Evidence map›Paper›PMID 20420661›Full record

ArticleWorld journal of surgical oncology2010

Analysis of post-operative changes in serum protein expression profiles from colorectal cancer patients by MALDI-TOF mass spectrometry: a pilot methodological study.

Christopher C L Liao, Anuja Mehta, Nicholas J Ward, Simon Marsh, Tan Arulampalam, John D Norton

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Article in World journal of surgical oncology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Screening for colorectal cancer: established and emerging modalities.Nature reviews. Gastroenterology & hepatology · 2011
    Review
  5. Article
  6. Review
4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Christopher C L LiaoDepartment of Biological Sciences, University of Essex, Wivenhoe Park, Colchester CO43SQ, UK.
Anuja Mehta
Nicholas J Ward
Simon Marsh
Tan Arulampalam
John D Norton

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMass spectrometry-based protein expression profiling of blood sera can be used to discriminate colorectal cancer (CRC) patients from unaffected individuals. In a pilot methodological study, we have evaluated the changes in protein expression profiles of sera from CRC patients that occur following surgery to establish the potential of this approach for monitoring post-surgical response and possible early prediction of disease recurrence.

methodsIn this initial pilot study, serum specimens from 11 cancer patients taken immediately prior to surgery and at approximately 6 weeks following surgery were analysed alongside 10 normal control sera by matrix-assisted laser desorption ionisation time of-flight-mass spectrometry (MALDI-TOF MS). Using a two-sided t-test the top 20 ranked protein peaks that discriminate normal from pre-operative sera were identified. These were used to classify post-operative sera by hierarchical clustering analysis (Spearman's Rank correlation) and, as an independent 'test' dataset, by k-nearest neighbour and weighted voting supervised learning algorithms.

resultsHierarchical cluster analysis classified post-operative sera from all six early Dukes' stage (A and B) patients as normal. The remaining five post-operative sera from more advanced Dukes' stages (C1 and C2) were classified as cancer. Analysis by supervised learning algorithms similarly grouped all advanced Dukes' stages as cancer, with four of the six post-operative sera from early Dukes' stages being classified as normal (P = 0.045; Fisher's exact test).

conclusionsThe results of this pilot methodological study illustrate the proof-of-concept of using protein expression profiling of post-surgical blood sera from individual patients to monitor disease course. Further validation on a larger patient cohort and using an independent post-operative sera dataset would be required to evaluate the potential clinical relevance of this approach. Prospective data, including follow-up on patient survival, could in the future, then be evaluated to inform decisions on individualised treatment modalities.

Indexed as

AgedAged, 80 and overAlgorithmsBiomarkers, TumorBlood ProteinsColorectal NeoplasmsDisease ProgressionFemaleHumansMaleMiddle AgedNeoplasm StagingPilot ProjectsPrognosisProteomicsSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationBiomarkers, TumorBlood Proteins

Identifiers

PMID20420661
PMCPMC2873338

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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.