Fig. 1

High expression of SGOL2 in HCC. A SGOL2 was overexpressed in HCC in Wurmbach liver database. B Protein expression of SGOL2 was elevated in HCC patients in HPA database. C Immunoblot analysis of SGOL2 in HCC samples and paracancerous tissues from patients in cohort 2, and GAPDH was used as a loading control. D-F SGOL2 staining of paired clinical specimens, and the statistic quantification results in cohorts 1 and 2(n = 202). Protein expression of SGOL2 in the poorly differentiated group was significantly higher than that in the well-differentiated group of cohort 2. G TCGA dataset analysis of the relationship between the SGOL2 expression levels and the prognosis of HCC patients (n = 364). H Overall survival (OS) analysis of HCC patients with high SGOL2 expression or low SGOL2 expression in cohort 1 (n = 100). I-J Identification of the optimal penalization coefficient lambda (λ) in the Lasso model in cohort 1. K The nomogram based on SGOL2 for predicting the prognosis of HCC patients in cohort 1. L ROC curve analysis was used to evaluate the performance of this nomogram for 3-year overall survival prediction in the training and validation groups. OS, overall survival; RFS, relapse-free survival; PFS, progression-free survival; DSS, disease-specific survival; HR, hazard ratio. The results are presented as the mean ± SD, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001