Expression profiling to predict outcome in breast cancer: the influence of sample selection
Gruvberger, Sofia LU ; Ringnér, Markus LU
; Edén, Patrik
LU
; Borg, Åke
LU
; Fernö, Mårten
LU
; Peterson, Carsten
LU
and Meltzer, Paul S
(2003)
In Breast Cancer Research
5(1).
p.23-26
- Abstract
- Gene expression profiling of tumors using DNA microarrays is a promising method for predicting prognosis and treatment response in cancer patients. It was recently reported that expression profiles of sporadic breast cancers could be used to predict disease recurrence better than currently available clinical and histopathological prognostic factors. Having observed an overlap in those data between the genes that predict outcome and those that predict estrogen receptor- status, we examined their predictive power in an independent data set. We conclude that it may be important to define prognostic expression profiles separately for estrogen receptor--positive and estrogen receptor--negative tumors.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/131208
- author
- Gruvberger, Sofia
LU
; Ringnér, Markus
LU
; Edén, Patrik
LU
; Borg, Åke
LU
; Fernö, Mårten
LU
; Peterson, Carsten
LU
and Meltzer, Paul S
- organization
- publishing date
- 2003-12-04
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Breast Cancer Research
- volume
- 5
- issue
- 1
- pages
- 23 - 26
- publisher
- BioMed Central (BMC)
- external identifiers
-
- wos:000180046700007
- pmid:12559041
- scopus:0012333539
- ISSN
- 1465-5411
- DOI
- 10.1186/bcr548
- language
- English
- LU publication?
- yes
- id
- b7b7790f-2677-427d-abbb-f9f9bc471918 (old id 131208)
- alternative location
- http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=Retrieve&db=PubMed&list_uids=12559041&dopt=Abstract
- date added to LUP
- 2016-04-01 11:53:56
- date last changed
- 2024-04-08 17:35:45
@article{b7b7790f-2677-427d-abbb-f9f9bc471918,
abstract = {{Gene expression profiling of tumors using DNA microarrays is a promising method for predicting prognosis and treatment response in cancer patients. It was recently reported that expression profiles of sporadic breast cancers could be used to predict disease recurrence better than currently available clinical and histopathological prognostic factors. Having observed an overlap in those data between the genes that predict outcome and those that predict estrogen receptor- status, we examined their predictive power in an independent data set. We conclude that it may be important to define prognostic expression profiles separately for estrogen receptor--positive and estrogen receptor--negative tumors.}},
author = {{Gruvberger, Sofia and Ringnér, Markus and Edén, Patrik and Borg, Åke and Fernö, Mårten and Peterson, Carsten and Meltzer, Paul S}},
issn = {{1465-5411}},
language = {{eng}},
month = {{12}},
number = {{1}},
pages = {{23--26}},
publisher = {{BioMed Central (BMC)}},
series = {{Breast Cancer Research}},
title = {{Expression profiling to predict outcome in breast cancer: the influence of sample selection}},
url = {{https://lup.lub.lu.se/search/files/2692862/624180.pdf}},
doi = {{10.1186/bcr548}},
volume = {{5}},
year = {{2003}},
}