Tissue Profiling by Mass Spectrometry
A Review of Methodology and Applications*
Robert L. Caldwell and
Richard M. Caprioli
Mass Spectrometry Research Center, Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, TN 37232-8575
 |
ABSTRACT
|
---|
Matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) has become a valuable tool to address a broad range of questions in many areas of biomedical research. One such application allows spectra to be obtained directly from intact tissues, termed "profiling" (low resolution) and "imaging" (high resolution). In light of the fact that MALDI tissue profiling allows over a thousand peptides and proteins to be rapidly detected from a variety of tissues, its application to disease processes is of special interest. For example, protein profiles from tumors may allow accurate prediction of tumor behavior, diagnosis, and prognosis and uncover etiologies underlying idiopathic diseases. MALDI MS, in conjunction with laser capture microdissection, is able to produce protein expression profiles from a relatively small number of cells from specific regions of heterogeneous tissue architectures. Imaging mass spectrometry enables the investigator to assess the spatial distribution of proteins, drugs, and their metabolites in intact tissues. This article provides an overview of several tissue profiling and imaging applications performed by MALDI MS, including sample preparation, matrix selection and application, histological staining prior to MALDI analysis, tissue profiling, imaging, and data analysis. Several applications represent direct translation of this technology to clinically relevant problems.
Matrix-assisted laser desorption/ionization (MALDI)1mass spectrometry (MS) from intact tissues has had a major impact on the study of molecular biology and biochemistry by permitting sensitive, rapid, and molecularly specific analyses of peptides and proteins. This technology provides information on molecular weights with high mass accuracy and protein modifications such as phosphorylation and acetylation and allows for the identification of proteins by peptide sequencing combined with protein data base searches. Although a more traditional application of MALDI MS combines separation technology such as two-dimensional gels for analysis of relatively pure proteins obtained from a complex biological sample, the required procedures are lengthy. Most importantly, because these protocols involve tissue mincing and extraction, spatial localization and relative concentrations of a given protein are lost.
Tissue profiling by MALDI MS can be performed on intact tissue sections for the determination of the spatial distribution of compounds and their relative expression levels without the need for molecularly specific exogenous compounds such as antibody-based reagents. Simple sample preparation protocols allow for fast and reliable analysis, typically resulting in the detection of over a thousand ion signals in the mass range of 2,00070,000 Da. These signals can be mapped to discrete tissue regions, thereby adding a new dimension to protein analysis.
In 1999, MALDI MS imaging was introduced for protein analysis from intact biological tissues by MALDI MS (1). In this study, direct profiling of proteins in murine tissue sections from several organs revealed hundreds of peptide and protein signals in the 230 kDa range. Importantly, some unique signals from segmented organs such as the proximal, intermediate, and distal colon were observed. Since this time, several other important scientific and clinically relevant advances have been made using this technology. For example, MALDI MS analyses of cancerous and non-cancerous human prostate cells from laser capture microdissection revealed overexpression of a protein in the cancerous tissue termed PCa-24, which potentially may be a useful prostate cancer biomarker (2). Other examples of direct analysis of peptides and proteins from intact tissues include the detection of proteins from rat pituitary (3), mouse brain (4), human brain tumor xenografts (4), and mouse prostate (5). In addition, small molecular weight pharmaceutical compounds have also been directly detected in tissue. For example, detection of the anti-cancer drug paclitaxel in rat liver and human ovarian tumor xenograft tissue using MALDI MS/MS analysis in a quadrupole ion trap instrument has been reported (6). The anti-tumor drug candidate SCH 226374 was detected in mouse tumors via MALDI MS/MS analysis in a hybrid quadrupole-time-of-flight mass spectrometer (7). Designing a MALDI MS tissue profiling experiment includes several important aspects that will optimize signal quality. Sample preparation for tissue profiling plays a crucial role in generating reproducible, quality data and is discussed below.
 |
Sample Preparation
|
---|
Sample Procurement and Sectioning
Preparation methods for MALDI MS tissue profiling must be carefully performed to maintain the spatial arrangement of compounds and avoid delocalization and degradation of the analytes. Experimental parameters that should be considered include treatment of tissue immediately after sample procurement (i.e. surgical removal, cell lysis), sectioning (i.e. temperature, section thickness), sample transfer to the MALDI target plate, matrix application, and tissue storage after sectioning. Careful handling of tissue samples, including freezing the tissue in liquid nitrogen immediately after procurement, is essential to preserve the native condition of the tissue. Tissues can remain frozen in a 80 °C freezer for over a year without significant degradation. Thin sections are cut on a cryostat for subsequent mounting onto MALDI plates. Although thickness is not critical, 1020 µm thick sections are optimal for handling and analyzing in the high vacuum environment of the mass spectrometer. Tissue blocks are mounted to the cryostat cutting stage and sliced with a stainless steel microtome blade. The sample stage temperature is typically maintained between 5 °C and 25 °C, depending on the tissue type. Tissues with high fat content require lower temperatures to achieve high quality sections. The tissue section is transferred with a light artists brush and positioned on a cold MALDI target plate. Care should be taken during the transfer to avoid deforming the tissue. With this method, there is no loss of water soluble proteins because any ice crystals that have formed on the section transfer to the MALDI plate along with the section. Unfortunately, paraffin-embedded, formalin-fixed tissues are not good candidates for MALDI MS tissue profiling because these treatments prevent efficient ionization of the proteins and peptides.
Matrix Selection and Application
Sinapinic acid (3,5-dimethoxy-4-hydroxycinnamic acid) is typically used for high molecular mass proteins whereas
-cyano-4-hydroxycinnamic acid is more commonly employed for low molecular mass proteins or peptides, i.e. below
3 kDa. Matrix concentration is also important in direct tissue analysis, affecting both the ultimate crystal coverage as well as the mass spectral signal quality. We have found that 1030 mg/ml sinapinic acid allows high quality mass spectra to be obtained from intact tissues. Matrix may be applied by either (1) depositing small droplets of matrix on specific regions of the tissue via a low volume automatic pipettes, a syringe pump attached to a small capillary (50100 µm in diameter), or an automated robotic spotter, and (2) by coating the entire tissue with a homogenous layer of the matrix solution (Fig. 1).

View larger version (25K):
[in this window]
[in a new window]
|
FIG. 1. Scheme outlining the different steps involved for profiling and imaging mass spectrometry of mammalian tissue samples. Adapted with permission from authors listed in Ref. 19.
|
|
For large sections, the tissue surface may be coated with a multiplicity of individual spots using a high density of low volume droplets. The desorption laser can sample each spot, producing a mass spectrum at one or more points in that spot. An image of a specific m/z signal can then be constructed by plotting the relative ion intensities of a given m/z signal over all the spots, providing a plot of the spatial distribution of that protein within the tissue. Image resolution is limited by two key parameters, matrix crystal size and on-target laser beam diameter. Another approach to matrix coating is to apply a continuous homogenous coating. This may be achieved using a deactivated glass spray nebulizer to spray matrix directly onto the tissue surface. The primary goal is to maximize solubilization of proteins within the tissue to enhance co-crystallization of proteins and matrix molecules while minimizing protein delocalization. For full matrix coverage over the entire tissue sample, a cycle of light matrix coatings is performed in which small volumes of matrix solution are deposited during each cycle. The sample plate is held vertically about 2030 cm from the sprayer nozzle. As matrix is nebulized from the sprayer, the device is moved parallel to the target to evenly apply matrix and just barely wet the sample surface. Deposition of a large quantity of solvent in any one region of the tissue must be avoided. The sample is allowed to dry for 12 min before the next coating cycle is performed. An average of about 10 cycles of coating and drying should be performed to achieve an even, dense crystal field. Cycling small volumes of matrix spray allows for a slow development of a dense matrix coat while minimizing the time the sample remains damp. Because different types of tissues can have different surface properties, the number of coating cycles can vary. For some samples, a more even coating is obtained when the final spray coating consists of only matrix solvent. This serves to redissolve and recrystallize the matrix, increasing the incorporation of proteins in the crystals.
A robotic device capable of acoustic droplet ejection (RapidSpotter, Picoliter Inc., Sunnyvale, CA) was developed to eject picoliter-sized matrix droplets onto the surface of the tissue, effectively coating the section. This technique allows for multiple droplet coats to be applied continuously. Droplets can therefore remain wet longer while minimizing molecule delocalization to within the droplet area. A review describing other practical aspects of direct tissue analysis has been published (8).
Histological Staining of Tissues Prior to MALDI Tissue Profiling
An important aspect of tissue profiling is to determine specific regions of interest from morphologically heterogeneous tissue sections using established histological protocols. For example, spectra from necrotic regions of tissue are significantly different from regions of cellular proliferation. This may be accomplished using two separate adjacent sections, one for histology and one for MALDI MS tissue profiling (9, 10). However, visual registration between both sections may not be easy because of differences in tissue architecture. Moreover, location of tissue features may be difficult to visualize in sections mounted on opaque media. One of the commonly used staining procedures in clinical pathology employs hematoxylin and eosin, although unfortunately the quality of the mass spectra from these sections is significantly compromised relative to that obtained from unstained sections. To circumvent these limitations, a protocol was developed to permit histology and protein profiling to be performed on the same tissue section. A series of commonly used histological dyes was tested for compatibility with mass spectrometric analysis. It was found that cresyl violet and methylene blue, as well as several other dyes, do not compromise overall mass spectra quality and allow specific regions of tissues to be easily analyzed (11). Fig. 2A shows nearly identical spectra obtained from non-stained with cresyl violet-stained mouse liver sections.

View larger version (45K):
[in this window]
[in a new window]
|
FIG. 2. A, photographs of two sections (5 µm thick) of mouse liver: (A) non-stained and (B) cresyl violet-stained. After sectioning, the sample was incubated with cresyl violet dye at room temperature for 30 s. The sample was washed for 15 s in 70% ethanol followed by a second washing in 100% ethanol. The sample was briefly dried in a desiccator, analyzed under a light microscope, and matrix deposited. Spectra are represented according to labels AD. Spectral data reveal no significant ionization differences between non-stained and stained sections. B, human STS biopsies were sectioned in a cryostat and stained with cresyl violet as described in Ref. 11. Sections were analyzed under a normal light microscope to identify regions of similar homology. A photograph of the image was made, and regions of interest were noted. Matrix was deposited specifically on identified regions, and virtually identical spectra were acquired. Spectra from the three regions were then processed and averaged.
|
|
Fig. 2B demonstrates protein profiles after cresyl violet staining of a high grade human soft tissue sarcoma (STS). Microscopic evaluation of the STS demonstrated morphological differences potentially resulting in heterogeneous spectra. However, spectra acquisition from the STS after cresyl violet staining allowed matrix to be deposited in regions specific for cellular proliferation. Notice the high level of signal homology acquired from cresyl violet-stained tissue. It is noted that for tissue profiling from histologically stained tissues, the tissue section must be transferred to electrically conductive indium-tin oxide-coated conductive glass slides for optimal spectral acquisition.
 |
Applications of Tissue Analysis
|
---|
Clinical Research Applications of MALDI MS Tissue Profiling
Early studies using direct profiling of proteins in murine tissue sections from several organs revealed hundreds of peptide and protein signals in the 230 kDa range (1). Importantly, some unique signals from segmented organs such as the proximal, intermediate, and distal colon were observed. Since this time, several other important scientific and clinically relevant advances have been made using this technology. For example, MALDI MS analyses of cancerous and non-cancerous human prostate cells from laser capture microdissection revealed overexpression of a protein in the cancerous tissue termed PCa-24, potentially useful as a prostate cancer biomarker (2). Other similar examples include studies carried out in azoxymethane-induced colon tumors in mice (12) as well as human non-small-cell lung carcinoma (NSCLC) (10). In the latter example, protein profiling from lung biopsies allowed classification of lung cancer histologies and distinguished primary tumors from metastatic lung tumors. Fig. 3 illustrates mass spectra generated from normal and cancerous human lung tissue. In this study, class-prediction models were found to classify lung tumor versus normal lung (82 MS signals) with 100% accuracy in a blinded test cohort.

View larger version (36K):
[in this window]
[in a new window]
|
FIG. 3. Detection of the optimum discriminatory biomarker sets in lung tumors. Representative MALDI time-of-flight MS spectra obtained from tumor and normal lung tissue samples are shown with the molecular weights (m/z values). Examples of the MS peaks identified by the statistical analyses as optimum discriminatory patterns between normal and tumor are indicated by asterisks.
|
|
This work also showed that protein profiling permitted discrimination between normal lung from primary NSCLC (91 MS signals), primary NSCLC could be distinguished from cancer metastatic to the lung (23 MS signals), adenocarcinoma from squamous cell carcinoma (20 MS signals), and squamous cell from large cell carcinoma (12 MS signals) with 100% accuracy between sample sets. Furthermore, protein expression patterns could also be correlated with good or poor prognosis of these cancer patients, illustrating the role of this technology in translational research. Thus, protein expression profiles were correlated to patient survival in 66 resected primary NSCLC biopsies. Significant proteins based on statistical tests were selected with known patient prognoses. To calculate a summary score for each patient, the weighted flexible compound covariate method (WFCCM) was employed, and sensitivity analysis was applied to distinguish profiles associated with survival patterns (10). Tissue profiling generated Kaplan-Meier survival curves based on proteomic patterns from 15 distinct MS peaks that divide these NSCLC patients into a group with poor prognosis (median survival 6 months, n = 25) and a group with good prognosis (median survival 33 months, n = 41, p < 0.0001).
Laser Capture Microdissection and Protein Profiling
Morphological alterations of healthy tissue may be the result of changes of many cell types. The isolation of specific cells (or cellular compartments) for protein profile analysis may be accomplished using laser capture microdissection (LCM). Briefly, a narrow laser beam (710 µm diameter) is focused onto a heat sensitive, ethylene vinyl acetate thermoplastic film. The laser heats and locally deforms the polymer, enabling contact to the cell(s) of interest. The cell binds the polymer and is lifted from the tissue section when the polymer is removed. The polymer film containing the specific cells can be transferred to a MALDI MS target plate using double-sided conductive tape. The "captured cells" are then spotted with matrix solution, and protein profiles are acquired by MALDI MS. Several reports have described the combination of LCM and MS technologies for the analysis of several cells, including normal breast stroma cells, normal breast epithelial cells, malignant invasive breast carcinoma cells, and malignant metastatic breast carcinoma cells from radical mastectomies (13, 14). Examples illustrating the combination of LCM with tissue profiling are shown in Fig. 4. Cells specific for normal breast epithelium cells, ductal carcinoma in situ, and invasive mammary carcinoma were isolated using LCM. Protein profiling shows unique protein patterns from these different disease subsets.

View larger version (31K):
[in this window]
[in a new window]
|
FIG. 4. Mass spectra from laser capture microdissected cells. Asterisks represent differentially expressed protein species between disease subsets. The figure was adapted with permission from Xu et al. DCIS, ductal carcinoma in situ; IMC, invasive mammary carcinoma.
|
|
LCM also provides a method of analyzing protein expression patterns of the same cell type but from varying disease conditions. For example, skeletal muscle cells from low grade and high grade STS might exhibit differential protein expression patterns, potentially allowing the two disease phenotypes to be better identified and understood.
Applications of MALDI MS Imaging
Imaging of a tissue section involves the generation of an ordered array of spots or pixels so that multiple molecular images can be produced from a tissue section. This array may contain several thousand (low resolution) or many tens of thousands (high resolution) pixels. We differentiate this mode from "profiling," where only several selected regions on a tissue are of interest and where a small number of pixels are used (say, 550). Thus, for high resolution images, the raster is accomplished by moving the sample under a fixed laser beam over a predetermined two-dimensional array or grid, generating a full mass spectrum at each grid coordinate. Software has been optimized to automate the scanning process, including fast data acquisition, online compression, and image reconstruction (15). Two-dimensional intensity maps can then be reconstructed to provide specific molecular images of a tissue. Typically, 20100 laser shots are averaged to provide a spectrum at every image coordinate pixel. The mass spectrum displays well over 500 distinct signals in a molecular mass range up to 100,000 Da. Protein ion density maps (or images) are obtained by displaying the intensities of specific mass-to-change values in two-dimensional space. Depending on the requirements of the analysis, image resolution can be chosen by changing the distance between the pixels.
IMS has distinct advantages over traditional techniques in ascertaining protein localization because of its unique molecular specificity. For example, Fig. 5 shows a mouse brain with a tumor (A) after sectioning with a cryostat prior to matrix coating and (B) the molecular image at m/z 11,307 (one of the isoforms of histone H4). The protein is highly expressed within the area of the tumor. Because IMS does not require an antibody or prior knowledge about potential protein targets, it is very well suited for discovery studies.

View larger version (57K):
[in this window]
[in a new window]
|
FIG. 5. An IMS analysis of a 12-µm coronal mouse brain section containing a tumor. A, photomicrograph of the section before matrix application. The area containing the tumor determined by a pathologist has been outlined in red. B, two-dimensional ion density map for a signal at m/z 11,307 is shown. This signal has been identified as histone H4. The ion density map is depicted as a pseudo-color image with white representing the highest protein concentration and black representing the lowest protein concentration. As shown, there is a higher abundance of histone H4 in the tumor area compared with the rest of the brain tissue. C, a human STS section embedded in normal tissue was mounted on a conductive glass MALDI target plate and stained with cresyl violet. The same tissue section was spray coated with matrix, and mass spectra were acquired across the specimen. A molecular image shows high concentration of 2,608 m/z in the tumor areas of the tissue section (D).
|
|
A powerful application is illustrated by imaging known proteins specific for different grades of soft tissue sarcomas.2 After the tissue was surgically excised from the patient, it was sectioned in a cryostat, stained with cresyl violet, and prepared for IMS. Fig. 5 shows the cresyl violet stain of the tissue section (C) and the image of a low grade STS protein biomarker (2,608 m/z, D). Here, higher concentrations of the protein (or peptide) were found to exist in tumor sections of the tissue. High quality images were acquired that preserved tissue integrity and permitted the localization of several other proteins that might serve as diagnostic markers for tumor behavior.
Data Mining and Statistical Analysis
One of the outcomes of MS based proteomic studies is the large amount of data produced, necessitating intensive and innovative data mining and management tools. Several available software programs address data management, including determination of statistical significance and relative abundance between particular protein species. Moreover, the need for such software amid the growing number of proteomics laboratories will ensure that such programming will be standardized, continually upgraded, and user friendly. For clinical studies, large numbers of patients need to be studied, each having unique aspects to their disease. Indeed, the base premise of individualized medicine is founded on this exciting but enormously complex molecular diversity. It is clear that innovative biocomputational studies are an absolute necessity in identifying individualized molecular patterns to aid in diagnosis and prognosis.
Examples of data analysis algorithms have been published and consist of four steps. Proteins are selected that are differentially expressed among histological groups. This selection is based on the Kruskal-Wallis test, Fishers exact test (dichotomizing the expression level as present or not), the Students t test, significance analysis of microarrays, weighted gene analysis, and the modified info score methods. The cutoff points for each method are p < 0.0001, p < 0.0001, p < 0.0001, 3.5, 2, and 0, respectively. Proteins are included in the final list if they meet at least three of these six selection criteria. The WFCCM is used in the class prediction model based on the selected proteins to verify whether the proteomic patterns could be used to classify tissue samples into two classes according to the chosen parameter, e.g. normal tissue versus tumor tissue. The WFCCM method is designed to combine the most significant proteins associated with the biological status from each analysis method, and it reduces the dimensionality of the problem using a new covariate obtained as a weighted sum of the most important predictors. The misclassification rate is estimated using the leave-one-out cross-validation class prediction method based on the WFCCM. The prediction model generated from a set of the training samples is applied to a test cohort, and blinded samples are classified on the basis of closeness of the two tissue classes determined with the WFCCM. Last, the agglomerative hierarchical clustering algorithm is applied to investigate the pattern among the statistically significant discriminator proteins.
Protein Identification
Identification of differentially expressed peptides and proteins in tissues enhances the understanding of the biological processes underlying disease. After processing of the raw mass spectra (baseline correction, Gaussian smoothing, calibration, normalization), and determination of statistical significance, a list of spectral features (m/z species) is generated. These species represent peptides and proteins with expressions that are significantly modulated by the disease. The identification strategy may vary for a particular protein because of sample complexity, protein abundance, or molecular weight. Typically, tissue is homogenized and separated into several extracts (i.e. cytoplasmic, nuclear, etc.) by a series of centrifugation steps. The crude extract of interest is separated into 6080 fractions by reverse-phase high performance liquid chromatography. Each fraction is analyzed by MALDI time-of-flight for presence of one or more protein species of interest, and the fractions are separated by one-dimensional gel electrophoresis. The gel is stained with one of several dyes, the gel bands are excised, and in-gel digestion (typically with trypsin) is performed. After digestion, the peptides are extracted from the gel and are analyzed by MS. A variety of on-line software exist for MALDI MS or electrospray ionization MS techniques that correlate peptide fragmentation patterns with theoretical protein matches found in data bases, based on peptide masses and sequence. Protein "hits" are ranked by both similarity to the theoretical pattern and coverage, i.e. the number of peptides that match the theoretical protein. Finally, immunohistochemistry can be employed to verify protein identification, assuming appropriate antibodies for the protein exist.
 |
DISCUSSION
|
---|
Tissue profiling and imaging mass spectrometry provide unique information that will greatly facilitate our understanding of normal biological and pathological processes. The high throughput nature of this technology provides the investigator with a tool to interrogate protein expression in tissue at the molecular level. IMS is still in an early stage of development, and improvements in sample preparation protocols, instrumentation, and data analysis will certainly follow. Nonetheless, the application of IMS to several clinical and biological problems demonstrates its utility in this arena. The fundamental contributions of the technology by rapidly providing molecular weight-specific maps or images at relatively high resolution and sensitivity provide a powerful tool for investigating a broad array of pathologies, chemotherapeutics, and discovery of disease biomarkers. Experiments have already been performed comparing the profiles obtained for healthy and cancerous tissue samples, and from these data several potential biomarkers were identified (16). This study also provided valuable information on the relative concentration of proteins within the section. The technology will also permit molecular assessment of disease from biopsies with the potential to identify patient subpopulations that are not evident based on the cellular phenotype determined microscopically.
Another potential application of IMS in surgical pathology is the rapid evaluation of surgical margins. There are several examples where analysis of surgical margins by frozen section is very difficult if not impossible, including lobular breast cancer, signet ring carcinomas of the gastrointestinal tract, and cholangiocarcinoma (reviewed in Ref 17). Each of these cancers is known to invade in monocellular fashion without producing a grossly identifiable mass. Given the sensitivity of MS, we envision that even a few tumor cells could be detected within a significantly larger portion of tissue. The practical implementation of MS for intraoperative margin assessment is likely to require a significant reduction in data acquisition and analysis time for scanning MS techniques to be useful for this application.
The capability of MALDI MS to measure susceptibility and response to therapeutic agents in tumor and surrounding tissues is a particularly exciting application. First, the original protein profile obtained from the primary tumor could be used to influence the selection of therapeutic agents. Levels of drugs such as chemotherapeutic agents or hormonal therapies could be measured directly from a tissue biopsy to assess the level of delivery to a particular organ site. The ability of drugs and other bioreactive molecules to effectively penetrate larger tumors is problematic and could be more adequately assessed by this technology. In addition, alterations in specific molecular pathways directly or indirectly modulated by the agent could be evaluated. This analysis could be initiated immediately after introducing the therapy and then continued at regular intervals. Studies of this type clearly establish proof of principle and have been reported (18). Similar methods could be envisioned to monitor disease relapse (or return to health) in patients treated with conservative therapy.
The information obtained from tissue profiling and IMS significantly augments but does not replace existing molecular biological techniques. Rather, these tools together will promote a more comprehensive understanding and facilitate new discoveries in biology and medicine.
 |
ACKNOWLEDGMENTS
|
---|
We thank Sarah A. Schwartz, Ph.D., and Ginger E. Holt, M.D. for expert assistance in helping obtain data presented here.
 |
FOOTNOTES
|
---|
Received, January 25, 2005
Published, MCP Papers in Press, January 26, 2005, DOI 10.1074/mcp.R500006-MCP200
1 The abbreviations used are: MALDI, matrix-assisted laser desorption ionization; MS, mass spectrometry; STS, soft tissue sarcoma; NSCLC, non-small-cell lung carcinoma; WFCCM, weighted flexible compound covariate method; LCM, laser capture microdissection; IMS, imaging mass spectrometry. 
2 R. L. Caldwell and R. M. Caprioli, manuscript in preparation. 
* This work was supported by National Institutes of Health Grants NIH/NIGMS GM58008 and NIH/NCI/NIDA CA86243. 
To whom correspondence should be addressed. Tel.: 615-322-4336; Fax: 615-343-8372; E-mail: richard.m.caprioli{at}vanderbilt.edu
 |
REFERENCES
|
---|
- Chaurand, P., Stoeckli, M., and Caprioli, R. M.
(1999) Direct profiling of proteins in biological tissue sections by MALDI mass spectrometry.
Anal. Chem.
71, 5263
5270[CrossRef][Medline]
- Zheng, Y., Xu, Y., Ye, B., Lei, J., Weinstein, M. H., OLeary, M. P., Richie, J. P., Mok, S. C., and Liu, B. C.
(2003) Prostate carcinoma tissue proteomics for biomarker discovery.
Cancer
98, 2576
2582[CrossRef][Medline]
- Caprioli, R. M., Farmer, T. B., and Gile, J.
(1997) Molecular imaging of biological samples: localization of peptides and proteins using MALDI-TOF MS.
Anal. Chem.
69, 4751
4760[CrossRef][Medline]
- Stoeckli, M., Chaurand, P., Hallahan, D. E., and Caprioli, R. M.
(2001) Imaging mass spectrometry: a new technology for the analysis of protein expression in mammalian tissues.
Nat. Med.
7, 493
496[CrossRef][Medline]
- Todd, P. J., Schaaff, T. G., Chaurand, P., and Caprioli, R. M.
(2001) Organic ion imaging of biological tissue with secondary ion mass spectrometry and matrix-assisted laser desorption/ionization.
J. Mass Spectrom.
36, 355
369[CrossRef][Medline]
- Troendle, F. J., Reddick, C. D., and Yost, R. A.
(1999) Detection of pharmaceutical compounds in tissue by matrix-assisted laser desorption/ionization and laser desorption/chemical ionization tandem mass spectrometry with a quadrupole ion trap.
J. Am. Soc. Mass Spectrom.
10, 1315
1321[CrossRef]
- Reyzer, M. L., Korfmacher, W. A., Ng, K., Hsieh, Y., and Caprioli, R. M.
(2002) Imaging of drugs in tissues by MALDI mass spectrometry. in Proc. 50th ASMS Conf. Mass Spectrometry and Allied Topics, Orlando, FL
- Schwartz, S. A., Reyzer, M. L., and Caprioli, R. M.
(2003) Direct tissue analysis using matrix-assisted laser desorption/ionization mass spectrometry: practical aspects of sample preparation.
J. Mass Spectrom.
38, 699
708[CrossRef][Medline]
- Fournier, I., Day, R., and Salzet, M.
(2003) Direct analysis of neuropeptides by in situ MALDI-TOF mass spectrometry in the rat brain.
Neuro. Endocrinol. Lett.
24, 9
14[Medline]
- Yanagisawa, K., Shyr, Y., Xu, B. J., Massion, P. P., Larsen, P. H., White, B. C., Roberts, J. R., Edgerton, M., Gonzalez, A., Nadaf, S., Moore, J. H., Caprioli, R. M., and Carbone, D. P.
(2003) Proteomic patterns of tumour subsets in non-small-cell lung cancer.
Lancet
362, 433
439[CrossRef][Medline]
- Chaurand, P., Schwartz, S. A., Billheimer, D., Xu, B. J., Crecelius, A., and Caprioli, R. M.
(2004) Integrating histology and imaging mass spectrometry.
Anal. Chem.
76, 1145
1155[CrossRef][Medline]
- Chaurand, P., DaGue, B. B., Pearsall, R. S., Threadgill, D. W., and Caprioli, R. M.
(2001) Profiling proteins from azoxymethane-induced colon tumors at the molecular level by matrix-assisted laser desorption/ionization mass spectrometry.
Proteomics
1, 1320
1326[CrossRef][Medline]
- Xu, B. J., Caprioli, R. M., Sanders, M. E., and Jensen, R. A.
(2002) Direct analysis of laser capture microdissected cells by MALDI mass spectrometry.
J. Am. Soc. Mass Spectrom.
13, 1292
1297[CrossRef][Medline]
- Palmer-Toy, D. E., Sarracino, D. A., Sgroi, D., LeVangie, R., and Leopold, P. E.
(2000) Direct acquisition of matrix-assisted laser desorption/ionization time-of-flight mass spectra from laser capture microdissected tissues.
Clin. Chem.
46, 1513
1516[Free Full Text]
- Stoeckli, M., Staab, D., Staufenbiel, M., Wiederhold, K. H., and Signor, L.
(2002) Molecular imaging of amyloid beta peptides in mouse brain sections using mass spectrometry.
Anal. Biochem.
311, 33
39[CrossRef][Medline]
- Chaurand, P., and Caprioli, R. M.
(2002) Direct profiling and imaging of peptides and proteins from mammalian cells and tissue sections by mass spectrometry.
Electrophoresis
23, 3125
3135[CrossRef][Medline]
- Chaurand, P., Sanders, M. E., Jensen, R. A., and Caprioli, R. M.
(2004) Proteomics in diagnostic pathology: profiling and imaging proteins directly in tissue sections.
Am. J. Pathol.
165, 1057
1068[Abstract/Free Full Text]
- Reyzer, M. L., Hsieh, Y., Ng, K., Korfmacher, W. A., and Caprioli, R. M.
(2003) Direct analysis of drug candidates in tissue by matrix-assisted laser desorption/ionization mass spectrometry.
J. Mass Spectrom.
38, 1081
1092[CrossRef][Medline]
- Chaurand, P., Schwartz, S. A., and Caprioli, R. M.
(2004) Profiling and imaging proteins in tissue sections by MS.
Anal. Chem.
76, 87A
93A[Medline]