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Integrative proteomics and tissue microarray profiling indicate the association between overexpressed serum proteins and non-small cell lung cancer.

Liu Y, Luo X, Hu H, Wang R, Sun Y, Zeng R, Chen H - PLoS ONE (2012)

Bottom Line: This serum proteomic dataset allowed us to discern the differential patterns and abnormal biological processes in the lung cancer blood.Of these proteins, Alpha-1B-glycoprotein (A1BG) and Leucine-rich alpha-2-glycoprotein (LRG1), two plasma glycoproteins with previously unknown function were selected as examples for which TMA and MRM verification were performed in a large sample set consisting about 100 patients.We revealed that A1BG and LRG1 were overexpressed in both the blood level and tumor sections, which can be referred to separate lung cancer patients from healthy cases.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Systems Biology, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Science, Chinese Academy of Sciences, Shanghai, China.

ABSTRACT
Lung cancer is the leading cause of cancer deaths worldwide. Clinically, the treatment of non-small cell lung cancer (NSCLC) can be improved by the early detection and risk screening among population. To meet this need, here we describe the application of extensive peptide level fractionation coupled with label free quantitative proteomics for the discovery of potential serum biomarkers for lung cancer, and the usage of Tissue microarray analysis (TMA) and Multiple reaction monitoring (MRM) assays for the following up validations in the verification phase. Using these state-of-art, currently available clinical proteomic approaches, in the discovery phase we confidently identified 647 serum proteins, and 101 proteins showed a statistically significant association with NSCLC in our 18 discovery samples. This serum proteomic dataset allowed us to discern the differential patterns and abnormal biological processes in the lung cancer blood. Of these proteins, Alpha-1B-glycoprotein (A1BG) and Leucine-rich alpha-2-glycoprotein (LRG1), two plasma glycoproteins with previously unknown function were selected as examples for which TMA and MRM verification were performed in a large sample set consisting about 100 patients. We revealed that A1BG and LRG1 were overexpressed in both the blood level and tumor sections, which can be referred to separate lung cancer patients from healthy cases.

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Related in: MedlinePlus

HCA and PCA of total serum proteomic data between samples.(A) Hierarchical clustering analysis and (B) Principal component analysis of all the 647 proteins quantified across the 18 serum samples. Ends of red arrows in (B) represent the PCA results for each protein.
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pone-0051748-g002: HCA and PCA of total serum proteomic data between samples.(A) Hierarchical clustering analysis and (B) Principal component analysis of all the 647 proteins quantified across the 18 serum samples. Ends of red arrows in (B) represent the PCA results for each protein.

Mentions: To establish a NSCLC associated serum proteome, we started with performing Hierarchical clustering analysis (HCA) and Principal component analysis (PCA) on the total proteome to address that, if substantial serum proteins were regulated due to NSCLC occurrence. HCA and PCA were both performed on the spectral counting information of all 647 serum proteins (see method). The HCA implied that NSCLC and normal subjects were incorporated into two big clusters (Figure 2A). Similarly, in PCA analysis, NSCLC sera could be separated from 5 normal controls by only one principal component, and the variation in the cancer group was much more than that in the normal group (Figure 2B). Because the MS analysis of control cases were inserted randomly into the sequencing runs of 13 NSCLC sera, the pre-analytical factors should be uncertain and less significant than the cancer phenotype. Though the relative positions of every NSCLC case in HCA and PCA were not the same, we observed moderate divergence between AD and SCC patients. To answer if the separation between cohorts was coming from only one or two significantly changed abundant proteins, we also employed PCA for all the protein identities (see the red arrows in Figure 2B). This “bi-plot” suggested that sizeable proteins, rather than a small number of proteins, contributed to the separation.


Integrative proteomics and tissue microarray profiling indicate the association between overexpressed serum proteins and non-small cell lung cancer.

Liu Y, Luo X, Hu H, Wang R, Sun Y, Zeng R, Chen H - PLoS ONE (2012)

HCA and PCA of total serum proteomic data between samples.(A) Hierarchical clustering analysis and (B) Principal component analysis of all the 647 proteins quantified across the 18 serum samples. Ends of red arrows in (B) represent the PCA results for each protein.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3526638&req=5

pone-0051748-g002: HCA and PCA of total serum proteomic data between samples.(A) Hierarchical clustering analysis and (B) Principal component analysis of all the 647 proteins quantified across the 18 serum samples. Ends of red arrows in (B) represent the PCA results for each protein.
Mentions: To establish a NSCLC associated serum proteome, we started with performing Hierarchical clustering analysis (HCA) and Principal component analysis (PCA) on the total proteome to address that, if substantial serum proteins were regulated due to NSCLC occurrence. HCA and PCA were both performed on the spectral counting information of all 647 serum proteins (see method). The HCA implied that NSCLC and normal subjects were incorporated into two big clusters (Figure 2A). Similarly, in PCA analysis, NSCLC sera could be separated from 5 normal controls by only one principal component, and the variation in the cancer group was much more than that in the normal group (Figure 2B). Because the MS analysis of control cases were inserted randomly into the sequencing runs of 13 NSCLC sera, the pre-analytical factors should be uncertain and less significant than the cancer phenotype. Though the relative positions of every NSCLC case in HCA and PCA were not the same, we observed moderate divergence between AD and SCC patients. To answer if the separation between cohorts was coming from only one or two significantly changed abundant proteins, we also employed PCA for all the protein identities (see the red arrows in Figure 2B). This “bi-plot” suggested that sizeable proteins, rather than a small number of proteins, contributed to the separation.

Bottom Line: This serum proteomic dataset allowed us to discern the differential patterns and abnormal biological processes in the lung cancer blood.Of these proteins, Alpha-1B-glycoprotein (A1BG) and Leucine-rich alpha-2-glycoprotein (LRG1), two plasma glycoproteins with previously unknown function were selected as examples for which TMA and MRM verification were performed in a large sample set consisting about 100 patients.We revealed that A1BG and LRG1 were overexpressed in both the blood level and tumor sections, which can be referred to separate lung cancer patients from healthy cases.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Systems Biology, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Science, Chinese Academy of Sciences, Shanghai, China.

ABSTRACT
Lung cancer is the leading cause of cancer deaths worldwide. Clinically, the treatment of non-small cell lung cancer (NSCLC) can be improved by the early detection and risk screening among population. To meet this need, here we describe the application of extensive peptide level fractionation coupled with label free quantitative proteomics for the discovery of potential serum biomarkers for lung cancer, and the usage of Tissue microarray analysis (TMA) and Multiple reaction monitoring (MRM) assays for the following up validations in the verification phase. Using these state-of-art, currently available clinical proteomic approaches, in the discovery phase we confidently identified 647 serum proteins, and 101 proteins showed a statistically significant association with NSCLC in our 18 discovery samples. This serum proteomic dataset allowed us to discern the differential patterns and abnormal biological processes in the lung cancer blood. Of these proteins, Alpha-1B-glycoprotein (A1BG) and Leucine-rich alpha-2-glycoprotein (LRG1), two plasma glycoproteins with previously unknown function were selected as examples for which TMA and MRM verification were performed in a large sample set consisting about 100 patients. We revealed that A1BG and LRG1 were overexpressed in both the blood level and tumor sections, which can be referred to separate lung cancer patients from healthy cases.

Show MeSH
Related in: MedlinePlus