Proteomics

Dataset Information

0

Organelle resolved proteomics reveals new chordoma cell surface markers required for proliferation and association with outcome


ABSTRACT: Here, we used a proteomics approach to identify novel chordoma-specific cell-surface protein markers. Four established chordoma cell lines (U-CH17P, U-CH17M, U-CH17S and U-CH11R) were analyzed by quantitative proteomics using a comprehensive organellar fractionation approach based on differential ultracentrifugation. A subtractive proteomics strategy was applied to identify proteins that are plasma membrane enriched. The expression profiles of these cell-surface proteins were validated across chordoma cell lines, patient surgical tissue samples, and normal tissue lysates. The essentiality of these candidates was evaluated using chordoma cell line growth in vitro.

INSTRUMENT(S): Orbitrap Fusion

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Dr. Thomas Kislinger  

PROVIDER: MSV000089171 | MassIVE | Thu Mar 31 06:25:00 BST 2022

REPOSITORIES: MassIVE

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1
altmetric image

Publications

Organelle resolved proteomics uncovers PLA2R1 as a novel cell surface marker required for chordoma growth.

Khan Shahbaz S   Zuccato Jeffrey A JA   Ignatchenko Vladimir V   Singh Olivia O   Govindarajan Meinusha M   Waas Matthew M   Mejia-Guerrero Salvador S   Gao Andrew A   Zadeh Gelareh G   Kislinger Thomas T  

Acta neuropathologica communications 20240307 1


Chordomas are clinically aggressive tumors with a high rate of disease progression despite maximal therapy. Given the limited therapeutic options available, there remains an urgent need for the development of novel therapies to improve clinical outcomes. Cell surface proteins are attractive therapeutic targets yet are challenging to profile with common methods. Four chordoma cell lines were analyzed by quantitative proteomics using a differential ultracentrifugation organellar fractionation appr  ...[more]

Similar Datasets

2015-07-22 | PXD001988 | Pride
2021-08-02 | GSE181277 | GEO
2022-11-28 | MSV000090794 | MassIVE
2018-03-21 | MSV000082189 | GNPS
2018-11-30 | GSE123140 | GEO
2018-12-01 | GSE123207 | GEO
2014-12-08 | E-GEOD-63940 | biostudies-arrayexpress
2011-02-16 | E-GEOD-27331 | biostudies-arrayexpress
2023-09-25 | PXD038271 | Pride
2002-12-22 | E-GEOD-92 | biostudies-arrayexpress