Detection of pancreatic cancer using antibody microarray-based serum protein profiling
(2008) In Proteomics 8(11). p.2211-2219- 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... (More)
- 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. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1039940
- author
- Ingvarsson, Johan LU ; Wingren, Christer LU ; Carlsson, Anders LU ; Ellmark, Peter LU ; Wahren, Britta ; Engström, Gunilla ; Harmenberg, Ulrika ; Krogh, Morten LU ; Peterson, Carsten LU and Borrebaeck, Carl LU
- organization
- publishing date
- 2008
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Proteomics
- volume
- 8
- issue
- 11
- pages
- 2211 - 2219
- publisher
- John Wiley & Sons Inc.
- external identifiers
-
- wos:000256961600009
- scopus:46049092019
- ISSN
- 1615-9861
- DOI
- 10.1002/pmic.200701167
- language
- English
- LU publication?
- yes
- id
- c704cb8c-2481-4cd4-abc9-dac23313d4aa (old id 1039940)
- date added to LUP
- 2016-04-01 12:13:11
- date last changed
- 2024-03-11 21:12:35
@article{c704cb8c-2481-4cd4-abc9-dac23313d4aa, 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 = {{Ingvarsson, Johan and Wingren, Christer and Carlsson, Anders and Ellmark, Peter and Wahren, Britta and Engström, Gunilla and Harmenberg, Ulrika and Krogh, Morten and Peterson, Carsten and Borrebaeck, Carl}}, issn = {{1615-9861}}, language = {{eng}}, number = {{11}}, pages = {{2211--2219}}, publisher = {{John Wiley & Sons Inc.}}, series = {{Proteomics}}, title = {{Detection of pancreatic cancer using antibody microarray-based serum protein profiling}}, url = {{http://dx.doi.org/10.1002/pmic.200701167}}, doi = {{10.1002/pmic.200701167}}, volume = {{8}}, year = {{2008}}, }