Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00209805%3A_____%2F19%3A00078216" target="_blank" >RIV/00209805:_____/19:00078216 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216224:14310/19:00107609

Výsledek na webu

<a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6656695/" target="_blank" >https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6656695/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.celrep.2019.06.046" target="_blank" >10.1016/j.celrep.2019.06.046</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry

Popis výsledku v původním jazyce

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 proteotypebased 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 &gt; 0.67), general correlation did not exceed R = 0.29, indicating the value of protein-level measurements of diseaseregulated genes. Overall, this study highlights how cancer tissue proteotyping can lead to more accurate patient stratification.

Název v anglickém jazyce

Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry

Popis výsledku anglicky

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 proteotypebased 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 &gt; 0.67), general correlation did not exceed R = 0.29, indicating the value of protein-level measurements of diseaseregulated genes. Overall, this study highlights how cancer tissue proteotyping can lead to more accurate patient stratification.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30204 - Oncology

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Cell Reports

ISSN

2211-1247

e-ISSN

—

Svazek periodika

28

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

20

Strana od-do

"832–843.e1–e7"

Kód UT WoS článku

000475582000021

EID výsledku v databázi Scopus

2-s2.0-85068466554