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      Laser-capture microdissection and protein extraction for protein fingerprint of OSCC and OLK.

      Artificial cells, blood substitutes, and immobilization biotechnology

      Staining and Labeling, Proteomics, isolation & purification, analysis, Proteins, Protein Array Analysis, methods, Peptide Mapping, metabolism, cytology, Mucous Membrane, pathology, diagnosis, Mouth Neoplasms, Microdissection, Mass Spectrometry, Leukoplakia, Oral, Lasers, Ice, Humans, Hematoxylin, Carcinoma, Squamous Cell, Biological Markers

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          Abstract

          To find new biomarkers and establish histopathology protein fingerprint models for early detection of oral squamous cell carcinoma (OSCC), laser capture microdissection (LCM) technology was utilized in 21 OSCC tissues and 7 oral leukoplaque (OLK) tissues as well as their adjacent normal tissues. Each sample was then detected by SELDI-TOF-MS technology and CM10 protein chip as well as bioinformatics tools. Three proteomic biomarker patterns were identified. Pattern 1 distinguishes patients with OLK from healthy individuals. Pattern 2 distinguishes patients with OSCC from healthy individuals. Pattern 3 distinguishes patients with OSCC from patients with OLK. The analysis yielded both a specificity and a sensitivity of 90.48% for pattern 1, a specificity of 100.00% and a sensitivity of 85.71% for pattern 2, and a specificity of 100.00% and a sensitivity of 85.71% for pattern 3. Proteome mass/charge 3714, 3515, and 4944 built the distinguished protein peaks between the OSCC tumor and adjacent normal tissues. The accuracy of the blind prediction was 90.48% (38/42). M/Z 15122 and 7569 built the distinguished protein peaks between the OLK and adjacent normal tissues. M/Z 3738 and 11366 built the distinguished protein peaks between the OSCC and the OLK. By employing LCM technology combined with SELDI-TOF-MS technology and bioinformatics approaches, histopathology would not only facilitate the discovery of better biomarkers for OSCC and OLK, but also provide a useful tool for molecular diagnosis by potential biomarker.

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          Journal
          10.1080/10731190903199028
          19735007

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