Grading breast cancer tissues using molecular portraits.
Olsson, Niclas LU ; Skoog, Petter LU ; James, Peter LU
; Hansson, Karin M
LU
; Waldemarson, Sofia
; Malmström, Per
LU
; Fernö, Mårten
LU
; Rydén, Lisa
LU
; Wingren, Christer
LU
and Borrebaeck, Carl
LU
(2013)
In Molecular & Cellular Proteomics
12(12).
p.3612-3623
- Abstract
- Tumor progression and prognosis of breast cancer patients is difficult to assess using current clinical and laboratory parameters, where a pathological grading is indicative of tumor aggressiveness. This grading is based on assessment of nuclear grade, tubule formation, and mitotic rate. We report here the first protein signatures associated with histological grades of breast cancer, using a novel affinity proteomics approach. We profiled 52 breast cancer tissue samples, by combining nine antibodies and label-free LC-MS/MS, which generated detailed quantified proteomic maps representing 1,388 proteins. The results showed that we could define in-depth molecular portraits of histologically graded breast cancer tumors. Consequently, a 49-plex... (More)
- Tumor progression and prognosis of breast cancer patients is difficult to assess using current clinical and laboratory parameters, where a pathological grading is indicative of tumor aggressiveness. This grading is based on assessment of nuclear grade, tubule formation, and mitotic rate. We report here the first protein signatures associated with histological grades of breast cancer, using a novel affinity proteomics approach. We profiled 52 breast cancer tissue samples, by combining nine antibodies and label-free LC-MS/MS, which generated detailed quantified proteomic maps representing 1,388 proteins. The results showed that we could define in-depth molecular portraits of histologically graded breast cancer tumors. Consequently, a 49-plex candidate tissue protein signature was defined that discriminated between histological grade 1, 2, and 3 of breast cancer tumors with high accuracy. Highly biologically relevant proteins were identified, and the differentially expressed proteins indicated further support for the current hypothesis regarding remodeling of tumor microenvironment during tumor progression. The protein signature was corroborated using meta-analysis of transcriptional profiling data from an independent patient cohort. In addition, the potential for using the markers to estimate the risk of distant metastasis free survival was also indicated. Taken together, these molecular portraits could pave the way for improved classification and prognostication of breast cancer. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4005298
- author
- Olsson, Niclas
LU
; Skoog, Petter
LU
; James, Peter
LU
; Hansson, Karin M
LU
; Waldemarson, Sofia
; Malmström, Per
LU
; Fernö, Mårten
LU
; Rydén, Lisa
LU
; Wingren, Christer
LU
and Borrebaeck, Carl
LU
- organization
- publishing date
- 2013
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Molecular & Cellular Proteomics
- volume
- 12
- issue
- 12
- pages
- 3612 - 3623
- publisher
- American Society for Biochemistry and Molecular Biology
- external identifiers
-
- pmid:23982162
- wos:000329993600015
- scopus:84890689655
- pmid:23982162
- ISSN
- 1535-9484
- DOI
- 10.1074/mcp.M113.030379
- language
- English
- LU publication?
- yes
- id
- 8a71120d-0e86-4d9e-a0b8-f9b58210828b (old id 4005298)
- alternative location
- http://www.ncbi.nlm.nih.gov/pubmed/23982162?dopt=Abstract
- date added to LUP
- 2016-04-01 09:48:23
- date last changed
- 2023-10-11 10:19:32
@article{8a71120d-0e86-4d9e-a0b8-f9b58210828b,
abstract = {{Tumor progression and prognosis of breast cancer patients is difficult to assess using current clinical and laboratory parameters, where a pathological grading is indicative of tumor aggressiveness. This grading is based on assessment of nuclear grade, tubule formation, and mitotic rate. We report here the first protein signatures associated with histological grades of breast cancer, using a novel affinity proteomics approach. We profiled 52 breast cancer tissue samples, by combining nine antibodies and label-free LC-MS/MS, which generated detailed quantified proteomic maps representing 1,388 proteins. The results showed that we could define in-depth molecular portraits of histologically graded breast cancer tumors. Consequently, a 49-plex candidate tissue protein signature was defined that discriminated between histological grade 1, 2, and 3 of breast cancer tumors with high accuracy. Highly biologically relevant proteins were identified, and the differentially expressed proteins indicated further support for the current hypothesis regarding remodeling of tumor microenvironment during tumor progression. The protein signature was corroborated using meta-analysis of transcriptional profiling data from an independent patient cohort. In addition, the potential for using the markers to estimate the risk of distant metastasis free survival was also indicated. Taken together, these molecular portraits could pave the way for improved classification and prognostication of breast cancer.}},
author = {{Olsson, Niclas and Skoog, Petter and James, Peter and Hansson, Karin M and Waldemarson, Sofia and Malmström, Per and Fernö, Mårten and Rydén, Lisa and Wingren, Christer and Borrebaeck, Carl}},
issn = {{1535-9484}},
language = {{eng}},
number = {{12}},
pages = {{3612--3623}},
publisher = {{American Society for Biochemistry and Molecular Biology}},
series = {{Molecular & Cellular Proteomics}},
title = {{Grading breast cancer tissues using molecular portraits.}},
url = {{http://dx.doi.org/10.1074/mcp.M113.030379}},
doi = {{10.1074/mcp.M113.030379}},
volume = {{12}},
year = {{2013}},
}