Abstract
Objective: To analyze the expression protein profiles of lung squamous cell carcinoma (SQCC) with shot gun proteomics and bioinformatics technique and to screen SQCC biomarkers in order to provide valuable clues for pathogenesis, early diagnosis and treatment of SQCC. Methods: Tumor cells were isolated and purified with laser capture microdissection (LCM) from 6 cases of fresh tissues of lung SQCC after operatoin and the total solution proteins were extracted. Proteins were identified by multiple-dimension liquid chromatography (MDLC) and ion trap tandem mass spectrum technology (shot gun proteomics). Biomarkers were screened based on prediction of the physio-chemical properties, molecular function, biological pathway and interaction of the expressoin proteins using bioinformatics technique. Results: A total of 60 LCM caps were collected and about 12 000 cells were harvested from every LCM cap. Altogether 860 non-redundant proteins were identified using shot gun proteomics technique. The physio-chemical properties, including molecular weight (MW), point of isoelectricity (PI), grand average of hydropathy (GRAVY), trans-membrane helices (TMH), subcellular location, posttranscription modification (PTM) and tissue distribution were analyzed using online bioinformatics tools and were further demonstrated through statistical graph. Biological function was analyzed by using gene ontology (GO) software and kyoto encyclopedia of genes and genomes (KEGG) biological pathway. Three valuable proteins, namely, mitogen-activated protein kinase (MAPK), annexin A1 (ANXA1) and high mobility group protein B1 (HMGPB1) were screened as candidate biomarkers for lung SQCC according to functoin annotatoin. Conclusion: Shot gun proteomics can globally isolate and identify the expression protein of tumor cell. The screened biomarker proteins based on bioinformatics technique may become a molecular target point of diagnosis and treatment of lung cancer.
| Original language | English |
|---|---|
| Pages (from-to) | 10-16+27 |
| Journal | Journal of Xi'an Jiaotong University (Medical Sciences) |
| Volume | 32 |
| Issue number | 1 |
| State | Published - Jan 2011 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- ANXA1
- Bioinformatics
- Biomarker protien
- HMGPB1
- Lung squamous cell carcinoma
- MAPK
- Shot gun proteomics
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