Proteomic analysis reveals successive aberrations in protein expression from healthy mucosa to invasive head and neck cancer

M. Roesch-Ely, Matthias Nees, S. Karsai, A. Ruess, R. Bogumi, U. Warnken, M. Schnölzer, A. Dietz, P. K. Plinkert, C. Hofele, F. X. Bosch

Research output: Contribution to journalArticleScientificpeer-review

96 Citations (Scopus)

Abstract

Development of head and neck squamous cell carcinoma (HNSCC) is a multistep process and in many cases involves a phenomenon coined ‘field cancerization’. In order to identify changes in protein expression occurring at different stages of tumorigenesis and field cancerization, we analysed 113 HNSCCs and 73 healthy, 99 tumor-distant and 18 tumor-adjacent squamous mucosae by SELDI-TOF-MS on IMAC30 ProteinChip Arrays. Forty-eight protein peaks were differentially expressed between healthy mucosa and HNSCC. Calgizarrin (S100A11), the Cystein proteinase inhibitor Cystatin A, Acyl-CoA-binding protein, Stratifin (14-3-3 sigma), Histone H4, α- and β-Hemoglobin, a C-terminal fragment of β-hemoglobin and the α-defensins 1–3 were identified by mass spectrometry. The α-defensins showed various alterations in expression as validated by immunohistochemistry (IHC). Supervised prediction analysis revealed excellent classification of healthy mucosa (94.5% correctly classified) and tumor samples (92.9% correctly classified). Application of this classifier to the tumor-adjacent and tumor-distant mucosa samples disclosed dramatic changes: only 59.6% of the tumor-distant biopsies were classified as normal, 27.3% were predicted as aberrant or HNSCC. Strikingly, 72% of the tumor-adjacent mucosae were predicted as aberrant. These data provide evidence for the existence of genetically altered fields with inconspicuous histology. Comparison of the protein profiles in the tumor-distant-samples with clinical outcome of 32 patients revealed a significant association between aberrant profiles with tumor relapse events (P=0.018; Fisher's exact test, two-tailed). We conclude that proteomic profiling in conjunction with protein identification greatly outperforms histopathological diagnosis and may have significant predictive power for clinical outcome and personalized risk assessment.
Original languageEnglish
Pages (from-to)54-64
JournalOncogene
Volume26
Issue number1
DOIs
Publication statusPublished - 2007
MoE publication typeA1 Journal article-refereed

Keywords

  • proteomics
  • SELDI-TOF-MS
  • HNSCC
  • field cancerization
  • protein biomarkers

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