Proteomics

Dataset Information

0

Deciphering Tissue-based Proteome Signatures Revealed Novel Subtyping and Prognostic Markers for Thymic Epithelial Tumors


ABSTRACT: Thymic epithelial tumors (TETs) belong to a group of tumors that rarely occur, but have unresolved mechanisms and heterogeneous clinical behaviors. Current care of TET patients demands biomarkers of high sensitivity and specificity for accurate histological classification and prognosis management. In this study, 90 fresh-frozen tissue samples were recruited to generate a quantitative and systematic view of proteomic landscape of TETs by data independent acquisition mass spectrometry (DIA-MS) leading to discovery of novel classifying molecules among different TET subtypes.

INSTRUMENT(S): Orbitrap Fusion

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Thymic Epithelium

SUBMITTER: Chen Meng  

LAB HEAD: Prof. Wei Yan

PROVIDER: PXD016498 | Pride | 2020-10-26

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
20160820_THYMOMA_DDA_03_01.raw Raw
20160820_THYMOMA_DDA_04_02.raw Raw
20160820_THYMOMA_DDA_17_01.raw Raw
20160820_THYMOMA_DDA_18_01.raw Raw
20160820_THYMOMA_DDA_33_02.raw Raw
Items per page:
1 - 5 of 106
altmetric image

Publications

Deciphering tissue-based proteome signatures revealed novel subtyping and prognostic markers for thymic epithelial tumors.

Ku Xin X   Sun Qiangling Q   Zhu Lei L   Gu Zhitao Z   Han Yuchen Y   Xu Ning N   Meng Chen C   Yang Xiaohua X   Yan Wei W   Fang Wentao W  

Molecular oncology 20200206 4


Thymic epithelial tumors (TETs) belong to a group of tumors that rarely occur, but have unresolved mechanisms and heterogeneous clinical behaviors. Current care of TET patients demands biomarkers of high sensitivity and specificity for accurate histological classification and prognosis management. In this study, 134 fresh-frozen tissue samples (84 tumor, 40 tumor adjacent, and 10 normal thymus) were recruited to generate a quantitative and systematic view of proteomic landscape of TETs. Among th  ...[more]

Similar Datasets

2020-12-10 | GSE158997 | GEO
| S-EPMC7138395 | biostudies-literature
| PRJNA700868 | ENA
| PRJNA91153 | ENA
| S-EPMC6995214 | biostudies-literature
2016-04-06 | E-GEOD-79978 | biostudies-arrayexpress
2012-07-04 | E-GEOD-35809 | biostudies-arrayexpress
2018-11-21 | PXD011061 | Pride
2010-08-01 | E-MEXP-2335 | biostudies-arrayexpress
| EGAD00010002355 | EGA