| BOUCHAL, Pavel, Olga T. SCHUBERT, Jakub FAKTOR, Lenka ČÁPKOVÁ, Hana IMRICHOVÁ, Karolína ZOUFALOVÁ, Vendula PÁRALOVÁ, Roman HRSTKA, Yansheng S. LIU, Holger A. EBHARDT, Eva BUDINSKÁ, Rudolf NENUTIL and Ruedi AEBERSOLD. Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry. Cell Reports. CAMBRIDGE: Cell Press, 2019, vol. 28, No 3, p. "832"-"843.e7", 20 pp. ISSN 2211-1247. Available from: https://dx.doi.org/10.1016/j.celrep.2019.06.046. |
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@article{1552277,
author = {Bouchal, Pavel and Schubert, Olga T. and Faktor, Jakub and Čápková, Lenka and Imrichová, Hana and Zoufalová, Karolína and Páralová, Vendula and Hrstka, Roman and Liu, Yansheng S. and Ebhardt, Holger A. and Budinská, Eva and Nenutil, Rudolf and Aebersold, Ruedi},
article_location = {CAMBRIDGE},
article_number = {3},
doi = {http://dx.doi.org/10.1016/j.celrep.2019.06.046},
keywords = {SWATH-MS; breast cancer; data independent acquisition; proteomics; tissue; transcriptomics; tumor classification},
language = {eng},
issn = {2211-1247},
journal = {Cell Reports},
title = {Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry},
url = {https://www.sciencedirect.com/science/article/pii/S2211124719308198},
volume = {28},
year = {2019}
}
TY - JOUR
ID - 1552277
AU - Bouchal, Pavel - Schubert, Olga T. - Faktor, Jakub - Čápková, Lenka - Imrichová, Hana - Zoufalová, Karolína - Páralová, Vendula - Hrstka, Roman - Liu, Yansheng S. - Ebhardt, Holger A. - Budinská, Eva - Nenutil, Rudolf - Aebersold, Ruedi
PY - 2019
TI - Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry
JF - Cell Reports
VL - 28
IS - 3
SP - "832"-"843.e7"
EP - "832"-"843.e7"
PB - Cell Press
SN - 22111247
KW - SWATH-MS
KW - breast cancer
KW - data independent acquisition
KW - proteomics
KW - tissue
KW - transcriptomics
KW - tumor classification
UR - https://www.sciencedirect.com/science/article/pii/S2211124719308198
L2 - https://www.sciencedirect.com/science/article/pii/S2211124719308198
N2 - Accurate classification of breast tumors is vital for patient management decisions and enables more precise cancer treatment. Here, we present a quantitative proteotyping approach based on sequential windowed acquisition of all theoretical fragment ion spectra (SWATH) mass spectrometry and establish key proteins for breast tumor classification. The study is based on 96 tissue samples representing five conventional breast cancer subtypes. SWATH proteotype patterns largely recapitulate these subtypes; however, they also reveal varying heterogeneity within the conventional subtypes, with triple negative tumors being the most heterogeneous. Proteins that contribute most strongly to the proteotype-based classification include INPP4B, CDK1, and ERBB2 and are associated with estrogen receptor (ER) status, tumor grade status, and HER2 status. Although these three key proteins exhibit high levels of correlation with transcript levels (R > 0.67), general correlation did not exceed R = 0.29, indicating the value of protein-level measurements of disease-regulated genes. Overall, this study highlights how cancer tissue proteotyping can lead to more accurate patient stratification.
ER -
BOUCHAL, Pavel, Olga T. SCHUBERT, Jakub FAKTOR, Lenka ČÁPKOVÁ, Hana IMRICHOVÁ, Karolína ZOUFALOVÁ, Vendula PÁRALOVÁ, Roman HRSTKA, Yansheng S. LIU, Holger A. EBHARDT, Eva BUDINSKÁ, Rudolf NENUTIL and Ruedi AEBERSOLD. Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry. \textit{Cell Reports}. CAMBRIDGE: Cell Press, 2019, vol.~28, No~3, p.~''832''-''843.e7'', 20 pp. ISSN~2211-1247. Available from: https://dx.doi.org/10.1016/j.celrep.2019.06.046.
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