Clinical and Translational Research
Copyright ©The Author(s) 2024.
World J Clin Cases. Aug 26, 2024; 12(24): 5568-5582
Published online Aug 26, 2024. doi: 10.12998/wjcc.v12.i24.5568
Table 1 Correlation between key genes and prognosis of hepatocellular carcinoma patients
CharacteristicTotal, nUnivariate analysis

Multivariate analysis

Hazard ratio (95%CI)
    P value
Hazard ratio (95%CI)
P value
ATIC3391.042 (1.027-1.058)    < 0.0011.011 (0.989-1.033)0.348
EZH23391.196 (1.128-1.269)    < 0.0011.087 (1.006-1.174)0.035
HDGF3391.010 (1.006-1.014)    < 0.0011.004 (0.999-1.026)0.104
HEXB3391.027 (1.014-1.039)    < 0.0011.013 (0.999-1.026)0.060
HSPA43391.040 (1.023-1.058)    < 0.0011.017 (0.996-1.039)0.117
NRAS3391.066 (1.042-1.091)    < 0.0011.031 (1.003-1.059)0.032
PPT13391.030 (1.019-1.041)    < 0.0011.004 (0.988-1.020)0.665
Table 2 Relationship between risk score and clinicopathological parameters in hepatocellular carcinoma patients
Variables
Total, n = 339
Risk score-low, n = 170
Risk score-high, n = 169
P value
Age61.000 (51.000, 68.000)62.000 (52.000, 69.000)59.000 (51.000, 67.000)0.083
Sex0.310
Female107 (31.6%)58 (34.1%)49 (29.0%)
Male232 (68.4%)112 (65.9%)112 (71.0%)
Stage0.876
S1+S2252 (74.3%)127 (74.7%)125 (74.0%)
S3+S487 (25.7%)43 (25.3%)44 (26.0%)
Grade0.457
G1+G2212 (62.5%)103 (60.6%)109 (64.5%)
G3+G4127 (35.5%)67 (39.4%)60 (35.5%)
Table 3 Correlation between risk scores in clinical features and hepatocellular carcinoma prognosis
Characteristic
Total, n
Multivariate analysis
Hazard ratio (95%CI)
P value
Risk score3395.339 (3.139-9.078)< 0.001
Age3391.018 (1.002-1.034)0.028
Sex3391.010 (1.006-1.014)0.172
Grade3391.113 (0.744-1.664)0.603
Stage3390.888 (0.579-1.363)0.588
Table 4 Binding energy between EZH2 and four chemotherapy drugs in molecular docking
Medicine
Hub targets (PDB ID)
Binding energy in kcal/mol
BelinostatEZH2 (5h14)-4.58
BRD-K34222889EZH2 (5h14)-4.23
CiclopiroxEZH2 (5h14)-4.07
Cytarabine hydrochlorideEZH2 (5h14)-1.75
Table 5 Difference in the area under the curves of EZH2, NRAS, and the risk score in diagnosing hepatocellular carcinoma
Name
EZH2
NRAS
Risk score
EZH2/< 0.05< 0.05
NRAS< 0.05/< 0.05
Risk score< 0.05< 0.05/
Table 6 Results of predicting EZH2 in the training set and validation set based on the logistic and random forest classifier algorithm
Classification model
AUC
Accuracy
Sensitivity
Specificity
F1 score
ValidationLogistic0.792 0.6670.800 0.833 0.833
Random Forest0.8120.750 1.000 0.750 0.833
TrainingLogistic0.787 0.750 0.679 0.881 0.744
Random Forest1.0000.938 1.000 1.0001.000