ArticleAmerican journal of translational research2014
Comparative membrane proteomic analysis between lung adenocarcinoma and normal tissue by iTRAQ labeling mass spectrometry.
Article in American journal of translational research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 17 citations in OpenAlex.
- Label-free Quantitative Proteomic Analysis of Cerebrospinal Fluid and Serum in Patients With Relapse-Remitting Multiple Sclerosis.Frontiers in genetics · 2022Article
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- ADFP promotes cell proliferation in lung adenocarcinoma via Akt phosphorylation.Journal of cellular and molecular medicine · 2021Article
- Co-Expression of Coxsackievirus/Adenovirus Receptors and Desmoglein 2 in Lung Adenocarcinoma: A Comprehensive Analysis of Bioinformatics and Tissue Microarrays.Journal of clinical medicine · 2020Article
- Article
- Expression profile and functional role of S100A14 in human cancer.Oncotarget · 2019Review
- Lung regeneration by multipotent stem cells residing at the bronchioalveolar-duct junction.Nature genetics · 2019Article
- DHX9 inhibits epithelial-mesenchymal transition in human lung adenocarcinoma cells by regulating STAT3.American journal of translational research · 2019Article
- Quantitative proteomic analysis of mitochondrial proteins differentially expressed between small cell lung cancer cells and normal human bronchial epithelial cells.Thoracic cancer · 2018Article
- Cell-surface marker discovery for lung cancer.Oncotarget · 2017Article
- Quantitative proteomics analysis of mitochondrial proteins in lung adenocarcinomas and normal lung tissue using iTRAQ and tandem mass spectrometry.American journal of translational research · 2017Article
- Differentially expressed proteins underlying childhood cortical dysplasia with epilepsy identified by iTRAQ proteomic profiling.PloS one · 2017Article
- Screening and Identification of APOC1 as a Novel Potential Biomarker for Differentiate ofFrontiers in microbiology · 2016Article
- Identification of adipophilin as a potential diagnostic tumor marker for lung adenocarcinoma.International journal of clinical and experimental medicine · 2014Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung adenocarcinoma, the most common type of lung cancer, has increased in recent years. Prognosis is still poor, and pathogenesis remains unclear. This study aimed to investigate the membrane protein profile differences between lung adenocarcinoma and normal tissue. Manual microdissection was used to isolate the target cells from tumor tissue and normal tissue. iTRAQ labeling combined with 2D-LC-MS/MS yielded a differential expression profile of membrane proteins. Bioinformatic analysis was performed using Gene Ontology, WEGO, PID, and KEGG. S100A14 protein was selectively verified by Western blotting. The relationship of S100A14 expression with clinicopathological features in lung cancer patients was evaluated using immunohistochemistry. As a result, 568 differential proteins were identified; 257 proteins were upregulated and 311 were downregulated. Of these proteins, 48% were found to be membrane bound or membrane associated. These proteins enable the physiological functions of binding, catalysis, molecular transduction, transport, and molecular structure. For these differential proteins, 35 pathways were significantly enriched through the Pathway Interaction Database, whereas 19 pathways were enriched via KEGG. The overexpression and cellular distribution of S100A14 in lung cancer were confirmed. We found that upregulation of S100A14 was associated with well or moderate differentiation. The iTRAQ-coupled 2D-LC-MS/MS technique is a potential method for comparing membrane protein profiles between tumor and normal tissue. Such analysis may also help in identifying novel biomarkers and the mechanisms underlying carcinogenesis.
Indexed as
Identifiers
24936219PMC4058308W251778098What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.