Hydrophobic protein in colorectal cancer in relation to tumor stages and grades

AIM: To identify differentially expressed hydrophobic proteins in colorectal cancer. METHODS: Eighteen pairs of colorectal cancerous tissues in addition to tissues from normal mucosa were analysed. Hydrophobic proteins were extracted from the tissues, separated using 2-D gel electrophoresis and analysed using Liquid Chromatography Tandem Mass Spectrometry (LC/MS/MS). Statistical analysis of the proteins was carried out in order to determine the significance of each protein to colorectal cancer (CRC) and also their relation to CRC stages, grades and patients’ gender. RESULTS: Thirteen differentially expressed proteins which were expressed abundantly in either cancerous or normal tissues were identified. A number of these proteins were found to relate strongly with a particular stage or grade of CRC. In addition, the association of these proteins with patient gender also appeared to be significant.CONCLUSION: Stomatin-like protein 2 was found to be a promising biomarker for CRC, especially in female patients. The differentially expressed proteins identified were associated with CRC and may act as drug target candidates.

Chemometrics of differentially expressed proteins from colorectal cancer patients

AIM:To evaluate the usefulness of differentially expressed proteins from colorectal cancer (CRC) tissues for differentiating cancer and normal tissues.METHODS:A Proteomic approach was used to identify the differentially expressed proteins between CRC and normal tissues.The proteins were extracted using Tris buffer and thiourea lysis buffer (TLB) for extraction of aqueous soluble and membrane-associated proteins,respectively.Chemometrics,namely principal component analysis (PCA) and linear discriminant analysis (LDA),were used to assess the usefulness of these proteins for identifying the cancerous state of tissues.RESULTS:Differentially expressed proteins identified were 37 aqueous soluble proteins in Tris extracts and 24 membrane-associated proteins in TLB extracts.Based on the protein spots intensity on 2D-gel images,PCA by applying an eigenvalue > 1 was successfully used to reduce the number of principal components (PCs) into 12 and seven PCs for Tris and TLB extracts,respectively,and subsequently six PCs,respectively from both the extracts were used for LDA.The LDA classification for Tris extract showed 82.7% of original samples were correctly classified,whereas 82.7% were correctly classified for the cross-validated samples.The LDA for TLB extract showed that 78.8% of original samples and 71.2% of the cross-validated samples were correctly classified.CONCLUSION:The classification of CRC tissues by PCA and LDA provided a promising distinction between normal and cancer types.These methods can possibly be used for identification of potential biomarkers among the differentially expressed proteins identified.