Association between the functional polymorphism Ile31Phe in the AURKA gene and susceptibility of hepatocellular carcinoma in chronic hepatitis B virus carriers

The role of Aurora kinase A in hepatocellular carcinoma: Unveiling the intriguing functions of a key but still underexplored factor in liver cancer

Aurora Kinase A (AURKA) plays a central role as a serine/threonine kinase in regulating cell cycle progression and mitotic functions. Over the years, extensive research has revealed the multifaceted roles of AURKA in cancer development and progression. AURKA's dysregulation is frequently observed in various human cancers, including hepatocellular carcinoma (HCC). Its overexpression in HCC has been associated with aggressive phenotypes and poor clinical outcomes. This review comprehensively explores the molecular mechanisms underlying AURKA expression in HCC and its functional implications in cell migration, invasion, epithelial-to-mesenchymal transition, metastasis, stemness, and drug resistance. This work focuses on the clinical significance of AURKA as a diagnostic and prognostic biomarker for HCC. High levels of AURKA expression have been correlated with shorter overall and disease-free survival in various cohorts, highlighting its potential utility as a sensitive prognostic indicator. Recent insights into AURKA's role in modulating the tumour microenvironment, particularly immune cell recruitment, may provide valuable information for personalized treatment strategies. AURKA's critical involvement in modulating cellular pathways and its overexpression in cancer makes it an attractive target for anticancer therapies. This review discusses the evidence about novel and selective AURKA inhibitors for more effective treatments for HCC.

A systematic study on the treatment of hepatitis B-related hepatocellular carcinoma with drugs based on bioinformatics and key target reverse network pharmacology and experimental verification

BACKGROUND

Chronic hepatitis B virus (HBV) infection is the major etiology of hepatocellular carcinoma (HCC). However, the mechanism of hepatitis B-related hepatocellular carcinoma (HBV-related HCC) is still unclear. Therefore, understanding the pathogenesis and searching for drugs to treat HBV-related HCC was an effective strategy to treat this disease.

PURPOSE

Bioinformatics was used to predict the potential targets of HBV-related HCC. The reverse network pharmacology of key targets was used to analyze the clinical drugs, traditional Chinese medicine (TCM) and small molecules of TCM in the treatment of HBV-related HCC.

METHODS

In this study, three microarray datasets totally containing 330 tumoral samples and 297 normal samples were selected from the GEO database. These microarray datasets were used to screen DEGs. And the expression profile and survival of 6 key genes were analyzed. In addition, Comparative Toxicogenomics Database and Coremine Medical database were used to enrich clinical drugs and TCM of HBV-related HCC by the 6 key targets. Then the obtained TCM were classified based on the Chinese Pharmacopoeia. Among these top 6 key genes, CDK1 and CCNB1 had the most connection nodes and the highest degree and were the most significantly expressed. In general, CDK1 and CCNB1 tend to form a complex, which is conducive to cell mitosis. Hence, this study mainly studied CDK1 and CCNB1. HERB database was used to predict small molecules TCM. The inhibition effect of quercetin, celastrol and cantharidin on HepG2.2.15 cells and Hep3B cells was verified by CCK8 experiment. The effects of quercetin, celastrol and cantharidin on CDK1 and CCNB1 of HepG2.2.15 cells and Hep3B cells were determined by Western Blot.

RESULTS

In short, 272 DEGs (53 upregulated and 219 downregulated) were identified. Among these DEGs, 6 key genes with high degree were identified, which were AURKA, BIRC5, CCNB1, CDK1, CDKN3 and TYMS. Kaplan-Meier plotter analysis showed that higher expression levels of AURKA, BIRC5, CCNB1, CDK1, CDKN3 and TYMS were associated with poor OS. According to the first 6 key targets, a variety of drugs and TCM were identified. These results showed that clinical drugs included targeted drugs, such as sorafenib, palbociclib and Dasatinib. and chemotherapy drugs, such as cisplatin and doxorubicin. TCM, such as the TCM flavor was mainly warm and bitter, and the main meridians were liver and lung. Small molecules of TCM included flavonoids, terpenoids, alkaloids and glycosides, such as quercetin, celastrol, cantharidin, hesperidin, silymarin, casticin, berberine and ursolic acid, which have great potential in anti-HBV-related HCC. For molecular docking of chemical components, the molecules with higher scores were flavonoids, alkaloids, etc. Three representative types of TCM small molecules were verified respectively, and it was found that quercetin, celastrol and cantharidin inhibited the proliferation of HepG2.2.15 cells and Hep3B cells along concentration gradient. Quercetin, celastrol and cantharidin decreased CDK1 expression in HepG2.2.15 and Hep3B cells, but for CCNB1, only cantharidin decreased CCNB1 expression in the two strains of cells.

CONCLUSION

In conclusion, AURKA, BIRC5, CCNB1, CDK1, CDKN3 and TYMS could be potential targets for the diagnosis and prognosis of HBV-related HCC. Clinical drugs include chemotherapeutic and targeted drug, traditional Chinese medicine is mainly bitter and warm TCM. Small molecular of TCM including flavonoids, terpenoids and glycosides and alkaloids, which have great potential in anti-HBV-related HCC. This study provides potential therapeutic targets and novel strategies for the treatment of HBV-related HCC.

Predictive Role of AURKA rs 1047972 Gene Polymorphism and the Risk of Development of Hepatocellular Carcinoma

ABBREVIATION

AFP: alpha-fetoprotein; ALP: alkaline phosphatase; ALT: alanine aminotransferase; AST: aspartate aminotransferase; AURKA: aurora kinase A; BCLC: Barcelona- Clinic Liver Cancer; CBC: complete blood count; CT: computed tomography; DM: diabetes mellitus; DNA: deoxyribonucleic acid; EDTA: ethylene diamine tetraacetic acid; GGT: gamma-glutamyl transferase; HB: hemoglobin; HBV: hepatitis B virus; HBsAg: hepatitis B surface antigen; HCC: hepatocellular carcinoma; HCV: hepatitis C virus; INR: international normalized ratio; mRNA: messenger ribonucleic acid; OR: odds ratio; PVT: portal vein thrombosis; RT-PCR: real-time polymerase chain reaction; SNP: single nucleotide polymorphism; WBCs: white blood cells.

The impact of Aurora kinase A genetic polymorphisms on cervical cancer progression and clinicopathologic characteristics

The aims of this study were to explore the involvement of Aurora kinase A (AURKA) gene single nucleotide polymorphisms (SNPs) in uterine cervical cancer that has not yet been investigated. One hundred and six patients with cervical invasive cancer and 94 patients with precancerous lesions, and 302 Taiwanese female individuals were included. AURKA SNPs rs2273535, rs6024836, rs2064863 and rs1047972 were analyzed for genotypic distributions using real-time polymerase chain reaction. There were no statistically significant differences in the genetic frequencies of AURKA SNPs among patients with invasive cancer and those with precancerous lesions of uterine cervix and control women. There were no associations among AURKA SNPs and clinicopathologcal variables and recurrence and survival events. However, in a multivariate analysis, cervical cancer patients with adenocarcinoma (HR: 3.18, 95% CI: 1.23-8.23; p=0.017) and larger tumor (HR: 5.61, 95% CI: 2.10-14.95; p=0.001) had poorer recurrence-free survival. In conclusion, tumor size and pelvic lymph node status rather than AURKA SNPs were the most obvious independent parameter that could significantly predict 5 years survival rate in Taiwanese women with cervical cancer.

AURKA rs2273535 T>A Polymorphism Associated With Cancer Risk: A Systematic Review With Meta-Analysis

Aurora kinase A (AURKA) is a cell cycle regulatory serine/threonine kinase that promotes cell cycle progression. It plays an important role in regulating the transition from G2 to M phase during mitosis. The association between the AURKA rs2273535 T>A polymorphism and cancer risk has been investigated, but the results remain inconsistent. To get a more accurate conclusion, we conducted a comprehensive meta-analysis of 36 case-control studies, involving 22,884 cancer cases and 30,497 healthy controls. Crude odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to determine the association of interest. Pooled analysis indicated that the AURKA rs2273535 T>A polymorphism increased the overall risk of cancer (homozygous: OR = 1.17, 95% CI = 1.04-1.33; recessive: OR = 1.15, 95% CI = 1.05-1.25; allele: OR = 1.07, 95% CI = 1.02-1.13). Stratification analysis by cancer type further showed that this polymorphism was associated with an increased breast cancer risk. This meta-analysis indicated that the AURKA rs2273535 T>A polymorphism was associated with an overall increased cancer risk, especially breast cancer. Further validation experiments are needed to strengthen our conclusion.

Bioinformatics analysis reveals meaningful markers and outcome predictors in HBV-associated hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common type of malignant neoplasm of the liver with high morbidity and mortality. Extensive research into the pathology of HCC has been performed; however, the molecular mechanisms underlying the development of hepatitis B virus-associated HCC have remained elusive. Thus, the present study aimed to identify critical genes and pathways associated with the development and progression of HCC. The expression profiles of the GSE121248 dataset were downloaded from the Gene Expression Omnibus database and the differentially expressed genes (DEGs) were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) analyses were performed by using the Database for Annotation, Visualization and Integrated Discovery. Subsequently, protein-protein interaction (PPI) networks were constructed for detecting hub genes. In the present study, 1,153 DEGs (777 upregulated and 376 downregulated genes) were identified and the PPI network yielded 15 hub genes. GO analysis revealed that the DEGs were primarily enriched in ‘protein binding’, ‘cytoplasm’ and ‘extracellular exosome’. KEGG analysis indicated that DEGs were accumulated in ‘metabolic pathways’, ‘chemical carcinogenesis’ and ‘fatty acid degradation’. After constructing the PPI network, cyclin-dependent kinase 1, cyclin B1, cyclin A2, mitotic arrest deficient 2 like 1, cyclin B2, DNA topoisomerase IIα, budding uninhibited by benzimidazoles (BUB)1, TTK protein kinase, non-SMC condensin I complex subunit G, NDC80 kinetochore complex component, aurora kinase A, kinesin family member 11, cell division cycle 20, BUB1B and abnormal spindle microtubule assembly were identified as hub genes based on the high degree of connectivity by using Cytoscape software. In addition, overall survival (OS) and disease-free survival (DFS) analyses were performed using the Gene Expression Profiling Interactive Analysis online database, which revealed that the increased expression of all hub genes were associated with poorer OS and DFS outcomes. Receiver operating characteristic curves were constructed using GraphPad prism 7.0 software. The results confirmed that 15 hub genes were able to distinguish HCC form normal tissues. Furthermore, the expression levels of three key genes were analyzed in tumor and normal samples of the Human Protein Atlas database. The present results may provide further insight into the underlying mechanisms of HCC and potential therapeutic targets for the treatment of this disease.

Relationship between Aurora-A V57I Polymorphism and the Risk of Cancer: A Meta-Analysis and Trial Sequential Analysis

Background: It is still conflicting for the correlation between cancer susceptibility and Aurora-A V57I (rs1047972) gene variant from the published researches. This meta-analysis was performed to access the correlation between cancer susceptibility and Aurora-A rs1047972 gene polymorphism by using meta-analysis methods.

Methods: Eligible studies published before Nov 1, 2019 were systematically searched in PMC, PubMed, EMBASE, Web of Science, Cochrane Library Database, China National Knowledge Infrastructure, Wanfang databases, in order to collect qualified case-control or cohort studies. The odds ratio (OR) and its 95% confidence interval (95%CI) were used to evaluate the correlation between Aurora-A rs1047972 gene polymorphism and cancer risk. Sensitivity analysis was used to examine the stability of the results; Egger's test and Begg's funnel chart were used to assess possible publication bias. Trial sequential analysis (TSA) was used to access whether the sample size of our meta-analysis was sufficient.

Results: The sample set extracted from 24 case-control studies involving 35,926 subjects (14,639 cases and 21,287 controls) for the association of Aurora-A rs1047972 gene polymorphism with cancer susceptibility. In our meta-analysis, Aurora-A rs1047972 polymorphism was associated with an increased risk of cancer susceptibility in overall populations (GA+GG vs. AA: P=0.039, OR=1.106; 95% CI 1.005-1.218; AA vs. GG: P=0.003, OR= 0.814; 95% CI, 0.710-0.934), and the GA/GG variant might be a risk factor for cancer susceptibility. In the stratified analysis by ethnicity, we found a significant association between Aurora-A rs1047972 variant and the susceptibility of the cancer in Caucasian population. In a subgroup analysis by cancer type, we observed a significantly increased susceptibility of lung cancer. In addition, an increased risk was found between Aurora-A rs1047972 polymorphism and cancer susceptibility in MALDI-TOF group and among population-based study (PB) patients. Our results were in a sufficiently large number of participants according to TSA and did not require more studies to confirm such association.

Conclusion: Our meta-analysis revealed that the susceptibility of cancer was associated with Aurora-A rs1047972 polymorphism, especially in Caucasians. And the GA/GG variant might be a risk factor for cancer susceptibility.

A Novel AURKA Mutant-Induced Early-Onset Severe Hepatocarcinogenesis Greater than Wild-Type via Activating Different Pathways in Zebrafish

Aurora A kinase (AURKA) is an important regulator in mitotic progression and is overexpressed frequently in human cancers, including hepatocellular carcinoma (HCC). Many AURKA mutations were identified in cancer patients. Overexpressing wild-type Aurka developed a low incidence of hepatic tumors after long latency in mice. However, none of the AURKA mutant animal models have ever been described. The mechanism of mutant AURKA-mediated hepatocarcinogenesis is still unclear. A novel AURKA mutation with a.a.352 Valine to Isoleucine (V352I) was identified from clinical specimens. By using liver-specific transgenic fish overexpressing both the mutant and wild-type AURKA, the AURKA(V352I)-induced hepatocarcinogenesis was earlier and much more severe than wild-type AURKA. Although an increase of the expression of lipogenic enzyme and lipogenic factor was observed in both AURKA(V352I) and AURKA(WT) transgenic fish, AURKA(V352I) has a greater probability to promote fibrosis at 3 months compared to AURKA(WT). Furthermore, the expression levels of cell cycle/proliferation markers were higher in the AURKA(V352I) mutant than AURKA(WT) in transgenic fish, implying that the AURKA(V352I) mutant may accelerate HCC progression. Moreover, we found that the AURKA(V352I) mutant activates AKT signaling and increases nuclear β-catenin, but AURKA(WT) only activates membrane form β-catenin, which may account for the differences. In this study, we provide a new insight, that the AURKA(V352I) mutation contributes to early onset hepatocarcinogenesis, possibly through activation of different pathways than AURKA(WT). This transgenic fish may serve as a drug-screening platform for potential precision medicine therapeutics.

Impacts of AURKA Genetic Polymorphism on Urothelial Cell Carcinoma Development

Urothelial cell carcinoma (UCC) is the most common primary malignancy of the urinary system and the second-most common type of renal cell carcinoma. Aurora kinase A (AURKA), a serine/threonine kinase, has a critical role in centrosome duplication, spindle assembly checkpoint, and cytokinesis. Here, we determined the correlation between UCC susceptibility and AURKA polymorphisms. We used real-time polymerase chain reaction to compare the genotype distributions and allelic frequencies of four single-nucleotide polymorphisms (SNPs) of AURKA, namely rs1047972, rs2273535, rs2064863, and rs6024836, between 431 UCC cases and 862 healthy controls. Logistic regression models demonstrated that the G allele of rs2064863, a genetic polymorphism of AURKA, exhibited a significant protective effect against UCC among the 862 nonsmokers. Moreover, patients with rs2064863 G allele exhibited a slightly lower risk of lymph node metastasis and those with rs6024836 G allele exhibited a lower risk of distant metastases. Our study suggested that several variants of AURKA SNPs rs2064863 and rs6024836 may serve as critical predictors for the clinical status of UCC.

Association of FAM65B, AGBL4, and CUX2 genetic polymorphisms with susceptibility to antituberculosis drug-induced hepatotoxicity: validation study in a Chinese Han population

OBJECTIVE

Antituberculosis (anti-TB) drug-induced hepatotoxicity (ATDH) is a serious adverse drug reaction, and its pathogenic mechanism has not been elucidated thoroughly to date. A recent genome-wide association study reported that seven single-nucleotide polymorphisms (SNPs) in the family with sequence similarity 65, member B gene (FAM65B), ATP/GTP-binding protein-like 4 gene (AGBL4), and cut-like homeobox 2 gene (CUX2) were associated strongly with ATDH in Ethiopian patients. We validated this relationship in a Chinese Han anti-TB treatment population.

PATIENTS AND METHODS

A 1 : 2 matched case-control study was carried out of 235 ATDH cases and 470 controls. Multivariate conditional logistic regression analysis was used to estimate the association between genotypes and risk of ATDH by odds ratios with 95% confidence intervals, and weight and hepatoprotectant use were used as covariates.

RESULTS

Patients with a polymorphism at rs10946737 in the FAM65B gene were at an increased risk of moderate and severe liver injury under the dominant model (adjusted odds ratio=2.147, 95% confidence interval: 1.067-4.323, P=0.032). No other genotypes or genetic risk scores were found to be significantly related to ATDH.

CONCLUSION

This is the first study to explore and validate the relationships between seven SNPs in the FAM65B, AGBL4, and CUX2 genes and ATDH in a Chinese population. On the basis of this case-control study, SNP rs10946737 in FAM65B may be associated with susceptibility to ATDH in Chinese Han anti-TB treatment patients. Further research is warranted to explain the role of the FAM65B gene and its contribution toward individual differences in susceptibility to ATDH.

Long non-coding RNA taurine-upregulated gene 1 promotes cells proliferation, migration and invasion while represses apoptosis, and upregulates AURKA expression in hepatocellular carcinoma

This study aimed to assess the effect of long non-coding RNA (lncRNA) taurine-upregulated gene 1 (TUG1) on cells proliferation, migration, invasion and apoptosis of hepatocellular carcinoma (HCC) cells. LncRNA TUG1 expression was detected in HCC cell lines (SMMC7721, HepG2 and BEL-7402 cells) and normal liver cells (L-02 cells) by qPCR assay. After the transfection of blank mimic, lncRNA TUG1 mimic, blank inhibitor and lncRNA TUG1 inhibitor plasmids into SMMC7721 cells, CKK8, wound-healing, matrigel assay, AV/PI, qPCR assay and western blot assays were performed to detect cells proliferation, migration, invasion, apoptosis, RNA expression and protein expression respectively. LncRNA TUG1 expression was increased in SMMC 7721 cells, HepG2 cells and BEL-7402 cells compared to L-02 cells. After transfection of lncRNA TUG1 mimic and inhibitor plasmids, cells proliferation, migration and invasion were observed to be increased in lncRNA TUG1 mimic group compared to blank mimic group (NC1), while were decreased in lncRNA TUG1 inhibitor group compared with blank inhibitor group (NC2). As to cells apoptosis, AV/PI assay disclosed that lncRNA TUG1 mimic suppressed cells apoptosis rate than NC1 while lncRNA TUG1 inhibitor promoted cells apoptosis rate than NC2, apoptosis markers (C-Caspase3 and Bcl) protein expression also supported the regulation of lncRNA TUG1 on cells apoptosis. In addition, lncRNA TUG1 positively regulated the protein and mRNA expressions of AURKA, but not SERPINE1 or BRAF. In conclusion, lncRNA TUG1 promotes cells proliferation, migration and invasion while represses apoptosis, and upregulates AURKA expression in HCC cells.

Identifying genes as potential prognostic indicators in patients with serous ovarian cancer resistant to carboplatin using integrated bioinformatics analysis

Serous ovarian cancer (SOC) accounts for >50% of all epithelial ovarian cancers. However, patients with SOC present with various degrees of response to platinum‑based chemotherapy and, thus, their survival may differ. The present study aimed to identify the candidate genes involved in the carcinogenesis and drug resistance of SOC by analyzing the microarray datasets GDS1381 and GDS3592. GDS1381 and GDS3592 were downloaded from the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/gds/). A total of 219 differentially expressed genes (DEGs) were identified. Potential genes that may predict the response to carboplatin and, thus, the prognosis of SOC were analyzed. The enriched functions and pathways of DEGs included extracellular region, extracellular space and extracellular exosome, among others. Upon screening the upregulated and downregulated genes on the connectivity map, 10 small‑molecule drugs were identified that may be helpful in improving drug sensitivity in patients with ovarian cancer. A total of 30 hub genes were screened for further analysis after constructing the protein‑to‑protein interaction network. Through survival analysis, comparison of genes across numerous analyses, and immunohistochemistry, GNAI1, non‑structural maintenance of chromosomes (non‑SMC) condensin I complex subunit H (NCAPH), matrix metallopeptidase 9 (MMP9), aurora kinase A (AURKA) and enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2) were identified as the key molecules that may be involved in the carcinogenesis and carboplatin resistance of SOC. In conclusion, GNAI1, NCAPH, MMP9, AURKA and EZH2 should be examined in further studies for the possibility of their participation in the carcinogenesis and carboplatin response of SOC.

Variations in the AURKA Gene: Biomarkers for the Development and Progression of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a liver malignancy and a major cause of cancer mortality worldwide. AURKA (aurora kinase A) is a mitotic serine/threonine kinase that functions as an oncogene and plays a critical role in hepatocarcinogenesis. We report on the association between 4 single nucleotide polymorphisms (SNPs) of the AURKA gene (rs1047972, rs2273535, rs2064836, and rs6024836) and HCC susceptibility as well as clinical outcomes in 312 patients with HCC and in 624 cancer-free controls. We found that carriers of the TT allele of the variant rs1047972 were at greater risk of HCC compared with wild-type (CC) carriers. Moreover, carriers of at least one A allele in rs2273535 were less likely to progress to stage III/IV disease, develop large tumors or be classified into Child-Pugh class B or C. Individuals with at least one G allele at AURKA SNP rs2064863 were at lower risk of developing large tumors or progressing to Child-Pugh grade B or C. Our results indicate that genetic variations in the AURKA gene may serve as an important predictor of early-stage HCC and be a reliable biomarker for the development of HCC.