AURKB as a Promising Prognostic Biomarker in Hepatocellular Carcinoma

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.

Identification and immune landscape analysis of fatty acid metabolism genes related subtypes of gastric cancer

Fatty acid metabolism (FAM) is associated with prognosis and immune microenvironment remodeling in many tumors. It is currently unknown how FAM affects the immunological microenvironment and prognosis of Gastric cancer (GC). Therefore, the current work aims to categorize GC samples based on the expression status of genes involved in FAM and to identify populations that might benefit from immunotherapy. In total, 50 FAM genes associated with overall survival (OS) were determined through univariate Cox proportional hazard regression analysis by mining the public TCGA and GEO databases. The GSE84437 and TCGA-STAD cohort samples were divided into two clusters using the "NMF" R package. According to the survival curve, patients in Cluster-1 showed considerably longer OS than those in Cluster-2. Patients in Cluster-1 exhibited earlier T stages, more intestinal GCs, and were older. MSI molecular subtypes were mainly distributed in Cluster-1, while GS molecular subtypes were distributed primarily in Cluster-2. There were 227 upregulated and 22 down-regulated genes (logFC > 1 or logFC < - 1, FDR < 0.05) in Cluster-2 compared with Cluster-1. One hub module (edges = 64, nodes = 12) was identified with a module score of 11.636 through Cytoscape plug-in MCODE. KEGG and GO analysis showed that the hub genes were associated with the cell cycle and cell division. Different immune cell infiltrates profile, and immune pathway enrichment existed between the subtypes. In conclusion, the current findings showed that practically all immunological checkpoint and immunoregulatory genes were elevated in patients with Cluster-2 GC, indicating that FAM subtypes may be crucial in GC immunotherapy.

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.

Comparative RNA-Sequencing Analysis Reveals High Complexity and Heterogeneity of Transcriptomic and Immune Profiles in Hepatocellular Carcinoma Tumors of Viral (HBV, HCV) and Non-Viral Etiology

Background and Objectives: Hepatocellular carcinoma (HCC), the most common type of primary liver cancer, is the leading cause of cancer-related mortality. It arises and progresses against fibrotic or cirrhotic backgrounds mainly due to infection with hepatitis viruses B (HBV) or C (HCV) or non-viral causes that lead to chronic inflammation and genomic changes. A better understanding of molecular and immune mechanisms in HCC subtypes is needed. Materials and Methods: To identify transcriptional changes in primary HCC tumors with or without hepatitis viral etiology, we analyzed the transcriptomes of 24 patients by next-generation sequencing. Results: We identified common and unique differentially expressed genes for each etiological tumor group and analyzed the expression of SLC, ATP binding cassette, cytochrome 450, cancer testis, and heat shock protein genes. Metascape functional enrichment analysis showed mainly upregulated cell-cycle pathways in HBV and HCV and upregulated cell response to stress in non-viral infection. GeneWalk analysis identified regulator, hub, and moonlighting genes and highlighted CCNB1, ACTN2, BRCA1, IGF1, CDK1, AURKA, AURKB, and TOP2A in the HCV group and HSF1, HSPA1A, HSP90AA1, HSPB1, HSPA5, PTK2, and AURKB in the group without viral infection as hub genes. Immune infiltrate analysis showed that T cell, cytotoxic, and natural killer cell markers were significantly more highly expressed in HCV than in non-viral tumors. Genes associated with monocyte activation had the highest expression levels in HBV, while high expression of genes involved in primary adaptive immune response and complement receptor activity characterized tumors without viral infection. Conclusions: Our comprehensive study underlines the high degree of complexity of immune profiles in the analyzed groups, which adds to the heterogeneous HCC genomic landscape. The biomarkers identified in each HCC group might serve as therapeutic targets.

The role of AURKA/miR-199b-3p in hepatocellular carcinoma cells

BACKGROUND

Previous studies proved that AURKA functions as an oncogene in several cancers. This article aimed to probe the miRNA-induced regulatory mechanism of AURKA in hepatocellular carcinoma (HCC).

METHODS

Differentially expressed genes in TCGA-LIHC dataset were screened by bioinformatics methods. Levels of miR-199b-3p and AURKA mRNA were examined by qRT-PCR. Western blot was utilized to evaluate protein levels of AURKA, p-AKT, and AKT. Dual-luciferase assay was introduced to explore their interaction. MTT, colony formation, scratch healing, transwell, and flow cytometry assays were introduced into cell proliferation, migration, invasion, and apoptosis assessment. The impact of miR-199b-3p/AURKA axis on HCC tumor growth was determined in a tumor xenograft model.

RESULTS

We found that AURKA was highly expressed in HCC and was coupled to poor prognosis of HCC. As manifested by cellular assays, compared to the normal cells HL-7702, AURKA presented notably high expression in HCC cell lines. Overexpressed AURKA evidently impelled the proliferation, colony formation, migration, and invasion of HCC cells while suppressing apoptosis. The regulatory gene upstream of AURKA was predicted to be miR-199b-3p by bioinformatics method, and there was a markedly negative correlation between the two. Overexpressed miR-199b-3p constrained HCC cell proliferation, migration, and invasion while fostering apoptosis, which could be counteracted by upregulating AURKA. MiR-199b-3p repressed the tumor growth in vivo by targeting AURKA and affected PI3K/AKT signaling pathway.

CONCLUSION

To summarize, this study implied the regulatory mechanism of miR-199b-3p/AURKA axis in HCC, and supplied optional therapeutic targets for HCC patients.

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

BACKGROUND

Currently, the only broadly used biomarker for hepatocellular carcinoma (HCC), alpha fetoprotein (AFP), has multiple limitations and the need for novel biomarkers is urgent. Aurora kinase B (AURKB) is a key mitotic protein kinase which performs a critical function in cell cycle progression. Nonetheless, neither the function nor the mechanism of AURKB in HCC following curative surgery is fully grasped at this time. This study sought to evaluate the impact of AURKB on prognosis and the tumor immune microenvironment (TIME) in HCC.

METHODS

We evaluated both the expression profile of AURKB in HCC and its clinical value using online databases and clinical specimens. The prognostic value of AURKB was studied by Kaplan-Meier survival analysis, and the link between AURKB and tumor-infiltrating immune cells (TIICs) were analyzed.

RESULTS

We found the mRNA expression patterns of AURKB were remarkably upregulated in HCC in contrast with adjoining normal tissues (P<0.001). Upregulation of the AURKB protein in HCC was additionally verified by clinical samples. The expression of AURKB was substantially associated with Child-Pugh, microvascular invasion (MVI), Edmondson-Steiner grade, and tumor recurrence. Furthermore, patients diagnosed with HCC who had a low AURKB expression had a better. Our data suggested age [hazard ratio (HR): 1.34], alanine aminotransferase (ALT) (HR: 1.65), tumor size (HR: 1.99), mor number (HR: 1.60), MVI (HR: 1.93), grade (HR: 5.58), and AURKB expression (HR: 3.63) independently functioned as prognostic risk indicators for HCC (P<0.05). Importantly, we also found AURKB expression was inversely linked to resting natural killer (NK) cells, M2 macrophages, activated mast cells, and naive B cells, and positively linked to M0 macrophages, T follicular helper cells (Tfh), regulatory T cells (Treg), and resting myeloid dendritic cells. In addition, AURKB expression was also positively linked to the immune checkpoints of PDCD1, CD274, CTLA4, and LAG3. Finally, 1,696 DEGs were discovered, and were predominantly implicated in chromosome segregation, cell cycle, xenobiotic metabolic process, calcium signaling pathway, bile secretion, tyrosine metabolism, and DNA replication.

CONCLUSIONS

AURKB may be a potential prognostic biomarker for HCC after curative surgery, which correlates with MVI and the TIME in HCC.

Non‑SMC condensin I complex subunit H promotes the malignant progression and cisplatin resistance of breast cancer MCF‑7 cells

Breast cancer is one of the most frequently diagnosed types of cancer worldwide. The present study aimed to investigate the role and underlying regulatory mechanism of non-structural maintenance of chromosome condensin I complex subunit H (NCAPH) in the malignant progression and cisplatin (DDP) resistance of breast cancer cells. Therefore, the mRNA and protein expression levels of NCAPH were first determined in breast cancer cells via reverse transcription-quantitative PCR and western blotting. Furthermore, following transfection of NCAPH interference plasmids, the effect of NCAPH knockdown on cell proliferation, migration, invasion were also assessed using CCK-8, wound healing and Transwell assays. Apoptosis was evaluated using TUNEL assay, and western blotting was performed in breast cancer cells and DDP-resistant breast cancer cells. The association between NCAPH and its downstream target, aurora kinase B (AURKB), was verified using bioinformatic analysis and the co-immunoprecipitation assay. Furthermore, the effect of AURKB overexpression on the aforementioned processes and the Akt/mTOR signaling pathway were also assessed. The results demonstrated that NCAPH mRNA and protein expression levels were significantly upregulated in breast cancer cells, whereas NCAPH knockdown significantly attenuated the proliferation, migration and invasion of breast cancer cells. NCAPH silencing also exacerbated the apoptosis of DDP-resistant breast cancer cells. AURKB mRNA and protein expression levels were also significantly upregulated in MCF-7 cells, whereas its overexpression significantly reversed the effects of NCAPH knockdown on breast cancer cells and the Akt/mTOR signaling pathway. Overall, NCAPH knockdown significantly downregulated AURKB mRNA and protein expression levels to block the Akt/mTOR signaling pathway and inhibited breast cancer cell proliferation, migration, invasion, and aggravate DDP-resistant breast cancer cell apoptosis, indicating that NCAPH may serve as a promising therapeutic target for breast cancer.