High expression of aurora kinase B predicts poor prognosis in hepatocellular carcinoma after curative surgery and its effects on the tumor microenvironment

Microcystin-LR activates serine/threonine kinases and alters the phosphoproteome in human HepaRG cells

Microcystin-LR (MCLR) exposure has been associated with development of hepatocellular carcinoma (HCC). Many of the carcinogenic mechanisms for MCLR have been attributed to the induction of cell survival and proliferation through altered protein phosphorylation pathways by inhibition of protein phosphatases 1 (PP1) and PP2A. The current study determined MCLR effects on the phosphoproteome in human HepaRG cells. Differentiated HepaRG cells were treated with either vehicle or MCLR followed by phosphoproteomic analysis and Western blotting of MAPK-activated proteins. MCLR decreased cell viability at 24 h at doses as low as 0.03 μM. MCLR also caused a dose-dependent increase in phosphorylation of signaling and stress kinases. The number of decreased phosphosites by 0.1 μM MCLR was similar between the 2 h (212) and 24 h (154) timepoints. In contrast, a greater number of phosphosites were increased at 24 h (567) versus the 2 h timepoint (136), indicating the hyperphosphorylation state caused by MCLR-mediated inhibition of PPs is time-dependent. A kinase perturbation analysis predicted that MCLR exposure at both 2 h and 24 h increased the function of aurora kinase B (AURKB), checkpoint kinase 1 (CHEK1), and serum and glucocorticoid-regulated kinase 1 (SGK1). STRING database analysis of the phosphosites altered by MCLR exposure revealed pathways associated with cell proliferation and survival, including ribosomal protein S6 kinase (RSK), and vascular endothelial growth factor receptor (VEGFR2)-mediated vascular permeability. In addition, several cancer-related KEGG pathways were enriched at both 2 h and 24 h timepoints, and multiple cancer-related disease-gene associations were identified at the 24 h timepoint. Many of the kinases and pathways described above play crucial roles in the development of HCC by affecting processes such as invasion and metastasis. Overall, our data indicate that MCLR-mediated changes in protein phosphorylation involve biological pathways related to carcinogenesis that may contribute to the development of HCC.

LINC01134: a pivotal oncogene with promising predictive maker and therapeutic target in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) represents a leading and fatal malignancy within the gastrointestinal tract. Recent advancements highlight the pivotal role of long non-coding RNAs (lncRNAs) in diverse biological pathways and pathologies, particularly in tumorigenesis. LINC01134, a particular lncRNA, has attracted considerable attention due to its oncogenic potential in hepatoma. Current research underscores LINC01134's potential in augmenting the onset and progression of HCC, with notable implications in drug resistance. This review comprehensively explores the molecular functions and regulatory mechanisms of LINC01134 in HCC, offering a fresh perspective for therapeutic interventions. By delving into LINC01134's multifaceted roles, we aim to foster novel strategies in HCC management.

Overexpression of Aurora Kinase B Is Correlated with Diagnosis and Poor Prognosis in Hepatocellular Carcinoma

Aurora kinase B (AURKB) overexpression promotes tumor initiation and development by participating in the cell cycle. In this study, we focused on the mechanism of AURKB in hepatocellular carcinoma (HCC) progression and on AURKB's value as a diagnostic and prognostic biomarker in HCC. We used data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) to analyze AURKB expression in HCC. We found that the expression levels of AURKB in HCC samples were higher than those in the corresponding control group. R packages were used to analyze RNA sequencing data to identify AURKB-related differentially expressed genes (DEGs), and these genes were found to be significantly enriched during the cell cycle. The biological function of AURKB was verified, and the results showed that cell proliferation was slowed down and cells were arrested in the G2/M phase when AURKB was knocked down. AURKB overexpression resulted in significant differences in clinical symptoms, such as the clinical T stage and pathological stage. Kaplan-Meier survival analysis, Cox regression analysis, and Receiver Operating Characteristic (ROC) curve analysis suggested that AURKB overexpression has good diagnostic and prognostic potential in HCC. Therefore, AURKB may be used as a potential target for the diagnosis and cure of HCC.

New Opportunities in the Systemic Treatment of Hepatocellular Carcinoma-Today and Tomorrow

Hepatocellular carcinoma (HCC) is the most common primary liver cancer. Liver cirrhosis, hepatitis B, hepatitis C, and non-alcoholic fatty liver disease represent major risk factors of HCC. Multiple different treatment options are available, depending on the Barcelona Clinic Liver Cancer (BCLC) algorithm. Systemic treatment is reserved for certain patients in stages B and C, who will not benefit from regional treatment methods. In the last fifteen years, the arsenal of available therapeutics has largely expanded, which improved treatment outcomes. Nevertheless, not all patients respond to these agents and novel combinations and drugs are needed. In this review, we aim to summarize the pathway of trials investigating the safety and efficacy of targeted therapeutics and immunotherapies since the introduction of sorafenib. Furthermore, we discuss the current evidence regarding resistance mechanisms and potential novel targets in the treatment of advanced HCC.

Construction of a hepatocytes-related and protein kinase-related gene signature in HCC based on ScRNA-Seq analysis and machine learning algorithm

With recent advancements in single-cell sequencing and machine learning methods, new insights into hepatocellular carcinoma (HCC) progression have been provided. Protein kinase-related genes (PKRGs) affect cell growth, differentiation, apoptosis, and signaling during HCC progression, making the predictive relevance of PKRGs in HCC highly necessary for personalized medicine. In this study, we analyzed single-cell data of HCC and used the machine learning method of LASSO regression to construct PKRG prediction models in six major cell types. CDK4 and AURKB were found to be the best PKRG prognostic signature for predicting the overall survival of HCC patients (including TCGA, ICGC, and GEO datasets) in hepatocytes. Independent clinical factors were further screened out using the COX regression method, and a nomogram combining PKRGs and cancer status was created. Treatment with Palbociclib (CDK4 Inhibitor) and Barasertib (AURKB Inhibitor) inhibited HCC cell migration. Patients classified as PKRG high- or low-risk groups showed different tumor mutation burdens, immune infiltrations, and gene enrichment. The PKRG high-risk group showed higher tumor mutation burdens and gene set enrichment analysis indicated that cell cycle, base excision repair, and RNA degradation pathways were more enriched in these patients. Additionally, the PKRG high-risk group demonstrated higher infiltration levels of Naïve CD8+ T cells, Endothelial cells, M2 macrophage, and Tregs than the low-risk group. In summary, this study established the hepatocytes-related PKRG signature for prognostic stratification at the single-cell level by using machine learning algorithms in HCC and identified potential HCC treatment targets based on the PKRG signature.