Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
BMC Cancer
Published in: BMC Cancer 1/2008

Open Access 01-12-2008 | Research article

Gene-expression of metastasized versus non-metastasized primary head and neck squamous cell carcinomas: A pathway-based analysis

Authors: Erik F Hensen, Maria J De Herdt, Jelle J Goeman, Jan Oosting, Vincent THBM Smit, Cees J Cornelisse, Robert J Baatenburg de Jong

Published in: BMC Cancer | Issue 1/2008

Login to get access

Abstract

Background

Regional lymph node metastasis is an important prognostic factor in head and neck squamous cell carcinoma (HNSCC) and plays a decisive role in the choice of treatment. Here, we present an independent gene expression validation study of metastasized versus non-metastasized HNSCC.

Methods

We used a dataset recently published by Roepman et al. as reference dataset and an independent gene expression dataset of 11 metastasized and 11 non-metastasized HNSCC tumors as validation dataset. Reference and validation studies were performed on different microarray platforms with different probe sets and probe content. In addition to a supervised gene-based analysis, a supervised pathway-based analysis was performed, evaluating differences in gene expression for predefined tumorigenesis- and metastasis related gene sets.

Results

The gene-based analysis showed 26 significant differentially expressed genes in the reference dataset, 21 of which were present on the microarray platform used in the validation study. 7 of these genes appeared to be significantly expressed in the validation dataset, but failed to pass the correction for multiple testing. The pathway-based analysis revealed 23 significant differentially expressed gene sets, 7 of which were statistically validated. These gene sets are involved in extracellular matrix remodeling (MMPs, MMP regulating pathways and the uPA system), hypoxia and angiogenesis (HIF1α regulated angiogenic factors and HIF1α regulated invasion).

Conclusion

Pathways that are differentially expressed between metastasized and non-metastasized HNSCC are involved in the processes of extracellular matrix remodeling, hypoxia and angiogenesis. A supervised pathway-based analysis enhances the understanding of the biological context of the results, the comparability of results across different microarray studies, and reduces multiple testing problems by focusing on a limited number of pathways of interest instead of analyzing the large number of probes available on the microarray.
Appendix
Available only for authorised users
Literature
1.
Baatenburg de Jong RJ, Hermans J, Molenaar J, Briaire JJ, Le Cessie S: Prediction of survival in patients with head and neck cancer. Head Neck. 2001, 23 (9): 718-724. 10.1002/hed.1102.CrossRefPubMed
2.
Mamelle G, Pampurik J, Luboinski B, Lancar R, Lusinchi A, Bosq J: Lymph node prognostic factors in head and neck squamous cell carcinomas. Am J Surg. 1994, 168 (5): 494-498. 10.1016/S0002-9610(05)80109-6.CrossRefPubMed
3.
Roepman P, Wessels LF, Kettelarij N, Kemmeren P, Miles AJ, Lijnzaad P, Tilanus MG, Koole R, Hordijk GJ, Vliet van der PC, Reinders MJ, Slootweg PJ, Holstege FC: An expression profile for diagnosis of lymph node metastases from primary head and neck squamous cell carcinomas. Nat Genet. 2005, 37 (2): 182-186. 10.1038/ng1502.CrossRefPubMed
4.
Järvinen AK, Hautaniemi S, Edgren H, Auvinen P, Saarela J, Kallioniemi OP, Monni O: Are data from different gene expression microarray platforms comparable?. Genomics. 2004, 83 (6): 1164-1168. 10.1016/j.ygeno.2004.01.004.CrossRefPubMed
5.
Tan PK, Downey TJ, Spitznagel EL, Xu P, Fu D, Dimitrov DS, Lempicki RA, Raaka BM, Cam MC: Evaluation of gene expression measurements from commercial microarray platforms. Nucleic Acids Res. 2003, 31 (19): 5676-84. 10.1093/nar/gkg763.CrossRefPubMedPubMedCentral
6.
Irizarry RA, Warren D, Spencer F, Kim IF, Biswal S, Frank BC, Gabrielson E, Garcia JG, Geoghegan J, Germino G, Griffin C, Hilmer SC, Hoffman E, Jedlicka AE, Kawasaki E, Martínez-Murillo F, Morsberger L, Lee H, Petersen D, Quackenbush J, Scott A, Wilson M, Yang Y, Ye SQ, Yu W: Multiple-laboratory comparison of microarray platforms. Nat Methods. 2005, 2 (5): 345-50. 10.1038/nmeth756.CrossRefPubMed
7.
Kuo WP, Jenssen TK, Butte AJ, Ohno-Machado L, Kohane IS: Analysis of matched mRNA measurements from two different microarray technologies. Bioinformatics. 2002, 18 (3): 405-12. 10.1093/bioinformatics/18.3.405.CrossRefPubMed
8.
9.
Ein-Dor L, Kela I, Getz G, Givol D, Domany E: Outcome signature genes in breast cancer: is there a unique set?. Bioinformatics. 2005, 21 (2): 171-8. 10.1093/bioinformatics/bth469.CrossRefPubMed
10.
Roepman P, Kemmeren P, Wessels LF, Slootweg PJ, Holstege FC: Multiple robust signatures for detecting lymph node metastasis in head and neck cancer. Cancer Res. 2006, 66 (4): 2361-2366. 10.1158/0008-5472.CAN-05-3960.CrossRefPubMed
11.
Ogata H, Goto S, Sato K, Fujibuchi W, Bono H, Kanehisa M: KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 1999, 27 (1): 29-34. 10.1093/nar/27.1.29.CrossRefPubMedPubMedCentral
12.
13.
14.
Manoli Th, Gretz N, Gröne HJ, Kenzelmann M, Eils R, Brors B: Group testing for pathway analysis improves comparability of different microarray datasets. Bioinformatics. 2006, 22 (20): 2500-2506. 10.1093/bioinformatics/btl424.CrossRefPubMed
15.
16.
17.
Wu Z, Irizarry RA, Gentleman R, Martinez-Murillo F, Spencer F: A Model-Based Background Adjustment for Oligonucleotide Expression Arrays. J Am Stat Assoc. 2004, 99 (468): 909-917. 10.1198/016214504000000683.CrossRef
18.
Dai M, Wang P, Boyd AD, Kostov G, Athey B, Jones EG, Bunney WE, Myers RM, Speed TP, Akil H, Watson SJ, Meng F: Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data. Nucleic Acids Res. 2005, 33 (20): e175-10.1093/nar/gni179.CrossRefPubMedPubMedCentral
19.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J: Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 2004, 5 (10): R80-10.1186/gb-2004-5-10-r80.CrossRefPubMedPubMedCentral
20.
21.
Smyth GK: Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol. 2004, 3: Article 3-
22.
Benjamini Y, Hochberg Y: Controlling the false discovery rate: A practical and powerful approach to multiple testing. J Royal Stat Soc B. 1995, 57: 289-300.
23.
Fidler IJ: The pathogenesis of cancer metastasis: the 'seed and soil' hypothesis revisited. Nat Rev Cancer. 2003, 3 (6): 453-458. 10.1038/nrc1098.CrossRefPubMed
24.
Goeman JJ, Geer van de SA, de Kort F, van Houwelingen HC: A global test for groups of genes: testing association with a clinical outcome. Bioinformatics. 2004, 20 (1): 93-99. 10.1093/bioinformatics/btg382.CrossRefPubMed
25.
Yasumi M, Sakisaka T, Hoshino T, Kimura T, Sakamoto Y, Yamanaka T, Ohno S, Takai Y: Direct binding of Lgl2 to LGN during mitosis and its requirement for normal cell division. J Biol Chem. 2005, 280 (8): 6761-6765. 10.1074/jbc.C400440200.CrossRefPubMed
26.
Mori Y, Kono K, Matsumoto Y, Fujii H, Yamane T, Mitsumata M, Chen WT: The expression of a type II transmembrane serine protease (Seprase) in human gastric carcinoma. Oncology. 2004, 67 (5–6): 411-419. 10.1159/000082926.PubMed
27.
Iwasa S, Okada K, Chen WT, Jin X, Yamane T, Ooi A, Mitsumata M: Increased expression of seprase, a membrane-type serine protease, is associated with lymph node metastasis in human colorectal cancer. Cancer Lett. 2005, 227 (2): 229-236. 10.1016/j.canlet.2004.06.030.CrossRefPubMed
28.
Jin X, Iwasa S, Okada K, Mitsumata M, Ooi A: Expression patterns of seprase, a membrane serine protease, in cervical carcinoma and cervical intraepithelial neoplasm. Anticancer Res. 2003, 23 (4): 3195-3198.PubMed
29.
Andreasen PA, Kjoller L, Christensen L, Duffy MJ: The urokinase-type plasminogen activator system in cancer metastasis: a review. Int J Cancer. 1997, 72 (1): 1-22. 10.1002/(SICI)1097-0215(19970703)72:1<1::AID-IJC1>3.0.CO;2-Z.CrossRefPubMed
30.
Duffy MJ, Duggan C: The urokinase plasminogen activator system: a rich source of tumour markers for the individualised management of patients with cancer. Clin Biochem. 2004, 37 (7): 541-548. 10.1016/j.clinbiochem.2004.05.013.CrossRefPubMed
31.
Fujita M, Khazenzon NM, Bose S, Sekiguchi K, Sasaki T, Carter WG, Ljubimov AV, Black KL, Ljubimova JY: Overexpression of beta1-chain-containing laminins in capillary basement membranes of human breast cancer and its metastases. Breast Cancer Res. 2005, 7 (4): R411-421. 10.1186/bcr1011.CrossRefPubMedPubMedCentral
32.
Patarroyo M, Tryggvason K, Virtanen I: Laminin isoforms in tumor invasion, angiogenesis and metastasis. Semin Cancer Biol. 2002, 12 (3): 197-207. 10.1016/S1044-579X(02)00023-8.CrossRefPubMed
33.
Yu L, Mikloucich J, Sangster N, Perez A, McCormick PJ: MyoR is expressed in nonmyogenic cells and can inhibit their differentiation. Exp Cell Res. 2003, 289 (1): 162-173. 10.1016/S0014-4827(03)00252-0.CrossRefPubMed
34.
Mathas S, Janz M, Hummel F, Hummel M, Wollert-Wulf B, Lusatis S, Anagnostopoulos I, Lietz A, Sigvardsson M, Jundt F, Johrens K, Bommert K, Stein H, Dorken B: Intrinsic inhibition of transcription factor E2A by HLH proteins ABF-1 and Id2 mediates reprogramming of neoplastic B cells in Hodgkin lymphoma. Nat Immunol. 2006, 7 (2): 207-215. 10.1038/ni1285.CrossRefPubMed
35.
Schmalbach CE, Chepeha DB, Giordano TJ, Rubin MA, Teknos TN, Bradford CR, Wolf GT, Kuick R, Misek DE, Trask DK, Hanash S: Molecular profiling and the identification of genes associated with metastatic oral cavity/pharynx squamous cell carcinoma. Arch Otolaryngol Head Neck Surg. 2004, 130: 295-302. 10.1001/archotol.130.3.295.CrossRefPubMed
36.
Deryugina EI, Quigley JP: Matrix metalloproteinases and tumor metastasis. Cancer Metastasis Rev. 2006, 25 (1): 9-34. 10.1007/s10555-006-7886-9.CrossRefPubMed
37.
Chakraborti S, Mandal M, Das S, Mandal A, Chakraborti T: Regulation of matrix metalloproteinases: an overview. Mol Cell Biochem. 2003, 253 (1–2): 269-285. 10.1023/A:1026028303196.CrossRefPubMed
38.
Duffy MJ, Duggan C: The urokinase plasminogen activator system: a rich source of tumour markers for the individualised management of patients with cancer. Clin Biochem. 2004, 37 (7): 541-548. 10.1016/j.clinbiochem.2004.05.013.CrossRefPubMed
39.
Hirota K, Semenza GL: Regulation of angiogenesis by hypoxia-inducible factor 1. Crit Rev Oncol Hematol. 2006, 59 (1): 15-26. 10.1016/j.critrevonc.2005.12.003.CrossRefPubMed
40.
Choi KS, Bae MK, Jeong JW, Moon HE, Kim KW: Hypoxia-induced angiogenesis during carcinogenesis. J Biochem Mol Biol. 2003, 36 (1): 120-127.CrossRefPubMed
41.
Vaupel P: The role of hypoxia-induced factors in tumor progression. Oncologist. 2004, 9 (Suppl 5): 10-17. 10.1634/theoncologist.9-90005-10.CrossRefPubMed
Metadata
Title
Gene-expression of metastasized versus non-metastasized primary head and neck squamous cell carcinomas: A pathway-based analysis
Authors
Erik F Hensen
Maria J De Herdt
Jelle J Goeman
Jan Oosting
Vincent THBM Smit
Cees J Cornelisse
Robert J Baatenburg de Jong
Publication date
01-12-2008
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2008
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/1471-2407-8-168

Other articles of this Issue 1/2008

BMC Cancer 1/2008 Go to the issue

Research article

Penetrance estimates for BRCA1 and BRCA2based on genetic testing in a Clinical Cancer Genetics service setting: Risks of breast/ovarian cancer quoted should reflect the cancer burden in the family

Research article

Clinical implications of thymidylate synthetase, dihydropyrimidine dehydrogenase and orotate phosphoribosyl transferase activity levels in colorectal carcinoma following radical resection and administration of adjuvant 5-FU chemotherapy

Research article

Class I histone deacetylases 1, 2 and 3 are highly expressed in renal cell cancer

Research article

Nuclear hBD-1 accumulation in malignant salivary gland tumours

Research article

Efficacy of laser capture microdissection plus RT-PCR technique in analyzing gene expression levels in human gastric cancer and colon cancer

Research article

Flow-cytometric monitoring of disease-associated expression of 9-O-acetylated sialoglycoproteins in combination with known CD antigens, as an index for MRD in children with acute lymphoblastic leukaemia: a two-year longitudinal follow-up study
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Watch now

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine
Image Credits