Novel Biomarker Candidates to Predict Hepatic Fibrosis in Hepatitis C Identified by Serum Proteomics

[Guest guest]

http://www.springerlink.com/content/v0763q6158h2126n/

Digestive Diseases and Sciences

DOI: 10.1007/s10620-011-1745-4Online First™

Original Article

Novel Biomarker Candidates to Predict Hepatic Fibrosis in Hepatitis C Identified

by Serum Proteomics

Libang Yang, D. Rudser, LeeAnn Higgins, Hugo R. Rosen, Atif Zaman,

L. Corless, Larry and Glenn R. Gourley

Abstract

Background

Liver biopsy remains the gold standard to assess hepatic fibrosis. It is

desirable to predict hepatic fibrosis without the need for invasive liver

biopsy. Proteomic techniques allow unbiased assessment of proteins and might be

useful to identify proteins related to hepatic fibrosis.

Aims

We utilized two different proteomic methods to identify serum proteins as

candidate biomarkers to predict hepatic fibrosis stage in patients with chronic

hepatitis C virus (HCV) infection.

Methods

Serum was obtained from 24 people with chronic HCV at time of liver biopsy and

from 6 normals. Liver biopsy fibrosis was staged 1–4 (Batts–Ludwig). Pooled

serum samples (six in each of four fibrosis groups and controls) were analyzed

with 4- and 8-plex isobaric tags for relative and absolute quantitation (iTRAQ),

determining protein identification (ID) and ratios of relative protein

abundance. Nonpooled samples were analyzed with two-dimensional (2-D) gels and

difference in gel electrophoresis (DIGE) comparing different samples on the same

gel and across gels. Spots varying among groups were measured with densitometry,

excised, digested, and submitted for tandem mass spectrometry (MS/MS) protein

ID.

Results

iTRAQ identified 305 proteins (minimum 99% ID confidence); 66 were increased or

decreased compared with controls. Some proteins were increased or decreased for

specific fibrosis scores. From 704 DIGE protein spots, 66 were chosen, 41

excised, and 135 proteins identified, since one gel spot often identified more

than one protein.

Conclusions

Both proteomic methods identified two proteins as biomarker candidates for

predicting hepatic fibrosis: complement C4-A and inter-alpha-trypsin inhibitor

heavy chain H4.

[Guest guest]

http://www.springerlink.com/content/v0763q6158h2126n/

Digestive Diseases and Sciences

DOI: 10.1007/s10620-011-1745-4Online First™

Original Article

Novel Biomarker Candidates to Predict Hepatic Fibrosis in Hepatitis C Identified

by Serum Proteomics

Libang Yang, D. Rudser, LeeAnn Higgins, Hugo R. Rosen, Atif Zaman,

L. Corless, Larry and Glenn R. Gourley

Abstract

Background

Liver biopsy remains the gold standard to assess hepatic fibrosis. It is

desirable to predict hepatic fibrosis without the need for invasive liver

biopsy. Proteomic techniques allow unbiased assessment of proteins and might be

useful to identify proteins related to hepatic fibrosis.

Aims

We utilized two different proteomic methods to identify serum proteins as

candidate biomarkers to predict hepatic fibrosis stage in patients with chronic

hepatitis C virus (HCV) infection.

Methods

Serum was obtained from 24 people with chronic HCV at time of liver biopsy and

from 6 normals. Liver biopsy fibrosis was staged 1–4 (Batts–Ludwig). Pooled

serum samples (six in each of four fibrosis groups and controls) were analyzed

with 4- and 8-plex isobaric tags for relative and absolute quantitation (iTRAQ),

determining protein identification (ID) and ratios of relative protein

abundance. Nonpooled samples were analyzed with two-dimensional (2-D) gels and

difference in gel electrophoresis (DIGE) comparing different samples on the same

gel and across gels. Spots varying among groups were measured with densitometry,

excised, digested, and submitted for tandem mass spectrometry (MS/MS) protein

ID.

Results

iTRAQ identified 305 proteins (minimum 99% ID confidence); 66 were increased or

decreased compared with controls. Some proteins were increased or decreased for

specific fibrosis scores. From 704 DIGE protein spots, 66 were chosen, 41

excised, and 135 proteins identified, since one gel spot often identified more

than one protein.

Conclusions

Both proteomic methods identified two proteins as biomarker candidates for

predicting hepatic fibrosis: complement C4-A and inter-alpha-trypsin inhibitor

heavy chain H4.

[Guest guest]

http://www.springerlink.com/content/v0763q6158h2126n/

Digestive Diseases and Sciences

DOI: 10.1007/s10620-011-1745-4Online First™

Original Article

Novel Biomarker Candidates to Predict Hepatic Fibrosis in Hepatitis C Identified

by Serum Proteomics

Libang Yang, D. Rudser, LeeAnn Higgins, Hugo R. Rosen, Atif Zaman,

L. Corless, Larry and Glenn R. Gourley

Abstract

Background

Liver biopsy remains the gold standard to assess hepatic fibrosis. It is

desirable to predict hepatic fibrosis without the need for invasive liver

biopsy. Proteomic techniques allow unbiased assessment of proteins and might be

useful to identify proteins related to hepatic fibrosis.

Aims

We utilized two different proteomic methods to identify serum proteins as

candidate biomarkers to predict hepatic fibrosis stage in patients with chronic

hepatitis C virus (HCV) infection.

Methods

Serum was obtained from 24 people with chronic HCV at time of liver biopsy and

from 6 normals. Liver biopsy fibrosis was staged 1–4 (Batts–Ludwig). Pooled

serum samples (six in each of four fibrosis groups and controls) were analyzed

with 4- and 8-plex isobaric tags for relative and absolute quantitation (iTRAQ),

determining protein identification (ID) and ratios of relative protein

abundance. Nonpooled samples were analyzed with two-dimensional (2-D) gels and

difference in gel electrophoresis (DIGE) comparing different samples on the same

gel and across gels. Spots varying among groups were measured with densitometry,

excised, digested, and submitted for tandem mass spectrometry (MS/MS) protein

ID.

Results

iTRAQ identified 305 proteins (minimum 99% ID confidence); 66 were increased or

decreased compared with controls. Some proteins were increased or decreased for

specific fibrosis scores. From 704 DIGE protein spots, 66 were chosen, 41

excised, and 135 proteins identified, since one gel spot often identified more

than one protein.

Conclusions

Both proteomic methods identified two proteins as biomarker candidates for

predicting hepatic fibrosis: complement C4-A and inter-alpha-trypsin inhibitor

heavy chain H4.

[Guest guest]

http://www.springerlink.com/content/v0763q6158h2126n/

Digestive Diseases and Sciences

DOI: 10.1007/s10620-011-1745-4Online First™

Original Article

Novel Biomarker Candidates to Predict Hepatic Fibrosis in Hepatitis C Identified

by Serum Proteomics

Libang Yang, D. Rudser, LeeAnn Higgins, Hugo R. Rosen, Atif Zaman,

L. Corless, Larry and Glenn R. Gourley

Abstract

Background

Liver biopsy remains the gold standard to assess hepatic fibrosis. It is

desirable to predict hepatic fibrosis without the need for invasive liver

biopsy. Proteomic techniques allow unbiased assessment of proteins and might be

useful to identify proteins related to hepatic fibrosis.

Aims

We utilized two different proteomic methods to identify serum proteins as

candidate biomarkers to predict hepatic fibrosis stage in patients with chronic

hepatitis C virus (HCV) infection.

Methods

Serum was obtained from 24 people with chronic HCV at time of liver biopsy and

from 6 normals. Liver biopsy fibrosis was staged 1–4 (Batts–Ludwig). Pooled

serum samples (six in each of four fibrosis groups and controls) were analyzed

with 4- and 8-plex isobaric tags for relative and absolute quantitation (iTRAQ),

determining protein identification (ID) and ratios of relative protein

abundance. Nonpooled samples were analyzed with two-dimensional (2-D) gels and

difference in gel electrophoresis (DIGE) comparing different samples on the same

gel and across gels. Spots varying among groups were measured with densitometry,

excised, digested, and submitted for tandem mass spectrometry (MS/MS) protein

ID.

Results

iTRAQ identified 305 proteins (minimum 99% ID confidence); 66 were increased or

decreased compared with controls. Some proteins were increased or decreased for

specific fibrosis scores. From 704 DIGE protein spots, 66 were chosen, 41

excised, and 135 proteins identified, since one gel spot often identified more

than one protein.

Conclusions

Both proteomic methods identified two proteins as biomarker candidates for

predicting hepatic fibrosis: complement C4-A and inter-alpha-trypsin inhibitor

heavy chain H4.