Breast Cancer Classification Based on Proteotypes Obtained by
SWATH Mass Spectrometry

J 2019

Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry

BOUCHAL, Pavel; Olga T. SCHUBERT; Jakub FAKTOR; Lenka ČÁPKOVÁ; Hana IMRICHOVÁ et al.

Základní údaje

Originální název

Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry

Autoři

Vydání

Cell Reports, CAMBRIDGE, Cell Press, 2019, 2211-1247

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10601 Cell biology

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Odkazy

Full Text

Impakt faktor

Impact factor: 8.109

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14310/19:00107609

Organizační jednotka

Přírodovědecká fakulta

Klíčová slova anglicky

SWATH-MS; breast cancer; data independent acquisition; proteomics; tissue; transcriptomics; tumor classification

Štítky

H20, rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 17. 2. 2023 20:46, Mgr. Michaela Hylsová, Ph.D.

Anotace

V originále

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.

Návaznosti

GA17-05957S, projekt VaV

Název: Evaluace nových potenciálních cílů a inhibitorů pro blokování vývoje metastáz u luminálních A nádorů prsu

Investor: Grantová agentura ČR, Evaluace nových potenciálních cílů a inhibitorů pro blokování vývoje metastáz u luminálních A nádorů prsu

LM2015051, projekt VaV

Název: Centrum pro výzkum toxických látek v prostředí (Akronym: RECETOX RI)

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, Výzkumná infrastruktura RECETOX

MUNI/A/1575/2018, interní kód MU

Název: Podpora biochemického výzkumu v roce 2019

Investor: Masarykova univerzita, Podpora biochemického výzkumu v roce 2019, DO R. 2020_Kategorie A - Specifický výzkum - Studentské výzkumné projekty

MUNI/E/0514/2018, interní kód MU

Název: Revize a publikace rukopisu "Breast cancer classification based on proteotypes obtained by SWATH mass spectrometry"

Investor: Masarykova univerzita, Revize a publikace rukopisu "Breast cancer classification based on proteotypes obtained by SWATH mass spectrometry", Podpora zvýšení kvality vynikajících výsledků

Citovat

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 a Ruedi AEBERSOLD. Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry. Cell Reports. CAMBRIDGE: Cell Press, 2019, roč. 28, č. 3, s. "832"-"843.e7", 20 s. ISSN 2211-1247. Dostupné z: https://doi.org/10.1016/j.celrep.2019.06.046.

@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 = {https://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 a Ruedi AEBERSOLD. Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry. \textit{Cell Reports}. CAMBRIDGE: Cell Press, 2019, roč.~28, č.~3, s.~''832''-''843.e7'', 20 s. ISSN~2211-1247. Dostupné z: https://doi.org/10.1016/j.celrep.2019.06.046.

Přehled o publikaci