Identification of hub genes in hepatocellular carcinoma using integrated bioinformatic analysis

SP1/RNASEH2A accelerates the development of hepatocellular carcinoma by regulating EMT

Background

The expression level of Ribonuclease H2, subunit A (RNASEH2A) in hepatocellular carcinoma (HCC) has been reported, but the function of RNASEH2A on HCC cells development and the related molecular mechanisms remain unclear. Herein, we intend to explore the upstream regulator of RNASEH2A and its role in the HCC progression.

Methods

GEPIA website was employed to determine the level of RNASEH2A in HCC tissues and get a survival analysis. After reducing RNASEH2A expression by RNA interference, cell counting kit-8, colony formation, Western blot, Transwell and wound healing assays were performed to estimate the malignant properties of HCC cells. The transcriptional factor of RNASEH2A was predicted by UCSC and JASPAR database and confirmed by dual luciferase assay and Ch-IP assay. The expression level of EMT pathway related molecules was determined by western blotting.

Results

An increased expression of RNASEH2A was presented in HCC and predicted worse prognosis of HCC patients. Functionally, the results demonstrated that depletion of RNASEH2A suppressed HCC cell proliferation, cell cycle, migration and invasion. Moreover, we illustrated that SP1 targeted to the promoter of RNASEH2A and modulated its expression in HCC cell lines. RNASEH2A knockdown counteracted the function of SP1 overexpression in modulating HCC cell growth, cell cycle, and mobility. Then, our data showed that the SP1/RNASEH2A axis affected the malignant behaviors of HCC cells by regulating EMT process.

Conclusions

In summary, these results demonstrated that RNASEH2A promoted HCC cells development through regulating EMT process and was transcriptionally modulated by SP1.

The downstream PPARγ target LRRC1 participates in early stage adipocytic differentiation

LRRC1 is a regulator of cellular polarity that is expressed at high levels in a range of tumor tissue types. Here, we conducted an analysis of the previously unexplored role of LRRC1 as a component of the adipogenic differentiation network. During the early stage (days 3-7) adipocytic differentiation of human mesenchymal stem cells (MSCs), LRRC1 was found to be upregulated at both the mRNA and protein levels. Moreover, the expression of LRRC1 was found to be controlled by PPARγ, which is a key transcriptional regulator of adipogenesis. Inhibiting LRRC1 expression reduced the adipogenic potential of hMSCs, with a concomitant reduction in the expression of three adipogenesis-associated proteins (SCD, LIPE, FASN). Together, these data offer new insight into the functional importance of LRRC1 both in general and in the context of adipocytic differentiation.

Diagnostic and Prognostic Profiling of Nucleocytoplasmic Shuttling Genes in Hepatocellular Carcinoma

One of the key features of eukaryotic cells is the separation of nuclear and cytoplasmic compartments by a double-layer nuclear envelope. This separation is crucial for timely regulation of gene expression, mRNA biogenesis, cell cycle, and differentiation. Since transcription takes place in the nucleus and the major part of translation in the cytoplasm, proper distribution of biomolecules between these two compartments is ensured by nucleocytoplasmic shuttling proteins - karyopherins. Karyopherins transport biomolecules through nuclear pores bidirectionally in collaboration with Ran GTPases and utilize GTP as the source of energy. Different karyopherins transport different cargo molecules that play important roles in the regulation of cell physiology. In cancer cells, this nucleocytoplasmic transport is significantly dysregulated to support increased demands for the import of cell cycle-promoting biomolecules and export of cell cycle inhibitors and mRNAs. Here, we analysed genomic, transcriptomic and proteomic data from published datasets to comprehensively profile karyopherin genes in hepatocellular carcinoma. We have found out that expression of multiple karyopherin genes is increased in hepatocellular carcinoma in comparison to the normal liver, with importin subunit α-1, exportin 2, importin subunit β-1 and importin 9 being the most over-expressed. More-over, we have found that increased expression of these genes is associated with higher neoplasm grade as well as significantly worse overall survival of liver cancer patients. Taken together, our bioinformatic data-mining analysis provides a comprehensive geno-mic and transcriptomic landscape of karyopherins in hepatocellular carcinoma and identifies potential members that could be targeted in order to develop new treatment regimens.

Systematic analysis of MCM3 in pediatric medulloblastoma via multi-omics analysis

Minichromosome maintenance proteins are DNA-dependent ATPases that bind to replication origins and allow a single round of DNA replication. One member of this family, MCM3, is reportedly active in most cancers. To systematically elucidate the mechanisms affected by aberrant MCM3 expression and evaluate its clinical significance, we analyzed multi-omics data from the GEO database and validated them in cell lines and tumor samples. First, we showed the upregulation of MCM3 in medulloblastoma (MB) at bulk and single-cell RNA sequence levels and revealed the potential role of MCM3 via DNA replication. Then we found the dysregulation of MCM3 might result from abnormal methylation of MCM3. Moreover, we discovered that MCM3 might affect varied biological processes such as apoptosis, autophagy, and ferroptosis and that MCM3 was correlated with immune components such as fibroblast and neutrophils, which were associated with overall survival in different medulloblastoma subtypes. Furthermore, we found that MCM3 expression was correlated with the IC₅₀ values of cisplatin and etoposide. The nomogram of MCM3-related genes showed the reliable and better prediction of 1- and 5-year survival compared to current histological and molecular classifications. Overall, the results of our study demonstrated that MCM3 might serve as a potential biomarker with clinical significance and better guidance than current histological and molecular classifications for clinical decision-making.

Ribonuclease H2 Subunit A Preserves Genomic Integrity and Promotes Prostate Cancer Progression

Homeostasis of genomic integrity should be regulated to promote proliferation and inhibit DNA damage-induced cell death in cancer. Ribonuclease H2 (RNase H2) maintains genome stability by controlling DNA:RNA hybrid and R-loop levels. Here, we identified that RNase H2 subunit A (RNASEH2A), a component of RNase H2, is highly expressed in castration-resistant prostate cancer (CRPC) tissues compared with localized prostate cancer. Interestingly, we showed that RNASEH2A suppressed R-loop levels to prevent cell apoptosis induced by DNA damage in prostate cancer cells. Both in vivo and in vitro studies revealed that RNASEH2A promotes cell growth and migration via the negative regulation of p53 and positive regulation of AR and AR-V7. Mechanistically, epigenetic regulation followed by R-loop accumulation in these promoters was observed for these gene regulations. Importantly, IHC analysis demonstrated that R-loop formation increased in CRPC tissues and correlated with RNASEH2A expression levels. Notably, two small molecules targeting RNase H2 activity were found to suppress CRPC tumor growth with no significant toxic effects. Collectively, we propose that RNASEH2A overexpression is a hallmark of prostate cancer progression by maintaining genomic stability to prevent R-loop-mediated apoptosis induction. Targeting RNase H2 activity could be a potential strategy for treating CRPC tumors.

Significance

RNASEH2A was demonstrated to be highly upregulated in aggressive prostate cancer to degrade R-loop accumulation and preserve genomic stability for tumor growth, suggesting that RNase H2 activity could be a promising therapeutic target.

Mechanism of Phellodendron and Anemarrhena Drug Pair on the Treatment of Liver Cancer Based on Network Pharmacology and Bioinformatics

Background

This study aims to explore the key targets and signaling pathways of the traditional Chinese medicine Phellodendron and Anemarrhena drug pair (PADP) for the treatment of liver cancer.

Methods

Firstly, bioinformatics technology was used to analyze GSE62232 gene chip to obtain the differential genes of liver cancer. A network pharmacology technology was used to find the active components of PADP and their targets. Secondly, the differential genes were imported into STRING database to draw a PPI network, and network topology structure map combined with Cytoscape software. And the R language was used to identify differential gene targets and pathways through GO and KEGG pathway enrichment analysis. In addition, AutoDock Vina was used for molecular docking of core targets and core compounds. Moreover, GEPIA online analysis tool was used to perform survival analysis of the core target genes. Finally, RT-PCR was used to verify the changes of key target genes. CCK−8 assay was performed to detect cell proliferation. Flow cytometry was performed to detect the cell cycle and apoptotic. Transwell invasion assay was performed to detect cell invasion.

Results

Firstly, a total of 21,654 genes were obtained. After screening, 1019 differential genes were obtained, including 614 down-regulated genes and 405 up-regulated genes. Furthermore, after screening by ADME standards, 52 active ingredients were obtained, of which 37 were Phellodendron and 15 were Anemarrhena. And a total of 36 differential genes have been identified, including 13 up-regulated genes and 23 down-regulated genes. Moreover, through enrichment analysis, we found that PADP may treat liver cancer through multiple channels and multiple pathways including the p53 signaling pathway, IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway and so on. Secondly, the molecular docking results showed that there was certain affinity between the core compounds and core target genes. In addition, GEPIA online analysis showed that ESR1, AR, CCNB1, CDK1, AKR1C3 and CCNA2 might become potential target genes for the survival and prognosis of PADP for the treatment of liver cancer. Finally, it was found that PADP could up regulate genes ESR1 and AR, down regulate genes CCNB1, CDK1, AKR1C3, and CCNA2. PADP could promote the apoptosis of liver cancer cells, shorten the cell cycle, and inhibit the proliferation and invasion of liver cancer cells.

Conclusion

PADP may treat liver cancer through multiple targets, multiple channels, and multiple pathways, thereby suppressing cancer cells and improving the living quality of patients.

Long non-coding RNA HAGLROS facilitates tumorigenesis and progression in hepatocellular carcinoma by sponging miR-26b-5p to up-regulate karyopherin α2 (KPNA2) and inactivate p53 signaling

Hepatocellular carcinoma (HCC) is a principal histologic type of liver cancer with high mortality. Long non-coding RNAs (LncRNAs) exert a crucial role in the pathogenesis of human tumors. To date, the functions and mechanisms of lncRNA HAGLROS in HCC are rarely reported. In the current study, HAGLROS exhibited a higher level in HCC tissues and cells. HAGLROS expression was positively correlated with tumor size, TNM stage and poor clinical prognosis. Loss-of-function experiments showed that knockdown of HAGLROS significantly lowered cell proliferation, cell cycle progression, migration, invasion and epithelial to mesenchymal transition (EMT) but induced apoptosis in vitro. Consistently, tumor growth in the nude mice was effectively slowed by the depletion of HAGLROS. Mechanistically, HAGLROS could competitively bind to miR-26b-5p to prevent the suppression of miR-26b-5p on its downstream target gene Karyopherin α2 (KPNA2). Moreover, the inhibitory effects of HAGLROS knockdown on cell malignant behaviors were reversed due to the miR-26b-5p down-regulation or KPNA2 overexpression. It was interesting to note that HAGLROS inactivated p53 signaling through targeting miR-26b-5p/KPNA2. In conclusion, our results demonstrated that HAGLROS contributed to the malignant progression of HCC via serving as a sponge for miR-26b-5p to facilitate KPNA2 expression and inactivate p53 signaling. Targeting HAGLROS/miR-26b-5p/KPNA2 axis might be an alternative therapeutic strategy for HCC patients.

Identification of Differentially Expressed Genes Associated with the Prognosis and Diagnosis of Hepatocellular Carcinoma by Integrated Bioinformatics Analysis

OBJECTIVE

The goal of this study was to understand the possible core genes associated with hepatocellular carcinoma (HCC) pathogenesis and prognosis.

METHODS

GEO contains datasets of gene expression, miRNA, and methylation patterns of diseased and healthy/control patients. The GSE62232 dataset was selected by employing the server Gene Expression Omnibus. A total of 91 samples were collected, including 81 HCC and 10 healthy samples as control. GSE62232 was analysed through GEO2R, and Functional Enrichment Analysis was performed to extract rational information from a set of DEGs. The Protein-Protein Relationship Networking search method has been used for extracting the interacting genes. MCC method was used to calculate the top 10 genes according to their importance. Hub genes in the network were analysed using GEPIA to estimate the effect of their differential expression on cancer progression.

RESULTS

We identified the top 10 hub genes through CytoHubba plugin. These included BUB1, BUB1B, CCNB1, CCNA2, CCNB2, CDC20, CDK1 and MAD2L1, NCAPG, and NDC80. NCAPG and NDC80 reported for the first time in this study while the remaining from a recently reported literature. The pathogenesis of HCC may be directly linked with the aforementioned genes. In this analysis, we found critical genes for HCC that showed recommendations for future prognostic and predictive biomarkers studies that could promote selective molecular therapy for HCC.

The role of CpG island methylator phenotype in the clinical course of hepatocellular carcinoma

MOTIVATION

Aberrant DNA methylation is strongly associated with heterogeneity in tumors. This study investigated the prognostic value of CpG island methylator phenotype in hepatocellular carcinoma (HCC).

RESULTS

A total of 319 HCC samples with 21 121 CpG sites were included in this study and 215 disease-free survival (DFS) and overall survival (OS)-related CpG sites were identified. These CpG sites were divided into seven clusters by using consensus clustering method. Cluster 4, which constructed the prognostic prediction model as the seed cluster to evaluate survival risk for DFS and OS of HCC patients, had the lowest methylation level with the worse prognosis. The low-risk group patients had a significantly prolonged DFS and OS than the patients in the high-risk group (P = 0.008 and P < 0.001, respectively). A receiver operating characteristic curve results for predicting DFS and OS were 0.691 and 0.695, respectively. These results suggested that the CpG site methylation appears to be an informative prognostic biomarker in HCC. The CpG site methylation-related prognostic model may be an innovative insight to evaluate clinical outcomes for HCC patients.

AVAILABILITY AND IMPLEMENTATION

The code of the analysis is available at https://www.bioconductor.org.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Construction of a ceRNA Network and Analysis of Tumor Immune Infiltration in Pancreatic Adenocarcinoma

Pancreatic adenocarcinoma (PAAD) is characterized by high malignancy, frequent metastasis, and recurrence with an unfavorable prognosis. This study is aimed at constructing a prognostic model for tumor-infiltrating immune cells and a competing endogenous RNA (ceRNA) network in PAAD and analyzing susceptibilities of chemotherapy and immunotherapy of PAAD. Gene expression profiles and clinical information of PAAD were downloaded from The Cancer Genome Atlas (TCGA) database and divided into the tumor group and the normal group. A total of five PAAD survival-related key genes in the ceRNA network and three survival-related immune infiltrating cells were uncovered, and two survival risk models and nomograms were constructed. The efficiency and performance of the two models were verified using multi-index area under the curve analysis at different time points, decision curve analysis, and calibration curves. Co-expression analysis showed that LRRC1, MIR600HG, and RNF166 in the ceRNA network and tumor-infiltrating immune cells including CD8 T cells and M1 macrophages were likely related to the PAAD prognosis, and the expression of key ceRNA-related genes was experimently validated in tissues and cell lines by RT-qPCR. Patients with low risk scores for key genes in the ceRNA network displayed a positive response to anti-programmed death-1 (PD-1) treatment and greater sensitivity to chemotherapeutic drugs such as docetaxel, lapatinib, and paclitaxel. More importantly, our results suggested that the IC50 values of gemcitabine in PAAD were not significantly different between the high and low risk groups. The expression levels of immune checkpoints were significantly different in the high-risk and low-risk groups. The prognostic model, nomogram, and drug analysis may provide an essential reference for PAAD patient management in the clinic.

Identification of Five Hub Genes as Key Prognostic Biomarkers in Liver Cancer via Integrated Bioinformatics Analysis

Liver cancer is one of the most common cancers and the top leading cause of cancer death globally. However, the molecular mechanisms of liver tumorigenesis and progression remain unclear. In the current study, we investigated the hub genes and the potential molecular pathways through which these genes contribute to liver cancer onset and development. The weighted gene co-expression network analysis (WCGNA) was performed on the main data attained from the GEO (Gene Expression Omnibus) database. The Cancer Genome Atlas (TCGA) dataset was used to evaluate the association between prognosis and these hub genes. The expression of genes from the black module was found to be significantly related to liver cancer. Based on the results of protein-protein interaction, gene co-expression network, and survival analyses, DNA topoisomerase II alpha (TOP2A), ribonucleotide reductase regulatory subunit M2 (RRM2), never in mitosis-related kinase 2 (NEK2), cyclin-dependent kinase 1 (CDK1), and cyclin B1 (CCNB1) were identified as the hub genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses showed that the differentially expressed genes (DEGs) were enriched in the immune-associated pathways. These hub genes were further screened and validated using statistical and functional analyses. Additionally, the TOP2A, RRM2, NEK2, CDK1, and CCNB1 proteins were overexpressed in tumor liver tissues as compared to normal liver tissues according to the Human Protein Atlas database and previous studies. Our results suggest the potential use of TOP2A, RRM2,&nbsp;NEK2, CDK1, and CCNB1 as prognostic biomarkers in liver cancer.

Clinical Value and Underlying Mechanisms of Upregulated LINC00485 in Hepatocellular Carcinoma

Aims

This study aimed to reveal the functional role of LINC00485 in hepatocellular carcinoma (HCC).

Materials & Methods

210 serum samples from Zhongnan Hospital of Wuhan University were employed to evaluate clinical value of LINC00485. Bioinformatics analysis was adopted to explore its potential mechanisms.

Results

LINC00485 was confirmed to be upregulated in HCC tissues and serum samples. Survival analysis and receiver operating characteristic curve revealed its prognostic and diagnostic roles. The combination of serum LINC00485 with AFP can remarkably improve diagnostic ability of HCC. Exploration of the underlying mechanism demonstrated that LINC00485 might exert pro-oncogenic activity by LINC00485—three miRNAs—four mRNAs network.

Conclusions

Our study unveiled that upregulated LINC00485 could act as a potential diagnostic and prognostic biomarker and provide a novel insight into the molecular mechanisms of LINC00485 in HCC pathogenesis.

Hypoxia-induced RNASEH2A limits activation of cGAS-STING signaling in HCC and predicts poor prognosis

BACKGROUND

Hypoxia is a hallmark of solid cancers, including hepatocellular carcinoma (HCC). There is scarce information about how hypoxia avoids immunologic stress and maintains a cancer-promoting microenvironment.

METHODS

The Cancer Genome Atlas, RNA-seq data, and Oncomine database were used to discover the correlation of RNASEH2A with tumor progression; then expression of RNASEH2A mRNA and protein were detected in HCC tissues and cells subjected to hypoxia or with the treatment of CoCl₂ via real-time quantitative polymerase chain reaction and immunochemistry assays. Finally, the effect of RNASEH2A on cell proliferation and the involved signaling pathway was explored further.

RESULTS

RNASEH2A was positively correlated with tumor grade, size, vascular invasion, and poor prognosis. The expression of RNASEH2A mRNA and protein were increased and dependent on hypoxia-inducible factor 2α in HCC tissues and cell lines. Knockout of RNASEH2A in HCC cells greatly reduced cell proliferation and induced the transcription of multiple cGAS-STING (cyclic GMP-AMP synthase-stimulator of interferon genes) targeted type 1 interferon-related genes, including IFIT1, USP18, and CXCL10, which suggests knockout of RNASEH2A may produce immunologic stress and tumor suppressive effects.

CONCLUSIONS

RNASEH2A plays a critical role and potentially predicts patient outcomes in HCC, which uncovers a new mechanism that RNASEH2A contributes to limit immunologic stress of cancer cells in the context of hypoxia.

Increased expression of KPNA2 predicts unfavorable prognosis in ovarian cancer patients, possibly by targeting KIF4A signaling

Background

Karyopherin α-2 (KPNA2) is a member of karyopherin family, which is proved to be responsible for the import or export of cargo proteins. Studies have determined that KPNA2 is associated with the development and prognosis of various cancers, yet the role of KPNA2 in ovarian carcinoma and its potential molecular mechanisms remains unclear.

Materials and methods

The expression and prognosis of KPNA2 in ovarian cancer was investigated using GEPIA and Oncomine analyses. Mutations of KPNA2 in ovarian cancer were analyzed by cBioPortal database. The prognostic value of KPNA2 expression was evaluated by our own ovarian carcinoma samples using RT-qPCR. Subsequently, the cell growth, migration and invasion of ovarian cancer cells were investigated by CCK-8 and transwell assay, respectively. The protein levels of KPNA2 and KIF4A were determined by western blot.

Results

We obtained the following important results. (1) KPNA2 and KIF4A wereoverexpressed in ovairan cancer tissues and cells. (2) Among patients with ovarian cancer, overexpressed KPNA2 was associated with lower survival rate. (3) Mutations (R197* and S140F) in KPNA2 will have some influences on protein structure, and then may cause protein function abnormal. (4) KPNA2 konckdown inhibited proliferation, migration, invasion, as well as the expression of KIF4A.

Conclusion

KPNA2, as a tumorigenic gene in ovarian cancer, accelerated tumor progression by up-regulating KIF4A, suggesting that KPNA2 might be a hopeful indicator of treatment and poor prognosis.

A gene module identification algorithm and its applications to identify gene modules and key genes of hepatocellular carcinoma

To further improve the effect of gene modules identification, combining the Newman algorithm in community detection and K-means algorithm framework, a new method of gene module identification, GCNA-Kpca algorithm, was proposed. The core idea of the algorithm was to build a gene co-expression network (GCN) based on gene expression data firstly; Then the Newman algorithm was used to initially identify gene modules based on the topology of GCN, and the number of clusters and clustering centers were determined; Finally the number of clusters and clustering centers were input into the K-means algorithm framework, and the secondary clustering was performed based on the gene expression profile to obtain the final gene modules. The algorithm took into account the role of modularity in the clustering process, and could find the optimal membership module for each gene through multiple iterations. Experimental results showed that the algorithm proposed in this paper had the best performance in error rate, biological significance and CNN classification indicators (Precision, Recall and F-score). The gene module obtained by GCNA-Kpca was used for the task of key gene identification, and these key genes had the highest prognostic significance. Moreover, GCNA-Kpca algorithm was used to identify 10 key genes in hepatocellular carcinoma (HCC): CDC20, CCNB1, EIF4A3, H2AFX, NOP56, RFC4, NOP58, AURKA, PCNA, and FEN1. According to the validation, it was reasonable to speculate that these 10 key genes could be biomarkers for HCC. And NOP56 and NOP58 are key genes for HCC that we discovered for the first time.

DNA methylation patterns-based subtype distinction and identification of soft tissue sarcoma prognosis

Soft tissue sarcomas (STSs) are heterogeneous at the clinical with a variable tendency of aggressive behavior. In this study, we constructed a specific DNA methylation-based classification to identify the distinct prognosis-subtypes of STSs based on the DNA methylation spectrum from the TCGA database. Eventually, samples were clustered into 4 subgroups, and their survival curves were distinct from each other. Meanwhile, the samples in each subgroup reflected differentially in several clinical features. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was also conducted on the genes of the corresponding promoter regions of the above-described specific methylation sites, revealing that these genes were mainly concentrated in certain cancer-associated biological functions and pathways. In addition, we calculated the differences among clustered methylation sites and performed the specific methylation sites with LASSO algorithm. The selection operator algorithm was employed to derive a risk signature model, and a prognostic signature based on these methylation sites performed well for risk stratification in STSs patients. At last, a nomogram consisted of clinical features and risk score was developed for the survival prediction. This study declares that DNA methylation-based STSs subtype classification is highly relevant for future development of personalized therapy as it identifies the prediction value of patient prognosis.

Identification of hub genes and biological pathways in hepatocellular carcinoma by integrated bioinformatics analysis

Background

Hepatocellular carcinoma (HCC), the main type of liver cancer in human, is one of the most prevalent and deadly malignancies in the world. The present study aimed to identify hub genes and key biological pathways by integrated bioinformatics analysis.

Methods

A bioinformatics pipeline based on gene co-expression network (GCN) analysis was built to analyze the gene expression profile of HCC. Firstly, differentially expressed genes (DEGs) were identified and a GCN was constructed with Pearson correlation analysis. Then, the gene modules were identified with 3 different community detection algorithms, and the correlation analysis between gene modules and clinical indicators was performed. Moreover, we used the Search Tool for the Retrieval of Interacting Genes (STRING) database to construct a protein protein interaction (PPI) network of the key gene module, and we identified the hub genes using nine topology analysis algorithms based on this PPI network. Further, we used the Oncomine analysis, survival analysis, GEO data set and random forest algorithm to verify the important roles of hub genes in HCC. Lastly, we explored the methylation changes of hub genes using another GEO data (GSE73003).

Results

Firstly, among the expression profiles, 4,130 up-regulated genes and 471 down-regulated genes were identified. Next, the multi-level algorithm which had the highest modularity divided the GCN into nine gene modules. Also, a key gene module (m1) was identified. The biological processes of GO enrichment of m1 mainly included the processes of mitosis and meiosis and the functions of catalytic and exodeoxyribonuclease activity. Besides, these genes were enriched in the cell cycle and mitotic pathway. Furthermore, we identified 11 hub genes, MCM3, TRMT6, AURKA, CDC20, TOP2A, ECT2, TK1, MCM2, FEN1, NCAPD2 and KPNA2 which played key roles in HCC. The results of multiple verification methods indicated that the 11 hub genes had highly diagnostic efficiencies to distinguish tumors from normal tissues. Lastly, the methylation changes of gene CDC20, TOP2A, TK1, FEN1 in HCC samples had statistical significance (P-value < 0.05).

Conclusion

MCM3, TRMT6, AURKA, CDC20, TOP2A, ECT2, TK1, MCM2, FEN1, NCAPD2 and KPNA2 could be potential biomarkers or therapeutic targets for HCC. Meanwhile, the metabolic pathway, the cell cycle and mitotic pathway might played vital roles in the progression of HCC.

An aberrant DNA methylation signature for predicting hepatocellular carcinoma

Background

By the time they are clinically diagnosed, patients with hepatocellular carcinoma (HCC) are often at the advanced stage. DNA methylation has become a useful predictor of prognosis for cancer patients. Research on DNA methylation as a biomarker for assessing the risk of occurrence in HCC patients is limited. The purpose of this study was to develop an efficient methylation site model for predicting survival in patients with HCC.

Methods

DNA methylation and gene expression profile data were extracted from The Cancer Genome Atlas (TCGA) database. Markers of DNA-methylated site in two subsets (the training subset and the test subset) were identified using a random survival forest algorithm and Cox proportional hazards regression. Then, Gene Ontology annotations were applied to investigate the functions of DNA methylation signatures.

Results

A total of 37 hub genes containing 713 methylated sites were identified among the differentially methylated genes (DMGs) and differentially expressed genes (DEGs). Finally, seven methylation sites (cg12824782, cg24871714, cg18683774, cg22796509, cg19450025, cg10474350, and cg06511917) were identified. In the training group and the test group, the area under the curve predicting the survival of patients with HCC was 0.750 and 0.742, respectively. The seven methylation sites signature could be used to divide the patients in the training group into high- and low-risk subgroups [overall survival (OS): 2.81 vs. 2.11 years; log-rank test, P<0.05]. Then, the prediction ability of the model was validated in the test dataset through risk stratification (OS: 2.04 vs. 2.88 years; log-rank test, P<0.05). Functional analysis demonstrated that these signature genes were related to the activity of DNA-binding transcription activator, RNA polymerase II distal enhancer sequence-specific DNA binding, and enhancer sequence-specific DNA binding.

Conclusions

The results of this study showed that the signature is useful for predicting the survival of HCC patients and thus, can facilitate treatment-related decision-making.

KPNA2-Associated Immune Analyses Highlight the Dysregulation and Prognostic Effects of GRB2, NRAS, and Their RNA-Binding Proteins in Hepatocellular Carcinoma

Karyopherin α2 (KPNA2) was reported to be overexpressed and have unfavorable prognostic effects in many malignancies including hepatocellular carcinoma (HCC). Although its contributions to inflammatory response were reported in many studies, its specific associations with immune infiltrations and immune pathways during cancer progression were unclear. Here, we aimed to identify new markers for HCC diagnosis and prognosis through KPNA2-associated immune analyses. RNA-seq expression data of HCC datasets were downloaded from The Cancer Genome Atlas and International Cancer Genome Consortium. The gene expressions were counts per million normalized. The infiltrations of 24 kinds of immune cells in the samples were evaluated with ImmuCellAI (Immune Cell Abundance Identifier). The Spearman correlations of the immune infiltrations with KPNA2 expression were investigated, and the specific positive correlation of B-cell infiltration with KPNA2 expression in HCC tumors was identified. Fifteen genes in KEGG (Kyoto Encyclopedia of Genes and Genomes) B-cell receptor signaling pathway presented significant correlations with KPNA2 expression in HCC. Among them, GRB2 and NRAS were indicated to be independent unfavorable prognostic factors for HCC overall survival. Clinical Proteomic Tumor Analysis Consortium HCC dataset was investigated to validate the results at protein level. The upregulation and unfavorable prognostic effects of KPNA2 and GRB2 were confirmed, whereas, unlike its mRNA form, NRAS protein was presented to be downregulated and have favorable prognostic effects. Through receiver operating characteristic curve analysis, the diagnostic potential of the three proteins was shown. The RNA-binding proteins (RBPs) of KPNA2, NRAS, and GRB2, downloaded via The Encyclopedia of RNA Interactomes, were investigated for their clinical significance in HCC at protein level. An eight-RBP signature with independent prognostic value and dysregulations in HCC was identified. All the RBPs were significantly correlated with MKI67 expression and at least one of KPNA2, GRB2, and NRAS at protein level in HCC, indicating their roles in HCC progression and the regulation of the three proteins. We concluded that KPNA2, GRB2, NRAS, and their RBPs might have coordinating roles in HCC immunoregulation and progression. They might be new markers for HCC diagnosis and prognosis predication and new targets for HCC immunotherapy.

Analyses of DNA Methylation Involved in the Activation of Nuclear Karyopherin Alpha 2 Leading to Identify the Progression and Prognostic Significance Across Human Breast Cancer

Background

Karyopherin alpha 2 (KPNA2) is a nuclear import factor that plays a crucial role in nucleocytoplasmic transport, as well as cell proliferation, migration, and invasion in several cancers. However, the roles of KPNA2 in breast cancer as well as the underlying molecular mechanisms have not been elucidated.

Materials and Methods

To evaluate gene expression alterations during breast carcinogenesis, KPNA2 expression was analyzed using the Gene Expression Profiling Interactive Analysis and Oncomine analyses. The correlation between methylation and expression was analyzed using the MEXPRESS tool, UALCAN cancer database, and cBioPortal browser. Then, the expression and prognostic value of KPNA2 were investigated by our own breast cancer samples using RT-PCR. KPNA2 methylation level was detected by methylation-specific PCR.

Results

We obtained the following important results. (1) KPNA2 expression was significantly higher in breast cancer than normal samples and regulated by aberrant DNA hypomethylation of promoter region. (2) Among patients with breast cancer, those with higher KPNA2 expression had a lower survival rate. (3) The major mutation type of KPNA2 in breast cancer samples was missense mutation. (4) Homer1 was able to promote breast cancer progression may be through upregulating TPX2 expression.

Conclusion

Our findings suggest that aberrant DNA hypomethylation of promoter regions contributes to the aberrant expression of KPNA2 in breast cancer, which might be a potential indicator of poor prognosis.

Telomere attrition and dysfunction: a potential trigger of the progeroid phenotype in nijmegen breakage syndrome

Background: Nibrin, as part of the NBN/MRE11/RAD50 complex, is mutated in Nijmegen breakage syndrome (NBS), which leads to impaired DNA damage response and lymphoid malignancy.

Results: Telomere length (TL) was markedly reduced in homozygous patients (and comparably so in all chromosomes) by ~40% (qPCR) and was slightly reduced in NBS heterozygotes older than 30 years (~25% in qPCR), in accordance with the respective cancer rates. Humanized cancer-free NBS mice had normal TL. Telomere elongation was inducible by telomerase and/or alternative telomere lengthening but was associated with abnormal expression of telomeric genes involved in aging and/or cell growth. Lymphoblastoid cells from NBS patients with long survival times (>12 years) displayed the shortest telomeres and low caspase 7 activity.

Conclusions: NBS is a secondary telomeropathy. The two-edged sword of telomere attrition enhances the cancer-prone situation in NBS but can also lead to a relatively stable cellular phenotype in tumor survivors. Results suggest a modular model for progeroid syndromes with abnormal expression of telomeric genes as a molecular basis.

Methods: We studied TL and function in 38 homozygous individuals, 27 heterozygotes, one homozygous fetus, six NBS lymphoblastoid cell lines, and humanized NBS mice, all with the same founder NBN mutation: c.657_661del5.

The Scribble family in cancer: twentieth anniversary

Among the more than 160 PDZ containing proteins described in humans, the cytoplasmic scaffold Scribble stands out because of its essential role in many steps of cancer development and dissemination. Its fame has somehow blurred the importance of homologous proteins, Erbin and Lano, all belonging to the LRR and PDZ (LAP) protein family first described twenty years ago. In this review, we will retrace the history of LAP family protein research and draw attention to their contribution in cancer by detailing the features of its members at the structural and functional levels, and highlighting their shared-but also different-implication in the tumoral process.