Protein and Peptide Mass Spectrometry in Drug Discovery (Gross/Protein Mass Spec Drug Discovery) || Comparative Proteomics by Direct Tissue Analysis Using Imaging Mass Spectrometry

CHAPTER 5

Comparative Proteomics by DirectTissue Analysis Using Imaging MassSpectrometry

MICHELLE L. REYZER and RICHARD M. CAPRIOLI

5.1 INTRODUCTION

The modern study of proteomics has transformed the way new drug targets are

identified, in large part owing to the technological advances in mass spectrometry

(MS). Extensive comparative proteomics studies are routinely performed by using

standard gel electrophoresis and high-performance liquid chromatography (HPLC)

approaches coupled to electrospray (ESI) ormatrix-assisted laser desorption/ionization

(MALDI) mass spectrometric techniques for peptide and protein identification. These

studies result in a catalog of potential biomarkers that are differentially expressed in

disease, or in subjects treated with drugs, compared to healthy controls. The rationale

behind these studies is that some of these changes are directly due to the disease

pathology and thus present viable targets for drugdiscovery. Similar studiesmay alsobe

used to assess toxicity, drug resistance, and drug efficacy,makingMS-based proteomics

an important tool for the development of new, safe, and effective pharmaceuticals.

With the development of imaging mass spectrometry (IMS) [1,2], these studies

may now be performed directly on tissue sections, precluding the need for extensive

sample preparation. MALDI mass spectrometry allows the use of thin sections of

frozen tissues (biopsies, dissected animal organs, whole-body animal samples) to be

analyzed. These tissue sections are directly thaw-mounted on conductive plates,

coated or spotted with MALDI matrix, and mass spectra are obtained at discrete

locations over the entire section. The mass spectra contain signals from proteins and

peptides (as well as lipids, pharmaceuticals, endogenous small molecules, etc.) that

are expressed in specific locations within the tissue. Spectra may be obtained with

high spatial resolution (�50–200mm, down to �10 mm with special optics) and

Protein and Peptide Mass Spectrometry in Drug Discovery, Edited by Michael L. Gross, Guodong Chen,and Birendra N. Pramanik.� 2012 John Wiley & Sons, Inc. Published 2012 by John Wiley & Sons, Inc.

129

excellent mass accuracy (typically 5–10 ppm for most TOF-MS instruments) from a

typical mass range of up to around 50 kDa.

Thus IMS may be used to perform routine comparative proteomics analyses, with

signals of overexpressed and underexpressed materials being determined in the

different sample groups. IMS, however, provides additional information compared

to standard gel and HPLC-based analyses. For example, an assessment may be made

as to what proteins are being expressed where. Because conventional approaches

typically use homogenized tissues prior to gel and HPLC separation, any spatial

information is lost. Furthermore signals obtained from a MALDI mass spectrum

correspond to proteins in the form in which they are present in the tissues (i.e.,

including any modifications or cleavages). This highly specific output may provide

important information for future drug discovery, as only proteins in a certain state

(modified or unmodified) may be biologically relevant.

5.2 CONVENTIONAL COMPARATIVE PROTEOMICS

There are many examples in the literature that demonstrate the power of comparative

proteomics as a discovery tool, with drug discovery as its ultimate goal. One example

describes the use of comparative proteomics to identify patterns in cancer cells that

become resistant to various chemotherapies [3]. The authors reviewed 29 studies

employing conventional proteomics technologies to uncover differences in cell lines

from cancer cells that had developed resistance to chemotherapy compared to cell

lines that remained responsive. Thirty-eight different cell lines were examined, and

differences were found in proteins involved in many relevant biochemical pathways.

Half or more of the cell lines exhibited expression changes in proteins involved with

calcium-binding, chaperone, cytoskeleton, and metabolism processes. The authors

concluded thatmodel cancer cell lines exhibitmultiplemechanisms of drug resistance

and that further studywill help identify predictive factors to aid prognosis. In addition

they state, “. . . these proteinsmay be used as targets for developing chemo-sensitizing

therapeutics that can be used to enhance the chemo-sensitivity of cancers to currently

available anticancer drugs in combination therapy.”[3]

Another report describes the identification of proteomic markers for hepatic

steatosis (fatty liver), which is often an early sign of drug toxicity [4]. The authors

injected a compound (designated CDA) into rats and analyzed the protein expression

differences in the livers after 2 and 5 days of treatment and compared the results with

those from controls. Liver homogenates were subjected to 2D DIGE separation

followed by spot excision, tryptic digestion, and MALDI mass fingerprinting for

protein identification. Subsequently these experiments were repeated in an in vitro rat

hepatocytemodel. The spot pattern was similar between the liver and hepatocyte gels,

and from the 14 spots identified from the hepatocyte gel, 6 proteins were identical to

proteins identified from the liver gel, suggesting that similar pathways were being

affected in the in vitromodel as in the whole-animal. An important conclusion is that

the in vitromodel can be used as a surrogate to whole-animal studies. This can allow

for rapid, high-throughput screening of drug toxicity earlier in the drug discovery

130 COMPARATIVE PROTEOMICS BY DIRECT TISSUE ANALYSIS

process, minimizing costly, late-stage failures of drug candidates owing to toxicity

issues [4].

5.3 COMPARATIVE PROTEOMICS USING IMAGING MS

Imaging mass spectrometry has been successfully applied to comparative proteomics

studies involving human lung cancer [5–7], brain cancer [8,9], breast cancer [10],

ovarian cancer [11], as well as other diseases. These studies are typically performed

via histology-directed protein profiling [10] that is better suited for high-throughput

analysis of many samples (tens to hundreds) with the ultimate goal of discovering

statistically significant proteomic markers. This approach, however, is often com-

plemented by a high-resolution image analysis of one or several representative tissue

specimens. The images obtained can confirm the presence of the statistically

significant biomarkers while highlighting their localization. Further visual inspection

of the images can reveal other proteins that show similar localization patterns.

Examples of these two modes of analysis are presented below.

5.3.1 Biomarker Discovery: Breast Cancer

In histology-directed protein profiling, optical images of tissue sections are examined

by a pathologist whomarks regions that are highly enriched in certain cell populations

(typically480% of one cell type; e.g., normal epithelial cells, tumor cells, or stroma

cells). These optical images are overlayed onto images of serial sections that are

mounted onto MALDI plates for mass spectral analysis. Precise x, y coordinates are

generated for each marked region on the MALDI plate. Small volumes of matrix

(�pL to nL) are then precisely deposited on the tissue by using robotic spotters [12] at

the positions marked, affording discrete spots of matrix approximately 150 to 200 mmin diameter; the materials in those spots are subsequently analyzed. The resulting

mass spectra thus correspond to unique positions on the tissue and contain profiles

primarily from one cell type. These protein profiles are then evaluated by using

biostatistical analysis, with the ultimate goal of determining differentially expressed

proteins among the different cell types. This experiment can be thought of as directed

low-resolution imaging, because although a high-resolution picture of protein distri-

bution is not generated, each spectrum is linked to a specific location on the tissue.

Other approaches to molecular profiling of heterogeneous tissues utilize laser

capture microdissection (LCM) [13,14]. LCM extracts small clusters of individual

cells from a tissue section, which can then be analyzed byMALDImass spectrometry

to obtainmolecular profiles. These analyses result in profiles that are unique to distinct

cell populations, but the data may be compromised by the harsh washing and

dehydration steps required for LCM. In addition LCM can be quite time-consuming,

requiring hundreds of cells of a single type to be extracted manually onto a single

region of a polymeric cap to produce good quality mass spectra.

An example of the histology-directed approach is the analysis of human breast

cancer specimens [15]. Breast tissue is quite heterogeneous, containing discrete

COMPARATIVE PROTEOMICS USING IMAGING MS 131

ductal and lobular functional units, surrounding stroma, and fatty tissue. In addition

there are many types and stages of breast cancer, from localized ductal carcinoma

in situ (DCIS) to invasive mammary cancer (IMC). These cancers may be present in

the same sample in close proximity to each other. To derive meaningful data from

these tissues, it is critical that themolecular profiles originate from, and thus represent,

primarily the proteins present in the distinct cell types.

The process is illustrated in Figure 5.1 [15]. Figure 5.1A shows an image of anH&E

stained section of a human breast cancer tissue that was annotated by a pathologist. In

this case the marked circles are color-coded to differentiate the distinct cell types (red

circles denote stroma cells, black circles are IMC, blue circles are DCIS, and green

circles are nontumor epithelium). Figure 5.1B is a close-up view of one region of the

tissue (Figure 5.1A), highlighting the close proximity of different cell types within the

tissue section. The large circular shaded area represents the spot size that would result

FIGURE 5.1 Histology-directed protein profiling for comparative proteomics. (A) H&E

stained section of human breast cancer specimen annotated by a pathologist to locate regions of

interest: red, peritumoral stroma; black, IMC; blue, DCIS; and green, non-tumor epithelium.

(B) Illustration of the different surface areas profiled by the histology-directed strategy (colored

spots) and traditional profiling (shaded area). (C) Overlay of the aligned H&E image with the

section on the MALDI target plate for matrix spotting. (D) Optical image of the section on the

MALDI target plate after robotic deposition of matrix onto the designated sites. Reproduced

with permission from [15]. (See the color version of this figure in Color Plates section.)


after typical manual deposition of matrix with a mechanical pipette (�100 nL

generates a spot�1mm in diameter). Protein profiles obtained from such a manually

derived spot would contain proteins from all three cell types and would only provide

an average protein distribution upon statistical analysis.

An overlay of the marked H&E image with the serial section on the MALDI plate

(Figure 5.1C) shows that the images are aligned along both internal and external

contours to maximize placement accuracy. Figure 5.1D shows an image of the tissue

on theMALDI plate after spotting. A clear correlation is observed between the actual

matrix spot locations in Figure 5.1D and the marked regions on the serial section in

Figure 5.1A. Profiles acquired from this sample were analyzed by unsupervised

classification followed by multidimensional scaling (MDS) of the distance in three

dimensions. TheMDS results show that normal epithelium, stroma, and cancer (DCIS

and IMC) separate into three distinct groups. Further supervised analysis of the DCIS

and IMC profiles reveal a small, but noticeable, separation, indicating that molecular

differences can be observed even between similar pathologies.

This technology was also used to explore whether biomarkers may be found that

correlate to drug response in a mouse model of breast cancer [16]. In this case tumors

from transgenic mice expressing human HER2 (human epidermal growth factor

receptor 2) were transplanted into wild-type mice, where they continued to grow and

show HER2 overexpression. The antibody Herceptin binds to the HER2 receptor and

shows antitumor activity in these tumors (notated as 1282 tumors). Another tumor line

(Fo5), from the same transgenic founder, spontaneously developed resistance to

Herceptin, while maintaining similar expression levels of HER2 and similar levels of

Herceptin-HER2 binding. Fo5 and 1282 tumors were harvested after a single dose of

Herceptin (30mg/kg i.p.) and subjected to MS analysis. The mass spectra in the mass

range of 9700 to 10,200Da obtained for both sensitive (1282) and resistant (Fo5)

tumor lines (Figure 5.2) show that treatment with Herceptin induces an increase of the

species of m/z 9739, 9970, and 10,164 compared to the untreated tumor, whereas no

change is evident for those signals in the resistant tumor after Herceptin treatment.

Several other signals were found to exhibit a similar pattern, including those

corresponding to ions of m/z 4795 and 9212 suggesting that these signals may be

biomarkers of Herceptin resistance [16].

5.3.2 Biomarker Discovery: Toxicity

Identification of compounds that have adverse toxicity profiles is of critical impor-

tance in drug discovery. Similar studies to the one highlighted earlier involving

hepatic steatosis have been conducted using MALDI IMS. For example, a group of

monkeys was given the known nephrotoxicant gentamicin along with everninomicin

to determine if the combination produced nephrotoxicity. After seven days of

combination treatment (10mg/kg gentamicin and 30mg/kg everninomicin), the

animals were sacrificed and their kidneys removed and flash frozen for MALDI

analysis. Matrix was deposited on the kidney sections manually, and protein profiles

were obtained to reveal an overall indication of proteomic effects. Several signals

showed significant intensity differences compared to controls, including a signal for


an ion ofm/z 12,922 (shown in Figure 5.3A). This result was followed up with a high-

resolution imaging analysis of kidneys from one control and one dosed monkey. As

shown in Figure 5.3B, the treated monkey kidney shows an intense signal corre-

sponding to the m/z 12,924 ion that is localized to the cortex. There is no noticeable

signal in the medulla of the treated monkey, nor is there measureable signal anywhere

in the control kidney. This protein was identified as transthyretin via HPLC-MS/MS

and 2D gel electrophoresis. Subsequently these results were correlated with Western

blot and immunohistochemistry experiments, which also showed a significant

increase in transthyretin in the kidney cortex of treated animals. An analogous study

undertaken in rats found similar results, with gentamicin-treated rats expressing an

increase of transthyretin in the kidney cortex [17].

5.3.3 Correlating Drug and Protein Distributions

One unique advantage of imagingmass spectrometry is the ability to locate positionally

a given compoundwithmolecular specificity. This allows compound distributions to be

obtained in a label-free manner, while differentiating signals originating from a parent

compound and its metabolites. This has been demonstrated for olanzapine distribution

9739

1282 tumors Control

9970

10164

Herceptin treated

9970

Fo5 tumors

9700 9800 9900 10000 10100 102009700 9800 9900

Nor

mal

ized

inte

nsity

10000 10100 10200m/z

FIGURE 5.2 Drug-induced changes in the proteome predict for therapeutic resistance. Mice

bearing Fo5 (Herceptin-resistant) and 1282 (Herceptin-sensitive) tumors were treated with a

single dose of Herceptin (30mg/kg i.p). Tumors were harvested after dosing and subjected to

mass spectral proteomic analysis. Statistically significant changes observed after Herceptin-

treatment in the 1282 tumors that are not observed in the Fo5 tumors are shown (an increase

inm/z 9739 and 10,164). The sensitive tumor line traces consist of untreated tumors (average of

20 spectra from 6 tumors) and Herceptin-treated tumors (average of 13 spectra from 4 tumors).

The resistant tumor line traces consist of untreated tumors (average of 11 spectra from3 tumors)

and Herceptin-treated tumors (average of 20 spectra from 4 tumors). (See the color version of

this figure in Color Plates section.)


inwhole-body rat sections [18]. In this case the distribution for olanzapine aswell as for

two first-pass metabolites, N-desmethyl-olanzapine and 2-hydroxymethyl-olanzapine,

were detected from whole-body rat sections 2 h after dosing. Three unique fragmenta-

tion transitions were monitored (via MS/MS), one for each compound, thus generating

three molecularly specific images from the same whole-body section.

This approach may be combined with protein distribution analyses to obtain a

picture of proteomic changes associated with drug dosing. The information gleaned

from such experiments may be useful for evaluating drug efficacy, elucidating

biochemical pathways or drug mechanisms, discovering biomarkers for response or

resistance, or establishing co-localization of a drug and its protein target.

One application of this technology being investigated in our laboratory is the

distribution of antituberculosis drugs in infected rabbit lungs. Current chemotherapy

regimens for people infectedwithM. tuberculosis last for sixmonths or longer, but the

factors that affect the slow rate of bacterial killing are largely unknown. It is known

that tuberculosis infection results in the formation of a heterogeneous collection of

pulmonary granulomas. One possibility for the different rates of bacterial killing may

be related to the penetration of the drugs into the different granulomas. Proteins (or

other endogenous compounds, e.g., lipids) present in themicroenvironment surround-

ing the granulomas may influence drug accessibility and penetration. Imaging mass

spectrometry allows the drugs themselves to be located and the surrounding proteins

(and lipids) to be visualized, which may lead to a better understanding of the

mechanism of action of the drugs in vivo.

An example is the imaging of a lung from a rabbit infected with M. tuberculosis

and then orally dosed with a combination of antituberculosis drugs, including rifampin

(RIF) at 30mg/kg for 5 days, and sacrificed 1 h 5min after the final dose (Figure 5.4).

Figure 5.4A is an optical image of a thaw-mounted section of the lung on a gold-coated

MALDI plate (which gives the tissue the overall yellow color). Several distinct

control 7-day treated

m/z 12,924transthyretin

control7-day treated

12700 12820 12940 13060 13180 13300

12,922

13,136

rela

tive

inte

nsity

m/z

(A) (B)

FIGURE 5.3 Drug-induced changes in the proteome correlate with drug-induced toxicity.

Monkeys were dosed with a combination of the known nephrotoxicant gentamicin (10mg/kg)

and everninomicin (30mg/kg) for 7 days. Kidneys were harvested and subjected to mass

spectral proteomic analysis. (A) A signal at m/z 12,922 (subsequently identified as trans-

thyretin) was found to be significantly increased in the dosed kidneys compared to controls.

(B) High-resolution image analysis of kidneys from one control and one dosed monkey show

the transthyretin ion is localized to the cortex of the dosed kidneys. (See the color version of this

figure in Color Plates section.)


granulomas can be observed on the optical section (light, whitish areas denoted by

arrows). Figure 5.4B shows a reconstructed ion image for RIF, obtained via tandem

massspectrometry innegative-ionmode.ThedeprotonatedRIFmoleculeofm/z821was

dissociated and the primary fragments ofm/z 397 and 722 were summed for the image.

The drug can clearly be observed localizing in several of the granulomas compared to

adjacent uninvolved lung tissue. Figure 5.4C shows an H&E stained slide of a separate

section from the same tissue, where many small granulomas are clearly observed.

Figure 5.4D is a reconstructed ion image for several protein signals obtained from a

section cut serially to the H&E section. A signal for anm/z 11,345 ion (shown in green)

shows distinct localization to the granuloma areas, and perhaps sub-localization to the

outer ring of the granulomas. Another signal for an ion ofm/z 15,787 is not present to a

noticeable degree in thegranulomas, but rather appears in the adjacentuninvolved tissue.

Its distribution in the lung tissue, however, appears to be heterogeneous. Further study

willberequired to identify theseproteinsandtodeterminewhat role, if any, theymayplay

in affecting the distribution of RIF or the other drugs in the lung tissue generally and

granulomas specifically. Nevertheless, the information obtained from these experiments

will certainly be beneficial for understanding how the existing antituberculosis therapies

work andwill help to facilitate the process of drug design for next-generation therapies.

5.4 CONCLUSIONS

Imaging mass spectrometry has tremendous potential for advancing and supporting

the drug discovery process. Comparative proteomics experiments may be performed

FIGURE 5.4 Examining drug distribution in the granuloma microenvironment in a rabbit

model of tuberculosis infection. Rabbits were infected with M. tuberculosis and orally dosed

with a combination of antituberculosis drugs, including rifampin at 30mg/kg for 5 days.

(A) Optical image of an infected rabbit lung section on a gold-coatedMALDI target plate. This

animalwas sacrificed1 h 5min after the final dose.Granulomas are indicatedwithwhite arrows.

(B)MALDIMS image of the distribution of rifampin (MS/MSm/z 821!m/z 397 þ m/z 722)

in the lung section shown in A. Rifampin appears to localize to granulomas compared to

surrounding lung. (C)H&E stained serial section of the lung tissue shown inA, with granulomas

indicated by black arrows. (D) MALDI MS protein image showing the localization of m/z

11,345 (green) to the granuloma areas andm/z 15,787 (red) to adjacent uninvolved tissue. (See

the color version of this figure in Color Plates section.)


and the results used as a starting point for selecting promising drug targets, understand-

ing the biologicalmechanisms of a pathology, or for probing the global effects of a drug

on the proteome of an organism. Toxicity andADME studiesmay also be performed by

monitoring the drug and any known metabolites on individual organ or whole-body

animal sections. The same (or serial) sections may also be analyzed for proteomic

effects thatmaybe indicators of drug toxicity or efficacy.Because these experiments are

label-free and can make use of the same samples for multiple analyses, this technology

has the potential to save money and resources now needed for the analyses performed.

Furthermore the overall impact will be to save resources for the development because

these experiments can be performed early in the drug discovery stage.

ACKNOWLEDGMENTS

The authors thankWalter Korfmacher, Ron Snyder, Eddie Yi-Zhong Gu, and Annette

Erskine for the samples and analysis of transthyretin in monkey kidneys, and Clif

Barry III, JoAnne Flynn, and Laura Via for the collaboration on tuberculosis imaging.

Funding from NIH (5R01 GM058008), DOD (W81XWH-05-1-0179), and the Bill

and Melinda Gates Foundation is acknowledged.

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Protein and Peptide Mass Spectrometry in Drug Discovery (Gross/Protein Mass Spec Drug Discovery) || Comparative Proteomics by Direct Tissue Analysis Using Imaging Mass Spectrometry