Detection of pancreatic cancer using antibody microarray-based serum protein profiling

Johan Ingvarsson; Christer Wingren; Anders Carlsson; Peter Ellmark; Britta Wahren; Gunilla Engström; Ulrika Harmenberg; Morten Krogh; Carsten Peterson; Carl Borrebaeck

doi:10.1002/pmic.200701167

Detection of pancreatic cancer using antibody microarray-based serum protein profiling

Johan Ingvarsson, Christer Wingren, Anders Carlsson, Peter Ellmark, Britta Wahren, Gunilla Engström, Ulrika Harmenberg, Morten Krogh, Carsten Peterson, Carl Borrebaeck

Department of Immunotechnology

Research output: Contribution to journal › Article › peer-review

Abstract

The driving force behind oncoproteomics is to identify protein signatures that are associated with a particular malignancy. Here, we have used a recombinant scFv antibody microarray in an attempt to classify sera derived from pancreatic adenocarcinoma patients versus healthy subjects. Based on analysis of nonfractionated, directly labeled, whole human serum proteomes we have identified a protein signature based on 19 nonredundant analytes, that discriminates between cancer patients and healthy subjects. Furthermore, a potential protein signature, consisting of 21 protein analytes, could be defined that was shown to be associated with cancer patients having a life expectancy of <12 months. Taken together, the data suggest that antibody microarray analysis of complex proteomes will be a useful tool to define disease associated protein signatures.

Original language	English
Pages (from-to)	2211-2219
Journal	Proteomics
Volume	8
Issue number	11
DOIs	https://doi.org/10.1002/pmic.200701167
Publication status	Published - 2008

Subject classification (UKÄ)

Immunology in the medical area
Biophysics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1002/pmic.200701167

Cite this

@article{c704cb8c24814cd4abc9dac23313d4aa,

title = "Detection of pancreatic cancer using antibody microarray-based serum protein profiling",

abstract = "The driving force behind oncoproteomics is to identify protein signatures that are associated with a particular malignancy. Here, we have used a recombinant scFv antibody microarray in an attempt to classify sera derived from pancreatic adenocarcinoma patients versus healthy subjects. Based on analysis of nonfractionated, directly labeled, whole human serum proteomes we have identified a protein signature based on 19 nonredundant analytes, that discriminates between cancer patients and healthy subjects. Furthermore, a potential protein signature, consisting of 21 protein analytes, could be defined that was shown to be associated with cancer patients having a life expectancy of <12 months. Taken together, the data suggest that antibody microarray analysis of complex proteomes will be a useful tool to define disease associated protein signatures.",

author = "Johan Ingvarsson and Christer Wingren and Anders Carlsson and Peter Ellmark and Britta Wahren and Gunilla Engstr{\"o}m and Ulrika Harmenberg and Morten Krogh and Carsten Peterson and Carl Borrebaeck",

year = "2008",

doi = "10.1002/pmic.200701167",

language = "English",

volume = "8",

pages = "2211--2219",

journal = "Proteomics",

issn = "1615-9861",

publisher = "John Wiley & Sons Inc.",

number = "11",

}

TY - JOUR

T1 - Detection of pancreatic cancer using antibody microarray-based serum protein profiling

AU - Ingvarsson, Johan

AU - Wingren, Christer

AU - Carlsson, Anders

AU - Ellmark, Peter

AU - Wahren, Britta

AU - Engström, Gunilla

AU - Harmenberg, Ulrika

AU - Krogh, Morten

AU - Peterson, Carsten

AU - Borrebaeck, Carl

PY - 2008

Y1 - 2008

N2 - The driving force behind oncoproteomics is to identify protein signatures that are associated with a particular malignancy. Here, we have used a recombinant scFv antibody microarray in an attempt to classify sera derived from pancreatic adenocarcinoma patients versus healthy subjects. Based on analysis of nonfractionated, directly labeled, whole human serum proteomes we have identified a protein signature based on 19 nonredundant analytes, that discriminates between cancer patients and healthy subjects. Furthermore, a potential protein signature, consisting of 21 protein analytes, could be defined that was shown to be associated with cancer patients having a life expectancy of <12 months. Taken together, the data suggest that antibody microarray analysis of complex proteomes will be a useful tool to define disease associated protein signatures.

AB - The driving force behind oncoproteomics is to identify protein signatures that are associated with a particular malignancy. Here, we have used a recombinant scFv antibody microarray in an attempt to classify sera derived from pancreatic adenocarcinoma patients versus healthy subjects. Based on analysis of nonfractionated, directly labeled, whole human serum proteomes we have identified a protein signature based on 19 nonredundant analytes, that discriminates between cancer patients and healthy subjects. Furthermore, a potential protein signature, consisting of 21 protein analytes, could be defined that was shown to be associated with cancer patients having a life expectancy of <12 months. Taken together, the data suggest that antibody microarray analysis of complex proteomes will be a useful tool to define disease associated protein signatures.

U2 - 10.1002/pmic.200701167

DO - 10.1002/pmic.200701167

M3 - Article

SN - 1615-9861

VL - 8

SP - 2211

EP - 2219

JO - Proteomics

JF - Proteomics

IS - 11

ER -

Detection of pancreatic cancer using antibody microarray-based serum protein profiling

Abstract

Subject classification (UKÄ)

UN SDGs

Access to Document

Fingerprint

Cite this