tsougeni et al., 2011). This monolithic column was configured on 2 mm PMMA plates, and consisted of 32 parallel microchannels with common input and output ports (Figure 8). The isolated, purified and enriched phosphopeptides were deposited onto a MALDI target and then off-line analyzed with a MALDI-MS system. The phosphopeptide binding specificity of the bidentate TiO2–ZrO2 chemistry at acidic pH environments, the larger number of theoretical plates (or, the density of these binding sites per unit area), and the high S/V ratio of microporous monolithic configuration all corroborated towards achieving this goal.

Conceptually, multiple chromatographic modalities can be integrated in a single lab chip format thanks to the latest developments of piezo-electric actuators, cantilevers, micropumps and valves, micro- and nano- mixing chambers, electroosmotically induced hydraulic pumping and other lab chip components (Figure 9). As such, these components operate under very small flow-rates (1-10 nL/min) conducive toward the optimum operation of nano-chromatographic dimensions (i.e. inner diameters < 20 μm) that also incorporate the attributes just discussed (Culbertson, Ramsey, & Ramsey, 2000; Hoeman, Lange, Roman, Higgins, & Culbertson, 2009; Jahnisch, Hessel, Lowe, & Baerns, 2004;

Another fundamental component to an integrated lab chip design is the on-line ionization source interface. In particular, the nano-electrospray ionization (nESI) source is the most suitable interface for lab chip designs when MS-based platforms are used as the detection system. Contributing factors for the ideality of the nESI source include their intrinsic nondestructive operation leading to the efficient ionization of a broad range of biomolecules including sugars, amino acids, fatty acids, nucleic acids, peptides and proteins. Therefore, the chemical integrity of these biomolecules remains intact thanks to this "soft" ionization imparted by the nESI interface (Wilm, 2011). Another contributing factor is that the nESI efficiency can be enhanced at the low nL/mL flow rate regime, provided of course that the correct geometry is utilized (Figure 10). In fact, at these flow rates, the nESI interface is less prone to the suppression effects observed when reagents essential to the operation of

McKnight, Culbertson, Jacobson, & Ramsey, 2001).

capillary electrophoresis and electrochromatography.

respectively.

the advancements made in microfluidic lab-on-chip (lab chip) devices (Astorga-Wells,Vollmer, Bergman, & Jornvall, 2005; Culbertson, 2006; Gottschlich, Culbertson, McKnight, Jacobson, & Ramsey, 2000; Koster & Verpoorte, 2007; Lion et al., 2003). The ever more effective bioanalyte detection is driven by the ability to integrate their extraction from complex multi-cellular matrices at decreased dilutional effects, followed by their ultra highresolution separation, enrichment and purification upstream to the MS detection process. The lab chip devices actualize such a principle. One of several optimal characteristics of a lab chip device includes the high surface-to-volume (S/V) ratios of its microfluidic channels for analyte capture and chromatographic separation. Maintaining optimum S/V ratios is conducive toward fast and effective interaction between the solution phase bioanalyte with the stationary phase binding site. As a result, the bioanalyte to be measured exhibits

Fig. 5. Illustration of the lateral-diffusion effect of a specific amount for a given analyte species under a constant chromatographic medium. The analyte amount gets distributed over a wider distribution due to its diffusion in a time dependent manner therefore reducing its mass density at the apex. The decrease of the diffusional path of the analyte results to the increase of its mass density at the apex and consequently its improved detection at this point (Culbertson et al., 2002).

the advancements made in microfluidic lab-on-chip (lab chip) devices (Astorga-Wells,Vollmer, Bergman, & Jornvall, 2005; Culbertson, 2006; Gottschlich, Culbertson, McKnight, Jacobson, & Ramsey, 2000; Koster & Verpoorte, 2007; Lion et al., 2003). The ever more effective bioanalyte detection is driven by the ability to integrate their extraction from complex multi-cellular matrices at decreased dilutional effects, followed by their ultra highresolution separation, enrichment and purification upstream to the MS detection process. The lab chip devices actualize such a principle. One of several optimal characteristics of a lab chip device includes the high surface-to-volume (S/V) ratios of its microfluidic channels for analyte capture and chromatographic separation. Maintaining optimum S/V ratios is conducive toward fast and effective interaction between the solution phase bioanalyte with the stationary phase binding site. As a result, the bioanalyte to be measured exhibits

Fig. 5. Illustration of the lateral-diffusion effect of a specific amount for a given analyte species under a constant chromatographic medium. The analyte amount gets distributed over a wider distribution due to its diffusion in a time dependent manner therefore reducing its mass density at the apex. The decrease of the diffusional path of the analyte results to the increase of its mass density at the apex and consequently its improved

detection at this point (Culbertson et al., 2002).

decreased lateral diffusion thus increasing its mass density leading to improved MS-based measurement sensitivity (Figure 7)(Culbertson, Jacobson, & Michael Ramsey, 2002). Other physico-chemical parameters that also play a role in achieving ideal diffusional kinetic profiles for a given chromatographic process, include the geometry of the chambers, their material properties (i.e., porous vs. non-porous), the actual chemistry (i.e. ion-exchange, hydrophilic/hydrophobic interaction, etc.) and configuration (packed vs. open tubular) of the interactive binding sites, the chemical composition of the solution phase (i.e., affecting viscosity, ion charge and mobility, etc.)(Culbertson et al., 2005; Koster & Verpoorte, 2007). Concordantly, the lab chip devices can fully exploit the very high-speed (> 40 kHz) with high-resolution (>30,000 m/Δm) signal acquisition features of the current MS platforms retrofitted with on-line or off-line ionization interfaces, such as the ESI or MALDI type, respectively.

These design features were incorporated in the development and application of a lab chip device based on a TiO2–ZrO2 monolithic chemical affinity chromatography format for the more selective and sensitive analysis of phosphopeptides at higher loading capacities relative to other more mainstream approaches such as those based on micropipette tips (Tsougeni et al., 2011). This monolithic column was configured on 2 mm PMMA plates, and consisted of 32 parallel microchannels with common input and output ports (Figure 8). The isolated, purified and enriched phosphopeptides were deposited onto a MALDI target and then off-line analyzed with a MALDI-MS system. The phosphopeptide binding specificity of the bidentate TiO2–ZrO2 chemistry at acidic pH environments, the larger number of theoretical plates (or, the density of these binding sites per unit area), and the high S/V ratio of microporous monolithic configuration all corroborated towards achieving this goal.

Conceptually, multiple chromatographic modalities can be integrated in a single lab chip format thanks to the latest developments of piezo-electric actuators, cantilevers, micropumps and valves, micro- and nano- mixing chambers, electroosmotically induced hydraulic pumping and other lab chip components (Figure 9). As such, these components operate under very small flow-rates (1-10 nL/min) conducive toward the optimum operation of nano-chromatographic dimensions (i.e. inner diameters < 20 μm) that also incorporate the attributes just discussed (Culbertson, Ramsey, & Ramsey, 2000; Hoeman, Lange, Roman, Higgins, & Culbertson, 2009; Jahnisch, Hessel, Lowe, & Baerns, 2004; McKnight, Culbertson, Jacobson, & Ramsey, 2001).

Another fundamental component to an integrated lab chip design is the on-line ionization source interface. In particular, the nano-electrospray ionization (nESI) source is the most suitable interface for lab chip designs when MS-based platforms are used as the detection system. Contributing factors for the ideality of the nESI source include their intrinsic nondestructive operation leading to the efficient ionization of a broad range of biomolecules including sugars, amino acids, fatty acids, nucleic acids, peptides and proteins. Therefore, the chemical integrity of these biomolecules remains intact thanks to this "soft" ionization imparted by the nESI interface (Wilm, 2011). Another contributing factor is that the nESI efficiency can be enhanced at the low nL/mL flow rate regime, provided of course that the correct geometry is utilized (Figure 10). In fact, at these flow rates, the nESI interface is less prone to the suppression effects observed when reagents essential to the operation of capillary electrophoresis and electrochromatography.

The Discovery of Cancer Tissue Specific Proteins in Serum: Case Studies on Prostate Cancer 351

Fig. 7. Illustrative representations of various mixing chambers with different operational modes that are applicable to lab chip devices. These designs allow for the efficient mixing of reagents at nano-flow rates and assist the integration of various modes of chromatographic

Such integrated lab chip designs will allow for the effective miniaturization and automation of multi-dimensional MudPIT approaches illustrated in the previous section. Theoretically, such a lab chip reconfiguration of the more traditional lab bench analytical methodology can increase the bioanalyte sensitivity by more than several orders of magnitude. Consequently, full proteomes can be fully characterized by vastly smaller biological starting amounts (i.e. fg levels vs. μg levels). At this level of analytical sensitivity techniques such as laser capture microdissection and cell sorting can effectively be incorporated to research protocols. Also biomolecules constituting exosome entities found in plasma occurring at very low levels can also be detected. It is hypothesized that exosome biology may help explain how a particular organ secrete or shed proteins and other biomolecules such as DNA and mRNA into the systemic circulation. The exosome composition may be highly depended on the disease state of the organ (i.e. initiation stage carcinogenesis). Therefore exosomes may play a crucial role

in using plasma as a biopsy source to interrogate the tissue pathophysiology status.

technique (i.e. multidimensional MudPIT) (Jahnisch et al., 2004).

Fig. 6. Schematic representation of the fabrication process with direct lithography and plasma etching followed by liquid deposition of the TiO2–ZrO2 stationary phase: (1) spin coating of a thin inorganic (ORMOCER) photoresist as an etching mask on PMMA sheets, (2) lithography on photoresist polymer, using mask exposure, (3) photoresist development, (4) deep plasma etching of polymeric substrate, (5) liquid deposition of the thin TiO2–ZrO2 lm and baking at 95°C, (6) rinsing with 0.1 M NaOH and DI water and baking at 95°C, and (7) sealing with lamination lms. The relative thickness in the gure does not correspond to the real thickness. SEM image insets: (a) a PMMA micro-column consisting of 32 parallel microchannels after etching (a zoomed image showing the roughness at the microchannel bottom is also shown), (b) a PMMA micro-column after liquid phase deposition of TiO2– ZrO2 (a zoomed image of the crystallites is also shown), and (c) a cross-section of the column, after bonding with the lamination lm (for details see also ESI†) (Tsougeni et al., 2011).

Fig. 6. Schematic representation of the fabrication process with direct lithography and plasma etching followed by liquid deposition of the TiO2–ZrO2 stationary phase: (1) spin coating of a thin inorganic (ORMOCER) photoresist as an etching mask on PMMA sheets, (2) lithography on photoresist polymer, using mask exposure, (3) photoresist development, (4) deep plasma etching of polymeric substrate, (5) liquid deposition of the thin TiO2–ZrO2 lm and baking at 95°C, (6) rinsing with 0.1 M NaOH and DI water and baking at 95°C, and (7) sealing with lamination lms. The relative thickness in the gure does not correspond to the real thickness. SEM image insets: (a) a PMMA micro-column consisting of 32 parallel microchannels after etching (a zoomed image showing the roughness at the microchannel bottom is also shown), (b) a PMMA micro-column after liquid phase deposition of TiO2– ZrO2 (a zoomed image of the crystallites is also shown), and (c) a cross-section of the column, after bonding with the lamination lm (for details see also ESI†) (Tsougeni et al.,

2011).

Fig. 7. Illustrative representations of various mixing chambers with different operational modes that are applicable to lab chip devices. These designs allow for the efficient mixing of reagents at nano-flow rates and assist the integration of various modes of chromatographic technique (i.e. multidimensional MudPIT) (Jahnisch et al., 2004).

Such integrated lab chip designs will allow for the effective miniaturization and automation of multi-dimensional MudPIT approaches illustrated in the previous section. Theoretically, such a lab chip reconfiguration of the more traditional lab bench analytical methodology can increase the bioanalyte sensitivity by more than several orders of magnitude. Consequently, full proteomes can be fully characterized by vastly smaller biological starting amounts (i.e. fg levels vs. μg levels). At this level of analytical sensitivity techniques such as laser capture microdissection and cell sorting can effectively be incorporated to research protocols. Also biomolecules constituting exosome entities found in plasma occurring at very low levels can also be detected. It is hypothesized that exosome biology may help explain how a particular organ secrete or shed proteins and other biomolecules such as DNA and mRNA into the systemic circulation. The exosome composition may be highly depended on the disease state of the organ (i.e. initiation stage carcinogenesis). Therefore exosomes may play a crucial role in using plasma as a biopsy source to interrogate the tissue pathophysiology status.

The Discovery of Cancer Tissue Specific Proteins in Serum: Case Studies on Prostate Cancer 353

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Fig. 8. Schematic nESI designs that allow its operation at the low nL/mL flow regime. Geometries, dimensions, along with their material compositions all play a pivotal role in the optimal nESI process (Lion et al., 2003).
