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Cancer associated proteins in blood plasma : Determining normal variation

Stenemo, Markus; Teleman, Johan LU ; Sjöström, Martin LU ; Grubb, Gabriel; Malmström, Erik LU ; Malmström, Johan LU and Niméus, Emma LU (2016) In Proteomics 16(13). p.1928-1937
Abstract

Protein biomarkers have the potential to improve diagnosis, stratification of patients into treatment cohorts, follow disease progression and treatment response. One distinct group of potential biomarkers comprises proteins which have been linked to cancer, known as cancer associated proteins (CAPs). We determined the normal variation of 86 CAPs in 72 individual plasma samples collected from ten individuals using SRM mass spectrometry. Samples were collected weekly during 5 weeks from ten volunteers and over one day at nine fixed time points from three volunteers. We determined the degree of the normal variation depending on interpersonal variation, variation due to time of day, and variation over weeks and observed that the variation... (More)

Protein biomarkers have the potential to improve diagnosis, stratification of patients into treatment cohorts, follow disease progression and treatment response. One distinct group of potential biomarkers comprises proteins which have been linked to cancer, known as cancer associated proteins (CAPs). We determined the normal variation of 86 CAPs in 72 individual plasma samples collected from ten individuals using SRM mass spectrometry. Samples were collected weekly during 5 weeks from ten volunteers and over one day at nine fixed time points from three volunteers. We determined the degree of the normal variation depending on interpersonal variation, variation due to time of day, and variation over weeks and observed that the variation dependent on the time of day appeared to be the most important. Subdivision of the proteins resulted in two predominant protein groups containing 21 proteins with relatively high variation in all three factors (day, week and individual), and 22 proteins with relatively low variation in all factors. We present a strategy for prioritizing biomarker candidates for future studies based on stratification over their normal variation and have made all data publicly available. Our findings can be used to improve selection of biomarker candidates in future studies and to determine which proteins are most suitable depending on study design.

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Biomarkers, Biomedicine, Blood proteome, Cancer associated proteins, Mass spectrometry, Normal variation
in
Proteomics
volume
16
issue
13
pages
10 pages
publisher
John Wiley & Sons
external identifiers
  • Scopus:84971667805
  • WOS:000379925900013
  • Scopus:84990243033
ISSN
1615-9853
DOI
10.1002/pmic.201500204
language
English
LU publication?
yes
id
55149a66-3a4b-4be9-b5e7-8f8b29c9d5be
date added to LUP
2016-06-16 08:03:44
date last changed
2017-01-16 15:08:15
@article{55149a66-3a4b-4be9-b5e7-8f8b29c9d5be,
  abstract     = {<p>Protein biomarkers have the potential to improve diagnosis, stratification of patients into treatment cohorts, follow disease progression and treatment response. One distinct group of potential biomarkers comprises proteins which have been linked to cancer, known as cancer associated proteins (CAPs). We determined the normal variation of 86 CAPs in 72 individual plasma samples collected from ten individuals using SRM mass spectrometry. Samples were collected weekly during 5 weeks from ten volunteers and over one day at nine fixed time points from three volunteers. We determined the degree of the normal variation depending on interpersonal variation, variation due to time of day, and variation over weeks and observed that the variation dependent on the time of day appeared to be the most important. Subdivision of the proteins resulted in two predominant protein groups containing 21 proteins with relatively high variation in all three factors (day, week and individual), and 22 proteins with relatively low variation in all factors. We present a strategy for prioritizing biomarker candidates for future studies based on stratification over their normal variation and have made all data publicly available. Our findings can be used to improve selection of biomarker candidates in future studies and to determine which proteins are most suitable depending on study design.</p>},
  author       = {Stenemo, Markus and Teleman, Johan and Sjöström, Martin and Grubb, Gabriel and Malmström, Erik and Malmström, Johan and Niméus, Emma},
  issn         = {1615-9853},
  keyword      = {Biomarkers,Biomedicine,Blood proteome,Cancer associated proteins,Mass spectrometry,Normal variation},
  language     = {eng},
  month        = {06},
  number       = {13},
  pages        = {1928--1937},
  publisher    = {John Wiley & Sons},
  series       = {Proteomics},
  title        = {Cancer associated proteins in blood plasma : Determining normal variation},
  url          = {http://dx.doi.org/10.1002/pmic.201500204},
  volume       = {16},
  year         = {2016},
}