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Clinical Cancer Research 14, 1002, February 15, 2008. doi: 10.1158/1078-0432.CCR-07-1497
© 2008 American Association for Cancer Research
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Human Cancer Biology

Proteomic Analysis of Laser-Captured Paraffin-Embedded Tissues: A Molecular Portrait of Head and Neck Cancer Progression

Vyomesh Patel1, Brian L. Hood2, Alfredo A. Molinolo1, Norman H. Lee4, Thomas P. Conrads2, John C. Braisted5, David B. Krizman3, Timothy D. Veenstra2 and J. Silvio Gutkind1

Authors' Affiliations: 1 Oral and Pharyngeal Cancer Branch, National Institute of Craniofacial and Dental Research, NIH, Bethesda, Maryland; 2 Laboratory of Proteomics and Analytical Technologies, Science Applications International Corporation-Frederick, Inc., National Cancer Institute, Frederick, Maryland; 3 Expression Pathology Incorporated, Gaithersburg, Maryland; 4 Department of Pharmacology and Physiology, The George Washington University Medical Center, Washington, District of Columbia; and 5 Pathogen Functional Genomics Resource Center, J. Craig Venter Institute, Rockville, Maryland

Requests for reprints: J. Silvio Gutkind, Oral and Pharyngeal Cancer Branch, National Institute of Dental and Craniofacial Research, NIH, 30 Convent Drive, Building 30, Room 211, Bethesda, MD 20892-4330. Phone: 301-496-6259; Fax: 301-402-0823; E-mail: sg39v{at}nih.gov.


   Abstract
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 Abstract
Materials and Methods
 Results
 Discussion
 References
 
Purpose: Squamous cell carcinoma of the head and neck (HNSCC), the sixth most prevalent cancer among men worldwide, is associated with poor prognosis, which has improved only marginally over the past three decades. A proteomic analysis of HNSCC lesions may help identify novel molecular targets for the early detection, prevention, and treatment of HNSCC.

Experimental Design: Laser capture microdissection was combined with recently developed techniques for protein extraction from formalin-fixed paraffin-embedded (FFPE) tissues and a novel proteomics platform. Approximately 20,000 cells procured from FFPE tissue sections of normal oral epithelium and well, moderately, and poorly differentiated HNSCC were processed for mass spectrometry and bioinformatic analysis.

Results: A large number of proteins expressed in normal oral epithelium and HNSCC, including cytokeratins, intermediate filaments, differentiation markers, and proteins involved in stem cell maintenance, signal transduction, migration, cell cycle regulation, growth and angiogenesis, matrix degradation, and proteins with tumor suppressive and oncogenic potential, were readily detected. Of interest, the relative expression of many of these molecules followed a distinct pattern in normal squamous epithelia and well, moderately, and poorly differentiated HNSCC tumor tissues. Representative proteins were further validated using immunohistochemical studies in HNSCC tissue sections and tissue microarrays.

Conclusions: The ability to combine laser capture microdissection and in-depth proteomic analysis of FFPE tissues provided a wealth of information regarding the nature of the proteins expressed in normal squamous epithelium and during HNSCC progression, which may allow the development of novel biomarkers of diagnostic and prognostic value and the identification of novel targets for therapeutic intervention in HNSCC.

Head and neck squamous cell carcinoma (HNSCC) is the sixth most frequent cancer in the United States and the fourth most prevalent cancer among men worldwide (1). The prognosis of HNSCC patients is relatively poor, largely due to the advanced nature of the disease at the time of diagnosis. The identification of the molecular mechanisms underlying HNSCC initiation and progression could aid in the development of new diagnostic and treatment options for this disease (2, 3). In this regard, analysis of mRNA transcripts using high-throughput gene array analysis has helped identify numerous molecules that may contribute to cancer development (reviewed in ref. 4). A shortcoming of this approach, however, stems from the discordance between transcript levels and protein abundance in a highly complex and readily changing disease microenvironment such as cancer (5). A proteomic analysis is urgently needed, as it allows the comprehensive assessment of the distinct molecular profile of each cancer type, thus affording the opportunity of identifying novel prognostic markers and therapeutic targets (6).

Improved protein extraction protocols (7) combined with recently developed mass spectrometry (MS) techniques and fully annotated genomic databases has allowed the identification of trace amounts of proteins present in complex samples (8). Furthermore, the combination of proteomic analysis with laser capture microdissection may afford performing the proteomic characterization of normal and pathologic cell populations from clinical specimens, thus reflecting their protein make up as they exist in vivo (9). We have recently conducted the first proteome-wide analysis of microdissected frozen HNSCC tissue (10). Although protein recovery was acceptable, challenges related to the poor histology and limited availability of appropriately preserved frozen tissue samples still remain.

Formalin fixation and tissue embedding in paraffin wax (FFPE) is a universal approach for tissue processing, histologic evaluation, and routine diagnosis, as it preserves the cellular morphology and tissue architecture. FFPE clinical specimens, however, are not routinely used for MS-based proteomic studies because formaldehyde-induced cross-linking renders proteins relatively insoluble and unsuitable for extraction and subsequent MS analysis (11). In this study, we combined the use of laser capture microdissection, newly developed procedures enabling the extraction of peptides directly from FFPE samples, and optimized chromatographic approaches to undertake a large-scale proteomic study to identify proteins expressed in FFPE HNSCC tissues. We show that this novel proteomics platform enables the identification of hundreds of proteins expressed in normal oral epithelium and cancerous HNSCC lesions. A large number of differentiation markers, stem cell proteins, and molecules that are likely to play key roles in aberrant cell growth, including proteins involved in cell cycle control, angiogenesis, and metastasis, were identified. These proteins may represent novel biomarkers with diagnostic and prognostic value for HNSCC, as well as new potential molecular targets for pharmacologic intervention in this disease.


   Materials and Methods
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 Abstract
 Materials and Methods
Results
 Discussion
 References
 
Tissues. Appropriate paraffin blocks of formalin-fixed tissues from normal squamous epithelium (n = 4), and well differentiated (WD; n = 4), moderately differentiated (MD; n = 4), and poorly differentiated (PD; n = 4) HNSCC were retrieved from the Head and Neck Cancer Tissue Array Repository (TMA)6 (12), under an approved Research Activity Involving Human Subjects protocol, from the Office of Human Subjects Research, NIH, involving the use of anonymous normal and HNSCC tissues. Before analysis, H&E-stained section from each sample was evaluated and the suitability of inclusion for the study was determined. Five-micrometer sections were used for all subsequent analysis.

Immunohistochemistry. Primary antibodies used for validation studies include mouse anti–desmoglein-3 (Invitrogen; 1:25), rabbit anti-cytokeratin 4 (Abcam; 1:100), mouse anti-cytokeratin 16 (Abcam; 1:25), rabbit anti-desmoplakin antibody (Abcam; 1:200), and mouse anti-vimentin (Dako; 1:100). Secondary antibodies conjugated with biotin (Vector) were used, diluted to 1:400. Tissue slides containing archival FFPE sections, or tissue microarrays (TMA)6 consisting of 508 HNSCC and controls, were processed for immunohistochemical analysis as described in Supplementary Material.

Laser capture microdissection and protein extraction. FFPE oral cancer tissue sections were deparaffinized in SafeClear II, hydrated, and stained in Mayer's hematoxylin followed by dehydration as described in Supplementary Material. For laser capture microdissection, stained uncovered slides were air dried and ~20,000 cells were captured onto CapSure LCM Caps (MDS Analytical Technologies) using a PIXCELL IIe microdissection equipment (MDS Analytical Technologies). Caps were transferred to a 0.5 mL sterile Eppendorf tube for protein extraction using the Liquid Tissue MS Protein Prep kit according to the manufacturer's protocol (Expression Pathology, Inc.), as described in Supplementary Material.

Tandem MS and bioinformatic analysis. FFPE-extracted samples were processed, quantified, and used for nanoflow reversed-phase liquid chromatography followed by tandem MS, as described in Supplementary Material. The spectra were searched against the UniProt human protein database (06/2005 release) from the European Bioinformatics Institute7 using SEQUEST (Thermo Electron). Results were further filtered using software developed in-house to determine unique peptides and proteins, which has a predicted error <1.5% (13).

To facilitate the biological interpretation of the extensive protein lists generated in these studies, the protein accession numbers were used to classify the proteins in Gene Ontology categories, based on their biological process and molecular and cellular functions (14), and to perform Expression Analysis Systematic Explorer analysis,8 which enables the discovery of enriched biological themes within gene/protein lists, and the generation of protein annotation tables.


   Results
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 Abstract
 Materials and Methods
 Results
Discussion
 References
 
HNSCC samples and laser capture microdissection. To gain insight into the nature of proteins expressed during HNSCC progression, we conducted a proteomic analysis of FFPE HNSCC tumors arising within the oral cavity. Tissue samples were classified using light microscopic examination of H&E-stained sections into normal (i.e., oral stratified epithelia lacking malignant features) or squamous carcinomas that were WD, MD, or PD. Each group consisted of four independent samples. The available clinical information is included in Table 1 . The analytic workflow for the overall study is depicted in Fig. 1 , which is the result of combining two different technology platforms, laser capture microdissection, and tandem MS. As shown schematically (Fig. 1A) and in detail (Fig. 1B), laser capture microdissection is well suited for the rapid procurement of specific cell populations, which are captured onto caps for immediate processing and analysis. The complexity of the resulting peptide mixture extracted from each sample is exemplified in Fig. 1A by the base peak spectrum of a representative WD HNSCC tumor (right). A tandem MS spectrum identifying a peptide originating from vimentin is also shown in this figure. This proteomic platform results in broad dynamic range of peptide measurements, which may aid in the identification of important molecules involved in squamous carcinogenesis as well as biomarkers for HNSCC progression.


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  		Table 1. Clinical features of HNSCC cases and summary of the liquid chromatography–tandem MS data

 

Figure 1
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  		Fig. 1. Work flow for protein analysis of FFPE oral squamous cell carcinoma. A, different steps involved in the process of protein analysis from laser-captured FFPE cancer tissues, including (from left to right) tissue biopsy, laser capture microdissection, sample preparation, and analysis by reversed-phase liquid chromatography–tandem MS. The latter involves the initial separation of complex peptide mixtures by Nanoflow reversed-phase liquid chromatography, followed by LIT MS. A complex base peak chromatogram of a representative HNSCC case is included, as well as the tandem MS spectra of a selected peptide whose identity was confirmed as vimentin. B, laser capture microdissection of a WD FFPE oral squamous cell carcinoma (top left). The area of interest is pulsed with laser (bottom left) and captured cells were retrieved on a cap (bottom right). Remnant tissue remains on the slide (top right).

 
Protein abundance in normal and tumor HNSCC. Samples containing ~20,000 cells were processed as described in Materials and Methods and analyzed using gas phase fractionation in the m/z dimension (GPFm/z). To enable the comparison of protein expression across all tissue samples, we used a spectral count method in which each protein that was identified in any one set was evaluated based on the number of unique peptides identified, and the total number of times that those peptides were observed in five successive runs for each set (Table 1). The number of proteins identified for each set as a group (all four sample results pooled together) ranged from 391 in the normal oral epithelia to 866 total proteins in the WD HNSCC tumors.

The data sets for each group of clinical samples were sorted based on the number of peptides identified in all tissues combined and the percentage of these total peptides detected in normal and each of the classified HNSCC tissues. Those proteins detected in normal and all HNSCC tissues are listed in Table 2 and sorted based on the number of identified peptides. As indicated, 115 proteins were identified as shared across all normal and tumor tissues. The utility of this overall approach is reflected in the identification of 49 peptides for glyceraldehyde-3-phosphate dehydrogenase, a protein product of a housekeeping gene routinely used to normalize gene expression experiments. In spite of observing fewer overall peptides in normal oral epithelia, which may have resulted from a reduced protein recovery from these samples, the relative detection level of glyceraldehyde-3-phosphate dehydrogenase was nearly equal across all tissue groups analyzed in this study. Thus, it is also possible that normal tissues might exhibit a greater diversity of molecules, therefore fewer achieving the lowest limit of detection of our current analytic method.


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  		Table 2. Proteins identified in both normal and tumor HNSCC tissues

 
Two groups of proteins, cytokeratins and desmosomal proteins, stood out as the most abundant in all four-tissue sets. With few notable exceptions, most keratins were nearly equally represented across all tissue samples. For example, cytokeratin 5, a keratin expressed in basal layer of normal stratified epithelia, was the most abundant and was identified by a similar number of peptides in each tissue group. Cytokeratin 14, another basal keratin, was less abundant in normal tissues. Conversely, cytokeratin 4, which is expressed in the nonkeratinazing layer of stratified epithelium, was more abundant in the normal samples. Desmosomal proteins, including desmoplakin, plakophilin 1, periplakin, and desmoglein precursors, were prominent in all samples. Also notable in this list were the family of calcium-binding proteins (calgranulin A, calgranulin B, S100 A14, calmodulin-like protein), keratinocyte differentiation markers (involucrin, small proline-rich protein 3, profilin 1, cornifin A, cornifin B), and many membrane-related molecules (Annexin A1, actin-like protein 2). A number of proteins including heat shock protein 27 (HSP27) (15), HSP70 (16), and glutathione S-transferase (15), expected to be of higher abundance in tumor samples, were identified. A number of signaling molecules (e.g., Ras GTPase-activating-like protein IQGAP1, obscurin, tyrosine-protein kinase ITK) were also identified. Conversely, the DNA excision repair protein ERCC-5 was found to be less abundant in tumor samples. These data indicate that the analysis of FFPE tissues enables the identification of a broad range of functionally diverse proteins in normal and tumor squamous epithelia, albeit many exhibit a distinct expression profile.

Proteins detected only in HNSCC. Having identified common proteins in both normal and tumor samples, a list of molecules only identified in tumor samples was collated (Table 3 ). Forty-two proteins unique to HNSCC were readily detected by multiple peptides (>10). Among them, the most abundant was vimentin, a protein involved in epithelial-mesenchymal transition. A variety of proteins involved in cell migration, signaling, and proteolysis were also identified. Eighty-five less abundant proteins (i.e., identified by >4 peptides but <10 peptides) across all tumor samples were also detected. This group included proteins involved in DNA synthesis, metabolism, and cell signaling. These data provide a list of proteins that may play a putative role in tumor progression.


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  		Table 3. Proteins identified only in tumoral HNSCC tissues

 
Proteins detected in normal oral squamous epithelium. To gain insight into the proteins identified exclusively in normal samples, the initial data set was sorted to filter out molecules not found within the tumors, in descending order based on peptide numbers (Supplementary Table S1). The proteins in this list were identified by fewer peptides, reflecting their lower abundance in normal oral squamous epithelium. Interestingly, proteins identified by ≥3 unique peptides included the low-density lipoprotein receptor-related protein 12 precursor, also known as suppressor of tumorigenicity protein 7, and two particular proteins identified with a single peptide included, activin β B chain and adenomatous polyposis coli protein. The data indicate that a subset of proteins are expressed preferentially in normal tissues, indicating that they could play a role in any of the biological functions done by normal stratified oral epithelium, including maintenance of normal differentiation program and tumor suppression.

Proteins detected in differentiated tumor tissues. Proteins of interest detected exclusively in the WD tumors, albeit with few peptides, included those involved in the dynamic function of the cytoskeleton, as well as molecules stimulating the Notch pathway, such as Delta 4 and Delta 1 (Supplementary Table S2). Proteins of interest and detected only in the MD group with one peptide include Wilms' tumor-associated protein and esophageal cancer–related gene-coding leucine-zipper motif, and unusual cadherins and desmosomal proteins for epithelial cells such as placental cadherin and protocadherin {gamma} A6 (Supplementary Table S3). Interesting proteins detected only the PD group include the potential oncoprotein AF1q (17), two peptides derived from epithelial protein lost in neoplasm, and numerous proteins involved in cell cycle control and fatty acid metabolism and membrane trafficking (Supplementary Table S4).

Comparisons of proteins between samples. The list of proteins identified in each group was also compared to explore whether they could increase our understanding of HNSCC pathogenesis and its progression. Proteins identified only in normal and WD tumors by ≥3 peptides included the stem cell protein PIWIL3 (ref. 18; Table 4 ; Supplementary Table S5). A number of proteins were common to WD and MD tumors, represented by oncoprotein DJ-1 (Supplementary Table S6). Similarly, common proteins between MD and PD tumors included the tumor promigratory protein JWA. Notably, low-abundance proteins shared by the same group of HNSCC tumors also included signal transducer and activator of transcription 3, its activating kinase, Janus-activated kinase 2, and the key translational regulating protein mammalian target of rapamycin (Supplementary Table S7), which are implicated in HNSCC progression (19, 20). Full lists of proteins for these comparisons are available in Supplementary Tables S5 to S7.


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  		Table 4. Representative proteins of interest for HNSCC

 
Gene ontology analysis. Analysis of each sample set resulted in the identification of a large number of proteins. Therefore, it was necessary to integrate these data based on our currently available knowledge of biological functions to determine their individual biological roles and to recognize categories of proteins that may be underrepresented or overrepresented in tumors. For this, we used bioinformatic tools to classify proteins across each of the HNSCC tumor types into different gene ontology categories. This approach enabled the examination of the overall cellular compartment in which the identified proteins are expected to reside and function. Although a minimal difference was observed between normal and HNSCC samples, we found that 133-295, 10-21, 77-185, and 86-184 proteins were associated with the cytoplasm, extracellular matrix, membrane, and the nucleus, respectively. Analysis of the biological processes in which these proteins act revealed several groups of molecules that were highly represented in tumors, many involved in cell adhesion, cell cycle, cell differentiation, cellular metabolic process, cell motility, endopeptidase activity, signal transduction, and gene transcription and translation, closely aligned with the processes of carcinogenesis. Indeed, a large number of proteins belonging to these functional groups were ascribed to tumors, and to their normal tissue counterpart, albeit to a lesser extent (Supplementary Table S8). A detailed list of molecules predicted to participate in signal transduction (238 proteins), protein phosphorylation (39 proteins), endopeptidase activity (35 proteins), cell motility (47 proteins), cell cycle regulation (99 proteins), and cell adhesion (71 proteins) across normal tissues and the different tumor phenotypes is provided in Supplementary Tables S9 to S14.

Detection of novel proteins in normal and tumor HNSCC. A key advantage afforded by this proteome-wide analysis is the potential for discovery of new molecules yet to be described for normal and malignant oral squamous tissues. Several hypothetical novel proteins, whose existence is predicated on computational analysis of open reading frames (21), were found to be present in normal and tumor samples. These proteins were collated and organized in descending order based on peptide number. As seen in Supplementary Table S15, the majority of the proteins with ≥4 peptides were detected in either tumor or normal samples. Collectively, the emerging information identified many novel proteins in normal and tumor samples, whose nature can now be analyzed. In this regard, structural features of these previously predicted proteins are quite diverse and suggestive of multiple roles in signal transduction, cell communication, and secretion, among others. Future work could help establish their possible role in HNSCC development and progression.

Proteins identified as of interest for HNSCC. The ability to discriminate subsets of proteins differentially abundant within normal oral squamous epithelia and tumors exhibiting distinct differentiation characteristics provided an opportunity to mine the data to identify proteins of interest as well as putative biomarkers of HNSCC development and progression. A selected group of molecules identified as being differentially abundant were sorted by total peptide number and their relative distribution across the normal and tumor samples (Table 4). Notably, the peptide distribution of the cytokeratins 14, 17, and 16 was observed to be lower in the normal samples compared with the WD, MD, and PD tumor samples. By contrast, the peptide distribution of cytokeratin 4 was higher in normal (~77%) compared with the tumor samples (~4-12%). Also included in the list are cytokeratins 7 and 18 albeit with a lower peptide number. The relative distribution indicates that these molecules are less abundant in normal samples than in MD and PD tumors, respectively. Molecules involved in cell-to-cell interaction were also identified as potential biomarkers and include desmoplakin, democollin 2A/2B, demoglein 3 precursor, plakophilin 1, and plakophilin 3. The total peptide number for this group of proteins ranged from 7 to 385, with a relative similar distribution in all samples with the exception of democollin 2A/2B, which was undetectable in normal samples. Furthermore, from the total peptide number of 385 for desmoplakin, ~44% of these were detected in well-differentiated tumors and in the other samples indicating close to equal levels. Other proteins of interest include HSP27 and HSP70, vimentin, glutathione S-transferase, and integrin β4. In all these proteins, the distribution of peptides was low to undetectable in normal samples when compared with the tumors. Among the latter, we found proteins that may play a role in tumor progression, such as SET protein (phosphatase 2A inhibitor I2PP2A) and ELAV-like protein 1 (Hu-antigen R), and many surface proteins, including 4F2 cell surface antigen heavy chain (CD98), and, as described above, integrin β4 (CD104 antigen), which may represent promising markers to study tumor progression.

Validation of biomarkers by immunohistochemistry. Having identified proteins of potential interest to HNSCC progression, a subset of these were chosen for validation based on the relative abundance of corresponding peptides in the different samples analyzed. Validation studies were conducted using standard immunohistochemistry in archival HNSCC tissues followed by in-depth analysis of hundreds of HNSCC cases using a recently developed HNSCC-specific TMA. As seen in Fig. 2A , cytokeratin 4 was detected predominantly in the suprabasal layers of the control normal tissues, whereas the expression of this molecule in HNSCC tumors was restricted to only few cells in <20% of WD tumors. Most MD to WD cells stained positive for cytokeratin 16, whereas in the normal tissues this protein was present in the suprabasal layers of the oral squamous epithelium (second from top). Desmoplakin (third from top) was found to be predominantly membranous, with a higher immunoreactivity in the suprabasal areas of the squamous epithelium in normal tissues. Tumor cells showed intense staining of the membrane together with a moderate to strong cytoplasmic staining, distributed mostly along the more differentiated areas of all the tumor cases examined. Analysis of desmoglein-3 (fourth from top) showed sharp staining within the membrane in normal oral squamous mucosa with a stronger signal in suprabasal layers. Desmoglein-3 was also positive in all tumor samples, following a membrane distribution and a less intense cytoplasmic signal. Immunodetection of vimentin (bottom) was positive in only a few normal isolated cells with very distinct dendritic-like morphology in the oral squamous epithelium, whereas the underlying stromal cells were all intensely stained. By contrast, a high proportion of the malignant squamous cells in the tumor cases showed increased immunoreactivity to vimentin. Collectively, the data indicate that the profile of protein expression identified using MS is reflected in an independent archival HNSCC sample set.


Figure 2
Figure 2
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  		Fig. 2. Validation of biomarkers by immunohistochemistry on archival HNSCC tissues. A, archival tissues consisting normal and tumor HNSCC were processed and used for immunodetection of the indicated proteins with appropriate antibodies as described in Materials and Methods. B, analysis of HNSCC biomarkers in HNSCC-specific TMA. Head and neck–specific TMAs consisting of control and WD, MD, and PD HNSCC tumor samples were stained for indicated proteins with appropriate antibodies as described in Materials and Methods. Representative TMA cores are depicted (top). Stained TMAs were "scored" based on tissue differentiation and staining intensity. For cytokeratin 4 and cytokeratin 16, light gray represents >5% and <25% of cells stained; mid gray, 26% to 50% of the cells stained; dark gray, 51% to 75%; and black, 76% to 100% of the cells stained. For vimentin and desmoplakin, the percentage of positive tumors for each stage of differentiation (black box) compared with negative (white box) is depicted. In each case, the number of nonneoplastic (Normal) tissues analyzed was 10, and the number of HNSCC cancer tissues is indicated.

 
The previous data indicated that a subset of proteins (cytokeratin 4, cytokeratin 16, vimentin, and desmoplakin) could effectively distinguish the differing differentiation compartments in archival HNSCC tissues. Therefore, we chose to use an oral cancer–specific TMA for the high-throughput staining and scoring of these predictive immunohistochemical markers in this cancer type. As shown in Fig. 2B (top), although cytokeratin 4 was poorly expressed in the majority of the tumors (left and inset), strong staining for cytokeratin 16 in HNSCC was observed almost exclusively in WD tumors or otherwise WD areas (second from left and inset), as most MD and PD tumors failed to react strongly. Vimentin immunoreactivity was almost exclusively limited to a subset of malignant tumors, and in the majority of the cases this staining was focal (third from left and inset). Finally, staining for desmoplakin was strongly positive in normal tissues as well as in almost all tumor samples (right and inset).

A semiquantitative analysis was applied to the TMA staining. As indicated in Fig. 2B (bottom), cytokeratin 4 and cytokeratin 16 scored positive in normal tissues based on the staining pattern of the suprabasal layer, and their expression in tumors was often restricted to WD areas. For the evaluation of vimentin (third from left) and desmoplakin (right), we classified cell staining in each tissue core as positive and negative because no clear correlation with tumor differentiation was noted from the initial analysis. Of note, vimentin and desmoplakin were assessed to be negative and strongly positive, respectively, in all the relevant normal oral epithelial tissues analyzed.


   Discussion
Top
 Abstract
 Materials and Methods
 Results
 Discussion
References
 
In this study, we describe the utility of a novel proteomics platform for the global detection of expressed proteins in FFPE tissues and its use for biomarker discovery and identification of proteins that may contribute to HNSCC development and progression. This approach enabled identification of a large number of molecules, including cytokeratins and intermediate filament proteins, differentiation markers, proteins involved in stem cell maintenance, signal transduction and cell cycle regulation, growth and angiogenic factors, matrix-degrading proteases, and proteins with tumor suppressive and oncogenic potential. Of interest, detection and relative expression of many of these molecules followed a distinct pattern in normal squamous epithelia and WD, MD, and PD HNSCC tumor tissues. The ability to correlate protein expression profiles with histopathologic classification of disease may allow the development of novel biomarkers of diagnostic and prognostic value and may help identify novel targets for therapeutic intervention in HNSCC.

Certain advantages embedded within the workflow developed for this study include the efficient solubilization and digestion of proteins from FFPE archival tissue without fractionation, such that they are amenable for identification using tandem MS for a complete proteomic representation (7). Furthermore, optimization of combining laser capture microdissection with shotgun proteomic technologies enabled the detection of proteins expressed primarily within the tumor cells rather than in the stroma and other complex cellular components of the tumor microenvironment. Although the exactness of MS identifications can be challenging, particularly for low abundant proteins, current MS instrumentation and improved bioinformatic capabilities provide a high probability of protein identification (22). Thus, rather than reporting proteins identified by two or more unique peptide sequence matches, a common practice in the field that may sacrifice many correct protein identifications derived from high-quality single hits, we chose to report here all proteins identified based on stringent biophysical and statistical criteria. Indeed, the ability to take advantage of new technological developments may now enable the discovery of molecules that although present in low abundance may nevertheless play important biological roles in tumor development.

In this regard, it was encouraging that certain proteins indicative of "proof of principle" could be readily detected. For example, the total peptide number for glyceraldehyde-3-phosphate dehydrogenase, a protein frequently used for normalization, was nearly equally distributed across the different samples, suggesting that the protein recovery was similar for each group of tissues. Further validation of our analysis was illustrated by the identification of members of the taste receptors (T2R13, T2R38), olfactory receptors (5M11, 13C4, JCG2), and oral facial proteins (oral-facial-digital syndrome 1 protein), each with a single peptide. Although these proteins may not be involved in cancer, they are nevertheless known to be expressed in oral squamous tissues (23–25). The abundance of the cytokeratins (1, 4, 5, 7, 14, 16–18) and the desmosomal proteins (desmoplakin, desmoglein 3, desmocollin, epiplakin, plakophilins) was striking, particularly when considering the limited amount of sample available for the proteomic analysis. Noteworthy, desmoglein 1 and desmoglein 3 are both expressed in the skin, but the 130 kDa molecule desmoglein 3 is preferentially expressed in oral epithelium (26). As these molecules function together to maintain structural integrity of the normal oral epithelium, changes in their relative levels might represent putative biomarkers of disease progression (26).

From these long lists of proteins identified in normal and cancer cells, can we find those that may contribute to cancer development? The answer is likely yes, when considering the nature of many of the proteins identified that are predicted to be involved in cell cycle regulation, signal transduction, and proteolysis. For example, checkpoint kinase 1, a serine/threonine protein kinase that is a key mediator in the DNA damage–induced checkpoint network (27), was highly detected in normal epithelia but poorly detected in HNSCC tumors. Similarly, Apc, the protein product of the adenomatous polyposis coli (apc) gene that prevents aberrant activity of the Wnt/β-catenin signaling system and is the most frequently mutated molecule in colon cancer (28), was detected as a single peptide only in normal oral epithelium. Low-density lipoprotein receptor–related protein 12, also known as suppressor of tumorigenicity protein 7, a tumor suppressive protein whose gene is located on human chromosome 8 q22.2-23.1, a locus of high polymorphism and genetic alterations in cancer biopsies including HNSCC (29), was only found in normal oral epithelium. Similarly, a single peptide for cyclin K, a protein that acts as a regulatory subunit of CDK9 thereby regulating the transcription of a subset of genes (30), was detected only in normal tissues. As cyclin K is regulated by p53, its loss in tumor tissues may reflect the decreased p53 activity that characterizes HNSCC (3). Aligned with this possibility, individual peptides for a tumor suppressor gene on 17p13.3, hypermethylated in cancer 1, HIC-1, and a direct target for p53 that is involved in the inhibition of cell growth and the initiation of cell death and senescence programs in response to DNA damage (31), were identified in normal epithelial cells but only in one case of PD tumor sample. Thus, a DNA damage sensing molecule, checkpoint kinase 1, at least two p53 targets, cyclin K and HIC-1, as well as lipoprotein receptor–related protein 12 and Apc, the latter a well-known tumor suppressor protein poorly investigated in HNSCC, seem to be more prominent in normal epithelial than in tumor cells. Collectively, these results suggest the existence of a network of tumor-restricting mechanisms that protect the integrity of the normal squamous epithelium whose loss or decreased expression and function may contribute to HNSCC progression.

On the other hand, several proteins involved in cell cycle progression, particularly G2-M transition and mitosis, such as septin 9 and centromeric protein E, were only detected in tumor samples, reflecting their active state of proliferation. An unusual cell cycle regulating protein, prohibitin, which has been recently observed to play an unexpected function in the activation of Raf/MEK/ERK pathway by Ras and in modulating epithelial cell adhesion and migration (32), was only detected in tumors. Another surprising finding was the detection of two peptides derived from EVI-5 oncogene. This protein was first identified in experimental T-cell lymphomas by retroviral insertion strategies and has been recently shown to act together with Polo-like kinase to ensure mitotic fidelity (33). Thus, both prohibitin and EVI-5 may represent excellent candidates to play a role in aberrant cell growth in HNSCC.

Several molecules with a role in the transduction of proliferative signals were also identified in normal and tumor HNSCC cells. For example, epidermal growth factor receptor was detected in tumor samples but not in normal oral epithelial tissues, reflecting the overexpression of this growth factor tyrosine kinase receptor in HNSCC (34). We also found expression of one epidermal growth factor receptor ligand, neuregulin-2, in HNSCC, suggesting an increased complexity of the epidermal growth factor receptor network in squamous carcinogenesis. Similarly, numerous signaling molecules involved in cell migration were detected in HNSCC cells. They include several members of the Rho family of small GTPases, and few peptides derived from two novel guanine nucleotide exchange factors for Rho GTPases, RhoGEF 10 and RhoGEF 19, in tumor cells, all suggestive of an important role for Rho GTPases and their regulatory proteins and downstream targets in HNSCC progression. Two cell surface receptors, integrin β4 and plexin B1, which are involved in cell motility were also readily detected in tumor cells. In this regard, whereas integrin β4 contributes to keratinocyte cell migration and facilitates tumor angiogenesis (35), plexin B1, which was initially identified based on its role in axons guidance, is now known to play an important role in endothelial cell migration and tumor angiogenesis (36). We have also shown that HNSCC express high levels of the plexin B1 ligand, semaphorin 4D (37), suggesting the existence of an autocrine plexin B1–semaphorin 4D loop that may promote HNSCC cell migration. These proteins may also promote aberrant HNSCC growth, as suggested by recent studies indicating that integrin β4 and plexin B1 can stimulate members of the epidermal growth factor receptor and Met family of growth factor receptors (38–40).

Proteases and their inhibitors form a complex proteolytic system and are ultimately responsible for cancer cell invasion and metastasis. In this study, the abundance of members of the ADAMTS proteases family was particularly notable. These proteases likely contribute to extracellular matrix degradation, cell-to-cell adhesion, cell proliferation, and migration, and the processing of cytokines and growth factors, all aiding tumor progression and angiogenesis. Cathepsin D, which is a lysosomal aspartic protease, was also detected in the samples. Although cathepsins are involved in bulk protein turnover, they also have specialized roles in processes such as growth factor turnover and antigen presentation (41, 42). Cathepsin D was the most detectable protease in HNSCC samples, particularly in MD tumor cells. This cathepsin is often observed to be largely overexpressed in breast cancer tissues and their derived cell lines and its expression levels correlate with the incidence of clinical metastasis and shorter survival times (43). Furthermore, cathepsin D overexpression increases the growth and metastatic potential of different cancer cells in vivo (43). Thus, emerging evidence and our present findings suggest that this protease may play an unsuspected role in HNSCC progression.

Taken together, the ability to combine laser capture microdissection and in-depth proteomic analysis of formalin-fixed, paraffin-embedded tissues provides a wealth of information regarding the nature of the proteins expressed in normal squamous epithelium and tumor progression. These proteins include a number of tumor suppressor molecules and microRNA processing proteins likely involved in protecting the integrity of the cellular genome in normal epithelial cells and their resident progenitor stem cells, as well as many molecules involved in aberrant cell proliferation, survival, angiogenesis, proteolysis, and migration, whose contribution to tumor growth, resistance to treatment, and the metastatic spread of HNSCC can now begin to be explored. The emerging information has also enabled identification of a large number of proteins that are differentially expressed in normal oral squamous epithelia and tumors exhibiting distinct differentiation characteristics, thus representing suitable makers to study tumor progression. The future evaluation of the tumor makers described in this study may afford an opportunity to explore their diagnostic and prognostic value, in particular for the early detection of HNSCC. On the other hand, we expect that our study, documenting the successful use of proteomic techniques and bioinformatic tools to analyze molecules expressed in archival tumor and normal tissues, may now provide a proof of principle that will boost ongoing systems to increase the scale of data-generating proteomic efforts, which may ultimately lead to discovery of novel clinically relevant biomarkers and therapeutic targets for HNSCC and other human malignancies.


   Acknowledgments
 
We thank Thomas H. Bugge, Ana Raimondi, Panomwat Amornphimoltham, Chidchanok Leethanakul, Robert T. Dorsam, Thomas Guiel, and Marlene Darfler for their technical help, advice, and guidance.


   Footnotes
 
Grant support: Intramural Program, National Institute of Dental and Craniofacial Research and National Cancer Institute, NIH, under contract NO1-CO-12400.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/).

The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organization imply endorsement by the U.S. Government.

Current address for B.L. Hood and T.P. Conrads: Clinical Proteomics Facility, University of Pittsburgh Cancer Institute, Pittsburgh, Pennsylvania.

6 http://www.nidcr.nih.gov/Research/ResearchResources/HeadandNeckTissueArrayInitiative.htm Back

7 http://www.ebi.ac.uk/integr8 Back

8 http://david.abcc.ncifcrf.gov Back

Received 6/ 8/07; revised 10/19/07; accepted 12/ 5/07.


   References
Top
 Abstract
 Materials and Methods
 Results
 Discussion
 References
 

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