Large-Scale Proteomics Analysis of Human Ovarian Cancer for Biomarkers
Bengtsson, S ; Krogh, Morten LU ; Al-Khalili Szigyarto, C ; Uhlen, M ; Schedvins, K ; Silfversward, C ; Linder, S ; Auer, G ; Alaiya, A and James, Peter LU
(2007)
In Journal of Proteome Research
6(4).
p.1440-1450
- Abstract
- Ovarian cancer is usually found at a late stage when the prognosis is often bad. Relative survival rates decrease with tumor stage or grade, and the 5-year survival rate for women with carcinoma is only 38%. Thus, there is a great need to find biomarkers that can be used to carry out routine screening, especially in high-risk patient groups. Here, we present a large-scale study of 64 tissue samples taken from patients at all stages and show that we can identify statistically valid markers using nonsupervised methods that distinguish between normal, benign, borderline, and malignant tissue. We have identified 217 of the significantly changing protein spots. We are expressing and raising antibodies to 35 of these. Currently, we have... (More)
- Ovarian cancer is usually found at a late stage when the prognosis is often bad. Relative survival rates decrease with tumor stage or grade, and the 5-year survival rate for women with carcinoma is only 38%. Thus, there is a great need to find biomarkers that can be used to carry out routine screening, especially in high-risk patient groups. Here, we present a large-scale study of 64 tissue samples taken from patients at all stages and show that we can identify statistically valid markers using nonsupervised methods that distinguish between normal, benign, borderline, and malignant tissue. We have identified 217 of the significantly changing protein spots. We are expressing and raising antibodies to 35 of these. Currently, we have validated 5 of these antibodies for use in immunohistochemical analysis using tissue microarrays of healthy and diseased ovarian, as well as other, human tissues. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/599980
- author
- Bengtsson, S
; Krogh, Morten
LU
; Al-Khalili Szigyarto, C
; Uhlen, M
; Schedvins, K
; Silfversward, C
; Linder, S
; Auer, G
; Alaiya, A
and James, Peter
LU
- organization
- publishing date
- 2007
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Journal of Proteome Research
- volume
- 6
- issue
- 4
- pages
- 1440 - 1450
- publisher
- The American Chemical Society (ACS)
- external identifiers
-
- wos:000245510900022
- scopus:34248207230
- pmid:17315909
- ISSN
- 1535-3893
- DOI
- 10.1021/pr060593y
- language
- English
- LU publication?
- yes
- id
- 8c6e414a-5ef0-4e7e-8afc-489b8c8ffa55 (old id 599980)
- date added to LUP
- 2016-04-01 11:51:44
- date last changed
- 2024-03-25 16:27:56
@article{8c6e414a-5ef0-4e7e-8afc-489b8c8ffa55,
abstract = {{Ovarian cancer is usually found at a late stage when the prognosis is often bad. Relative survival rates decrease with tumor stage or grade, and the 5-year survival rate for women with carcinoma is only 38%. Thus, there is a great need to find biomarkers that can be used to carry out routine screening, especially in high-risk patient groups. Here, we present a large-scale study of 64 tissue samples taken from patients at all stages and show that we can identify statistically valid markers using nonsupervised methods that distinguish between normal, benign, borderline, and malignant tissue. We have identified 217 of the significantly changing protein spots. We are expressing and raising antibodies to 35 of these. Currently, we have validated 5 of these antibodies for use in immunohistochemical analysis using tissue microarrays of healthy and diseased ovarian, as well as other, human tissues.}},
author = {{Bengtsson, S and Krogh, Morten and Al-Khalili Szigyarto, C and Uhlen, M and Schedvins, K and Silfversward, C and Linder, S and Auer, G and Alaiya, A and James, Peter}},
issn = {{1535-3893}},
language = {{eng}},
number = {{4}},
pages = {{1440--1450}},
publisher = {{The American Chemical Society (ACS)}},
series = {{Journal of Proteome Research}},
title = {{Large-Scale Proteomics Analysis of Human Ovarian Cancer for Biomarkers}},
url = {{http://dx.doi.org/10.1021/pr060593y}},
doi = {{10.1021/pr060593y}},
volume = {{6}},
year = {{2007}},
}