Overexpression of denticleless E3 ubiquitin protein ligase homolog (DTL) is related to poor outcome in gastric carcinoma. Oncotarget. 2015;6:36615-36624. [PMID: 26472028 PMCID: PMC4742199 DOI: 10.18632/oncotarget.5620]

Non-canonical function of histone methyltransferase G9a in the translational regulation of chronic inflammation

We report a novel translation-regulatory function of G9a, a histone methyltransferase and well-understood transcriptional repressor, in promoting hyperinflammation and lymphopenia; two hallmarks of endotoxin tolerance (ET)-associated chronic inflammatory complications. Using multiple approaches, we demonstrate that G9a interacts with multiple translation regulators during ET, particularly the N6-methyladenosine (m6A) RNA methyltransferase METTL3, to co-upregulate expression of certain m6A-modified mRNAs that encode immune-checkpoint and anti-inflammatory proteins. Mechanistically, G9a promotes m6A methyltransferase activity of METTL3 at translational/post-translational level by regulating its expression, its methylation, and its cytosolic localization during ET. Additionally, from a broader view extended from the G9a-METTL3-m6A translation regulatory axis, our translatome proteomics approach identified numerous "G9a-translated" proteins that unite the networks associated with inflammation dysregulation, T cell dysfunction, and systemic cytokine response. In sum, we identified a previously unrecognized function of G9a in protein-specific translation that can be leveraged to treat ET-related chronic inflammatory diseases.

Ubiquitination Is a Novel Post-Translational Modification of VMP1 in Autophagy of Human Tumor Cells

Autophagy is a tightly regulated catabolic process involved in the degradation and recycling of proteins and organelles. Ubiquitination plays an important role in the regulation of autophagy. Vacuole Membrane Protein 1 (VMP1) is an essential autophagy protein. The expression of VMP1 in pancreatic cancer stem cells carrying the activated Kirsten rat sarcoma viral oncogene homolog (KRAS) triggers autophagy and enables therapy resistance. Using biochemical and cellular approaches, we identified ubiquitination as a post-translational modification of VMP1 from the initial steps in autophagosome biogenesis. VMP1 remains ubiquitinated as part of the autophagosome membrane throughout autophagic flux until autolysosome formation. However, VMP1 is not degraded by autophagy, nor by the ubiquitin-proteasomal system. Mass spectrometry and immunoprecipitation showed that the cell division cycle protein cdt2 (Cdt2), the substrate recognition subunit of the E3 ligase complex associated with cancer, cullin-RING ubiquitin ligase complex 4 (CRL4), is a novel interactor of VMP1 and is involved in VMP1 ubiquitination. VMP1 ubiquitination decreases under the CRL inhibitor MLN4924 and increases with Cdt2 overexpression. Moreover, VMP1 recruitment and autophagosome formation is significantly affected by CRL inhibition. Our results indicate that ubiquitination is a novel post-translational modification of VMP1 during autophagy in human tumor cells. VMP1 ubiquitination may be of clinical relevance in tumor-cell-therapy resistance.

Gastric Cancer Biomarker Candidates Identified by Machine Learning and Integrative Bioinformatics: Toward Personalized Medicine

Gastric cancer (GC) is among the leading causes of cancer-related deaths worldwide. The discovery of robust diagnostic biomarkers for GC remains a challenge. This study sought to identify biomarker candidates for GC by integrating machine learning (ML) and bioinformatics approaches. Transcriptome profiles of patients with GC were analyzed to identify differentially expressed genes between the tumor and adjacent normal tissues. Subsequently, we constructed protein-protein interaction networks so as to find the significant hub genes. Along with the bioinformatics integration of ML methods such as support vector machine, the recursive feature elimination was used to select the most informative genes. The analysis unraveled 160 significant genes, with 88 upregulated and 72 downregulated, 10 hub genes, and 12 features from the variable selection method. The integrated analyses found that EXO1, DTL, KIF14, and TRIP13 genes are significant and poised as potential diagnostic biomarkers in relation to GC. The receiver operating characteristic curve analysis found KIF14 and TRIP13 are strongly associated with diagnosis of GC. We suggest KIF14 and TRIP13 are considered as biomarker candidates that might potentially inform future research on diagnosis, prognosis, or therapeutic targets for GC. These findings collectively offer new future possibilities for precision/personalized medicine research and development for patients with GC.

Pan-cancer analysis and experimental validation of DTL as a potential diagnosis, prognosis and immunotherapy biomarker

BACKGROUND

DTL has been found to be related with multiple cancers. However, comprehensive analyses, which identify the prediction value of DTL in diagnosis, prognosis, immune infiltration and treatment, have rarely been reported so far.

METHODS

Combined with the data online databases, the gene expression, gene mutation, function enrichment and the correlations with the immunity status and clinical indexes of DTL were analyzed. Expression of DTL and the degree of immune cell infiltration were examined by immunofluorescence (IF) and immunohistochemistry (IHC) and analyzed by statistical analysis. Furthermore, the influences of DTL on the cell cycle, cell proliferation and apoptosis were detected by live cell imaging, IF and flow cytometric (FC) analysis. Genomic stability assays were conducted by chromosome slide preparation.

RESULTS

DTL was widely expressed in various cells and tissues, while it was overexpressed in tumor tissues except acute myeloid leukemia (LAML). Pan-cancer bioinformatics analysis showed that the expression of DTL was correlated with the prognosis, immunotherapy, and clinical indexes in various cancers. In addition, gene set enrichment analysis (GSEA) uncovered that DTL was enriched in oocyte meiosis, pyrimidine metabolism, the cell cycle, the G2M checkpoint, mTORC1 signaling and E2F targets. Furthermore, the overexpression of DTL, and its association with immune cell infiltration and clinical indexes in liver hepatocellular carcinoma (LIHC), bladder urothelial carcinoma (BLCA) and stomach adenocarcinoma (STAD) were verified in our study. It was also verified that overexpression of DTL could regulate the cell cycle, promote cell proliferation and cause genomic instability in cultured cells, which may be the reason why DTL plays a role in the occurrence, progression and treatment of cancer.

CONCLUSIONS

Collectively, this study suggested that DTL is of clinical value in the diagnosis, prognosis and treatment of various cancers, and may be a potential biomarker in certain cancers.

A patient-specific functional module and path identification technique from RNA-seq data

With the advancement of new technologies, a huge amount of high dimensional data is being generated which is opening new opportunities and challenges to the study of cancer and diseases. In particular, distinguishing the patient-specific key components and modules which drive tumorigenesis is necessary to analyze. A complex disease generally does not initiate from the dysregulation of a single component but it is the result of the dysfunction of a group of components and networks which differs from patient to patient. However, a patient-specific network is required to understand the disease and its molecular mechanism. We address this requirement by constructing a patient-specific network by sample-specific network theory with integrating cancer-specific differentially expressed genes and elite genes. By elucidating patient-specific networks, it can identify the regulatory modules, driver genes as well as personalized disease networks which can lead to personalized drug design. This method can provide insight into how genes are associating with each other and characterized the patient-specific disease subtypes. The results show that this method can be beneficial for the detection of patient-specific differential modules and interaction between genes. Extensive analysis using existing literature, gene enrichment and survival analysis for three cancer types STAD, PAAD and LUAD shows the effectiveness of this method over other existing methods. In addition, this method can be useful for personalized therapeutics and drug design. This methodology is implemented in the R language and is available at https://github.com/riasatazim/PatientSpecificRNANetwork.

Bioinformatics Prediction and Machine Learning on Gene Expression Data Identifies Novel Gene Candidates in Gastric Cancer

Gastric cancer (GC) is one of the five most common cancers in the world and unfortunately has a high mortality rate. To date, the pathogenesis and disease genes of GC are unclear, so the need for new diagnostic and prognostic strategies for GC is undeniable. Despite particular findings in this regard, a holistic approach encompassing molecular data from different biological levels for GC has been lacking. To translate Big Data into system-level biomarkers, in this study, we integrated three different GC gene expression data with three different biological networks for the first time and captured biologically significant (i.e., reporter) transcripts, hub proteins, transcription factors, and receptor molecules of GC. We analyzed the revealed biomolecules with independent RNA-seq data for their diagnostic and prognostic capabilities. While this holistic approach uncovered biomolecules already associated with GC, it also revealed novel system biomarker candidates for GC. Classification performances of novel candidate biomarkers with machine learning approaches were investigated. With this study, AES, CEBPZ, GRK6, HPGDS, SKIL, and SP3 were identified for the first time as diagnostic and/or prognostic biomarker candidates for GC. Consequently, we have provided valuable data for further experimental and clinical efforts that may be useful for the diagnosis and/or prognosis of GC.

Cell cycle-related genes associate with sensitivity to hydrogen peroxide-induced toxicity

Reactive oxygen species (ROS) such as hydrogen peroxide (H2O2) are well-described agents in physiology and pathology. Chronic inflammation causes incessant H2O2 generation associated with disease occurrences such as diabetes, autoimmunity, and cancer. In cancer, conditioning of the tumor microenvironment, e.g., hypoxia and ROS generation, has been associated with disease outcomes and therapeutic efficacy. Many reports have investigated the roles of the action of H2O2 across many cell lines and disease models. The genes predisposing tumor cell lines to H2O2-mediated demise are less deciphered, however. To this end, we performed in-house transcriptional profiling of 35 cell lines and simultaneously investigated each cell line's H2O2 inhibitory concentration (IC25) based on metabolic activity. More than 100-fold differences were observed between the most resistant and sensitive cell lines. Correlation and gene ontology pathway analysis identified a rigid association with genes intertwined in cell cycle progression and proliferation, as such functional categories dominated the top ten significant processes. The ten most substantially correlating genes (Spearman r > 0.70 or < -0.70) were validated using qPCR, showing complete congruency with microarray analysis findings. Western blotting confirmed the correlation of cell cycle-related proteins negatively correlating with H2O2 IC25. Top genes related to ROS production or antioxidant defense were only modest in correlation (Spearman r > 0.40 or < -0.40). In conclusion, our in-house transcriptomic correlation analysis revealed a set of cell cycle-associated genes associated with a priori resistance or sensitivity to H2O2-induced cellular demise with the detailed and causative roles of individual genes remaining unclear.

Identification of DTL as Related Biomarker and Immune Infiltration Characteristics of Nasopharyngeal Carcinoma via Comprehensive Strategies

Purpose

Although considerable progress has been made in basic and clinical research on nasopharyngeal carcinoma (NPC), the biomarkers of the progression of NPC have not been fully studied and described. This study was designed to identify potential novel biomarkers for NPC using integrated analyses and explore the immune cell infiltration in this pathological process.

Methods

Five GEO data sets were downloaded from gene expression omnibus database (GEO) and analysed to identify differentially expressed genes (DEGs), followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. The four algorithms were adopted for screening of novel and key biomarkers for NPC, including random forest (RF) machine learning algorithm, least absolute shrinkage and selection operator (LASSO) logistic regression, support vector machine-recursive feature elimination (SVM-RFE), and weighted gene co-expression network analysis (WGCNA). Lastly, CIBERSORT was used to assess the infiltration of immune cells in NPC, and the correlation between diagnostic markers and infiltrating immune cells was analyzed.

Results

Herein, we identified 46 DEGs, and enrichment analysis results showed that DEGs and several kinds of signaling pathways might be closely associated with the occurrence and progression of NPC. DTL was recognized as NPC-related biomarker. DTL, also known as retinoic acid-regulated nuclear matrix-associated protein (RAMP), or DNA replication factor 2 (CDT2), is reported to be correlated with the cell proliferation, cell cycle arrest and cell invasion in hepatocellular carcinoma, breast cancer and gastric cancer. Immune infiltration analysis demonstrated that macrophages M0, macrophages M1 and T cells CD4 memory activated were linked to pathogenesis of NPC.

Conclusion

In summary, we adopted a comprehensive strategy to screen DTL as biomarkers related to NPC and explore the critical role of immune cell infiltration in NPC.

DTL Is a Prognostic Biomarker and Promotes Bladder Cancer Progression through Regulating the AKT/mTOR axis

Background

Denticleless E3 ubiquitin protein ligase homolog (DTL) has been reported to be an important regulator for tumorigenesis and progression. Nonetheless, the biological functions and molecular mechanisms of DTL in BCa remain elusive.

Methods

We implemented integrative bioinformatics analysis to explore the diagnostic and prognostic values of DTL based on The Cancer Genome Atlas (TCGA), ArrayExpress, and Gene Expression Omnibus (GEO) databases. Then, we utilized qRT-PCR and immunohistochemistry to verify the clinical significance of DTL expression according to clinical specimens and tissue microarray (TMA). Moreover, the biological functions and underlying mechanisms of DTL in BCa were investigated through in vitro and in vivo experiments.

Results

Integrative bioinformatics analysis revealed that DTL was a key gene associated with BCa progression, and increased DTL expression was correlated with malignant biological behavior and poor prognosis. Experiments on clinical specimens and tissue microarray (TMA) further confirmed our findings. Bioinformatics analysis demonstrated that DTL could be associated with cell cycle- and DNA replication-associated pathways in BCa. The suppression of DTL inhibited BCa cell proliferation, migration, and invasion in vivo and in vitro. Mechanistically, DTL may promote BCa progression through the AKT/mTOR pathway.

Conclusions

Increased DTL expression was correlated with malignant biological behavior and poor prognosis of BCa patients, and it may promote BCa progression through the AKT/mTOR pathway. Our research provided a potential predictor and therapeutic target for BCa.

Identification of Key Biomarkers and Pathways in Small-Cell Lung Cancer Using Biological Analysis

Background

Small-cell lung cancer (SCLC) is a major cause of carcinoma-related deaths worldwide. The aim of this study was to identify the key biomarkers and pathways in SCLC using biological analysis.

Methods

Key genes involved in the development of SCLC were identified by downloading three datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened using the GEO2R online analyzer; for the functional annotation and pathway enrichment analysis of genes, Funrich software was used. Construction of protein-to-protein interaction (PPI) networks was accomplished using the Search Tool for the Retrieval of Interacting Genes (STRING), and network visualization and module identification were performed using Cytoscape.

Results

A total of 268 DEGs were ultimately obtained. The enriched functions and pathways of the upregulated DEGs included cell cycle, mitotic, and DNA replication, and the downregulated DEGs were enriched in epithelial-to-mesenchymal transition, serotonin degradation, and noradrenaline. Analysis of significant modules demonstrated that the upregulated genes are primarily concentrated in functions related to cell cycle and DNA replication. Kaplan-Meier analysis of hub genes revealed that they may promote the carcinogenesis and progression of SCLC. The result of ONCOMINE demonstrated that these 10 hub genes were significantly overexpressed in SCLC compared with normal samples.

Conclusion

Identification of the molecular functions and signaling pathways of participating DEGs can deepen the current understanding of the molecular mechanisms of SCLC. The knowledge gained from this work may contribute to the development of treatment options and improve the prognosis of SCLC in the future.

Screening and predicted value of potential biomarkers for breast cancer using bioinformatics analysis

Breast cancer is the most common cancer and the leading cause of cancer-related deaths in women. Increasing molecular targets have been discovered for breast cancer prognosis and therapy. However, there is still an urgent need to identify new biomarkers. Therefore, we evaluated biomarkers that may aid the diagnosis and treatment of breast cancer. We searched three mRNA microarray datasets (GSE134359, GSE31448 and GSE42568) and identified differentially expressed genes (DEGs) by comparing tumor and non-tumor tissues using GEO2R. Functional and pathway enrichment analyses of the DEGs were performed using the DAVID database. The protein-protein interaction (PPI) network was plotted with STRING and visualized using Cytoscape. Module analysis of the PPI network was done using MCODE. The associations between the identified genes and overall survival (OS) were analyzed using an online Kaplan-Meier tool. The redundancy analysis was conducted by DepMap. Finally, we verified the screened HUB gene at the protein level. A total of 268 DEGs were identified, which were mostly enriched in cell division, cell proliferation, and signal transduction. The PPI network comprised 236 nodes and 2132 edges. Two significant modules were identified in the PPI network. Elevated expression of the genes Discs large-associated protein 5 (DLGAP5), aurora kinase A (AURKA), ubiquitin-conjugating enzyme E2 C (UBE2C), ribonucleotide reductase regulatory subunit M2(RRM2), kinesin family member 23(KIF23), kinesin family member 11(KIF11), non-structural maintenance of chromosome condensin 1 complex subunit G (NCAPG), ZW10 interactor (ZWINT), and denticleless E3 ubiquitin protein ligase homolog(DTL) are associated with poor OS of breast cancer patients. The enriched functions and pathways included cell cycle, oocyte meiosis and the p53 signaling pathway. The DEGs in breast cancer have the potential to become useful targets for the diagnosis and treatment of breast cancer.

MiR-490-5p Restrains Progression of Gastric cancer through DTL Repression

Gastric cancer (GC) accounts for a main cause of cancer-related deaths. This study sought for molecular mechanism of miR-490-5p/DTL axis in affecting GC progression, thus bringing new hope for treatment of GC. Expression data of differentially expressed miRNAs and mRNAs in GC tissue from TCGA database were analyzed. MiR-490-5p and DTL mRNA expression levels in GC were evaluated with qRT-PCR. Cell viability was confirmed with CCK-8 method. Cell cycle distribution and apoptosis were analyzed with flow cytometry. Cell migratory and invasive potential was proved with Transwell assay. The targeted relationship between DTL and miR-490-5p was analyzed with dual-luciferase assay. The results indicated a decreased miR-490-5p level in GC cells. MiR-490-5p upregulation hampered proliferation, migration, invasion and promote cell apoptosis. DTL was the target of and inversely associated with miR-490-5p, and it could remarkably induce the carcinogenesis of GC. MiR-490-5p mediated GC cell progression by DTL repression. In conclusion, miR-490-5p and DTL may be valuable in diagnosis and treatment for GC.

Identification of genes associated with clinicopathological features of colorectal cancer

Objective

To identify genes associated with the clinicopathological features of colorectal cancer (CRC).

Methods

Gene expression profiles were downloaded and preprocessed by GEOquery and affy R packages, respectively. The limma package was applied to identify the differentially expressed genes (DEGs) in CRC. Gene Ontology and Kyoto Gene and Genome Encyclopedia (KEGG) pathway enrichment analyses for the DEGs were carried out using the clusterProfiler package. Protein–protein interaction (PPI) and weighted gene co-expression (WGC) networks were constructed using the STRING database and WGCNA package, respectively.

Results

A total of 523 DEGs (283 downregulated and 240 upregulated genes) in CRC tissues were identified. These DEGs were mainly enriched in 111 biological processes, 16 cellular components and 40 molecular functions, such as proteinaceous extracellular matrix, extracellular structure organization and chemokine-mediated signalling pathway. PPI and WGC networks showed that four upregulated genes (KIF2C, CDC45, CEP55 and DTL) were key genes. Subgroup analysis based on individual cancer stages and histological subtypes indicated that the expression of these key genes was upregulated in CRC stages I–IV, adenocarcinoma and mucinous adenocarcinoma.

Conclusions

The study provides new insights into understanding the pathogenesis of CRC. These identified genes may act as potential targets for CRC diagnosis and treatment.

Identification of HCG18 and MCM3AP-AS1 That Associate With Bone Metastasis, Poor Prognosis and Increased Abundance of M2 Macrophage Infiltration in Prostate Cancer

Background:

Bone metastasis is a leading cause of the high mortality rate of prostate cancer (PCa), but curative strategies remain lacking. Recent studies suggest long non-coding RNAs (lncRNAs) may be potential targets to develop drugs. However, PCa bone metastasis-specifically-related lncRNAs were rarely reported. This study aimed to identify crucial lncRNAs and reveal their function mechanisms.

Methods:

GSE32269 and GSE26964 microarray datasets, downloaded from the Gene Expression Omnibus database, were used to analyze differentially expressed genes (DEGs)/lncRNAs (DELs) and miRNAs (DEMs), respectively. Weighted gene co-expression network analysis was performed to screen PCa bone metastasis-associated modules. The co-expression and competing endogenous RNAs (ceRNAs) networks were constructed to identify hub lncRNAs. Univariate Cox regression analysis was conducted to determine their prognostic values. The correlation of lncRNAs with immune infiltrating cells was analyzed by using Tumor IMmune Estimation Resource. Therapeutic drugs were predicted by querying the Connectivity Map (CMap) and the Comparative Toxicogenomics Database (CTD).

Results:

A total of 18 DELs, 2,614 DEGs and 86 DEMs were screened between bone metastatic and primary PCa samples. Four modules enriched by DEGs were shown to be bone metastasis-associated. LncRNA HCG18 and MCM3AP-AS1 were identified to be important because they existed in both of the co-expression and ceRNA networks (forming the relationship pairs: HCG18/MCM3AP-AS1-KNTC1, MCM3AP-AS1-hsa-miR-508-3p-DTL and HCG18/MCM3AP-AS1-hsa-miR-127-3p-CDKN3). All the genes in these interaction pairs were significantly associated with overall survival of PCa patients. Also, HCG18, MCM3AP-AS1 and their target mRNAs were positively correlated with various tumor-infiltrated immune cells, especially increased M2 macrophages. Valproic acid and trichostatin A may be effective to treat PCa bone metastasis by targeting HCG18 and MCM3AP-AS1.

Conclusion:

HCG18 and MCM3AP-AS1 that regulate M2 macrophage infiltration may be important targets to treat PCa bone metastasis and improve prognosis.

Bioinformatics analysis of multi-omics data identifying molecular biomarker candidates and epigenetically regulatory targets associated with retinoblastoma

Retinoblastoma (RB) is the commonest malignant tumor of the infant retina. Besides genetic changes, epigenetic events are also considered to implicate the occurrence of RB. This study aimed to identify significantly altered protein-coding genes, DNA methylation, microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and their molecular functions and pathways associated with RB, and investigate the epigenetically regulatory mechanism of DNA methylation modification and non-coding RNAs on key genes of RB via bioinformatics method.We obtained multi-omics data on protein-coding genes, DNA methylation, miRNAs, and lncRNAs from the Gene Expression Omnibus database. We identified differentially expressed genes (DEGs) using the Limma package in R, discerned their biological functions and pathways using enrichment analysis, and conducted the modular analysis based on protein-protein interaction network to identify hub genes of RB. Survival analyses based on The Cancer Genome Atlas clinical database were performed to analyze prognostic values of key genes of RB. Subsequently, we identified the differentially methylated genes, differentially expressed miRNAs (DEMs) and lncRNAs (DELs), and intersected them with key genes to analyze possible targets of the underlying epigenetic regulatory mechanisms. Finally, the ceRNA network of lncRNAs-miRNAs-mRNAs was constructed using Cytoscape.A total of 193 DEGs, 74 differentially methylated-DEGs (DM-DEGs), 45 DEMs, 5 DELs were identified. The molecular pathways of DEGs were enriched in cell cycle, p53 signaling pathway, and DNA replication. A total of 10 key genes were identified and found significantly associated with poor survival outcome based on survival analyses, including CDK1, BUB1, CCNB2, TOP2A, CCNB1, RRM2, KIF11, KIF20A, NDC80, and TTK. We further found that hub genes MCM6 and KIF14 were differentially methylated, key gene RRM2 was targeted by DEMs, and key genes TTK, RRM2, and CDK1 were indirectly regulated by DELs. Additionally, the ceRNA network with 222 regulatory associations was constructed to visualize the correlations between lncRNAs-miRNAs-mRNAs.This study presents an integrated bioinformatics analysis of genetic and epigenetic changes that may be associated with the development of RB. Findings may yield many new insights into the molecular biomarker candidates and epigenetically regulatory targets of RB.

Novel gene-specific translation mechanism of dysregulated, chronic inflammation reveals promising, multifaceted COVID-19 therapeutics

Hyperinflammation and lymphopenia provoked by SARS-CoV-2-activated macrophages contribute to the high mortality of Coronavirus Disease 2019 (COVID-19) patients. Thus, defining host pathways aberrantly activated in patient macrophages is critical for developing effective therapeutics. We discovered that G9a, a histone methyltransferase that is overexpressed in COVID-19 patients with high viral load, activates translation of specific genes that induce hyperinflammation and impairment of T cell function or lymphopenia. This noncanonical, pro-translation activity of G9a contrasts with its canonical epigenetic function. In endotoxin-tolerant (ET) macrophages that mimic conditions which render patients with pre-existing chronic inflammatory diseases vulnerable to severe symptoms, our chemoproteomic approach with a biotinylated inhibitor of G9a identified multiple G9a-associated translation regulatory pathways that were upregulated by SARS-CoV-2 infection. Further, quantitative translatome analysis of ET macrophages treated progressively with the G9a inhibitor profiled G9a-translated proteins that unite the networks associated with viral replication and the SARS-CoV-2-induced host response in severe patients. Accordingly, inhibition of G9a-associated pathways produced multifaceted, systematic effects, namely, restoration of T cell function, mitigation of hyperinflammation, and suppression of viral replication. Importantly, as a host-directed mechanism, this G9a-targeted, combined therapeutics is refractory to emerging antiviral-resistant mutants of SARS-CoV-2, or any virus, that hijacks host responses.

LMTK3 promotes tumorigenesis in bladder cancer via the ERK/MAPK pathway

Lemur tyrosine kinase 3 (LMTK3) is a key member of the serine–threonine tyrosine kinase family. It plays an important role in breast cancer tumorigenesis and progression. However, its biological role in bladder cancer remains elusive. In this study, we demonstrated that LMTK3 was overexpressed in bladder cancer and was positively correlated with bladder cancer malignancy. High LMTK3 expression predicted poor overall survival. Knockdown of LMTK3 in bladder cancer cells triggered cell‐cycle arrest at G2/M phase, suppressed cell growth, and induced cell apoptosis in bladder cancer cells. Furthermore, Transwell assays revealed that reduction of LMTK3 decreased cell migration by regulating the epithelial‐to‐mesenchymal transition pathway. Conversely, LKTM3 overexpression was shown to promote proliferation and migration of bladder cancer cells. We assessed phosphorylation of MEK and ERK1/2 in bladder cancer cells depleted of LMTK3 and demonstrated a reduced phosphorylation status compared with the control group. Using an MAPK signaling‐specific inhibitor, U0126, we could rescue the promotion of proliferation and viability in LMTK3‐overexpressing cells. In conclusion, we extend the status of LMTK3 as an oncogene in bladder cancer and provide evidence for its function via the activation of the ERK/MAPK pathway. Thus, targeting LMTK3 may hold potential as a diagnostic and prognostic biomarker and as a possible future treatment for bladder cancer.

The Non-coding Side of Medulloblastoma

Medulloblastoma (MB) is the most common pediatric brain tumor and a primary cause of cancer-related death in children. Until a few years ago, only clinical and histological features were exploited for MB pathological classification and outcome prognosis. In the past decade, the advancement of high-throughput molecular analyses that integrate genetic, epigenetic, and expression data, together with the availability of increasing wealth of patient samples, revealed the existence of four molecularly distinct MB subgroups. Their further classification into 12 subtypes not only reduced the well-characterized intertumoral heterogeneity, but also provided new opportunities for the design of targets for precision oncology. Moreover, the identification of tumorigenic and self-renewing subpopulations of cancer stem cells in MB has increased our knowledge of its biology. Despite these advancements, the origin of MB is still debated, and its molecular bases are poorly characterized. A major goal in the field is to identify the key genes that drive tumor growth and the mechanisms through which they are able to promote tumorigenesis. So far, only protein-coding genes acting as oncogenic drivers have been characterized in each MB subgroup. The contribution of the non-coding side of the genome, which produces a plethora of transcripts that control fundamental biological processes, as the cell choice between proliferation and differentiation, is still unappreciated. This review wants to fill this major gap by summarizing the recent findings on the impact of non-coding RNAs in MB initiation and progression. Furthermore, their potential role as specific MB biomarkers and novel therapeutic targets is also highlighted.

Common and specific gene signatures among three different endometriosis subtypes

Aims

To identify the common and specific molecular mechanisms of three well-defined subtypes of endometriosis (EMs): ovarian endometriosis (OE), peritoneal endometriosis (PE), and deep infiltrating endometriosis (DIE).

Methods

Four microarray datasets: GSE7305 and GSE7307 for OE, E-MTAB-694 for PE, and GSE25628 for DIE were downloaded from public databases and conducted to compare ectopic lesions (EC) with eutopic endometrium (EU) from EMs patients. Differentially expressed genes (DEGs) identified by limma package were divided into two parts: common DEGs among three subtypes and specific DEGs in each subtype, both of which were subsequently performed with the Kyoto Encyclopedia of Genes (KEGG) pathway enrichment analysis. The protein-protein interaction (PPI) network was constructed by common DEGs and five hub genes were screened out from the PPI network. Besides, these five hub genes together with selected interested pathway-related genes were further validated in an independent OE RNA-sequencing dataset GSE105764.

Results

A total of 54 EC samples from three EMs subtypes (OE, PE, DIE) and 58 EU samples were analyzed, from which we obtained 148 common DEGs among three subtypes, and 729 specific DEGs in OE, 777 specific DEGs in PE and 36 specific DEGs in DIE. The most enriched pathway of 148 shared DEGs was arachidonic acid (AA) metabolism, in which most genes were up-regulated in EC, indicating inflammation was the most common pathogenesis of three subtypes. Besides, five hub genes AURKB, RRM2, DTL, CCNB1, CCNB2 identified from the PPI network constructed by 148 shared DEGs were all associated with cell cycle and mitosis, and down-regulated in EC, suggesting a slow and controlled proliferation in ectopic lesions. The KEGG pathway analysis of specific DEGs in each subtype revealed that abnormal ovarian steroidogenesis was a prominent feature in OE; OE and DIE seems to be at more risk of malignant development since both of their specific DEGs were enriched in the pathways in cancer, though enriched genes were different, while PE tended to be more associated with dysregulated peritoneal immune and inflammatory microenvironment.

Conclusion

By integrated bioinformatic analysis, we explored common and specific molecular signatures among different subtypes of endometriosis: activated arachidonic acid (AA) metabolism-related inflammatory process and a slow and controlled proliferation in ectopic lesions were common features in OE, PE and DIE; OE and DIE seemed to be at more risk of malignant development while PE tended to be more associated with dysregulated peritoneal immune and inflammatory microenvironment, all of which could deepen our perception of endometriosis.

Bioinformatic analysis identifies potentially key differentially expressed genes in oncogenesis and progression of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most common and lethal types of cancer within the urinary system. Great efforts have been made to elucidate the pathogeny. However, the molecular mechanism of ccRCC is still not well understood. The aim of this study is to identify key genes in the carcinogenesis and progression of ccRCC. The mRNA microarray dataset GSE53757 was downloaded from the Gene Expression Omnibus database. The GSE53757 dataset contains tumor and matched paracancerous specimens from 72 ccRCC patients with clinical stage I to IV. The linear model of microarray data (limma) package in R language was used to identify differentially expressed genes (DEGs). The protein–protein interaction (PPI) network of the DEGs was constructed using the search tool for the retrieval of interacting genes (STRING). Subsequently, we visualized molecular interaction networks by Cytoscape software and analyzed modules with MCODE. A total of 1,284, 1,416, 1,610 and 1,185 up-regulated genes, and 932, 1,236, 1,006 and 929 down-regulated genes were identified from clinical stage I to IV ccRCC patients, respectively. The overlapping DEGs among the four clinical stages contain 870 up-regulated and 645 down-regulated genes. The enrichment analysis of DEGs in the top module was carried out with DAVID. The results showed the DEGs of the top module were mainly enriched in microtubule-based movement, mitotic cytokinesis and mitotic chromosome condensation. Eleven up-regulated genes and one down-regulated gene were identified as hub genes. Survival analysis showed the high expression of CENPE, KIF20A, KIF4A, MELK, NCAPG, NDC80, NUF2, TOP2A, TPX2 and UBE2C, and low expression of ACADM gene could be involved in the carcinogenesis, invasion or recurrence of ccRCC. Literature retrieval results showed the hub gene NDC80, CENPE and ACADM might be novel targets for the diagnosis, clinical treatment and prognosis of ccRCC. In conclusion, the findings of present study may help us understand the molecular mechanisms underlying the carcinogenesis and progression of ccRCC, and provide potential diagnostic, therapeutic and prognostic biomarkers.

Identification of key biomarkers associated with development and prognosis in patients with ovarian carcinoma: evidence from bioinformatic analysis

BACKGROUND

Ovarian cancer (OC) is the deadliest cause in the gynecological malignancies. Most OC patients are diagnosed in advanced stages with less than 40% of women cured. However, the possible mechanism underlying tumorigenesis and candidate biomarkers remain to be further elucidated.

RESULTS

Gene expression profiles of GSE18520, GSE54388, and GSE27651 were available from Gene Expression Omnibus (GEO) database with a total of 91 OC samples and 22 normal ovarian (OV) tissues. Three hundred forty-nine differentially expressed genes (DEGs) were screened between OC tissues and OV tissues via GEO2R and online Venn software, followed by KEGG pathway and gene ontology (GO) enrichment analysis. The enriched functions and pathways of these DEGs contain male gonad development, cellular response to transforming growth factor beta stimulus, positive regulation of transcription from RNA polymerase II promoter, calcium independent cell-cell adhesion via plasma membrane cell adhesion molecules, extracellular matrix organization, pathways in cancer, cell cycle, cell adhesion molecules, PI3K-AKT signaling pathway, and progesterone mediated oocyte maturation. The protein-protein network (PPI) was established and module analysis was carried out using STRING and Cytoscape. Next, with PPI network analyzed by four topological methods in Cytohubba plugin of Cytoscape, 6 overlapping genes (DTL, DLGAP5, KIF15, NUSAP1, RRM2, and TOP2A) were eventually selected. GEPIA and Oncomine were implemented for validating the gene expression and all the six hub genes were highly expressed in OC specimens compared to normal OV tissues. Furthermore, 5 of 6 genes except for DTL were associated with worse prognosis using Kaplan Meier-plotter online tool and 3 of 6 genes were significantly related to clinical stages, including RRM2, DTL, and KIF15. Additionally, cBioPortal showed that TOP2A and RRM2 were the targets of cancer drugs in patients with OC, indicating the other four genes may also be potential drug targets.

CONCLUSION

Six hub genes (DTL, DLGAP5, KIF15, NUSAP1, RRM2, and TOP2A) present promising predictive value for the development and prognosis of OC and may be used as candidate targets for diagnosis and treatment of OC.

Identification of novel mRNA-miRNA-lncRNA competing endogenous RNA network associated with prognosis of breast cancer

Aim: To identify novel competing endogenous RNA (ceRNA) network related to patients prognosis in breast cancer. Materials & methods: Dysregulated mRNA based on intersection of three Gene Expression Omnibus and The Cancer Genome Atlas datasets were analyzed by bioinformatics. Results: In total 72 upregulated and 208 downregulated genes were identified. Functional analysis showed that some pathways related to cancer were significantly enriched. By means of stepwise reverse prediction and validation from mRNA to lncRNA, 19 hub genes, nine key miRNA and four key lncRNAs were identified by expression and survival analysis. Ultimately, the coexpression analysis identified RRM2-let-7a-5p-SNHG16/MAL2 as key ceRNA subnetwork associated with prognosis of breast cancer. Conclusion: We successfully constructed a novel ceRNA network, among which each component was significantly associated with breast cancer prognosis.

Common Molecular Alterations in Canine Oligodendroglioma and Human Malignant Gliomas and Potential Novel Therapeutic Targets

Spontaneous canine (Canis lupus) oligodendroglioma (ODG) holds tremendous potential as an immunocompetent large animal model of human malignant gliomas (MG). However, the feasibility of utilizing this model in pre-clinical studies depends on a thorough understanding of the similarities and differences of the molecular pathways associated with gliomas between the two species. We have previously shown that canine ODG has an immune landscape and expression pattern of commonly described oncogenes similar to that of human MG. In the current study, we performed a comprehensive analysis of canine ODG RNAseq data from 4 dogs with ODG and 2 normal controls to identify highly dysregulated genes in canine tumors. We then evaluated the expression of these genes in human MG using Xena Browser, a publicly available database. STRING-database inquiry was used in order to determine the suggested protein associations of these differentially expressed genes as well as the dysregulated pathways commonly enriched by the protein products of these genes in both canine ODG and human MG. Our results revealed that 3,712 (23%) of the 15,895 differentially expressed genes demonstrated significant up- or downregulation (log2-fold change > 2.0). Of the 3,712 altered genes, ~50% were upregulated (n = 1858) and ~50% were downregulated (n = 1854). Most of these genes were also found to have altered expression in human MG. Protein association and pathway analysis revealed common pathways enriched by members of the up- and downregulated gene categories in both species. In summary, we demonstrate that a similar pattern of gene dysregulation characterizes both human MG and canine ODG and provide additional support for the use of the canine model in order to therapeutically target these common genes. The results of such therapeutic targeting in the canine model can serve to more accurately predict the efficacy of anti-glioma therapies in human patients.

DTL promotes cancer progression by PDCD4 ubiquitin-dependent degradation

Background

Ubiquitin E3 ligase CUL4A plays important oncogenic roles in the development of cancers. DTL, one of the CUL4-DDB1 associated factors (DCAFs), may involve in the process of cancer development. Programmed cell death 4 (PDCD4) is a tumor suppressor gene involved in cell apoptosis, transformation, invasion and tumor progression.

Methods

Affinity-purification mass spectrometry was used to identify potential DTL interaction proteins. Co-immunoprecipitation (Co-IP) was performed to verify protein interaction between DTL and PDCD4. mRNA levels in cancer cells and tissues were detected by Quantitative real-time PCR. Lentivirus was used to establish stable overexpression and knocking down cell lines for DTL and PDCD4. Transwell and wound healing assays were used to determine migration ability of cancer cells. Matrigel assay was used to determine invasion ability of cancer cells. MTT and colony formation assays were used to evaluate proliferation of cancer cells.

Results

In this study, programmed cell death 4 (PDCD4) was identified as a potential substrate of DTL. Co-IP and immunofluorescence assays further confirmed the interaction between DTL and PDCD4. Moreover, DTL overexpression decreased the protein level and accelerated the degradation rate of PDCD4. Through in vitro ubiquitination experiment, we proved that PDCD4 was degraded by DTL through ubiquitination. Clinically DTL was significantly up-regulated in cancer tissues than that in normal tissues. The survival curves showed that cancer patients with higher DTL expression owned lower survival rate. Functional experiments showed that DTL not only enhanced the proliferation and migration abilities of cancer cells, but also promoted the tumorigenesis in nude mice. Rescued experiment results demonstrated that silencing PDCD4 simultaneous with DTL recovered the phenotypes defect caused by DTL knocking down.

Conclusions

Our results elucidated that DTL enhanced the motility and proliferation of cancer cells through degrading PDCD4 to promote the development of cancers.

Electronic supplementary material

The online version of this article (10.1186/s13046-019-1358-x) contains supplementary material, which is available to authorized users.

Identification of a functional polymorphism within the 3'-untranslated region of denticleless E3 ubiquitin protein ligase homolog associated with survival in acral melanoma

BACKGROUND

High expression of denticleless E3 ubiquitin protein ligase homologue (DTL) correlates with poor disease-free survival and overall survival in cutaneous melanoma, but the molecular features and clinical significance of this gene in acral melanoma (AM) remain unclear.

METHODS

The expression levels of DTL were compared between AM and benign melanocytic nevi using existing Gene Expression Omnibus data and validated in fresh frozen tissues. Two candidate tag single-nucleotide polymorphisms (SNPs) in the 3'-untranslated region (3'UTR) of DTL in patients with AM were sequenced and analysed for their association with survival in a discovery cohort (n = 570), and the significant SNP was subjected to a replication cohort (n = 201). The expression of DTL was evaluated by immunohistochemistry. The microRNA interacting with rs11275300:C > G was predicted using in silico target prediction tools and validated by in vitro analysis.

RESULTS

DTL was overexpressed in AM compared with benign melanocytic nevi. rs11275300:C > G was found to be significantly associated with progression-free survival and overall survival of patients with AM in both cohorts and the combined cohort. Furthermore, the DTL expression level in the patients with the rs11275300:G allele was higher than that in patients with the CC genotype. In vitro analysis demonstrated that DTL was a direct target of hsa-miR-4672, and the rs11275300:G allele interfered with the binding affinity of hsa-miR-4672 with the 3'UTR of DTL and thereby increased DTL expression.

CONCLUSION

The rs11275300:G allele in the 3'UTR of DTL may lead to a poor prognosis and allele-specific increase in the expression of DTL by post-transcriptional regulation in AM.

PPARα gene is a diagnostic and prognostic biomarker in clear cell renal cell carcinoma by integrated bioinformatics analysis

Genetic alterations in lipid metabolism genes are correlated with progression and poor prognosis of Clear cell renal cell carcinoma (ccRCC). PPARα play a critical role in lipid metabolism. This study aimed to identify that PPARα is a diagnosis and prognostic biomarker in ccRCC by integrated bioinformatics analysis. UALCAN database was used to explore the differential expression status and prognostic value of PPARα gene in various tumor types, qRT-PCR and immunohistochemical staining experiments were utilized for validation. Next, ccRCC data were obtained from TCGA. Correlation between PPARα expression levels and patients' clinicopathological characteristics was assessed, and the clinically diagnosis and prognostic value of PPARα were explored in ccRCC. According to the gene set enrichment analysis (GSEA) analysis, PPARα gene associated biological pathways were identified. PPARα has prognostic significance only in ccRCC tumors. Expression of PPARα was associated with ccRCC stages. PPARα was significantly down-regulated in ccRCC and associated with survival. Gender, tumor dimension, grade and stage showed a significant relevance with PPARα expression. Lower PPARα expression revealed significantly poorer survival and progression compared with higher PPARα expression. Adjusted by other clinical risk factors, PPARα remained an independent prognostic factor. Moreover, Low PPARα expression was a potential diagnostic biomarker of ccRCC. A nomogram was constructed based on PPARα expression and other clinicopathological risk factors, and it performed well in predict patients survival. GSEA analysis showed that PPARα gene associated biological pathways were enriched in mTOR pathway, AKT pathway, IGF1-mTOR pathway and Wnt signaling pathways. In conclusion, PPARα expression was decreased in ccRCC tumors. Lower expression of PPARα is closely correlated with poorer survival. It can be used as a clinically diagnosis and prognostic biomarker in ccRCC.

Integrative analyses of key genes and regulatory elements in fluoride-affected osteosarcoma

Osteosarcoma is one of the most malignant tumors in adolescents with severe outcomes while fluoride is one of the most abundant elements in the environment. Epidemiological evidence has elucidated the relationship between fluoride and osteosarcoma, but the molecular mechanisms are extremely complicated. Microarray profiles were downloaded from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) in the progression of fluoride-affected osteosarcoma. The functional enrichment analysis was performed, a protein-protein interaction network, a microRNA-messenger RNA (mRNA) and a transcription factors-mRNA regulatory network were constructed and performed using Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape. A total of 171 DEGs were identified. The functions and pathways of the DEGs were enriched in nucleolus, protein ubiquitination, protein binding, RNA transport, and the spliceosome. Eighteen hub genes were identified and functional analysis revealed that these genes are mainly enriched in protein binding, nucleoplasm, and ribosomal RNA processing. Survival analysis showed that the hub genes may be involved in the invasion or recurrence of osteosarcoma. In conclusion, the DEGs and hub genes with their regulatory elements identified in this study will help us understand the molecular mechanisms underlying fluoride-affected osteosarcoma and provide candidate targets for future research.

Dysregulated circular RNAs in medulloblastoma regulate proliferation and growth of tumor cells via host genes

Circular RNAs (circRNAs) have been demonstrated to be involved in various biological processes. Nevertheless, the function of circRNAs in medulloblastoma (MB) is still unknown. The present study aimed to investigate the expression profiles of circRNAs and related mechanisms for regulating the proliferation and growth of tumor cells in MB. The expression profiles of circRNAs were screened from four normal cerebellum and four MB samples using a HiSeq Sequencer. Bioinformatic analysis was employed to predict the interaction between circRNAs and mRNAs in MB. Subsequently, the expression levels of eight differential circRNAs [circ-SKA3 (hsa_circ_0029696), circ-DTL (hsa_circ_0000179), circ-CRTAM, circ-MAP3K5 (hsa_circ_0006856), circ-RIMS1-1 (hsa_circ_0132250), circ-RIMS1-2 (hsa_circ_0076967), circ-FLT3-1 (hsa_circ_0100165), and circ-FLT3-2 (hsa_circ_0100168)] were validated using quantitative reverse transcription-polymerase chain reaction. Moreover, circ-SKA3 and circ-DTL were silenced using small interfering RNAs and their host genes were overexpressed to investigate their role in the pathogenesis of MB. A total of 33 circRNAs were found to be differentially expressed in MB tissues (fold change ≥ 2.0, FDR <0.05), of which three were upregulated and 30 were downregulated; six circRNAs were experimentally validated successfully. Upregulated circ-SKA3 and circ-DTL promoted the proliferation migration and invasion in vitro by regulating the expression of host genes. This novel study exploited the profiling of circRNAs in MB and demonstrated that circ-SKA3 and circ-DTL were crucial in the tumorigenesis and development of MB and might be considered as novel and potential biomarkers for the diagnosis and new targets for the intervention of MB.

A functional genomics screen reveals a strong synergistic effect between docetaxel and the mitotic gene DLGAP5 that is mediated by the androgen receptor

Based on a molecular classification of prostate cancer using gene expression pathway signatures, we derived a set of 48 genes in critical pathways that significantly predicts clinical outcome in all tested patient cohorts. We tested these genes in a functional genomics screen in a panel of three prostate cancer cell lines (LNCaP, PC3, DU145), using RNA interference. The screen revealed several genes whose knockdown caused strong growth inhibition in all cell lines. Additionally, we tested the gene set in the presence of docetaxel to see whether any gene exhibited additive or synergistic effects with the drug. We observed a strong synergistic effect between DLGAP5 knockdown and docetaxel in the androgen-sensitive line LNCaP, but not in the two other androgen-independent lines. We then tested whether this effect was connected to androgen pathways and found that knockdown of the androgen receptor by si-RNA attenuated the synergy significantly. Similarly, androgen desensitized LNCaP-AI cells had a higher IC50 to docetaxel and did not exhibit the synergistic interaction. Short-term exposure to enzalutamide did not significantly alter the behaviour of parental LNCaP cells. An immunofluorescence analysis in LNCaP cells suggests that under the double insult of DLGAP5 knockdown and docetaxel, cells predominantly arrest in metaphase. In contrast, the knockdown of the androgen receptor by siRNA appears to assist cells to progress through metaphase in to anaphase, even in the presence of docetaxel. Our data suggest that DLGAP5 has a unique function in stabilizing spindle formation and surviving microtubule assault from docetaxel, in an androgen-regulated cell cycle system.

Potential biomarkers of HCC based on gene expression and DNA methylation profiles

The aim of the present study was to identify potential biomarkers of hepatocellular carcinoma (HCC). Three gene expression profiles of GSE95698, GSE49515 and GSE76427 and a DNA methylation profile of GSE73003 were downloaded from the Gene Expression Omnibus (GEO) database, each comprising data regarding HCC and control tissue samples. The differentially expressed genes (DEGs) between the HCC group and the control group were identified using the limma software package. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the overlapping DEGs. The PPI network of the overlapping DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins. A total of 41 DEGs were identified in HCC the group compared with control group. The overlapping DEGs were enriched in 11 GO terms and 3 KEGG pathways. A total of 6,349 DMSs were identified, and 6 of the differentially expressed genes were also differentially methylated [Denticleless protein homolog (DTL), Dual specificity phosphatase 1 (DUSP1), Eomesodermin, Endothelial cell specific molecule 1, Nuclear factor κ-light-chain gene enhancer of activated B cells inhibitor, α (NFKBIA) and suppressor of cytokine signaling 2 (SOCS2)]. The present study suggested that DTL, DUSP1, NFKBIA and SOCS2 may be potential biomarkers of HCC, and the tumor protein 'p53 signaling', 'forkhead box O1' signaling and 'metabolic' pathways may serve roles in the pathogenesis of HCC.

Potential new biomarkers for squamous carcinoma of the uterine cervix

Aim

An in silico pathway analysis was performed in an attempt to identify new biomarkers for cervical carcinoma.

Methods

Three publicly available Affymetrix gene expression data sets (GSE5787, GSE7803, GSE9750) were retrieved, vouching for a total 9 cervical cancer cell lines, 39 normal cervical samples, 7 CIN3 samples and 111 cervical cancer samples. An Agilent data set (GSE7410; 5 normal cervical samples, 35 samples from invasive cervical cancer) was selected as a validation set. Predication analysis of microarrays was performed in the Affymetrix sets to identify cervical cancer biomarkers. We compared the lists of differentially expressed genes between normal and CIN3 samples on the one hand (n=1923) and between CIN3 and invasive cancer samples on the other hand (n=628).

Results

Seven probe sets were identified that were significantly overexpressed (at least 2 fold increase expression level, and false discovery rate <5%) in both CIN3 samples respective to normal samples and in cancer samples respective to CIN3 samples. From these, five probes sets could be validated in the Agilent data set (P<0.001) comparing the normal with the invasive cancer samples, corresponding to the genes DTL, HMGB3, KIF2C, NEK2 and RFC4. These genes were additionally overexpressed in cervical cancer cell lines respective to the cancer samples. The literature on these markers was reviewed.

Conclusion

Novel biomarkers in combination with primary human papilloma virus (HPV) testing may allow complete cervical screening by objective, non-morphological molecular methods, which may be particularly important in developing countries.

Bioinformatics analysis of aberrantly methylated-differentially expressed genes and pathways in hepatocellular carcinoma

AIM

To discover methylated-differentially expressed genes (MDEGs) in hepatocellular carcinoma (HCC) and to explore relevant hub genes and potential pathways.

METHODS

The data of expression profiling GSE25097 and methylation profiling GSE57956 were gained from GEO Datasets. We analyzed the differentially methylated genes and differentially expressed genes online using GEO2R. Functional and enrichment analyses of MDEGs were conducted using the DAVID database. A protein-protein interaction (PPI) network was performed by STRING and then visualized in Cytoscape. Hub genes were ranked by cytoHubba, and a module analysis of the PPI network was conducted by MCODE in Cytoscape software.

RESULTS

In total, we categorized 266 genes as hypermethylated, lowly expressed genes (Hyper-LGs) referring to endogenous and hormone stimulus, cell surface receptor linked signal transduction and behavior. In addition, 161 genes were labelled as hypomethylated, highly expressed genes (Hypo-HGs) referring to DNA replication and metabolic process, cell cycle and division. Pathway analysis illustrated that Hyper-LGs were enriched in cancer, Wnt, and chemokine signalling pathways, while Hypo-HGs were related to cell cycle and steroid hormone biosynthesis pathways. Based on PPI networks, PTGS2, PIK3CD, CXCL1, ESR1, and MMP2 were identified as hub genes for Hyper-LGs, and CDC45, DTL, AURKB, CDKN3, MCM2, and MCM10 were hub genes for Hypo-HGs by combining six ranked methods of cytoHubba.

CONCLUSION

In the study, we disclose numerous novel genetic and epigenetic regulations and offer a vital molecular groundwork to understand the pathogenesis of HCC. Hub genes, including PTGS2, PIK3CD, CXCL1, ESR1, MMP2, CDC45, DTL, AURKB, CDKN3, MCM2, and MCM10, can be used as biomarkers based on aberrant methylation for the accurate diagnosis and treatment of HCC.

Integrative Analysis of Dysregulated lncRNA-Associated ceRNA Network Reveals Functional lncRNAs in Gastric Cancer

Mounting evidence suggests that long noncoding RNAs (lncRNAs) play important roles in the regulation of gene expression by acting as competing endogenous RNA (ceRNA). However, the regulatory mechanisms of lncRNA as ceRNA in gastric cancer (GC) are not fully understood. Here, we first constructed a dysregulated lncRNA-associated ceRNA network by integrating analysis of gene expression profiles of lncRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs). Then, we determined three lncRNAs (RP5-1120P11, DLEU2, and DDX11-AS1) as hub lncRNAs, in which associated ceRNA subnetworks were involved in cell cycle-related processes and cancer-related pathways. Furthermore, we confirmed that the two lncRNAs (DLEU2 and DDX11-AS1) were significantly upregulated in GC tissues, promote GC cell proliferation, and negatively regulate miRNA expression, respectively. The hub lncRNAs (DLEU2 and DDX11-AS1) could have oncogenic functions, and act as potential ceRNAs to sponge miRNA. Our findings not only provide novel insights on ceRNA regulation in GC, but can also provide opportunities for the functional characterization of lncRNAs in future studies.

The Neddylation Inhibitor Pevonedistat (MLN4924) Suppresses and Radiosensitizes Head and Neck Squamous Carcinoma Cells and Tumors

The cullin RING E3 ubiquitin ligase 4 (CRL4) with its substrate receptor CDT2 (CRL4-CDT2) is emerging as a critical regulator of DNA replication through targeting CDT1, SET8, and p21 for ubiquitin-dependent proteolysis. The aberrant increased stability of these proteins in cells with inactivated CRL4-CDT2 results in DNA rereplication, which is deleterious to cells due to the accumulation of replication intermediates and stalled replication forks. Here, we demonstrate that CDT2 is overexpressed in head and neck squamous cell carcinoma (HNSCC), and its depletion by siRNA inhibits the proliferation of human papilloma virus-negative (HPV-ve) HNSCC cells primarily through the induction of rereplication. Treatment of HNSCC with the NEDD8-activating enzyme inhibitor pevonedistat (MLN4924), which inhibits all cullin-based ligases, induces significant rereplication and inhibits HNSCC cell proliferation in culture and HNSCC xenografts in mice. Pevonedistat additionally sensitizes HNSCC cells to ionizing radiation (IR) and enhances IR-induced suppression of xenografts in mice. Induction of rereplication via CDT2 depletion, or via the stabilization or activation of CDT1, also radiosensitizes HNSCC cells. Collectively, these results demonstrate that induction of rereplication represents a novel approach to treating radioresistant HNSCC tumors and suggest that pevonedistat may be considered as an adjuvant for IR-based treatments. Mol Cancer Ther; 17(2); 368-80. ©2017 AACRSee all articles in this MCT Focus section, "Developmental Therapeutics in Radiation Oncology."

Overexpression of CTEN relates to tumor malignant potential and poor outcomes of adenocarcinoma of the esophagogastric junction

Background

To detect a novel treatment target for adenocarcinoma of the esophagogastric junction (AEG), we tested whether C-terminal tensin-like (CTEN), a member of the tensin gene family and frequently overexpressed in various cancers, acts as a cancer-promoting gene through overexpression in AEG.

Materials and Methods

We analyzed 5 gastric adenocarcinoma (GC) cell lines and 104 primary AEG tumors curatively resected in our hospital between 2000 and 2010.

Results

CTEN overexpression was detected in GC cell lines (2/5 cell lines; 40%) and primary AEG tumor samples (35/104 cases; 34%). CTEN knockdown using several specific siRNAs inhibited the proliferation, migration, and invasion of CTEN-overexpressing cells. CTEN overexpression was significantly correlated with more aggressive venous and lymphatic invasion, deeper tumor depth, and higher rates of lymph node metastasis and recurrence. Patients with CTEN-overexpressing tumors had a worse overall rate of survival than those with non-expressing tumors (P < 0.0001, log-rank test) in an expression-dependent manner. CTEN positivity was independently associated with a worse outcome in the multivariate analysis (P = 0.0423, hazard ratio 3.54 [1.04-16.4]).

Conclusions

CTEN plays a crucial role in tumor cell proliferation, migration, and invasion through its overexpression, which highlights its usefulness as a prognosticator and potential therapeutic target in AEG.

Evidence for genetic association between chromosome 1q loci and predisposition to colorectal neoplasia

BACKGROUND

A substantial fraction of familial colorectal cancer (CRC) and polyposis heritability remains unexplained. This study aimed to identify predisposing loci in patients with these disorders.

METHODS

Homozygosity mapping was performed using 222 563 SNPs in 302 index patients with various colorectal neoplasms and 3367 controls. Linkage analysis, exome and whole-genome sequencing were performed in a family affected by microsatellite stable CRCs. Candidate variants were genotyped in 10 554 cases and 21 480 controls. Gene expression was assessed at the mRNA and protein level.

RESULTS

Homozygosity mapping revealed a disease-associated region at 1q32.3 which was part of the linkage region 1q32.2-42.2 identified in the CRC family. This includes a region previously associated with risk of CRC. Sequencing identified the p.Asp1432Glu variant in the MIA3 gene (known as TANGO1 or TANGO) and 472 additional rare, shared variants within the linkage region. In both cases and controls the population frequency was 0.02% for this MIA3 variant. The MIA3 mutant allele showed predominant mRNA expression in normal, cancer and precancerous tissues. Furthermore, immunohistochemistry revealed increased expression of MIA3 in adenomatous tissues.

CONCLUSIONS

Taken together, our two independent strategies associate genetic variations in chromosome 1q loci and predisposition to familial CRC and polyps, which warrants further investigation.

Overexpression of TRIM44 is related to invasive potential and malignant outcomes in esophageal squamous cell carcinoma

Recent studies have shown that some members of the tripartite motif-containing protein family function as important regulators for carcinogenesis. In this study, we investigated whether tripartite motif-containing protein 44 acts as a cancer-promoting gene through its overexpression in esophageal squamous cell carcinoma. We analyzed esophageal squamous cell carcinoma cell lines to evaluate malignant potential and also analyzed 68 primary tumors to evaluate clinical relevance of tripartite motif-containing protein 44 protein in esophageal squamous cell carcinoma patients. Expression of the tripartite motif-containing protein 44 protein was detected in esophageal squamous cell carcinoma cell lines (8/14 cell lines; 57%) and primary tumor samples of esophageal squamous cell carcinoma (39/68 cases; 57%). Knockdown of tripartite motif-containing protein 44 expression in esophageal squamous cell carcinoma cells using several specific small interfering RNAs inhibited cell migration and invasion, but not cell proliferation. Immunohistochemical analysis demonstrated that the overexpression of the tripartite motif-containing protein 44 protein in the tumor infiltrated region was associated with the status of lymph node metastasis ( p = 0.049), and the overall survival rates were significantly worse among patients with tripartite motif-containing protein 44-overexpressing tumors than those with non-expressing tumors ( p = 0.029). Moreover, multivariate Cox regression model identified that overexpression of the tripartite motif-containing protein 44 protein was an independent worse prognostic factor (hazard ratio = 2.815; p = 0.041), as well as lymphatic invasion (hazard ratio = 2.735; p = 0.037). These results suggest that tripartite motif-containing protein 44 protein could play a crucial role in tumor invasion through its overexpression and highlight its usefulness as a predictor and potential therapeutic target in esophageal squamous cell carcinoma.

Overexpression of YWHAZ as an independent prognostic factor in adenocarcinoma of the esophago-gastric junction

Several studies have demonstrated that YWHAZ (14-3-3ζ), included in the 14-3-3 family of proteins, is implicated in the initiation and progression of cancers. To detect a novel treatment target for adenocarcinoma of the esophagogastric junction (AEG), we tested whether YWHAZ acted as a cancer-promoting gene through its overexpression in AEG. We analyzed YWHAZ protein expression in 92 consecutive primary AEG tumors, which had been curatively resected in our institution between 2000 and 2010. Overexpression of the YWHAZ protein was frequently detected in primary AEG tumor samples (46% (42/92)). Overexpression of YWHAZ was significantly correlated with Siewert type III tumor, larger tumor size (≥40 mm) and higher rates of lymph node metastasis and recurrence. Patients with YWHAZ-overexpressing tumors had a worse overall rate of survival than those with non-expressing tumors (P = 0.011, log-rank test) in an intensity expression-dependent manner. Patients with YWHAZ-overexpression tumors had worse overall survival rates than those with lower-expression tumors. YWHAZ positivity was independently associated with a worse outcome in the multivariate analysis (P = 0.0015, hazard ratio 4.49 [1.736-13.06]). In conclusion, YWHAZ plays a crucial role in poor outcomes of patients with AEG through its overexpression, which highlights its usefulness as a prognosticator and potential therapeutic target and indicator in AEG.