Expression of aurora kinase A correlates with the Wnt-modulator RACGAP1 in gastric cancer

Increased PTCHD4 expression via m6A modification of PTCHD4 mRNA promotes senescent cell survival

RNA modifications, including N6-methyladenosine (m6A), critically modulate protein expression programs in a range of cellular processes. Although the transcriptomes of cells undergoing senescence are strongly regulated, the landscape and impact of m6A modifications during senescence are poorly understood. Here, we report a robust m6A modification of PTCHD4 mRNA, encoding Patched Domain-Containing Protein 4, in senescent cells. The METTL3/METTL14 complex was found to incorporate the m6A modification on PTCHD4 mRNA; addition of m6A rendered PTCHD4 mRNA more stable and increased PTCHD4 production. MeRIP RT-qPCR and eCLIP analyses were used to map this m6A modification to the last exon of PTCHD4 mRNA. Further investigation identified IGF2BP1, but not other m6A readers, as responsible for the stabilization and increased abundance of m6A-modified PTCHD4 mRNA. Silencing PTCHD4, a transmembrane protein, enhanced growth arrest and DNA damage in pre-senescent cells and sensitized them to senolysis and apoptosis. Our results indicate that m6A modification of PTCHD4 mRNA increases the production of PTCHD4, a protein associated with senescent cell survival, supporting the notion that regulating m6A modification on specific mRNAs could be exploited to eliminate senescent cells for therapeutic benefit.

Oncogenic and immunological roles of RACGAP1 in pan-cancer and its potential value in nasopharyngeal carcinoma

A particular GTPase-activating protein called RACGAP1 is involved in apoptosis, proliferation, invasion, metastasis, and drug resistance in a variety of malignancies. Nevertheless, the role of RACGAP1 in pan-cancer was less studied, and its value of the expression and prognostic of nasopharyngeal carcinoma (NPC) has not been explored. Hence, the goal of this study was to investigate the oncogenic and immunological roles of RACGAP1 in various cancers and its potential value in NPC. We comprehensively analyzed RACGAP1 expression, prognostic value, function, methylation levels, relationship with immune cells, immune infiltration, and immunotherapy response in pan-cancer utilizing multiple databases. The results discovered that RACGAP1 expression was elevated in most cancers and suggested poor prognosis, which could be related to the involvement of RACGAP1 in various cancer-related pathways such as the cell cycle and correlated with RACGAP1 methylation levels, immune cell infiltration and reaction to immunotherapy, and chemoresistance. RACGAP1 could inhibit anti-tumor immunity and immunotherapy responses by fostering immune cell infiltration and cytotoxic T lymphocyte dysfunction. Significantly, we validated that RACGAP1 mRNA and protein were highly expressed in NPC. The Gene Expression Omnibus database revealed that elevated RACGAP1 expression was associated with shorter PFS in patients with NPC, and RACGAP1 potentially influenced cell cycle progression, DNA replication, metabolism, and immune-related pathways, resulting in the recurrence and metastasis of NPC. This study indicated that RACGAP1 could be a potential biomarker in pan-cancer and NPC.

Overexpression of RACGAP1 by E2F1 Promotes Neuroendocrine Differentiation of Prostate Cancer by Stabilizing EZH2 Expression

Neuroendocrine prostate cancer (NEPC) is a lethal subtype of prostate cancer. It is characterized by the loss of androgen receptor (AR) signaling in neuroendocrine transdifferentiation, and finally, resistance to AR-targeted therapy. With the application of a new generation of potent AR inhibitors, the incidence of NEPC is gradually increasing. The molecular mechanism of neuroendocrine differentiation (NED) after androgen deprivation therapy (ADT) remains largely unclear. In this study, using NEPC-related genome sequencing database analyses, we screened RACGAP1, a common differentially expressed gene. We investigated RACGAP1 expression in clinical prostate cancer specimens by IHC. Regulated pathways were examined by Western blotting, qRT-PCR, luciferase reporter, chromatin immunoprecipitation, and immunoprecipitation assays. The corresponding function of RACGAP1 in prostate cancer was analyzed by CCK-8 and Transwell assays. The changes of neuroendocrine markers and AR expression in C4-2-R and C4-2B-R cells were detected in vitro. We confirmed that RACGAP1 contributed to NE transdifferentiation of prostate cancer. Patients with high tumor RACGAP1 expression had shorter relapse-free survival time. The expression of RACGAP1 was induced by E2F1. RACGAP1 promoted neuroendocrine transdifferentiation of prostate cancer by stabilizing EZH2 expression in the ubiquitin-proteasome pathway. Moreover, overexpression of RACGAP1 promoted enzalutamide resistance of castration-resistant prostate cancer (CRPC) cells. Our results showed that the upregulation of RACGAP1 by E2F1 increased EZH2 expression, which drove NEPC progression. This study explored the molecular mechanism of NED and may provide novel methods and ideas for targeted therapy of NEPC.

Chebulagic acid suppresses gastric cancer by inhibiting the AURKA/β-catenin/Wnt pathway

Gastric cancer (GC) is a prevalent malignant neoplasm that poses a serious threat to human health. Overexpression of Aurora A (AURKA) is frequently associated with the self-renewal and tumorigenicity of various cancers. Chebulagic acid (CA) has been examined as a potential tumor suppressor based on its ability against numerous tumor biological activities. However, the possible mechanisms of CA inhibition of the progression of GC by mediating the AURKA/β-catenin/Wnt signaling pathway have not been investigated. The present study investigated the level of AURKA expression in GC. We further examined the effect of CA on cell proliferation, migration, and apoptosis in the MKN1 and NUGC3 GC cell lines, and its efficacy in suppressing tumor growth was assessed in tumor bearing mice model. We demonstrated that AURKA was highly expressed in GC and associated with poor prognosis. We demonstrated that treatment with CA significantly inhibited the proliferation and migration of GC cells and induced apoptosis. Compared to the vehicle group, CA treatment severely diminished the volume and weight and the metastasis of tumors. CA also inhibited the expression of AURKA and the AURKA/β-catenin/Wnt signaling pathway in vitro and in vivo. Collectively, the present results demonstrated that high expression of AURKA may be an independent factor of poor prognosis in patients with GC, and CA significantly suppressed the tumor biological functions of GC and inhibited the AURKA/β-catenin/Wnt pathway.

Role of AURKA in the hypothalamus-pituitary-testicular axis in Tibetan sheep from Tianzhu

The mitosis-associated protein aurora kinase A (AURKA) regulates the maturation of germ cells. We have previously reported using transcriptome analysis that AURKA is expressed in yak testes. Although Tibetan sheep possess an immense economic value, their reproductive rate is low. Herein, the expression and functions of AURKA in the hypothalamus-pituitary-testicular (HPT) axis in Tibetan sheep from Tianzhu were investigated. The cDNA sequence of sheep AURKA was cloned and bioinformatics techniques were used to predict its structure. Tissue expression of AURKA was determined by qPCR, immunoblotting, immunostaining, and immunohistochemistry. The AURKA coding sequence was found to be 1218 bp in length, encoding a 405-amino acid polypeptide chain. Furthermore, the highest sequence similarity of AURKA with the corresponding sequence in other species was seen in goat and cattle; the least degree of similarity was seen in the domestic cat. In addition, AURKA expression was elevated in the testes compared to that in the hypothalamus and pituitary (p < 0.01). Moreover, AURKA was mainly localized in the hypothalamic paraventricular nucleus (magnocellular), chromophobe cells of the pituitary, and spermatogenic cells of the testis. These results indicated that AURKA might participate in sheep reproductive regulation, thus providing a reference for the study of AURKA function in the reproductive process of Tibetan sheep from Tianzhu.

Prognostic Prediction Using a Stemness Index-Related Signature in a Cohort of Gastric Cancer

Background

With characteristic self-renewal and multipotent differentiation, cancer stem cells (CSCs) have a crucial influence on the metastasis, relapse and drug resistance of gastric cancer (GC). However, the genes that participates in the stemness of GC stem cells have not been identified.

Methods

The mRNA expression-based stemness index (mRNAsi) was analyzed with differential expressions in GC. The weighted gene co-expression network analysis (WGCNA) was utilized to build a co-expression network targeting differentially expressed genes (DEG) and discover mRNAsi-related modules and genes. We assessed the association between the key genes at both the transcription and protein level. Gene Expression Omnibus (GEO) database was used to validate the expression levels of the key genes. The risk model was established according to the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Furthermore, we determined the prognostic value of the model by employing Kaplan-Meier (KM) plus multivariate Cox analysis.

Results

GC tissues exhibited a substantially higher mRNAsi relative to the healthy non-tumor tissues. Based on WGCNA, 17 key genes (ARHGAP11A, BUB1, BUB1B, C1orf112, CENPF, KIF14, KIF15, KIF18B, KIF4A, NCAPH, PLK4, RACGAP1, RAD54L, SGO2, TPX2, TTK, and XRCC2) were identified. These key genes were clearly overexpressed in GC and validated in the GEO database. The protein-protein interaction (PPI) network as assessed by STRING indicated that the key genes were tightly connected. After LASSO analysis, a nine-gene risk model (BUB1B, NCAPH, KIF15, RAD54L, KIF18B, KIF4A, TTK, SGO2, C1orf112) was constructed. The overall survival in the high-risk group was relatively poor. The area under curve (AUC) of risk score was higher compared to that of clinicopathological characteristics. According to the multivariate Cox analysis, the nine-gene risk model was a predictor of disease outcomes in GC patients (HR, 7.606; 95% CI, 3.037-19.051; P < 0.001). We constructed a prognostic nomogram with well-fitted calibration curve based on risk score and clinical data.

Conclusion

The 17 mRNAsi-related key genes identified in this study could be potential treatment targets in GC treatment, considering that they can inhibit the stemness properties. The nine-gene risk model can be employed to predict the disease outcomes of the patients.

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.

MicroRNA-490-3p suppresses hepatocellular carcinoma cell proliferation and migration by targeting the aurora kinase A gene (AURKA)

INTRODUCTION

Hepatocellular carcinoma (HCC) is the most common and prevalent cancer type among liver cancers. In this study, expression of miR-490-3p and aurora kinase A gene (AURKA) was investigated in HCC. Additionally, we explored the microRNA (miR)-490-3p/AURKA relationship as well as the influence on HCC cell proliferation and migration.

MATERIAL AND METHODS

The dual luciferase reporter assay serves to verify the target relationship between miR-490-3p and AURKA. miR-490-3p mimics, AURKA siRNA and AURKA cDNA, were transfected into HCC cells. Quantitative real-time polymerase chain reaction and western blot were chosen for examining the relative expression of miR-490-3p and AURKA in HCC tissues, adjacent tissues, HCC cells and normal cells. The study detected the proliferation of HCC cells with the application of MTT assay and colony formation assay. Transwell assay was applied for the observation of migration, and wound healing assay for invasion.

RESULTS

The experiment results showed that miR-490-3p expression was down-regulated and AURKA expression was up-regulated in HCC cells and tissues. AURKA was the target gene of miR-490-3p and overexpression of miR-490-3p could inhibit the expression of AURKA in HCC cells. miR-490-3p overexpression could inhibit HCC cell migration and invasion, while AURKA promoted HCC cell migration. All experiment results indicated that miR-490-3p was low-expressed while AURKA was over-expressed in HCC cells and tissues compared to normal liver cells and tissues.

CONCLUSIONS

miR-490-3p could down-regulate the expression of AURKA, thus suppressing the proliferation and migration of HCC cells.

Explorative analysis of the gene expression profile during liver regeneration of mouse: a microarray-based study

The liver is an amazing organ due to its powerful regenerative capacity. Although many studies on liver regeneration have been documented, the detailed mechanisms remain unclear. Two-third partial hepatectomy (PH) in rodents plays a crucial role in the study of liver regeneration. In this study, the time series data of gene expression during liver regeneration in mouse were analyzed using the gene set numbered GSE6998 in GEO. A variety of bioinformatics methods, including masigPro, Weighted Gene Co-expression Network Analysis (WGCNA), spatial analysis of functional enrichment (SAFE) and ingenuity canonical pathway analysis (IPA) were used to identify and compare the significantly changed pathways, potential upstream regulators and key genes during liver regeneration. Our study showed that liver regeneration in the mouse is a coordinated process, which cell-cycle-related progress are at the centre of the interaction network involved in liver regeneration. Several candidate upstream regulators including PPARA, NFE2L2, MAD1 and CNR1 and some key genes such as Cdk1, Plk1, Cdc20, Aurka, Racgap1, Cenpa, Rrm1, Rrm2 were identified. In conclusion, these findings could contribute to revealing the molecular mechanism of liver regeneration after PH, which could provide new ideas and treatment methods for regenerative medicine, oncological drug development and oncological treatment.

Identification of Biomarkers for Controlling Cancer Stem Cell Characteristics in Bladder Cancer by Network Analysis of Transcriptome Data Stemness Indices

Background: Stem cells characterized by self-renewal and therapeutic resistance play crucial roles in bladder cancer (BLCA). However, the genes modulating the maintenance and proliferation of BLCA stem cells are still unclear. In this study, we aimed to characterize the expression of stem cell-related genes in BLCA.

Methods: The mRNA expression-based stemness index (mRNAsi) of The Cancer Genome Atlas (TCGA) was evaluated and corrected by tumor purity. Corrected mRNAsi were further analyzed with regard to muscle-invasive bladder cancer molecular subtypes, survival analysis, pathological staging characteristics, and outcomes after primary treatment. Next, weighted gene co-expression network analysis was used to find modules of interest and key genes. Functional enrichment analysis was performed to functionally annotate the modules and key genes. The expression levels of key genes in all cancers were validated using Oncomine and Gene Expression Omnibus (GEO) database containing molecular subtypes in BLCA. Protein interaction networks were used to identify upstream genes, and the relationships between genes were analyzed at the protein and transcription levels.

Findings: mRNAsi was significantly upregulated in cancer tissues. Corrected mRNAsi in BLCA increased as tumor stage increased, with T3 having the highest stem cell characteristics. Lower corrected mRNAsi scores had better overall survival and treatment outcome. The modules of interest and key genes were determined based on topological overlap measurement clustering results and the inclusion criteria. For 13 key genes (AURKA, BUB1B, CDCA5, CDCA8, KIF11, KIF18B, KIF2C, KIFC1, KPNA2, NCAPG, NEK2, NUSAP1, and RACGAP1), enriched gene ontology terms related to cell proliferation (e.g., mitotic nuclear division, spindle, and microtubule binding) were determined. Their expression did not differ according to the pathological stages of BLCA, and these genes were clearly overexpressed in many types of cancers. In GEO database, the expression levels of 13 key genes were higher in basal subtype with the highest stem cell characteristics than in luminal and its subtypes. AURKB and PLK1 may be regulated upstream of other key genes, and the key genes were found to be strongly correlated with each other and with upstream genes.

Interpretation: The 13 key genes identified in this study were found to play important roles in the maintenance of BLCA stem cells. Controlling the upstream genes AURKB and PLK1 may have applications in the treatment of BLCA. These genes may act as therapeutic targets for inhibiting the stemness characteristics of BLCA.

Bioinformatics analyses of significant genes, related pathways and candidate prognostic biomarkers in glioblastoma

Glioblastoma (GBM) is the most common type of malignant tumor of the central nervous system. The prognosis of patients with GBM is very poor, with a survival time of ~15 months. GBM is highly heterogeneous and highly aggressive. Surgical removal of intracranial tumors does provide a good advantage for patients as there is a high rate of recurrence. The understanding of this type of cancer needs to be strengthened, and the aim of the present study was to identify gene signatures present in GBM and uncover their potential mechanisms. The gene expression profiles of GSE15824 and GSE51062 were downloaded from the Gene Expression Omnibus database. Normalization of the data from primary GBM samples and normal samples in the two databases was conducted using R software. Then, joint analysis of the data was performed. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, and the protein‑protein interaction (PPI) network of the differentially expressed genes (DEGs) was constructed using Cytoscape software. Identification of prognostic biomarkers was conducted using UALCAN. In total, 9,341 DEGs were identified in the GBM samples, including 9,175 upregulated genes and 166 downregulated genes. The top 1,000 upregulated DEGs and all of the downregulated DEGs were selected for GO, KEGG and prognostic biomarker analyses. The GO results showed that the upregulated DEGs were significantly enriched in biological processes (BP), including immune response, cell division and cell proliferation, and the downregulated DEGs were also significantly enriched in BP, including cell growth, intracellular signal transduction and signal transduction by protein phosphorylation. KEGG pathway analysis showed that the upregulated DEGs were enriched in circadian entrainment, cytokine‑cytokine receptor interaction and maturity onset diabetes of the young, while the downregulated DEGs were enriched in the TGF‑β signaling pathway, MAPK signaling pathway and pathways in cancer. All of the downregulated genes and the top 1,000 upregulated genes were selected to establish the PPI network, and the sub‑networks revealed that these genes were involved in significant pathways, including olfactory transduction, neuroactive ligand‑receptor interaction and viral carcinogenesis. In total, seven genes were identified as good prognostic biomarkers. In conclusion, the identified DEGs and hub genes contribute to the understanding of the molecular mechanisms underlying the development of GBM and they may be used as diagnostic and prognostic biomarkers and molecular targets for the treatment of patients with GBM in the future.

The Association Between AURKA Gene rs2273535 Polymorphism and Gastric Cancer Risk in a Chinese Population

The Aurora kinase A (AURKA) gene is frequently amplified and overexpressed in gastric cancer (GC). The overexpression of AURKA promotes inflammation and tumorigenesis in GC. We performed co-expression analysis to identify genes associated with AURKA and speculated its function through the COXPRESdb and STRING databases. We also conducted a hospital-based case-control study involving 385 GC cases and 470 controls in a Chinese population to evaluate the role of AURKA gene rs2273535 polymorphism in the risk of GC. Genotyping was performed using a custom-by-design 48-Plex single nucleotide polymorphism (SNP) Scan™ Kit. Co-expression analysis indicated that the overexpression of AURKA may be associated with poor prognosis of GC. In addition, TT genotypes of rs2273535 polymorphism increased the risk of GC by 72% compared to the AA genotypes. This significant correlation was also observed in the allelic and dominant models. The stratified analysis suggested that TT+AT genotypes showed positive correlation with the risk of GC among female, age <55 years group and non-smokers compared to AA genotypes. In conclusion, AURKA plays an important role in the development of GC. Larger studies with more diverse ethnic populations are needed to confirm these results.

Co-expression Network Analysis of Biomarkers for Adrenocortical Carcinoma

Adrenocortical carcinoma (ACC) is a rare malignancy with a poor prognosis. And currently, there are no specific diagnostic biomarkers for ACC. In our study, we aimed to screen biomarkers for disease diagnosis, progression and prognosis. We firstly used the microarray data from public database Gene Expression Omnibus database to construct a weighted gene co-expression network, and then to identify gene modules associated with clinical features of ACC. Though this algorithm, a significant module with R² = 0.64 (P = 9 × 10^-5) was identified. Co-expression network and protein–protein interaction network were performed for screen the candidate hub genes. Checked by The Cancer Genome Atlas (TCGA) database, another independent dataset GSE19750, and GEPIA database, using one-way ANOVA, Pearson’s correlation, survival analysis, diagnostic capacity (ROC curve) and expression level revalidation, a total 12 real hub genes were identified. Gene ontology and KEGG pathway analysis of genes in the significant module revealed that the hub genes are significantly enriched in cell cycle regulation. Moreover, gene set enrichment analysis suggests that the samples with highly expressed hub genes are correlated with cell cycle. Taken together, our integrated analysis has identified 12 hub genes that are associated with the progression and prognosis of ACC; these hub genes might lead to poor outcomes by regulating the cell cycle.

Proliferation markers RacGAP1 and Ki-67 in gastrointestinal stromal tumors by immunohistochemistry with respect to clinicopathological features and different risk stratification systems

RacGAP1 is a protein associated with cell proliferation, cell growth regulation, cell transformation and metastasis. The present study was designed to evaluate RacGAP1 expression in gastrointestinal stromal tumors (GISTs) for the first time in the literature and to determine its association with some predictive clinicopathological features, Ki-67 proliferation index, and risk stratification systems of Armed Forces Institute of Pathology (AFIP) and modified National Institutes of Health (NIH). Paraffin-embedded tissues of 100 GISTs were investigated, retrospectively. High (≥10%) Ki-67 proliferation index, higher mitotic count, high cellularity, small intestinal location, and high-risk groups according to both AFIP and modified NIH criteria were found to be correlated with RacGAP1 positivity in the univariate analysis (all P values <0.05). The association between RacGAP1 expression and higher cellularity was supported by the multivariate analysis (P=0.023). High (≥10%) Ki-67 proliferation index was correlated with higher nuclear pleomorphism, necrosis, ulceration, small intestinal location, greater tumor size, higher mitotic count, and high risk group according to AFIP and NIH criteria in the univariate analysis (all P values <0.05). The correlation of Ki-67 proliferation index and mitotic count and high risk group according to AFIP criteria was confirmed by the multivariate analysis (all P values <0.05). In conclusion, higher RacGAP1 expression and Ki-67 index might be considered as effective complementation of risk stratification systems and unfavorable clinicopathological features in predicting poor outcome of GISTs. However, the utility of RacGAP1 expression in GISTs should be further validated in larger cohorts of patients with long-term follow-up data.

Screening and identification of key biomarkers in hepatocellular carcinoma: Evidence from bioinformatic analysis

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. Intense efforts have been made to elucidate the pathogeny, but the molecular mechanisms of HCC are still not well understood. To identify the candidate genes in the carcinogenesis and progression of HCC, microarray datasets GSE19665, GSE33006 and GSE41804 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and function enrichment analyses were performed. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using STRING and Cytoscape. A total of 273 DEGs were identified, consisting of 189 downregulated genes and 84 upregulated genes. The enriched functions and pathways of the DEGs include protein activation cascade, complement activation, carbohydrate binding, complement and coagulation cascades, mitotic cell cycle and oocyte meiosis. Sixteen hub genes were identified and biological process analysis revealed that these genes were mainly enriched in cell division, cell cycle and nuclear division. Survival analysis showed that BUB1, CDC20, KIF20A, RACGAP1 and CEP55 may be involved in the carcinogenesis, invasion or recurrence of HCC. In conclusion, DEGs and hub genes identified in the present study help us understand the molecular mechanisms underlying the carcinogenesis and progression of HCC, and provide candidate targets for diagnosis and treatment of HCC.

Activation of EIF4E by Aurora Kinase A Depicts a Novel Druggable Axis in Everolimus-Resistant Cancer Cells

Purpose: Aurora kinase A (AURKA) is overexpressed in several cancer types, making it an attractive druggable target in clinical trials. In this study, we investigated the role of AURKA in regulating EIF4E, cap-dependent translation, and resistance to mTOR inhibitor, RAD001 (everolimus).Experimental Design: Tumor xenografts and in vitro cell models of upper gastrointestinal adenocarcinomas (UGC) were used to determine the role of AURKA in the activation of EIF4E and cap-dependent translation. Overexpression, knockdown, and pharmacologic inhibition of AURKA were used in vitro and in vivoResults: Using in vitro cell models, we found that high protein levels of AURKA mediate phosphorylation of EIF4E and upregulation of c-MYC. Notably, we detected overexpression of endogenous AURKA in everolimus-resistant UGC cell models. AURKA mediated phosphorylation of EIF4E, activation of cap-dependent translation, and an increase in c-MYC protein levels. Targeting AURKA using genetic knockdown or a small-molecule inhibitor, alisertib, reversed these molecular events, leading to a decrease in cancer cell survival in acquired and intrinsic resistant cell models. Mechanistic studies demonstrated that AURKA binds to and inactivates protein phosphatase 2A, a negative regulator of EIF4E, leading to phosphorylation and activation of EIF4E in an AKT-, ERK1/2-, and mTOR-independent manner. Data from tumor xenograft mouse models confirmed that everolimus-resistant cancer cells are sensitive to alisertib.Conclusions: Our results indicate that AURKA plays an important role in the activation of EIF4E and cap-dependent translation. Targeting the AURKA-EIF4E-c-MYC axis using alisertib is a novel therapeutic strategy that can be applicable for everolimus-resistant tumors and/or subgroups of cancers that show overexpression of AURKA and activation of EIF4E and c-MYC. Clin Cancer Res; 23(14); 3756-68. ©2017 AACR.

Expression of aurora kinase A correlates with the Wnt-modulator RACGAP1 in gastric cancer

Canonical Wnt signaling is involved in gastric carcinogenesis. The aim of this study was to identify the link between Wnt signaling and aurora kinase A (AURKA), a target for the treatment of gastrointestinal cancers. Publicly available microarray data were used to identify phenotype‐specific protein–protein interaction (PPI) subnetworks. The in silico analysis revealed a gastric cancer‐specific PPI subnetwork consisting of 2745 proteins and 50,935 interactions. We focused on the link of AURKA to a Wnt‐specific interaction module consisting of 92 proteins. There was a direct association of AURKA with Rac GTPase‐activating protein 1 (RACGAP1), as well as with CTNBB1 (β‐catenin) and CDKN1A as second‐order interactors. Differential expression analysis revealed a significant downregulation of both AURKA and RACGAP1 in gastric cancer compared to noncancer controls. Biopsies from a prospective cohort of 56 patients with gastric cancer (32 intestinal type, 24 diffuse type) and 20 noncancer controls were used for validation of the identified targets. The RT‐PCR data confirmed a strong correlation of AURKA and RACGAP1 gene expression both in the tumor, the tumor‐adjacent and the tumor‐distant mucosa. RACGAP1 in the tumor was also associated with CTNBB1 expression, and inversely associated with CDKN1A gene expression. Immunohistochemistry confirmed expression of the RACGAP1 protein in gastric cancer and the tumor‐adjacent mucosa. RACGAP1 expression was not associated with tumor stage, grading, Lauren type, Helicobacter pylori infection, or age. In conclusion, AURKA is directly associated with the expression of RACGAP1, a modulator of the canonical Wnt signaling pathway.