LC-MS Based Detection and Quantification of N-glycans in Human Serum Samples
Tsung-Heng Tsai¹, Minkun Wang¹, Cristina Di Poto¹, Yi Zhao¹, Yunli Hu², Shiyue Zhou², Yehia Mechref², Habtom W. Ressom¹
¹Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC; ²Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX
Objective
LC-MS Data Acquisition
The objective of this study is to identify candidate N-glycan biomarkers by
comparing the levels of permethylated N-glycans in sera of hepatocellular
carcinoma (HCC) patients with those of cirrhotic patients from two cohorts
(Egypt and US) using LC-MS.
•
•
Table III: List of candidate N-glycan biomarkers
Thermo Scientific LTQ Orbitrap Velos mass spectrometer coupled to the
Ultimate Dionex 3000 HPLC system (Nano LC 350 nL/min)
Five MS/MS scans per MS scan on positive mode
Hepatocellular Carcinoma
•
•
•
•
Cohort
Egypt
[4,3,2,0,0]
PNGase F Digestion
•
Structure
US
Solid-Phase Extraction
Human Serum
(10 𝝁l)
LC-MS/MS Data
Proteins &
Glycoproteins
Permethylated
N-Glycans
Proteins &
N-Glycans
Egypt
N-Glycans
[4,3,0,1,0]
Reduced
N-Glycans
Egypt
[4,3,0,0,0]
LC-MS/MS
Solid-Phase Permethylation
US
Reducing N-Glycans
LC-MS Data Preprocessing
Study Population
The participants in this study consist of 89 subjects (40 HCC cases and 49
cirrhotic controls) from Egypt (Table I) and 94 subjects (48 HCC cases and 46
cirrhotic controls) from the US (Table II).
Gender
HCV
Serology
HBV
Serology
Male (%)
MELD
AFP
HCC
Stage
53.2 (3.9)
53.8 (7.6) 0.3530
77.5%
67.3% 0.3474
HCV Ab (+)
HBsAg (+)
Mean (SD)
100.0%
100.0% 1.0000
0.0%
6.1% 0.2492
18.6 (7.7)
MELD ≤ 10
Median
(IQR)
Stage I
20.0%
275.9
(1244.3)
72.5%
Stage II
15.0%
Stage III
5.0%
Unknown
7.5%
HCC (N=48)
CIRR (N=46) p-value
60.2 (6.0)
58.9 (7.1) 0.3443
Age
Mean (SD)
Gender
Male (%)
77.1%
73.9% 0.8121
Caucasian
50.0%
63.0%
African
American
33.3%
26.1% 0.4566
Others
16.7%
10.9%
HCV
Serology
HCV Ab (+)
68.8%
41.3% 0.0033
HCV RNA (+)
62.5%
39.1% 0.0385
HBV
Serology
Anti-HBV (+)
45.8%
26.1% 0.0554
8.3%
2.2% 0.3619
Mean (SD)
11.3 (4.1)
17.3 (16.1) 0.0190
MELD ≤ 10
47.9%
10.9% 0.0042
38.8 (91.1)
4.5 (11.85) 0.0001
Ethnicity
(%)
18.9 (7.1) 0.1328
12.2% 0.3863
MELD
AFP
HBsAg (+)
Median (IQR)
Stage I
Stage II
HCC Stage
Stage III
Unknown
•
RT
Batch
FC
1032.549
2
31.6
E1
↓ 1.85
1032.549
2
32.2
E3
↓ 2.34
1032.552
2
32.1
E4
↓ 1.80
1032.547
2
29.9
U3
↓ 2.22
1032.547
2
29.9
U4
↓ 2.47
1829.979
1
25.8
E1
↓ 2.77
1829.985
1
25.7
E4
↓ 1.54
1847.006
1
25.8
E1
↓ 2.76
915.493
2
25.8
E1
↓ 2.50
915.497
2
25.7
E4
↓ 1.38
Re[M+H+NH4]2+
924.005
2
25.8
E1
↓ 2.75
Re[M+2NH4]2+
932.519
2
25.8
E1
↓ 2.61
Re[M+3H]3+
610.667
3
25.7
E4
↓ 1.44
836.961
2
23.6
E1
↓ 2.68
836.961
2
23.5
E3
↓ 1.75
Re[M+2H]2+
828.448
2
23.6
E1
↓ 2.17
Re[M+2H]2+
828.447
2
23.5
U4
↓ 3.84
1038.056
2
32.8
E1
↓ 2.74
1038.059
2
32.6
E4
↓ 1.69
Re[M+H+NH4]2+
1046.568
2
29.9
E1
↓ 2.49
Re[M+3H]3+
692.373
3
29.9
E1
↓ 2.46
Re[M+2H]2+
1038.055
2
27.7
U3
↓ 1.34
Re[M+2H]2+
1038.055
2
48.6
U4
↓ 2.19
1233.648
2
31.8
E1
↓ 2.41
1233.652
2
31.6
E4
↓ 1.76
1242.164
2
31.6
E4
↓ 1.52
822.769
3
31.8
E1
↓ 2.27
822.771
3
31.6
E4
↓ 1.74
1233.646
2
29.2
U3
↓ 2.21
1233.646
2
29.1
U4
↓ 2.67
822.768
3
29.2
U3
↓ 2.28
822.768
3
29.1
U4
↓ 2.56
1885.965
2
34.0
U2
↓ 2.06
1885.967
2
33.9
U3
↓ 1.28
1885.966
2
33.8
U4
↓ 1.33
1026.054
2
25.5
U1
↑ 1.58
1034.567
2
25.5
U1
↑ 1.65
1034.567
2
25.4
U4
↑ 1.89
Re[M+2H]2+
Re[M+2H]2+
•
•
Deisotoping (DeconTools) [Jaitly et al., BMC Bioinformatics 2009]:
RAW data → Ion list
Peak detection (In-house algorithm): Ion list → Peak list
(1) Find the ion (deisotoped) with highest intensity
(2) Record its mass (𝑚), scan number and charge
(3) Based on the desired precision, define the mass range [𝑚−∆𝑚, 𝑚+∆𝑚]
(4) Link ions within the mass range in adjacent scans
Peak matching (SIMA) [Voss et al., Bioinformatics 2011]:
Peak list → consensus list
Each cohort analyzed in four batches (n≈24): E1/E2/E3/E4 in the Egyptian
cohort; U1/U2/U3/U4 in the US cohort.
Balanced assignment of cases (HCC) and controls (CIRR) into each batch in
terms of age, race, gender, smoking, alcohol, and BMI.
Re[M+2H]2+
Re[M+H+NH4]2+
Re[M+2H]2+
[5,3,0,1,0]
US
Statistical Analysis
Re[M+2H]2+
Egypt
Pre-processed LC-MS data
Re[M+2H]2+
US
Log-transformation
Re[M+3H]3+
Δm/z: 20 ppm
Δrt: 50 s
Wilcoxon test
on each batch
t-test on
each batch
US
Re[M+H+NH4]2+
US
[4,3,1,1,0]
Group comparison within
each batch
Δm/z: 20 ppm
Δrt: 50 s
FC same direction
Overlapping between batches
p-value < 0.05/4
FC same direction
Re[M+2H]2+
[5,3,3,1,3]
ANOVA test on common
peaks among 4 batches
p-value < 0.05
Significant peaks
in each batch
Re[M+H+NH4]2+
Re[M+3H]3+
[5,3,1,0,1]
54.2%
22.9%
6.3%
16.7%
Study Design
•
•
Table II: Characteristics of the US cohort
HCC (N=40) CIRR (N=49) p-value
Mean(SD)
z
Re[M+H]+
Egypt
Age
m/z
Re[M+NH4]+
Hepatocellular carcinoma (HCC) is a significant worldwide health problem
with as many as 600,000 new cases diagnosed each year.
Primary liver cancer is the fifth most common cancer worldwide and the
third most common cause of cancer mortality.
Patients with cirrhosis have an annual risk of 1-2% for developing HCC.
Malignant conversion of cirrhosis to HCC is often diagnosed at a late stage.
Glycoproteins as new HCC markers include AFP-L3, GP73, etc.
Table I: Characteristics of the Egyptian cohort
Adduct
Re[M+2NH4]2+
Literature
• [Goldman et al., Clin Cancer Res 2009]
• [Liu et al., Hepatology 2007]
• [Tanabe et al., Biochem Biophys Res
Commun 2008]
• [Liu et al., 2007]
• [Tanabe et al., 2008]
• [Tanabe et al., 2008]
• [Liu et al., 2007]
• [Tanabe et al., 2008]
• [Goldman et al., 2009]
• [Ressom et al., J Proteome Res 2008]
• [Tang et al., J Proteome Res 2010]
•
•
•
•
[Liu et al., 2007]
[Ressom et al. 2008]
[Tanabe et al., 2008]
[Tang et al., 2010]
Summary
•
•
Overlapping between batches
Permethylation of glycans enzymatically removed from serum proteins
allows relative quantification of hundreds of oligosaccharides .
The proposed workflow design allows identification of reliable
candidate biomarkers for HCC.
Future Work
Candidate N-Glycan Biomarkers
•
•
•
14 candidate markers are identified with putative structure.
Seven of them were previously reported in the literature (Table III).
A preliminary stratified analysis on the US cohort revealed the
presence of four markers specific to Caucasians, six to African
Americans and an additional one to both races.
•
•
•
•
Clustering of related ions with different charge states and adduct types
Stratified analysis to evaluate the effect of age, gender, race, viral
infection, alcoholic cirrhosis, etc.
Multivariate analysis to identify a panel of biomarkers
Quantitation of candidates from this study by SRM on TSQ Vantage
Acknowledgements
This work was supported by NIH Grants R01CA143420 and R01GM086746.