Diagnostic value of 5 serum biomarkers for hepatocellular

Cancer Biol Med 2021. doi: 10.20892/j.issn.2095-3941.2020.0207

ORIGINAL ARTICLE

Diagnostic value of 5 serum biomarkers for hepatocellular carcinoma with different epidemiological backgrounds: A large-scale, retrospective study

Dongming Liu1*, Yi Luo2*, Lu Chen1*, Liwei Chen2, Duo Zuo3, Yueguo Li3, Xiaofang Zhang4, Jing Wu5, Qing Xi2, Guangtao Li2, Lisha Qi6, Xiaofen Yue7, Xiehua Zhang8, Zhuoyu Sun9, Ning Zhang10, Tianqiang Song1, Wei Lu1, Hua Guo2

1Department of Hepatobiliary, Liver Cancer Research Center for Prevention and Therapy; 2Department of Tumor Cell Biology; 3Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China; 4Medical Laboratory, Tianjin Medical University General Hospital, Tianjin 300052, China; 5Clinical Laboratory, Tianjin Third Central Hospital, Tianjin 300170, China; 6Department of Pathology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China; 7Department of Tianjin Research Institute of Liver Diseases, Tianjin Second People’s Hospital, Tianjin 300192, China; 8Department of Infectious Diseases, The First Affiliated Hospital of Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou 014010, China; 9Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China; 10The Center for Translational Cancer Research, Peking University First Hospital, Beijing 100034, China

ABSTRACT Objective: Hepatocellular carcinoma (HCC) is a lethal global disease that requires an accurate diagnosis. We assessed the potential of

5 serum biomarkers (AFP, AFU, GGT-II, GPC3, and HGF) in the diagnosis of HCC.

Methods: In this retrospective study, we measured the serum levels of each biomarker using ELISAs in 921 participants, including

298 patients with HCC, 154 patients with chronic hepatitis (CH), 122 patients with liver cirrhosis (LC), and 347 healthy controls

from 3 hospitals. Patients negative for hepatitis B surface antigen and hepatitis C antibody (called “NBNC-HCC”) and patients

positive for the above indices (called “HBV-HCC and HCV-HCC”) were enrolled. The selected diagnostic model was constructed

using a training cohort (n = 468), and a validation cohort (n = 453) was used to validate our results. Receiver operating characteristic

analysis was used to evaluate the diagnostic accuracy.

Results: The α-L-fucosidase (AFU)/α-fetoprotein (AFP) combination was best able to distinguish NBNC-HCC [area under the

curve: 0.986 (95% confidence interval: 0.958–0.997), sensitivity: 92.6%, specificity: 98.9%] from healthy controls in the test cohort.

For screening populations at risk of developing HCC (CH and LC), the AFP/AFU combination improved the diagnostic specificity

for early-stage HCC [area under the curve: 0.776 (0.712–0.831), sensitivity: 52.5%, specificity: 91.6% in the test group]. In all-stage

HBV-HCC and HCV-HCC, AFU was also the best candidate biomarker combined with AFP [area under the curve: 0.835 (0.784–

0.877), sensitivity 69.1%, specificity: 87.4% in the test group]. All results were verified in the validation group.

Conclusions: The AFP/AFU combination could be used to identify NBNC-HCC from healthy controls and hepatitis-related HCC

from at-risk patients.

KEYWORDS Hepatocellular carcinoma; serum; biomarker; AFP; AFU

Introduction

Hepatocellular carcinoma (HCC) is the third leading cause of

cancer death worldwide, accounting for more than 600,000

deaths each year1-3. The prognoses of HCC patients are gen-

erally poor, and the median survival of patients is only 6–20

months4,5. The main reason for the poor prognosis of HCC is

the lack of a timely and accurate diagnosis6,7. Thus, according

*These authors contributed equally to this work.Correspondence to: Hua Guo, Wei Lu, Tianqiang SongE-mail: [email protected], [email protected], [email protected] ID: https://orcid.org/0000-0002-3345-8005, https://orcid.org/0000-0001-9467-3780, https://orcid.org/0000-0001-6465-4300Received May 04, 2020; accepted October 13, 2020.Available at www.cancerbiomed.org©2021 Cancer Biology & Medicine. Creative Commons Attribution-NonCommercial 4.0 International License

mailto:[email protected]



https://orcid.org/0000-0002-3345-8005,

https://orcid.org/0000-0001-9467-3780,

https://orcid.org/0000-0001-6465-4300

https://orcid.org/0000-0001-6465-4300

http://www.cancerbiomed.org

Cancer Biol Med Vol 18, No 1 February 2021 257

to the epidemiological characteristics of HCC, we divided our

research protocol into the diagnoses of NBNC-HCC patients

(patients who are negative for hepatitis B surface antigen and

hepatitis C antibody)8 and the diagnosis of hepatitis (such

as HBV or HCV)-related HCC patients9,10. Although hepati-

tis-related HCC accounts for the greatest percentage of HCC

patients in China, the percentage of NBNC-HCC patients is

rapidly increasing8,11. Thus, we recruited this type of HCC

patient. We also enrolled patients with a history of alco-

hol use, aflatoxin exposure, or nonalcoholic steatohepatitis

as the “healthy controls,” when compared with the NBNC-

HCC patients. This study was conducted because it is critical

to develop novel assays to identify NBNC-HCC patients, to

increase the likelihood of effective treatments.

When diagnosed at an early stage, HCC can be treated with

surgery, transplantation, or radiofrequency ablation, which

results in a 5-year survival of 40%–70%12, whereas the lack of

effective treatments for patients diagnosed with mid- or late-

stage disease is associated with a dramatic decrease in survival.

Despite the low sensitivity, α-fetoprotein (AFP) is a unique

serum biomarker for HCC. Unfortunately, the level of AFP

may be elevated in patients with nonmalignant chronic liver

diseases, including approximately 40% of patients with hepa-

titis and 30% of patients with cirrhosis13. Thus, only approx-

imately 10%–40% of HCC patients are diagnosed at an early

stage using the current AFP-based procedures14. This limita-

tion restricts the early diagnoses of HBV-HCC and HCV-HCC

based on serum AFP levels.

Over the past several years, serum microRNA panels have

become a promising approach for diagnosing early-stage

HCC. These panels differentiate HCC patients from healthy

and at-risk controls, and provide prognostic values for HCC15.

However, these panels often require the accurate detection of

several serum miRNA levels, which may be complicated and

costly for HCC screening in large populations. Thus, use of

serum protein biomarkers is still a reliable and economic

approach for screening HCC in a large population. In the past

decade, many studies of serum biomarkers for detecting HCC

have been documented12,16-18. More studies have been focused

on HBV-HCC, with few studies associated with various etiol-

ogies, such as hepatitis C virus infection, alcohol-related liver

disease, or nonalcoholic steatohepatitis.

Numerous protein serum biomarkers have been suggested

for diagnosing HCC, including α-L-fucosidase (AFU), γ-glu-

tamyl transferase isoenzyme II (GGT-II), glypican-3 (GPC3),

and hepatocyte growth factor (HGF)19-22. AFU is a lysosomal

enzyme detected in most mammalian cells, and is related to

the degradation of fucose-containing fucoglycoconjugates23.

The expression of AFU was higher in HCC samples than in

healthy controls and in patients with chronic hepatic disease24.

GPC3 is a component of heparin sulfate proteoglycans25. It

is highly expressed in HCC cells and tissues26. Recent studies

reported that GPC3 was examined in HCC cells, but not in

benign liver tissues27. GGT-II acted as the second candidate

serum marker and was shown to have a higher sensitivity and

specificity for hepatoma patients. Surprisingly, it was almost

undetectable in other chronic liver diseases28. Cui et al.19

observed a lower sensitivity and specificity of GGT-II of 74%

and 82.2%, respectively. However, their findings still showed

GGT-II might be a promising supplemental biomarker for

HCC diagnosis. HGF is many times dysregulated, playing an

essential role in malignant tumors, including HCC29. Kim

et al.30 reported that the combination of serum bFGF and

HGF levels might be candidate biomarkers for HCC patients

who could benefit from sorafenib therapy. However, limi-

tations such as small sample sizes and single-center designs

have prevented their widespread application.

Herein, we evaluated the sensitivity and specificity of these

biomarkers in a large-scale, retrospective study to identify

a more accurate diagnostic method for NBNC-HCC and

hepatitis-related HCC screening in normal populations and

at-risk populations. Our results showed that the combination

of AFU and AFP protein biomarkers detected NBNC-HCC

in the normal population and in hepatitis-related HCC in

the at-risk population with stable and reliable cut-off values.

Moreover, the combination maintained diagnostic specificity

and improved the sensitivity for the detection of NBNC-HCC

and hepatitis-related HCC populations, when compared with

AFP alone.

Materials and methods

Ethical approval

Our experiments on human subjects were in accordance with

the ethical standards of the Helsinki Declaration (amended

in 2000) of the World Medical Association. In addition, this

study was approved by the Ethics Committees of Tianjin

Medical University Cancer Institute and Hospital (Approval

No. bc2020083). All patients were informed about the study,

and gave their consent for participation.

258 Liu et al. Serum biomarkers for HCC with different epidemiological backgrounds

Study design and patients

A total of 996 subjects who visited the Tianjin Medical University

Cancer Institute and Hospital, Tianjin Medical University

General Hospital or Tianjin Third Central Hospital between July

2012 and April 2014 were recruited in this study for different

cohorts (Supplementary Figure S1). Patients with HCC were

diagnosed based on ultrasound, computed tomography, or mag-

netic resonance imaging, and the diagnoses were confirmed his-

topathologically according to the AASLD guidelines. According

to different etiologies, we divided the HCC patients into the hep-

atitis-related HCC and NBNC-HCC groups. Tumor stage was

defined according to the Barcelona Clinic Liver Cancer (BCLC)

staging system. For the purpose of this study, we classified tum-

ors with BCLC stage 0 + A as early-stage hepatitis-related HCC

and patients who were suffering from chronic hepatitis or liver

cirrhosis as at-risk patients. None of the patients underwent any

treatment, including surgery, chemotherapy, or radiotherapy,

before blood sampling. The diagnosis of cirrhosis was confirmed

by liver biopsy and/or clinical, laboratory, and imaging evidence.

Chronic hepatitis was defined as chronic necroinflammatory

disease of the liver caused by persistent HBV or HCV infection.

Healthy controls were used for comparison with NBNC-HCC

patients. They were recruited from the Physical Examination

Center at Tianjin Medical University Cancer Institute and

Hospital, and were eligible if they had no viral hepatitis and no

malignant disease. Participants with a history of alcohol use, afla-

toxin exposure, or nonalcoholic steatohepatitis also met the cri-

teria for healthy controls. Patients were excluded for the follow-

ing reasons: (1) 27 patients had primary liver cancer other than

HCC, (2) 2 patients had metastatic liver cancer, (3) 11 patients

had liver sarcoma or adenocarcinoma, and (4) 35 patients did

not have available clinical data. Thus, 468 patients, including

150 HCC patients (123 hepatitis-related HCC patients and 27

NBNC-HCC patients), 82 chronic hepatitis (CH) patients, 61

liver cirrhosis (LC) patients, and 175 healthy controls (HC), were

recruited from the three hospitals as the test group between July

2012 and June 2013. When we finished the analysis of the test

group, 453 patients who were matched for age and sex with the

test group were recruited from the same hospitals as the valida-

tion group. The validation cohort was comprised of 121 hepati-

tis-related HCC patients, 72 CH patients, and 61 LC patients as

one subgroup and 27 NBNC-HCC patients and 172 HC patients

as another subgroup. The data involving 5 factors and demo-

graphic characteristics such as sex and age of patients are listed

in Supplementary Table S1–S5.

Statistical analysis

Statistical analyses were performed using SPSS statistical soft-

ware for Windows, version 25.0 (SPSS, Chicago, IL, USA) and

MedCalc, version 18.2.1 (https://www.medcalc.org/). Differences

between two independent groups were tested using the Mann-

Whitney U test (continuous variables and nonparametric anal-

yses). P values < 0.05 were considered to be significant, and all

P values were two-sided. To assess whether the combination of

AFU and AFP was better than either of them alone, a new varia-

ble predicted probability (P) for HCC was created on the basis of

an equation obtained by binary logistic regression:

(a). all-stage HBV-HCC and HCV-HCC vs. CH and LC in the test cohort: (P): 0.007668*AFP + 0.033718*AFU-1.347426

(b). all-stage HBV-HCC and HCV-HCC vs. CH and LC in the validation cohort(P): 0.001227*AFP + 0.017566*AFU-0.957458

(c). early-stage HBV-HCC and HCV-HCC vs. CH and LC in the test cohort(P): 0.005890*AFP + 0.018753*AFU-1.557863

(d). early-stage HBV-HCC and HCV-HCC vs. CH and LC in the validation cohort(P): 0.000921*AFP + 0.011742*AFU-1.166897

(e). NBNC-HCC vs. HC in the test cohort(P): 0.059672*AFP + 0.403175*AFU-8.669705

(f). NBNC-HCC vs. HC in the validation cohort(P): 0.047177*AFP + 0.211019*AFU-5.707287

Nomogram for the hepatitis-related HCC and NBNC-HCC populations

A nomogram was formulated based on the results of logistic

regression analyses and by using the rms package of R, ver-

sion 3.0 (http://www.r-project.org/). The nomogram was

based on proportionally converting each regression coefficient

in multivariate logistic regression to a total points scale. For

the diagnosis of HCC based on the model, the total score for

each participant was calculated with the nomogram. We could

preliminarily predict the likelihood of a participant suffering

from HCC based on the probability.

Blood samples

Blood samples were obtained by peripheral venous puncture

before any surgical or chemotherapeutic treatment. After clot-

ting and within 1 h of collection, the blood samples were cen-

trifuged at 3,000 × g for 5 min, and serum aliquots were stored

at –80 °C until analysis.

https://www.medcalc.org/

http://www.r-project.org/


Serum tumor marker detection

The AFP, AFU, GGT-II, GPC3, and HGF serum levels were

analyzed according to the manufacturer’s instructions using

ELISA kits (Cusabio, Wuhan, China and eBioscience, San

Diego, CA, USA). All assays were performed in duplicate.

Immunohistochemistry (IHC) staining

IHC staining was used to examine the expression levels of

AFU in paraffin-embedded samples of HCC tissues accord-

ing to previously described methods31. An anti-AFU (FUCA2)

antibody was purchased from Bioss (bs-16192R, 1:200; Bioss,

Woburn, MA, USA). The IHC score was used to evaluate the

correlation between AFU expression and overall survival (OS)

and disease-free survival (DFS) of HCC patients.

Bioinformatic analysis

Correlation between AFU or AFP/AFU combination expres-

sion and overall/DFS in HCC patients was based on the

Kaplan-Meier method (http://kmplot.com/analysis/). The

threshold of significance was set at P < 0.05.

Results

The serum levels of AFP, AFU, GPC3, GGT-II, and HGF in the test group

In the test cohort, all 463 patients were tested for serum

levels of AFP, AFU, GPC3, GGT-II, and HGF. The median

plasma levels of all 5 tumor markers were found to be sig-

nificantly higher in the NBNC-HCC subgroup than in the

healthy controls (Figure 1A–1E). In the HBV-HCC and

HCV-HCC subgroups, the levels of AFU, GPC3, and GGT-II

were significantly higher in the LC group than in the CH

group (Figure 1B–1D), suggesting that elevated levels of

these three biomarkers may be associated with the progres-

sion of hepatitis to liver cirrhosis. The HBV-HCC and HCV-

HCC patient median plasma levels of AFP, AFU, and HGF

were found to be significantly higher than those of the CH

and LC patients (Figure 1A, 1B, and 1E), indicating that a

high expression of these biomarkers was associated with the

progression of liver disease. Generally, a high level of these

3 candidate markers was associated with the onset of HBV-

HCC and HCV-HCC.

The combination of AFP and AFU had high accuracy in the detection of NBNC-HCC

The area under the curve (AUC) values of AFP, AFU, GPC3,

GGT-II, and HGF were 0.792, 0.967, 0.825, 0.824, and 0.759,

respectively (Figure 2A–2E). Each serum biomarker could

be a candidate serum biomarker combined with AFP in

diagnosing NBNC-HCC. Thus, we determined the different

values of the receiver operating characteristic (ROC) curve

with various combinations of serum biomarkers (AFP, AFU,

GPC3, GGT-II, and HGF). The 5 biomarker combinations

performed well (AUC: 0.989, sensitivity: 92.6%, specificity:

98.9%) (Figure 2F). The best 4/3/2 biomarker combinations

had a similar AUC, sensitivity, and specificity compared with

the 5 biomarker combination (AUC: 0.989, sensitivity: 92.6%,

specificity: 99.4%; AUC: 0.989, sensitivity: 92.6%, specific-

ity: 99.4%; AUC: 0.986, sensitivity: 92.6%, specificity: 98.9%,

respectively) (Figure 2G–2I). The combination results of the

remaining serum indicators are shown in Supplementary

Figure S2–S4. After combining various factors (such as AUC,

sensitivity, and specificity), we chose the combination of AFP

and AFU as the diagnostic combination for NBNC-HCC. The

predictive values and likelihood ratios for AFU and AFP in the

diagnosis of NBNC-HCC are shown in Table 1. The combi-

nation improved the sensitivity of AFP in diagnosing NBNC-

HCC, while the specificity was relatively unchanged.

According to the stable cutoff value of AFP and AFU in

detecting NBNC-HCC, we verified the results of the test

cohort in the validation cohort. First, the trends of AFP and

AFU concentrations in healthy controls and NBNC-HCC

patients were consistent with those in the test cohort (Figure

1F and 1G). Furthermore, the AUC, sensitivity, specificity, PPV

(positive predictive value), NPV (negative predictive value),

positive LR (likelihood ratio), and negative LR of AFP, AFU,

and their combinations were similar to those in the test cohort

at the optimum cut-off value (Supplementary Figure S5 and

Table 1). The AUC of the combination was better than any

other single biomarker (only AFP or AFU) of NBNC-HCC in

the test and validation groups (Figure 3A and 3B). We used a

nomogram model for the clinical application of these 2 serum

markers (Figure 3C). For example, if the AFP and AFU values

of a “healthy person” (including individuals with a history of

alcohol, aflatoxin exposure, or nonalcoholic steatohepatitis)

were 50 ng/mL and 20 mU/mL, respectively, then based on the

nomogram model, the probability of this participant develop-

ing NBNC-HCC was nearly 90%.

http://kmplot.com/analysis/


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Figure 1 The median plasma levels of AFP (A), AFU (B), GPC3 (C), GGT-II (D), and HGF (E) in the test cohort and AFP (F) and AFU (G) in the validation cohort. HC, healthy controls; CH, chronic hepatitis; LC, liver cirrhosis; HCC, hepatocellular carcinoma. *P < 0.05; **P < 0.01; ***P < 0.001; P > 0.05 means no significance (NS).


The combined AFP/AFU panel showed an improvement in the diagnostic sensitivity for the detection of all-stage and early-stage hepatitis-related HCC

The AUC values of AFP, AFU, GPC3, GGT-II, and HGF in the

all-stage HBV-HCC and HCV-HCC groups were 0.780, 0.752,

0.520, 0.547, and 0.735, respectively (Figure 4A–4E). Because

there was no significance between GGT-II and GPC3 in

detecting all-stage HBV-HCC and HCV-HCC, we chose AFP,

AFU, and HGF in a combination model (Figure 4F–4I). The

diagnostic performance of the serum biomarkers in different

subgroups was further evaluated. Among these combinations,

the AFP/AFU panel outperformed the others and exhibited a

0 0.2 0.4

AUC = 0.79295% CI (0.729–0.845)

AUC = 0.82495% CI (0.764–0.874)

AUC = 0.98995% CI (0.963–0.998)

AUC = 0.98995% CI (0.963–0.998)

AUC = 0.98695% CI (0.958–0.997)

AUC = 0.75995% CI (0.694–0.817)

AUC = 0.98995% CI (0.963–0.998)

AUC = 0.96795% CI (0.932–0.987)

AUC = 0.82595% CI (0.766–0.875)

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AFP + AFU

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AFP + AFU + HGF AFP + AFU + GPC3 + HGF

Figure 2 The receiver operating characteristic curve of AFP (A), AFU (B), GPC3 (C), GGT-II (D), HGF (E), AFP + AFU + GGT-II + GPC3 + HGF (F), AFP + AFU + GPC3 + HGF (G), AFP + AFU + HGF (H), and AFP + AFU (I) in the detection of the NBNC-HCC test group. The sensitivity and specificity represented by the red dots are shown in detail (lower). (A). AFP sensitivity: 59.3% and specificity: 98.9%; (B). AFU sensitivity: 85.2% and specificity: 98.9%; (C). GPC3 sensitivity: 100.0% and specificity: 72.6%; (D). GGT-II sensitivity: 92.6% and specificity: 58.3%; (E). HGF sensi-tivity: 51.9% and specificity: 88.6%; (F). AFP + AFU + GPC3 + GGT-II + HGF sensitivity: 92.6% and specificity: 98.9%; (G). AFP + AFU + GPC3 + HGF sensitivity: 92.6% and specificity: 99.4%; (H). AFP + AFU + HGF sensitivity: 92.6% and specificity: 99.4%; (I). AFP + AFU sensitivity: 92.6% and specificity: 98.9%.


greater diagnostic sensitivity and specificity for the differen-

tiation of all-stage HBV-HCC and HCV-HCC patients from

CH and LC patients [AUC: 0.835 (0.784–0.877), sensitivity:

69.1%, specificity: 87.4%] (Figure 4G). The diagnostic values

of serum AFP and AFU were 42.34 ng/mL and 13.94 mU/mL,

respectively. Regarding early stage HBV-HCC and HCV-HCC,

the AUC values of AFP, AFU, GPC3, GGT-II, and HGF were

0.741, 0.666, 0.517, 0.510, and 0.665, respectively (Figure

5A–5E). We observed similar results in this test cohort with

the all-stage HBV-HCC and HCV-HCC groups. AFP, AFU, and

HGF were selected for the combination model (Figure 5F–5I).

The AFP/AFU combination was also notable for early-stage

HBV-HCC and HCV-HCC [AUC: 0.776 (0.712–0.831), sen-

sitivity: 52.5%, specificity: 91.6%] in the test cohort (Figure

5G). In summary, the AFP/AFU panel improved the diagnos-

tic sensitivity without a loss of specificity in the detection of

all-stage HBV-HCC and HCV-HCC (Table 2: AFP vs. AFP +

AFU: sensitivity 52.8% vs. 69.1%, specificity 93.7% vs. 87.4%)

and early-stage HBV-HCC and HCV-HCC (Table 2: AFP vs.

AFP + AFU, sensitivity: 44.3% vs. 52.5%, specificity: 93.7% vs.

91.6%) among at-risk patients.

In the validation cohort, the concentrations of AFP and

AFU in CH-, LC-, and hepatitis-related HCC patients are

shown in Figure 1F and 1G. The results were similar to those

in the test cohort. The ROC curves of single serum markers

and combined serum markers in the validation group are

shown in Supplementary Figure S6 (the results for all-stage

HBV-HCC and HCV-HCC are shown in A, B, and E; the

results for early-stage HBV-HCC and HCV-HCC are shown

in C, D, and F). Compared with the optimum diagnostic cut-

off values of AFP and AFU for HBV-HCC and HCV-HCC in

the test group, the parameter values in the validation group

for all-stage and early-stage hepatitis-related HCC are sum-

marized in Table 2 [AUC: 0.841 (0.790–0.884), sensitivity:

71.9%, specificity: 86.5% in the validation cohort for all-stage

HBV-HCC and HCV-HCC; AUC: 0.791 (0.728–0.845), sensi-

tivity: 75.4%, specificity: 73.7% in the validation cohort for

early-stage HBV-HCC and HCV-HCC]. The AUC of the AFP/

AFU combination was better than any other single biomarker

(only AFP or AFU) of all-stage (Figure 6A and 6B) and

early-stage (Figure 6C and 6D) hepatitis-related HCC in the

test and validation groups. We also constructed a nomogram

model for the clinical application of these 2 serum markers in

HBV-HCC and HCV-HCC (Figure 6E). For example, if the

AFP and AFU values of an “at-risk person” (such as an indi-

vidual with HBV or HCV) were 60 ng/mL and 25 mU/mL, Tabl

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Neg

ativ

e P

AUC

Sen

sitiv

ity S

peci

ficity

PPV

NPV

Pos

itive

Neg

ativ

e P

(95%

CI)

(%

) (

%)

(%

) (

%)

LR

LR

val

ue(9

5% C

I) (

%)

(%

) (

%)

(%

) L

R

LR v

alue

NBN

C-H

CC v

s. H

C (re

sults

for m

easu

rem

ent o

f AFU

, AFP

, or b

oth

in th

e di

agno

sis

of N

BNC-

HCC

)

AFP

0.7

92 (0

.729

–0.8

45)

59.3

% 9

8.9%

88.

9% 9

4.0%

51.

85 0

.41

<0.

001

0.7

07 (0

.639

–0.7

69)

51.9

% 9

7.7%

77.

8% 9

2.8%

22.

25 0

.49

0.0

02

AFU

0.9

67 (0

.932

–0.9

87)

85.2

% 9

8.9%

92.

0% 9

7.7%

74.

54 0

.15

<0.

001

0.9

48 (0

.907

–0.9

74)

74.1

% 9

6.5%

76.

9% 9

6.0%

21.

23 0

.27

<0.

001

AFP

+ A

FU 0

.986

(0.9

58–0

.997

) 92

.6%

98.

9% 9

2.6%

98.

9% 8

1.02

0.0

75 <

0.00

1 0.

969

(0.9

34–0

.988

) 88

.9%

94.

8% 7

2.7%

98.

2% 1

6.99

0.1

2 <

0.00

1

The

diag

nost

ic c

utof

f val

ues

of s

erum

AFP

and

AFU

wer

e 43

.23

ng/m

L an

d 16

.75

mU

/mL,

resp

ectiv

ely.


respectively, then based on the nomogram model, the prob-

ability of this individual developing HBV-HCC and HCV-

HCC was nearly 75%.

Overall, the AFP/AFU panel improved the accuracy for

diagnosing all-stage and early-stage hepatitis-related HCC

compared to any other single marker. Moreover, the inclusion

of demographic characteristics assisted in the detection of

disease.

The AFP/AFU combination was effective in predicting the survival of HCC patients

We evaluated the AFU levels in predicting HCC patient prog-

noses based on a KM plotter database. The results showed that

patients with low expression of AFU might have better prog-

noses (Supplementary Figure S7A and B). Thus, we assessed

the value of the AFP/AFU combination in forecasting survival

of HCC patients. The 5-year overall/DFS of HCC patients

with low expression of the AFP/AFU combination was almost

60% and 40%, respectively, while the survival of patients with

high expression was approximately 40% and 25%, respec-

tively (Supplementary Figure S7C and D). Overall, the results

showed that the AFP/AFU combination was effective in pre-

dicting HCC prognosis.

We also verified the results of the KM plotter based on our

IHC data. First, we found that patients with high AFU levels

had worse prognoses (Supplementary Figure S7E and F). In

addition, the IHC results of the AFP/AFU combination in pre-

dicting HCC prognoses were consistent with those in the KM

plotter database (Supplementary Figure S7G and H). Thus,

the AFP and AFU panel was effective in predicting the survival

of HCC patients.

00

Points

AFP (ng/mL)

AFU (mU/mL)

Total points

Probability of HCC

0.2 0.4 0.6

1-specificity

0.001

0

0

0

0 10 20 30 40 50 60 70 80 90 100

20 40 60 80 100 120 140 160 180

5 10 15 20 25 30 ≥35

≥200

20 40 60 80 100 120 140 160 180 200

0.01 0.1 0.4 0.8 0.95 0.999

Nomogram-NBNC-HCC vs. HC

Sens

itivi

ty

Sens

itivi

ty

NBNC-HCC vs. HC (test) NBNC-HCC vs. HC (validation)

0.8 1.0 0 0.2 0.4 0.6

1-specificity

0.8 1.0

AFP + AFU

AFP

AFU

AFP + AFU

AFP

AFU

0.2

0.4

0.6

0.8

1.0

A

C

B

0

0.2

0.4

0.6

0.8

1.0

Figure 3 Diagnostic outcomes and nomograms for the combination of serum AFP and AFU in the diagnosis of NBNC-HCC. (A). Receiver operating characteristic curves (ROCs) for AFU, AFP, or both for all patients with NBNC-HCC vs. HC in the test cohort. (B). ROC curves for AFU, AFP, or both for all patients with NBNC-HCC vs. HC in the validation cohort. (C). Nomogram of the combined AFP/AFU in diagnosing NBNC-HCC.


Discussion

There is a consensus that early diagnosis is the key to improv-

ing the survival of HCC patients4. Several preliminary studies

have suggested that serum biomarkers, including AFP, AFU,

GGT-II, HGF, and GPC3, may be used for the diagnosis of

HCC19-22. However, these markers are not currently included

in routine clinical assessments because of the lack of large-

scale, multicenter clinical investigations.

Over the past 2 decades, infection with hepatitis B virus

(HBV) or hepatitis C virus (HCV) has been associated with

approximately 85% of worldwide HCC32. Due to the promotion

of antiviral therapy, the number of patients with other causes of

HCC (hepatitis B virus surface antigen-negative and hepatitis

0 0.2 0.4

AUC = 0.78095% CI (0.725–0.828)

AUC = 0.54795% CI (0.485–0.608)

AUC = 0.83595% CI (0.784–0.877)

AUC = 0.83695% CI (0.786–0.878)

AUC = 0.76195% CI (0.705–0.811)

AUC = 0.73595% CI (0.678–0.787)

AUC = 0.83695% CI (0.786–0.879)

AUC = 0.75295% CI (0.696–0.803)

AUC = 0.52095% CI (0.458–0.581)

1-speci�city

1-speci�city


Sens

itivi

ty

Sens

itivi

ty

AFP

GGT-II HGF AFP + AFU + HGF

AFU + HGF

AFU GPC3

0.6 0.8 1.0

0 0.2 0.4 0.6 0.8 1.0

1-speci�city

0 0.2 0.4 0.6 0.8 1.0

1-speci�city

0 0.2 0.4 0.6 0.8 1.0

1-speci�city

0 0.2 0.4 0.6 0.8 1.0

1-speci�city

0 0.2 0.4 0.6 0.8 1.0

1-speci�city

0 0.2 0.4 0.6 0.8 1.0

0 0.2 0.4 0.6 0.8 1.0 0 0.2 0.4 0.6 0.8 1.0

0.2

0

0.4

0.6

0.8

1.0Se

nsiti

vity

0.2

0

0.4

0.6

0.8

1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0Se

nsiti

vity

0.2

0

0.4

0.6

0.8

1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0

A

D

G

E

H I

B C

F

0.2

0

0.4

0.6

0.8

1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0

AFP + HGF AFP + AFU

Figure 4 The receiver operating characteristic curves of AFP (A), AFU (B), GPC3 (C), GGT-II (D), and HGF (E), AFP + AFU + HGF (F), AFP + AFU (G), AFP + HGF (H), AFU + HGF (I) in the detection of all-stage HBV-HCC and HCV-HCC of the test group. The sensitivity and specificity repre-sented by the red dots are shown in detail (lower). (A). AFP sensitivity: 52.8% and specificity: 93.7%; (B). AFU sensitivity: 71.5% and specificity: 67.1%; (C). GPC3 sensitivity: 91.1% and specificity: 25.9%; (D). GGT-II sensitivity: 73.2% and specificity: 38.5%; (E). HGF sensitivity: 61.8% and specificity: 75.5%; (F). AFP + AFU + HGF sensitivity: 65.9% and specificity: 89.5%; (G). AFP + AFU sensitivity: 69.1% and specificity: 87.4%; (H). AFP + HGF sensitivity: 74.8% and specificity: 79.0%; (I). AFU + HGF sensitivity: 63.4% and specificity: 76.9%.


C virus antibody-negative or NBNC-HCC) is increasing8,11. In

our study of 401 subjects (202 in the test cohort and 199 in

the validation cohort), the levels of all 5 markers were signifi-

cantly higher in NBNC-HCC patients than in healthy controls.

We therefore further studied the diagnostic capabilities of these

5 markers for NBNC-HCC. It is worth mentioning that the

healthy controls in this study only referred to individuals who

had not been infected with HBV or HCV. The healthy controls

may have suffered from alcohol-related liver disease, nonalco-

holic steatohepatitis, or aflatoxin exposure33. The combination

of AFP and AFU was uniquely associated with the progres-

sion of NBNC-HCC (HC to NBNC-HCC). This combination

showed promising characteristics as a diagnostic marker for

NBNC-HCC. Their diagnostic capability outperformed that of

AUC = 0.74195% CI (0.675–0.800)

AUC = 0.51095% CI (0.440–0.581)

AUC = 0.77695% CI (0.712–0.831)

AUC = 0.77495% CI (0.710–0.829) AUC = 0.666

95% CI (0.597–0.730)

AUC = 0.66595% CI (0.596–0.730)

AUC = 0.77095% CI (0.706–0.826)

AUC = 0.66695% CI (0.597–0.730)

AUC = 0.51795% CI (0.447–0.588)

1-speci�city

1-speci�city


Sens

itivi

ty

Sens

itivi

ty

AFP

GGT-II HGF AFP + AFU + HGF

AFU + HGF

AFU GPC3

0 0.2 0.4 0.6 0.8 1.0

0 0.2 0.4 0.6 0.8 1.0

1-speci�city

0 0.2 0.4 0.6 0.8 1.0

1-speci�city

0 0.2 0.4 0.6 0.8 1.0

1-speci�city

0 0.2 0.4 0.6 0.8 1.0

1-speci�city

0 0.2 0.4 0.6 0.8 1.0

1-speci�city

0 0.2 0.4 0.6 0.8 1.0

0 0.2 0.4 0.6 0.8 1.0 0 0.2 0.4 0.6 0.8 1.0

0.2

0

0.4

0.6

0.8

1.0Se

nsiti

vity

0.2

0

0.4

0.6

0.8

1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0

A

D

G

E

H I

B C

F

0.2

0

0.4

0.6

0.8

1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0

AFP + HGF AFP + AFU

Figure 5 The receiver operating characteristic curves of AFP (A), AFU (B), GPC3 (C), GGT-II (D), and HGF (E), AFP + AFU + HGF (F), AFP + AFU (G), AFP + HGF (H), and AFU + HGF (I) in the detection of early-stage HBV-HCC and HCV-HCC of the test group. The sensitivity and specificity represented by the red dots are shown in detail (lower). (A). AFP sensitivity: 44.3% and specificity: 93.7%; (B). AFU sensitivity: 63.9% and spec-ificity: 67.1%; (C). GPC3 sensitivity: 86.9% and specificity: 28.0%; (D). GGT-II sensitivity: 96.7% and specificity: 11.9%; (E). HGF sensitivity: 50.8% and specificity: 75.5%; (F). AFP + AFU + HGF sensitivity: 52.5% and specificity: 90.2%; (G). AFP + AFU sensitivity: 52.5% and specificity: 91.6%; (H). AFP + HGF sensitivity: 50.8% and specificity: 90.9%; (I). AFU + HGF sensitivity: 34.4% and specificity: 93.0%.


any other serum marker in this study (AUC: 0.986, 95% CI:

0.958–0.997, sensitivity: 92.6%, specificity: 98.9% in the test

cohort; AUC: 0.969, 95% CI: 0.934–0.988, sensitivity: 88.9%,

specificity: 94.8% in the validation cohort). Considering vari-

ous factors, such as the incidence of NBNC-HCC, our study is

the first large-scale, retrospective analysis of serum biomarkers

in NBNC-HCC patients.

In China, the incidence and mortality of hepatitis-related

HCC is still high34. The HBV-HCC and HCV-HCC patient

median plasma levels of AFP, AFU, and HGF were found to

be significantly higher than those of CH and LC patients.

We showed that the rise of these 3 serum biomarkers may be

related to the occurrence of HBV-HCC and HCV-HCC. Thus,

we paid particular attention to these 3 serum markers for dif-

ferentiating HBV-HCC and HCV-HCC patients from at-risk

(CH and LC) patients. This differentiation has also been the

focus of current research worldwide35. In our study, AFU

showed promising accuracy in identifying HBV-HCC and

HCV-HCC patients from the at-risk population. We found

that the combination of AFP and AFU uniquely reflected the

progression of HBV-HCC and HCV-HCC (CH to LC to HBV-

HCC and HCV-HCC). For all-stage hepatitis-related HCC

vs. CH and LC, the ROC curves showed that the AFP/AFU

combination had an AUC of 0.835 (95% CI: 0.784–0.877), a

sensitivity of 69.1%, and a specificity of 87.4%. Our results

are comparable with other promising markers, especially in

terms of diagnostic sensitivity (e.g., DKK1: 74.8% vs. 69.1%

in all-stage detection)12. Similar results were also shown in

early-stage HBV-HCC and HCV-HCC (AUC: 0.776, 95%

CI: 0.712–0.831, sensitivity: 52.5%, specificity: 91.6%). Most

importantly, the AFP/AFU panel improved the diagnostic sen-

sitivity in the absence of a loss of specificity in the detection

of HBV-HCC and HCV-HCC. Notably, this strategy showed

an advantage for using an AFP/AFU panel. Our findings

are consistent with the results of basic and clinical research

studies23,36,37. AFU was also considered to be a prognostic and

disease recurrence marker and has been shown to be associ-

ated with metastasis and reduced overall survival38.

Zhang et al.39 assessed the diagnostic value for HCC in com-

bination with AFU, AFP, and TK1. They enrolled participants

including 116 patients with HCC, 109 patients with benign

hepatic diseases (such as hepatitis and liver cirrhosis), and 104

normal subjects. The results showed that the AUC was 0.718

for AFU, 0.832 for AFP, 0.773 for TK1, and 0.900 for the com-

bination of these markers. The results were similar to our data

in the detection of HBV-HCC and HCV-HCC (0.780 for AFP, Tabl

e 2

Resu

lts fo

r mea

sure

men

t of s

erum

AFU

, AFP

, or b

oth,

in th

e di

agno

sis

of H

BV-H

CC a

nd H

CV-H

CC

Test

Val

idat

ion

AUC

Sen

sitiv

ity S

peci

ficity

PPV

NPV

Pos

itive

Neg

ativ

e P

AUC

Sen

sitiv

ity S

peci

ficity

PPV

NPV

Pos

itive

Neg

ativ

e P

(95%

CI)

(%

) (

%)

(%

) (

%)

LR

LR

val

ue(9

5% C

I) (

%)

(%

) (

%)

(%

) L

R

LR v

alue

Hep

atiti

s-H

CC v

s. CH

and

LC

(resu

lts fo

r the

mea

sure

men

t of A

FU, A

FP, o

r bot

h in

dia

gnos

is o

f hep

atiti

s-H

CC)

AFP

0.7

80 (0

.725

–0.8

28)

52.8

% 9

3.7%

87.

8% 6

9.8%

8.4

0 0

.50

<0.

001

0.80

9 (0

.755

–0.8

55)

62.8

% 9

0.2%

85.

4% 7

2.7%

6.4

1 0

.41

<0.

001

AFU

0.7

52 (0

.696

–0.8

03)

71.5

% 6

7.1%

65.

2% 7

3.3%

2.1

8 0

.42

<0.

001

0.72

7 (0

.668

–0.7

81)

69.4

% 6

5.4%

64.

6% 7

0.2%

2.0

0 0

.47

<0.

001

AFP

+ A

FU 0

.835

(0.7

84–0

.877

) 69

.1%

87.

4% 8

2.5%

76.

7% 5

.49

0.3

5 <

0.00

1 0.

841

(0.7

90–0

.884

) 71

.9%

86.

5% 8

2.9%

77.

2% 5

.31

0.3

2 <

0.00

1

Early

hep

atiti

s-H

CC v

s. CH

and

LC

(resu

lts fo

r mea

sure

men

t of A

FU, A

FP, o

r bot

h in

dia

gnos

is o

f ear

ly h

epat

itis-

HCC

)

AFP

0.7

41 (0

.675

–0.8

00)

44.3

% 9

3.7%

75.

0% 7

9.8%

7.0

3 0

.59

<0.

001

0.75

8 (0

.693

–0.8

16)

52.2

% 9

0.2%

73.

5% 7

8.4%

5.3

3 0

.53

<0.

001

AFU

0.6

66 (0

.597

–0.7

30)

63.9

% 6

7.1%

45.

3% 8

1.4%

1.9

4 0

.54

<0.

001

0.67

1 (0

.602

–0.7

36)

56.5

% 6

5.4%

45.

9% 7

4.4%

1.6

3 0

.67

<0.

001

AFP

+ A

FU 0

.776

(0.7

12–0

.831

) 52

.5%

91.

6% 7

2.7%

81.

9% 6

.25

0.5

2 <

0.00

1 0.

791

(0.7

28–0

.845

) 75

.4%

73.

7% 5

9.8%

85.

2% 2

.86

0.3

3 <

0.00

1

The

diag

nost

ic c

utof

f val

ues

of s

erum

AFP

and

AFU

wer

e 42

.34

ng/m

L an

d 13

.94

mU

/mL,

resp

ectiv

ely.


00 0.2

HBV- and HCV-HCC vs. CH + LC (test) HBV- and HCV-HCC vs. CH + LC (validation)

Early HBV- and HCV-HCC vs. CH + LC (test)

Nomogram HBV- and HCV-HCC vs. CH and LC

Early HBV- and HCV-HCC vs. CH + LC (validation)

AFP + AFU

AFP

AFU

AFP + AFU

AFP

AFU

AFP + AFU

AFP

AFU

AFP + AFU

AFP

AFU

0.4 0.6

1-specificity

Sens

itivi

ty

Sens

itivi

ty

0.8 1.0

0 0.2 0.4 0.6

1-specificity

0.8 1.0 0 0.2 0.4 0.6

1-specificity

0.8 1.0

0 0.2 0.4 0.6

1-specificity

0.8 1.0

0.2

0.4

0.6

0.8

1.0

A

C

E

D

B

0

Sens

itivi

ty

0.2

0.4

Points

AFP (ng/mL)

AFU (mU/mL)

Total points

Probability of HCC0.1

0 20 40 60 80 100 120 140 160 180

0 10 20 30 40 50 60 70 80 90 100

0 20 40 60 80 100 120 140 160 180

0 5 10 15 20 25 30 ≥.35

≥200

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0.95

0.6

0.8

1.0

0

Sens

itivi

ty

0.2

0.4

0.6

0.8

1.0

0

0.2

0.4

0.6

0.8

1.0

Figure 6 Diagnostic outcomes and nomogram for the combination of serum AFP and AFU of all-stage and early stage hepatitis-related hepatocellular carcinoma (HCC). (A). Receiver operating characteristic curves (ROCs) for AFU, AFP, or both for all patients with all-stage HBV-HCC and HCV-HCC vs. CH and LC in the test cohort. (B). ROC curves for AFU, AFP, or both for all patients with all-stage HBV-HCC and HCV-HCC vs. CH and LC in the validation cohort. (C). ROC curves for AFU, AFP, or both for all patients with early-stage HBV-HCC and HCV-HCC vs. CH and LC in the test cohort. (D). ROC curves for AFU, AFP, or both for all patients with early-stage HBV-HCC and HCV-HCC vs. CH and LC in the validation cohort. (E). Nomogram of the combined AFP/AFU in diagnosing HBV-HCC and HCV-HCC.


0.752 for AFU, and 0.835 for the combination). In addition,

we showed that the AFP/AFU combination was effective in

detecting NBNC-HCC patients. Zhu et al.40 found that the

AUCs were 0.80, 0.80, and 0.87 for serum AFU, 5′-NT, and

AFP, respectively. The correlation of AFU and AFP was sig-

nificant. However, they did not identify the combination of

these markers. In addition, the number of participants was too

low (36 for HCC and 36 for healthy controls). Xing et al.24

reported that a combination of AFU and AFP (AUC: 0.582)

did not improve the diagnostic efficacy compared with AFP

(AUC: 0.764) alone for HCC patients. They showed that the

majority of HCC patients (85.5%) had chronic HBV and

only 13 patients (6.9%) had chronic HCV, so there were some

NBNC-HCC patients (7.6%) who were enrolled in the HCC

cohort. Based on the etiology of HCC, patients with hepati-

tis do not progress to NBNC-HCC. This part of NBNC-HCC

patients might therefore cause bias in the results. However,

patients with benign disease would not evolve to HBV or

HCV-related HCC. This phenomenon might lead to a low

AUC of AFU and its combination. We enrolled patients with

hepatitis or liver cirrhosis as controls of hepatitis-related HCC

patients. In addition, healthy controls were used for compari-

son with NBNC-HCC patients. Thus, the results regarding the

AUC of the AFP/AFU combination in our study were more

convincing.

Conclusions

To the best of our knowledge, this is the first report show-

ing the potential of AFU in diagnosing NBNC-HCC and

hepatitis-related HCC, based on a study with a large sample

size and independent validation. Wang et al.21 reported that

preoperative serum AFU is a prognostic predictor of HCC

based on survival prognosis data. We showed that AFU was

a promising diagnostic marker for NBNC-HCC and hepa-

titis-related HCC, with a high degree of accuracy and clini-

cally applicable cut-off concentrations; AFU could also serve

as a reliable second-line marker for the detection of HCC.

The AFP/AFU panel had a high degree of accuracy for dif-

ferentiating NBNC-HCC from healthy controls and hepati-

tis-related HCC in patients at risk for developing HCC. The

assays, which are easy to perform and cost effective, can be

translated into a standard protocol for the clinical diagnosis

of HCC, which may identify asymptomatic patients early for

curative treatments. We are currently conducting a prospec-

tive study to confirm the present findings and to determine

the potential utility of measuring AFP/AFU levels to moni-

tor therapeutic responses, and for the prognostic diagnosis

of HCC.

Grant support

This work was supported by the National Natural Science

Foundation of China (Grant Nos. 81972656 and 31671421),

the Key Project of Tianjin Natural Science Foundation (Grant

No. 18JCZDJC35200), the State Key Project on Infectious

Diseases of China (Grant No. 2018ZX10723204), and the

National 135 Major Project of China (2018ZX10302205).

Conflict of interest statement

No potential conflicts of interest are disclosed.

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Cite this article as: Liu D, Luo Y, Chen L, Chen L, Zuo D, Li Y, et al. Diagnostic

value of 5 serum biomarkers for hepatocellular carcinoma with different

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Med. 2021; 18: 256-270. doi: 10.20892/j.issn.2095-3941.2020.0207


Supplementary materials

Table S1a The information of 347 healthy controls (test group)

Number AFP (ng/mL) AFU (mU/mL) GGT2 (mU/mL) GPC3 (ng/mL) HGF (ng/mL) Gender Age

2 0.000 6.127 515.942 0.285 0.390 Female 43

4 0.000 8.380 425.294 0.000 0.338 Female 37

5 0.000 6.177 504.611 0.000 0.292 Male 33

6 0.000 11.423 512.364 0.000 0.334 Female 31

8 0.000 3.335 470.021 0.000 0.253 Female 27

9 5.057 7.472 175.415 0.000 0.395 Female 45

14 0.000 10.465 345.976 1.373 0.296 Female 31

18 1.253 9.153 315.562 0.000 0.364 Female 24

19 0.000 3.201 394.879 0.000 0.235 Female 30

20 0.000 10.633 721.689 0.000 0.372 Male 68

24 0.000 13.592 501.033 0.000 0.500 Male 45

25 10.323 4.950 337.031 0.000 0.429 Female 25

27 25.244 11.171 437.221 0.000 0.271 Female 25

28 0.000 5.151 438.414 0.000 0.262 Female 34

30 11.786 5.017 353.133 0.000 0.346 Female 27

33 0.000 5.026 573.241 0.000 0.454 Male 40

34 0.000 1.719 531.221 0.000 0.307 Female 24

38 0.000 3.587 869.350 0.000 0.245 Female 26

39 8.157 3.548 888.569 0.000 0.280 Female 48

41 4.650 5.551 611.978 0.000 0.571 Female 25

43 0.000 8.255 737.381 0.000 0.417 Female 24

44 0.000 8.877 947.723 0.000 0.394 Female 25

46 0.000 6.757 1,483.200 0.000 0.351 Male 43

47 0.000 8.138 704.553 0.000 0.330 Female 29

48 0.000 8.955 826.017 0.000 0.635 Female 28

51 3.375 7.360 741.732 0.000 0.153 Male 28

52 0.000 8.177 857.532 0.000 0.209 Female 35

54 0.000 4.929 1,234.749 12.793 0.173 Female 23

55 0.000 6.504 1,814.282 0.000 0.130 Male 32

56 0.000 7.127 855.562 0.000 0.234 Female 29

60 2.418 5.882 867.380 0.000 0.212 Female 26

61 0.000 8.994 833.239 0.000 0.184 Female 28

63 21.864 9.675 1,582.157 0.000 0.199 Male 37

64 0.000 3.606 1,368.139 0.000 0.240 Female 26



68 0.000 4.326 824.047 0.000 0.229 Female 41

71 0.000 4.442 711.119 0.000 0.210 Female 30

72 0.825 5.609 827.330 0.000 0.193 Female 27

73 13.275 8.540 548.900 0.558 0.211 Male 26

78 19.292 2.717 530.420 0.000 0.222 Female 29

80 6.829 0.000 290.177 0.000 0.232 Female 31

81 24.449 9.319 397.664 0.156 0.220 Male 48

83 12.416 15.598 513.448 1.906 0.368 Male 54

84 3.391 4.349 407.093 0.558 0.172 Female 24

85 4.680 13.466 350.144 0.582 0.383 Female 33

86 39.062 16.186 372.018 0.000 0.316 Male 42

87 10.267 7.614 263.400 0.000 0.275 Female 29

88 20.581 4.143 443.299 1.078 0.164 Male 33

92 2.961 9.510 579.072 0.440 0.191 Female 25

93 13.705 6.026 434.248 0.000 0.155 Female 33

95 16.284 15.406 642.433 0.535 0.270 Male 32

96 30.466 6.746 568.889 0.000 0.186 Female 28

98 8.978 2.908 457.631 0.000 0.598 Female 26

101 4.250 3.879 235.491 0.000 0.412 Female 48

103 18.862 4.746 543.997 0.000 0.477 Male 26

105 8.548 1.100 491.197 0.000 0.384 Female 69

106 12.846 4.820 422.556 0.000 0.405 Male 83

111 4.250 2.776 375.790 0.416 0.416 Female 58

112 11.127 2.306 257.743 2.426 0.472 Female 63

116 0.000 3.031 1,194.775 0.000 0.414 Female 56

118 11.324 12.467 502.778 0.000 0.538 Male 68

119 0.000 3.672 415.533 0.000 0.357 Male 51

121 0.000 2.454 681.926 0.000 0.594 Female 66

122 0.000 1.589 601.881 0.000 0.441 Female 56

124 0.000 3.367 831.427 0.000 0.471 Female 64

125 3.074 3.928 760.276 0.000 0.379 Male 64

128 16.365 2.021 1,183.854 0.000 0.519 Female 59

129 0.000 3.095 567.576 0.000 0.741 Male 62

131 18.657 2.822 615.010 0.000 0.371 Female 65

132 0.000 4.697 738.253 0.133 0.450 Female 57

Table S1a (continued)



135 1.241 3.127 456.614 0.000 0.386 Female 42

138 0.000 5.081 742.912 0.000 0.565 Female 63

141 0.000 2.614 744.183 0.000 0.385 Female 59

142 0.000 4.489 895.802 0.000 0.496 Female 58

145 0.000 5.081 902.313 0.000 0.167 Male 75

146 0.000 0.515 842.015 0.000 0.162 Female 62

147 20.032 3.287 602.728 0.000 0.236 Male 63

151 5.824 2.117 534.965 0.000 0.119 Female 25

155 0.000 1.486 412.283 0.000 0.222 Female 68

158 0.000 1.612 361.943 0.000 0.105 Male 19

159 0.000 1.517 331.942 0.000 0.137 Female 59

161 0.000 1.722 417.368 0.000 0.171 Female 63

162 0.000 5.505 490.590 0.000 0.179 Male 72

163 0.000 4.307 643.645 0.000 0.206 Female 73

164 0.000 5.378 621.780 0.000 0.178 Female 51

165 0.000 2.825 497.709 0.000 0.172 Female 61

166 0.000 6.387 460.589 0.000 0.188 Female 63

170 0.000 2.132 327.366 0.000 0.203 Male 67

173 0.000 5.410 440.758 0.000 0.169 Male 79

174 0.000 5.142 360.926 0.000 0.227 Female 69

182 0.000 0.000 250.075 0.000 0.149 Male 79

183 0.000 4.795 178.887 0.000 0.159 Female 61

184 0.000 3.172 329.399 0.421 0.166 Male 62

185 0.000 0.000 485.505 0.000 0.151 Female 58

186 0.000 5.898 345.671 0.000 0.192 Female 65

191 0.000 1.990 276.517 0.356 0.259 Female 69

193 0.000 7.058 733.206 0.000 0.511 Female 60

196 0.000 5.215 1,042.845 0.000 0.763 Female 70

200 5.258 9.515 458.420 0.000 0.650 Female 60

201 0.000 6.414 703.338 0.000 0.681 Male 68

202 0.000 5.858 624.828 0.000 0.581 Male 72

203 0.000 9.691 641.042 0.000 0.654 Female 77

207 0.000 6.999 6,310.173 0.184 0.489 Female 64

209 0.000 5.420 984.543 0.000 0.853 Female 61

212 0.000 6.034 910.708 0.000 0.506 Male 75

214 0.000 9.164 767.341 0.000 0.534 Male 85




216 0.000 9.077 940.576 0.000 0.421 Male 74

217 31.529 4.366 2,609.853 0.000 0.782 Female 68

218 3.798 4.922 709.312 0.000 0.591 Female 64

220 0.000 3.284 633.361 0.000 0.458 Female 64

221 0.000 5.039 699.071 0.000 0.451 Female 50

222 0.000 5.478 839.024 0.000 0.471 Female 76

223 0.000 10.686 840.731 0.000 0.484 Male 40

224 7.204 6.882 751.980 0.000 0.433 Male 71

225 17.907 2.845 593.253 0.000 0.719 Male 70

228 9.150 8.608 752.834 0.000 0.601 Female 67

229 0.393 8.433 623.974 0.000 0.487 Male 68

234 0.000 8.158 373.547 0.000 0.499 Male 55

236 7.064 7.813 352.357 0.000 0.546 Female 57

237 0.000 11.062 563.081 0.000 0.787 Female 58

238 7.972 5.209 406.510 0.000 0.477 Female 63

239 0.707 8.366 703.171 0.000 0.671 Female 62

240 7.518 1.844 332.344 0.000 0.536 Male 66

241 12.059 10.785 591.334 0.000 0.757 Female 74

243 22.502 16.753 525.410 0.000 0.576 Male 75

246 4.340 12.744 697.285 0.000 0.791 Female 62

248 8.880 4.633 592.512 0.000 0.587 Female 65

249 9.789 12.905 467.726 0.000 0.936 Female 66

250 3.886 16.247 860.920 0.000 0.974 Male 55

251 12.513 7.767 531.296 0.000 0.688 Male 52

257 1.162 17.952 840.907 9.686 0.892 Male 50

258 1.162 15.325 651.373 15.446 0.951 Male 45

259 7.972 13.043 770.273 4.281 0.857 Male 59

261 0.000 14.080 767.919 5.973 0.711 Male 52

263 0.000 12.537 943.528 5.673 0.798 Male 58

265 26.588 17.952 544.245 14.354 1.176 Male 52

266 7.518 10.209 716.121 9.823 0.819 Male 47

267 7.064 14.380 777.447 29.521 0.707 Male 41

270 0.000 14.703 707.880 15.638 0.489 Male 50

274 26.315 9.557 394.531 0.000 0.855 Male 45

275 0.000 1.454 570.850 0.000 0.747 Female 41

277 5.034 0.968 431.558 0.000 0.527 Male 60




278 20.313 3.443 406.874 40.221 0.689 Female 30

279 8.308 4.226 376.018 152.273 0.504 Female 30

285 7.217 5.939 1,741.841 58.902 0.617 Male 44

287 5.580 1.750 491.506 61.529 0.627 Male 28

289 6.671 1.708 577.902 55.979 0.221 Female 39

291 13.765 8.245 596.416 8.754 0.287 Female 44

292 8.308 7.209 469.467 32.677 0.376 Female 31

293 5.580 9.218 560.271 16.261 0.377 Male 26

298 31.772 4.204 515.309 42.915 0.443 Male 62

302 2.306 9.642 555.863 17.633 0.490 Male 56

303 14.856 8.076 372.492 2.366 0.457 Female 35

304 14.311 10.297 228.792 24.291 0.482 Male 51

306 4.489 7.272 632.561 27.777 0.465 Male 27

308 8.308 7.949 423.624 2.727 0.408 Male 30

310 0.000 12.455 507.375 6.372 0.451 Male 33

312 43.231 4.310 207.634 32.631 0.348 Male 54

314 0.000 2.864 352.573 25.491 0.302 Male 27

317 0.000 7.899 2,416.889 23.458 0.438 Male 31

320 0.000 7.899 674.299 23.967 0.650 Female 31

323 67.991 9.235 761.287 18.944 0.313 Female 62

324 0.000 7.248 773.440 10.672 0.305 Female 65

326 0.000 2.916 474.100 69.076 0.517 Female 30

330 0.000 2.881 797.745 14.659 0.307 Male 68

331 0.000 7.847 1,419.580 51.709 0.288 Male 40

332 0.000 6.974 827.807 22.966 0.459 Female 40

334 0.000 4.851 731.865 51.983 0.458 Female 33

335 0.000 3.875 764.485 36.921 0.471 Female 57

337 56.645 5.621 495.847 23.091 0.343 Female 70

339 0.000 6.152 702.602 23.722 0.319 Female 62

340 0.000 5.981 511.198 53.962 0.379 Female 43

341 0.000 3.977 564.286 1.438 0.258 Female 38

342 0.000 12.968 739.540 169.094 0.338 Male 41

343 0.000 3.412 685.173 49.386 0.359 Male 38

345 0.000 7.625 473.461 24.516 0.314 Male 58



Table S1b The information of 347 healthy controls (validation group)


1 0.000 2.209 322.718 0.000 0.358 Female 24

3 0.000 6.362 502.822 0.000 0.263 Female 27

7 10.323 11.305 423.504 0.000 0.302 Female 42

10 0.000 7.001 512.960 0.000 0.424 Female 27

11 0.000 9.304 442.588 0.000 0.457 Male 52

12 0.000 10.196 523.695 0.000 0.347 Female 30

13 0.000 9.019 337.627 0.984 0.261 Female 24

15 0.000 5.219 567.230 0.000 0.310 Female 28

16 0.000 4.058 552.917 0.000 0.242 Female 26

17 36.947 2.579 279.779 0.000 0.307 Female 31

21 7.105 15.711 738.984 0.000 0.472 Male 54

22 12.956 3.100 246.383 0.000 0.236 Female 28

23 0.000 7.690 569.019 0.285 0.404 Female 55

26 12.371 5.958 384.144 0.000 0.314 Male 57

29 0.000 5.605 224.913 0.000 0.258 Female 31

31 55.964 10.212 383.548 0.000 0.222 Female 31

32 12.078 4.428 319.736 0.000 0.296 Female 48

35 0.000 5.357 494.454 0.000 0.353 Female 23

36 0.000 7.379 837.835 0.000 0.341 Female 24

37 35.572 8.099 622.483 0.000 0.382 Female 28

40 0.000 2.322 728.189 0.000 0.194 Female 26

42 0.000 5.357 1,445.981 0.000 0.459 Female 32

45 0.000 6.932 834.552 0.000 0.363 Female 35

49 34.616 4.870 803.037 0.000 0.189 Male 37

50 14.851 5.240 1,399.506 0.000 0.232 Male 28

53 0.000 9.519 726.689 0.000 0.256 Male 50

57 11.663 8.410 847.027 0.000 0.349 Male 45

58 0.000 3.840 742.634 0.000 0.166 Female 31

59 4.331 10.919 785.967 0.000 0.229 Female 27

62 0.000 5.901 1,380.162 0.000 0.228 Male 54

65 18.995 3.275 606.069 0.000 0.167 Female 35

66 9.750 2.206 795.158 0.000 0.211 Male 40

67 0.000 5.473 828.643 0.000 0.188 Male 43

69 0.000 6.115 908.743 0.000 0.223 Female 27



70 0.000 11.950 857.532 0.000 0.271 Female 41

74 27.458 13.348 402.567 0.464 0.305 Female 43

75 4.250 4.937 451.973 0.000 0.117 Female 25

76 8.978 1.350 501.380 0.000 0.163 Female 42

77 19.292 1.247 411.619 0.000 0.129 Female 25

79 14.565 2.379 329.401 0.298 0.211 Male 31

82 5.110 8.996 618.295 0.133 0.200 Female 27

89 5.110 5.908 467.436 1.409 0.168 Female 56

90 0.000 7.863 364.852 0.298 0.221 Male 51

91 3.820 12.451 308.658 0.000 0.288 Female 30

94 4.680 19.200 454.613 0.606 0.389 Female 29

97 5.539 9.510 387.104 0.984 0.599 Male 27

99 5.969 11.745 387.858 0.653 0.746 Male 80

100 3.391 7.319 455.745 0.000 0.538 Female 41

102 5.539 3.291 516.088 0.000 0.479 Male 67

104 22.301 2.320 387.481 0.000 0.406 Female 62

107 6.829 6.820 469.322 0.000 0.501 Female 69

108 9.407 2.453 535.323 0.000 0.441 Female 77

109 16.284 2.350 597.929 0.000 0.413 Male 77

110 11.127 0.615 424.442 0.000 0.440 Male 63

113 0.000 2.406 407.063 0.000 0.471 Female 47

114 0.000 4.425 692.090 0.000 0.575 Female 68

115 0.000 2.854 586.211 0.000 0.371 Female 58

117 0.000 5.514 565.458 0.000 0.429 Female 75

120 7.657 1.525 509.977 0.000 0.435 Female 70

123 0.000 3.415 526.918 0.000 0.488 Female 80

126 3.532 5.049 533.694 0.000 0.498 Female 55

127 3.532 4.681 598.493 0.000 0.379 Male 63

130 0.000 1.044 731.901 0.000 0.449 Female 64

133 0.000 3.736 690.819 0.000 0.376 Female 59

134 0.000 7.292 529.459 0.000 0.384 Female 74

136 36.990 4.761 483.719 0.026 0.386 Male 43

137 3.991 4.809 745.030 0.000 0.626 Female 84

139 0.000 6.027 621.363 0.000 0.456 Female 63

140 0.000 3.015 576.470 0.000 0.487 Female 71

Table S1b (continued)



143 0.000 5.658 537.930 0.000 0.462 Female 58

144 0.000 2.983 644.656 0.000 0.522 Female 80

148 0.000 0.000 566.305 0.000 0.171 Female 63

149 1.699 4.232 3,051.854 0.000 0.332 Female 75

150 0.000 2.630 472.284 0.000 0.203 Male 68

152 24.157 2.390 582.822 0.000 0.316 Female 62

153 8.780 1.722 442.792 0.000 0.153 Female 58

154 0.000 1.439 309.568 0.000 0.172 Male 48

156 47.907 5.962 457.030 0.726 0.178 Female 63

157 0.000 2.037 456.521 0.639 0.159 Female 61

160 0.000 2.274 486.014 0.000 0.170 Female 69

167 0.000 10.280 643.137 0.000 0.192 Female 51

168 0.000 12.108 516.523 0.465 0.208 Male 58

169 0.000 4.055 626.356 0.000 0.276 Male 80

171 0.000 2.967 467.200 0.000 0.150 Male 73

172 0.000 4.086 736.698 0.182 0.135 Female 59

175 0.000 19.168 222.109 0.508 0.366 Male 77

176 0.000 3.078 316.179 0.030 0.147 Male 56

177 33.392 3.802 482.454 0.008 0.222 Male 66

178 0.000 2.211 377.197 0.000 0.300 Female 60

179 0.000 5.126 529.235 0.008 0.237 Male 78

180 0.000 3.566 362.451 0.000 0.178 Female 74

181 0.000 2.164 629.407 0.000 0.154 Female 77

187 0.000 0.588 359.400 0.000 0.172 Female 52

188 0.000 0.000 408.724 0.000 0.157 Female 57

189 0.000 4.196 474.827 0.000 0.180 Female 61

190 0.000 3.755 319.230 0.000 0.186 Female 60

192 1.838 4.228 296.856 0.247 0.192 Female 56

194 0.000 7.906 612.027 0.000 0.782 Male 53

195 0.000 9.106 657.256 0.000 0.761 Male 46

197 0.000 9.984 637.628 0.499 0.688 Female 82

198 11.582 1.616 658.963 0.000 0.477 Female 62

199 0.000 6.005 616.294 0.000 0.595 Female 56

204 0.000 6.209 516.449 0.000 0.499 Female 63

205 2.825 6.092 806.596 0.000 0.452 Male 68




206 5.744 9.106 760.514 0.355 0.489 Female 61

208 0.000 3.986 577.892 0.000 0.458 Female 73

210 0.393 5.215 1,589.362 0.000 0.589 Female 59

211 2.825 9.925 850.971 0.000 0.534 Female 67

213 0.000 8.550 842.438 0.000 0.506 Female 66

215 3.312 6.970 829.637 0.000 0.416 Female 61

219 7.204 7.204 677.737 0.000 0.494 Male 62

226 1.366 7.848 733.206 0.000 0.638 Female 56

227 58.774 2.845 749.420 0.000 0.484 Female 63

230 12.069 9.749 810.010 0.000 0.518 Female 61

231 11.096 1.616 891.080 0.000 0.451 Male 66

232 2.339 3.723 651.282 0.000 0.471 Female 73

233 17.053 8.757 520.701 0.000 0.959 Female 55

235 4.340 6.822 460.662 0.000 0.749 Female 57

242 5.248 11.799 1,428.173 0.000 0.870 Male 49

244 5.248 7.467 690.222 0.000 0.515 Male 70

245 0.000 8.435 530.119 0.000 0.586 Female 61

247 7.972 12.583 620.765 0.377 0.790 Female 70

252 1.162 24.018 714.943 0.000 0.763 Male 52

253 10.697 16.477 458.308 0.000 0.854 Male 53

254 0.000 12.191 606.638 0.000 0.841 Female 74

255 5.702 13.182 790.286 9.195 0.801 Male 58

256 7.972 10.324 786.754 0.000 0.592 Male 51

260 24.772 14.587 692.576 2.779 0.604 Male 51

262 0.000 9.449 664.323 4.881 0.532 Male 45

264 0.000 3.411 344.117 1.551 0.451 Male 51

268 12.967 20.486 742.020 52.528 0.729 Male 51

269 0.000 13.251 701.994 14.873 0.566 Male 52

271 0.000 8.343 586.626 23.363 0.688 Male 43

272 0.000 12.168 672.563 68.580 0.716 Male 46

273 0.000 5.664 361.031 23.083 0.995 Male 46

276 2.306 7.991 470.348 1.464 0.663 Male 46

280 15.948 8.457 351.333 7.924 0.548 Male 71

281 0.123 6.532 517.073 15.106 0.938 Female 20

282 7.763 2.893 506.493 37.261 0.793 Female 23




283 1.215 3.189 305.491 54.828 0.711 Female 26

284 12.674 5.030 805.353 52.333 0.509 Male 40

286 5.034 2.639 592.008 267.161 0.627 Female 28

288 6.126 3.041 153.857 39.622 0.653 Female 22

290 10.491 34.149 1,097.318 335.264 0.897 Male 27

294 18.676 10.234 851.196 9.909 0.467 Male 30

295 23.041 8.901 354.860 13.446 0.411 Male 34

296 21.950 2.173 223.503 4.207 0.235 Male 33

297 7.217 1.095 606.995 10.054 0.218 Male 42

299 25.769 8.266 536.468 16.586 0.338 Male 25

300 14.856 7.314 356.623 22.649 0.373 Female 37

301 9.945 5.156 420.979 13.410 0.252 Male 33

305 0.000 8.922 500.322 15.539 0.675 Male 62

307 6.671 14.782 366.320 23.263 0.418 Male 41

309 0.000 8.372 466.822 15.828 0.489 Male 28

311 14.856 9.070 199.700 21.603 0.699 Male 51

313 0.000 11.170 576.439 44.420 0.391 Male 47

315 0.000 2.590 865.776 38.233 0.395 Male 30

316 0.000 4.868 898.607 12.528 0.318 Female 35

318 0.000 5.621 742.099 16.973 0.415 Female 66

319 0.000 13.995 532.305 40.362 0.379 Male 60

321 0.000 2.642 570.682 1.094 0.475 Female 47

322 0.000 5.056 513.756 23.366 0.540 Female 41

325 57.185 0.000 878.336 4.806 0.344 Female 40

327 0.000 3.121 634.004 0.063 0.578 Female 46

328 0.000 1.871 680.056 7.487 0.369 Female 31

329 0.000 6.032 738.901 22.679 0.291 Male 31

333 0.000 5.227 576.439 106.452 0.337 Female 42

336 0.000 12.933 641.040 176.700 0.283 Female 33

338 0.000 1.152 593.708 66.447 0.271 Female 47

344 0.000 17.249 843.158 110.541 0.384 Male 35

346 0.000 2.196 478.578 12.528 0.209 Male 61

347 0.000 8.156 728.027 20.090 0.323 Male 69



Table S2a The information of 54 NBNC-HCC patients (test group)


9 1,895.072 479.602 14,431.953 38.260 4.291 Female 68

620 103.799 8.725 711.468 4.045 0.238 Female 49

545 88.895 9.277 7,278.588 3.062 0.508 Female 65

395 1,303.483 174.560 12,793.993 16.906 2.034 Female 77

590 1,245.818 36.586 4,023.670 30.478 0.311 Male 54

586 427.605 16.869 1,507.894 51.215 0.570 Male 60

574 435.096 17.330 9,471.676 13.364 0.346 Male 73

543 893.821 32.685 1,643.010 26.444 1.053 Male 69

132 55.332 32.535 702.669 22.067 0.525 Male 62

94 0.000 33.453 291.770 5.691 1.195 Male 40

72 5,887.511 49.575 921.998 21.104 0.733 Male 56

45 9,630.275 192.102 5,128.398 5.418 1.461 Male 61

19 0.000 253.009 7,026.921 31.044 1.578 Male 72

18 0.000 43.676 762.983 6.796 1.029 Male 49

65 3,208.245 29.461 1,296.319 0.720 0.848 Male 57

589 9.957 7.497 724.291 10.818 0.223 Male 47

473 11.526 78.777 1,401.820 6.096 0.392 Male 49

459 367.386 30.063 9,080.726 8.021 0.441 Male 79

367 14.006 26.425 538.084 1.084 0.371 Male 66

195 5,966.582 384.668 13,014.503 15.682 1.325 Male 73

193 0.000 202.639 634.542 7.732 1.137 Male 64

157 7.859 14.117 671.018 22.448 0.616 Male 67

129 2.584 21.124 842.257 19.302 0.703 Male 52

115 0.000 21.124 711.596 1.007 0.475 Male 57

8 0.000 26.625 638.297 18.225 0.936 Male 61

598 6,626.332 28.049 15,256.585 18.983 0.299 Male 58

87 7,673.842 71.793 1,768.286 12.708 1.100 Male 58


Table S2b The information of 54 NBNC-HCC patients (validation group)


636 7,357.865 8.035 599.087 19.989 0.218 Female 62

628 0.000 8.280 451.785 1.467 0.208 Female 39

542 3.727 17.651 687.167 5.365 0.398 Female 62

393 182.199 18.098 977.582 5.289 0.474 Female 52

294 0.000 487.276 5,452.020 10.940 2.870 Female 55

231 7.795 321.586 625.718 129.202 1.794 Female 76

229 0.000 80.686 584.808 17.504 1.036 Female 72

80 44.989 47.079 1,860.445 12.291 0.631 Female 50

646 64.684 10.706 729.246 2.868 0.236 Male 40

616 0.000 76.231 2,331.890 236.046 1.306 Male 70

603 0.000 12.614 811.063 6.311 0.321 Male 21

572 3,304.545 8.781 6,867.373 20.216 0.297 Male 65

556 0.000 17.386 906.014 4.151 0.374 Male 77

524 892.291 14.432 8,949.422 139.367 0.605 Male 63

523 5,804.144 66.970 2,510.479 16.133 1.118 Male 60

486 33.048 19.702 618.687 2.651 0.538 Male 47

463 0.000 13.065 636.543 55.485 0.302 Male 54

422 65.080 18.596 765.263 6.572 0.350 Male 66

373 735.086 59.020 805.772 3.048 0.519 Male 63

203 375.112 625.725 5,492.826 13.993 0.983 Male 72

185 0.000 169.128 1,489.102 13.794 0.749 Male 52

138 0.000 69.744 784.637 18.358 1.418 Male 59

73 72.010 21.360 248.074 1.597 0.479 Male 66

57 2.921 32.959 294.995 0.000 0.920 Male 58

23 9,294.590 36.968 743.033 58.214 0.705 Male 70

11 6,119.195 76.334 2,671.297 37.285 1.083 Male 62

5 10,817.572 121.048 1,639.530 10.541 1.482 Male 77


Table S3a The information of 154 hepatitis patients (test group)


4 0.000 33.712 2,296.099 6.708 0.930 Female 56

91 0.000 15.270 771.755 47.542 0.826 Female 62

148 0.000 13.256 370.937 0.000 0.802 Female 75

80 0.000 19.843 258.479 0.288 0.722 Female 55

149 0.000 8.476 436.495 14.507 0.612 Female 73

6 0.000 3.930 360.443 0.193 0.601 Female 81

55 0.000 20.249 503.238 24.519 0.591 Female 27

30 19.281 4.121 2,852.941 1.052 0.588 Female 55

28 0.000 10.349 2,130.785 8.013 0.548 Female 62

43 448.103 18.947 330.408 16.005 0.510 Female 63

10 0.000 0.834 4,419.132 14.608 0.506 Female 58

111 0.000 11.457 192.518 2.551 0.476 Female 30

12 1.934 6.681 630.131 10.183 0.451 Female 60

64 0.000 3.870 1,340.159 21.521 0.441 Female 58

74 0.000 5.246 812.586 0.000 0.415 Female 33

152 0.000 5.107 79.650 124.536 0.406 Female 49

103 0.000 14.961 575.769 249.865 0.387 Female 88

21 0.000 0.624 924.221 0.537 0.374 Female 34

75 0.000 6.984 475.170 0.354 0.365 Female 63

145 0.000 9.730 1,012.364 16.331 0.360 Female 67

31 8.892 7.483 525.635 15.489 0.352 Female 66

41 0.000 0.000 528.137 0.000 0.342 Female 66

127 0.000 12.848 266.911 11.830 0.331 Female 53

63 0.000 8.924 593.415 6.157 0.308 Female 55

46 0.000 3.261 525.635 4.189 0.295 Female 57

132 15.551 5.629 238.331 8.599 0.275 Female 56

51 0.000 4.254 457.254 0.000 0.274 Female 62

123 0.000 12.719 260.241 12.164 0.270 Female 82

113 0.000 16.945 295.642 6.144 0.267 Female 36

118 0.000 7.721 329.504 43.163 0.254 Female 36

102 0.000 14.652 426.471 15.304 0.246 Female 71

146 0.000 5.420 296.439 33.829 0.211 Female 68

88 0.000 2.593 396.200 0.029 0.193 Female 54

47 0.000 6.961 620.288 0.000 0.188 Female 58

119 0.000 3.160 144.804 2.979 0.159 Female 43

84 0.000 0.509 5,386.430 0.000 0.070 Female 50



8 0.000 10.598 712.101 28.676 0.988 Male 22

20 9.691 17.820 661.417 0.665 0.987 Male 63

7 0.000 12.145 2,690.393 89.557 0.966 Male 80

83 0.000 13.052 742.714 0.000 0.865 Male 40

33 0.000 12.413 2,794.616 1.675 0.782 Male 38

106 0.000 26.504 657.857 58.107 0.739 Male 62

141 0.000 18.559 445.435 29.456 0.703 Male 60

77 0.000 16.730 1,547.571 81.292 0.665 Male 37

16 11.689 12.566 3,408.180 91.712 0.568 Male 66

99 0.000 25.978 674.788 14.424 0.537 Male 43

67 0.000 10.413 2,306.657 9.036 0.523 Male 33

62 0.000 30.063 426.199 0.442 0.519 Male 44

85 0.000 12.353 690.758 13.191 0.515 Male 53

128 0.232 9.234 569.101 2.665 0.492 Male 77

44 49.250 7.713 4,151.063 1.632 0.447 Male 43

130 0.000 12.891 1,631.498 63.595 0.428 Male 40

140 0.000 19.264 814.944 12.041 0.426 Male 30

32 0.000 13.846 3,416.174 8.550 0.418 Male 49

122 0.000 15.296 864.618 14.781 0.417 Male 69

14 0.901 3.605 830.363 10.612 0.404 Male 29

155 20.338 6.805 228.646 24.076 0.396 Male 54

95 0.000 7.206 328.477 3.289 0.389 Male 56

36 0.000 8.133 2,345.740 0.601 0.369 Male 27

109 0.000 16.172 392.096 8.928 0.348 Male 64

164 5.328 0.000 768.046 29.778 0.343 Male 63

169 0.000 0.124 1,351.050 19.362 0.337 Male 49

79 0.000 18.895 2,140.239 9.806 0.330 Male 25

150 0.000 13.256 877.523 199.148 0.322 Male 44

86 0.000 4.863 332.440 0.794 0.317 Male 55

171 401.717 7.307 2,615.363 39.726 0.314 Male 41

131 0.000 6.387 510.993 24.850 0.302 Male 62

161 0.000 2.981 1,060.837 23.174 0.297 Male 49

69 0.000 6.036 1,064.152 17.147 0.283 Male 25

135 0.000 3.488 328.473 0.918 0.277 Male 57

129 0.000 6.700 420.851 0.000 0.271 Male 20




170 0.000 4.629 2,065.907 10.217 0.250 Male 52

66 0.000 4.096 1,257.576 4.706 0.243 Male 29

37 0.000 3.968 1,944.007 3.437 0.240 Male 30

163 0.000 2.582 820.856 21.575 0.237 Male 66

138 0.000 4.349 486.409 0.000 0.222 Male 61

162 0.000 2.417 850.125 7.125 0.210 Male 42

120 0.000 6.046 266.911 0.243 0.202 Male 31

42 0.000 1.255 4,137.875 0.687 0.202 Male 61

53 13.169 2.765 5,400.203 0.000 0.156 Male 30

90 63.563 17.795 1,243.409 21.300 0.513 Male 40

100 42.340 84.894 4,935.180 5.597 0.876 Male 46



Table S3b The information of 154 hepatitis patients (validation group)


98 474.436 25.202 486.498 23.513 0.600 Female 32

48 27.915 7.660 3,236.716 6.245 0.437 Female 46

15 25.275 7.866 1,239.505 11.859 0.843 Female 26

78 9.072 10.458 686.577 11.894 0.731 Female 60

17 2.499 4.445 785.310 7.927 0.421 Female 48

73 0.000 7.277 3,029.426 3.607 0.987 Female 27

19 0.000 22.024 790.942 0.000 0.970 Female 43

2 0.000 8.036 722.910 34.394 0.791 Female 64

26 0.000 23.017 5,820.360 5.972 0.763 Female 29

49 0.000 13.052 620.886 12.443 0.715 Female 38

114 0.000 24.031 950.297 15.399 0.611 Female 66

96 0.000 12.307 543.960 83.425 0.572 Female 35

13 0.000 6.089 561.301 7.261 0.549 Female 30

112 0.000 11.869 285.894 0.434 0.485 Female 27

168 0.000 10.081 830.400 14.776 0.464 Female 46

156 0.000 8.738 843.999 31.749 0.388 Female 47

158 0.000 2.129 1,126.420 3.099 0.371 Female 57

157 0.000 13.283 1,495.704 0.071 0.366 Female 81

68 0.000 7.954 948.309 5.871 0.350 Female 57

94 0.000 9.937 343.869 9.070 0.333 Female 27

154 0.000 5.499 382.112 0.000 0.315 Female 32

151 0.000 11.167 596.666 7.597 0.277 Female 47

167 0.000 2.802 902.299 4.379 0.274 Female 67

52 0.000 1.140 554.597 0.000 0.253 Female 20

133 0.000 4.167 373.172 49.701 0.250 Female 30

124 0.000 6.278 385.939 24.917 0.238 Female 55

72 0.000 1.637 607.747 0.000 0.221 Female 25

45 0.000 1.350 1,093.725 2.406 0.204 Female 44

153 0.000 10.279 408.186 0.000 0.190 Female 68

101 219.763 17.589 518.307 100.118 0.535 Male 28

136 17.466 14.745 2,471.872 59.010 0.397 Male 49

11 13.288 0.000 718.417 14.403 0.312 Male 30

38 8.493 6.413 787.188 21.891 0.346 Male 17

142 5.019 7.327 471.509 27.539 0.321 Male 57

87 4.976 0.000 388.576 0.000 0.180 Male 28

39 0.101 3.968 2,220.762 3.910 0.198 Male 36



104 0.000 16.610 222.275 294.007 0.963 Male 20

22 0.000 6.394 825.357 0.000 0.632 Male 28

126 0.000 20.295 288.459 71.460 0.542 Male 71

60 0.000 12.646 3,580.859 18.686 0.519 Male 42

125 0.000 11.818 2,476.641 0.291 0.518 Male 45

58 0.000 2.898 15,138.761 91.864 0.510 Male 38

82 0.000 6.374 722.409 236.751 0.502 Male 63

59 0.000 14.947 1,801.335 0.000 0.449 Male 44

35 0.000 7.694 851.637 1.353 0.443 Male 40

166 0.000 5.357 1,247.496 1.260 0.427 Male 51

108 0.000 17.331 502.402 22.689 0.417 Male 29

144 0.000 10.775 315.064 102.886 0.416 Male 51

5 0.000 4.217 502.243 64.780 0.414 Male 24

137 0.000 16.939 622.740 38.144 0.404 Male 43

50 0.000 7.164 449.490 0.000 0.390 Male 48

34 0.000 20.075 17,961.375 17.229 0.382 Male 43

81 0.000 5.630 423.811 0.000 0.361 Male 40

143 0.000 18.115 382.857 222.017 0.355 Male 88

40 0.000 7.292 728.369 2.320 0.342 Male 57

56 0.000 29.960 810.948 0.000 0.339 Male 50

70 0.000 9.059 924.720 18.642 0.331 Male 52

93 0.000 8.700 236.128 7.833 0.328 Male 66

165 0.000 0.000 876.848 10.644 0.305 Male 42

147 0.000 10.331 394.031 20.402 0.300 Male 42

27 0.000 15.852 904.824 1.740 0.297 Male 59

139 0.000 8.529 309.849 0.000 0.289 Male 28

76 0.000 5.224 776.754 0.926 0.283 Male 25

116 0.000 14.446 491.115 15.447 0.272 Male 51

134 0.000 6.230 1,461.243 31.083 0.271 Male 23

89 0.000 4.964 308.981 2.051 0.270 Male 54

160 0.000 1.566 754.685 22.801 0.264 Male 60

110 0.000 22.356 597.317 1.671 0.246 Male 32

29 0.000 2.688 1,038.700 1.396 0.234 Male 24

121 0.000 4.912 495.733 0.077 0.211 Male 30

92 0.000 13.209 635.283 18.469 0.128 Male 62

54 46.758 18.805 611.928 6.047 0.812 Male 42



Table S4a The information of 122 liver cirrhosis patients (test group)


66 0.000 25.480 750.370 7.247 0.770 Female 58

132 11.959 16.730 791.360 0.137 0.678 Female 66

88 40.886 17.747 756.035 63.879 0.674 Female 52

64 0.000 18.221 2,808.378 4.731 0.586 Female 60

111 0.000 20.965 806.361 151.712 0.584 Female 58

50 0.000 8.039 517.043 4.731 0.488 Female 68

109 0.000 5.481 1,767.259 113.406 0.470 Female 53

130 38.686 10.771 607.834 5.060 0.446 Female 58

97 0.000 9.132 371.566 66.681 0.439 Female 47

34 0.000 15.931 4,091.807 2.003 0.420 Female 57

113 23.837 5.865 799.924 14.529 0.402 Female 61

12 0.000 20.872 5,950.131 42.933 0.377 Female 56

131 29.390 9.690 2,284.608 2.372 0.374 Female 63

93 0.000 9.996 537.759 27.150 0.353 Female 52

28 0.000 12.159 1,389.649 0.000 0.320 Female 67

39 15.573 11.011 8,781.347 1.249 0.317 Female 58

36 0.000 8.862 687.157 0.000 0.309 Female 55

15 0.000 9.781 9,807.197 52.948 0.307 Female 34

17 0.000 11.154 3,213.889 37.136 0.276 Female 64

134 74.709 22.569 1,444.856 65.761 0.227 Female 44

25 11.067 17.448 6,662.214 33.222 0.730 Female 62

61 0.000 20.843 1,918.679 7.499 0.631 Female 61

44 0.000 11.341 3,559.411 0.000 0.537 Female 43

3 0.000 16.444 2,139.721 109.676 0.425 Female 69

42 0.000 21.064 3,182.935 8.757 0.386 Female 74

2 0.000 14.763 3,843.661 71.194 0.344 Female 55

128 19.319 16.054 10,257.127 0.089 0.330 Female 52

136 20.481 6.928 441.131 96.684 0.157 Female 56

86 0.000 14.928 634.315 148.098 0.736 Male 48

147 86.717 10.276 866.809 30.909 0.697 Male 51

59 0.000 8.972 746.686 0.094 0.566 Male 58

125 26.678 22.857 790.340 30.523 0.550 Male 71

30 18.953 13.942 3,593.142 1.788 0.537 Male 50

96 0.000 10.188 626.708 34.205 0.494 Male 61

92 0.000 12.398 3,653.862 1.139 0.485 Male 53

168 0.000 7.051 730.635 16.419 0.466 Male 57



107 31.144 14.736 4,670.679 20.631 0.451 Male 63

90 0.000 23.095 503.818 22.036 0.446 Male 37

77 0.000 3.125 328.540 3.006 0.443 Male 55

149 37.524 4.242 661.872 5.298 0.415 Male 39

20 0.000 153.755 2,824.100 7.284 0.375 Male 81

41 0.000 6.149 536.078 17.563 0.327 Male 51

116 0.000 7.466 686.982 0.000 0.269 Male 60

7 0.000 15.296 1,336.447 13.823 0.195 Male 40

114 0.000 7.098 493.870 61.342 0.165 Male 63

148 58.828 27.544 5,168.250 86.835 1.565 Male 48

68 0.000 19.825 596.252 0.000 0.919 Male 36

85 0.000 38.537 13,256.484 55.564 0.873 Male 83

115 150.484 21.077 3,670.743 19.226 0.711 Male 53

95 0.000 16.882 8,772.287 115.475 0.608 Male 59

45 0.000 8.316 767.562 189.195 0.526 Male 51

89 45.757 12.622 4,459.584 33.976 0.518 Male 49

84 0.000 12.959 695.760 105.751 0.513 Male 64

83 5.977 19.188 2,134.075 7.724 0.484 Male 63

35 1.678 78.515 4,407.081 4.302 0.464 Male 58

80 0.000 11.038 4,075.448 2.790 0.456 Male 69

119 35.203 4.055 926.606 38.065 0.396 Male 52

72 0.000 4.385 537.306 2.287 0.382 Male 53

102 0.000 13.487 857.857 263.322 0.283 Male 64

122 13.896 12.602 1,884.033 0.588 0.259 Male 62

156 35.200 6.013 620.069 9.365 0.461 Male 47



Table S4b The information of 122 liver cirrhosis patients (validation group)


144 84.393 14.929 612.932 53.989 0.389 Female 66

31 35.854 22.471 6,648.916 1.895 0.419 Female 56

158 20.093 8.444 843.869 12.719 0.349 Female 41

129 19.319 6.673 665.441 0.000 0.353 Female 57

159 14.670 19.687 401.877 4.870 0.375 Female 69

38 13.696 4.391 4,390.777 0.351 0.532 Female 56

123 12.346 10.261 694.499 23.946 0.314 Female 58

1 8.438 57.606 13,737.133 2.686 0.539 Female 62

127 6.923 12.152 556.345 1.397 0.276 Female 64

10 4.307 55.399 9,944.413 244.758 0.739 Female 67

26 4.307 14.332 12,638.712 2.758 0.503 Female 79

106 2.324 9.100 926.324 168.472 0.429 Female 58

108 1.512 21.174 10,330.802 41.274 0.634 Female 79

33 0.000 95.614 3,015.989 22.481 0.584 Female 64

73 0.000 12.878 732.563 2.898 0.488 Female 62

57 0.000 17.138 789.667 176.297 0.472 Female 56

164 0.000 7.203 910.142 4.170 0.454 Female 57

5 0.000 48.923 1,265.965 13.248 0.448 Female 80

51 0.000 10.887 848.613 115.078 0.440 Female 65

58 0.000 16.886 793.965 2.682 0.412 Female 68

13 0.000 11.544 5,664.016 13.284 0.278 Female 62

69 0.000 15.903 1,466.135 23.710 0.901 Female 77

60 0.000 53.580 1,309.998 15.658 0.842 Female 78

37 0.000 7.649 2,003.123 2.111 0.722 Female 60

65 0.000 6.754 2,124.246 1.927 0.521 Female 38

54 0.000 19.154 2,491.420 6.313 0.516 Female 76

100 0.000 7.786 1,080.498 11.193 0.509 Female 50

43 0.000 9.047 1,619.109 0.777 0.482 Female 56

121 7,087.474 45.786 2,327.570 4.442 0.551 Male 63

56 529.387 17.339 5,001.452 4.300 0.587 Male 55

135 155.277 11.762 791.870 57.486 0.246 Male 52

126 84.005 10.921 7,268.692 0.000 0.249 Male 65

137 63.476 15.769 694.499 55.374 0.733 Male 41

120 46.569 9.420 589.841 0.086 0.318 Male 48

19 33.225 15.193 4,705.558 54.897 0.676 Male 61

32 26.089 56.840 6,366.152 10.410 0.683 Male 59



22 13.320 193.434 4,003.065 281.905 0.599 Male 71

29 9.565 13.409 2,483.094 0.351 0.327 Male 77

11 5.433 12.774 2,646.735 19.858 0.621 Male 49

27 4.682 7.485 701.973 0.000 0.304 Male 58

105 3.947 3.399 1,976.577 1.534 0.174 Male 71

99 1.918 9.820 725.605 0.000 0.384 Male 60

162 0.961 187.848 10,392.088 37.033 1.954 Male 53

82 0.700 18.724 825.087 125.973 1.050 Male 46

87 0.294 9.820 1,356.832 3.773 0.375 Male 31

91 0.000 14.336 533.078 324.506 0.581 Male 60

46 0.000 51.457 645.373 134.265 0.569 Male 59

76 0.000 2.797 366.609 14.867 0.491 Male 56

75 0.000 5.620 291.699 0.274 0.469 Male 24

55 0.000 17.339 739.932 130.167 0.446 Male 65

101 0.000 9.180 755.449 22.519 0.443 Male 63

94 0.000 12.062 845.568 37.708 0.422 Male 29

79 0.000 5.796 1,029.354 2.215 0.400 Male 39

118 0.000 11.646 612.078 4.563 0.326 Male 55

71 0.000 11.895 601.164 35.859 0.309 Male 28

62 0.000 35.971 574.147 7.714 0.397 Male 64

110 0.000 51.260 1,465.170 67.278 0.338 Male 51

48 0.000 7.737 824.666 1.424 0.265 Male 50

98 52.840 39.656 631.885 6.032 0.200 Male 60

141 49.919 13.022 1,056.713 3.704 0.135 Male 58

103 51.440 9.932 1,608.696 17.075 0.572 Male 53



Table S5a The information of 244 hepatitis HCC (test group)


553 545.774 21.156 770.980 9.449 0.822 Female 61

625 0.000 34.861 2,334.766 7.940 0.764 Female 66

215 5,139.339 20.564 738.022 9.984 0.729 Female 61

205 0.000 252.200 282.390 13.529 0.695 Female 60

641 1,353.368 10.239 482.896 8.193 0.656 Female 60

166 0.000 15.244 341.524 7.952 0.621 Female 60

549 0.000 19.994 1,715.524 9.524 0.619 Female 62

548 11.712 12.761 1,783.750 2.914 0.605 Female 62

219 781.657 14.984 187.734 9.951 0.470 Female 59

158 57.593 18.964 2,396.014 20.125 0.446 Female 51

405 2,430.981 16.024 552.622 14.863 0.386 Female 35

660 12.794 2.033 2,245.969 27.692 0.363 Female 54

624 129.614 6.922 1,094.828 4.886 0.304 Female 67

645 4,673.718 9.103 434.008 3.709 0.286 Female 35

189 386.961 14.101 400.309 8.229 0.266 Female 60

571 5,963.545 48.031 12,111.739 70.245 1.571 Female 23

271 9,559.211 49.808 3,695.517 1.829 1.314 Female 51

175 0.000 52.577 526.249 44.585 1.120 Female 53

256 2,560.416 20.516 2,304.106 1.490 1.074 Female 57

28 71.590 18.400 673.209 10.364 0.974 Female 38

51 1,748.145 16.248 467.061 0.000 0.920 Female 52

482 1,151.405 18.790 3,324.837 10.040 0.829 Female 59

183 1,856.493 287.940 618.499 67.007 0.830 Female 56

597 0.000 13.276 1,648.955 9.989 0.521 Female 63

528 6,504.857 12.680 2,383.991 16.876 0.448 Female 53

105 117.866 19.286 360.675 5.440 0.809 Male 52

103 116.709 34.349 668.226 23.360 0.793 Male 50

177 185.529 174.699 770.911 48.421 0.791 Male 59

202 2,908.996 132.040 6,253.708 33.533 0.786 Male 57

591 77.380 12.795 934.489 11.626 0.761 Male 63

452 5,886.027 95.877 9,974.303 13.723 0.740 Male 41

551 5,035.737 18.670 596.368 34.794 0.721 Male 61

38 68.843 19.788 357.338 1.072 0.710 Male 56

223 0.000 15.126 358.596 11.541 0.681 Male 51

377 2,110.446 92.937 6,199.594 2.438 0.677 Male 58

638 15.399 15.270 842.041 54.896 0.664 Male 56



477 5,622.440 16.328 1,590.350 13.794 0.663 Male 45

442 278.796 34.689 1,690.819 9.185 0.655 Male 57

3 6,457.829 22.518 748.647 30.870 0.634 Male 35

99 3,577.713 14.260 482.519 13.418 0.623 Male 54

27 22.148 21.332 759.658 15.382 0.588 Male 49

557 476.144 12.537 10,369.306 10.588 0.582 Male 65

131 0.000 14.380 601.223 19.254 0.574 Male 59

479 21.536 6.344 499.056 12.582 0.568 Male 47

252 2,644.511 21.016 1,610.891 2.811 0.556 Male 53

208 0.000 8.976 655.398 15.748 0.551 Male 48

540 37.661 18.364 12,459.634 2.740 0.545 Male 60

303 0.000 20.168 1,204.981 0.169 0.542 Male 62

14 63.350 28.140 672.378 3.580 0.538 Male 58

275 6,387.175 61.427 8,111.757 10.195 0.522 Male 60

633 0.000 16.740 827.658 6.679 0.512 Male 45

546 6,887.685 11.580 1,643.010 2.864 0.504 Male 49

554 27.681 16.958 9,656.203 9.226 0.499 Male 70

110 47.043 17.555 1,416.192 0.837 0.491 Male 54

159 0.000 17.724 814.162 9.598 0.480 Male 48

140 108.080 21.816 4,109.390 7.904 0.475 Male 60

413 5,416.129 49.280 3,943.944 1.226 0.464 Male 53

651 25.691 7.664 3,760.865 12.804 0.462 Male 57

560 1.731 9.114 612.083 36.287 0.455 Male 61

55 5.668 11.730 349.025 0.000 0.445 Male 60

500 5.520 6.842 773.137 24.284 0.432 Male 54

511 0.000 2.527 828.489 14.507 0.430 Male 47

601 10.893 6.794 722.047 12.738 0.426 Male 58

555 17.700 15.064 1,704.274 19.228 0.421 Male 67

460 427.446 8.722 1,043.711 3.459 0.416 Male 55

567 60.284 16.571 697.061 123.702 0.414 Male 52

649 0.000 7.224 2,963.970 27.836 0.410 Male 51

647 0.000 8.012 1,154.634 18.336 0.404 Male 44

541 0.000 14.045 548.059 11.355 0.395 Male 44

588 12.766 10.989 667.584 8.292 0.363 Male 82

609 67.813 15.849 788.293 5.727 0.362 Male 56




527 0.000 8.462 894.955 33.432 0.354 Male 46

509 54.069 0.867 479.415 23.321 0.347 Male 63

612 0.000 9.460 845.436 13.573 0.338 Male 59

372 567.464 48.923 706.861 2.201 0.317 Male 39

592 194.434 23.411 4,312.584 10.272 0.307 Male 57

584 10.893 15.404 2,227.369 49.970 0.301 Male 59

596 110.155 96.378 20,084.400 19.205 0.299 Male 59

648 373.209 6.661 2,776.921 0.000 0.298 Male 66

613 0.000 7.990 823.849 5.783 0.289 Male 44

659 0.000 11.894 876.212 6.672 0.274 Male 52

582 0.000 9.303 847.717 16.436 0.265 Male 69

583 0.000 8.099 677.165 70.670 0.263 Male 50

570 428.541 5.951 700.031 13.021 0.258 Male 53

278 0.000 21.713 1,840.606 2.642 3.730 Male 45

21 9,797.067 195.955 1,708.972 355.697 2.633 Male 44

7 2.921 60.984 3,854.782 49.639 2.309 Male 50

190 9.770 135.316 678.661 20.088 2.238 Male 62

283 138.925 75.798 14,314.019 19.238 1.842 Male 40

59 7.972 129.682 4,795.568 18.890 1.725 Male 52

32 0.000 38.262 1,235.579 0.047 1.511 Male 55

136 0.000 51.914 453.519 137.894 1.495 Male 52

191 215.151 434.019 742.033 8.891 1.444 Male 55

58 6,094.917 97.200 5,485.909 9.234 1.398 Male 66

70 6,531.637 105.350 2,163.427 22.357 1.346 Male 60

197 6,102.796 156.701 1,691.291 6.805 1.231 Male 43

79 0.000 22.205 456.470 73.586 1.217 Male 61

181 3,087.239 343.843 406.726 16.245 1.197 Male 72

34 9,823.263 115.061 1,487.400 20.222 1.176 Male 38

139 102.806 0.000 576.877 3.160 1.141 Male 53

301 120.418 76.502 1,234.232 1.998 1.108 Male 56

114 1.077 34.375 1,154.684 2.822 1.024 Male 44

42 16.655 48.972 505.299 2.167 1.008 Male 50

85 71.595 13.032 334.625 2.809 0.968 Male 50

296 42.923 99.391 870.927 64.424 0.954 Male 63

146 254.268 71.919 4,562.507 12.018 0.945 Male 44




212 0.000 34.467 340.948 45.022 0.935 Male 60

68 4,451.586 39.734 4,399.074 18.431 0.926 Male 60

67 0.000 18.376 352.272 0.177 0.903 Male 50

398 0.000 13.756 3,484.362 32.309 0.900 Male 43

124 0.000 46.230 964.002 18.673 0.880 Male 45

259 10.536 57.183 1,214.695 26.935 0.854 Male 58

312 0.000 25.792 727.271 2.540 0.844 Male 57

407 56.071 124.458 3,782.968 18.166 0.837 Male 56

387 7.413 86.047 2,383.693 2.254 1.018 Male 56

563 161.421 70.705 5,493.725 20.317 0.808 Male 84

17 0.000 51.062 3,893.093 42.721 1.033 Male 60

199 0.000 45.361 764.494 15.450 0.800 Male 57

269 17.476 21.930 351.253 2.608 1.285 Male 78

173 858.104 20.280 630.531 16.941 1.299 Male 65

371 4,716.357 17.166 1,172.866 1.795 0.428 Male 73

84 0.000 14.340 183.371 1.430 0.343 Male 67

656 12.794 4.230 3,153.492 4.939 0.266 Male 59



Table S5b The information of 244 hepatitis HCC (validation group)


650 9,852.325 12.210 4,283.284 10.591 0.514 Female 44

47 9,633.117 18.021 614.191 0.000 0.764 Female 55

46 5,382.944 14.497 1,169.839 0.000 0.974 Female 42

69 4,984.456 16.111 2,242.602 3.769 0.642 Female 59

579 4,560.545 8.460 746.732 5.422 0.270 Female 67

31 903.122 155.249 7,233.668 10.753 1.037 Female 57

537 554.388 8.258 3,400.518 1.948 0.411 Female 63

569 456.925 6.774 713.819 13.728 0.423 Female 62

587 318.043 12.313 11,851.811 13.647 0.680 Female 49

247 184.034 12.468 529.449 3.014 0.446 Female 65

610 129.614 15.537 920.992 10.939 0.352 Female 63

307 126.202 8.814 896.832 3.658 1.439 Female 70

402 58.073 132.238 15,918.837 14.744 1.003 Female 71

606 24.940 6.874 1,219.911 1.542 0.309 Female 57

566 19.031 9.298 1,444.578 23.857 0.426 Female 63

43 16.655 96.260 226.833 1.354 1.146 Female 56

575 9.957 7.336 872.402 7.989 0.285 Female 64

453 9.024 10.769 864.200 0.000 0.420 Female 65

562 0.000 6.629 6,833.949 5.216 0.347 Female 59

62 59.375 60.795 311.097 1.765 2.049 Female 77

167 0.000 13.722 1,802.633 4.007 0.574 Female 34

644 4,831.734 11.063 4,400.320 5.026 0.718 Female 56

654 10,340.953 1.841 657.336 6.432 0.288 Male 54

306 9,504.523 83.511 5,806.052 21.382 1.333 Male 49

615 7,589.057 17.519 5,724.224 76.724 0.468 Male 56

82 6,428.845 32.986 494.283 27.011 0.453 Male 36

64 6,373.376 43.353 1,238.855 15.047 0.924 Male 62

37 6,232.097 104.771 818.198 1.708 1.259 Male 69

16 6,214.831 39.433 875.201 17.254 1.213 Male 45

273 6,209.024 20.951 744.541 19.238 1.223 Male 55

178 6,136.615 159.149 3,136.487 39.649 0.663 Male 45

187 6,071.655 273.419 4,300.544 5.844 0.928 Male 55

397 5,999.737 21.141 5,464.136 2.699 0.302 Male 43

507 5,575.943 66.806 4,566.809 76.817 0.725 Male 48

370 5,285.960 80.587 4,093.100 2.303 0.792 Male 63



116 5,149.800 48.661 1,802.633 2.313 0.460 Male 53

385 5,111.872 21.484 2,932.634 7.726 0.788 Male 67

382 5,069.321 13.204 766.521 1.535 0.295 Male 65

180 4,713.706 703.627 2,962.245 116.129 1.832 Male 46

475 4,499.951 6.427 965.083 8.211 0.538 Male 31

169 3,518.442 17.517 857.541 5.701 0.667 Male 59

100 3,446.153 39.274 666.546 15.214 1.119 Male 59

388 2,610.837 19.865 10,162.328 8.240 0.738 Male 56

489 2,296.835 11.958 708.857 1.440 0.619 Male 51

96 2,195.566 26.766 342.188 13.209 0.843 Male 57

639 1,865.760 13.756 674.008 29.225 0.362 Male 27

577 1,837.225 20.401 13,565.523 13.708 0.526 Male 50

78 1,661.705 10.208 259.838 24.279 0.415 Male 53

246 1,553.839 18.211 2,735.734 3.725 0.585 Male 64

446 1,372.806 10.520 478.522 1.986 0.365 Male 57

75 1,063.240 32.939 830.405 4.104 0.710 Male 45

461 733.012 12.567 12,522.107 14.483 0.479 Male 48

147 550.388 36.054 1,346.208 18.044 0.906 Male 57

547 541.150 10.316 855.376 9.672 0.301 Male 34

176 519.243 53.613 569.566 14.721 0.403 Male 53

576 477.239 19.977 1,929.334 31.040 0.701 Male 50

456 454.474 13.065 1,013.741 0.000 0.464 Male 44

519 415.595 12.476 3,443.506 7.593 0.483 Male 51

317 404.954 20.603 767.306 21.466 0.945 Male 46

565 359.038 10.235 839.661 144.788 0.338 Male 58

66 305.264 41.759 1,289.495 2.809 1.075 Male 68

392 267.832 30.417 6,689.392 8.830 1.384 Male 58

201 260.572 185.869 995.518 60.244 0.566 Male 53

12 247.384 11.872 369.806 51.479 0.470 Male 59

89 198.840 50.325 593.439 45.623 2.258 Male 44

184 192.441 551.973 6,795.512 11.740 0.825 Male 56

76 185.720 11.915 144.717 36.082 0.388 Male 58

53 178.714 67.456 499.480 2.450 2.363 Male 45

260 164.371 33.079 881.132 23.490 0.902 Male 57

196 152.945 70.806 0.000 8.925 0.612 Male 65




274 147.021 32.624 4,467.932 3.725 0.570 Male 44

134 136.715 34.583 1,371.196 17.293 1.120 Male 62

573 136.375 7.276 2,349.475 34.995 0.548 Male 48

310 133.141 21.734 737.476 1.321 0.772 Male 48

593 95.172 123.940 2,512.192 48.343 0.575 Male 56

148 80.199 24.664 804.114 11.727 1.180 Male 62

653 67.094 7.128 7,067.529 5.339 0.952 Male 52

360 45.236 23.070 474.499 0.508 0.432 Male 56

261 32.513 22.376 4,726.772 12.362 0.657 Male 53

77 31.877 50.151 256.477 36.130 1.551 Male 55

81 25.188 98.377 827.044 33.375 2.118 Male 44

74 25.188 17.196 356.473 3.477 0.498 Male 51

450 10.025 16.964 610.652 43.078 0.695 Male 45

585 9.957 6.734 673.425 18.518 0.262 Male 52

561 8.385 14.289 645.260 9.350 0.552 Male 52

126 6.352 59.547 6,736.497 48.009 1.509 Male 50

41 5.668 16.019 378.950 4.499 0.894 Male 48

165 4.845 10.904 539.545 14.631 0.761 Male 56

534 4.392 4.815 651.662 4.226 0.298 Male 57

425 4.019 15.056 477.629 0.000 0.359 Male 36

118 2.584 17.254 805.625 10.396 0.820 Male 54

594 0.000 24.314 1,531.477 18.154 3.502 Male 50

617 0.000 316.716 15,108.376 30.733 1.689 Male 72

539 0.000 74.438 2,992.270 144.788 1.471 Male 54

88 0.000 21.376 473.276 8.072 1.009 Male 48

447 0.000 56.567 911.517 4.813 0.963 Male 66

172 0.000 206.436 649.783 62.461 0.864 Male 63

614 0.000 28.599 875.912 10.266 0.844 Male 54

171 0.000 20.598 652.352 37.079 0.795 Male 49

30 0.000 18.778 766.308 0.000 0.655 Male 55

455 0.000 38.916 867.771 0.751 0.624 Male 57

599 0.000 17.391 761.693 8.292 0.623 Male 70

499 0.000 18.458 895.447 65.053 0.601 Male 62

162 0.000 11.712 506.271 8.460 0.544 Male 49

108 0.000 17.686 853.619 2.725 0.506 Male 59




163 0.000 11.130 289.584 1.394 0.501 Male 58

538 0.000 6.710 425.248 1.602 0.444 Male 63

396 0.000 18.430 846.344 2.960 0.405 Male 69

383 0.000 3.670 600.391 5.825 0.363 Male 59

564 0.000 6.608 382.759 34.513 0.305 Male 66

658 0.000 4.340 899.117 0.000 0.266 Male 64

605 0.000 8.119 737.756 2.249 0.265 Male 52

20 0.000 274.126 3,216.747 3.439 1.822 Male 69

44 123.779 121.444 300.813 4.146 0.890 Male 76

50 439.658 77.904 633.310 0.153 1.159 Male 55

130 70.403 47.763 4,285.802 12.187 1.028 Male 55

168 0.000 45.117 931.627 4.128 1.389 Male 61

611 0.000 21.927 3,670.746 17.888 0.548 Male 74

151 4,520.299 18.982 2,603.688 15.406 0.475 Male 73

107 0.000 15.188 722.958 5.798 0.528 Male 53

619 7,322.315 12.888 1,191.285 20.746 0.284 Male 61



996 subjects enrolled in Tianjin Medical University CancerInstitute and Hospital, Tianjin Third Central Hospital andTianjin Medical University General Hospital from July 2012to April 2014

75 excludedPrimary liver cancer other than HCC (27): ICC (23)and HCC-CC (4)Metastatic liver cancer (2)Other liver tumor such as sarcoma and adenoma,etc (11)Clinical data not available (35): HCC (34) and HBV(1)

921 subjects enrolled (all with values of AFP, AFU,GGT-II, GPC3 and HGF)

NBNC-HCC group Hepatitis-HCC group

HC NBNC-HCC CH LC Hepatitis-HCC

202 test cohort27 HCC175 HC

199 validation cohort27 HCC172 HC

266 test cohort

•

• •

•

• • •

• • • •

• •

• 82 CH61 LC

254 validation cohort121 HCC72 CH61 LC

202 ELISA testing at Tianjin MedicalUniversity Cancer Institute andHospital and the performance of thefive serum markers assessed by ROCanalysis

266 ELISA testing at Tianjin MedicalUniversity Cancer Institute andHospital and the performance of thefive serum markers assessed by ROCanalysis

Diagnostic exploration Diagnostic validation Diagnostic exploration Diagnostic validation

123 HCC

Figure S1 The study design. HC, healthy controls; CH, chronic hepatitis; LC, liver cirrhosis; HCC, hepatocellular carcinoma.


0 0.2 0.4

AUC = 0.98695% CI (0.958–0.997)

AUC = 0.91395% CI (0.866–0.968)

AUC = 0.98895% CI (0.962–0.998)

1-speci�city

Sens

itivi

ty

AFP + AFU + GGT-II + GPC3

AFP + GGT-II + GPC3 + HGF

AFP + AFU + GGT-II + HGF

0.6 0.8 1.0

0 0.2 0.41-speci�city

0.6 0.8 1.0

0 0.2 0.4

1-speci�city

0.6 0.8 1.0

0.2

0

0.4

0.6

0.8

1.0A

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0

C

AUC = 0.98395% CI (0.954–0.996)

AFU + GGT-II + GPC3 + HGF

0 0.2 0.4

1-speci�city

0.6 0.8 1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0

D

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0B

Figure S2 The 4 arrangements of serum biomarkers in the combination model. The sensitivity and specificity represented by the red dots were shown in detail below. (A). AFP + AFU + GGT-II + GPC3 sensitivity: 92.6% and specificity: 99.4%; (B). AFP + AFU + GGT-II + HGF sensi-tivity: 92.6% and specificity: 98.3%; (C). AFP + GPC3 + GGT-II + HGF sensitivity, 77.8% and specificity: 94.9%; (D). AFU + GPC3 + GGT-II + HGF sensitivity; 88.9% and specificity: 100.0%.


0 0.2 0.4

AUC = 0.98695% CI (0.959–0.997)

AUC = 0.83395% CI (0.774–0.881)

AUC = 0.91595% CI (0.868–0.950)

AUC = 0.98695% CI (0.959–0.997)

1-speci�city

Sens

itivi

ty

AFP + AFU + GGT-II

AFP + GGT-II + GPC3 AFP + GGT-II + HGF

AFP + AFU + GPC3

0.6 0.8 1.0

0 0.2 0.4

1-speci�city

0.6 0.8 1.0 0 0.2 0.4

1-speci�city

0.6 0.8 1.0

0 0.2 0.4

1-speci�city

0.6 0.8 1.0

0.2

0

0.4

0.6

0.8

1.0A

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0D

AUC = 0.97595% CI (0.943–0.992)

AFU + GGT-II + GPC3

0 0.2 0.4

1-speci�city

0.6 0.8 1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0G

AUC = 0.98395% CI (0.955–0.996)

AFU + GGT-II + HGF

0 0.2 0.4

1-speci�city

0.6 0.8 1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0H

AUC = 0.97495% CI (0.942–0.991)

AFU + GPC3 + HGF

0 0.2 0.4

1-speci�city

0.6 0.8 1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0I

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0E

AUC = 0.91495% CI (0.867–0.949)

AFP + GPC3 + HGF

0 0.2 0.4

1-speci�city

0.6 0.8 1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0F

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0B

AUC = 0.86895% CI (0.814–0.912)

GGT-II + GPC3 + HGF

0 0.2 0.4

1-speci�city

0.6 0.8 1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0C

Figure S3 The 3 arrangements of serum biomarkers in the combination model. The sensitivity and specificity represented by the red dots are shown in detail below. (A). AFP + AFU + GGT-II sensitivity: 92.6% and specificity: 100.0%; (B). AFP + AFU + GPC3 sensitivity: 92.6% and specificity: 98.9%; (C). GGT-II + GPC3 + HGF sensitivity: 74.1% and specificity: 89.1%; (D). AFP + GGT-II + GPC3 sensitivity: 63.0% and specificity: 98.3%; (E). AFP + GGT-II + HGF sensitivity: 77.8% and specificity: 94.9%; (F). AFP + GPC3 + HGF sensitivity: 77.8% and specificity: 95.4%; (G). AFU + GGT-II + GPC3 sensitivity: 88.9% and specificity: 100.0%; (H). AFU + GGT-II + HGF sensitivity: 88.9% and specificity: 98.9%; (I). AFU + GPC3 + HGF sensitivity: 85.2% and specificity: 97.7%.


0 0.2 0.4

AUC = 0.82695% CI (0.767–0.876)

AUC = 0.91695% CI (0.868–0.950)

AUC = 0.97595% CI (0.943–0.992)

AUC = 0.83895% CI (0.780–0.886)

1-speci�city

Sens

itivi

ty

AFP + GGT-II

AFP + HGF AFU + GGT-II

AFP + GPC3

0.6 0.8 1.0

0 0.2 0.4

1-speci�city

0.6 0.8 1.0 0 0.2 0.4

1-speci�city

0.6 0.8 1.0

0 0.2 0.4

1-speci�city

0.6 0.8 1.0

0.2

0

0.4

0.6

0.8

1.0A

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0D

AUC = 0.97495% CI (0.942–0.991)

AFU + HGF


0.6 0.8 1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0G

AUC = 0.83695% CI (0.777–0.884)

GGT-II + GPC3

0 0.2 0.4

1-speci�city

0.6 0.8 1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0H

AUC = 0.86895% CI (0.814–0.912)

GGT-II + HGF

0 0.2 0.4

1-speci�city

0.6 0.8 1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0I

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0E

AUC = 0.96695% CI (0.931–0.986)

AFU + GPC3

0 0.2 0.4

1-speci�city

0.6 0.8 1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0F

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0B

AUC = 0.76595% CI (0.700–0.822)

GPC3 + HGF

0 0.2 0.4

1-speci�city

0.6 0.8 1.0

Sens

itivi

ty

0.2

0

0.4

0.6

0.8

1.0C

Figure S4 The 2 arrangements of serum biomarkers in the combination model. The sensitivity and specificity represented by the red dots are shown in detail below. (A). AFP + GGT-II sensitivity: 63.0% and specificity: 98.3%; (B). AFP + GPC3 sensitivity: 59.3% and specificity: 98.3%; (C). GPC3 + HGF sensitivity: 59.3% and specificity: 83.4%; (D). AFP + HGF sensitivity: 77.8% and specificity: 94.9%; (E). AFU + GGT-II sensitivity: 88.9% and specificity: 100.0%; (F). AFU + GPC3 sensitivity: 85.2% and specificity: 98.9%; (G). AFU + HGF sensitivity: 88.9% and specificity: 94.9%; (H). GGT-II + GPC3 sensitivity: 81.5% and specificity: 72.5%; (I). GGT-II + HGF sensitivity: 74.1% and specificity: 87.4%.


0 0.2 0.4

AUC = 0.70795% CI (0.639–0.769)

AUC = 0.96995% CI (0.934–0.988)

1-speci�city

Sens

itivi

ty

AFP

0.6 0.8 1.0


0.6 0.8 1.0

0.2

0

0.4

0.6

0.8

1.0A

Sens

itivi

ty

0.2

0

0.4

0.6

AFP + AFU

0.8

1.0C

0 0.2 0.4

AUC = 0.94895% CI (0.907–0.974)

1-speci�city

Sens

itivi

ty

AFU

0.6 0.8 1.0

0.2

0

0.4

0.6

0.8

1.0B

Figure S5 The receiver operating characteristic curves of AFP (A) AFU (B) and AFP + AFU (C) in the detection of the NBNC-HCC validation group. The sensitivity and specificity represented by the red dots are shown in detail below. (A). AFP sensitivity: 51.9% and specificity: 97.7%; (B). AFU sensitivity: 74.1% and specificity: 96.5%; (C). AFP + AFU sensitivity: 88.9% and specificity: 94.8%.


0 0.2 0.4

AUC = 0.80995% CI (0.755–0.855)

1-speci�city

Sens

itivi

ty

AFP

0.6 0.8 1.0

0.2

0

0.4

0.6

0.8

1.0

A

0 0.2 0.4

AUC = 0.75895% CI (0.693–0.816)

1-speci�city

Sens

itivi

ty

AFP

0.6 0.8 1.0

0.2

0

0.4

0.6

0.8

1.0C

0 0.2 0.4

AUC = 0.84195% CI (0.790–0.884)

1-speci�city

Sens

itivi

ty

AFP + AFU

0.6 0.8 1.0

0.2

0

0.4

0.6

0.8

1.0E

0 0.2 0.4

AUC = 0.79195% CI (0.728–0.845)

1-speci�city

Sens

itivi

ty

AFP + AFU

0.6 0.8 1.0

0.2

0

0.4

0.6

0.8

1.0F

0 0.2 0.4

AUC = 0.67195% CI (0.602–0.736)

1-speci�city

Sens

itivi

ty

AFU

0.6 0.8 1.0

0.2

0

0.4

0.6

0.8

1.0D

0 0.2 0.4

AUC = 0.72795% CI (0.668–0.781)

1-speci�city

Sens

itivi

ty

AFU

0.6 0.8 1.0

0.2

0

0.4

0.6

0.8

1.0

B

Figure S6 The serum biomarkers AFP, AFU, and combination model of all-stage and early-stage hepatitis-hepatocellular carcinoma (HCC) in the validation cohort. (A), (B), and (E) show the AFP, AFU, and the combination model of all-stage hepatitis-HCC; (C), (D), and (F) show AFP, AFU, and the combination model of early-stage hepatitis-HCC. The sensitivity and specificity represented by the red dots are shown in detail below. (A). AFP sensitivity: 62.8% and specificity: 90.2%; (B). AFU sensitivity: 69.4% and specificity: 65.4%; (C). AFP sensitivity: 52.2% and speci-ficity: 90.2%; (D). AFU sensitivity: 56.5% and specificity: 65.4%; (E). AFP + AFU sensitivity: 71.9% and specificity: 86.5%; (F). AFP + AFU sensitivity: 75.4% and specificity: 73.7%.


0.0

0 20 40

AFU expression AFU expression

TCGA datasets-overall survival

IHC data-overall survival IHC data-overall survivalIHC data-diseasefree survival IHC data-diseasefree survival

TCGA datasets-overall survivalA

E F G H

B C DTCGA datasets-diseasefree survival TCGA datasets-diseasefree survival

LowHigh

AFU expressionLowHigh

AFU expression

LowHigh

LowHigh

AFP/AFU expressionLowHigh


AFP/AFUexpression

LowHigh


60Time (month)

Surv

ival

rate

Number at risk

Number at risk

Number at risk Number at riskLow 265 208 245142 83 134 58 29 13 4 064 33 37 17 616 5 1

99 108 119 48 26 13 6 2 140 22 10 3 121

1020 9 3 1 0High

Low 78 73 52 35 6104 63

4932

3522

2814

41

7810437 21 5

00High

Number at riskLowHigh

9442

6227

3917

65

00

11270

00


5823

4215

3210

41

00

11270


LowHigh

LowHigh

80 100

HR = 1.78 (1.24–2.56)

logrank P = 0.0014

HR = 2.319 (1.603–3.355)

logrank P < 0.0001

HR = 2.309 (1.630–3.271)

logrank P < 0.0001

HR = 1.609 (1.131–2.289)

logrank P = 0.007

HR = 1.831 (1.309–2.562)

logrank P < 0.0001

HR = 1.95 (1.40–2.73)

logrank P = 6.6e–05

HR = 1.66 (1.17–2.36)

logrank P = 0.004

HR = 1.55 (1.12–2.16)

logrank P = 0.0083

120

0 20 40 60Time (month)

80 100 0 20 40 60Time (month)

80 100 0 20 40 60Time (month)

80 100 0 20 40 60Time (month)

80 100

0 20 40 60Time (month) Time (month)

80 100 120 0 20 40 60 80 100 120Time (month)

0 20 40 60 80 100 120

0.2

0.4

0.6

0.8

1.0

0.0

Surv

ival

rate

0.2

0.4

0.6

0.8

1.0

0.0

0.2

0.4

0.6

0.8

1.0

0.0

0.2

0.4

0.6

0.8

1.0

0.0

0.2

0.4

0.6

0.8

1.0

0.0

0.2

0.4

0.6

0.8

1.0

0.0

0.2

0.4

0.6

0.8

1.0

0.0

0.2

0.4

0.6

0.8

1.0

Number at risk176 70 31 11 3 1 0140 35 16 9 4 2 1

LowHigh

Figure S7 The AFU and AFP/AFU combination model for predicting hepatocellular carcinoma (HCC) prognosis. (A), (B) The survival curves [overall survival (OS) and disease-free survival (DFS)] of HCC patients with different expressions of AFU based on The Cancer Genome Atlas (TCGA) database. (C), (D) The survival curves (OS and DFS) of HCC patients with different expressions of AFP/AFU based on TCGA database. (E), (F) The survival curves (OS and DFS) of HCC patients with different expressions of AFU based on our immunohistochemistry (IHC) data. (G), (H) The survival curves (OS and DFS) of HCC patients with different expressions of AFP/AFU based on our IHC data.

Documents

Diagnostic value of 5 serum biomarkers for hepatocellular