Antibody microarray-based oncoproteomics
(2006) In Expert Opinion on Biological Therapy 6(8). p.833-838- Abstract
- The driving force behind oncoproteomics is the belief that certain protein signatures or patterns exist that are associated with a particular malignancy. if so, the correlation of clinical parameters with defined protein expression patterns would allow us to predict disease progression and perhaps even postulate improved therapeutic modalities. The technological challenges to achieve these goals are significant, as the human proteome is not defined. No general methodological approach exists today, and human cancer can, furthermore, be divided into several disease subgroups. One potential solution to finding cancer-associated protein signatures is the emerging technology of affinity proteomics. This approach addresses some of the... (More)
- The driving force behind oncoproteomics is the belief that certain protein signatures or patterns exist that are associated with a particular malignancy. if so, the correlation of clinical parameters with defined protein expression patterns would allow us to predict disease progression and perhaps even postulate improved therapeutic modalities. The technological challenges to achieve these goals are significant, as the human proteome is not defined. No general methodological approach exists today, and human cancer can, furthermore, be divided into several disease subgroups. One potential solution to finding cancer-associated protein signatures is the emerging technology of affinity proteomics. This approach addresses some of the shortcomings of traditional proteomics and combines it with the power of microarrays. The present review focuses on the role of antibody microarrays in oncoproteomics and its potential to provide a truly proteome-wide analytical approach. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/399577
- author
- Borrebaeck, Carl LU
- organization
- publishing date
- 2006
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- recombinant, antibody, proteome analysis, microarray, affinity proteomics, cancer
- in
- Expert Opinion on Biological Therapy
- volume
- 6
- issue
- 8
- pages
- 833 - 838
- publisher
- Ashley Publications
- external identifiers
-
- pmid:16856804
- wos:000239378700010
- scopus:33746820320
- ISSN
- 1471-2598
- DOI
- 10.1517/14712598.6.8.833
- language
- English
- LU publication?
- yes
- id
- d50ee478-c7b3-417d-b0ef-24d760aadcf3 (old id 399577)
- date added to LUP
- 2016-04-01 11:44:47
- date last changed
- 2022-01-26 17:34:29
@article{d50ee478-c7b3-417d-b0ef-24d760aadcf3,
abstract = {{The driving force behind oncoproteomics is the belief that certain protein signatures or patterns exist that are associated with a particular malignancy. if so, the correlation of clinical parameters with defined protein expression patterns would allow us to predict disease progression and perhaps even postulate improved therapeutic modalities. The technological challenges to achieve these goals are significant, as the human proteome is not defined. No general methodological approach exists today, and human cancer can, furthermore, be divided into several disease subgroups. One potential solution to finding cancer-associated protein signatures is the emerging technology of affinity proteomics. This approach addresses some of the shortcomings of traditional proteomics and combines it with the power of microarrays. The present review focuses on the role of antibody microarrays in oncoproteomics and its potential to provide a truly proteome-wide analytical approach.}},
author = {{Borrebaeck, Carl}},
issn = {{1471-2598}},
keywords = {{recombinant; antibody; proteome analysis; microarray; affinity proteomics; cancer}},
language = {{eng}},
number = {{8}},
pages = {{833--838}},
publisher = {{Ashley Publications}},
series = {{Expert Opinion on Biological Therapy}},
title = {{Antibody microarray-based oncoproteomics}},
url = {{http://dx.doi.org/10.1517/14712598.6.8.833}},
doi = {{10.1517/14712598.6.8.833}},
volume = {{6}},
year = {{2006}},
}