Increased AURKA promotes cell proliferation and predicts poor prognosis in bladder cancer

A comprehensive review on role of Aurora kinase inhibitors (AKIs) in cancer therapeutics

Aurora kinases (AURKs) are a family of serine /threonine protein kinases that have a crucial role in cell cycle process mainly in the event of chromosomal segregation, centrosome maturation and cytokinesis. The family consists of three members including Aurora kinase A (AURK-A), Aurora kinase B (AURK-B) and Aurora kinase C (AURK-C). All AURKs contain a conserved kinase domain for their activity but differ in their cellular localization and functions. AURK-A and AURK-B are expressed mainly in somatic cells while the expression of AURK-C is limited to germ cells. AURK-A promotes G2 to M transition of cell cycle by controlling centrosome maturation and mitotic spindle assembly. AURK-B and AURK-C form the chromosome passenger complex (CPC) that ensures proper chromosomal alignments and segregation. Aberrant expression of AURK-A and AURK-B has been detected in several solid tumours and malignancies. Hence, they have become an attractive therapeutic target against cancer. The first part of this review focuses on AURKs structure, functions, subcellular localization, and their role in tumorigenesis. The review also highlights the functional and clinical impact of selective as well as pan kinase inhibitors. Currently, >60 compounds that target AURKs are in preclinical and clinical studies. The drawbacks of existing inhibitors like selectivity, drug resistance and toxicity have also been addressed. Since, majority of inhibitors are Aurora kinase inhibitor (AKI) type-1 that bind to the active (DFGin and Cin) conformation of the kinase, this information may be utilized to design highly selective kinase inhibitors that can be combined with other therapeutic agents for better clinical outcomes.

Pan-cancer analysis and in vitro validation of the oncogenic and prognostic roles of AURKA in human cancers

Background

Aurora kinase A (AURKA) plays a pivotal role in regulating cell mitosis and tumor progression. However, its prognostic significance across diverse cancer types remains relatively unexplored.

Methods

We conducted a comprehensive analysis of AURKA expression in various cancers using data from The Cancer Genome Atlas, Genotype-Tissue Expression, and The Human Protein Atlas databases. Our investigation encompassed an exploration of the associations between AURKA expression and clinical characteristics, shedding light on potential functional roles of AURKA. Additionally, we delved into the relationship between AURKA and the tumor microenvironment. To substantiate the role of AURKA, we carried out in vitro experiments in esophageal adenocarcinoma (EAC), prostate cancer (PRAD), and pancreatic cancer (PAAD) cells.

Results

Our analysis revealed that AURKA is prominently overexpressed in a majority of the cancer types under investigation. Elevated AURKA expression correlated closely with poorer prognosis and advanced tumor stages. AURKA was found to be associated with key pathways involved in the cell cycle and arachidonic acid metabolism. Moreover, AURKA expression exhibited significant correlations with immunoregulatory genes and immune cell profiles. Notably, in vitro experiments demonstrated that silencing AURKA expression resulted in reduced cell viability in EAC, PRAD, and PAAD cells, as well as a decrease in clone formation, cell cycle elongation, diminished cell invasion and reduced spheroid size in EAC cells (OE33 and OE19).

Conclusion

Our study elucidates the oncogenic role of AURKA and underscores its prognostic value across a spectrum of cancers, including EAC. These findings suggest that AURKA holds promise as a predictive biomarker for EAC and various other tumor types.

AURKA inhibitor-induced PD-L1 upregulation impairs antitumor immune responses

Introduction

Tumor immunotherapy targeting PD-L1 has emerged as one of the powerful tools for tumor therapy. Numerous studies indicate that tumor-targeted drugs critically have an influence on the interaction between the immune system and tumors by changing the expression of PD-L1, which is beneficial for immunotherapy. Our study provided novel evidence for improving the drug regimen in tumor targeted therapy and immunotherapy.

Methods

The expression of PD-L1 on SKBR3, MDA-MB-231, MCF7, 4T1, MC38 and B16 cells was evaluated by flow cytometry after treatment with six preclinical targeted drugs (ARN-509, AZD3514, Galeterone, Neratinib, MLN8237 and LGK974). AURKA was knockdowned by using the specific siRNA or CRISPR-Cas9 technology. In the 4T1-breast tumor and colorectal cancer xenograft tumor models, we determined the number of infiltrated CD3+ and CD8+ T cells in tumor tissues by IHC.

Results

We found that AURKA inhibitor MLN8237 promoted the expression of PD-L1 in a time- and concentration-dependent manner while exerted its antitumor effect. Knockdown of AURKA could induce the upregulation of PD-L1 on SKBR3 cells. MLN8237-induced PD-L1 upregulation was mainly associated with the phosphorylation of STAT3. In the 4T1-breast tumor xenograft model, the infiltrated CD3+ and CD8+ T cells decreased after treatment with MLN8237. When treated with MLN8237 in combination with anti-PD-L1 antibody, the volumes of tumor were significantly reduced and accompanied by increasing the infiltration of CD3+ and CD8+ T cells in colorectal cancer xenograft tumor model.

Discussion

Our data demonstrated that MLN8237 improved the effect of immunology-related therapy on tumor cells by interacting with anti-PD-L1 antibody, which contributed to producing creative sparks for exploring the possible solutions to overcoming drug resistance to tumor targeted therapy.

Predictive Value of Gene Databases in Discovering New Biomarkers and New Therapeutic Targets in Lung Cancer

Background and Objectives: The molecular mechanisms of lung cancer are still unclear. Investigation of immune cell infiltration (ICI) and the hub gene will facilitate the identification of specific biomarkers. Materials and Methods: Key modules of ICI and immune cell-associated differential genes, as well as ICI profiles, were identified using lung cancer microarray data from the single sample gene set enrichment analysis (ssGSEA) and weighted gene co-expression network analysis (WGCNA) in the gene expression omnibus (GEO) database. Protein–protein interaction networks were used to identify hub genes. The receiver operating characteristic (ROC) curve was used to assess the diagnostic significance of the hub genes, and survival analysis was performed using gene expression profiling interactive analysis (GEPIA). Results: Significant changes in ICI were found in lung cancer tissues versus adjacent normal tissues. WGCNA results showed the highest correlation of yellow and blue modules with ICI. Protein–protein interaction networks identified four hub genes, namely CENPF, AURKA, PBK, and CCNB1. The lung adenocarcinoma patients in the low hub gene expression group showed higher overall survival and longer median survival than the high expression group. They were associated with a decreased risk of lung cancer in patients, indicating their potential role as cancer suppressor genes and potential targets for future therapeutic development. Conclusions: CENPF, AURKA, PBK, and CCNB1 show great potential as biomarkers and immunotherapeutic targets specific to lung cancer. Lung cancer patients’ prognoses are often foreseen using matched prognostic models, and genes CENPF, AURKA, PBK, and CCNB1 in lung cancer may serve as therapeutic targets, which require further investigations.

AURKA, as a potential prognostic biomarker, regulates autophagy and immune infiltration in nasopharyngeal carcinoma

BACKGROUND

Dysfunction of Aurora A (AURKA) plays crucial role in tumorigenesis and development of many types of cancer. However, the role of AURKA in nasopharyngeal carcinoma (NPC) has not been investigated yet.

MATERIALS AND METHODS

Two independent NPC cohorts (GSE61218 and GSE102349) were enrolled from public database to investigate the expression level of AURKA between NPC and nasopharyngitis samples, the association of AURKA expression level with prognosis in NPC, and the potential mechanism of AURKA in NPC by using bioinformatics analyses. The expression level of AURKA protein in 62 paired NPC and nasopharyngitis tissues was evaluated by immunohistochemistry (IHC). Two NPC cell lines (SUNE-1 and CNE-2) were enrolled and the expression levels of AURKA in the NPC cells were inhibited by RNA interference. The expression levels of mRNAs were tested by qPCR and western-blotting. CCK-8 assay was applied to measure the cell growth. Cell migration was measured by using wound healing assays.

RESULTS

AURKA was highly expressed in NPC samples compared to nasopharyngitis samples in GSE61218, which was confirmed by IHC. High expression of AURKA was associated with worse prognosis in GSE102349. Notably, silencing of AURKA was associated with significantly decreased cell growth and migration in NPC. Moreover, we found that the differentially expressed genes between high and low AURKA expression groups in GSE102349 were majorly enriched in both autophagy-related and immune-related pathways. Additionally, the expression level of AURKA was associated with the expression levels of autophagy-related genes and the infiltration of immune cells.

CONCLUSION

AURKA overexpressed in NPC, which was associated with poor prognosis. Silencing of AURKA inhibited the proliferation and migration of NPC cells. Besides, AURKA might participate in the regulation of both autophagy and immunity in NPC.

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.

Bioinformatics-based identification of key genes and pathways associated with colorectal cancer diagnosis, treatment, and prognosis

Colorectal cancer (CRC) is known to display a high risk of metastasis and recurrence. The main objective of our investigation was to shed more light on CRC pathogenesis by screening CRC datasets for the identification of key genes and signaling pathways, possibly leading to new approaches for the diagnosis and treatment of CRC. We downloaded the colorectal cancer datasets from the Gene Expression Omnibus (GEO) database site. We used GEO2R to screen for differentially expressed genes (DEGs) of which those with a fold change >1 were considered as up-regulated and those with a fold change <-1 were considered as down-regulated on the basis of a P < .05. "Gene ontology (GO)" and "Kyoto Encyclopedia of Genes and Genomes (KEGG)" data were analyzed by the "DAVID" software. The online search tool "STRING" was used to search for interacting genes or proteins and we used Cytoscape (v3.8.0) to generate a PPI network map and to identify key genes. Finally, survival analysis and stage mapping of key genes were performed using "GEPIA" with the aim of elucidating their potential impact on CRC. Our study revealed 120 intersecting genes of which 55 were up- and 65 were downregulated, respectively. GO analysis revealed that these genes were involved in cell proliferation, exosome secretion, G2/M transition, cytosol, protein binding, and protein kinase activity. KEGG pathway analysis showed that these genes were involved in cell cycle and mineral absorption. The Cytoscape PPI map showed 17 nodes and 262 edges, and 10 hub genes were identified by top 10 degrees. Survival analysis demonstrated that the AURKA, CCNB1, and CCNA2 genes were strongly associated with the survival rate of CRC patients. In addition, CCNB1, CCNA2, CDK1, CKS2, MAD2L1, and DLGAP5 could be correlated to pathological CRC staging. In this research, we identified key genes that may explain the molecular mechanism of occurrence and progression of CRC but may also contribute to an improvement in the clinical staging and prognosis of CRC patients.

Identification of Hub Genes for Early Diagnosis and Predicting Prognosis in Colon Adenocarcinoma

Colon adenocarcinoma (COAD) is among the most common digestive system malignancies worldwide, and its pathogenesis and gene signatures remain unclear. This study explored the genetic characteristics and molecular mechanisms underlying colon cancer development. Three gene expression data sets were obtained from the Gene Expression Omnibus (GEO) database. GEO2R was used to determine differentially expressed genes (DEGs) between COAD and normal tissues. Then, the intersection of the data sets was obtained. Metascape was used to perform the functional enrichment analyses. Next, STRING was used to build protein-protein interaction (PPI) networks. Hub genes were identified and analysed using Cytoscape. Next, survival analysis and expression analysis of the hub genes were performed. ROC curve analysis was performed for further test of the diagnostic efficacy. Finally, alterations in the hub genes were predicted and analysed by cBioPortal. Altogether, 436 DEGs were detected. The DEGs were mainly enriched in cell cycle phase transition, nuclear division, meiotic nuclear division, and cytokinesis. Based on PPI networks, 20 hub genes were selected. Among them, 6 hub genes (CCNB1, CCNA2, AURKA, NCAPG, DLGAP5, and CENPE) showed significant prognostic value in colon cancer (P < 0.05), while 5 hub genes (CDK1, CCNB1, CCNA2, MAD2L1, and DLGAP5) were associated with early colon cancer diagnosis and ROC curve analysis showed good diagnostic accuracy. In conclusion, integrated bioinformatics analysis was used to identify hub genes that reveal the potential mechanism of carcinogenesis and progression of colon cancer. The hub genes might be novel biomarkers for early diagnosis, treatment, and prognosis of colon cancer.

Integrated Analysis of Transcriptome Data Revealed AURKA and KIF20A as Critical Genes in Medulloblastoma Progression

Medulloblastoma is the neuroepithelial tumor with the highest degree of malignancy in the central nervous system, accounting for about 8% to 10% of children’s brain tumors. It has a high degree of malignancy and is easily transmitted through cerebrospinal fluid, with a relatively poor prognosis. Although medulloblastoma has been widely studied and treated, its molecular mechanism remains unclear. To determine which gene plays a crucial role in medulloblastoma development and progression, we analyzed three microarray datasets from Gene Expression Omnibus. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used to detect and evaluate differentially expressed genes. Protein interaction network was established, and the hub genes were determined in cytoHubba through various assessment methods, while the target genes were screened out using survival analysis. Ultimately, human medulloblastoma samples were utilized to confirm target gene expression. In conclusion, This study found that aurora kinase A (AURKA) and kinesin family member 20A (KIF20A) may be involved in the initiation and development of medulloblastoma, have a close association with prognosis, and may become a potential therapeutic target and prognostic marker of MED.

The cell cycle-related genes RHAMM, AURKA, TPX2, PLK1, and PLK4 are associated with the poor prognosis of breast cancer patients

Breast cancer is the third most common type of cancer diagnosed. Cell cycle is a complex but highly organized and controlled process, in which normal cells sense mitogenic growth signals that instruct them to enter and progress through their cell cycle. This process culminates in cell division generating two daughter cells with identical amounts of genetic material. Uncontrolled proliferation is one of the hallmarks of cancer. In this study, we analyzed the expression of the cell cycle-related genes receptor for hyaluronan (HA)-mediated motility (RHAMM), AURKA, TPX2, PLK1, and PLK4 and correlated them with the prognosis in a collective of 3952 breast cancer patients. A high messenger RNA expression of all studied genes correlated with a poor prognosis. Stratifying the patients according to the expression of hormonal receptors, we found that in patients with estrogen and progesterone receptor-positive and human epithelial growth factor receptor 2-negative tumors, and Luminal A and Luminal B tumors, the expression of the five analyzed genes correlates with worse survival. qPCR analysis of a panel of breast cancer cell lines representative of major molecular subtypes indicated a predominant expression in the luminal subtype. In vitro experiments showed that radiation influences the expression of the five analyzed genes both in luminal and triple-negative model cell lines. Functional analysis of MDA-MB-231 cells showed that small interfering RNA knockdown of PLK4 and TPX2 and pharmacological inhibition of PLK1 had an impact on the cell cycle and colony formation. Looking for a potential upstream regulation by microRNAs, we observed a differential expression of RHAMM, AURKA, TPX2, PLK1, and PLK4 after transfecting the MDA-MB-231 cells with three different microRNAs. Survival analysis of miR-34c-5p, miR-375, and miR-142-3p showed a different impact on the prognosis of breast cancer patients. Our study suggests that RHAMM, AURKA, TPX2, PLK1, and PLK4 can be used as potential targets for treatment or as a prognostic value in breast cancer patients.

AURKA gene polymorphisms and central nervous system tumor susceptibility in Chinese children

INTRODUCTION

Central nervous system (CNS) tumors comprise 15-20% of all malignancies occurring in childhood and adolescence. Previous researches have shown that overexpression and amplification of the AURKA gene could induce multiple human malignancies, with which the connection of CNS tumor susceptibility has not been extensively studied.

MATERIAL AND METHODS

In this study, we assessed whether and to what extent AURKA gene single nucleotide polymorphisms (SNPs) (rs1047972 C > T, rs2273535 T > A, rs8173 G > C) were associated with CNS tumor susceptibility, based on a case-control analysis in 191 CNS tumor patients and 248 controls. We determined this correlation using odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

AURKA gene rs8173 G > C exhibited a crucial function to CNS tumor susceptibility fall-off (GC/CC vs. GG: adjusted OR = 0.68, 95% CI = 0.46-0.998, P = 0.049). In addition, the combined effect of lowering the risk of developing CNS tumors was more pronounced in carriers with 3 protective genotypes than others (adjusted OR = 0.55, 95% CI = 0.31-0.98, P = 0.044). Further stratification analysis illustrated that the existence of rs8173 GC/CC and three protective genotypes lowered CNS tumor risk in some subgroups.

CONCLUSIONS

Our research suggested that the AURKA gene rs8173 G > C could significantly reduce CNS tumor susceptibility in Chinese children. More functional experiments are needed to explore the role of the AURKA gene rs8173 G > C.

AURKB as a Promising Prognostic Biomarker in Hepatocellular Carcinoma

The Aurora kinases form a family of 3 genes encoding serine/threonine kinases and are involved in the regulation of cell division during the mitosis. This study was designed to investigate the prognostic role of Aurora kinases in hepatocellular carcinoma (HCC). In this study, we analyzed the expression, overall survival (OS) data, promoter methylation level, and relationship with immunoinhibitors of Aurora kinases in patients with HCC from GEPIA2, UALCAN, OncoLnc, and TISIDB databases. Protein-protein interaction (PPI) network, gene ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome pathway analysis were performed using the STRING database and Cytoscape software. We found that the mRNA expression, stages of HCC, and OS of AURKA and AURKB in HCC tissues were significantly different from control tissues, but there were significant inconsistencies in promoter methylation level and relationship with immunoinhibitors for AURKA and AURKB. None of the above items were significantly different for AURKC. Furthermore, a hub module including AURKA, AURKB, and AURKC was identified within the PPI network constructed with the Molecular Complex Detection (MCODE) plug-in in Cytoscape software. Our results show that AURKB could be a potential biomarker for HCC prognosis.

LINC00958 promotes bladder cancer carcinogenesis by targeting miR-490-3p and AURKA

Background

Bladder cancer is a prevalent malignancy of the urinary system, in which long non-coding RNAs (lncRNAs) are highly associated. We aimed to elucidate the role of LINC00958 in bladder cancer.

Methods

LINC00958 expression levels were measured using qRT-PCR. The interaction of LINC00958-miR-490-3p-AURKA was analyzed by luciferase, RIP, and RNA pull-down assays. The biological roles of LINC00958, miR-490-3p, and AURKA in bladder cancer cells were analyzed using CCK8, BrdU, and transwell assays.

Results

Increased expression of LINC00958 and AURKA was observed in bladder cancer tissues and cell lines. Decreased LINC00958 expression repressed bladder cancer progression and downregulation of miR-490-3p accelerated bladder cancer cell progression. Moreover, LINC00958 sponges miR-490-3p to upregulate AURKA expression, thereby promoting carcinogenesis in bladder cancer cells.

Conclusions

Our study revealed that LINC00958 facilitated cell proliferation and invasion, and suppressed cell apoptosis by sponging miR-490-3p and upregulating AURKA, thus inspiring a new treatment method for bladder cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08882-6.

Combined inhibition of AURKA and HSF1 suppresses proliferation and promotes apoptosis in hepatocellular carcinoma by activating endoplasmic reticulum stress

PURPOSE

In this study we aimed to assess the anti-tumor effect of co-inhibition of Aurora kinase A (AURKA) and heat shock transcription factor 1 (HSF1) on hepatocellular carcinoma (HCC), as well as to explore the mechanism involved.

METHODS

Expression of AURKA and HSF1 in primary HCC tissues and cell lines was detected by immunohistochemistry (IHC), qRT-PCR and Western blotting. AURKA was knocked down in HepG2 and BEL-7402 HCC cells using lentivirus-mediated RNA interference. Next, CCK-8, clone formation, transwell and flow cytometry assays were used to assess their viability, migration, invasion and apoptosis, respectively. The expression of proteins related to cell cycle progression, apoptosis and endoplasmic reticulum stress (ERS) was analyzed using Western blotting. In addition, in vivo tumor growth of HCC cells was assessed using a nude mouse xenograft model, and the resulting tumors were evaluated using HE staining and IHC.

RESULTS

Both AURKA and HSF1 were highly expressed in HCC tissues and cells, while being negatively related to HCC prognosis. Knockdown of AURKA significantly inhibited the colony forming and migrating capacities of HCC cells. In addition, we found that treatment with an AURKA inhibitor (Danusertib) led to marked reductions in the proliferation and migration capacities of the HCC cells, and promoted their apoptosis. Notably, combined inhibition of AURKA and HSF1 induced HCC cell apoptosis, while increasing the expression of ERS-associated proteins, including p-eIF2α, ATF4 and CHOP. Finally, we found that co-inhibition of AURKA and HSF1 elicited an excellent in vivo antitumor effect in a HCC mouse model with a relatively low cytotoxicity.

CONCLUSIONS

Combined inhibition of AURKA and HSF1 shows an excellent anti-tumor effect on HCC cells in vitro and in vivo, which may be mediated by ERS. These findings suggest that both AURKA and HSF1 may serve as targets for HCC treatment.

Bladder Cancer-related microRNAs With In Vivo Efficacy in Preclinical Models

Progressive and metastatic bladder cancer remain difficult to treat. In this review, we critique seven up-regulated and 25 down-regulated microRNAs in order to identify new therapeutic entities and corresponding targets. These microRNAs were selected with respect to their efficacy in bladder cancer-related preclinical in vivo models. MicroRNAs and related targets interfering with chemoresistance, cell-cycle, signaling, apoptosis, autophagy, transcription factor modulation, epigenetic modification and metabolism are described. In addition, we highlight microRNAs targeting transmembrane receptors and secreted factors. We discuss druggability issues for the identified targets.

Integrated bioinformatics analysis reveals CDK1 and PLK1 as potential therapeutic targets of lung adenocarcinoma

ABSTRACT

This study is to identify potential biomarkers and therapeutic targets for lung adenocarcinoma (LUAD).GSE6044 and GSE118370 raw data from the Gene Expression Omnibus database were normalized with Robust Multichip Average. After merging these two datasets, the combat function of sva packages was used to eliminate batch effects. Then, limma packages were used to filtrate differentially expressed genes. We constructed protein-protein interaction relationships using STRING database and hub genes were identified based on connectivity degrees. The cBioportal database was used to explore the alterations of the hub genes. The promoter methylation of cyclin dependent kinase 1 (CDK1) and polo-like Kinase 1 (PLK1) and their association with tumor immune infiltration in patients with LUAD were investigated using DiseaseMeth version 2.0 and TIMER databases. The Cancer Genome Atlas-LUAD dataset was used to perform gene set enrichment analysis.We identified 10 hub genes, which were upregulated in LUAD, among which 8 were successfully verified in the Cancer Genome Atlas and Oncomine databases. Kaplan-Meier analysis indicated that the expressions of CDK1 and PLK1 in LUAD patients were associated with overall survival and disease-free survival. The methylation levels in the promoter regions of these 2 genes in LUAD patients were lower than those in normal lung tissues. Their expressions in LUAD were associated with tumor stages and relative abundance of tumor infiltrating immune cells, such as B cells, CD4+ T cells, and macrophages. Moreover, cell cycle, DNA replication, homologous recombination, mismatch repair, P53 signaling pathway, and small cell lung cancer signaling were significantly enriched in CDK1 and PLK1 high expression phenotype.CDK1 and PLK1 may be used as potential biomarkers and therapeutic targets for LUAD.

Identification of potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma via integrated bioinformatics analysis

Objective

The objective was to identify potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma (HCC).

Methods

Gene expression profile datasets were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between HCC and normal samples were identified via an integrated analysis. A protein–protein interaction network was constructed and analyzed using the STRING database and Cytoscape software, and enrichment analyses were carried out through DAVID. Gene Expression Profiling Interactive Analysis and Kaplan–Meier plotter were used to determine expression and prognostic values of hub genes.

Results

We identified 11 hub genes (CDK1, CCNB2, CDC20, CCNB1, TOP2A, CCNA2, MELK, PBK, TPX2, KIF20A, and AURKA) that might be closely related to the pathogenesis and prognosis of HCC. Enrichment analyses indicated that the DEGs were significantly enriched in metabolism-associated pathways, and hub genes and module 1 were highly associated with cell cycle pathway.

Conclusions

In this study, we identified key genes of HCC, which indicated directions for further research into diagnostic and prognostic biomarkers that could facilitate targeted molecular therapy for HCC.

The Role of circRNAs in Human Papillomavirus (HPV)-Associated Cancers

Circular RNAs (circRNAs) are a new class of "non-coding RNAs" that originate from non-sequential back-splicing of exons and/or introns of precursor messenger RNAs (pre-mRNAs). These molecules are generally produced at low levels in a cell-type-specific manner in mammalian tissues, but due to their circular conformation they are unaffected by the cell mRNA decay machinery. circRNAs can sponge multiple microRNAs or RNA-binding proteins and play a crucial role in the regulation of gene expression and protein translation. Many circRNAs have been shown to be aberrantly expressed in several cancer types, and to sustain specific oncogenic processes. Particularly, in virus-associated malignancies such as human papillomavirus (HPV)-associated anogenital carcinoma and oropharyngeal and oral cancers, circRNAs have been shown to be involved in tumorigenesis and cancer progression, as well as in drug resistance, and some are useful diagnostic and prognostic markers. HPV-derived circRNAs, encompassing the HPV E7 oncogene, have been shown to be expressed and to serve as transcript for synthesis of the E7 oncoprotein, thus reinforcing the virus oncogenic activity in HPV-associated cancers. In this review, we summarize research advances in the biogenesis of cell and viral circRNAs, their features and functions in the pathophysiology of HPV-associated tumors, and their importance as diagnostic, prognostic, and therapeutic targets in anogenital and oropharyngeal and oral cancers.

AURKA and FAM83A are prognostic biomarkers and correlated with Tumor-infiltrating Lymphocytes in smoking related Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) has become the main histologic type, which account for nearly 40% of lung cancer. The present study aimed to investigate the gene expression signature in smoking related LUAD. A total of 45 smoking related DEGs in LUAD were identified and functional enrichment analysis was also performed. Then Cox's regression model and Kaplan-Meier analysis were used to screen potential prognostic genes. Finally, AURKA and FAM83A were left for further immune-related mechanism exploration. Kaplan-Meier analysis indicated survival rates are related to different immune cell (B cell and Dendritic cell) infiltration levels. Mechanistically, we further explore the correlation between AURKA and FAM83A gene expression levels and tumor-infiltrating lymphocytes (TILs) level as well as their response to immunomodulators. The results suggested that AURKA and FAM83A are highly expressed in smoking related LUAD, and negatively correlated to B cell and Dendritic cell infiltration levels. At the same time, B cell and Dendritic cell infiltration levels also related to the prognosis of LUAD. We further revealed AURKA and FAM83A could be novel targets to improve the prognosis of LUAD through regulated the response to immunomodulators.

Identification of grade-related genes and construction of a robust genomic-clinicopathologic nomogram for predicting recurrence of bladder cancer

BACKGROUND

Bladder cancer (BC) is a common tumor in the urinary system with a high recurrence rate. The individualized treatment and follow-up after surgery is the key to a successful outcome. Currently, the surveillance strategies are mainly depending on tumor stage and grade. Previous evidence has proved that tumor grade was a significant and independent risk factor of BC recurrence. Exploring the grade-related genes may provide us a new approach to predict prognosis and guide the post-operative treatment in BC patients.

METHODS

In this study, the weighted gene co-expression network analysis was applied to identify the hub gene module correlated with BC grade using GSE71576. After constructing a protein-protein interaction (PPI) network with the hub genes inside the hub gene module, we identified some potential core genes. TCGA and another independent dataset were used for further validation.

RESULTS

The results revealed that the expression of AURKA, CCNA2, CCNB1, KIF11, TTK, BUB1B, BUB1, and CDK1 were significantly higher in high-grade BC, showing a strong ability to distinguish BC grade. The expression levels of the 8 genes in normal, paracancerous, tumorous, and recurrent bladder tissues were progressively increased. By conducting survival analysis, we proved their prognostic value in predicting the recurrence of BC. Eventually, we constructed a prognostic nomogram by combining the 8-core-gene panel with clinicopathologic features, which had shown great performance in predicting the recurrence of BC.

CONCLUSION

We identified 8 core genes that revealed a significant correlation with the tumor grade as well as the recurrence of BC. Finally, we proved the value of a novel prognostic nomogram for predicting the relapse-free survival of BC patients after surgery, which could guide their treatment and follow-up.

PUF60/AURKA Axis Contributes to Tumor Progression and Malignant Phenotypes in Bladder Cancer

Abnormal expression or mutation of RNA splicing proteins are widely observed in human cancers. Here, we identified poly(U) binding splicing factor 60 (PUF60) as one of the most differentially expressed genes out of 97 RNA splicing proteins between normal and bladder cancer tissues by bioinformatics analysis of TCGA bladder cancer expression data. The expression of PUF60 was significantly higher in tumor tissues, while high PUF60 expression was associated with malignant phenotypes of bladder cancer and shorter survival time. Moreover, we identified aurora kinase A (AURKA) as a new downstream target of PUF60 in bladder cancer cells. PUF60 knockdown significantly inhibited cell viability and colony formation capacity in bladder cancer cells, whereas AURKA overexpression reversed this inhibition effect. Overexpression of PUF60 significantly promoted cell viability and colony formation in bladder cancer cells, while treatment with AURKA specific inhibitor reversed this promotive effect. Mechanistically, PUF60 specifically bound to the AURKA promoter, thereby activating its transcription and expression. Furthermore, we showed that there was a significant positive correlation between PUF60 and AURKA expression in bladder cancer tissues, and PUF60 and AURKA expression contributed to tumor progression and malignant phenotypes in the patients with bladder cancer. Collectively, these results indicate that the PUF60/AURKA axis plays a key role in regulating tumorigenesis and progression of bladder cancer, and may be a potential prognostic biomarker and therapeutic target for bladder cancer patients.

The role of Aurora-A in human cancers and future therapeutics

Aurora-A is a mitotic serine/threonine-protein kinase and an oncogene. In normal cells, Aurora-A appears from G2 phase and localizes at the centrosome, where it participates in centrosome replication, isolation and maturation. Aurora-A also maintains Golgi apparatus structure and spindle assembly. Aurora-A undergoes ubiquitination-mediated degradation after the cell division phase. Aurora-A is abnormally expressed in tumor cells and promotes cell proliferation by regulating mitotic substrates, such as PP1, PLK1, TPX2, and LAST2, and affects other molecules through a non-mitotic pathway to promote cell invasion and metastasis. Some molecules in tumor cells also indirectly act on Aurora-A to regulate tumor cells. Aurora-A also mediates resistance to chemotherapy and radiotherapy and is involved in tumor immunotherapy. Clinical trials of Aurora-A molecular inhibitors are currently underway, and clinical transformation is just around the corner.

Quantitative Proteomics of Urinary Bladder Cancer Cell Lines Identify UAP1 as a Potential Therapeutic Target

Bladder carcinoma (BC) incidence and mortality rates are increasing worldwide. The development of novel therapeutic strategies is required to improve clinical management of this cancer. Aberrant protein expression may lead to cancer initiation and progression. Therefore, the identification of these potential protein targets and limiting their expression levels would provide alternative treatment options. In this study, we utilized a liquid-chromatography tandem mass spectrometry-based global proteomics approach to identify differentially expressed proteins in bladder cancer cell lines. A total of 3913 proteins were identified in this study, of which 479 proteins were overexpressed and 141 proteins were downregulated in 4 out of 6 BC cell lines when compared with normal human urothelial cell line (TERT-NHUC). We evaluated the role of UDP-N-acetylhexosamine pyrophosphorylase (UAP1) in bladder cancer pathogenesis. The silencing of UAP1 led to reduction in proliferation, invasion, colony formation and migration capability of bladder cancer cell lines. Thus, our study reveals UAP1 as a promising therapeutic target for bladder cancer.

Inhibition of Aurora Kinase A by Alisertib Reduces Cell Proliferation and Induces Apoptosis and Autophagy in HuH-6 Human Hepatoblastoma Cells

Purpose

Aurora kinase A (AURKA), which belongs to the serine/threonine protein kinase family, has been identified as a key driver of the genesis and progression of diverse tumors. The aim of this study was to determine the clinical significance of AURKA in patients with hepatoblastoma (HB) and the effect of inhibiting AURKA in the HB cell line HuH-6.

Methods

The expression of AURKA in HB tissue and adjacent normal liver tissue was detected by immunohistochemistry. Then, statistical analysis was performed to evaluate the association between AURKA expression and the clinicopathological characteristics of HB. The effect of AURKA knockdown on cell viability was assessed by CCK-8 assay. EdU and CCK-8 assays, Western blotting, flow cytometry, and transmission electron microscopy (TEM) were used to examine the effect of alisertib (ALS), a selective AURKA small-molecule inhibitor, on the cell cycle, proliferation, apoptosis, and autophagy in HuH-6 human hepatoblastoma cells.

Results

The expression of AURKA was significantly higher in HB tissue than in adjacent normal tissue. Furthermore, high AURKA expression was associated with advanced Children’s Oncology Group (COG) stage and tumor metastasis of HB. In vitro, AURKA knockdown significantly reduced the viability of HuH-6 cells, while ALS treatment significantly suppressed HuH-6 cell proliferation and induced G1-phase cell cycle arrest by reducing cyclin-D1 expression. Moreover, ALS promoted apoptosis and autophagy by decreasing the activity of p38 MAPK in HuH-6 cells.

Conclusion

High expression of AURKA is a potential predictor of poor prognosis in HB patients. AURKA knockdown reduced the viability of HuH-6 cells, and ALS treatment inhibited cell proliferation and induced apoptosis and autophagy via the p38 MAPK signaling pathway. Our results suggest that AURKA may be a novel therapeutic target and ALS a potential therapeutic drug for the treatment of HB.

Identification of Key Biomarkers in Bladder Cancer: Evidence from a Bioinformatics Analysis

Bladder cancer (BCa) is one of the most common malignancies and has a relatively poor outcome worldwide. However, the molecular mechanisms and processes of BCa development and progression remain poorly understood. Therefore, the present study aimed to identify candidate genes in the carcinogenesis and progression of BCa. Five GEO datasets and TCGA-BLCA datasets were analyzed by statistical software R, FUNRICH, Cytoscape, and online instruments to identify differentially expressed genes (DEGs), to construct protein‒protein interaction networks (PPIs) and perform functional enrichment analysis and survival analyses. In total, we found 418 DEGs. We found 14 hub genes, and gene ontology (GO) analysis revealed DEG enrichment in networks and pathways related to cell cycle and proliferation, but also in cell movement, receptor signaling, and viral carcinogenesis. Compared with noncancerous tissues, TPM1, CRYAB, and CASQ2 were significantly downregulated in BCa, and the other hub genes were significant upregulated. Furthermore, MAD2L1 and CASQ2 potentially play a pivotal role in lymph nodal metastasis. CRYAB and CASQ2 were both significantly correlated with overall survival (OS) and disease-free survival (DFS). The present study highlights an up to now unrecognized possible role of CASQ2 in cancer (BCa). Furthermore, CRYAB has never been described in BCa, but our study suggests that it may also be a candidate biomarker in BCa.

Comprehensive analysis of TPX2-related ceRNA network as prognostic biomarkers in lung adenocarcinoma

Background and aim: Competing endogenous RNA (ceRNA) is believed to play vital roles in tumorigenesis. The goal of this study was to screen prognostic biomarkers in lung adenocarcinoma (LUAD). Methods: Common differentially expressed genes (DEGs) were collected from Gene Expression Omnibus (GEO) databases and The Cancer Genome Atlas databases (TCGA) using GEO2R and "limma" package in R, respectively. Overlapping DEGs were conducted using enrichment of functions and protein-protein interaction (PPI) network to discover significant candidate genes. By using a comprehensive analysis, we constructed an mRNA mediated ceRNA network. Survival rates were used Kaplan-Meier analysis. Statistical analysis was used to further identify the prognosis of studied genes. Results: Integrated analysis of GSE32863 and TCGA databases, a total of 886 overlapping DEGs, including 279 up-regulated and 607 down-regulated genes were identified. Considering the highest term of candidate genes in PPI, we identified TPX2, which was enriched in cell division signaling pathway. Besides, 35 differentially expressed miRNAs (DEmiRNAs) were predicted to target TPX2 and only 7 DEmiRNAs were identified to be prognostic biomarkers in LUAD. Then, 30 differentially expressed lncRNAs (DElncRNAs) were predicted to bind these 7 DEmiRNAs. Finally, we found that 7 DElncRNAs were correlated with the overall survival (all p <0.05). Furthermore, we identified elevated TPX2 was strongly correlated with the worse survival rate among 458 samples. Univariate and multivariate cox analysis showed TPX2 may act as an independent factor for prognosis in LUAD (p <0.05). Then pathway enrichment results suggested that TPX2 may facilitate tumorigenesis by participating in several cancer-related signaling pathways in LUAD, especially in Notch signal pathway. Conclusions: TPX2-related lncRNAs and miRNAs are related to the survival of LUAD. 7 lncRNAs, 7 miRNAs and TPX2 may serve as prognostic biomarkers in LUAD.

Clinical and Expression Significance of AKT1 by Co-expression Network Analysis in Endometrial Cancer

Introduction: Endometrial cancer is one of the most common uterine cancers worldwide. AKT is reported to regulate progesterone receptor B dependent transcription and angiogenesis in endometrial cancer. However, the potential mechanisms of AKT in the tumor progression of endometrial cancer remain unclear.

Methods: We used GSE72708 with gene expression profiles of AKT regulation from the GEO database. We performed GSEA analysis to explore pathway enrichments. We found that most upregulated enriched pathways in siAKT group were associated with acid metabolism and immune network. Endometrial cancer and various signaling pathways were downregulated enriched. Moreover, different molecular mechanism of regulation between progestin (R5020) and AKT was identified, which were related to VEGF signaling pathway. The hub genes were evaluated by immunohistochemical staining of endometrial cancer tissues.

Results: We screened out a total of 623 differentially expressed genes among different groups. According to weighted gene co-expression network analysis (WGCNA) method, four distinct modules were identified. We found brown module showed a very high positive correlation with siAKT group and a very high negative correlation with R5020 group. A total of six hub genes including PBK, BIRC5, AURKA, GTSE1, KNSTRN, and PSMB10 were finally identified associated with AKT1. In addition, the data also shows that the higher expression of AKT1, GTSE1, BIRC5, AURKA, and KNSTRN is significantly associate with poor prognosis of endometrial cancer.

Conclusion: Our study identified six hub genes related to the prognosis of endometrial cancer, which may provide new insights into the underlying biological mechanisms driving the tumorigenesis of endometrial cancer, especially in AKT1 regulation.