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. 2016 May 24:6:26499.
doi: 10.1038/srep26499.

Quantitative Proteomics Analysis of Tissue Interstitial Fluid for Identification of Novel Serum Candidate Diagnostic Marker for Hepatocellular Carcinoma

Wei Sun  1 , Baocai Xing  2 , Lihai Guo  3 , Zhilei Liu  1   4 , Jinsong Mu  5 , Longqin Sun  1 , Handong Wei  1 , Xiaohang Zhao  6 , Xiaohong Qian  1 , Ying Jiang  1 , Fuchu He  1   7
Affiliations

Quantitative Proteomics Analysis of Tissue Interstitial Fluid for Identification of Novel Serum Candidate Diagnostic Marker for Hepatocellular Carcinoma

Wei Sun et al. Sci Rep. .

Abstract

Hepatocellular carcinoma (HCC) is the fifth most common malignant cancer in the world. The sensitivity of alpha-fetoprotein (AFP) is still inadequate for HCC diagnosis. Tissue interstitial fluid (TIF), as the liquid microenvironment of cancer cells, was used for biomarker discovery in this study. Paired tumor and nontumor TIF samples from 6 HBV-HCC patients were analyzed by a proteomic technique named iTRAQ (isobaric tag for relative and absolute quantitation). Totally, 241 up-regulated proteins (ratio ≥ 1.3, p < 0.05) and 288 down-regulated proteins (ratio ≤ -1.3, p < 0.05) in tumor TIF were identified. Interestingly, proteins in S100 family were found remarkably up-regulated in tumor TIF. One dramatically up-regulated protein S100A9 (ratio = 19) was further validated by ELISA in sera from liver cirrhosis (LC, HCC high risk population) and HCC patients (n = 47 for each group). The level of this protein was significantly elevated in HCC sera compared with LC (p < 0.0001). The area under the curve of this protein to distinguish HCC from LC was 0.83, with sensitivity of 91% (higher than AFP) and specificity of 66%. This result demonstrated the potential of S100A9 as a candidate HCC diagnostic biomarker. And TIF was a kind of promising material to identify candidate tumor biomarkers that could be detected in serum.

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Conflict of interest statement

The authors declare no competing financial interests.

Figures

Figure 1
Figure 1. Diagram for preparation and iTRAQ analysis of liver TIF samples from HCC tissues.
Figure 2
Figure 2. Proteins identified and differentially expressed in HCC TIFs.
(A) Proteins identified in HCC TIF and HPPP. (B) Volcano plot of differentially expressed proteins.
Figure 3
Figure 3
Significantly enriched (p < 0.05) Gene Ontology Terms in up-regulated (A) and down-regulated (B) proteins.
Figure 4
Figure 4. Western blot validated the up-regulation of S100A9 in HCC TIF samples.
(A) Western blot of 4 paired HCC TIF samples. (B) Expression ratios of S100A9 in 4 paired samples (repeated three times).
Figure 5
Figure 5. ELISA validation of serum S100A9 in LC and HCC patients.
(A) S100A9 concentration in LC and HCC sera. (B) ROC curve of S100A9 to distinguish LC and HCC patients. (C) S100A9 concentration in well differentiated (Edmondson grade I) and less differentiated (Edmondson grade II+III) HCC sera. (D) ROC curve of S100A9 to distinguish AFP negative (≤20 ng/ml) LC and HCC patients.
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