Evidence map›Paper›PMID 21547128›Full record

ArticleWorld journal of gastroenterology2011

Chemometrics of differentially expressed proteins from colorectal cancer patients.

Lay-Chin Yeoh, Saravanan Dharmaraj, Boon-Hui Gooi, Manjit Singh, Lay-Harn Gam

Abstract read
In one paragraph

Article in World journal of gastroenterology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Lay-Chin YeohSchool of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, 11800, Malaysia.
Saravanan Dharmaraj
Boon-Hui Gooi
Manjit Singh
Lay-Harn Gam

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo evaluate the usefulness of differentially expressed proteins from colorectal cancer (CRC) tissues for differentiating cancer and normal tissues.

methodsA 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.

resultsDifferentially 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.

conclusionThe 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.

Indexed as

AdultAgedAged, 80 and overBiomarkers, TumorColorectal NeoplasmsHumansMiddle AgedNeoplasm ProteinsPrincipal Component AnalysisProteomicsBiomarkers, TumorNeoplasm ProteinsColorectal cancerLinear discriminant analysisMarker proteinPrincipal component analysisProteomics

Identifiers

PMID21547128
PMCPMC3084394

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.