Fig. 1: High SPAK expression is associated with poor prognosis and immune exhaustion in HCC.

a A differential expression analysis of 514 protein kinases was performed on the TCGA-LIHC (top) and ICGC-LIRI (bottom) datasets. A Venn diagram was used to visualize the overlap of upregulated genes between the two datasets. HCC samples were classified into three subtypes using NTP, and the expression of 14 genes was compared across these TME subtypes. b The correlation between T cell exhaustion scores and the expression of SPAK and PTK7 was analyzed. c wide-range data mining was employed to examine differences in SPAK mRNA expression between HCC tumor and adjacent non-tumor tissues. d IHC analysis was conducted on SPAK protein expression in a TMA containing HCC cases (n = 119 patients, scale bars, 400  μm (L), 100 μm (R)). e SPAK mRNA expression was quantified by qRT-PCR in paired fresh HCC tissue samples (n = 116 patients). f SPAK protein expression was quantified by immuneblotting in paired fresh HCC tissue samples (n = 144 patients). g Kaplan-Meier survival analysis was performed to investigate the relationship between SPAK expression and OS (n = 107 patients) as well as DFS (n = 111 patients) in HCC patients. h A forest plot was used to display the results of a multivariate analysis identifying factors associated with OS and DFS; a P values were calculated using Empirical Bayes moderated linear model and Negative binomial generalized linear model. b P values were calculated using a Spearman correlation analysis (two-tailed). d, f P values were calculated using a paired t test (two-tailed). g P values were calculated using a Kaplan–Meier test (two-tailed). h P values were calculated using a Partial Likelihood Estimation. Source data are provided as a Source Data file.