Dataset for quantitative phospho-proteomics analysis of a serial hepatoma cell lines with increasing invasion and metastasis potential

Xiaohua Xing; Hui Yuan; Ying Sun; Kun Ke; Xiuqing Dong; Hui Chen; Xiaolong Liu; Bixing Zhao; Aimin Huang

doi:10.1016/j.dib.2019.104634

Dataset for quantitative phospho-proteomics analysis of a serial hepatoma cell lines with increasing invasion and metastasis potential

Data Brief. 2019 Oct 14:27:104634. doi: 10.1016/j.dib.2019.104634. eCollection 2019 Dec.

Authors

Xiaohua Xing^{1

2}, Hui Yuan^{1

3}, Ying Sun¹, Kun Ke^{1

3}, Xiuqing Dong¹, Hui Chen³, Xiaolong Liu^{1

2}, Bixing Zhao¹, Aimin Huang²

Affiliations

¹ The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350025, People's Republic of China.
² The School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350004, People's Republic of China.
³ The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350007, People's Republic of China.

Abstract

Hepatoma is one of the most common malignant tumor, and most patients have very poor prognosis. Early prediction and intervention of the hepatoma recurrence/metastasis are the most effective way to improve the patients' clinical outcomes. Here, we used isobaric tags for relative and absolute quantitation (iTRAQ) based quantitative phospho-proteomics approach to identify biomarkers associated with hepatoma recurrence/metastasis in hepatoma cell lines with increasing metastasis ability. In total, 75 phosphorylated peptides corresponding to 60 phosphoproteins were significantly dysregulated. Bioinformatics analysis (GO, KEGG and IPA) allowed these data to be organized into distinct categories. These data represent the first in-depth proteomics analysis of a serial hepatoma cell lines with increasing invasion and metastasis potential. The data are related to (Xing et al., 2019).

Keywords: ANXA2Tyr23; FLNASer2152; Hepatoma; Prognosis; Quantitative phospho-proteomics.