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Comparative mitochondrial proteomic analysis of human large cell lung cancer cell lines with different metastasis potential.

Authors :
Liu, Zhenkun
Xu, Song
Li, Lu
Zhong, Xiaorong
Chen, Chun
Fan, Yaguang
Shen, Wang
Zu, Lingling
Xue, Feng
Wang, Min
Zhou, Qinghua
Source :
Thoracic Cancer. May2019, Vol. 10 Issue 5, p1111-1128. 18p.
Publication Year :
2019

Abstract

Background: Lung cancer is a highly aggressive cancer with a poor prognosis and is associated with distant metastasis; however, there are no clinically recognized biomarkers for the early diagnosis and prediction of lung cancer metastasis. We sought to identify the differential mitochondrial protein profiles and understand the molecular mechanisms governing lung cancer metastasis. Methods: Mitochondrial proteomic analysis was performed to screen and identify the differential mitochondrial protein profiles between human large cell lung cancer cell lines with high (L‐9981) and low (NL‐9980) metastatic potential by two‐dimensional differential gel electrophoresis. Western blot was used to validate the differential mitochondrial proteins from the two cells. Bioinformatic proteome analysis was performed using the Mascot search engine and messenger RNA expression of the 37 genes of the differential mitochondrial proteins were detected by real‐time PCR. Results: Two hundred and seventeen mitochondrial proteins were differentially expressed between L‐9981 and NL‐9980 cells (P < 0.05). Sixty‐four analyzed proteins were identified by matrix‐assisted laser desorption/ionization‐time of flight mass spectrometry coupled with database interrogation. Ontology analysis revealed that these proteins were mainly involved in the regulation of translation, amino acid metabolism, tricarboxylic acid cycle, cancer invasion and metastasis, oxidative phosphorylation, intracellular signaling pathway, cell cycle, and apoptosis. Conclusion: Our results suggest that the incorporation of more samples and new datasets will permit the definition of a collection of proteins as potential biomarkers for the prediction and diagnosis of lung cancer metastasis. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17597706
Volume :
10
Issue :
5
Database :
Academic Search Index
Journal :
Thoracic Cancer
Publication Type :
Academic Journal
Accession number :
136238725
Full Text :
https://doi.org/10.1111/1759-7714.13052