RacGAP1 expression, increasing tumor malignant potential, as a predictive biomarker for lymph node metastasis and poor prognosis in colorectal cancer

Reciprocal regulation between RACGAP1 and AR contributes to endocrine therapy resistance in prostate cancer

BACKGROUND

Endocrine resistance driven by sustained activation of androgen receptor (AR) signaling pathway in advanced prostate cancer (PCa) is fatal. Characterization of mechanisms underlying aberrant AR pathway activation to search for potential therapeutic strategy is particularly important. Rac GTPase-activating protein 1 (RACGAP1) is one of the specific GTPase-activating proteins. As a novel tumor proto-oncogene, overexpression of RACGAP1 was related to the occurrence of various tumors.

METHODS

Bioinformatics methods were used to analyze the relationship of expression level between RACGAP1 and AR as well as AR pathway activation. qRT-PCR and western blotting assays were performed to assess the expression of AR/AR-V7 and RACGAP1 in PCa cells. Immunoprecipitation and immunofluorescence experiments were conducted to detect the interaction and co-localization between RACGAP1 and AR/AR-V7. Gain- and loss-of-function analyses were conducted to investigate the biological roles of RACGAP1 in PCa cells, using MTS and colony formation assays. In vivo experiments were conducted to evaluate the effect of RACGAP1 inhibition on the tumor growth.

RESULTS

RACGAP1 was a gene activated by AR, which was markedly upregulated in PCa patients with CRPC and enzalutamide resistance. AR transcriptionally activated RACGAP1 expression by binding to its promoter region. Reciprocally, nuclear RACGAP1 bound to the N-terminal domain (NTD) of both AR and AR-V7, blocking their interaction with the E3 ubiquitin ligase MDM2. Consequently, this prevented the degradation of AR/AR-V7 in a ubiquitin-proteasome-dependent pathway. Notably, the positive feedback loop between RACGAP1 and AR/AR-V7 contributed to endocrine therapy resistance of CRPC. Combination of enzalutamide and in vivo cholesterol-conjugated RIG-I siRNA drugs targeting RACGAP1 induced potent inhibition of xenograft tumor growth of PCa.

CONCLUSION

In summary, our results reveal that reciprocal regulation between RACGAP1 and AR/AR-V7 contributes to the endocrine resistance in PCa. These findings highlight the therapeutic potential of combined RACGAP1 inhibition and enzalutamide in treatment of advanced PCa.

Unravelling the molecular mechanistic pathway underlying the anticancer effects of kaempferol in colorectal cancer: a reverse pharmacology network approach

Colorectal cancer (CRC) is the third most diagnosed and highly fatal malignancy, presenting serious health concerns worldwide. The search for an effective cure for CRC is challenging and poses a serious concern. Kaempferol is a potent anti-cancerous bioactive compound often suggested for treating various cancers, including CRC. However, its underlying molecular mechanism against CRC remains unclear. The present study delves into kaempferol's molecular pathways and underlying molecular mechanisms against CRC targets. The target protein-coding genes for kaempferol were retrieved, and the CRC-associated genes were curated. Twelve common targets with a disease specificity index of > 0.6 were validated for their protein expression at different stages of CRC. Over-expressed USP1, SETD7, POLH, TDP1 and RACGAP1 were selected for further studies. The binding affinities of kaempferol to the corresponding proteins were evaluated using molecular docking and Molecular Dynamics (MD) simulations. SETD7 exhibited the highest binding affinity with the lowest binding energy (- 8.06 kcal/mol). Additionally, the MD simulation, and MM-PBSA conferred SETD7-kaempferol complex had the least root-mean-square deviation with lower interaction energy and higher conformational stability. The protein-protein interaction of SETD7 constructed revealed direct interactors, namely, DNMT1, FOXO1, FOXO3, FOXO4, H3-3B, H3-4, H3C12, H3C13, SETD7, SIRT1 and TP53, have a potential role in cancer progression through FOXO signalling. In summary, our study revealed kaempferol's multi-target and synergistic effect on multiple CRC targets and its underlying mechanisms. Finally, the study recommends in-vitro and in-vivo trials for validation of anti-cancerous drugs for CRC.

RACGAP1 promotes lung cancer cell proliferation through the PI3K/AKT signaling pathway

We aimed to investigate the expression and clinic significance of Rac GTPase Activating Protein 1 (RACGAP1) in human lung adenocarcinoma (LUAD). Online database analysis revealed a significant increase in RACGAP1 mRNA expression among 26 types of tumor tissues, including LUAD tissues. Online database and tissue microarray analyses indicated that RACGAP1 expression was significantly upregulated in LUAD tissues. Genetic variation analysis identified four different genetic variations of RACGAPs in LUAD. Moreover, online database analysis showed that RACGAP1 upregulation was correlated with shorter survival in patients with LUAD. After silencing RACGAP1 expression in A549 cells using siRNA and assessing its protein levels via Western blotting, we found that RACGAP1 knockdown inhibited cell growth and induced apoptosis determined using the Cell Counting Kit-8 assay, colony formation assay, and flow cytometry. Mechanistically, western blot analysis indicated that Bax expression increased, whereas Bcl-2 expression decreased. Moreover, RACGAP1 knockdown attenuated PI3K/AKT pathway activation in lung cancer cells. Taken together, our findings showed that RACGAP1 was overexpressed in LUAD tissues and played an important role in lung cancer by increasing cell growth through the PI3K/AKT signaling pathway. This study suggests recommends evaluating RACGAP1 in clinical settings as a novel biomarker and potential therapeutic target for lung cancer.

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.

SynergyX: a multi-modality mutual attention network for interpretable drug synergy prediction

Discovering effective anti-tumor drug combinations is crucial for advancing cancer therapy. Taking full account of intricate biological interactions is highly important in accurately predicting drug synergy. However, the extremely limited prior knowledge poses great challenges in developing current computational methods. To address this, we introduce SynergyX, a multi-modality mutual attention network to improve anti-tumor drug synergy prediction. It dynamically captures cross-modal interactions, allowing for the modeling of complex biological networks and drug interactions. A convolution-augmented attention structure is adopted to integrate multi-omic data in this framework effectively. Compared with other state-of-the-art models, SynergyX demonstrates superior predictive accuracy in both the General Test and Blind Test and cross-dataset validation. By exhaustively screening combinations of approved drugs, SynergyX reveals its ability to identify promising drug combination candidates for potential lung cancer treatment. Another notable advantage lies in its multidimensional interpretability. Taking Sorafenib and Vorinostat as an example, SynergyX serves as a powerful tool for uncovering drug-gene interactions and deciphering cell selectivity mechanisms. In summary, SynergyX provides an illuminating and interpretable framework, poised to catalyze the expedition of drug synergy discovery and deepen our comprehension of rational combination therapy.

Integrated whole transcriptome profiling revealed a convoluted circular RNA-based competing endogenous RNAs regulatory network in colorectal cancer

Recently, it has been identified that circRNAs can act as miRNA sponge to regulate gene expression in various types of cancers, associating them with cancer initiation and progression. The present study aims to identify colorectal cancer-related circRNAs and the underpinning mechanisms of circRNA/miRNA/mRNA networks in the development and progress of Colorectal Cancer. Differentially expressed circRNAs, miRNAs, and mRNAs were identified in GEO microarray datasets using the Limma package of R. The analysis of differentially expressed circRNAs resulted in 23 upregulated and 31 downregulated circRNAs. CeRNAs networks were constructed by intersecting the results of predicted and experimentally validated databases, circbank and miRWalk, and by performing DEMs and DEGs analysis using Cytoscape. Next, functional enrichment analysis was performed for DEGs included in ceRNA networks. Followed by survival analysis, expression profile assessment using TCGA and GEO data, and ROC curve analysis we identified a ceRNA sub-networks that revealed the potential regulatory effect of hsa_circ_0001955 and hsa_circ_0071681 on survival-related genes, namely KLF4, MYC, CCNA2, RACGAP1, and CD44. Overall, we constructed a convoluted regulatory network and outlined its likely mechanisms of action in CRC, which may contribute to the development of more effective approaches for early diagnosis, prognosis, and treatment of CRC.

Racgap1 knockdown results in cells with multiple cilia due to cytokinesis failure

Most mammalian cells have a single primary cilium that acts as a signalling hub in mediating cellular functions. However, little is known about the mechanisms that result in aberrant supernumerary primary cilia per cell. In this study, we re-analysed a previously published whole-genome siRNA-based reverse genetic screen for genes mediating ciliogenesis to identify knockdowns that permit multi-ciliation. We identified siRNA knockdowns that caused significant formation of supernumerary cilia, validated candidate hits in different cell-lines and confirmed that RACGAP1, a component of the centralspindlin complex, was the strongest candidate hit at the whole-genome level. Following loss of RACGAP1, mother centrioles were specified correctly prior to ciliogenesis and the cilia appeared normal. Live cell imaging revealed that increased cilia incidence was caused by cytokinesis failure which led to the formation of multinucleate cells with supernumerary cilia. This suggests that the signalling mechanisms for ciliogenesis are unable to identify supernumerary centrosomes and therefore allow ciliation of duplicated centrosomes as if they were in a new diploid daughter cell. These results, demonstrating that aberrant ciliogenesis is de-coupled from cell cycle regulation, have functional implications in diseases marked by centrosomal amplification.

The integrative multi-omics approach identifies the novel competing endogenous RNA (ceRNA) network in colorectal cancer

Circular RNAs (circRNA) are known to function as competing endogenous RNA (ceRNA) in various cancers by regulating microRNAs (miRNA). However, in colorectal cancer (CRC), the precise pathological role of circ000240/miRNA/mRNA remains indeterminate. The expression level of hsa_circ_000240 was evaluated using qRT-PCR in matching pairs of CRC tumor and adjacent normal tissue samples in our laboratory. Then, to determine whether hsa_circ_000240 acted as a ceRNA in CRC, the linked miRNAs and gene targets were retrieved. Topological analysis of candidate genes using a network approach identified the most critical hub genes and subnetworks related to CRC disease. Microarray and bulk RNA sequencing analyses were utilized to comprehensively evaluate the expression levels of both miRNA and mRNA in CRC. Single-cell RNA-seq analysis was also used to evaluate the significant overall survival (OS) genes at the cellular level. ATAC-seq data provided insights into candidate genes' accessible chromatin regions. The research uncovered a considerable upregulation of hsa_circ_000240 in CRC tissues. Three miRNAs interacted with the target circRNA. One thousand six hundred eighty intersected genes regulated by three miRNAs were further identified, and the relevant functionality of identified neighbor genes highlighted their relevance to cancer. The topological analysis of the constructed network has identified 33 hub genes with notably high expression in CRC. Among these genes, eight, including CHEK1, CDC6, FANCI, GINS2, MAD2L1, ORC1, RACGAP1, and SMC4, have demonstrated a significant impact on overall survival. The utilization of single-cell RNA sequencing unequivocally corroborated the augmented expression levels of CDC6 and ORC1 in individuals with CRC, alongside their noteworthy connection with the infiltration of immune cells. ATAC-seq analyses revealed altered accessibility regions in Chr2, 4, and 12 for CDC6 and ORC1 high-expression. Correlation analysis of CDC6 and ORC1 further highlighted the association of candidate gene expression with exhaustion markers such as CTLA4, CD247, TIGIT, and CD244. The candidate genes exhibit a positive correlation with chromatin remodeling and histone acetylation. These epigenetic modifications play a significant role in influencing the cancer progression following expression of CDC6 and ORC1 in CRC. Additionally, results showed that the methylation rate of the promoter region of CDC6 was elevated in CRC disease, confirming the functional importance of CDC6 and their interaction with hsa_circ_000240 and associated ceRNA in CRC. In conclusion, this study highlights hsa_circ_000240's role as a ceRNA in CRC. It opens new avenues for further dissection of CDC6, ORC1, and underlying novel epigenetics and immunotherapy targets for CRC therapy.

Improvement of variables interpretability in kernel PCA

BACKGROUND

Kernel methods have been proven to be a powerful tool for the integration and analysis of high-throughput technologies generated data. Kernels offer a nonlinear version of any linear algorithm solely based on dot products. The kernelized version of principal component analysis is a valid nonlinear alternative to tackle the nonlinearity of biological sample spaces. This paper proposes a novel methodology to obtain a data-driven feature importance based on the kernel PCA representation of the data.

RESULTS

The proposed method, kernel PCA Interpretable Gradient (KPCA-IG), provides a data-driven feature importance that is computationally fast and based solely on linear algebra calculations. It has been compared with existing methods on three benchmark datasets. The accuracy obtained using KPCA-IG selected features is equal to or greater than the other methods' average. Also, the computational complexity required demonstrates the high efficiency of the method. An exhaustive literature search has been conducted on the selected genes from a publicly available Hepatocellular carcinoma dataset to validate the retained features from a biological point of view. The results once again remark on the appropriateness of the computed ranking.

CONCLUSIONS

The black-box nature of kernel PCA needs new methods to interpret the original features. Our proposed methodology KPCA-IG proved to be a valid alternative to select influential variables in high-dimensional high-throughput datasets, potentially unravelling new biological and medical biomarkers.

Transcriptomic Characterization of Genes Regulating the Stemness in Porcine Atrial Cardiomyocytes during Primary In Vitro Culture

Heart failure remains a major cause of death worldwide. There is a need to establish new management options as current treatment is frequently suboptimal. Clinical approaches based on autologous stem cell transplant is potentially a good alternative. The heart was long considered an organ unable to regenerate and renew. However, several reports imply that it may possess modest intrinsic regenerative potential. To allow for detailed characterization of cell cultures, whole transcriptome profiling was performed after 0, 7, 15, and 30 days of in vitro cell cultures (IVC) from the right atrial appendage and right atrial wall utilizing microarray technology. In total, 4239 differentially expressed genes (DEGs) with ratio > abs |2| and adjusted p-value ≤ 0.05 for the right atrial wall and 4662 DEGs for the right atrial appendage were identified. It was shown that a subset of DEGs, which have demonstrated some regulation of expression levels with the duration of the cell culture, were enriched in the following GO BP (Gene Ontology Biological Process) terms: "stem cell population maintenance" and "stem cell proliferation". The results were validated by RT-qPCR. The establishment and detailed characterization of in vitro culture of myocardial cells may be important for future applications of these cells in heart regeneration processes.

A multi-omics signature to predict the prognosis of invasive ductal carcinoma of the breast

BACKGROUND

Precisely evaluating the prognosis of invasive ductal carcinoma (IDC) of the breast is challenging as most prognostic signatures use single-omics data based on gene or clinical information.

METHODS

Whole-slide images (WSIs), transcriptome, and clinical data of breast IDC were collected from the Cancer Genome Atlas Database. The cancer-associated fibroblast (CAF) gene sets were downloaded from the Molecular Signatures Database. The WSI feature was extracted by artificial feature engineering. The CAF prognostic genes were determined by the Gene Set Enrichment Analysis, the Wilcoxon test, and univariate Cox regression. The IDC patients were divided into the training and test sets. The prognostic signatures based on WSIs, IDC-CAFs, bi-omics, and tri-omics were constructed using multivariate Cox regression. The samples were divided into low- and high-risk groups according to the median risk score. The Kaplan-Meier survival and receiver operating characteristic curves were applied to validate the prediction performance of the four signatures.

RESULTS

In total, 508 IDC patients with complete data were included. The area under the curve (AUC) of single-omics signature based on WSI characteristics and CAFs was 0.765 and 0.775, whereas the AUC of bi-omics was 0.823. The tri-omics signature based on WSIs, CAFs, and lymph node status demonstrated the best predictive value with an AUC of 0.897.

CONCLUSION

The multi-omics signature based on WSIs, CAFs, and clinical characteristics showed excellent prediction ability in breast IDC patients, whose risk factors can also provide a valuable diagnostic reference for the clinical course.

Assessment of RACGAP1 as a Prognostic and Immunological Biomarker in Multiple Human Tumors: A Multiomics Analysis

Several recent studies have pointed out that arc GTPase activating protein 1 (RACGAP1) is a putative oncogene in many human tumors. However, to date, no pan-cancer analysis has been performed to study the different aspects of this gene expression and behavior in tumor tissues. Here, we applied several bioinformatics tools to perform a comprehensive analysis for RACGAP1. First, we assessed the expression of RACGAP1 in several types of human tumors and tried to correlate that with the stage of the tumors analyzed. We then performed a survival analysis to study the correlation between RACGAP1 upregulation in tumors and the clinical outcome. Additionally, we investigated the mutation forms, the correlation with several immune cell infiltration, the phosphorylation status of the interested protein in normal and tumor tissues, and the potential molecular mechanisms of RACGAP1 in cancerous tissue. The results demonstrated that RACGAP1, a highly expressed gene across several types of tumors, correlated with a poor prognosis in several types of human cancers. Moreover, it was found that RACGAP1 affects the tumor immune microenvironment by influencing the infiltration level of several immune cells. Collectively, the current study provides a comprehensive overview of the oncogenic roles of RACGAP1, where our results nominate it as a potential prognostic biomarker and a target for antitumor therapy development.

Upregulation of circ_0008812 and circ_0001583 predicts poor prognosis and promotes breast cancer proliferation

Background: Accumulating evidence suggests that circular RNAs (circRNAs) are highly correlated with tumor progression and pathogenesis in breast cancer. Whereas, their regulatory roles and corresponding mechanisms in breast cancer are still not exhaustive. Thus, we intended to establish circRNA-mediated competive endogenous RNA (ceRNA) network to uncover the possible roles and clinical implications of circRNAs in breast cancer.

Methods: Microarray and RNA-sequencing (RNA-seq) data were download from GEO and TCGA database to screen for differentially expressed RNAs (DEcircRNAs, DEmiRNAs, DEmRNAs) in breast cancer. By implementing online databases, we established ceRNA networks, performed gene set enrichment analysis, constructed protein-protein interaction (PPI) networks, and assessed the expression levels and prognostic significance of hub genes. Subsequently, we explored the functions of prognosis-related genes and constructed gene-drug interaction networks. Finally, the functional roles of DEcircRNAs in breast cancer were revealed via MTT and colony formation assay.

Results: Based on the identified 8 DEcircRNAs, 25 miRNAs and 216 mRNAs, a ceRNA regulatory network was established. Further analysis revealed that prominent enrichments were transcription factor binding, transforming growth factor-beta (TGF-β) and Apelin signaling pathway etc. PPI network and survival curves analysis showed that elevated levels of hub genes (RACGAP1 and KPNA2) were associated with poorer prognosis. They were found to be positively relevant to cell cycle and proliferation. Then a prognostic sub-network of ceRNA was constructed, consisting of 2 circRNAs, 4 miRNAs and 2 mRNAs. The gene-drug interaction network showed that numerous drugs could regulate the expression of these two prognosis-related genes. Functional experiments showed that depletion of circ_0008812 and circ_0001583 could significantly inhibit the proliferation of MCF-7 cells.

Conclusion: Our study constructed 4 prognostic regulatory axes that are significantly correlated with tumor prognosis in breast cancer patients, and uncover the roles of circ_0008812 and circ_0001583 in breast cancer, providing a new perspective into the molecular mechanisms of breast cancer pathogenesis.

ELIMINATOR: essentiality analysis using multisystem networks and integer programming

A gene is considered as essential when it is indispensable for cells to grow and replicate in a certain environment. However, gene essentiality is not a structural property but rather a contextual one, which depends on the specific biological conditions affecting the cell. This circumstantial essentiality of genes is what brings the attention of scientist since we can identify genes essential for cancer cells but not essential for healthy cells. This same contextuality makes their identification extremely challenging. Huge experimental efforts such as Project Achilles where the essentiality of thousands of genes is measured together with a plethora of molecular data (transcriptomics, copy number, mutations, etc.) in over one thousand cell lines can shed light on the causality behind the essentiality of a gene in a given environment. Here, we present an in-silico method for the identification of patient-specific essential genes using constraint-based modelling (CBM). Our method expands the ideas behind traditional CBM to accommodate multisystem networks. In essence, it first calculates the minimum number of lowly expressed genes required to be activated by the cell to sustain life as defined by a set of requirements; and second, it performs an exhaustive in-silico gene knockout to find those that lead to the need of activating additional lowly expressed genes. We validated the proposed methodology using a set of 452 cancer cell lines derived from the Cancer Cell Line Encyclopedia where an exhaustive experimental large-scale gene knockout study using CRISPR (Achilles Project) evaluates the impact of each removal. We also show that the integration of different essentiality predictions per gene, what we called Essentiality Congruity Score, reduces the number of false positives. Finally, we explored our method in a breast cancer patient dataset, and our results showed high concordance with previous publications. These findings suggest that identifying genes whose activity is fundamental to sustain cellular life in a patient-specific manner is feasible using in-silico methods. The patient-level gene essentiality predictions can pave the way for precision medicine by identifying potential drug targets whose deletion can induce death in tumour cells.

Up-Regulation of RACGAP1 Promotes Progressions of Hepatocellular Carcinoma Regulated by GABPA via PI3K/AKT Pathway

Hepatocellular carcinoma (HCC) is one of the dominating tumors causing death due to lack of timely discovery and valid treatment. Abnormal increase of Rac GTPase activating protein 1 (RACGAP1) has been verified to be an oncogene in plenty tumors. The profound mechanism of RACGAP1 was rarely reported in HCC. In this study, we explored the function and mechanism of RACGAP1 in HCC through multiple analysis and experiments. RACGAP1 expression was up-regulated in HCC samples and the high expression of RACGAP1 was an independent prognostic risk factor for HCC patients. Meanwhile, RACGAP1 promoted developments of HCC both in vitro and in vivo. We verified that RACGAP1 promoted proliferation of HCC via PI3K/AKT/CDK2 and PI3K/AKT/GSK3β/Cyclin D1 signaling pathway. RACGAP1 accelerated the invasion and metastasis of HCC via phosphorylation of GSK3β and nuclear translocation of β-catenin. Furthermore, by luciferase reporter assay and Chromatin immunoprecipitation (ChIP) assay, we confirmed Recombinant GA Binding Protein Transcription Factor Alpha (GABPA) regulated the transcription of RACGAP1. All these findings revealed that RACGAP1 promotes the progression of HCC through a novel mechanism, which might be a new therapeutic target for HCC patients.

RacGAP1 promotes the malignant progression of cervical cancer by regulating AP-1 via miR-192 and p-JNK

Cervical cancer (CC) is the most frequently diagnosed genital tract cancer in females worldwide. Rac GTPase-activating protein 1 (RacGAP1) is one of the specific GTPase-activating proteins. As a novel tumor protooncogene, overexpression of RacGAP1 was related to the occurrence of various tumors, but its function in CC is still unclear. In this study, bioinformatics analyses showed that RacGAP1 might be a key candidate gene in the progression of CC. RacGAP1 was significantly overexpressed in CC tissues. High RacGAP1 expression was positively associated with poor prognosis. Downregulating RacGAP1 significantly inhibited the proliferation, migration, and invasion of CC cells, while overexpressing RacGAP1 had the opposite effects. Further research showed that miR-192, which plays as a tumor suppressor in CC, was identified as a downstream target of RacGAP1 in CC cells. miR-192 inhibition could partially rescue the decrease in cell proliferation, migration, and invasion caused by RacGAP1 downregulation. In opposite, miR-192 overexpression could decrease the promotion of malignant progression caused by RacGAP1 upregulation. Mechanism studies revealed that RacGAP1 could regulate the expression and phosphorylation of c-Jun, which was the component of AP-1, via miR-192 and p-JNK separately. These findings suggested that RacGAP1 promoted tumorigenicity, migration, and invasion of CC. Therefore, it represented a potential novel prognostic marker in CC and may probably be a therapeutic target.

Comprehensive analyses reveal the carcinogenic and immunological roles of ANLN in human cancers

Background

Anillin (ANLN) is an actin-binding protein that is essential for cell division and contributes to cell growth and migration. Although previous studies have shown that ANLN is related to carcinogenesis, no pan-cancer analyses of ANLN have been reported. Accordingly, in this study, we evaluated the carcinogenic roles of ANLN in various cancer types using online databases.

Methods

We evaluated the potential carcinogenic roles of ANLN using TIMER2 and Gene Expression Omnibus databases with 33 types of cancers. We further investigated the associations of ANLN with patient prognosis, genetic alterations, phosphorylation levels, and immune infiltration in multiple cancers using GEPIA2, cBioPortal, UACLAN, and TIMER2 databases. Additionally, the potential functions of ANLN were explored using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Reverse transcription quantitative polymerase chain reaction and immunohistochemistry were used to determine ANLN mRNA and protein expression in colorectal cancer (CRC), gastric cancer (GC), and hepatocellular carcinoma (HCC) cell lines.

Results

ANLN was overexpressed in various tumor tissues compared with corresponding normal tissues, and significant correlations between ANLN expression and patient prognosis, genetic alterations, phosphorylation levels, and immune infiltration were noted. Moreover, enrichment analysis suggested that ANLN functionally affected endocytosis, regulation of actin cytoskeleton, and oxytocin signaling pathways. Importantly, ANLN mRNA and protein expression levels were upregulated in gastrointestinal cancers, including CRC, GC, and HCC.

Conclusions

Our findings suggested that ANLN participated in tumorigenesis and cancer progression and may have applications as a promising biomarker of immune infiltration and prognosis in various cancers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02610-1.

Identification of potential biomarkers for diagnosis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) has a high mortality rate owing to its complexity. Identification of abnormally expressed genes in HCC tissues compared to those in normal liver tissues is a viable strategy for investigating the mechanisms of HCC tumorigenesis and progression as a means of developing novel treatments. A significant advantage of the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) is that the data therein were collected from different independent researchers and may be integrated, allowing for a more robust data analysis. Accordingly, in the present study, the gene expression profiles for HCC and control samples were downloaded from the GEO and TCGA. Functional enrichment analysis was performed using a Metascape dataset, and a protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/proteins (STRING) online database. The prognostic value of mRNA for HCC was assessed using the Kaplan-Meier Plotter, a public online tool. A gene mRNA heatmap and DNA amplification numbers were obtained from cBioPortal. A total of 2,553 upregulated genes were identified. Functional enrichment analysis revealed that these differentially expressed genes (DEGs) were mainly accumulated in metabolism of RNA and the cell cycle. Considering the complexity and heterogeneity of the molecular alterations in HCC, multiple genes for the prognostication of patients with HCC are more reliable than a single gene. Thus, the PPI network and univariate Cox regression analysis were applied to screen candidate genes (small nuclear ribonucleoprotein polypeptide B and B1, nucleoporin 37, Rac GTPase activating protein 1, kinesin family member 20A, minichromosome maintenance 10 replication initiation factor, ubiquitin conjugating enzyme E2 C and hyaluronan mediated motility receptor) that are associated with the overall survival and progression-free survival of patients with HCC. In conclusion, the present study identified a set of genes that are associated with overall survival and progression-free survival of patients with HCC, providing valuable information for the prognosis of HCC.

Identification of key genes and carcinogenic pathways in hepatitis B virus-associated hepatocellular carcinoma through bioinformatics analysis

Backgrounds/Aims

Mechanisms for the development of hepatocellular carcinoma (HCC) in hepatitis B virus (HBV)-infected patients remain unclear. The aim of the present study was to identify genes and pathways involved in the development of HBV-associated HCC.

Methods

The GSE121248 gene dataset, which included 70 HCCs and 37 adjacent liver tissues, was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) in HCCs and adjacent liver tissues were identified. Gene ontology and Kyoto Encyclopedia of Genes and Genome pathway enrichment analyses were then performed.

Results

Of 134 DEGs identified, 34 were up-regulated and 100 were down-regulated in HCCs. The 34 up-regulated DEGs were mainly involved in nuclear division, organelle fission, spindle and midbody formation, histone kinase activity, and p53 signaling pathway, whereas the 100 down-regulated DEGs were involved in steroid and hormone metabolism, collagen-coated extracellular matrix, oxidoreductase activity, and activity on paired donors, including incorporation or reduction of molecular oxygen, monooxygenase activity, and retinol metabolism. Analyses of protein-protein interaction networks with a high degree of connectivity identified significant modules containing 14 hub genes, including ANLN, ASPM, BUB1B, CCNB1, CDK1, CDKN3, ECT2, HMMR, NEK2, PBK, PRC1, RACGAP1, RRM2, and TOP2A, which were mainly associated with nuclear division, organelle fission, spindle formation, protein serine/threonine kinase activity, p53 signaling pathway, and cell cycle.

Conclusions

This study identified key genes and carcinogenic pathways that play essential roles in the development of HBV-associated HCC. This may provide important information for the development of diagnostic and therapeutic targets for HCC.

The emerging roles of srGAPs in cancer

GTPase activating proteins (GAPs) were initially considered as the inhibitors of cell signaling pathways because of their nature to activate the intrinsic GTPase activity of the RhoGTPases. But recent studies of dysregulated GAPs in many cancers such as glioblastoma, colorectal cancer, breast cancer, and renal cancer have elucidated the important roles of GAPs in carcinogenesis and GAPs have been shown to perform multiple nonconventional functions in different contexts. We have discussed the recent developments in the roles played by different types of srGAPs (SLIT-ROBO Rho GTPase-activating proteins) in cancer.

FaNDOM: Fast nested distance-based seeding of optical maps

Optical mapping (OM) provides single-molecule readouts of fluorescently labeled sequence motifs on long fragments of DNA, resolved to nucleotide-level coordinates. With the advent of microfluidic technologies for analysis of DNA molecules, it is possible to inexpensively generate long OM data ( > 150 kbp) at high coverage. In addition to scaffolding for de novo assembly, OM data can be aligned to a reference genome for identification of genomic structural variants. We introduce FaNDOM (Fast Nested Distance Seeding of Optical Maps)-an optical map alignment tool that greatly reduces the search space of the alignment process. On four benchmark human datasets, FaNDOM was significantly (4-14×) faster than competing tools while maintaining comparable sensitivity and specificity. We used FaNDOM to map variants in three cancer cell lines and identified many biologically interesting structural variants, including deletions, duplications, gene fusions and gene-disrupting rearrangements. FaNDOM is publicly available at https://github.com/jluebeck/FaNDOM.

Identifying Stage II Colorectal Cancer Recurrence Associated Genes by Microarray Meta-Analysis and Building Predictive Models with Machine Learning Algorithms

Background

Stage II colorectal cancer patients had heterogeneous prognosis, and patients with recurrent events had poor survival. In this study, we aimed to identify stage II colorectal cancer recurrence associated genes by microarray meta-analysis and build predictive models to stratify patients' recurrence-free survival.

Methods

We searched the GEO database to retrieve eligible microarray datasets. The microarray meta-analysis was used to identify universal recurrence associated genes. Total samples were randomly divided into the training set and the test set. Two survival models (lasso Cox model and random survival forest model) were trained in the training set, and AUC values of the time-dependent receiver operating characteristic (ROC) curves were calculated. Survival analysis was performed to determine whether there was significant difference between the predicted high and low risk groups in the test set.

Results

Six datasets containing 651 stage II colorectal cancer patients were included in this study. The microarray meta-analysis identified 479 recurrence associated genes. KEGG and GO enrichment analysis showed that G protein-coupled glutamate receptor binding and Hedgehog signaling were significantly enriched. AUC values of the lasso Cox model and the random survival forest model were 0.815 and 0.993 at 60 months, respectively. In addition, the random survival forest model demonstrated that the effects of gene expression on the recurrence-free survival probability were nonlinear. According to the risk scores computed by the random survival forest model, the high risk group had significantly higher recurrence risk than the low risk group (HR = 1.824, 95% CI: 1.079-3.084, p = 0.025).

Conclusions

We identified 479 stage II colorectal cancer recurrence associated genes by microarray meta-analysis. The random survival forest model which was based on the recurrence associated gene signature could strongly predict the recurrence risk of stage II colorectal cancer patients.

RACGAP1 modulates ECT2-Dependent mitochondrial quality control to drive breast cancer metastasis

Most cancer deaths are due to the colonization of tumor cells in distant organs. More evidence indicates that overexpression of RACGAP1 plays a critical role in cancer metastasis. However, the underlying mechanism still remains poorly understood. Here we found that RACGAP1 promoted breast cancer metastasis through regulating mitochondrial quality control. Overexpression of RACGAP1 in breast cancer cells led to the fragmentation of mitochondria, increased mitophagy intensity, mitochondrial turnover, and aerobic glycolysis ATP production. We showed that RACGAP1 promoted mitochondrial fission through recruiting ECT2 during anaphase and subsequently had activated ERK-DRP1 pathway. We further demonstrated the phosphorylation of RACGAP1 is essential for its ability of binding with ECT2 and its downstream effects. RACGAP1 overexpression also increased the expression of PGC-1a, a key mitochondrial biogenesis regulator, presumably by the increased mitophagy intensity induced by RACGAP1. PGC-1a increased the enrichment of DNMT1 in mitochondria, mitochondrial DNMT1 augmented mitochondrial DNA methylation and upregulated mitochondrial genome transcription. Our data indicated that RACGAP1 simultaneously facilitated mitophagy and mitochondrial biogenesis through regulating DRP1 phosphorylation and PGC-1a expression, eventually improved mitochondrial quality control in breast cancer cells. Our study provided a new angle in understanding the RACGAP1-overexpression related malignancy in breast cancer patients.

Long non-coding RNA RACGAP1P promotes breast cancer invasion and metastasis via miR-345-5p/RACGAP1-mediated mitochondrial fission

Long non-coding RNAs (lncRNAs) are emerging as key molecules in various cancers, yet their potential roles in the pathogenesis of breast cancer are not fully understood. Herein, using microarray analysis, we revealed that the lncRNA RACGAP1P, the pseudogene of Rac GTPase activating protein 1 (RACGAP1), was up-regulated in breast cancer tissues. Its high expression was confirmed in 25 pairs of breast cancer tissues and 8 breast cell lines by qRT-PCR. Subsequently, we found that RACGAP1P expression was positively correlated with lymph node metastasis, distant metastasis, TNM stage, and shorter survival time in 102 breast cancer patients. Then, in vitro and in vivo experiments were designed to investigate the biological function and regulatory mechanism of RACGAP1P in breast cancer cell lines. Overexpression of RACGAP1P in MDA-MB-231 and MCF7 breast cell lines increased their invasive ability and enhanced their mitochondrial fission. Conversely, inhibition of mitochondrial fission by Mdivi-1 could reduce the invasive ability of RACGAP1P-overexpressing cell lines. Furthermore, the promotion of mitochondrial fission by RACGAP1P depended on its competitive binding with miR-345-5p against its parental gene RACGAP1, leading to the activation of dynamin-related protein 1 (Drp1). In conclusion, lncRNA RACGAP1P promotes breast cancer invasion and metastasis via miR-345-5p/RACGAP1 pathway-mediated mitochondrial fission.

Preoperative heat shock protein 47 levels identify colorectal cancer patients with lymph node metastasis and poor prognosis

Accumulating evidence suggests that overexpression of heat shock protein 47 (HSP47) increases cancer progression, and that HSP47 level in the tumor-associated stroma may serve as a diagnostic marker in various cancers. The present study aimed to evaluate whether HSP47 gene expression in colorectal cancer (CRC) tissues could be used to identify lymph node (LN) metastasis status preoperatively in patients with CRC. To do so, HSP47 gene expression was determined and its association with the clinicopathological characteristics of patients with CRC was analyzed. A total of 139 surgical specimens from patients with CRC and 36 patients with benign colonic disease undergoing surgery at Mie University Hospital were analyzed. HSP47 gene expression was determined by reverse transcription quantitative PCR using Power SYBR Green PCR methods. Expression level of HSP47 was significantly higher in CRC tissues compared with normal tissue from patients with benign colonic disease. Furthermore, high HSP47 expression was significantly associated with tumor progression, including high T stage, lymph node metastasis and venous invasion, and high TNM stage. High HSP47 expression may therefore serve as a novel predictive biomarker for determining patients with CRC and LN metastasis. According to Kaplan-Meier analysis, patients with high HSP47 expression level had significantly poorer overall survival than those with low HSP47 expression level. Furthermore, multivariate analyses identified HSP47 expression as an independent predictive marker for LN metastasis and poor overall survival in patients with CRC. In summary, the present study demonstrated that HSP47 expression may be considered as a novel biomarker for predicting LN metastasis status and prognosis in patients with CRC.

RACGAP1 is transcriptionally regulated by E2F3, and its depletion leads to mitotic catastrophe in esophageal squamous cell carcinoma

Background

RACGAP1 has significant involvement in tumorigenesis of cancers, including liver cancer, stomach cancer, and colon cancer. However, the role and the exact mechanism of RACGAP1 in esophageal squamous cell carcinoma (ESCC) has not been explored.

Methods

QPCR and Western blots analysis was performed to analyze the expression of RACGAP1 in ESCC. MTT assays and colony formation assays were performed to explore the functional role of RACGAP1 in ESCC. Cell cycle analysis and immunofluorescence assays were used to investigate the function of RACGAP1 involvement in mitotic catastrophe. At last, we conducted the public datasets mining to explore the expression status and prognosis value of RACGAP1 as well as the correlation between RACGAP1 and E2F3 in various cancers.

Results

The high abnormal expression of RACGAP1 is observed in ESCC and associated with worse clinical outcomes of patients with ESCC. RACGAP1, a novel cell cycle associated gene regulated by E2F3, acts as an oncogenic driver in ESCC cell lines. Notably, for the first time, RACGAP1 depletion induced severe mitotic catastrophe, followed by massive cell death.

Conclusions

Our findings showed the essential role of RACGAP1 in ESCC cancer cell survival and the therapeutic potential of RACGAP1 as a molecular target for ESCC.

Bioinformatics analysis shows that TOP2A functions as a key candidate gene in the progression of cervical cancer

Cervical cancer (CC) is one of the most prevalent types of cancer affecting females worldwide. However, the molecular mechanisms underlying the development and progression of CC remains to be elucidated. Taking the high incidence and mortality rates amongst women into consideration, the identification of novel biomarkers to prevent CC is of great significance and required to improve diagnosis. Using three raw microarray datasets from the Gene Expression Omnibus database, 188 differentially expressed genes (DEGs) were identified. Gene Ontology and pathway analyses were performed on the DEGs. Through protein-protein interaction network construction and module analysis, eight hub genes [cell division cycle 6, cyclin-dependent kinase 1 (CDK1), cell division control protein 45, budding uninhibited by benzimidazoles 1 (BUB1), DNA topoisomerase II α (TOP2A) and minichromosome maintenance complex component 4, CCNB2 and CCNB1] were identified, but only TOP2A was considered a prognostic factor in survival analysis. There were strong positive correlations between TOP2A and BUB1 (P<0.0001, rs=0.635), CDK1 (P<0.0001, rs=0.511), centromere protein F (CENPF) (P<0.0001, rs=0.677), Rac GTPase activating protein 1 (RACGAP1) (P<0.0001, rs=0.612), F-box protein 5 (FBXO5) (P<0.0001, rs=0.585) and BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) (P<0.0001, rs=0.584). Additionally, BUB1, CDK1, CENPF, RACGAP1, FBXO5 and BUB1B are all potentially suitable candidate targets for the diagnosis and treatment of CC. In conclusion, the present study identified TOP2A as a potential tumor oncogene and a biomarker for the prognosis of CC.

Bioinformatics Analysis of Prognostic miRNA Signature and Potential Critical Genes in Colon Cancer

This study aims to lay a foundation for studying the regulation of microRNAs (miRNAs) in colon cancer by applying bioinformatics methods to identify miRNAs and their potential critical target genes associated with colon cancer and prognosis. Data of differentially expressed miRNAs (DEMs) and genes (DEGs) downloaded from two independent databases (TCGA and GEO) and analyzed by R software resulted in 472 DEMs and 565 DEGs in colon cancers, respectively. Next, we developed an 8-miRNA (hsa-mir-6854, hsa-mir-4437, hsa-mir-216a, hsa-mir-3677, hsa-mir-887, hsa-mir-4999, hsa-mir-34b, and hsa-mir-3189) prognostic signature for patients with colon cancer by Cox proportional hazards regression analysis. To predict the target genes of these miRNAs, we used TargetScan and miRDB. The intersection of DEGs with the target genes predicted for these eight miRNAs retrieved 112 consensus genes. GO and KEGG pathway enrichment analyses showed these 112 genes were mainly involved in protein binding, one-carbon metabolic process, nitrogen metabolism, proteoglycans in cancer, and chemokine signaling pathways. The protein-protein interaction network of the consensus genes, constructed using the STRING database and imported into Cytoscape, identified 14 critical genes in the pathogenesis of colon cancer (CEP55, DTL, FANCI, HMMR, KIF15, MCM6, MKI67, NCAPG2, NEK2, RACGAP1, RRM2, TOP2A, UBE2C, and ZWILCH). Finally, we verified the critical genes by weighted gene co-expression network analysis (WGCNA) of the GEO data, and further mined the core genes involved in colon cancer. In summary, this study identified an 8-miRNA model that can effectively predict the prognosis of colon cancer patients and 14 critical genes with vital roles in colon cancer carcinogenesis. Our findings contribute new ideas for elucidating the molecular mechanisms of colon cancer carcinogenesis and provide new therapeutic targets and biomarkers for future treatment and prognosis.

RacGAP1 ameliorates acute kidney injury by promoting proliferation and suppressing apoptosis of renal tubular cells

BACKGROUND

Acute kidney injury (AKI) remains correlated with high mortality. Novel therapeutic strategies are urgently needed for AKI patients. Rac GTPase-activating protein 1 (RacGAP1) regulates the activity of RhoGTPase and acts as a predictive biomarker in several types of malignant tumor but the role of RacGAP1 in AKI has not been revealed.

METHODS

Animal models of AKI induced by renal ischemia-reperfusion (I/R) and cisplatin treatment were generated in C57BL/6 mice. Hypoxia/reoxygenation (H/R) and cisplatin treatment were practiced in human renal tubular epithelial (HK-2) and renal tubular duct epithelial cells of rat (NRK-52E) cells. The role of RacGAP1 in cell proliferation and apoptosis was estimated using western bolting, immunocytochemistry and flow cytometry. Verteporfin was used to activate the Hippo pathway to show whether the protective effects of RacGAP1 on cell growth and survival in renal tubular cells were dependent on the activation of YAP.

RESULTS

The expression of RacGAP1 was significantly increased in mice kidneys after I/R or cisplatin treatment, combined with increased expression of RacGAP1 in H/R or cisplatin challenged cells. Overexpression of RacGAP1 protected HK2 and NRK-52E cells by promoting proliferation and decreasing apoptosis. We also disclosed that RacGAP1 exerted its function through activation of YAP.

CONCLUSION

The present study provides evidence that RacGAP1 is involved in AKI. It promotes proliferation and limits apoptosis of tubular epithelial cells via stimulating activation and nuclear translocation of YAP. Consequently, RacGAP1 may be a novel therapeutic target for AKI.

Rac1 Signaling: From Intestinal Homeostasis to Colorectal Cancer Metastasis

The small GTPase Rac1 has been implicated in a variety of dynamic cell biological processes, including cell proliferation, cell survival, cell-cell contacts, epithelial mesenchymal transition (EMT), cell motility, and invasiveness. These processes are orchestrated through the fine tuning of Rac1 activity by upstream cell surface receptors and effectors that regulate the cycling Rac1-GDP (off state)/Rac1-GTP (on state), but also through the tuning of Rac1 accumulation, activity, and subcellular localization by post translational modifications or recruitment into molecular scaffolds. Another level of regulation involves Rac1 transcripts stability and splicing. Downstream, Rac1 initiates a series of signaling networks, including regulatory complex of actin cytoskeleton remodeling, activation of protein kinases (PAKs, MAPKs) and transcription factors (NFkB, Wnt/β-catenin/TCF, STAT3, Snail), production of reactive oxygen species (NADPH oxidase holoenzymes, mitochondrial ROS). Thus, this GTPase, its regulators, and effector systems might be involved at different steps of the neoplastic progression from dysplasia to the metastatic cascade. After briefly placing Rac1 and its effector systems in the more general context of intestinal homeostasis and in wound healing after intestinal injury, the present review mainly focuses on the several levels of Rac1 signaling pathway dysregulation in colorectal carcinogenesis, their biological significance, and their clinical impact.

Identification of hub genes and pathways in adrenocortical carcinoma by integrated bioinformatic analysis

Adrenocortical carcinoma (ACC), a rare malignant neoplasm originating from adrenal cortical cells, has high malignancy and few treatments. Therefore, it is necessary to explore the molecular mechanism of tumorigenesis, screen and verify potential biomarkers, which will provide new clues for the treatment and diagnosis of ACC. In this paper, three gene expression profiles (GSE10927, GSE12368 and GSE90713) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were obtained using the Limma package. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were enriched by DAVID. Protein‐protein interaction (PPI) network was evaluated by STRING database, and PPI network was constructed by Cytoscape. Finally, GEPIA was used to validate hub genes’ expression. Compared with normal adrenal tissues, 74 up‐regulated DEGs and 126 down‐regulated DEGs were found in ACC samples; GO analysis showed that up‐regulated DEGs were enriched in organelle fission, nuclear division, spindle, et al, while down‐regulated DEGs were enriched in angiogenesis, proteinaceous extracellular matrix and growth factor activity; KEGG pathway analysis showed that up‐regulated DEGs were significantly enriched in cell cycle, cellular senescence and progesterone‐mediated oocyte maturation; Nine hub genes (CCNB1, CDK1, TOP2A, CCNA2, CDKN3, MAD2L1, RACGAP1, BUB1 and CCNB2) were identified by PPI network; ACC patients with high expression of 9 hub genes were all associated with worse overall survival (OS). These hub genes and pathways might be involved in the tumorigenesis, which will offer the opportunities to develop the new therapeutic targets of ACC.

The genetic association between type 2 diabetic and hepatocellular carcinomas

Background

Type 2 diabetes mellitus (T2DM) and hepatocellular carcinoma (HCC) are both major health problems throughout the world. It has been reported that T2DM is an independent risk factor for HCC, although the pathophysiology is still unclear.

Methods

In order to identify differentially expressed genes (DEGs) in T2DM and HCC, gene expression datasets for T2DM (GSE15653), HCC (GSE60502) and metformin-treated cells (GSE69850) were obtained from the Gene Expression Omnibus database repository. Protein-protein interaction (PPI) networks for the DEGs were constructed and gene clusters selected for functional enrichment analysis. Ten genes with the highest degree of connectivity were selected as hub genes and prognostic analysis together with analysis of gene expression and protein distribution were performed for these genes. Lastly, we investigated associations between the hub genes and genes associated with metformin treatment in hepatocarcinoma cells.

Results

In total, 256 common DEGs, including 155 up-regulated genes and 101 down-regulated genes, were identified. Enrichment analyses showed that the genes of the major module were largely associated with the cell cycle. All of the 10 hub genes (CCNA2, CCNB1, MAD2L1, BU1B, RACGAP1, CHEK1, BUB1, ASPM, NCAPG and TTK) have a strong association with lower overall survival in liver cancer patients and four genes (CCNA2, CCNB1, CHEK1 and BUB1) have reduced expression in metformin-treated samples.

Conclusions

This study identified a number of genes that may play important roles in the association of T2DM and HCC, including four genes which may be the target of metformin treatment for diabetes and HCC. The specific mechanisms involved remain to be identified.

CCNB2, NUSAP1 and TK1 are associated with the prognosis and progression of hepatocellular carcinoma, as revealed by co-expression analysis

The mortality rate associated with hepatocellular carcinoma (HCC) is the third highest among all digestive system tumors. However, the causes of HCC development and the underlying mechanisms have remained to be fully elucidated. In the present bioinformatics study, genetic markers were identified and their association with HCC was determined. The mRNA expression datasets GSE87630, GSE74656 and GSE76427 were downloaded from the Gene Expression Omnibus (GEO) database. A total of 96 differentially expressed genes (DEGs) were screened from the 3 GEO datasets, including 25 upregulated and 71 downregulated genes. DEGs were uploaded to the database for Annotation, Visualization and Integrated Discovery to screen for enriched Gene Ontology terms in various categories and the Search Tool for the Retrieval of Interacting Genes/Proteins was used to identify the interactions and functions of the DEGs. A total of 3 genetic markers were identified in a stepwise pathway and functional analysis in a previous study. The association of the genetic markers with prognosis was analysed using the UALCAN online analysis tool. Regression analysis was also performed to identify the relationship between HCC grade and disease recurrence and the expression of genetic markers using The Cancer Genome Atlas HCC dataset. In addition, the expression of the 3 genetic markers in HCC tissues was determined using reverse transcription-quantitative PCR, the Oncomine database and the Human Protein Atlas database. The expression levels of the 3 genetic markers cyclin B2 (CCNB2), nucleolar and spindle-associated protein 1 (NUSAP1) and thymidine kinase 1 (TK1) were significantly correlated with each other and high mRNA expression of CCNB2 was significantly associated with poor overall survival of patients with HCC. Receiver operating characteristic curve analysis indicated that NUSAP1 and TK1 were capable of distinguishing between recurrent and non-recurrent HCC. Furthermore, CCNB2, NUSAP1 and TK1 were highly correlated with the HCC grade. It was also indicated that the mRNA expression of CCNB2, NUSAPA and TK1 was increased in primary HCC tissues when compared with that in adjacent tissues. The present study identified that the CCNB2, NUSAP1 and TK1 genes may serve as prognostic markers for HCC, and may be of value from the perspectives of basic research and clinical treatment of HCC.

lncRNA MAGI2-AS3 Prevents the Development of HCC via Recruiting KDM1A and Promoting H3K4me2 Demethylation of the RACGAP1 Promoter

Accumulating studies have implicated the role of long non-coding RNAs (lncRNAs) in the pathogenesis of hepatocellular carcinoma (HCC) through the regulating transcription and mRNA stability. A recent report has linked Rac GTPase-activating protein 1 (RACGAP1) to the early recurrence of HCC. The current study aimed to ascertain whether MAGI2 antisense RNA 3 (MAGI2-AS3) influences the development of HCC by regulating RACGAP1. MAGI2-AS3 expression was initially quantified in both the HCC tissues and cell lines. In order to elucidate the role of MAGI2-AS3 in the development of HCC, MAGI2-AS3 was overexpressed or silenced in HCC cells after which cell proliferation, apoptosis, invasion, and migration were evaluated. Chromatin immunoprecipitation (ChIP), RNA immunoprecipitation (RIP), and biotin-labeled RNA pull-down assays were conducted to determine the interactions among MAGI2-AS3, KDM1A, and RACGAP1. Finally, the effects of MAGI2-AS3 and RACGAP1 on the tumorigenesis of transplanted HCC cells in nude mice were evaluated. MAGI2-AS3 was found to be under-expressed in HCC tissues and cell lines. The restoration of MAGI2-AS3 was identified to markedly inhibit HCC cell growth, migrating ability, and invasiveness, and promote cell apoptosis. Interaction between MAGI2-AS3 and KDM1A was identified. KDM1A recruited by MAGI2-AS3 was found to promote H3K4me2 demethylation at the RACGAP1 promoter, which ultimately decreased the expression of RACGAP1. We also identified that RACGAP1 knockdown eliminated the stimulatory effects of MAGI2-AS3 silencing on the malignant phenotypes of HCC cells. Additionally, the expression of MAGI2-AS3 reduced tumor weight and size in HCC transplanted nude mice. Taken together, the key observations of the current study demonstrate the potential of MAGI2-AS3 as a tumor suppressor and a promising target for HCC treatment.

Transcriptome sequencing profiles of cervical cancer tissues and SiHa cells

High-risk human papillomavirus (HPV) is a causal factor for cervical cancer, of which HPV16 is the predominant genotype, but the detailed mechanism remains to be elucidated. In this study, we performed transcriptome sequencing in cervical cancer tissues with HPV16-positive and normal tissues with HPV16-negative, and SiHa cells with or without HPV16 E6/E7 knockdown, and identified 140 differential expressed genes (DEGs) in two data sets. We carried out a series of bioinformatic analyses to learn more about the 140 DEGs, and found that 140 DEGs were mostly enriched in cell cycle and DNA repair through Kyoto Encyclopedia of Genes and Genomes pathway enrichment, Gene Ontology annotation, and gene set enrichment analysis. A total of 20 genes including RMI1, MKI67, FANCB, KIF14, CENPI, RACGAP1, EXO1, KIF4A, FOXM1, C19orf57, PSRC1, NUSAP1, CIT, NDC80, MCM7, GINS2, MCM6, ORC1, TLX2, and UHRF1 were screened by co-expression analysis; of those, the expressions of 6 (CENPI, FANCB, KIF14, ORC1, RACGAP1, and RMI1) were verified by qRT-PCR. Further, we found that E2F family, NF-Y, AhR:Arnt, and KROX family may be involved in modulating DEGs by TransFind prediction. TF2DNA database and co-expression analysis suggested that 12 TFs (ZNF367, TLX2, DEPDC1B, E2F8, ZNF541, EGR2, ZMAT3, HES6, CEBPA, MYBL2, FOXM1, and RAD51) were upstream modulators of DEGs. Our findings may provide a new understanding for effects of HPV oncogenes in the maintenance of cancerous state at the transcriptional level.

Lambda-Carrageenan Enhances the Effects of Radiation Therapy in Cancer Treatment by Suppressing Cancer Cell Invasion and Metastasis through Racgap1 Inhibition

Radiotherapy is used extensively in cancer treatment, but radioresistance and the metastatic potential of cancer cells that survive radiation remain critical issues. There is a need for novel treatments to improve radiotherapy. Here, we evaluated the therapeutic benefit of λ-carrageenan (CGN) to enhance the efficacy of radiation treatment and investigated the underlying molecular mechanism. CGN treatment decreased viability in irradiated cancer cells and enhanced reactive oxygen species accumulation, apoptosis, and polyploid formation. Additionally, CGN suppressed radiation-induced chemoinvasion and invasive growth in 3D lrECM culture. We also screened target molecules using a gene expression microarray analysis and focused on Rac GTPase-activating protein 1 (RacGAP1). Protein expression of RacGAP1 was upregulated in several cancer cell lines after radiation, which was significantly suppressed by CGN treatment. Knockdown of RacGAP1 decreased cell viability and invasiveness after radiation. Overexpression of RacGAP1 partially rescued CGN cytotoxicity. In a mouse xenograft model, local irradiation followed by CGN treatment significantly decreased tumor growth and lung metastasis compared to either treatment alone. Taken together, these results suggest that CGN may enhance the effectiveness of radiation in cancer therapy by decreasing cancer cell viability and suppressing both radiation-induced invasive activity and distal metastasis through downregulating RacGAP1 expression.

MERIT: Systematic Analysis and Characterization of Mutational Effect on RNA Interactome Topology

The interaction between RNA-binding proteins (RBPs) and RNA plays an important role in regulating cellular function. However, decoding genome-wide protein-RNA regulatory networks as well as how cancer-related mutations impair RNA regulatory activities in hepatocellular carcinoma (HCC) remains mostly undetermined. We explored the genetic alteration patterns of RBPs and found that deleterious mutations are likely to occur on the surface of RBPs. We then constructed protein-RNA interactome networks by integration of target binding screens and expression profiles. Network analysis highlights regulatory principles among interacting RBPs. In addition, somatic mutations selectively target functionally important genes (cancer genes, core fitness genes, or conserved genes) and perturb the RBP-gene regulatory networks in cancer. These regulatory patterns were further validated using independent data. A computational method (Mutational Effect on RNA Interactome Topology) and a web-based, user-friendly resource were further proposed to analyze the RBP-gene regulatory networks across cancer types. Pan-cancer analysis also suggests that cancer cells selectively target "vulnerability" genes to perturb protein-RNA interactome that is involved in cancer hallmark-related functions. Specifically, we experimentally validated four pairs of RBP-gene interactions perturbed by mutations in HCC, which play critical roles in cell proliferation. Based on the expression of perturbed RBP and target genes, we identified three subtypes of HCC with different survival rates. Conclusion: Our results provide a valuable resource for characterizing somatic mutation-perturbed protein-RNA regulatory networks in HCC, yielding valuable insights into the genotype-phenotype relationships underlying human cancer, and potential biomarkers for precision medicine.

Identification of hub genes in prostate cancer using robust rank aggregation and weighted gene co-expression network analysis

The pathogenic mechanisms of prostate cancer (PCa) remain to be defined. In this study, we utilized the Robust Rank Aggregation (RRA) method to integrate 10 eligible PCa microarray datasets from the GEO and identified a set of significant differentially expressed genes (DEGs) between tumor samples and normal, matched specimens. To explore potential associations between gene sets and PCa clinical features and to identify hub genes, we utilized WGCNA to construct gene co-expression networks incorporating the DEGs screened with the use of RRA. From the key module, we selected LMNB1, TK1, ZWINT, and RACGAP1 for validation. We found that these genes were up-regulated in PCa samples, and higher expression levels were associated with higher Gleason scores and tumor grades. Moreover, ROC and K-M plots indicated these genes had good diagnostic and prognostic value for PCa. On the other hand, methylation analyses suggested that the abnormal up-regulation of these four genes likely resulted from hypomethylation, while GSEA and GSVA for single hub gene revealed they all had a close association with proliferation of PCa cells. These findings provide new insight into PCa pathogenesis, and identify LMNB1, TK1, RACGAP1 and ZWINT as candidate biomarkers for diagnosis and prognosis of PCa.

Rac GTPase-Activating Protein 1 (RACGAP1) as an Oncogenic Enhancer in Esophageal Carcinoma

PURPOSE

Rac GTPase-activating protein 1 (RACGAP1) is associated with cell proliferation, and there is much evidence of its oncogenic role. This study investigated the clinical importance and functional role of RACGAP1 in esophageal carcinoma (EC).

METHODS

A total of 81 EC patients were enrolled in the study. We assessed the immunohistochemical score of EC tissues and adjacent normal esophageal mucosae, and then performed multiple cell function tests by means of in vitro experiments to elucidate the functional role of RACGAP1 using RNA interference technology in EC cell lines.

RESULTS

RACGAP1 was significantly overexpressed in EC tissues compared with the adjacent normal esophageal mucosae (p < 0.0001). Moreover, RACGAP1 overexpression was significantly correlated with poor overall survival (p = 0.032) and disease-free survival (p = 0.012) in EC patients. High RACGAP1 expression was also significantly correlated with the presence of lymphatic invasion (p = 0.012), vessel invasion (p = 0.003), and advanced TNM (tumor-node-metastasis) stage (p = 0.046) in EC patients. In vitro analysis demonstrated that RACGAP1 was involved in the proliferation, tumorigenicity, invasion, migration, and anoikis resistance in EC cells.

CONCLUSIONS

RACGAP1 plays a pivotal role in EC development, suggesting that it could be used as an indicator of prognosis in EC patients.

Pseudogene RACGAP1P activates RACGAP1/Rho/ERK signalling axis as a competing endogenous RNA to promote hepatocellular carcinoma early recurrence

Accumulating evidence has indicated crucial roles for pseudogenes in human cancers. However, the roles played by pseudogenes in the pathogenesis of HCC, particularly HCC early recurrence, still incompletely elucidated. Herein, we identify a novel early recurrence related pseudogene RACGAP1P which was significantly upregulated in HCC and was associated with larger tumour size, advanced clinical stage, abnormal AFP level and shorter survival time. In vitro and in vivo experiments have shown that RACGAP1P is a prerequisite for the development of malignant characteristics of HCC cells, including cell growth and migration. Mechanistic investigations indicated that RACGAP1P elicits its oncogenic activity as a ceRNA to sequestrate miR-15-5p from its endogenous target RACGAP1, thereby leading to the upregulation of RACGAP1 and the activation of RhoA/ERK signalling. These results may provide new insights into the functional crosstalk of the pseudogene/miRNA/parent-gene genetic network during HCC early relapse and may contribute to improving the clinical intervention for this subset of HCC patients.

Investigation of differentially expressed genes in nasopharyngeal carcinoma by integrated bioinformatics analysis

Nasopharyngeal carcinoma (NPC) is a common malignancy of the head and neck. The aim of the present study was to conduct an integrated bioinformatics analysis of differentially expressed genes (DEGs) and to explore the molecular mechanisms of NPC. Two profiling datasets, GSE12452 and GSE34573, were downloaded from the Gene Expression Omnibus database and included 44 NPC specimens and 13 normal nasopharyngeal tissues. R software was used to identify the DEGs between NPC and normal nasopharyngeal tissues. Distributions of DEGs in chromosomes were explored based on the annotation file and the CYTOBAND database of DAVID. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were applied. Additionally, a protein-protein interaction (PPI) network, constructed using the STRING database and visualized by Cytoscape, was used to identify hub genes, key modules and important transcription factors (TFs). A total of 906 DEGs were identified; 434 (47.90%) DEGs were upregulated and 472 (52.10%) were downregulated. The DEGs were demonstrated to be enriched in chromosome 7p15-p14, 2q31, 1q21-q22, 1q21, 4q21 and 1p31-p22. DEGs were mainly enriched for the following GO terms: 'Cilium movement', 'microtubule bundle formation' and 'axoneme assembly'. KEGG pathway enrichment analysis revealed that pathways for 'cell cycle', 'DNA replication', 'interleukin-17 signaling', 'amoebiasis' and 'glutathione metabolism' were enriched. In addition, a PPI network comprising 867 nodes and 1,241 edges was constructed. Finally, five hub genes (aurora kinase A, cell division cycle 6, mitotic arrest deficient 2-like 1, DNA topoisomerase 2α and TPX2 microtubule nucleation factor), 8 modules, and 14 TFs were identified. Modules analysis revealed that cyclin-dependent kinase 1 and exportin 1 were involved in the pathway of Epstein-Barr virus infection. In summary, the hub genes, key modules and TFs identified in this study may promote our understanding of the pathogenesis of NPC and require further in-depth investigation.

Identification of prognostic biomarkers for breast cancer based on miRNA and mRNA co-expression network

PURPOSE

Breast cancer (BC) remains a serious health threat for women due to its high incidence and the trend of rejuvenation. Accumulating evidence has highlighted that microRNAs (miRNAs) and messenger RNAs (mRNAs) could play important roles in various biological processes involved in the pathogenesis of BC. The present study aimed to identify potential prognostic biomarkers associated with BC.

METHODS

Here, original gene expression profiles of patients with BC was downloaded from The Cancer Genome Atlas (TCGA) database. TargetScan, miRDB, and miRTarBase databases were used to predict the target genes of prognostic-related differentially expressed miRNAs (DEMs). Subsequently, functional enrichment analysis and topological analysis were performed on the overlaps of target genes and differentially expressed mRNAs (DEGs), and Kaplan-Meier analysis was used to predict prognosis-related target genes to identify prognostic biomarkers.

RESULTS

A total of 218 DEMs and 2222 DEGs were extracted in which eight miRNAs were associated with prognosis, and 278 target DEGs were screened out incorporated into functional enrichment analysis and protein-protein interaction network visualization studies. Additionally, five hub genes (CXCL12, IGF1, LEF1, MMP1, and RACGAP1) were observed as potential biomarkers for BC prognosis through survival analysis.

CONCLUSION

We performed a distinctive correlation analysis of miRNA-mRNA in BC patients, and identified eight miRNAs and five hub genes may be effective biomarkers for the prognosis of BC patients.

Gene Regulation by Antitumor miR-204-5p in Pancreatic Ductal Adenocarcinoma: The Clinical Significance of Direct RACGAP1 Regulation

Previously, we established a microRNA (miRNA) expression signature in pancreatic ductal adenocarcinoma (PDAC) tissues using RNA sequencing and found significantly reduced expression of miR-204-5p. Here, we aimed to investigate the functional significance of miR-204-5p and to identify miR-204-5p target genes involved in PDAC pathogenesis. Cancer cell migration and invasion were significantly inhibited by ectopic expression of miR-204-5p in PDAC cells. Comprehensive gene expression analyses and in silico database searches revealed 25 putative targets regulated by miR-204-5p in PDAC cells. Among these target genes, high expression levels of RACGAP1, DHRS9, AP1S3, FOXC1, PRP11, RHBDL2 and MUC4 were significant predictors of a poor prognosis of patients with PDAC. In this study, we focused on RACGAP1 (Rac guanosine triphosphatase-activating protein 1) because its expression was most significantly predictive of PDAC pathogenesis (overall survival rate: p = 0.0000548; disease-free survival rate: p = 0.0014). Overexpression of RACGAP1 was detected in PDAC clinical specimens, and its expression enhanced the migration and invasion of PDAC cells. Moreover, downstream genes affected by RACGAP1 (e.g., MMP28, CEP55, CDK1, ANLN and S100A14) are involved in PDAC pathogenesis. Our strategy to identify antitumor miRNAs and their target genes will help elucidate the molecular pathogenesis of PDAC.

miR-4324-RACGAP1-STAT3-ESR1 feedback loop inhibits proliferation and metastasis of bladder cancer

Considering the importance of microRNAs (miRNAs) in regulating cellular processes, we performed microarray analysis and revealed miR-4324 as one of the most differentially expressed miRNAs in bladder cancer (BCa). Then, we discovered that miR-4324 was a negative regulator of Rac GTPase activating protein 1 (RACGAP1) and that RACGAP1 functioned as an oncogenic protein in BCa. Our studies indicated that ectopic overexpression of miR-4324 in BCa cells significantly suppressed cell proliferation and metastasis and enhanced chemotherapy sensitivity to doxorubicin by repressing RACGAP1 expression. Further studies showed that estrogen receptor 1 (ESR1) increased the expression of miR-4324 by binding to its promoter, while the downregulation of ESR1 in BCa was caused by hypermethylation of its promoter. p-STAT3 induced the enrichment of DNMT3B by binding to the ESR1 promoter and then induced methylation of the ESR1 promoter. In turn, RACGAP1 induced STAT3 phosphorylation, increasing p-STAT3 expression and promoting its translocation to the nucleus. Therefore, the miR-4324-RACGAP1-STAT3-ESR1 feedback loop could be a critical regulator of BCa progression.

Integrated Bioinformatics Analysis of Hub Genes and Pathways in Anaplastic Thyroid Carcinomas

Anaplastic thyroid carcinoma (ATC) is a very rare malignancy; the pathogenesis of which is still not fully understood. The aim of the present study was to identify hub genes and pathways in ATC by microarray expression profiling. Two independent datasets (GSE27155 and GSE53072) were downloaded from GEO database. The differentially expressed genes (DEGs) between ATC tissues and normal thyroid tissues were screened out by the limma package and then enriched by gene ontology (GO) and KEGG pathway analysis. The hub genes were selected by protein-protein interaction (PPI) analysis. A total of 141 common upregulated and 87 common downregulated genes were screened out. These DEGs were significantly enriched in the phagosome and NF-kappa B signaling pathway. Through PPI analysis, TOP2A, TYMS, CCNB1, RACGAP1, FEN1, PRC1, and UBE2C were selected as hub genes, which were highly expressed in ATC tissues. TCGA data suggested that the expression levels of TOP2A, TYMS, FEN1, and PRC1 genes were also upregulated in other histological subtypes of thyroid carcinoma. High expression of TOP2A, TYMS, FEN1, PRC1, or UBE2C gene significantly decreased disease-free survival of patients with other thyroid carcinomas. In conclusion, the present study identified several hub genes and pathways, which will contribute to elucidating the pathogenesis of ATC and providing therapeutic targets for ATC.

Expression and potential molecular mechanisms of miR‑204‑5p in breast cancer, based on bioinformatics and a meta‑analysis of 2,306 cases

Breast cancer (BC) is the most common cancer among women worldwide. However, there is insufficient research that focuses on the expression and molecular mechanisms of microRNA (miR)‑204‑5p in BC. In the current study, data were downloaded from the Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO) and the University of California Santa Cruz (UCSC) Xena databases. They were then used to undertake a meta‑analysis that leveraged the standard mean difference (SMD) and summarized receiver operating characteristic (sROC) to evaluate the expression of the precursor miR‑204 and mature miR‑204‑5p in BC. Additionally, an intersection of predicted genes, differentially expressed genes (DEGs) from the TCGA database and the GEO database were plotted to acquire desirable putative genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein‑protein interaction (PPI) network analyses were performed to assess the potential pathways and hub genes of miR‑204‑5p in BC. A decreased trend in precursor miR‑204 expression was detected in 1,077 BC tissue samples in comparison to 104 para‑carcinoma tissue samples in the TCGA database. Further, the expression of mature miR‑204‑5p was markedly downregulated in 756 BC tissue samples in comparison to 76 para‑carcinoma tissue samples in the UCSC Xena database. The outcome of the SMD from meta‑analysis also indicated that the expression of miR‑204‑5p was markedly reduced in 2,306 BC tissue samples in comparison to 367 para‑carcinoma tissue samples. Additionally, the ROC and sROC values indicated that miR‑204‑5p had a great discriminatory capacity for BC. In GO analysis, 'cell development', 'cell surface activity', and 'receptor agonist activity' were the most enriched terms; in KEGG analysis, 'endocytosis' was significantly enriched. Rac GTPase activating protein 1 (RACGAP1) was considered the hub gene in the PPI network. In conclusion, miR‑204‑5p may serve a suppressor role in the oncogenesis and advancement of BC, and miR‑204‑5p may have crucial functions in BC by targeting RACGAP1.

Predictive value of lymphangiogenesis and proliferation markers on mRNA level in urothelial carcinoma of the bladder after radical cystectomy

OBJECTIVE

To evaluate the mRNA expression of lymphangiogenesis and proliferation markers and to examine its association with histopathological characteristics and clinical outcome in patients with urothelial carcinoma of the bladder (UCB) after radical cystectomy (RC).

PATIENTS AND METHODS

Gene expression analysis of the vascular endothelial growth -C and -D (VEGF-C/-D), its receptor VEGF receptor-3 (VEGFR-3), MKI67, and RACGAP1 was performed in 108 patients after radical cystectomy and their correlation with clinical-pathological parameters was investigated. Uni- and multivariate regression analyses were used to identify predictors for cancer-specific survival (CSS), recurrence-free survival (RFS) and overall survival (OS) after RC.

RESULTS

The expression of RACGAP1 and VEGFR-3 showed an association with a higher pT stage (P = 0.049; P = 0.009). MKI67 showed an association with a high-grade urothelial carcinoma of the bladder (P = 0.021). VEGFR-3 expression was significantly associated with the presence of lymphovascular invasion (LVI) (P = 0.016) and lymph node metastases (pN+) (P = 0.028). With the univariate analysis, overexpression of VEGFR-3 (P = 0.029) and the clinical-pathological parameters pT stage (P < 0.0001), pN+ (P = 0.0004), LVI (P < 0.0001) and female gender (P = 0.021) were significantly associated with a reduced CSS. Multivariate analysis identified a higher pT stage (P = 0.017) and LVI (P = 0.008) as independent predictors for reduced CSS. Independent predictors for reduced OS were a higher pT stage (P = 0.0007) and LVI (P = 0.0021), while overexpression of VEGF-D was associated with better OS (P < 0.0001).

CONCLUSIONS

The mRNA expression of the investigated markers showed associations with common histopathological parameters. Increased expression of VEGF-D is independently associated with better overall survival.

Ectromelia virus induces tubulin cytoskeletal rearrangement in immune cells accompanied by a loss of the microtubule organizing center and increased α-tubulin acetylation

Ectromelia virus (ECTV) is an orthopoxvirus that productively replicates in dendritic cells (DCs), but its influence on the microtubule (MT) cytoskeleton in DCs is not known. Here, we show that ECTV infection of primary murine granulocyte-macrophage colony stimulating factor-derived bone marrow cells (GM-BM) downregulates numerous genes engaged in MT cytoskeleton organization and dynamics. In infected cells, the MT cytoskeleton undergoes dramatic rearrangement and relaxation, accompanied by disappearance of the microtubule organizing centre (MTOC) and increased acetylation and stabilization of MTs, which are exploited by progeny virions for intracellular transport. This indicates a strong ability of ECTV to subvert the MT cytoskeleton of highly specialized immune cells.