ArticleThoracic cancer2019
Comparative mitochondrial proteomic analysis of human large cell lung cancer cell lines with different metastasis potential.
Article in Thoracic cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Mitochondrial ribosomal proteins in metastasis and their potential use as prognostic and therapeutic targets.Cancer metastasis reviews · 2024Review
- Review
- Advances in the application of proteomics in lung cancer.Frontiers in oncology · 2022Review
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLung 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.
methodsMitochondrial 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.
resultsTwo 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.
conclusionOur 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.
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