Original Article
Copyright ©2011 Baishideng Publishing Group Co., Limited. All rights reserved.
World J Gastroenterol. Apr 28, 2011; 17(16): 2096-2103
Published online Apr 28, 2011. doi: 10.3748/wjg.v17.i16.2096
Chemometrics of differentially expressed proteins from colorectal cancer patients
Lay-Chin Yeoh, Saravanan Dharmaraj, Boon-Hui Gooi, Manjit Singh, Lay-Harn Gam
Lay-Chin Yeoh, Lay-Harn Gam, School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, 11800, Malaysia
Saravanan Dharmaraj, Centre for Drug Research, Universiti Sains Malaysia, Penang, 11800, Malaysia
Boon-Hui Gooi, Manjit Singh, Department of Surgery, Penang General Hospital, Penang, 10990, Malaysia
Author contributions: Gam LH conceived the design of the study and edited the manuscript; Yeoh LC carried out the experimental work and manuscript writing; Dharmaraj S carried out the statistical analyses; Gooi BH and Singh M provided the colorectal cancer specimens and patient information.
Supported by Research Universiti Grant, Grant No. 1001/PFARMASI/815007
Correspondence to: Lay-Harn Gam, PhD, School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, 11800, Malaysia. layharn@usm.my
Telephone: +60-4-6533888 Fax: +60-4-6570017
Received: August 13, 2010
Revised: September 18, 2010
Accepted: September 25, 2010
Published online: April 28, 2011

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.

Keywords: Colorectal cancer, Proteomics, Marker protein, Principal component analysis, Linear discriminant analysis