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SECTION I: SYMPOSIUM I: Papers Presented at the 2005 Meeting of the Musculoskeletal Tumor Society

Proteomic Profiling in Musculoskeletal Oncology by MALDI Mass Spectrometry

Holt, Ginger, E; Schwartz, Herbert, S; Caldwell, Robert, L

Author Information
Clinical Orthopaedics and Related Research: September 2006 - Volume 450 - Issue - p 105-110
doi: 10.1097/01.blo.0000229328.68287.93


Proteomics is an emerging discipline that evaluates global protein expression profiles from a wide variety of biological materials. Amplification deficiencies and the complexities of posttranslational modifications, among other differences, have made the study of the proteome difficult.10,11 Proteomic evaluation involves the detection and characterization of the protein component of cells and tissues by partial sequence analysis and database matching.1,5 Technological discoveries to evaluate the proteome have advanced the identification and characterization of proteins in normal and diseased states. These tools include protein databases, bioinformatics, and mass spectrometry instrumentation.3,4

Other methods of protein detection exist, but mass spectrometry has proven an important tool detecting, identifying, and characterizing proteins in tissues.5 Matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) is distinguished by its ease of use, high throughput application, and protein detection sensitivity. These features make it particularly useful in the clinical application of tissue profiling and protein detection.6 MALDI MS has revolutionized the analysis of biomolecules by permitting sensitive, rapid and molecularly specific detection of proteins and peptides, often from low concentrations (pmolnmol) of complex starting material.1

Tissue profiling with MALDI MS, introduced by Chaurand et al, can identify unique proteins in human tissue.7 With this method, a fresh tissue specimen is sectioned and mounted, an energy absorbing matrix, which allows proteins to be aerosolized by the instrument's laser, is deposited on the sample, and a UV laser is used to irradiate each matrix droplet surface (desorption). The desorption process creates protonated, singly charged molecules that are accelerated down a time of flight mass spectrometer where the mass-to-charge (m/z) ratio of each ion is determined. The m/z value represents the molecular weight of the protein plus one proton. Data are collected as a series of mass spectra peaks corresponding to the desorbed peptides and proteins based on their molecular weight.

Tissue profiling has been used to evaluate lung, prostate, brain, and other cancers,2,12-15 and MALDI MS tissue profiling has recently been used to successfully subclassify and predict clinical outcome of lung tumors.12 Using surgically resected lung tumors and normal human lung tissue, hierarchical clustering of mass spectrometry signals allowed the authors to correlate tumor subtypes and clinical outcome. Class prediction models were also able to predict nodal involvement, which directly correlated with Kaplan-Meier survival analysis in 100% of 15 cases. Mass spectrometry signals were used to accurately differentiate major histological subtypes of nonsmall-cell lung cancer.

Traditionally, histologic grades based on anatomic pathology have been used to guide treatment and predict outcome in sarcoma patients.6 Survival curves have plateaued as treatment advances cannot differentiate high risk from low risk patients in the American Joint Commission on Cancer (AJCC) cancer stages.9 Protein biomarkers may allow clinicians to reclassify cancer so more aggressive treatments can be administered to the highest risk patients, to define molecular targets for novel therapeutic regimens, and improve overall understanding of oncogenesis.

Our hypothesis was MALDI MS tissue profiling technology could be used to detect differentially expressed proteins in high grade and low grade soft tissue sarcomas.


We evaluated protein profiles from high grade (n = 30) soft tissue sarcomas, low grade (n = 10) soft tissue sarcomas and skeletal muscle controls (n = 8) (Table 1). Institutional review board approval was obtained for procuring the sarcoma and control tissues from adult patients undergoing soft tissue sarcoma resections at Vanderbilt University Medical Center (VUMC). Tissues were also procured from the Cooperative Human Tissues Network at VUMC. We obtained prior Institutional Review Board approval for procuring the soft tissue sarcomas.

Number and Type of Soft Tissue Sarcoma Analyzed

After surgical excision of the tissue (patient-matched tumor and control tissue), specimens were divided for routine clinical pathology and research use. Tissue was wrapped in aluminum foil, removed from the operating room, snap frozen in liquid N2, and kept at −80°C until later use. Thin tissue sections (10-12 microns) were cut with a Leica Jung cryostat (Leica Microsystems AG, Welzlar, Germany) at −15°C from fresh snapfrozen human soft tissue sarcoma and human skeletal muscle control samples. The glass MALDI MS target plates were maintained at −15°C in the cryostat chamber. The different frozen sections were transferred to the cold target plates and thaw-mounted by warming the plate. Before staining, macroscopic drying was achieved by placing the MALDI MS target plates in a desiccator for at least 30 minutes. Several hundred microliters of cresyl violet dye were directly deposited on the sections using a Pasteur pipette and allowed to react for 30 seconds.

Excess stain was removed by plunging the plates for 15 seconds in two successive Petri dishes, containing 70% and 100% ethanol, respectively. The sections were allowed to dry in a desiccator for up to 30 minutes. Photomicrographs of the sections were obtained under magnification using an Olympus BX 50 microscope (Olympus America Inc, Melville, NY) equipped with a digital camera. Regions of cellular proliferation were identified for depositing matrix.

Matrix (sinapinic acid at 30 mg/mL in a mixture of 50:50:0.1 acetonitrile/H2O/trifluoroacetic acid by volume) was deposited in discrete droplets on the various tissue sections. Two 200 nL drops of matrix were successively deposited on the section at the same regions identified after cresyl violet staining and allowed to dry. The first droplet was allowed to almost dry before the second droplet was deposited. After matrix deposition, the sections were allowed to dry in a desiccator for at least 30 minutes (Fig 1).

Fig 1A
Fig 1A:
D. Photomicrographs describe soft tissue sarcoma tissue preparation for cresyl violet staining and MALDI MS tissue profiling. (A) Tissues are sectioned in a cryostat (12 μm thick) and transferred to a conductive glass slide (stain, cresyl violet; magnification, 4×). (B) Sections are stained with cresyl violet and evaluated under a light microscope for specific regions to be tissue profiled (regions 1-3 in red) (stain, cresyl violet; magnification, 4×). (C) Matrix (200 nL) is deposited on the specific tissue regions (1-3) and allowed to dry in a desiccator for 30 minutes (stain, cresyl violet; magnification, 4×). (D) Highly homologous spectra (1-3) are acquired from specific regions in the intact tissue and are averaged to generate a mass spectrum representative of proteins expressed in regions of cellular proliferation.

Mass spectrometric analyses were performed in the positive linear mode at +25 kV of accelerating potential on an Applied Biosystems Inc (Framingham, MA) Voyager DE-STR time-of-flight mass spectrometer under optimized delayed extraction conditions for all of the investigated tissue sections. This mass spectrometer is equipped with a 337 nm N2 laser capable of operating at repetition rates of 3 or 20 Hz. Data were internally calibrated with peaks from hemoglobin alpha and beta chains. A baseline of each spectrum was corrected by use of Data Explorer software (Applied Biosystems, Foster City, CA) and used for additional statistical analyses.

To verify observations from MALDI MS tissue profiling, immunohistochemistry was performed to detect calcyclin (10090 m/z) overexpression in high grade soft tissue sarcoma compared with low grade soft tissue sarcoma and control. Tissue sections from control tissue, low and high grade soft tissue sarcoma were paraffin embedded and sectioned (5 μm) in a microtome. The sections were floated over a warm water bath (40°C) and transferred to a slide and baked overnight. Slides were deparaffinized through two changes of xylene for 20 minutes each, then two changes each of 100% and 95% alcohol for 10 minutes each. They were placed in a phosphate-buffered saline (PBS) buffer solution, then incubated in 95° C target retrieval solution (TRS, citrate buffer) for 20 minutes and allowed to cool for 20 minutes in TRS. The slides were placed back into PBS buffer. One hundred μL of peroxidase blocking reagent was placed on each section and allowed to stand for 10 minutes. After a buffer rinse, 100 μL of protein block was added to each section for 10 minutes, followed by another buffer rinse. A 1:1000 dilution of S100A6 (Sigma, St Louis, MO) was then added in 100 μL portions to each section and left to incubate overnight at 4ºC and rinsed with buffer the following day. The secondary antibody, a labeled mouse/rabbit dual polymer with peroxidase, was added for 30 minutes (100 μL/section). Another buffer rinse was followed by a 3 minute distilled water step, with 100 μL of distilled water added to each section. Two more buffer rinses were followed by addition of diaminobenzidine (DAB) + (100 μL/section) for a 10 minute incubation period. The slides were briefly rinsed in buffer and counterstained with hematoxylin for approximately 1 minute. A 5 minute water rinse was then used to remove any excess hematoxylin. The slides were cleared of water through two changes each of 95% and 100% alcohol for 10 dips. After 1 minute sessions through two changes of xylene, the slides were permanently secured with mounting media and cover glass.

Analyses were performed to determine the statistical significance of peaks representing differentially expressed proteins. Peak heights from the individual spectra after normalization were entered into the statistical software package InStat (Graph- Pad Software, San Diego, CA), and the ANOVA Tukey-Kramer multiple comparisons test was used to test statistical differences between high grade soft tissue sarcoma and control tissue samples. Statistical significance was determined as p ≤ 0.05.


We found differentially expressed proteins in high grade and low grade soft tissue sarcomas. There were no differences between low grade and control tissues. Calcyclin (p = 0.02), macrophage inhibitory factor (MIF) (p = 0.05), and calgranulin (p = 0.001) were overexpressed in the high grade soft tissue sarcoma when compared to soft tissue sarcoma and controls (Figs 2 and 3). Immunohisto-chemistry confirmed an increase in calcyclin, staining in high grade versus low grade soft tissue sarcoma and control tissues (Fig 4).

Fig 2
Fig 2:
Averaged mass spectra overlay from high grade STS, low grade STS, and skeletal muscle control from m/z 4000 to 24,000. Protein profiles from each category were internally calibrated, baselined and normalized before averaging. Each peak represents one specific protein expressed in the intact tissue specimen. The y-axis represents signal intensity and the x-axis represents the mass-to-charge ratio. (A) This graph shows signal intensity (0 to 1500), m/z from 4500 to 8000. (B) This graph shows signal intensity (0 to 2500), m/z from 12,000 to 24,000.
Fig 3
Fig 3:
The mass-to-charge (m/z) species representative of soft tissue sarcoma subsets and control tissue are shown. Differentially expressed m/z species in each tissue category are shown. The species outlined in control tissues are consistently absent in the tumor categories. After normalization, peak heights were used to compute statistical significance.*=p < 0.05, **=p < 0.01, *** = p < 0.001.
Fig 4A
Fig 4A:
C. The abundance of S100A6 staining observed from the high grade soft tissue sarcoma section compared with low grade and control tissue is comparable to the MALDI MS profiling data. (A) Immunohistochemical staining for S100A6 from smooth muscle control (stain, IHC or S100A6, magnification, 100×A). (B) Immunohistochemical staining for S100A6 from low grade soft tissue sarcoma (stain, IHC or S100A6, magnification, 100×A). (C) Immunohistochemical staining for S100A6 from high grade soft tissue sarcoma (stain, IHC or S100A6, magnification, 100×A).

Besides modulated protein expression between high grade and low grade soft tissue sarcoma, several peaks were also observed that were absent in soft tissue sarcoma tissue compared with control tissues. These peaks are currently under evaluation for identification.


The purpose of this report is two-fold. In a broader view, it introduces a new proteomic tool, tissue profiling mass spectrometry, to the orthopaedic research community. Secondly, it summarizes a recent application of the technology aimed to detect protein biomarkers differentiating STS grades. Tissue profiling permitted rapid and reproducible assessment of hundreds of proteins from specific regions of intact STS and skeletal muscle control specimens. Many differences in protein expression were observed between tumor grades and control. Consistent with standard histological analysis, we detected no differences between control and low grade STS tissues. Several of these m/z signals were identified by protein isolation, peptide mass fingerprinting and sequencing. Finally, immunohisto-chemical analysis was performed to validate the findings when appropriate antibodies existed.

Study limitations include sample size and database limitations. Small numbers are inherent to sarcoma research as were the small number of samples available for evaluation. Despite this, we had adequate power to identify differences. As more samples are prospectively accrued the power of analysis will certainly increase.

A limitation to MALDI-TOF protein identification is a series of time consuming steps (3-4 days) including tissue homoginization, partial protein purification and peptide sequencing. Technological advances such as automation and in situ protein sequencing are decreasing time requirements for this high throughput process.

The findings we report are similar to those for previous MALDI MS cancer prediction model evaluations, including those of nonsmall cell lung carcinoma and glioblastoma multiforme.12,14 In these studies high grade and low grade proteomic profiles successfully correlated with histologic controls. Several proteins found in high grade sarcomas have been previously identified in other cancers.8,13 Calcyclin, for example, has been overexpressed in these highly invasive cancers.10

Research endeavors currently stemming from this work include identification of biomarkers that: (1) predict lung metastasis from the primary sarcoma; and (2) augment histologic classification of sarcoma subsets that are difficult to differentially diagnose. Finally, detection of tumor biomarkers in patient-matched serum may permit a relatively noninvasive diagnostic test to determine a patient's response to therapy or tumor behavior.


The authors are grateful to Richard M. Caprioli, PhD, Stanley E. Cohen, Professor of Biochemistry, for the use of his laboratory in preparation for this manuscript.


1. Aebersold R, Goodlett DR. Mass spectrometry in proteomics. Chem Rev. 2001;101:269-295.
2. Banez LL, Srivastava S, Moul JW. Proteomics in prostate cancer. Curr Opin Urol. 2005;15:151-156.
3. Brown RS, Lennon JJ. Mass resolution improvement by incorporation of pulsed ion extraction in a matrix-assisted laser-desorption ionization linear time-of-flight mass-spectrometer. Anal Chem. 1995;67:1998-2003.
4. Chaurand P, DaGue BB, Pearsall RS, Threadgill DW, Caprioli RM. Profiling proteins from azoxymethane-induced colon tumors at the molecular level by matrix-assisted laser desorption/ionization mass spectrometry. Proteomics. 2001;1:1320-1326.
5. Chaurand P, Sanders ME, Jensen RA, Caprioli RM. Proteomics in Diagnostic pathology: profiling and imaging proteins directly in soft tissue sections. Am J Pathol. 2004;165:1057-1068.
6. Chaurand P, Schwartz SA, Billheimer D, Xu BJ, Crecelius A, Caprioli RM. Integrating histology and imaging mass spectrometry. Anal Chem. 2004;76:1145-1155.
7. Chaurand P, Stoeckli M, Caprioli RM. Direct profiling of proteins in biological tissue sections by MALDI mass spectrometry. Anal Chem. 1999;71:5263-5270.
8. Crnogorac-Jurcevic T, Missiaglia E, Blaveri E, Gangeswaran R, Jones M, Terris B, Costello E, Neoptolemos JP, Lemoine NR. Molecular alterations in pancreatic carcinoma: expression profiling shows that dysregulated expression of S100 genes is highly prevalent. J Pathol. 2003;201:63-74.
9. Greene FL, Page DL, Fleming ID, eds. American Joint Commission on Cancer Staging Manual, 6th ed. New York: Springer-Verlag; 2002.
10. Liebler DC. Introduction to Proteomics: Tools for the New Biology. Totowa NJ: Humana Press Inc; 2001.
11. Roepstorff P. Mass spectrometry in protein studies from genome to function. Curr Opin Biotechnol. 1997;8:6-13.
12. Schwartz SA, Weil RJ, Johnson MD, Toms SA, Caprioli RM. Protein profiling in brain tumors using mass spectrometry: feasibility of a new technique for the analysis of protein expression. Clin Cancer Res. 2004;10:981-987.
13. Stulik J, Osterreicher J, Koupilova K, Knizek J, Bures J, Jandik P, Langr F, Dedic K, Schafer BW, Heizmann CW. Diferential expression of the Ca++ binding SA100A6 protein in normal, preneoplastic and neoplastic colon mucosa. Eur J Cancer. 2000;36:1050-1059.
14. Yanagisawa K, Shyr Y, Xu BJ, Massion PP, Larsen PH, White BC, Roberts JR, Edgerton M, Gonzalez A, Nadaf S, Moore JH, Caprioli RM, Carbone DP. Proteomic patterns of tumour subsets in non-small-cell lung cancer. Lancet. 2003;362:433-439.
15. Zheng Y, Xu Y, Ye B, Lei J, Weinstein MH, O'Leary MP, Richie JP, Mok SC, Liu BC. Prostate carcinoma tissue proteomics for biomarker discovery. Cancer. 2003;98:2576-2582.
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