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

The role of Cyclin Dependent Kinase Inhibitor 3 (CDKN3) in promoting human tumors: Literature review and pan-cancer analysis

Background

Although many experiments and clinical studies have proved the link between the expression of CDKN3 and human tumors, we have not been able to identify any bioinformatics study in which the extensive tumor-promoting effect of CDKN3 was systematically analyzed.

Objective

Explore the extensive tumor-promoting effects of CDKN3 and review the research progress of CDKN3 in cancer.

Methods

We systematically reviewed the literature on CDKN3 and tumors. We explored the potential tumor-promoting effects of CDKN3 on different tumors in the TCGA database and the GTEx database using multiple platforms and websites. We studied the expression level of CDKN3, survival, prognosis, diagnosis, genetic variation, immune infiltration, and enrichment analysis using databases such as TIMER 2.0, GEPIA2, cBioPortal, and STRING.

Results

We found that CDKN3 is highly expressed in most tumors. The expression of CDKN3 is closely related to the prognosis of some tumors. And CDKN3 may have diagnostic value. The conclusion of our literature review is roughly the same, but there are differences, which are worthy of further study. Moreover, CDKN3 may be related to immune cell infiltration in tumor tissues. The genetic alteration of LUAD, STAD, SARC, PCPG, and ESCA with "Amplification" as the main type. In addition, through enrichment analysis, we found that CDKN3 affects tumors mainly through the control of the cell cycle and mitosis.

Conclusion

CDKN3 is highly expressed in most tumor tissues and has a statistical correlation with survival prognosis. It has extensive tumor-promoting effects that may be related to mechanisms such as immune infiltration.

Comprehensive Analysis Reveals the Potential Roles of CDKN3 in Pancancer and Verification in Endometrial Cancer

Background

Cyclin-dependent kinase inhibitor 3 (CDKN3) has been studied in many cancers. However, the comprehensive and systematic pancancer analysis of CDKN3 genes is still lacking.

Methods

Data were downloaded from online databases. R was used for analysis of the differential expression and gene alteration of CDKN3 and of the associations between CDKN3 expression and survival, signaling pathways, and drug sensitivity. Clinical samples and in vitro experiments were selected for verification.

Results

CDKN3 expression was higher in most types of cancers, and this phenotype was significantly correlated with poor survival. CDKN3 showed gene alterations and copy number alterations in many cancers and associated with some immune-related pathways and factors. Drug sensitivity analysis elucidated that CDKN3 could be a useful marker for therapy selection. Clinical samples elucidated CDKN3 expressed high in endometrial cancer tissue. In vitro studies showed that CDKN3 induced pro-tumor effect in immune environment and facilitated endometrial cancer cell proliferation and G1/S phase transition.

Conclusion

CDKN3 has been shown to be highly expressed in most types of cancers and promoted cancer cell progression. CDKN3 may serve as a novel marker in clinical diagnosis, treatment, and prognosis prediction in future.

Identification of biomarkers of renal ischemia-reperfusion injury by bioinformatics analysis and single-cell sequencing analysis combined with in vivo validation

BACKGROUND

Renal ischemia-reperfusion injury (IRI) is a serious clinical complication of kidney injury. This research dealt with investigating the hub genes and pathways associated with renal IRI.

METHODS

The transcriptome expression dataset of mouse renal ischemia samples (GSE39548) was obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were filtered by R software for key genes utilized for gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and gene enrichment analysis (GSEA). The gene co-expression network was developed by WGCNA analysis to screen important modules. Hub genes from the intersection of DEGs and WGCNA were subjected to protein-protein interaction (PPI) network. The biomarkers obtained by SVM-REF and LASSO algorithm were validated by other datasets and subjected to GSEA analysis. The expression of biomarkers in renal IRI was detected by qRT-PCR and subjected to single-cell analysis.

RESULTS

A total of 157 DEGs were discovered. Biological function analysis depicted that the DEGs were primarily involved in cytokine-cytokine receptor interaction, as well as the signaling pathways IL-17, MAPK, and TNF. The intersection of DEGs and the genes obtained by WGCNA analysis yielded 149 hubs genes. Based on SVM-REF and LASSO algorithm, cyp1a1 and pdk4 were determined as potential biomarkers in individuals with renal ischemia and showed good diagnostic value. qRT-PCR results depicted that cyp1a1 and pdk4 were significantly up-regulated in renal ischemia mice (P < 0.05). Finally, the single-cell analysis identified the expression of Cyp1a1 and Pdk4 in mice kidney tissue.

CONCLUSION

cyp1a1 and pdk4 were identified to play important roles in renal IRI. This research provides a new perspective and basis for studying the pathogenesis of renal IRI and developing new treatments.

MiR-96-5p Suppresses Progression of Arsenite-Induced Human Keratinocyte Proliferation and Malignant Transformation by Targeting Denticleless E3 Ubiquitin Protein Ligase Homolog

Long-term exposure to arsenic has been linked to a variety of cancers, among which skin cancer is the most prevalent form. However, the mechanism underlying arsenic carcinogenesis is unclear, and there is still limited information on the role of miRNAs in arsenic-induced skin cancer. This study aims to explore the role of miR-96-5p in the arsenite-induced proliferation and malignant transformation of human HaCaT keratinocytes. The GEO database (accession numbers GSE97303, GSE97305, and GSE97306) was used to extract mRNA and miRNA expression profiles of HaCaT cells treated with or without 0.1 μmol/L sodium arsenite for 3 and 7 weeks. In this paper, according to the CCK8 assay result, HaCaT cells exposed to 0.1 μmol/L sodium arsenite for 48 h were finalized. CCK8, MTT, EdU incorporation, and colony formation assays were used to determine the viability and proliferation of HaCaT cells and transformed HaCaT (T-HaCaT) cells. The subcellular localization and relative expression levels of DTL, as well as miR-96-5p in HaCaT cells induced by arsenite, were determined via immunofluorescence, RT-qPCR, and Western blot. Dual-luciferase reporter assay was performed to identify miR-96-5p bound directly to DTL. Transfection of miR-96-5p mimics or DTL siRNA was conducted to verify the arsenite-induced viability of HaCaT cells and T-HaCaT cells. T-HaCaT cells and nude mice were used to construct arsenite-induced malignant transformation and an in vivo xenograft model to demonstrate the over-expressed effect of miR-96-5p. The results showed that DTL was the target gene of miR-96-5p. Meanwhile, we also found that 0.1 μmol/L sodium arsenite upregulated DTL by decreasing the miR-96-5p level, leading to the proliferation and malignant transformation of HaCaT cells. MiR-96-5p agomir treatment slowed the growth of transplanted HaCaT cells transformed by arsenite in a manner associated with DTL downregulation in the nude mice xenograft model. Taken together, we confirmed that miR-96-5p, as a potent regulator of DTL, suppressed arsenite-induced HaCaT cell proliferation and malignant transformation, which might provide a novel therapeutic target for the treatment of arsenic-induced skin cancer.

Analysis and experimental validation of the innate immune gene PSMD1 in liver hepatocellular carcinoma and pan-cancer

This work intends to examine the diagnostic, prognostic, and biological roles of PSMD1 (proteasome 26S subunit, non-ATPase 1) in liver hepatocellular carcinoma (LIHC) and other malignancies, using bioinformatics techniques. PSMD1 is an innate immune gene that has been identified as a biomarker for several cancers. By analyzing TCGA data, we determined that PSMD1 has excellent diagnostic and prognostic value in LIHC. We also examined its correlation with stage-matching clinical features, particularly T staging and stage staging. Independent prognostic analysis, nomogram, and Decision Curve Analysis (DCA) analysis confirmed the predictive ability of PSMD1 on patient clinical outcomes. Our focus was on exploring the biological process, immune infiltration, and genetic variation in which PSMD1 is involved in LIHC. We found a close relationship between PSMD1 and the tumor microenvironment (TME), as well as various immune cell infiltration, immune function, and immune checkpoints. Furthermore, our results suggested that liver cancer patients with low PSMD1 expression were more actively responsive to immunotherapy according to TIDE predictions. Additionally, we observed significant differences in patient survival based on the different immune molecular types of tumors and their correlation with PSMD1 expression. The close relationship between PSMD1 and copy number variation (CNV), tumor mutational burden (TMB), and methylation was also confirmed, showing a significant impact on patient survival. Moreover, the pan-cancer analysis revealed that PSMD1 is closely related to the diagnosis and prognosis of various cancers, as well as immune infiltration across different cancer types. In summary, PSMD1 has the potential to be a useful diagnostic and prognostic biomarker for LIHC and other types of cancers. It is closely associated with indicators such as immune infiltration, CNV, TMB, and methylation. The identification of PSMD1 may offer a potential intervention target for LIHC and various cancers.

Reconstruction of the regulatory hypermethylation network controlling hepatocellular carcinoma development during hepatitis C viral infection

Hepatocellular carcinoma (HCC) has been associated with hepatitis C viral (HCV) infection as a potential risk factor. Nonetheless, the precise genetic regulatory mechanisms triggered by the virus, leading to virus-induced hepatocarcinogenesis, remain unclear. We hypothesized that HCV proteins might modulate the activity of aberrantly methylated HCC genes through regulatory pathways. Virus-host regulatory pathways, interactions between proteins, gene expression, transport, and stability regulation, were reconstructed using the ANDSystem. Gene expression regulation was statistically significant. Gene network analysis identified four out of 70 HCC marker genes whose expression regulation by viral proteins may be associated with HCC: DNA-binding protein inhibitor ID - 1 (ID1), flap endonuclease 1 (FEN1), cyclin-dependent kinase inhibitor 2A (CDKN2A), and telomerase reverse transcriptase (TERT). It suggested the following viral protein effects in HCV/human protein heterocomplexes: HCV NS3(p70) protein activates human STAT3 and NOTC1; NS2-3(p23), NS5B(p68), NS1(E2), and core(p21) activate SETD2; NS5A inhibits SMYD3; and NS3 inhibits CCN2. Interestingly, NS3 and E1(gp32) activate c-Jun when it positively regulates CDKN2A and inhibit it when it represses TERT. The discovered regulatory mechanisms might be key areas of focus for creating medications and preventative therapies to decrease the likelihood of HCC development during HCV infection.

Bioinformatics and pathway enrichment analysis identified hub genes and potential biomarker for gastric cancer prognosis

Introduction

Gastric cancer is one of the most common cancers in the world. This study aimed to identify genes, biomarkers, and metabolic pathways affecting gastric cancer using bioinformatic analysis and meta-analysis.

Methods

Datasets containing gene expression profiles of tumor lesions and adjacent non-tumor mucosa samples were downloaded. Common differentially expressed genes between data sets were selected to identify hub genes and further analysis. Gene Expression Profiling and Interactive Analyses (GEPIA) and the Kaplan-Meier method were used to further validate the expression level of genes and plot the overall survivalcurve, respectively.

Results and disscussion

KEGG pathway analysis showed that the most important pathway was enriched in ECM-receptor interaction. Hub genes includingCOL1A2, FN1, BGN, THBS2, COL5A2, COL6A3, SPARC and COL12A1 wereidentified. The top interactive miRNAs including miR-29a-3p, miR-101-3p,miR-183-5p, and miR-15a-5p targeted the most hub genes. The survival chart showed an increase in mortality in patients with gastric cancer, which shows the importance of the role of these genes in the development of the disease and can be considered candidate genes in the prevention and early diagnosis of gastric cancer.

Identification of the miR-423-3p/VLDLR Regulatory Network for Glioma Using Transcriptome Analysis

As the most prevalent primary CNS tumor, glioma is characterized by high mortality and morbidity. This research aims to investigate glioma-associated microRNAs (miRNAs) and their target mRNAs, as well as to explore their biological functions in gliomas. The Gene Expression Omnibus (GEO) database was applied to acquire the GSE112264 miRNA microarray dataset and the GSE15824 mRNA dataset. We selected samples from the GSE112264 dataset and the GSE15824 to identify differently expressed miRNAs (DE-miRNAs) as well as differentially expressed mRNAs (DEGs), respectively. Next, the intersections of mRNA and target mRNAs of miRNA were selected, and we constructed miRNA-mRNA regulation networks. These DEGs were selected for Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses by conducting the package clusterProfiler. After conducting Cytoscape software, a protein-protein interaction (PPI) network was created. Next, survival analysis of the miR-423-3p was confirmed by conducting TCGA database. Subsequently, Quantitative real-time PCR (qRT-PCR) was conducted to verify miR-423-3p's expression. Finally, miR-423-3p's biological functions of in effecting the cell proliferative, migratory, and invasive capabilities of glioma were investigated by performing Cell Counting Kit-8 (CCK-8) and Transwell assays. Our analysis elucidated a novel miRNA-mRNA regulatory network related to glioma carcinogenesis, which may be considered as future therapeutic biomarkers for glioma.

Influence of verapamil on pressure overload-induced ventricular arrhythmias by regulating gene-expression profiles

BACKGROUND

Life-threatening ventricular arrhythmias can lead to sudden cardiac death in patients. This study aimed to investigate the changes in gene profiles involved when verapamil (VRP) affects increased wall stress (pressure overload)-induced ventricular arrhythmias, thus revealing the potential causative molecular mechanisms and therapeutic targets through gene-expression identification and functional analysis.

METHODS

Animal models with wall stress-induced ventricular arrhythmias were established. Low (0.5 mg/kg) and high (1 mg/kg) doses of VRP were administered intravenously 10 minutes before transverse aortic constriction, and average ventricular arrhythmia scores were calculated. Next, we evaluated the molecular role of VRP by characterising differential gene-expression profiles between VRP-pretreated (1 mg/kg) and control groups using RNA-sequencing technology. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to reveal molecular function. A protein-protein interaction (PPI) network was then developed.

RESULTS

VRP exerted its anti-arrhythmic effects in response to increases in left ventricular (LV) afterload. We detected differentially expressed genes (DEGs), of which 36 were upregulated and 1 397 downregulated, between the VRP-pretreated and model groups during acute increases in LV wall stress. GO analysis demonstrated that the DEGs were associated with cytoskeletal protein binding. KEGG analysis showed that enriched pathways were mainly distributed in adherens junctions, actin cytoskeleton regulation and the MAPK signalling pathway. Centralities analysis of the PPI identified Rac1, Grb2, Rbm8a and Mapk1 as hub genes.

CONCLUSIONS

VRP prevented acute pressure overload-induced ventricular arrhythmias, possibly through the hub genes Rac1, Grb2, Rbm8a and Mapk1 as potential targets of VRP.

MCM2 in human cancer: functions, mechanisms, and clinical significance

Background

Aberrant DNA replication is the main source of genomic instability that leads to tumorigenesis and progression. MCM2, a core subunit of eukaryotic helicase, plays a vital role in DNA replication. The dysfunction of MCM2 results in the occurrence and progression of multiple cancers through impairing DNA replication and cell proliferation.

Conclusions

MCM2 is a vital regulator in DNA replication. The overexpression of MCM2 was detected in multiple types of cancers, and the dysfunction of MCM2 was correlated with the progression and poor prognoses of malignant tumors. According to the altered expression of MCM2 and its correlation with clinicopathological features of cancer patients, MCM2 was thought to be a sensitive biomarker for cancer diagnosis, prognosis, and chemotherapy response. The anti-tumor effect induced by MCM2 inhibition implies the potential of MCM2 to be a novel therapeutic target for cancer treatment. Since DNA replication stress, which may stimulate anti-tumor immunity, frequently occurs in MCM2 deficient cells, it also proposes the possibility that MCM2 targeting improves the effect of tumor immunotherapy.

Systematic pan‑cancer analysis identifies CDC45 as having an oncogenic role in human cancers

Cell division cycle 45 (CDC45) is an essential protein required for the initiation of DNA replication. In the present study, the role of CDC45 across 33 cancers was systematically investigated. It was observed that the expression of CDC45 was significantly upregulated in most cancers, exhibiting a marked negative correlation with the overall survival. Next, there was no significant difference in prognosis between the genomically altered and unaltered groups with respect to clinical outcomes. A decreased level of CDC45 at the DNA promoter region was also identified in several cancers. Furthermore, CDC45 expression was associated with the levels of tumor-infiltrating immune cells in some specific cancer types. In addition, CDC45 was associated with m⁶A methylation, and CDC45 expression was primarily positively correlated with ‘writers’ and ‘readers’ in various cancers, particularly HNRNPC, RBM15 and YTHDC1. Gene enrichment analysis was also performed. In addition, the AUC of each cancer with respect to its 1-, 3-, and 5-year survival rates were explored. Finally, CCK-8 assays, EdU assays and cell cycle analysis were conducted. In conclusion, the present study demonstrated that CDC45 may be a potential biomarker and target for cancer treatment.

Aberrantly methylated-differentially expressed genes and related pathways in cholangiocarcinoma

This study aimed to explore aberrantly methylated-differentially expressed genes and related pathways in cholangiocarcinoma (CCA).The mRNA expression data (GSE26566) and methylation profiling data (GSE44965) were collected from the Gene Expression Omnibus (GEO) Datasets. Differentially expressed genes and differentially methylated genes were identified using GEO2R. Gene ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using clusterprofiler in R. MCODE clustering tool was used to screen modules of the protein-protein interaction network in Cytoscape. Related pathways of hub gene by using gene set enrichment analysis.Eighty-one hypermethylated, lowly expressed genes (Hyper-LGs) and 76 hypomethylated, highly expressed genes (Hypo-HGs) were identified in this study. Hyper-LGs were enriched in ion channel binding and transcription factor activity, which was associated with Mineral absorption and Cell adhesion molecules. Hypo-HGs were enriched in cysteine-type endopeptidase activity, which was associated with Sphingolipid signaling pathway and T cell receptor signaling pathway. Based on protein-protein interaction networks, MYC and VWF were identified as hub genes for Hyper-LGs, and no hub genes for Hypo-HGs.This study found methylated-differentially expressed genes and signaling pathways that are connected with the CCA by using a series of bioinformatics databases and tools. MYC and VWF act as hub genes of CCA, which can be used as biomarkers based on aberrant methylation for the accurate diagnosis and treatment of CCA.

Scutellarin protects the kidney from ischemia/reperfusion injury by targeting Nrf2

BACKGROUND

Acute kidney injury (AKI) results in high morbidity and mortality among inpatients, while effective treatment and intervention are still absent. Therefore, this study aims to explore the effects of Scutellarin (Scu) in experimental models in vivo and in vitro.

METHODS

In vivo experiment, we employed a total of 30 Wistar rats, which further were modelled by a bilateral renal pedicle clip for 45 min, then received 50 mg/kg/day Scu. In vitro, HK-2 cells were administered with 20μΜ Scu and then incubated in hypoxia/reoxygenation (H/R) conditions for 24 h. The knockdown of Nrf2 expression was conducted by small interfering RNA (siRNA) transfection.

RESULTS

As a result, the AKI model was well established with an increased SCr, BUN, KIM-1 level, and histological injury score, while Scu treatment reduced the levels above and increased the antioxidative enzyme HO-1. H/R induced an increase of ROS in HK-2 cells, while Scu decreased the ROS level. Bioinformatics results showed the transcription factor Nrf2 was a hub protein during the AKI, which also bound to Scu with low binding energy, indicating that the downstream effect of Scu might be mediated by Nrf2. To verify the suppose above, we employed siRNA against Nrf2, which shows a significant increase in ROS after Nrf2 was blocked. Meanwhile, the HO-1 showed similar expression compared with the 'H/R + Nrf2 siRNA' and 'H/R + Nrf2 siRNA + Scu' group, implying the protective effect of Scu was mediated by the Nrf2/HO-1 pathway.

CONCLUSION

Scu led to up-regulation of HO-1 through activating the Nrf2 signalling pathway, protecting the kidneys from ischemia/reperfusion (I/R)-induced oxidative damage.

CENPF as an independent prognostic and metastasis biomarker corresponding to CD4+ memory T cells in cutaneous melanoma

Owing to recent advances in immunotherapies, the overall survival of patients with skin cutaneous melanoma (SKCM) has increased; however, the 5-year survival rate of metastatic patients remains poor. Skin cutaneous melanoma-upregulated genes were screened via analysis of differentially expressed genes (GSE3189 and GSE46517), and metastasis-related oncogenes were identified via weighted gene coexpression network analysis of the GSE46517 dataset. As confirmed by the Tumor Immune Estimation Resource, we found highly expressed centromere protein F (CENPF) in SKCM and its metastases. Immunostaining of human melanoma tissues demonstrated high CENPF expression. According to the Kaplan-Meier survival curve log-rank test, receiver-operating characteristic curve, and univariate and multivariate analyses, the Cancer Genome Atlas (TCGA) database suggested CENPF be a typical independent predictor of SKCM. The CIBERSORT algorithm classified the types of the immune cells from GSE46517 and showed higher proportion of CD4+ memory-activated T cells in metastatic melanoma. Single-sample gene set enrichment analysis of TCGA data confirmed the correlation between CENPF and activated CD4+ T cells. Centromere protein F was positively correlated with tumor mutational burden and CD4+ memory T cell markers (interleukin [IL]-23A, CD28, and CD62L), negatively associated with memory T cell maintenance factors (IL-7 and IL-15) by correlation analysis. Moreover, immunofluorescence showed high coexpression of CENPF and IL23A, CD4 in melanoma. Upregulated CENPF might lead to premature depletion of CD4+ memory T cells and immunosuppression. Nomogram indicated CENPF clinical predictive value for 1-, 3-, 5-, and 7-year melanoma overall survival. Therefore, CENPF plays a vital role in the progression and metastasis of melanoma and can be an effective therapeutic target.

Development of a Model System to Study Expression Profile of RAC2 Gene in Breast Cancer MDA-MB-231 Cell Line

The RAC2 gene encoding GTPases involve cellular signaling of actin polymerization, cell migration, and formation of the phagocytic NADPH oxidase complex. Oncogenic mutations in the RAC2 gene have been identified in various cancers, and extensive research is in progress to delineate its signaling pathways and identify potential therapeutic targets in breast cancers. This paper explored developing a bioinformatics model system to understand the RAC2 gene expression pattern concerning estrogenic receptor status in breast cancers. We have used the MDA-MB-231 breast cancer cell line to identify RAC2 gene expression. To simplify the development of model system with one dataset, we retrieved the microarray dataset GSE27515 from the Gene Expression Omnibus (GEO) for the differential gene expression analysis. Then, network analysis, pathway enrichment analysis, volcano plot, ORA, and the up/downregulated genes were used to highlight genes involved in signaling network pathways. We observed that the RAC2 gene is upregulated in the GSM679722, GSM676923, and GSM679724 downregulated in the samples GSM676925, GSM676926, and GSM676927 from the GEO dataset. Our observation found that the RAC2 gene is upregulated in the estrogen receptor (ER) negative breast cancers and downregulated in ER-positive breast cancer, involving pathways such as focal adhesion, MAPK signaling, axon guidance, and VEGF signaling pathway.

Bioinformatics Analysis of Autophagy and Mitophagy Markers Associated with Delayed Cerebral Ischemia Following Subarachnoid Hemorrhage

Objective

To evaluate the interactions among differentially expressed autophagy and mitophagy markers in subarachnoid hemorrhage (SAH) patients with delayed cerebral ischemia (DCI).

Methods

The expression data of autophagy and mitophagy-related makers in the cerebrospinal fluid (CSF) cells was analyzed by real-time reverse transcription-polymerase chain reaction and Western blotting. The markers included death-associated protein kinase (DAPK)-1, BCL2 interacting protein 3 like (BNIP3L), Bcl-1 antagonist X, PINK, Unc-51 like autophagy activating kinase 1, nuclear dot protein 52, and p62. In silico functional analyses including gene ontology enrichment and the protein-protein interaction network were performed.

Results

A total of 56 SAH patients were included and 22 (38.6%) of them experienced DCI. The DCI patients had significantly increased mRNA levels of DAPK1, BNIP3L, and PINK1, and increased expression of BECN1 compared to the non-DCI patients. The most enriched biological process was the positive regulation of autophagy, followed by the response to mitochondrial depolarization. The molecular functions ubiquitin-like protein ligase binding and ubiquitin-protein ligase binding were enriched. In the cluster of cellular components, Lewy bodies and the phagophore assembly site were enriched. BECN1 was the most connected gene among the differentially expressed markers related to autophagy and mitophagy in the development of DCI.

Conclusion

Our study may provide novel insight into mitochondrial dysfunction in DCI pathogenesis.

Identification and Validation of Hub Genes Predicting Prognosis of Hepatocellular Carcinoma

INTRODUCTION

The aim of this study is selecting the hub genes associated with hepatocellular carcinoma (HCC) to construct a Cox regression model for predicting prognosis in HCC patients.

METHODS

Using HCC patient data from the ICGC and TCGA databases, screened for 40 core genes highly correlated with histological grade of HCC. Univariate and multivariate Cox regression analyses were performed on the genes highly associated with HCC prognosis, and the model was established. The expression of those genes was measured by immunohistochemistry in 110 HCC patients who underwent the surgery in the First Affiliated Hospital of Wenzhou Medical University. The survival of HCC patients was analyzed by the Kaplan-Meier method.

RESULTS

Eight genes (CDC45, CENPA, MCM10, MELK, CDC20, ASF1B, FANCD2, and NCAPH) were correlated with prognosis, and the same result was observed in 110 HCC patients. Using the regression model, the HCC patients in the training set were classified as high- and low-risk groups. The overall survival of patients in the high-risk group was shorter than that in the low-risk group, and the same results were obtained in the verification set.

CONCLUSION

This study found that the risk model according to these 8 genes can be used as a predictor of prognosis in HCC. These genes may become alternative biomarkers and therapeutic targets and provide new therapeutic strategies for HCC.

Label-free quantitative proteomic and phosphoproteomic analyses of renal biopsy tissues in membranous nephropathy

PURPOSE

Membranous nephropathy (MN) is a common cause of nephrotic syndrome in adults. However, the underlying mechanisms of its occurrence and development are not completely clear. Thus, it is essential to explore the mechanisms.

EXPERIMENTAL DESIGN

Here, we employed label-free quantification and liquid chromatography-tandem mass spectrometry analysis techniques to investigate the proteomic and phosphoproteomic alterations in renal biopsy tissues of MN patients. Samples were collected from 16 MN patients and 10 controls. Immunohistochemistry (IHC) was performed to validate the hub phosphoprotein.

RESULTS

We focused on the changes in the phosphoproteome in MN group versus control group (CG). Totally, 1704 phosphoproteins containing 3241 phosphosites were identified and quantified. The phosphorylation levels of 216 phosphoproteins containing 297 phosphosites were differentially regulated in stage II MN group versus CG, and 333 phosphoproteins containing 461 phosphosites were differentially phosphorylated in stage III MN group versus CG. In each comparison, several differential phosphoproteins were factors, kinases and receptors involved in cellular processes, biological regulation and other biological processes. The subcellular location of most of the differential phosphoproteins was the nucleus. Protein-protein interaction analysis showed that the connections among the differential phosphoproteins were extremely complex, and several signalling pathways probably associated with MN were identified. The hub phosphoprotein was validated by IHC.

CONCLUSIONS AND CLINICAL RELEVANCE

This investigation can provide direct insight into the global phosphorylation events in MN group versus CG and may help to shed light on the potential pathogenic mechanisms of MN.

Identification of Differentially-Methylated Genes and Pathways in Patients with Delayed Cerebral Ischemia Following Subarachnoid Hemorrhage

Objective

We reported the differentially methylated genes in patients with subarachnoid hemorrhage (SAH) using bioinformatics analyses to explore the biological characteristics of the development of delayed cerebral ischemia (DCI).

Methods

DNA methylation profiles obtained from 40 SAH patients from an epigenome-wide association study were analyzed. Functional enrichment analysis, protein-protein interaction (PPI) network, and module analyses were carried out.

Results

A total of 13 patients (32.5%) experienced DCI during the follow-up. In total, we categorized the genes into the two groups of hypermethylation (n=910) and hypomethylation (n=870). The hypermethylated genes referred to biological processes of organic cyclic compound biosynthesis, nucleobase-containing compound biosynthesis, heterocycle biosynthesis, aromatic compound biosynthesis and cellular nitrogen compound biosynthesis. The hypomethylated genes referred to biological processes of carbohydrate metabolism, the regulation of cell size, and the detection of a stimulus, and molecular functions of amylase activity, and hydrolase activity. Based on PPI network and module analysis, three hypermethylation modules were mainly associated with antigen-processing, Golgi-to-ER retrograde transport, and G alpha (i) signaling events, and two hypomethylation modules were associated with post-translational protein phosphorylation and the regulation of natural killer cell chemotaxis. VHL, KIF3A, KIFAP3, RACGAP1, and OPRM1 were identified as hub genes for hypermethylation, and ALB and IL5 as hub genes for hypomethylation.

Conclusion

This study provided novel insights into DCI pathogenesis following SAH. Differently methylated hub genes can be useful biomarkers for the accurate DCI diagnosis.

AURKB, CHEK1 and NEK2 as the Potential Target Proteins of Scutellaria barbata on Hepatocellular Carcinoma: An Integrated Bioinformatics Analysis

Objective

We aim to explore the potential anti-HCC mechanism of Scutellaria barbata through integrated bioinformatics analysis.

Methods

We searched active ingredients and related targets of Scutellaria barbata via TCMSP database, PubChem and SwissTargetPrediction database. Then, we identified HCC disease targets from GEO dataset by WGCNA. Next, the intersected targets of disease targets and drug targets were input into STRING database to construct PPI networking in order to obtain potential therapeutic targets of Scutellaria barbata. Cytoscape software was used to carry out network topology analysis of potential targets. We used the R package for GO analysis and KEGG analysis. Finally, we used AutoDock vina and PyMOL software for molecular docking.

Results

Sixteen active components from Scutellaria barbata were lastly selected for further investigation. A total of 442 component targets were identified from 16 active ingredients of Scutellaria barbata after the removal of duplicate targets. GSE45436 was selected for construction of WGCNA and screening of differentially expressed genes. A total of 354 genes were up-regulated in HCC samples and 100 were down-regulated in HCC patients. Twenty-one common genes were obtained by intersection and 10 critical targets were filtered for further investigation. The enrichment analysis showed that cell cycle, DNA replication, p53 signaling pathway were mainly involved. The molecular docking results showed that 4 potential combinations were with the best binding energy and molecular interactions.

Conclusion

AURKB, CHEK1 and NEK2 could be the potential target proteins of Scutellaria barbata in treating HCC. Cell cycle, DNA replication, p53 signaling pathway consist of the fundamental regulation cores in this mechanism.

Identification of potential core genes and pathways predicting pathogenesis in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is the most common subtype of head and neck cancer; however, its pathogenesis and potential therapeutic targets remain largely unknown. In the present study, we analyzed three gene expression profiles and screened differentially expressed genes (DEGs) between HNSCC and normal tissues. The DEGs were subjected to gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), protein–protein interaction (PPI), and survival analyses, while the connectivity map (CMap) database was used to predict candidate small molecules that may reverse the biological state of HNSCC. Finally, we measured the expression of the most relevant core gene in vitro and examined the effect of the top predicted potential drug against the proliferation of HNSCC cell lines. Among the 208 DEGs and ten hub genes identified, CDK1 and CDC45 were associated with unfavorable HNSCC prognosis, and three potential small molecule drugs for treating HNSCC were identified. Increased CDK1 expression was confirmed in HNSCC cells, and menadione, the top predicted potential drug, exerted significant inhibitory effects against HNSCC cell proliferation and markedly reversed CDK1 expression. Together, the findings of the present study suggest that the ten hub genes and pathways identified may be closely related to HNSCC pathogenesis. In particular, CDK1 and CDC45 overexpression could be reliable biomarkers for predicting unfavorable prognosis in patients with HNSCC, while the new candidate small molecules identified by CMap analysis provide new avenues for the development of potential drugs to treat HNSCC.

A Novel Epigenetic Machine Learning Model to Define Risk of Progression for Hepatocellular Carcinoma Patients

Although extensive advancements have been made in treatment against hepatocellular carcinoma (HCC), the prognosis of HCC patients remains unsatisfied. It is now clearly established that extensive epigenetic changes act as a driver in human tumors. This study exploits HCC epigenetic deregulation to define a novel prognostic model for monitoring the progression of HCC. We analyzed the genome-wide DNA methylation profile of 374 primary tumor specimens using the Illumina 450 K array data from The Cancer Genome Atlas. We initially used a novel combination of Machine Learning algorithms (Recursive Features Selection, Boruta) to capture early tumor progression features. The subsets of probes obtained were used to train and validate Random Forest models to predict a Progression Free Survival greater or less than 6 months. The model based on 34 epigenetic probes showed the best performance, scoring 0.80 accuracy and 0.51 Matthews Correlation Coefficient on testset. Then, we generated and validated a progression signature based on 4 methylation probes capable of stratifying HCC patients at high and low risk of progression. Survival analysis showed that high risk patients are characterized by a poorer progression free survival compared to low risk patients. Moreover, decision curve analysis confirmed the strength of this predictive tool over conventional clinical parameters. Functional enrichment analysis highlighted that high risk patients differentiated themselves by the upregulation of proliferative pathways. Ultimately, we propose the oncogenic MCM2 gene as a methylation-driven gene of which the representative epigenetic markers could serve both as predictive and prognostic markers. Briefly, our work provides several potential HCC progression epigenetic biomarkers as well as a new signature that may enhance patients surveillance and advances in personalized treatment.

Identification of Hub Genes as Potential Prognostic Biomarkers in Cervical Cancer Using Comprehensive Bioinformatics Analysis and Validation Studies

Background

Cervical cancer belongs to one of the most common female cancers; yet, the exact underlying mechanisms are still elusive. Recently, microarray and sequencing technologies have been widely used for screening biomarkers and molecular mechanism discovery in cancer studies. In this study, we aimed to analyse the microarray datasets using comprehensive bioinformatics tools and identified novel biomarkers associated with the prognosis of patients with cervical cancer.

Methods

The differentially expressed genes (DEGs) from Gene Expression Omnibus (GEO) datasets including GSE138080, GSE113942 and GSE63514 were analysed using GEO2R tool. The functional enrichment analysis was performed using g:Profiler tool. The protein-protein interaction (PPI) network construction and hub genes identification were performed using the STRING database and Cytoscape software, respectively. The hub genes were subjected to expression and survival analysis in the cervical cancer. The EdU incorporation and Cell Counting Kit-8 assays were performed to evaluate the effects of hub gene knockdown on the proliferation of cervical cancer cells.

Results

A total of 89 overlapping DEGs (63 up-regulated and 26 down-regulated genes) were identified in the microarray datasets. The functional enrichment analysis indicated that the overlapping DEGs were mainly associated with "DNA replication" and "cell cycle". Furthermore, the PPI network analysis revealed that the network contains 87 nodes and 309 edges. Sub-module analysis using the Molecular Complex Detection tool identified 21 hub genes from the PPI network. The expression levels of the 21 hub genes were all up-regulated in the cervical cancer tissues when compared to normal cervical tissues as analysed by GEPIA tool. The survival analysis showed that the low expression of cell division cycle 45 (CDC45), GINS complex subunit 2 (GINS2), minichromosome maintenance complex component 2 (MCM2) and proliferating cell nuclear antigen (PCNA) was significantly correlated with the shorter overall survival of patients with cervical cancer. Moreover, the protein expression levels of GINS2, MCM2 and PCNA, but not CDC45, were significantly up-regulated in the cervical cancer tissues when compared to normal cervical tissues. Finally, knockdown of MCM2 significantly suppressed the proliferation of HeLa and SiHa cells.

Conclusion

In conclusion, we screened a total of 89 overlapping DEGs from the GEO datasets, and further analysis identified four hub genes (CDC45, GINS2, MCM2 and PCNA) that were likely associated with the prognosis of patients with cervical cancer. MCM2 knockdown repressed the cervical cancer cell proliferation. The current findings may provide novel insights into understanding the pathophysiology of cervical cancer and develop therapeutic targets for patients with cervical cancer.

System-Wide Pollution of Biomedical Data: Consequence of the Search for Hub Genes of Hepatocellular Carcinoma Without Spatiotemporal Consideration

Biomedical institutions rely on data evaluation and are turning into data factories. Big-data storage centers, supercomputing systems, and increased algorithmic efficiency allow us to analyze the ever-increasing amount of data generated every day in biomedical research centers. In network science, the principal intrinsic problem is how to integrate the data and information from different experiments on genes or proteins. Data curation is an essential process in annotating new functional data to known genes or proteins, undertaken by a biobank curator, which is then reflected in the calculated networks. We provide an example of how protein-protein networks today have space-time limits. The next step is the integration of data and information from different biobanks. Omics data and networks are essential parts of this step but also have flawed protocols and errors. Consider data from patients with cancer: from biopsy procedures to experimental tests, to archiving methods and computational algorithms, these are continuously handled so require critical and continuous "updates" to obtain reproducible, reliable, and correct results. We show, as a second example, how all this distorts studies in cellular hepatocellular carcinoma. It is not unlikely that these flawed data have been polluting biobanks for some time before stringent conditions for the veracity of data were implemented in Big data. Therefore, all this could contribute to errors in future medical decisions.

Weighted Gene Coexpression Network Analysis Reveals Essential Genes and Pathways in Bipolar Disorder

Bipolar disorder (BD) is a major and highly heritable mental illness with severe psychosocial impairment, but its etiology and pathogenesis remains unclear. This study aimed to identify the essential pathways and genes involved in BD using weighted gene coexpression network analysis (WGCNA), a bioinformatic method studying the relationships between genes and phenotypes. Using two available BD gene expression datasets (GSE5388, GSE5389), we constructed a gene coexpression network and identified modules related to BD. The analyses of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways were performed to explore functional enrichment of the candidate modules. A protein-protein interaction (PPI) network was further constructed to identify the potential hub genes. Ten coexpression modules were identified from the top 5,000 genes in 77 samples and three modules were significantly associated with BD, which were involved in several biological processes (e.g., the actin filament-based process) and pathways (e.g., MAPK signaling). Four genes (NOTCH1, POMC, NGF, and DRD2) were identified as candidate hub genes by PPI analysis and CytoHubba. Finally, we carried out validation analyses in a separate dataset, GSE12649, and verified NOTCH1 as a hub gene and the involvement of several biological processes such as actin filament-based process and axon development. Taken together, our findings revealed several candidate pathways and genes (NOTCH1) in the pathogenesis of BD and call for further investigation for their potential research values in BD diagnosis and treatment.

Molecular Mechanisms Underlying Intestinal Ischemia/Reperfusion Injury: Bioinformatics Analysis and In Vivo Validation

Background

Intestinal ischemia/reperfusion (I/R) injury is a serious clinical complication. This study aimed to explore the hub genes and pathways of intestinal I/R injury.

Material/Methods

GSE96733 from the GEO website was extracted to analyze the differentially expressed genes (DEGs) of intestinal I/R injured and sham-operated mice at 3 h and 6 h after surgery. The DAVID and STRING databases were used to construct functional enrichment analyses of DEGs and the protein–protein interaction (PPI) network. In Cytoscape software, cytoHubba was used to identify hub genes, and MCODE was used for module analysis. Testing by qRT-PCR detected the expression of hub genes in intestinal I/R injury. Western blot analysis detected the key proteins involved with the important pathways of intestinal I/R injury.

Results

IL-6, IL-10, CXCL1, CXCL2, and IL-1β were identified as critical upregulated genes, while IRF7, IFIT3, IFIT1, Herc6, and Oasl2 were identified as hub genes among the downregulated genes. The qRT-PCR testing showed the expression of critical upregulated genes was significantly increased in intestinal I/R injury (P<0.05), while the expression of hub downregulated genes was notably reduced (P<0.05). The proteins of CXCL1 and CXCR2 were upregulated following intestinal I/R injury (P<0.05) and the CXCL1/CXCR2 axis was involved with intestinal I/R injury.

Conclusions

The results of the present study identified IL-6, IL-10, CXCL1, CXCL2, IL-1β, IRF7, IFIT3, IFIT1, Herc6, and Oasl2 as hub genes in intestinal I/R injury and identified the involvement of the CXCL1/CXCR2 axis in intestinal I/R injury.

Elucidation of the miR164c-Guided Gene/Protein Interaction Network Controlling Seed Vigor in Rice

MicroRNAs (miRNAs) play important roles in various aspects of plant physiology and metabolism. The expression level of miR164c is negatively correlated with seed vigor in rice (Oryza sativa L.); however, the mechanism of seed vigor regulation by miR164c remains unknown. Anti-aging capacity is an important indicator of seed vigor. Here, we report an miR164c-guided gene/protein interaction network that regulates the anti-aging ability of rice seeds. Seeds of the wild-type (WT) rice cultivar "Kasalath" and its transgenic derivatives, miR164c-silenced line (MIM164c) and miR164c overexpression line (OE164c), with significant differences in anti-aging capacity, showed significant differences in gene and protein expression levels. The differentially expressed genes (DEGs) or proteins were significantly enriched in six metabolic functional categories related to seed vigor, including "stress response," "protein processing in endoplasmic reticulum (ER)," "embryo development," "serine-type endopeptidase inhibitor," "energy metabolism," and "other." Differences in the expression levels of genes or proteins related to energy metabolism, serine endopeptidase, and stress response in seeds under normal storage conditions may be associated with anti-aging capacity. The results of gene/protein interaction analyses suggest that miR164c first targets PSK5, and the PSK5 protein then interacts with the ubiquitin-associated gene RPS27AA, which simultaneously impacts the genes/proteins in the six above-mentioned functional categories. Expression levels of some of the key genes and proteins in the interaction network were verified by real-time fluorescence quantitative PCR (RT-qPCR) and multiple reaction monitoring mass spectrometry (MRM-MS), respectively. Thus, the present study provides new insights into the miRNA-mediated gene and protein interaction network that regulates seed vigor.

Network Pharmacology-Based Study on the Mechanism of Scutellariae Radix for Hepatocellular Carcinoma Treatment

Hepatocellular carcinoma (HCC) is a malignant tumor without effective therapeutic drugs for most patients in advanced stages. Scutellariae Radix (SR) is a well-known anti-inflammatory and anticarcinogenic herbal medicine. However, the mechanism of SR against HCC remains to be clarified. In the present study, network pharmacology was utilized to characterize the mechanism of SR on HCC. The active components of SR and their targets were collected from the traditional Chinese medicine systems pharmacology database and the traditional Chinese medicine integrated database. HCC-related targets were acquired from the liver cancer databases OncoDB.HCC and Liverome. The gene ontology and the Kyoto Encyclopedia of Genes and Genomes pathway were analyzed using the Database for Annotation, Visualization, and Integrated Discovery. Component-component target and protein-protein interaction networks were set up. A total of 143 components of SR were identified, and 37 of them were considered as candidate active components. Fifty targets corresponding to 29 components of SR were mapped with targets of HCC. Functional enrichment analysis indicated that SR exerted an antihepatocarcinoma effect by regulating pathways in cancer, hepatitis B, viral carcinogenesis, and PI3K-Akt signaling. The holistic approach of network pharmacology can provide novel insights into the mechanistic study and therapeutic drug development of SR for HCC treatment.

Molecular targets of Yangyin Fuzheng Jiedu Prescription in the treatment of hepatocellular carcinoma based on network pharmacology analysis

Background

Yangyin Fuzheng Jiedu Prescription (YFJP) is a traditional Chinese medicine (TCM) indicated for the treatment of hepatocellular carcinoma (HCC). Its potential targets and molecular mechanisms are not clear. Therefore, this study intends to explore the molecular mechanism of YFJP based on network pharmacology analysis and in vitro validation.

Methods and results

Through univariate and multivariate analyses and survival analysis in HCC patients with or without YFJP treatment we found that drinking alcohol, alfafeto protein ≥ 400 ng/l, baseline portal vein tumor thrombus and total bilirubin level ≥ 18.8 μM) were independent risk factors for poor prognosis, while red blood cell count ≥ 4 × 10⁹/l and TCM treatment were independent protective factors. Besides, YFJP prolonged the cumulative survival of HCC patients. Using online pharmacological methods, we obtained 58 relevant compounds and molecular 53 targets. By using scratch test, Transwell assay, EdU assay, and TUNEL staining, we found that YFJP-containing serum repressed the migration, invasion and proliferation of HCC cells in vitro, and induced cell apoptosis. Moreover, YFJP diminished the gene expression of TP53, CCND1, p-EGFR, EGF, VEGFA, JUN, IL6, COX-2, AKT1, and MAPK1 in HCC cells, but elevated the expression of ESR1 and CASP3.

Conclusions

Taken together, results showed that YFJP attenuated HCC progression through mediating effects on HCC-related genes.

Epigenome-wide DNA methylation profiling of portal vein tumor thrombosis (PVTT) tissues in hepatocellular carcinoma patients

Aberrant methylation is a hallmark of hepatocellular carcinoma and plays an important role in tumor initiation and progression. However, the epigenome-wide methylation patterns of portal vein tumor thrombosis (PVTTs) have not been fully explored. Here, we performed epigenome-wide DNA methylation of adjacent normal tissues (ANTs), paired tumor tissues and paired PVTTs using an Infinium HumanMethylation450 array (n = 11) and conducted the Sequenom EpiTYPER assays to confirm the aberrantly methylated genes. MTS and apoptosis assay were used to assess the synergistic effect of two drugs on the HCC cell lines. We found the mean global methylation levels of HCC tissues and PVTTs were significantly lower than ANTs (P < 0.01). A total of 864 differentially methylated CpG sites annotated in 532 genes were identified between HCC tissues and paired PVTTs (|mean methylation difference|>10%, P < 0.005). The pathway analysis based on hypermethylated genes in PVTT tissues was interestingly enriched in regulation of actin cytoskeleton pathway (P = 4.48E−5). We found 23 genes whose methylation levels were gradually alternated in HCC tissues and PVTTs. Aberrant methylation status of TNFRSF10A, ZC3H3 and SLC9A3R2 were confirmed in a validation cohort (n = 48). The functional experiments demonstrated the combination of decitabine (DAC) and tumor necrosis factor-related apoptosis-inducing ligand (rh-TRAIL) could synergistically suppress the proliferation and induce apoptosis in SK-Hep-1 and Huh7 cell lines. Together, our findings indicated that DNA methylation plays an important role in the PVTT formation through regulating the metastasis-related pathways. The combination of DAC and rh-TRAIL might be a promising treatment strategy for HCC.

Exploring DNA Methylation Profiles Altered in Cryptogenic Hepatocellular Carcinomas by High-Throughput Targeted DNA Methylation Sequencing: A Preliminary Study for Cryptogenic Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) includes cryptogenic hepatocellular carcinomas (CR-HCC) that lack a defined cause. Specific DNA methylation patterns and comparisons of the aberrant alterations in DNA methylation between CR-HCC and adjacent peritumor tissues (APTs) have not yet been reported.

Methods

The SureSelectXT Methyl-Seq Target Enrichment System was used to sequence targeted DNA methylation in three paired CR-HCC tissues and APTs. Gene Ontology (GO) enrichment and KEGG pathway analysis were performed to investigate the DNA methylation mechanism of CR-HCC. The mRNA expression levels of HOXB-AS3, HOXB6, HOXB3, USP18, MAP3K6, TIRAP, TNNI2, SHC3, CTTN, and TFAP2A, selected from the identified signaling pathways, were evaluated by quantitative real-time PCR (qPCR).

Results

A total of 1728 differentially methylated regions (DMRs) were identified in tumor tissues compared with non-tumor tissues, of which 868 DMRs were hypermethylated and 860 were hypomethylated. The DMRs were mapped within 2091 DMR-associated genes (DMGs). The mRNA expression of HOXB-AS3, HOXB3, and MAP3K6 was downregulated in CR-HCC tissues compared to the APTs. However, the mRNA expression of TIRAP, SHC3, and CTTN was upregulated in the CR-HCC tissues. Differences between the mRNA expression of HOXB6, USP18, TNNI2, and TFAP2A in the CR-HCC and APTS tissues were not statistically significant. GO analysis showed that the molecular functions of “binding”, “protein binding”, and “cytoskeletal protein binding” were the main categories for the hypermethylated DMGs. The hypomethylated DMGs were mostly enriched in the molecular functions “binding”, “protein binding”, “calcium ion binding”, among others. KEGG pathway analysis showed that the hypermethylated DMGs were enriched in several pathways such as “estrogen signaling pathway”, while hypomethylated DMGs were enriched in several pathways such as “proteoglycans in cancer”, suggesting that epigenetic modifications play important roles in the cryptogenic hepatocarcinogenesis.

Conclusion

These results provide useful information for future work to characterize the functions of epigenetic mechanisms on CR-HCC.

Exploring celiac disease candidate pathways by global gene expression profiling and gene network cluster analysis

Celiac disease (CeD) is a gastrointestinal autoimmune disorder, whose specific molecular basis is not yet fully interpreted. Therefore, in this study, we compared the global gene expression profile of duodenum tissues from CeD patients, both at the time of disease diagnosis and after two years of the gluten-free diet. A series of advanced systems biology approaches like differential gene expression, protein–protein interactions, gene network-cluster analysis were deployed to annotate the candidate pathways relevant to CeD pathogenesis. The duodenum tissues from CeD patients revealed the differential expression of 106 up- and 193 down-regulated genes. The pathway enrichment of differentially expressed genes (DEGs) highlights the involvement of biological pathways related to loss of cell division regulation (cell cycle, p53 signalling pathway), immune system processes (NOD-like receptor signalling pathway, Th1, and Th2 cell differentiation, IL-17 signalling pathway) and impaired metabolism and absorption (mineral and vitamin absorptions and drug metabolism) in celiac disease. The molecular dysfunctions of these 3 biological events tend to increase the number of intraepithelial lymphocytes (IELs) and villous atrophy of the duodenal mucosa promoting the development of CeD. For the first time, this study highlights the involvement of aberrant cell division, immune system, absorption, and metabolism pathways in CeD pathophysiology and presents potential novel therapeutic opportunities.

Identification of potential crucial genes associated with the pathogenesis and prognosis of liver hepatocellular carcinoma

AIMS

Liver hepatocellular carcinoma (LIHC) is the main manifestation of primary liver cancer, with low survival rate and poor prognosis. Medical decision-making process of LIHC is so complex that new biomarkers for diagnosis and prognosis have yet to be explored, this study aimed to identify the genes involved in the pathophysiology of LIHC and biomarkers that can be used to predict the prognosis of LIHC.

METHODS

Six Gene Expression Omnibus (GEO) datasets selected from GEO were screened and integrated to find out the differential expression genes (DEGs) obtained from LIHC and normal hepatic tissues. The Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analysis of DEGs was implemented by DAVID. The Protein-protein interaction network was performed via STRING. In addition, Cox regression model was used to construct a gene prognostic signature.

RESULTS

We ascertained 10 hub genes, nine of them (CDK1, CDC20, CCNB1, Thymidylate synthetase, Nuclear division cycle80, NUF2, MAD2L1, CCNA2 and BIRC5) as biomarkers of progression in LIHC patients. We also build a six gene prognosis signature (SOCS2, GAS2L3, NLRP5, TAF3, UTP11 and GAGE2A), which can be implemented to predict over survival effectively.

CONCLUSIONS

We revealed promising genes that may participate in the pathophysiology of LIHC, and found available biomarkers for LIHC prognosis prediction, which were significant for researchers to further understand the molecular basis of LIHC and direct the synthesis medicine of LIHC.

Proteomic analysis revealed common, unique and systemic signatures in gender-dependent hepatocarcinogenesis

Hepatocellular carcinoma (HCC) is the most common liver cancer and is highly malignant. Male prevalence and frequent activation of the Ras signaling pathway are distinct characteristics of HCC. However, the underlying mechanisms remain to be elucidated. By exploring Hras12V transgenic mice showing male-biased hepatocarcinogenesis, we performed a high-throughput comparative proteomic analysis based on tandem-mass-tag (TMT) labeling combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) on the tissue samples obtained from HCC (T) and their paired adjacent precancerous (P) of Hras12V transgenic male and female mice (Ras-Tg) and normal liver (W) of wild-type male and female mice (Non-Tg). The further validation and investigation were performed using quantitative real-time PCR and western blot. Totally, 5193 proteins were quantified, originating from 5733 identified proteins. Finally, 1344 differentially expressed proteins (DEPs) (quantified in all examined samples; |ratios| ≥ 1.5, p < 0.05) were selected for further analysis. Comparison within W, P, and T of males and females indicated that the number of DEPs in males was much higher than that in females. Bioinformatics analyses showed the common and unique cluster-enriched items between sexes, indicating the common and gender-disparate pathways towards HCC. Expression change pattern analysis revealed HCC positive/negative-correlated and ras oncogene positive/negative-correlated DEPs and pathways. In addition, it showed that the ras oncogene gradually and significantly reduced the responses to sex hormones from hepatocytes to hepatoma cells and therefore shrunk the gender disparity between males and females, which may contribute to the cause of the loss of HCC clinical responses to the therapeutic approaches targeting sex hormone pathways. Additionally, gender disparity in the expression levels of key enzymes involved in retinol metabolism and terpenoid backbone/steroid biosynthesis pathways may contribute to male prevalence in hepatocarcinogenesis. Further, the biomarkers, SAA2, Orm2, and Serpina1e, may be sex differences. In conclusion, common and unique DEPs and pathways toward HCC initiated by ras oncogene from sexually dimorphic hepatocytes provide valuable and novel insights into clinical investigation and practice.

Identification of Potential Key Genes Associated With the Pathogenesis, Metastasis, and Prognosis of Triple-Negative Breast Cancer on the Basis of Integrated Bioinformatics Analysis

Objective: Breast cancer is the most common solid tumor affecting women and the second leading cause of cancer-related death worldwide, and triple-negative breast cancer (TNBC) is the most lethal subtype of breast cancer. We aimed to identify potential TNBC-specific therapeutic targets by performing an integrative analysis on previously published TNBC transcriptome microarray data.

Methods: Differentially expressed genes (DEGs) between TNBC and normal breast tissues were screened using six Gene Expression Omnibus (GEO) datasets, and DEGs between metastatic TNBC and non-metastatic TNBC were screened using one GEO dataset. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed on the overlapping DEGs. The Cancer Genome Atlas (TCGA) TNBC data were used to identify candidate genes that were strongly associated with survival. Expression of the candidate genes in TNBC cell lines was blocked or augmented using a lentivirus system, and transwell assays were used to determine their effect on TNBC migration.

Results: Eight upregulated genes and nine downregulated genes were found to be differentially expressed both between TNBC and normal breast tissues and between metastatic TNBC and non-metastatic TNBC. Among them, S100P and SDC1 were identified as poor prognostic genes. Furthermore, compared with control cells, SDC1-overexpressing TNBC cells showed enhanced migration ability, whereas SDC1 knockdown markedly reduced the migration of TNBC cells.

Conclusion: Our study determined that S100P and SDC1 may be potential treatment targets as well as prognostic biomarkers of TNBC.

Identification of methylated-differentially expressed genes and pathways in esophageal squamous cell carcinoma

Methylation, as an epigenetic modification, can affect gene expression and play a role in the occurrence and development of cancer. This research is devoted to discover methylated-differentially expressed genes (MDEGs) in esophageal squamous cell carcinoma (ESCC) and explore special associated pathways. We downloaded GSE51287 methylation profiles and GSE26886 expression profiles from GEO DataSets, and performed a comprehensive bioinformatics analysis. Totally, 19 hypermethylated, lowly expressed genes (Hyper-LGs) were identified, and involved in regulation of cell proliferation, phosphorus metabolic process and protein kinase activity. Meanwhile, 17 hypomethylated, highly expressed genes (Hypo-HGs) were participated in collagen catabolic process, metallopeptidase and cytokine activity. Pathway analysis determined that Hyper-LGs were enriched in arachidonic acid metabolism pathway, while Hypo-HGs were primarily associated with the cytokine-cytokine receptor interaction pathway. IL 6, MMP3, MMP9, SPP1 were identified as hub genes based on the PPI network that combined 7 ranked methods included in cytoHubba, and verification was performed in human tissues. Our integrated analysis identified many novel genetic lesions in ESCC and provides a crucial molecular foundation to improve our understanding of ESCC. Hub genes, including IL 6, MMP3, MMP9 and SPP1, could be considered for use as aberrant methylation-based biomarkers to facilitate the accurate diagnosis and therapy of ESCC.

Knowledge-based analyses reveal new candidate genes associated with risk of hepatitis B virus related hepatocellular carcinoma

BACKGROUND

Recent genome-wide association studies (GWASs) have suggested several susceptibility loci of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) by statistical analysis at individual single-nucleotide polymorphisms (SNPs). However, these loci only explain a small fraction of HBV-related HCC heritability. In the present study, we aimed to identify additional susceptibility loci of HBV-related HCC using advanced knowledge-based analysis.

METHODS

We performed knowledge-based analysis (including gene- and gene-set-based association tests) on variant-level association p-values from two existing GWASs of HBV-related HCC. Five different types of gene-sets were collected for the association analysis. A number of SNPs within the gene prioritized by the knowledge-based association tests were selected to replicate genetic associations in an independent sample of 965 cases and 923 controls.

RESULTS

The gene-based association analysis detected four genes significantly or suggestively associated with HBV-related HCC risk: SLC39A8, GOLGA8M, SMIM31, and WHAMMP2. The gene-set-based association analysis prioritized two promising gene sets for HCC, cell cycle G1/S transition and NOTCH1 intracellular domain regulates transcription. Within the gene sets, three promising candidate genes (CDC45, NCOR1 and KAT2A) were further prioritized for HCC. Among genes of liver-specific expression, multiple genes previously implicated in HCC were also highlighted. However, probably due to small sample size, none of the genes prioritized by the knowledge-based association analyses were successfully replicated by variant-level association test in the independent sample.

CONCLUSIONS

This comprehensive knowledge-based association mining study suggested several promising genes and gene-sets associated with HBV-related HCC risks, which would facilitate follow-up functional studies on the pathogenic mechanism of HCC.

Genome‑wide DNA methylation regulation analysis of long non‑coding RNAs in glioblastoma

Glioblastoma (GBM) is a malignant brain tumor associated with high mortality. Long non-coding RNAs (lncRNAs) are increasingly being recognized as its modulators. However, it remains mostly unexplored how lncRNAs are mediated by DNA methylation in GBM. The present study integrated multi-omics data to analyze the epigenetic dysregulation of lncRNAs in GBM. Widely aberrant methylation in the lncRNA promoters was observed, and the lncRNA promoters exhibited a more hypomethylated pattern in GBM. By combining transcriptional datasets, it was possible identify the lncRNAs whose transcriptional changes might be associated with the aberrant promoter methylation. Then, a methylation-mediated lncRNA regulatory network and functional enrichment analysis of aberrantly methylated lncRNAs showed that lncRNAs with different methylation patterns were involved in diverse GBM progression-related biological functions and pathways. Specifically, four lncRNAs whose increased expression may be regulated by the corresponding promoter hypomethylation were evaluated to have an excellent diagnostic effect and clinical prognostic value. Finally, through the construction of drug-target association networks, the present study identified potential therapeutic targets and small-molecule drugs for GBM treatment. The present study provides novel insights for understanding the regulation of lncRNAs by DNA methylation and developing cancer biomarkers in GBM.

Screening for genes and subnetworks associated with atypical teratoid/rhabdoid tumors using bioinformatics analysis

Objectives: Atypical teratoid/rhabdoid tumors (AT/RTs) are rare, fast-growing lesions of central nervous system and their prognosis is poor. Nowadays, multimodal managements, including surgery, chemotherapy and radiation therapy are advocated; however, low survival rate and severe neurocognitive toxicity of chemotherapy as well as the irreversible long-term sequelae of irradiation in infants and young children with AT/RTs are alarming. The aim of our study is to provide valid biological information for more tailored advance therapy for these lesions.Methods: Gene expression profile of GSE94349 was downloaded from GEO database and was analyzed using limma R package. Function and enrichment analyses of DEGs were performed based on DAVID database. PPI network construction, hub gene selection and module analysis were conducted in Cytoscape software.Results: In this study, 224 up-regulated genes and 572 down-regulated genes were selected as DEGs. The up-regulated genes were mainly enriched in molecular function and cell component, which mainly included protein binding and nucleus, respectively. The down-regulated DEGs were significantly involved in cell component such as plasma membrane and integral component of membrane. Cell cycle and retrograde endocannabinoid signaling were the main KEGG pathway of up and down DEGs, respectively. CDK1, CCNA2, CDC20, TOP2A were identified as hub genes and two significant network modules were also obtained.Conclusions: Our study may help to further understand the molecular characteristics and provide more tailored targets for future treatment of AT/RTs. Hub genes CDK1, CCNA2, CDC20, TOP2A as well as cell cycle signaling pathway may be new more tailored targets for future treatment of AT/RTs.

A four-methylated mRNA signature-based risk score system predicts survival in patients with hepatocellular carcinoma

Evidence suggests that altered DNA methylation plays a causative role in the pathogenesis of various cancers, including hepatocellular carcinoma (HCC). Thus, methylated differently expressed genes (MDEGs) could potentially serve as biomarkers and therapeutic targets in HCC. In the present study, screening four genomics profiling datasets (GSE62232, GSE84402, GSE73003 and GSE57956) enabled us to identify a total of 148 MDEGs. A signature was then established based on the top four MDEGs (BRCA1, CAD, CDC20 and RBM8A). Taking clinical variables into consideration, we constructed a risk score system consisting of the four-MDEG signature and the patients' clinical features, which was predictive of prognosis in HCC. The prognostic value of the HCC risk score system was confirmed using TCGA HCC samples. The scores were then used to construct a nomogram, performance of which was evaluated using Harrel's concordance index (C-index) and a calibration curve. The signature-based nomogram for prediction of overall survival in HCC patients exhibited good performance and was superior to traditional staging systems (C-index: 0.676 vs 0.629, P< 0.05). We have thus established a novel risk score system that is predictive of prognosis and is a potentially useful guide for personalized treatment of HCC patients.

Uncovering the potential differentially expressed miRNAs as diagnostic biomarkers for hepatocellular carcinoma based on machine learning in The Cancer Genome Atlas database

The present study aimed to identify novel diagnostic differentially expressed microRNAs (miRNAs/miRs) in order to understand the molecular mechanisms underlying hepatocellular carcinoma. The expression data of miRNA and mRNA were downloaded for differential expression analysis. Optimal diagnostic differentially expressed miRNA biomarkers were identified via a random forest algorithm. Classification models were established to distinguish patients with hepatocellular carcinoma and normal individuals. A regulatory network between optimal diagnostic differentially expressed miRNA and differentially expressed mRNAs was then constructed. The GSE63046 dataset and in vitro experiments were used to validate the expression of the optimal diagnostic differentially expressed miRNAs identified. In addition, diagnostic and prognostic analyses of optimal diagnostic differentially expressed miRNAs were performed. In total, 14 differentially expressed miRNAs (all upregulated) and 2,982 differentially expressed mRNAs (1,989 upregulated and 993 downregulated) were identified. hsa-miR-10b-5p, hsa-miR-10b-3p, hsa-miR-224-5p, hsa-miR-183-5p and hsa-miR-182-5p were considered as the optimal diagnostic biomarkers for hepatocellular carcinoma. The mRNAs targeted by these five miRNAs included secreted frizzled related protein 1 (SFRP1), endothelin receptor type B (EDNRB), nuclear receptor subfamily 4 group A member 3 (NR4A3), four and a half LIM domains 2 (FHL2), NK3 homeobox 1 (NKX3-1), interleukin 6 signal transducer (IL6ST) and forkhead box O1 (FOXO1). ‘Bile acid biosynthesis and cholesterol’ was the most enriched signaling pathways of these target mRNAs. The expression validation of the five miRNAs was consistent with the present bioinformatics analysis. Notably, hsa-miR-10b-5p and hsa-miR-10b-3p had a significant prognosis value for patients with hepatocellular carcinoma. In conclusion, the five differentially expressed miRNAs may be considered as diagnostic biomarkers for patients with hepatocellular carcinoma. In addition, the differential expression levels of the targets of these five mRNAs, including SFRP1, EDNRB, NR4A3, FHL2, NKX3−1, IL6ST and FOXO1, may be involved in hepatocellular carcinoma tumorigenesis.

Identification of Core Prognosis-Related Candidate Genes in Cervical Cancer via Integrated Bioinformatical Analysis

Purposes

Cervical cancer (CC) is one of the highest frequently occurred malignant gynecological tumors with high rates of morbidity and mortality. Here, we aimed to identify significant genes associated with poor outcome. Materials and methods. Differentially expressed genes (DEGs) between CC tissues and normal cervical tissues were picked out by GEO2R tool and Venn diagram software. Database for Annotation, Visualization and Integrated Discovery (DAVID) was performed to analyze gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway. The protein-protein interactions (PPIs) of these DEGs were visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING). Afterwards, Kaplan-Meier analysis was applied to analyze the overall survival among these genes. The Gene Expression Profiling Interactive Analysis (GEPIA) was applied for further validation of the expression level of these genes.

Results

The mRNA expression profile datasets of GSE63514, GSE27678, and GSE6791 were downloaded from the Gene Expression Omnibus database (GEO). In total, 76 CC tissues and 35 normal tissues were collected in the three profile datasets. There were totally 73 consistently expressed genes in the three datasets, including 65 up-regulated genes and 8 down-regulated genes. Of PPI network analyzed by Molecular Complex Detection (MCODE) plug-in, all 65 up-regulated genes and 4 down-regulated genes were selected. The results of the Kaplan-Meier survival analysis showed that 3 of the 65 up-regulated genes had a significantly worse prognosis, while 3 of the 4 down-regulated genes had a significantly better outcome. For validation in GEPIA, 4 of 6 genes (PLOD2, ANLN, AURKA, and AR) were confirmed to be significantly deregulated in CC tissues compared to normal tissues.

Conclusion

We have identified three up-regulated (PLOD2, ANLN, and AURKA) and a down-regulated DEGs (AR) with poor prognosis in CC on the basis of integrated bioinformatical methods, which could be regarded as potential therapeutic targets for CC patients.

Comprehensive analysis of DNA methylation and gene expression profiles in cholangiocarcinoma

BACKGROUND

The incidence of cholangiocarcinoma (CCA) has risen in recent years, and it has become a significant health burden worldwide. However, the mechanisms underlying tumorigenesis and progression of this disease remain largely unknown. An increasing number of studies have demonstrated crucial biological functions of epigenetic modifications, especially DNA methylation, in CCA. The present study aimed to identify and analyze methylation-regulated differentially expressed genes (MeDEGs) involved in CCA tumorigenesis and progression by bioinformatics analysis.

METHODS

The gene expression profiling dataset (GSE119336) and gene methylation profiling dataset (GSE38860) were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were identified using the limma packages of R and GEO2R, respectively. The MeDEGs were obtained by overlapping the DEGs and DMGs. Functional enrichment analyses of these genes were then carried out. Protein-protein interaction (PPI) networks were constructed using STRING and visualized in Cytoscape to determine hub genes. Finally, the results were verified based on The Cancer Genome Atlas (TCGA) database.

RESULTS

We identified 98 hypermethylated, downregulated genes and 93 hypomethylated, upregulated genes after overlapping the DEGs and DMGs. These genes were mainly enriched in the biological processes of the cell cycle, nuclear division, xenobiotic metabolism, drug catabolism, and negative regulation of proteolysis. The top nine hub genes of the PPI network were F2, AHSG, RRM2, AURKB, CCNA2, TOP2A, BIRC5, PLK1, and ASPM. Moreover, the expression and methylation status of the hub genes were significantly altered in TCGA.

CONCLUSIONS

Our study identified novel methylation-regulated differentially expressed genes (MeDEGs) and explored their related pathways and functions in CCA, which may provide novel insights into a further understanding of methylation-mediated regulatory mechanisms in CCA.

The Pharmacological Effects of Spatholobi Caulis Tannin in Cervical Cancer and Its Precise Therapeutic Effect on Related circRNA

The chemical components of Spatholobi Caulis tannin (SCT) have a modest therapeutic effect in patients with cervical cancer. However, the active components and the mechanism of action of SCT in HeLa cervical cancer cells need to be further studied. In this paper, 3D microfluidic chip technology was applied to simulate the effects of tannins in the human body, and the appropriate dose and time of administration were calculated. The cell cycle and apoptosis experiments demonstrated that SCT inhibits proliferation and stimulated apoptosis in HeLa cells. The differentially expressed genes were screened using The Cancer Genome Atlas (TCGA) and the GEO databases to identify common differentially expressed genes. A bioinformatic analysis of relevant genes, analysis using the molecular docking technique, and survival analysis were used to predict the target genes of SCT. Circular RNAs (circRNAs) associated with the SCT target genes and the regulatory effects of SCT on these circRNAs were determined. These studies showed that SCT mediates related circRNAs in HeLa cells to inhibit proliferation and promote apoptosis in HeLa cells. Thus, SCT may be an effective strategy for treating cervical cancer.

Identification of Flap endonuclease 1 as a potential core gene in hepatocellular carcinoma by integrated bioinformatics analysis

Hepatocellular carcinoma (HCC) is a common yet deadly form of malignant cancer. However, the specific mechanisms involved in HCC diagnosis have not yet fully elucidated. Herein, we screened four publically available Gene Expression Omnibus (GEO) expression profiles (GSE14520, GSE29721, GSE45267 and GSE60502), and used them to identify 409 differentially expressed genes (DEGs), including 142 and 267 up- and down-regulated genes, respectively. The DAVID database was used to look for functionally enriched pathways among DEGs, and the STRING database and Cytoscape platform were used to generate a protein-protein interaction (PPI) network for these DEGs. The cytoHubba plug-in was utilized to detect 185 hub genes, and three key clustering modules were constructed with the MCODE plug-in. Gene functional enrichment analyses of these three key clustering modules were further performed, and nine core genes including BIRC5, DLGAP5, DTL, FEN1, KIAA0101, KIF4A, MCM2, MKI67, and RFC4, were identified in the most critical cluster. Subsequently, the hierarchical clustering and expression of core genes in TCGA liver cancer tissues were analyzed using the UCSC Cancer Genomics Browser, and whether elevated core gene expression was linked to a poor prognosis in HCC patients was assessed using the GEPIA database. The PPI of the nine core genes revealed an interaction between FEN1, MCM2, RFC4, and BIRC5. Furthermore, the expression of FEN1 was positively correlated with that of three other core genes in TCGA liver cancer tissues. FEN1 expression in HCC and other tumor types was assessed with the FIREBROWSE and ONCOMINE databases, and results were verified in HCC samples and hepatoma cells. FEN1 levels were also positively correlated with tumor size, distant metastasis and vascular invasion. In conclusion, we identified nine core genes associated with HCC development, offering novel insight into HCC progression. In particular, the aberrantly elevated FEN1 may represent a potential biomarker for HCC diagnosis and treatment.

Identification of aberrantly methylated differentially expressed genes in glioblastoma multiforme and their association with patient survival

Glioblastoma multiforme (GBM) is the most malignant primary tumour type of the central nervous system with limited therapeutic options and poor prognosis, and its pathogenic mechanisms have remained to be fully elucidated. Aberrant DNA methylation is involved in multiple biological processes and may contribute to the occurrence and development of GBM by affecting the expression of certain genes. However, the specific molecular mechanisms remain to be fully elucidated. The present study focused on uncovering differentially expressed genes with altered methylation status in GBM and aimed to discover novel biomarkers for the diagnosis and treatment of GBM. These genes were identified by combined analysis of multiple gene expression and methylation datasets from gene expression omnibus (GSE16011, GSE50161 and GSE 50923) to increase the reliability. In addition, The Cancer Genome Atlas (TCGA) dataset for GBM was used to test the stability of the results. Overall, 251 hypomethylated upregulated genes (Hypo-UGs) and 199 hypermethylated downregulated genes (Hyper-DGs) were identified in the present study. Functional enrichment analysis revealed that the Hypo-UGs are involved in the regulation of immune- and infection-associated signalling, while the Hyper-DGs are involved in the regulation of synaptic transmission. The three hub genes for Hyper-DGs (somatostatin, neuropeptide Y and adenylate cyclase 2) and five hub genes for Hypo-UGs [interleukin-8, matrix metalloproteinase (MMP)9, cyclin-dependent kinase 1, 2′-5′-oligoadenylate synthetase 1, C-X-C motif chemokine ligand 10 and MMP2] were identified by protein-protein interaction network analysis. Among the Hypo-UGs and Hyper-DGs, overexpression of C-type lectin domain containing 5A, epithelial membrane protein 3, solute carrier family 43 member 3, STEAP3 metalloreductase, tumour necrosis factor α-induced protein 6 and apolipoprotein B mRNA editing enzyme catalytic subunit 3G was significantly associated with poor prognosis in the TCGA and GSE16011 datasets (P<0.001). In conclusion, the present study uncovered numerous novel aberrantly methylated genes and pathways associated with GBM. Methylation-based markers, including the hub genes and prognostic genes identified, may potentially serve as markers for the diagnosis of GBM and targets for its treatment.

Hepatocellular carcinoma: Therapeutic advances in signaling, epigenetic and immune targets

Hepatocellular carcinoma (HCC) remains a global medical burden with rising incidence due to chronic viral hepatitis and non-alcoholic fatty liver diseases. Treatment of advanced disease stages is still unsatisfying. Besides first and second generation tyrosine kinase inhibitors, immune checkpoint inhibitors have become central for the treatment of HCC. New modalities like epigenetic therapy using histone deacetylase inhibitors (HDACi) and cell therapy approaches with chimeric antigen receptor T cells (CAR-T cells) are currently under investigation in clinical trials. Development of such novel drugs is closely linked to the availability and improvement of novel preclinical and animal models and the identification of predictive biomarkers. The current status of treatment options for advanced HCC, emerging novel therapeutic approaches and different preclinical models for HCC drug discovery and development are reviewed here.

Microarray gene expression profiling and bioinformatics analysis reveal key differentially expressed genes in clival and sacral chordoma cell lines

OBJECTIVE

Chordoma is a rare tumor with a certain rate of distant metastasis. Skull base and sacrum are the two most common origin sites. This study tends to identify key differentially expressed genes (DEGs) between classical clival and sacral chordomas, provide new targets for future treatment options of chordomas.

METHODS

The gene expression profiles of GSE95084 and GSE68497 were downloaded from Gene Expression Omnibus database and were analyzed using the limma R package. Function and enrichment analyses of DEGs were performed based on DAVID Database. Protein-protein interaction (PPI) network was constructed using the Cytoscape based on the data collected from STRING online datasets. Hub genes selection and modules analyses of the PPI network were conducted by plugin cytoHubba and MCODE of Cytoscape software, respectively.

RESULT

In total, 728 genes, including 363 up-regulated genes and 365 down-regulated genes were selected as DEGs. Notably, GO analysis showed that both up-regulated and down-regulated DEGs were mainly involved in cell component such as an integral component of the membrane, plasma membrane and extracellular exosome. DEGs were mainly enriched in pathways like Pathways in cancer, PI3K-Akt signaling pathway, Cytokine-cytokine receptor interaction. FYN, ITGB3, ACTN2 and IGF1 were identified as hub genes and they were all involved in focal adhesion signaling pathway. Furthermore, five significant network modules were obtained from the PPI network.

CONCLUSION

This study helps to further understand the molecular characteristics of classic chordomas of two distinct sites. Hub genes FYN, ITGB3, ACTN2, and IGF1, as well as focal adhesion signaling pathway, would be new targets for future treatment options of chordomas.

Large-scale analysis reveals a novel risk score to predict overall survival in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is a major cause of cancer mortality and an increasing incidence worldwide; however, there are very few effective diagnostic approaches and prognostic biomarkers.

Materials and methods

One hundred forty-nine pairs of HCC samples from Gene Expression Omnibus (GEO) were obtained to screen differentially expressed genes (DEGs) between HCC and normal samples. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Gene ontology enrichment analyses, and protein–protein interaction network were used. Cox proportional hazards regression analysis was used to identify significant prognostic DEGs, with which a gene expression signature prognostic prediction model was identified in The Cancer Genome Atlas (TCGA) project discovery cohort. The robustness of this panel was assessed in the GSE14520 cohort. We verified details of the gene expression level of the key molecules through TCGA, GEO, and qPCR and used immunohistochemistry for substantiation in HCC tissues. The methylation states of these genes were also explored.

Results

Ninety-eight genes, consisting of 13 upregulated and 85 downregulated genes, were screened out in three datasets. KEGG and Gene ontology analysis for the DEGs revealed important biological features of each subtype. Protein–protein interaction network analysis was constructed, consisting of 64 nodes and 115 edges. A subset of four genes (SPINK1, TXNRD1, LCAT, and PZP) that formed a prognostic gene expression signature was established from TCGA and validated in GSE14520. Next, the expression details of the four genes were validated with TCGA, GEO, and clinical samples. The expression panels of the four genes were closely related to methylation states.

Conclusion

This study identified a novel four-gene signature biomarker for predicting the prognosis of HCC. The biomarkers may also reveal molecular mechanisms underlying development of the disease and provide new insights into interventional strategies.