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Research ArticleExperimental Studies

Detection of Micrometastases of Squamous Cell Carcinoma Tumor Cells in Muscle Tissue

SILKE STEINBACH, ESTHER L. YUH, MYKHAYLO BURBELKO and WALTER HUNDT
Anticancer Research December 2013, 33 (12) 5213-5221;
SILKE STEINBACH
1Department of Otolaryngology Head and Neck Surgery, Philipps University Marburg, Germany
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ESTHER L. YUH
2Lucas MRS Research Center, Department of Radiology, Stanford University School of Medicine, Stanford, CA, U.S.A.
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MYKHAYLO BURBELKO
3Department of Radiology, Philipps University Marburg, Germany
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WALTER HUNDT
3Department of Radiology, Philipps University Marburg, Germany
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  • For correspondence: hundt@med.uni-marburg.de
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Abstract

The aim of this study was to evaluate microarray technology in the detection of micrometastases of head and neck squamous cell carcinoma (HNSCC) in muscle tissue. Three hundred SCCVII tumor cells were injected intramuscularly into the right flank of ten C3H/Km mice. One week later, the animals were euthanized and the muscle tissue was taken out. Histology (H&E staining), microarray and reverse transcriptase polymerase chain reaction analysis (RT-PCR) of the tissue was performed. Histology showed a few tumor cells between the muscle fibers. Microarray technology showed the different gene expression pattern of the muscle tissue with micrometastases in comparison to normal muscle tissue. Only genes with a fold change difference of 10 or greater were considered. Gene expression analysis revealed changes in the expression levels of 91 genes of micrometastases in muscle tissue. RT-PCR confirmed gene up-regulation. Significant differences in gene expression between micrometastases in muscle tissue and pure muscle tissue were found. The genes found to be up-regulated could be used to detect micrometastases in muscle tissue.

  • Tumor tissue
  • muscle tissue
  • histology
  • gene expression

Head and neck malignancies account for 6% of all cancers diagnosed in the United States and result in an estimated 14,000 deaths annually (1). Although improvements in local control and survival have been achieved with the use of combined-modality therapies, 5-year survival rates for patients with head and neck cancer have not improved significantly over the past 20 years (2, 3). Local relapse is in most cases due to micrometastases, either in lymph nodes or the surrounding muscle tissue. The limitations of routine pathology for detecting micrometastatic disease (4, 5) have made it necessary to explore molecular means of diagnosis that can detect disease through tissue sampling. Molecular detection of head and neck squamous cell carcinoma (HNSCC) cells in a background of surrounding muscle tissue demands highly specific and sensitive biomarkers. Ideally, these biomarkers would be abundantly, yet exclusively, expressed in squamous epithelium, whereas having negligible expression in muscle tissue. One method for the molecular detection of these biomarkers that has shown promise in recent studies is microarray technology. It allows qualitative and quantitative analysis of biomarkers to be performed with great sensitivity and from minute amounts of starting material. Because this technology is sensitive, it offers the potential to improve clinical decision making (6-9). SCCVII is a syngeneic squamous cell carcinoma cell line of C3H mice and has been used as a model for human head and neck cancer (10). In this study, we applied gene expression microarray technology to muscle tissue after injection of squamous cell carcinoma cells in order to test if this method is a sensitive method of proving or excluding the presence of micrometastases in muscle tissue.

Materials and Methods

All animal experiments were performed in compliance with institutional animal care committee guidelines and with the approval of the Animal Care Committee.

Tumor cell implantation into muscle tissue. Ten C3H/Km (Stanford animal facility, CA, USA) male mice aged 12 weeks were anesthetized with intraperitoneal Nembutal (pentobarbital, Abbott Laboratories, CA, USA) (58 mg/kg) and their right flank was shaved and prepared with isopropyl alcohol. An average of 300 tumor cells (mouse SCC VII) in Hanks‘ solution were injected intramuscularly into the right flank of each mouse. The total volume of injection was 100 μl. One week later, the animals were euthanized and the muscle tissue taken out. As control, muscle tissue of the contralateral side of five animals was used and muscle tissue after injection of 100 μl saline. In addition, in five animals tumor was grown subcutaneously until a size of 500 mm3.

Histology. In order to reveal micrometastases in muscle tissue, hematoxylin and eosin (H&E) staining was performed. For the H&E staining, tissue samples were preserved in 10% formalin solution for 96 h. Afterwards, they were embedded in paraffin, sectioned, stained with H&E, and then mounted on glass slides.

Microarray analysis. For microarray analysis, samples of the muscle tissue with micrometastases, muscle tissue after injection of 100 μl saline, muscle tissue alone and tumor tissue alone was used. The tissue samples for microarray analysis were deep-frozen at a temperature of −80°C. In total, 10 muscle tissue samples with micrometastases, five muscle tissue samples and five tumor tissue samples were analyzed. The total RNA was isolated using TRIzol Reagent® (GibcoBRL Life Technologies, Rockville, MD, USA) and double-stranded cDNA was created using the SuperScript Choice system (Life Technologies, Rockville, MD, USA). In further steps, the cDNA was extracted and precipitated. Biotinylated cRNA was synthesized using Enzo Bio Array High Yield RNA Transcript Labelling Kit (Enzo Diagnostics Inc., Farmingdale, NY, USA). After incubation the labeled cRNA was cleaned-up according to the RNeasy Mini kit protocol (Qiagen, Valencia, CA, USA). The cRNA was fragmented and hybridized on the murine Genome U74Av2 set array. The chips were washed and stained with streptavidin phycoerythrin (SAPE; Molecular Probes, Eugene, OR, USA). To amplify staining, streptavidin phycoerythrin solution was added twice with an anti-streptavidin biotinylated antibody (Vector Laboratories, Burlingame, CA, USA) staining step in between. The probe array was scanned on a Hewlett-Packard confocal microscope scanner (Hewlett Packard Gene Array Scanner; Hewlett Packard Corporation, Palo Alto, CA, USA) at the excitation wavelength of 488 nm. The amount of light emitted at 570 nm was proportional to the target bound at each location on the probe array. All samples were prepared as described and hybridized onto the Affymetrix Murine Genome U74Av2 Set array (Affymetrix, Santa Clara, CA, USA).

Quantitative reverse transcriptase-polymerase chain reaction analysis (qRT-PCR). To validate the results of the microarray experiment quantitative real-time polymerase chain reaction assays on genes of interest was performed. qRT-PCR was performed according to standard procedures using the muscle tissue samples containing micrometastases. RNA was extracted from the tissue with the following steps: Tissue was homogenized in 5 ml of lysis buffer (6 mol/l urea, 3 mol/L lithium chloride, 50 mmol/l sodium acetate, 200 μg/ml heparin, and 0.1% sodium dodecyl sulphate). The homogenized tissue was centrifuged at 16000 g for 20 minutes, extracted twice with an equal volume of phenol and chloroform, and precipitated with ethanol. The RNA pellet was air dried and dissolved in water treated with diethylpyrocarbonate. RT-PCR was then performed (DNA Thermal Cycler 480; Perkin-Elmer, Oak Brook, IL, USA). For qRT-PCR the following genes were used in this study found to be highly up-regulated in the microarray experiment: Complement component 1, q subcomponent, c polypeptide, S100 calcium-binding protein A4, Cytokeratin (endoB) gene, Epithelial membrane protein 3, Epithelial membrane protein 1, Colony-stimulating factor 1 receptor, Apolipoprotein E, Stromal cell-derived factor, CD14 antigen. The primer for the different genes were as followed: for Complement component 1, q subcomponent, c polypeptide forward, 5’-GCTTGTAGTACACCAGCGTGTT-3’, and reverse, 5’-AAGGTGCCCGGTCTCTACTA-3’, for S100 calcium-binding protein A4 forward, 5’-GCTTGTAGTACACCAG CGTGTT-3’, and reverse, 5’-AAGGTGCCCGGTCTCTACTA-3’, for Cytokeratin (endoB) forward 5’-CTTGTGGAGTGGGTGGCTAT -3’, and reverse, 5’-CCACTTGGTGTCCAGAACCT-3’, for Epithelial membrane protein 3 forward 5’-CTTGTGGAGTGGGTGGCTAT -3’, and reverse, 5’-CCACTTGGTGTCCAGAACCT - 3’, for Epithelial membrane protein 1 forward 5’-ATTGCCAATGTCTGGTTGGTTT-3’, and reverse, 5’-AGAACGCCGATGATGAAGCT-3’, for Colony-stimulating factor 1 receptor forward 5’-AGATATTCGAGCAGGGTCTAC-3’, and reverse, 5’-GGGATATCAGTCAGAAAGGTT -3’, for Apolipoprotein E forward 5’-GTT GCTGGTCACATTCCTGG-3-3’, and reverse, 5’-GCAG GTAATCCCAAAAGCGAC -3’, for Stromal cell-derived factor forward 5’-AGGCTACCTGGATCAGGCTTC-3’, and reverse, 5’-ACATTCTTTTCAGCCTACCTCC-3’, for CD14 antigen forward 5’- AGAGGCAGCCGAAGAGTTCAC-3’, and reverse, 5’-GCGCTC CATGGTCGATAAGT -3’. GAPDH was used as an internal control for normalization. GAPDH-forward: 5’-TGCACCACCAACTGCT TAGC-3’; GAPDH-reverse: 5’-GGCATGGACTGTGGTCATGAG-3’. The cycling conditions used for the amplification were as follows: 5 min at 94°C followed by 40 cycles of 20 sec at 94°C, 20 sec at 59°C, and 30 sec at 72°C with a final extension at 72°C for 10 min. The products were checked in 2% agarose gel, along with a 100-base pair ladder (Promega, Madison, WI, USA). PCR amplification and quantitation was performed using ABI SYBR Green Master Mix (Applied Biosystems, Foster City, CA) and Stratagene MX3000P™ (Cedar Creek, Texas). The expression values of investigated genes compared with that of GAPDH were calculated using the 2−ΔΔCt method. The mean value and standard deviation of each analyzed tissue sample group was calculated. All reactions were conducted in triplicate.

Analysis of microarray data. Pre-processing of the Affymetrix arrays was carried out using GeneData Refiner 3.06 software (Genedata, Lexington, MA, USA). Each tissue sample was analyzed once, producing one result of fold change by comparing the samples with micrometastases with those of muscle tissue alone, and with tumor tissue samples. The mean value and standard deviation of each analyzed tissue sample group was calculated. Expression intensity values for each gene were derived using Refiner (Genedata, Lexington, MA, USA) by applying the Microarray Suite 5.0 algorithm (Affymetrix, Santa Clara, CA, USA).

Statistical analysis. Genes differentially expressed between the muscle tissue containing micrometastases compared to normal muscle tissue and tumor tissue were identified using a Satterthwaite t-test to robustly estimate significance despite unequal variance among groups (p<0.001). Only genes having a mean fold difference in expression of 10.0 or more were considered.

Results

Histology. In the muscle tissue after injection of tumor cells, no tumor cell nests were found however, a few tumor cells (Figure 1A, arrow) between the muscle fibers were detected, otherwise histology showed normal muscular tissue structure (H&E; Figure 1B).

Microarray analysis. Gene expression analysis revealed up-regulation of the expression of 91 genes in micrometastases in muscle tissue compared to pure muscle tissue and in 21 genes compared to pure tumor tissue.

The genes up-regulated in micrometastases from muscle tissue compared to pure muscle tissue are related to different functional groups. They belong to genes involved in immune response, protein binding, receptor activity, membrane function, cell matrix, cell growth, cell core, calcium binding, enzyme activity, lipid metabolism and nucleotide activity.

In the immune response group, the most up-regulated gene was complement component 1, q subcomponent, c polypeptide and complement component 1, q subcomponent, alpha polypeptide, with a fold increase of 108±14 and 103±14, respectively. In the protein binding group, the most specific up-regulated genes were the S100 calcium binding protein A4, calpactin I light chain and the S100 calcium-binding protein A6, with a fold increase of 108±7.6, 24±2.2 and 23±2.9, respectively. Different receptors were up-regulated by 11±4 to 17±2 fold, for example the mRNA for 4F2/CD98 light chain receptor, peptidylprolyl isomerase C-associated protein and the mannose receptor, C type 1. Two genes with important membrane function were up-regulated, the retinoic acid-inducible E3 protein and the proteolipid protein 2. The most up-regulated cell matrix gene was that for the cytokeratin (endoB), with a fold increase of 68±12. Genes affected which are related to cell growth were epithelial membrane protein 3, thymic shared antigen-1 (Tsa-1) gene and epithelial membrane protein 1 with a fold increases of 29±2.7, 29±2.5 and 16±1.5, respectively. In the group of genes for cell core and nucleotide activity, the Nsp-like 1 protein (Nspl1) (28±6.9-fold), mouse beta-tubulin (isotype Mß 5) (21±2.2- fold) and dynamin (18±1.7- fold) were up-regulated. An important function in calcium binding is held by endothelial monocyte-activating polypeptide I (29±3.9 fold increase). Up-regulated genes with a high enzyme activity were cathepsin S, mouse lysozyme M gene, Tyro protein tyrosine kinase binding protein, colony-stimulating factor 1 receptor and (cpp32) apoptotic protease mRNA with a fold increase of between 26±2.5 and 54±6.1. Genes involved in lipid metabolism were those for apolipoprotein E, phospholipid transfer protein and annexin III (Tables I, II and III). Genes up-regulated in micrometastases in muscle tissue compared to tumor tissue are those genes which are specifically up-regulated in muscle tissue. They belong to groups related to calcium metabolism, muscle contraction and development, energy supply, general metabolism, receptor activity and molecule transport and tissue regulation. These genes are specifically related to muscle tissue and muscle tissue metabolism (Table IV). Comparing the gene expression profile of the muscle tissue after injection of 100 μl saline and the contralateral muscle tissue, no significant gene expression differences were observed.

qRT-PCR. To validate gene expression profiling by microarray we performed qRT-PCR for genes highly up-regulated in micrometastases in muscle tissue. In micrometastases in muscle tissue we chose the complement component 1, q subcomponent, c polypeptide; S100 calcium-binding protein A4; cytokeratin (endoB); epithelial membrane protein 1 and 3; colony-stimulating factor 1 receptor; apolipoprotein E; stromal cell-derived factor; and CD14 antigen. Although the degree of up-regulation detected by the two methods varied, direct comparison of values of differentially expressed genes showed an overall pattern concordant between RT-PCR and Affymetrix cDNA array experiments the same trend for induction was detected by both methods for each target gene. No mismatches between the RT-PCR and the Affymetrix results were found. The overall gene expression changes obtained by RT-PCR were greater with smaller standard deviations (Table V).

Discussion

The sensitivity of pathological analysis by H&E staining for the detection of small tumor deposits in muscle tissue has been improved by the addition of immunohistochemical staining, which has been demonstrated to up-stage disease in many patients who were classified as having no clinically measurable metastatic disease (11), however there is always the possibility of missing very small micrometastases. Early studies focused on the detection of clonal genetic changes that were specific for HNSCC cells, such as mutations in p53 (12). In recent years, researchers have shifted focus from tumor-specific towards tissue specific markers, as they seek to take advantage of the differential gene expression between HNSCC cells and other tissues (13, 14). DNA microarray analysis of human tumor specimens to identify metastasis-related genes has been reported for several types of cancer (15-17). Roepman et al. identified 102 genes in primary tumors as an expression profile for the prediction of lymph node metastasis from primary HNSCC (18). Chung et al. also used DNA microarray to classify HNSCC and predict lymph node metastasis (19). Due to heterogeneity, HNSCC cells may utilize different gene products to achieve similar functions. Therefore, it is difficult to validate expression of a large number of genes at the protein level in tissue specimens, and to validate their biological relationship and functional pathways in metastasis. DNA microarray data mining analysis has provided important information for understanding the biological behaviors of metastatic HNSCC cells.

The gene expression pattern of micrometastases in muscle tissue in our experiment was completely different to that of pure muscle tissue and muscle tissue after injection of saline. The gene expression patterns of pure muscle tissue and muscle tissue after injection of saline did not differ significantly. This is an indication that the damage of muscle tissue due to the injection needle did not cause significant gene expression changes. In our experiment, we chose a fold difference of 10 or more in order to select only highly up-regulated genes in order to derive a very high specificity for the up-regulated genes. In other studies, gene expression was considered as significantly altered, if there was a fold difference of two or more (20, 21).

Figure 1.
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Figure 1.

A: Hematoxylin and eosin staining of muscle tissue after injection of tumor cells. The arrows indicate a few tumor cells between the muscle fibers. B: Hematoxylin and eosin staining of normal muscle tissue.

The up-regulated genes in micrometastases in muscle tissue found in our experiment belong to different physiological functional groups from those up-regulated in pure tumor tissue. The genes are important for immune response, protein binding, receptor activity, membrane function, cell matrix, cell growth, cell core, calcium binding, enzyme activity, lipid metabolism and nucleotide activity. In our experiment qRT-PCR was performed for nine of the highly up-regulated genes from the different physiological functional groups, and the results were consistent with the results of oligonucleotide microarray analysis. In the group of immune response genes the most up-regulated genes were complement component 1, q subcomponent, c polypeptide and complement component 1, q subcomponent, alpha polypeptide. C1q is the target recognition protein of the classical complement pathway that is crucial for the clearance of pathogens and apoptotic cells (22). It is involved in a number of immunological processes, such as phagocytosis of bacteria, neutralization of retroviruses, cell adhesion, modulation of dendritic cells, B-cells and fibroblasts, and maintenance of immune tolerance by clearance of apoptotic cells (23). In the group of genes for binding protein the most specific up-regulated gene was the S100 calcium-binding protein A4. S100A was shown to promote metastasis in several experimental animal models, and S100A4 and A6 protein expression is associated with patient outcome for a number of tumor types. These proteins have a wide range of biological functions, such as regulation of angiogenesis, cell survival, motility, and invasion (24). Different receptors were up-regulated, for example the mRNA for 4F2/CD98 light chain receptor. The precise function of the 4F2 molecule remains unknown. However, a role for 4F2 in the regulation of cell growth and activation has been suggested by the finding that 4F2 is expressed at low levels in most quiescent cells in vivo, but it is expressed at high levels on all dividing human tissue culture cells and most, if not all, malignant human cells (25). Two genes having an important membrane function were up-regulated the retinoic acid-inducible E3 protein mRNA and the proteolipid protein 2. Retinoic acid-inducible gene-I (Rig-I) is an intracellular pattern recognition receptor that plays important roles during innate immune responses. The mechanisms and signaling molecules that participate in the downstream events that follow activation of Rig-I are incompletely characterized. In addition, the factors that define the intracellular availability of Rig-I and determine the steady-state levels of this protein are only partially understood but are likely to play a major role during innate immune responses (26). Proteolipid protein 2 is a protein up-regulated in tumors, especially in oligodendrogliomas, and important for the development of tumors (27). The most up-regulated cell matrix gene was cytokeratin (endoB). Cytokeratin is a cytoskeletal intermediate filament protein. At present, there are 20 subtypes expressed in various types of human epithelial cells. The cytokeratin isotype depends on the cell type and the localization of cytokeratin in the cytoplasm (28). The most up-regulated gene related to cell growth was epithelial membrane protein 3. Epithelial membrane proteins are expressed in many tissues, and functions in cell growth, differentiation, and apoptosis have been reported. Epithelial membrane protein 1 and 3 are highly up-regulated during squamous differentiation and in certain tumors, and a role in tumorigenesis has been proposed. They are also highly up-regulated during squamous cell differentiation and in certain tumor types, and a role in tumorigenesis has been proposed (29). Of genes related to cell core and nucleotide activity, the most up-regulated gene was Nspl1. Nspl1 contributes to integrin and receptor tyrosine kinase signaling (30). An important function in calcium binding is played by endothelial monocyte-activating polypeptide I, which has a pro-coagulant activity (31). The most up-regulated gene with a high enzyme activity was that for cathepsin S. Cathepsins have been found to participate in apoptosis, and also play a role in the promotion of tumors during cancer progression. In addition, it has been suggested that the expression of lysosomal cathepsins are substantially increased in malignant tumors (32).

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Table I.

Comparison of the gene expression profile of micrometastases in muscle tissue compared to muscle tissue. Tumor specific genes related to immune response, protein binding and receptor activity found to be significantly up-regulated in micrometastases. Data are expressed as mean of the fold change (FC) and standard deviation (SD).

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Table II.

Comparison of the gene expression profile of micrometastases in muscle tissue compared to muscle tissue. Tumor-specific genes related to the cell membrane, cell matrix, cell growth and cell core and nucleotide activity found to be significantly up-regulated in micrometastases.

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Table III.

Comparison of the gene expression profile of micrometastasis containing muscle tissue compared to pure muscle tissue. Tumor specific genes related to calcium binding, enzym activity and lipid metabolism found to be significantly up-regulated in micrometastases.

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Table IV.

Comparison of the gene expression profile of micrometastases containing muscle tissue compared to pure tumor tissue. Specific genes are related to muscle tissue could be found to be significantly up-regulated in micrometastases.

A highly up-regulated gene active in the lipid metabolism was apolipoprotein E. This and its gene product are involved in cholesterol transport, lipid metabolism and protein synthesis, by mediating the binding of the low-density lipoprotein (LDL) receptor, and the apolipoprotein E receptor of lipids to specific lipoprotein receptors. It is also involved in numerous other functions, including tissue repair, immune response and regulation, as well as cell growth and differentiation (33). The differentially expressed genes here play crucial roles in the development, differentiation, and functioning of tumor tissues, and because they display remarkable tissue specificity (34, 35), the different patterns of gene expression are ideal for use as tissue classifiers. For example, the epithelial membrane protein 1 and 3 are highly up-regulated in squamous cell differentiation. This helps differentiate squamous cell tumor from other tumor types. The different gene expression patterns found in our study hold potential for assisting in the determination of the primary tumor site for metastases of unknown origin. Our demonstration of this highly discriminatory assay for the detection of small tumor deposits not detected by histology will hopefully supply the pilot data needed to incorporate this technique into a clinically-relevant application to improve staging of patients with metastatic HNSCC. The further clinical relevance of this study might be that it is helpful to apply microarray technology to surgical margins for molecular analysis. Several samples of the surrounding muscle tissue should be taken in order to assess more sensitively the possibility of micrometastasis to deeper tissue layers, however with the risk of missing nests of micrometastasis.

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Table V.

RT-PCR confirmed the up-regulation of selected genes when comparing micrometastases in muscle tissue to muscle tissue and micrometastases containing muscle tissue to tumor tissue.

Conclusion

Our animal model of metastatic HNSCC plus DNA microarray analysis provided valuable information on the unique biological behaviors of SCCVII cells. We identified the epithelial membrane protein 1 and 3 in the tumor cells, confirmed by qRT-PCR, and put forward putative molecular bases leading to these behaviors.

Acknowledgements

The Authors gratefully acknowledge Pauline Chu for technical assistance in histology

Footnotes

  • Author Contributions

    Silke Steinbach, conception and design, acquisition of data, analysis and interpretation of data, drafting the article, final approval of the version to be published; Esther L. Yuh, conception and design, acquisition of data, analysis and interpretation of data, drafting the article, final approval of the version to be published; Mykhaylo Burbelko, analysis and interpretation of data, drafting the article, final approval of the version to be published; Walter Hundt, conception and design, acquisition of data, analysis and interpretation of data, drafting the article, final approval of the version to be published.

  • This article is freely accessible online.

  • Sponsorships

    This study was supported in part by the Lucas Foundation.

  • Disclosures

    Competing interests: None.

  • Received September 29, 2013.
  • Revision received November 3, 2013.
  • Accepted November 4, 2013.
  • Copyright© 2013 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved

References

  1. ↵
    1. Edwards BK,
    2. Howe HL,
    3. Ries LA,
    4. Thun MJ,
    5. Rosenberg HM,
    6. Yancik R,
    7. Wingo PA,
    8. Jemal A,
    9. Feigal EG
    : Annual report to the nation on the status of cancer, 1973-1999, featuring implications of age and aging on U. S. cancer burden. Cancer 94: 2766-2792, 2002.
    OpenUrlCrossRefPubMed
  2. ↵
    1. Weir HK,
    2. Thun MJ,
    3. Hankey BF,
    4. Ries LA,
    5. Howe HL,
    6. Wingo PA,
    7. Jemal A,
    8. Ward E,
    9. Anderson RN,
    10. Edwards BK
    : Annual report to the nation on the status of cancer, 1975-2000, featuring the uses of surveillance data for cancer prevention and control. J Natl Cancer Inst 95(17): 1276-1299, 2003.
    OpenUrlAbstract/FREE Full Text
  3. ↵
    1. Swango PA
    : Cancers of the oral cavity and pharynx in the United States: An epidemiologic overview. J Public Health Dent 56(6): 309-318, 1996.
    OpenUrlCrossRefPubMed
  4. ↵
    1. Rhee D,
    2. Wenig BM,
    3. Smith RV
    : The significance of immunohistochemically demonstrated nodal micrometastases in patients with squamous cell carcinoma of the head and neck. Laryngoscope 112(11): 1970-1974, 2002.
    OpenUrlCrossRefPubMed
  5. ↵
    1. Thomsen JB,
    2. Christensen RK,
    3. Sorensen JA,
    4. Krogdahl A
    : Sentinel lymph nodes in cancer of the oral cavity: Is central step-sectioning enough? J Oral Pathol Med 36(7): 425-429, 2007.
    OpenUrlPubMed
  6. ↵
    1. Leethanakul C,
    2. Knezevic V,
    3. Patel V,
    4. Amornphimoltham P,
    5. Gillespie J,
    6. Shillitoe EJ,
    7. Emko P,
    8. Park MH,
    9. Emmert-Buck MR,
    10. Strausberg RL,
    11. Krizman DB,
    12. Gutkind JS
    : Gene discovery in oral squamous cell carcinoma through the head and neck cancer genome anatomy project: confirmation by microarray analysis. Oral Oncol 39(3): 248-258, 2003.
    OpenUrlCrossRefPubMed
    1. El-Naggar AK,
    2. Kim HW,
    3. Clayman GL,
    4. Coombes MM,
    5. Le B,
    6. Lai S,
    7. Zhan F,
    8. Luna MA,
    9. Hong WK,
    10. Lee JJ
    : Differential expression profiling of head and neck squamous carcinoma: significance in their phenotypic and biological classification. Oncogene 21(53): 8206-8219, 2002.
    OpenUrlCrossRefPubMed
    1. Alevizos I,
    2. Mahadevappa M,
    3. Zhang X,
    4. Ohyama H,
    5. Kohno Y,
    6. Posner M,
    7. Gallagher GT,
    8. Varvares M,
    9. Cohen D,
    10. Kim D,
    11. Kent R,
    12. Donoff RB,
    13. Todd R,
    14. Yung CM,
    15. Warrington JA,
    16. Wong DT
    : Oral cancer in vivo gene expression profiling assisted by laser capture microdissection and microarray analysis. Oncogene 20(43): 6196-6204, 2001.
    OpenUrlCrossRefPubMed
  7. ↵
    1. Warner GC,
    2. Reis PP,
    3. Jurisica I,
    4. Sultan M,
    5. Arora S,
    6. Macmillan C,
    7. Makitie AA,
    8. Grénman R,
    9. Reid N,
    10. Sukhai M,
    11. Freeman J,
    12. Gullane P,
    13. Irish J,
    14. Kamel-Reid S
    : Molecular classification of oral cancer by cDNA microarrays identifies overexpressed genes correlated with nodal metastasis. Int J Cancer 110: 857-868, 2004.
    OpenUrlCrossRefPubMed
  8. ↵
    1. Ning S,
    2. Yu N,
    3. Brown DM,
    4. Kanekal S,
    5. Knox SJ
    : Radiosensitization by intramoral administration of cisplatin in a sustained-release drug delivery system. Radiotherapy and Oncology 50(2): 215-223, 1999.
    OpenUrlCrossRefPubMed
  9. ↵
    1. Marley JJ,
    2. Robinson PA,
    3. Hume WJ
    . Expression of human cytokeratin 14 in normal, premalignant and malignant oral tissue following isolation by plaque differential hybridisation. Eur J Cancer 30B(5): 305-311, 1994.
    OpenUrl
  10. ↵
    1. Brennan JA,
    2. Mao L,
    3. Hruban RH,
    4. Boyle JO,
    5. Eby YJ,
    6. Koch WM,
    7. Goodman SN,
    8. Sidransky D
    : Molecular assessment of histopathological staging in squamous cell carcinoma of the head and neck. N Engl J Med 332(7): 429-435, 1995.
    OpenUrlCrossRefPubMed
  11. ↵
    1. Ferris RL,
    2. Xi L,
    3. Raja S,
    4. Hunt JL,
    5. Wang J,
    6. Gooding WE,
    7. Kelly L,
    8. Ching J,
    9. Luketich JD,
    10. Godfrey TE
    : Molecular staging of cervical lymph nodes in squamous cell carcinoma of the head and neck. Cancer Res 65(6): 2147-2156, 2005.
    OpenUrlAbstract/FREE Full Text
  12. ↵
    1. Mitas M,
    2. Cole DJ,
    3. Hoover L,
    4. Fraig MM,
    5. Mikhitarian K,
    6. Block MI,
    7. Hoffman BJ,
    8. Hawes RH,
    9. Gillanders WE,
    10. Wallace MB
    : Real-time reverse transcription–PCR detects KS1/4 mRNA in mediastinal lymph nodes from patients with non small cell lung cancer. Clin Chem 49(2): 312-315, 2003.
    OpenUrlFREE Full Text
  13. ↵
    1. Ramaswamy S,
    2. Ross KN,
    3. Lander ES,
    4. Golub TR
    : A molecular signature of metastasis in primary solid tumors. Nat Genet 33(1): 49-54, 2003.
    OpenUrlCrossRefPubMed
    1. Jones J,
    2. Otu H,
    3. Spentzos D,
    4. Kolia S,
    5. Inan M,
    6. Beecken WD,
    7. Fellbaum C,
    8. Gu X,
    9. Joseph M,
    10. Pantuck AJ,
    11. Jonas D,
    12. Libermann TA
    : Gene signature of progression and metastasis in renal cell cancer. Clin Cancer Res 11(16): 5730-5739, 2005.
    OpenUrlAbstract/FREE Full Text
  14. ↵
    1. Xi L,
    2. Lyons-Weiler J,
    3. Coello MC,
    4. Huang X,
    5. Gooding WE,
    6. Luketich JD,
    7. Godfrey TE
    : Prediction of lymph node metastasis by analysis of gene expression profiles in primary lung adenocarcinomas. Clin Cancer Res 11(11): 4128-4235, 2005.
    OpenUrlAbstract/FREE Full Text
  15. ↵
    1. Roepman P,
    2. Wessels LF,
    3. Kettelarij N,
    4. Kemmeren P,
    5. Miles AJ,
    6. Lijnzaad P,
    7. Tilanus MG,
    8. Koole R,
    9. Hordijk GJ,
    10. van der Vliet PC,
    11. Reinders MJ,
    12. Slootweg PJ,
    13. Holstege FC
    : An expression profile for diagnosis of lymph node metastases from primary head and neck squamous cell carcinomas. Nat Genet 37(2): 182-186, 2005.
    OpenUrlCrossRefPubMed
  16. ↵
    1. Chung CH,
    2. Parker JS,
    3. Karaca G,
    4. Wu J,
    5. Funkhouser WK,
    6. Moore D,
    7. Butterfoss D,
    8. Xiang D,
    9. Zanation A,
    10. Yin X,
    11. Shockley WW,
    12. Weissler MC,
    13. Dressler LG,
    14. Shores CG,
    15. Yarbrough WG,
    16. Perou CM
    : Molecular classification of head and neck squamous cell carcinomas using patterns of gene expression. Cancer Cell 5: 489-500, 2004.
    OpenUrlCrossRefPubMed
  17. ↵
    1. Yuvaraj S,
    2. Blanchard JJ,
    3. Daughtridge G,
    4. Kolb RJ,
    5. Shanmugarajan S,
    6. Bateman TA,
    7. Reddy SV
    : Microarray profile of gene expression during osteoclast differentiation in modelled microgravity. J Cell Biochem 111(5): 1179-87, 2010.
    OpenUrlPubMed
  18. ↵
    1. Sheng J,
    2. Zhang WY
    : Identification of biomarkers for cervical cancer in peripheral blood lymphocytes using ologonucleotide microarrays. Chin Med J 123(8): 1000-1005, 2010.
    OpenUrlPubMed
  19. ↵
    1. Kishore U,
    2. Reid KBM
    : C1q: Structure, function, and receptors. Immunopharmacology 49(1-2): 159-170, 2000.
    OpenUrlCrossRefPubMed
  20. ↵
    1. Kishore U,
    2. Ghai R,
    3. Greenhough TJ,
    4. Shrive AK,
    5. Bonifati DM,
    6. Gadjeva MG,
    7. Waters P,
    8. Kojouharova MS,
    9. Chakraborty T,
    10. Agrawal A
    : Structural and functional anatomy of the globular domain of complement protein C1q. Immunol Lett 95(2): 113-128, 2004.
    OpenUrlCrossRefPubMed
  21. ↵
    1. Boye K,
    2. Mælandsmo GM
    : S100A4 and Metastasis. A Small Actor Playing Many Roles. Am J Pathol 176(2): 528-535, 2010.
    OpenUrlCrossRefPubMed
  22. ↵
    1. Haynes BF,
    2. Hemler ME,
    3. Mann DL,
    4. Eisenbarth GS,
    5. Shelhamer J,
    6. Mostowski HS,
    7. Thomas CA,
    8. Strominger JL,
    9. Fauci AS
    : Characterization of a monoclonal antibody (4F2) that binds to human monocyte and to a subset of activated lymphocytes. J Immunol 126(4): 1409-1414, 1981.
    OpenUrlPubMed
  23. ↵
    1. Matsumiya T,
    2. Imaizumi T,
    3. Stafforini DM
    : The levels of retinoic acid regulated by heat shock protein 90-alpha. J Immunol 182(5): 2717-2725, 2009.
    OpenUrlAbstract/FREE Full Text
  24. ↵
    1. Popko B,
    2. Pearl DK,
    3. Walker DM,
    4. Comas TC,
    5. Baerwald KD,
    6. Burger PC,
    7. Scheithauer BW,
    8. Yates AJ
    : Molecular markers that identify human astrocytomas and oligodendrogliomas. J Neuropathol Exp Neurol 61(4): 329-338, 2002.
    OpenUrlPubMed
  25. ↵
    1. Moll R,
    2. Franke WW,
    3. Schiller DL,
    4. Geiger B,
    5. Krepler R
    : The catalog of human cytokeratins: Patterns of expression in normal epithelia, tumors and cultured cells. Cell 31(1): 11-24, 1982.
    OpenUrlCrossRefPubMed
  26. ↵
    1. Jetten AM,
    2. Suter U
    : The peripheral myelin protein 22 and epithelial membrane protein family. Prog Nucleic Acid Res Mol Biol 64: 97-129, 2000.
    OpenUrlPubMed
  27. ↵
    1. Garron ML,
    2. Arsenieva D,
    3. Zhong J,
    4. Bloom AB,
    5. Lerner A,
    6. O'Neill GM,
    7. Arold ST
    : Structural insights into the association between BCAR3 and CAS family members, an atypical complex implicated in anti-oestrogen resistance. J Mol Biol 386(1): 190-203, 2009.
    OpenUrlCrossRefPubMed
  28. ↵
    1. van Horssen R,
    2. Eggermont AM,
    3. ten Hagen TLM
    : Endothelial monocyte-activating polypeptide-II and its functions in(patho)physiological processes. Cytokine and Growth Factor Rev 17(5): 339-348, 2006.
    OpenUrlCrossRefPubMed
  29. ↵
    1. Laurent-Matha V,
    2. Maruani-Herrmann S,
    3. Prebois C,
    4. Beaujouin M,
    5. Glondu M,
    6. Noel A,
    7. Alvarez-Gonzalez ML,
    8. Blacher S,
    9. Coopman P,
    10. Baghdiguian S,
    11. Gilles C,
    12. Loncarek J,
    13. Freiss G,
    14. Vignon F,
    15. Liaudet-Coopman E
    : Catalytically inactive human cathepsin D triggers fibroblast invasive growth. J Cell Biol 168(3): 489-499, 2005.
    OpenUrlAbstract/FREE Full Text
  30. ↵
    1. Hartman RE,
    2. Laurer H,
    3. Longhi L,
    4. Bales KR,
    5. Paul SM,
    6. McIntosh TK,
    7. Holtzman DM
    : Apolipoprotein E4 influences amyloid deposition but not cell loss after traumatic brain injury in a mouse model of Alzheimer's disease. J Neurosci 22(23): 10083-10087, 2002.
    OpenUrlAbstract/FREE Full Text
  31. ↵
    1. Sempere LF,
    2. Freemantle S,
    3. Pitha-Rowe I,
    4. Moss E,
    5. Dmitrovsky E,
    6. Ambros V
    : Expression profiling of mammalian microRNAs uncovers a subset of brain-expressed microRNAs with possible roles in murine and human neuronal differentiation. Genome Biol 5(3): R13, 2004.
    OpenUrlCrossRefPubMed
  32. ↵
    1. Lee YS,
    2. Kim HK,
    3. Chung S,
    4. Kim KS,
    5. Dutta A
    : Depletion of human micro-RNA miR-125b reveals that it is critical for the proliferation of differentiated cells but not for the down-regulation of putative targets during differentiation. J Biol Chem 280(17): 16635-16641, 2005.
    OpenUrlAbstract/FREE Full Text
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Anticancer Research: 33 (12)
Anticancer Research
Vol. 33, Issue 12
December 2013
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Detection of Micrometastases of Squamous Cell Carcinoma Tumor Cells in Muscle Tissue
SILKE STEINBACH, ESTHER L. YUH, MYKHAYLO BURBELKO, WALTER HUNDT
Anticancer Research Dec 2013, 33 (12) 5213-5221;

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Detection of Micrometastases of Squamous Cell Carcinoma Tumor Cells in Muscle Tissue
SILKE STEINBACH, ESTHER L. YUH, MYKHAYLO BURBELKO, WALTER HUNDT
Anticancer Research Dec 2013, 33 (12) 5213-5221;
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Keywords

  • tumor tissue
  • muscle tissue
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  • gene expression
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