High expression of CDK19 in HCC
CDK19 is a cyclin-dependent transcription-regulating kinase. Both CDK19 and its homolog CDK8, being termed as ‘Mediator Kinase’, have been shown to play crucial roles in cellular homeostasis and to be related with several diseases. Based on Oncomine, we evaluated the expression of CDK19 in HCC from 4 GEO datasets (Roessler liver, Roessler liver 2, Chen liver, and Wurmbach liver) [26-28]. As a result, the expression of CDK19 in HCC tissues was significantly upregulated. For example, CDK19 showed 1.71-fold increases in the Roessler liver datasets (Figure 1A). The difference of CDK19 expression across these four studies was significant, indicating that there may be to some extent inter-patient variations existed. (P＜0.05) (Figure 1B). We next investigated the protein expression of CDK19 in HCC by using HPA database. As shown in Figure 1C, CDK19 was hardly detected in a normal liver tissue (Patient ID 2556), but from a liver tumor tissue (Patient ID 2177) it showed quite strong signal (Figure 1C).
To further explore the inter-patient variations of CDK19, we studied the expression patterns of CDK19 in TCGA-LIHC by using UALCAN, according to several different clinical features. As shown in Figure 2A, CDK19 had much higher expression in LIHC patients (n=371) than in normal control group (n=50) (Figure 2A). While clustering the patients into different subgroups based on their age, gender, race and weight, we can observe differential expression profiles (Figure 2B-2E). For example, the expression difference would not be significant between the control and patients at the age of 81-100 Yrs. Besides, there was seemingly a correlation between CDK19 expression and different tumor severity (Figure 2F-2H). Among it, the difference of patients between stage 1 and stage 3 was quite obvious (P=0.0021). Considering that TP53 is one of the most commonly mutated genes in HCC, we found that there may be a correlation link between TP53 and CDK19. Intriguingly, CDK19 was accumulated much more in patients with TP53 mutation than others, p=0.00012 (Figure 2I).
Survival results and multivariate analysis in HCC
We evaluated the prognostic significance of CDK19 in 364 patients using the Kaplan‐Meier Plotter database. We found that the higher the expression of CDK19, the worse the overall survival (OS, HR = 1.55, log‐rank P = 1.8E-2) in HCC patients (Figure 3A). The prognostic value of CDK19 in different clinical subgroups of HCC was investigated. The results indicated that OS was relatively poor in patients with high CDK19 mRNA expression, under the conditions of stage 2-3, stage 3-4, grade 2, male sex, Asian race, alcohol consumed and non‐hepatitis virus infected (Figure 3B-3H). Collectively, CDK19 expression level can serve as a valuable prognostic biomarker in HCC patients and the prognostic significance varies depending on different clinical subgroups, which can guide our clinical practice in a personized pattern.
Mutations of CDK19 in HCC
Next, we investigated mutation landscape of CDK19 in a large number of HCC patients by using cBioPortal software. Overall, 1000 samples from 998 patients allocated in five studies (AMC, INSERM, RIKEN, MSK and TCGA‐PanCancer Atlas) were selected for analysis [29-33]. From our datamining, 8 alterations of CDK19 were found, with one missense mutation which appeared in early HCC (Figure 4A). And the somatic mutant frequency of CDK19 was around 1% (Figure 4B). However, CDK19 somatic status can not be used to distinguish the OS in HCC patients (Figure 4C). In addition, we used COSMIC database to verify the mutation of CDK19 in HCC. There were only 9 mutations from 951 tissues (somatic mutation frequency: 0.95%) and the only type of mutations was missense substitution (Figure 4D). The substitution mutations solely occurred at C＞A (100%) (Figure 4E).
The relationship between CDK19 and immune infiltrates in HCC
To investigate the correlation between CDK19 and immune infiltrates, we used TIMER online tool. The relationships between 6 immune cell types (B cell, CD8+T cells, CD4+ T cells, macrophage, neutrophil and myeloid dendritic cell) and CDK19 expression were determined by Spearman tests (tumor purity adjusted, Figure 5A). It revealed that CDK19 was significantly in positive correlation with these 6 immune infiltrates, especially macrophage (R=0.48) and myeloid dendritic cell (R=0.458) (Figure 5B-5G). Then it inspired us to further research if there may be a potential association between CDK19 and immune cell gene markers. Similar to the findings above, CDK19 had positive correlations with the respective gene markers of those 6 immune cells (Table 1). Among the listed gene markers, QRSL1 (R=0.700), IRF5 (R= 0.483), STAT1 (R= 0.469), NRP1 (R=0.469) and PTGS2 (R=0.467) are most relevant ones (Table 1).
The genes correlated with CDK19 in HCC
We investigated the genes correlated with CDK19 using LinkedOmics software. As the volcano map showed (Figure 6A), the negatively and positively related genes were located to the left and right areas, respectively. The top 50 positively and negatively related genes were identified based on Spearman test, and were shown in heatmap separately (Figure 6B-6C). To address whether there is some hub genes existed, we input the top 200 positively related genes with CDK19 into the STRING online database and cytoscape software. Based on gene degree, the 10 most relevant hub genes were obtained, including CEP135, CEP162, CEP192, CEP290, CNTRL, HAUS6, IQCB1, NEDD1, TCTN2 and WDHD1 (Figure 6D). We were surprised to find that almost all Hub genes are directly involved in cell division and regulation of G2/M transition of mitotic cell cycle. The correlations between CDK19 and the 10 hub genes were validated by using GEPIA web-tool (Supplementary Figure 1). Lastly, we found that 8 of the 10 top hub genes presented excellent prognostic value in HCC (Figure 6E), especially IQCB1 (HR=2.05) and NEDD1 (HR=1.93) (Figure 6E).
PPI and KEGG/GO enrichment of CDK19 in HCC
By utilizing the STRING software, we constructed a protein-protein interaction (PPI) network based on the top 200 significantly related genes (Figure 7A). As shown in the network, CDK19 can directly interact with MED23 and CNOT2, through which further interact with other proteins. As we all know, MED23 and CNOT2 are both involved in regulation of gene expression and transcription. Meanwhile, we also found a lot of proteins in the network took part in tumor development, including PHIP driving glioblastoma motility and invasion, HDAC2 regulating breast cancer progression and proliferation and ZFN292 participating hepatoma proliferation and vasculogenic mimicry.
Then, we investigated the GO/KEGG enrichment signaling pathways, which CDK19 may be involved in. GO biological process analysis of CDK19 showed that binding to transcription cofactors, regulations of transcription factors and mRNA were significantly affected and enriched (Figure 7B). KEGG pathway enrichment showed that CDK19 is mainly involved in mitosis through different ways (Figure 7C).
CDK19 involved in several cellular functions of hepatic tumor cell lines
To validate the findings related with CDK19 from bioinformatics analysis, we chose two independent hepatic cell lines, Hep.G2 and SK-Hep-1, as our in-vitro models. Here, small hairpin RNA (shRNA) based method was utilized to knock down CDK19, and the lentivirus containing sh-CDK19 was employed as the transgene delivery tool. Firstly, after 48h of lentivirus infection, we isolated mRNA from the cells, and performed qPCR to check the CDK19 level. As shown in Figure 8A, CDK19 was knocked down successfully in both cell lines, comparing with non-targeting control (NC). To address if CDK19 is involved in cell growth, we next conducted cell viability assay. In comparison to the control, knocking-down of CDK19 clearly inhibited the proliferation of both SK-Hep-1 and Hep.G2 cells (Figure 8B).
As suggested from the bioinformatics analysis, CDK19 may have relations with migration and invasion abilities, directly or indirectly through interaction with other invasion-relevant proteins. Aiming to validate its involvement in migration, wound healing assay was performed in the two cell lines. As seen from Figure 8C, much less tumor cells can migrate while comparing with the control. In order to conform CDK19 has contributions to invasion ability, we did transwell invasion assay to the cell lines. Similar as above, knocking-down of CDK19 can significantly decrease the amount of invaded tumor cells (Figure 8D).
Taken together, knocking-down of CDK19 can decrease the proliferation, migration and invasion abilities of hepatic tumor cells, indicating that CDK19 may serve as a promising therapeutic target in HCC.