Distinct Diagnostic and Prognostic Values of Minichromosome Maintenance Gene Expression in Patients with Hepatocellular Carcinoma

Investigating the Mechanisms of Anti-tumoral Effect of Combination Therapy of Calcitriol and Sodium Pentaborate Pentahydrate on HepG2 Hepatocellular Carcinoma Cells

Hepatocellular carcinoma (HCC) is one of the most common primary liver cancers worldwide and is often associated with poor prognosis due to drug resistance. Combination therapies demonstrate superior efficacy at lower drug dosages on cancer cells compared to single treatments, resulting in less drug resistance in the cells. This study investigates the synergistic anti-tumoral effects of calcitriol, the biologically active form of vitamin D, and sodium pentaborate pentahydrate (NaB) on HepG2 cells. We examined the cell viability of NaB, calcitriol, or the combination of NaB and calcitriol on HepG2 cells and healthy human hepatic stellate cells (HHSC) using MTS. Our findings showed that combination therapy with 3.3 mM NaB and 1 µM calcitriol has a synergistic effect and a more cytotoxic effect on HepG2 cells. This combination significantly increased apoptosis and ROS levels compared to treatment alone with NaB or calcitriol. Gene expression and proteomics analysis revealed inhibition of DNA replication and the cell cycle process, further confirming the potent anti-proliferative effects of the combination therapy. When HepG2 cells were treated with a combination of 3.3 mM NaB and 1 µM calcitriol, mRNA levels of apoptosis-related genes AKT1 and MDM2 were downregulated, while p53 was upregulated. Additionally, cell cycle-related genes CDKN1A, GADD45A, and p27 were upregulated, whereas MCM2, MCM5, and MCM7 were downregulated. Furthermore, genes associated with the vitamin D receptor (VDR), including VDR and CYP24A1, were upregulated, while CYP27B1 was downregulated. Our proteomic analysis revealed decreased MCM2 and MCM5 protein expressions which was confirmed by western blotting. In conclusion, this study highlights the potential of NaB and calcitriol as a promising therapeutic strategy for HCC.

RNA Sequencing and Bioinformatics Analysis Reveals the Downregulation of DNA Replication Genes by Morindone in Colorectal Cancer Cells

Morindone, a natural anthraquinone compound, has been reported to have significant pharmacological properties in different cancers. However, its anticancer effects in colorectal cancer (CRC) and the underlying molecular mechanisms remain obscure. In this study, RNA sequencing was used to assess the differentially expressed genes (DEGs) following morindone treatment in two CRC cell lines, HCT116 and HT29 cells. Functional enrichment analysis of overlapping DEGs revealed that negative regulation of cell development from biological processes and the MAPK signalling pathway were the most significant Gene Ontology terms and Kyoto Encyclopaedia of Genes and Genome pathway, respectively. Seven hub genes were identified among the overlapping genes, including MCM5, MCM6, MCM10, GINS2, POLE2, PRIM1, and WDHD1. All hub genes were found downregulated and involved in DNA replication fork. Among these, GINS2 was identified as the most cancer-dependent gene in both cells with better survival outcomes. Validation was performed on seven hub genes with rt-qPCR, and the results were consistent with the RNA sequencing findings. Collectively, this study provides corroboration of the potential therapeutic benefits and suitable pharmacological targets of morindone in the treatment of CRC.

Regulation of cancer stem cells by CXCL1, a chemokine whose secretion is controlled by MCM2

BACKGROUND

A high expression pattern of minichromosome maintenance 2 (MCM2) has been observed in various cancers. MCM2 is a protein involved in the cell cycle and plays a role in cancer growth and differentiation by binding to six members of the MCM subfamily. The MCM protein family includes MCM2 through MCM7.

METHODS

MCM2 has shown high expression in both lung cancer stem cells (LCSCs) and glioma stem cells (GSCs). We investigated the characteristics of CSCs and the regulation of the epithelial-to-mesenchymal transition (EMT) phenomenon in LCSCs and GSCs by MCM2. Additionally, we explored secreted factors regulated by MCM2.

RESULTS

There was a significant difference in survival rates between lung cancer patients and brain cancer patients based on MCM2 expression. MCM2 was found to regulate both markers and regulatory proteins in LCSCs. Moreover, MCM2 is thought to be involved in cancer metastasis by regulating cell migration and invasion, not limited to lung cancer but also identified in glioma. Among chemokines, chemokine (C-X-C motif) ligand 1 (CXCL1) was found to be regulated by MCM2.

CONCLUSIONS

MCM2 not only participates in the cell cycle but also affects cancer cell growth by regulating the external microenvironment to create a favorable environment for cells. MCM2 is highly expressed in malignant carcinomas, including CSCs, and contributes to the malignancy of various cancers. Therefore, MCM2 may represent a crucial target for cancer therapeutics.

Identification and validation of candidate clinical signatures of apolipoprotein L isoforms in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a lethal malignancy worldwide with an increasing number of new cases each year. Apolipoprotein (APOL) isoforms have been explored for their associations with HCC.The GSE14520 cohort was used for training data; The Cancer Genome Atlas (TCGA) database was used for validated data. Diagnostic, prognostic significance and mechanisms were explored using these cohorts. Risk score models and nomograms were constructed using prognosis-related isoforms and clinical factors for survival prediction. Oncomine and HCCDB databases were further used for validation of diagnostic, prognostic significance. APOL1, 3, and 6 were differentially expressed in two cohorts (all P ≤ 0.05). APOL1 and APOL6 had diagnostic capacity whereas APOL3 and APOL6 had prognostic capacity in two cohorts (areas under curves [AUCs] > 0.7, P ≤ 0.05). Mechanism studies demonstrated that APOL3 and APOL6 might be involved in humoral chemokine signaling pathways (all P ≤ 0.05). Risk score models and nomograms were constructed and validated for survival prediction of HCC. Moreover, diagnostic values of APOL1 and weak APOL6 were validated in Oncomine database (AUC > 0.700, 0.694); prognostic values of APOL3 and APOL6 were validated in HCCDB database (all P < 0.05). Differentially expressed APOL1 and APOL6 might be diagnostic biomarkers; APOL3 and APOL6 might be prognostic biomarkers of RFS and OS for HCC via chemokine signaling pathways.

DNA replication: Mechanisms and therapeutic interventions for diseases

Accurate and integral cellular DNA replication is modulated by multiple replication-associated proteins, which is fundamental to preserve genome stability. Furthermore, replication proteins cooperate with multiple DNA damage factors to deal with replication stress through mechanisms beyond their role in replication. Cancer cells with chronic replication stress exhibit aberrant DNA replication and DNA damage response, providing an exploitable therapeutic target in tumors. Numerous evidence has indicated that posttranslational modifications (PTMs) of replication proteins present distinct functions in DNA replication and respond to replication stress. In addition, abundant replication proteins are involved in tumorigenesis and development, which act as diagnostic and prognostic biomarkers in some tumors, implying these proteins act as therapeutic targets in clinical. Replication-target cancer therapy emerges as the times require. In this context, we outline the current investigation of the DNA replication mechanism, and simultaneously enumerate the aberrant expression of replication proteins as hallmark for various diseases, revealing their therapeutic potential for target therapy. Meanwhile, we also discuss current observations that the novel PTM of replication proteins in response to replication stress, which seems to be a promising strategy to eliminate diseases.

Construction and validation of prognostic signature for hepatocellular carcinoma basing on hepatitis B virus related specific genes

BACKGROUND

Hepatocellular carcinoma (HCC) is a frequent primary liver cancer, and it is one of the leading cause of cancer-related deaths. Hepatitis B virus (HBV) infection is a crucial risk factor for HCC. Thus, this study aimed to explore the prognostic role of HBV-positive HCC related specific genes in HCC.

METHODS

The HCC related data were downloaded from three databases, including The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO). Univariate Cox regression analysis and LASSO Cox regression analysis were conducted to build the Risk score. Multivariate Cox regression analysis and survival analysis determined the independent prognostic indicators.

RESULTS

After cross analysis of differentially expressed genes (DEGs), we have identified 106 overlapped DEGs, which were probably HBV-positive HCC related specific genes. These 106 DEGs were significantly enriched in 213 GO terms and 8 KEGG pathways. Among that, 11 optimal genes were selected to build a Risk score, and Risk score was an independent prognostic factor for HCC. High risk HCC patients had worse OS. Moreover, five kinds of immune cells were differentially infiltrated between high and low risk HCC patients.

CONCLUSION

The prognostic signature, based on HMMR, MCM6, TPX2, KIF20A, CCL20, RGS2, NUSAP1, FABP5, FZD6, PBK, and STK39, is conducive to distinguish different prognosis of HCC patients.

MCM4 is a novel prognostic biomarker and promotes cancer cell growth in glioma

BACKGROUND

Gliomas account for 75% of all primary malignant brain tumors in adults and result in high mortality. Accumulated evidence has declared the minichromosome maintenance protein complex (MCM) gene family plays a critical role in modulating the cell cycle and DNA replication stress. However, the biological function and clinic characterization of nine MCM members in low-grade glioma are not yet clarified.

METHODS

In this study, we utilized diverse public databases, including The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Rembrandt, Human Protein Atlas (HPA), Linkedomics, cbioportal, Tumor and Immune System Interaction Database (TISIDB), single-sample GSEA (ssGSEA), Tumor Immune Estimation Resource (TIMER), Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Therapeutics Response Portal databases to explore the mRNA and protein expression profiles, gene mutation, clinical features, diagnosis, prognosis, signaling pathway, tumor mutational burden (TMB), immune subtype, immune cell infiltration, immune modulator and drug sensitivity of nine MCMs. Afterward, qRT-PCR was utilized to detect the expression of the MCM family in glioblastoma multiforme (GBM) cell lines. The one-, three-, or five-year survival rate was predicted by utilizing a nomogram established by cox proportional hazard regression.

RESULTS

In this study, we found that nine MCMs were consistently up-regulated in glioma tissues and glioma cell lines. Elevated nine MCMs expressions were significantly correlated with a higher tumor stage, isocitrate dehydrogenase (IDH) mutates, 1p/19q codeletion, histological type, and primary therapy outcome. Survival analyses showed that higher expression of MCM2-MCM8 (minichromosome maintenance protein2-8) and MCM10 (minichromosome maintenance protein 10) were linked with poor overall survival (OS) and progression-free survival (PFS) in glioma patients. On the other hand, up-regulated MCM2-MCM8 and MCM10 were significantly associated with shorter disease-specific survival (DSS) in glioma patients. Univariate and multivariate analyses revealed that MCM2 (minichromosome maintenance protein2), MCM4 (minichromosome maintenance protein 4), MCM6 (minichromosome maintenance protein 6), MCM7 (minichromosome maintenance protein 7) expression and tumor grade, 1p/19q codeletion, age, and primary therapy outcome were independent factors correlated with the clinical outcome of glioma patients. More importantly, a prognostic MCMs model constructed using the above five prognostic genes could predict the overall survival of glioma patients with medium-to-high accuracy. Furthermore, functional enrichment analysis indicated that MCMs principal participated in regulating cell cycle and DNA replication. DNA copy number variation (CNV) and DNA methylation significantly affect the expression of MCMs. Finally, we uncover that MCMs expression is highly correlated with immune cell infiltration, immune modulator, TMB, and drug sensitivity.

CONCLUSIONS

In summary, this finding confirmed that MCM4 is a potential target of precision therapy for patients with glioma.

Dissecting novel mechanisms of hepatitis B virus related hepatocellular carcinoma using meta-analysis of public data

BACKGROUND

Hepatitis B virus (HBV) is a cause of hepatocellular carcinoma (HCC). Interestingly, this process is not necessarily mediated through cirrhosis and may in fact involve oncogenic processes. Prior studies have suggested specific oncogenic gene expression pathways were affected by viral regulatory proteins. Thus, identifying these genes and associated pathways could highlight predictive factors for HCC transformation and has implications in early diagnosis and treatment.

AIM

To elucidate HBV oncogenesis in HCC and identify potential therapeutic targets.

METHODS

We employed our Search, Tag, Analyze, Resource platform to conduct a meta-analysis of public data from National Center for Biotechnology Information’s Gene Expression Omnibus. We performed meta-analysis consisting of 155 tumor samples compared against 185 adjacent non-tumor samples and analyzed results with ingenuity pathway analysis.

RESULTS

Our analysis revealed liver X receptors/retinoid X receptor (RXR) activation and farnesoid X receptor/RXR activation as top canonical pathways amongst others. Top upstream regulators identified included the Ras family gene rab-like protein 6 (RABL6). The role of RABL6 in oncogenesis is beginning to unfold but its specific role in HBV-related HCC remains undefined. Our causal analysis suggests RABL6 mediates pathogenesis of HBV-related HCC through promotion of genes related to cell division, epigenetic regulation, and Akt signaling. We conducted survival analysis that demonstrated increased mortality with higher RABL6 expression. Additionally, homeobox A10 (HOXA10) was a top upstream regulator and was strongly upregulated in our analysis. HOXA10 has recently been demonstrated to contribute to HCC pathogenesis in vitro. Our causal analysis suggests an in vivo role through downregulation of tumor suppressors and other mechanisms.

CONCLUSION

This meta-analysis describes possible roles of RABL6 and HOXA10 in the pathogenesis of HBV-related HCC. RABL6 and HOXA10 represent potential therapeutic targets and warrant further investigation.

Development and Validation of a Prognostic Classifier Based on Lipid Metabolism-Related Genes for Breast Cancer

Background

The changes of lipid metabolism have been implicated in the development of many tumors, but its role in breast invasive carcinoma (BRCA) remains to be fully established. Here, we attempted to ascertain the prognostic value of lipid metabolism-related genes in BRCA.

Methods

We obtained RNA expression data and clinical information for BRCA and normal samples from public databases and downloaded a lipid metabolism-related gene set. Ingenuity Pathway Analysis (IPA) was applied to identify the potential pathways and functions of Differentially Expressed Genes (DEGs) related to lipid metabolism. Subsequently, univariate and multivariate Cox regression analyses were utilized to construct the prognostic gene signature. Functional enrichment analysis of prognostic genes was achieved by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Kaplan-Meier analysis, Receiver Operating Characteristic (ROC) curves, clinical follow-up results were employed to assess the prognostic potency. Potential compounds targeting prognostic genes were screened by Connectivity Map (CMap) database and a prognostic gene-drug interaction network was constructed using Comparative Toxicogenomics Database (CTD). Furthermore, we separately validated the selected marker genes in BRCA samples and human breast cancer cell lines (MCF-7, MDA-MB-231).

Results

IPA and functional enrichment analysis demonstrated that the 162 lipid metabolism-related DEGs we obtained were involved in many lipid metabolism and BRCA pathological signatures. The prognostic classifier we constructed comprising SDC1 and SORBS1 can serve as an independent prognostic marker for BRCA. CMap filtered 37 potential compounds against prognostic genes, of which 16 compounds could target both two prognostic genes were identified by CTD. The functions of the two prognostic genes in breast cancer cells were verified by cell function experiments.

Conclusion

Within this study, we identified a novel prognostic classifier based on two lipid metabolism-related genes: SDC1 and SORBS1. This result highlighted a new perspective on the metabolic exploration of BRCA.

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.

The High Expression of Minichromosome Maintenance Complex Component 5 Is an Adverse Prognostic Factor in Lung Adenocarcinoma

Background. Minichromosome maintenance (MCM) genes are crucial for genomic DNA replication and are important biomarkers in tumor biology. In this study, we aimed to identify the diagnostic, therapeutic, and prognostic value of the MCM2–10 genes in patients with lung cancer. Methods. We examined the expression levels, gene networks, and protein networks of lung cancer using data from the ONCOMINE, GeneMANIA, and STRING databases. We conducted a functional enrichment analysis of MCM2–10 using the clusterProfiler package using TCGA data. The correlation between the MCM2–10 expression and lung cancer prognosis was evaluated using Cox regression analysis. The influence of clinical variables on overall survival (OS) was evaluated using univariate and multivariate analyses. The TIMER database was used to evaluate the correlation between tumor infiltrating levels and lung cancer. Kaplan–Meier Plotter pan-cancer RNA sequencing was used to estimate the correlation between the MCM5 expression and OS in different immune cell subgroups in patients with lung adenocarcinoma (LUAD). Finally, the 1-, 3-, and 5-year predictions of LUAD were performed using nomogram and calibration analysis. Results. The expression of MCM2, 3, 4, 5, 6, 7, 8, and 10 in lung cancer was higher than that for normal samples. The MCM5 expression was associated with poor OS in patients with LUAD, and prognosis was related to TNM stage, smoking status, and pathological stage. The MCM5 expression is correlated with immune invasion in LUAD and may affect prognosis due to immune infiltration. Conclusion. MCM5 may serve as a molecular biomarker for LUAD prognosis.

Novel Insight Into the Association Between Obesity and Hepatocellular Carcinoma Occurrence and Recurrence: High-Throughput Microarray Data Set Analysis of Differentially Expressed Genes

PURPOSE

This study aims to identify potential biomarkers of hepatocellular carcinoma (HCC) occurrence/recurrence and obesity, along with the molecular mechanisms that involve these biomarkers.

METHODS

Three microarray data sets, namely GSE18897, GSE25097, and GSE36376 (genetic suppressor elements associated with obesity, tumor, and recurrence, respectively), were downloaded from Gene Expression Omnibus database to be investigated for their expression as differentially expressed genes (DEGs) in HCC and obesity. The functional and pathway enrichment analysis of these DEGs were identified by the Database for Annotation Visualization and Integrated Discovery. The protein-protein interaction network analysis was performed with STRING online tool and Cytoscape software.

RESULTS

One hundred sixty common DEGs were screened. We found that these genes were associated with certain pathways such as metabolic pathways, terpenoid backbone biosynthesis, and adipocytokine signaling pathway. The involvements of 10 genes, including RPS16, RPS7, CCT3, HNRNPA2B1, EIF4G1, PSMC4, NHP2, EGR1, FDPS, and MCM4, were identified in the subnetwork. HNRNPA2B1 and RPS7 in the GSE18897 data set, RPS16, RPS7, CCT3, HNRNPA2B1, PSMC4, NHP2, FDPS, and MCM4 in the GSE25097 data set, and RPS16, RPS7, CCT3, HNRNPA2B1, EIF4G1, PSMC4, NHP2, FDPS, and MCM4 in the GSE36376 data set exhibited positive fold changes.

CONCLUSION

These DEGs and pathways could be of diagnostic value as potential biomarkers involved in the pathogenesis of HCC, pertaining to both obesity and HCC occurrence/recurrence.

Bioinformatics Analysis Reveals MCM3 as an Important Prognostic Marker in Cervical Cancer

The minichromosome maintenance complex 3 (MCM3) is essential for the regulation of DNA replication and cell cycle progression. However, the expression and prognostic values of MCM3 in cervical cancer (CC) have not been well-studied. Herein, we investigated the expression patterns and survival data of MCM3 in cervical cancer patients from the ONCOMINE, GEPIA, Human Protein Atlas, UALCAN, Kaplan-Meier Plotter, and LinkedOmics databases. The expression level of MCM3 is negatively correlated with advanced tumor stage and metastatic status. Specifically, MCM3 is significantly differentially expressed between patients in stage 1 and stage 3 cervical cancer with p value 0.0138. Similarly, the p values between stage 1 and stage 4 cervical cancer, between stage 2 and stage 3, and between stage 2 and stage 4 are 0.00089, 0.0244, and 0.00197, respectively. Not only that, cervical cancer patients with high mRNA expression of MCM3 may indicate longer overall survival but indicate shorter relapse-free survival. PRIM2 and MCM6 are positively correlated genes of MCM3. Bioinformatics analysis revealed that MCM3 might be considered a biological indicator for prognostic evaluation of cervical cancer. However, it is currently limited to bioinformatics analysis, and more clinical tissue specimens and cell experiments are needed to further explore the role of MCM3 in the occurrence and progression of cervical cancer.

Identification of Multiple Hub Genes and Pathways in Hepatocellular Carcinoma: A Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is a common malignant tumor of the digestive system, and its early asymptomatic characteristic increases the difficulty of diagnosis and treatment. This study is aimed at obtaining some novel biomarkers with diagnostic and prognostic meaning and may find out potential therapeutic targets for HCC. We screen differentially expressed genes (DEGs) from the HCC gene expression profile GSE14520 using GEO2R. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted by using the clusterProfiler software while a protein-protein interaction (PPI) network was performed based on the STRING database. Then, prognosis analysis of hub genes was conducted using The Cancer Genome Atlas (TCGA) database. Quantitative real-time polymerase chain reaction (qRT-PCR) was utilized to further verify the expression of hub genes and explore the correlation between gene expression and clinicopathological parameters. A total of 1053 DEGs were captured, containing 497 upregulated genes and 556 downregulated genes. GO and KEGG analysis indicated that the downregulated DEGs were mainly enriched in the fatty acid catabolic process while upregulated DEGs were primarily enriched in the cell cycle. Simultaneously, ten hub genes (CYP3A4, UGT1A6, AOX1, UGT1A4, UGT2B15, CDK1, CCNB1, MAD2L1, CCNB2, and CDC20) were identified by the PPI network. Five prognosis-related hub genes (CYP3A4, CDK1, CCNB1, MAD2L1, and CDC20) were uncovered by the survival analysis based on TCGA database. The ten hub genes were further validated by qRT-PCR using samples obtained from our hospital. The prognosis-related hub genes such as CYP3A4, CDK1, CCNB1, MAD2L1, and CDC20 could be considered potential diagnosis biomarkers and prognosis targets for HCC. We also use Oncomine for further verification, and we found CCNB1, CCNB2, CDK1, and CYP3A4 which were highly expressed in HCC. Meanwhile, CCNB1, CCNB2, and CDK1 are highly expressed in almost all cancer types, which may play an important role in cancer. Still, further functional study should be conducted to explore the underlying mechanism and biological effect in the near future.

Comparative protein profiling reveals the inhibitory role of curcumin on IL-17A mediated minichromosome maintenance (MCM) proteins as novel putative markers for acute lung injury in vivo

The Pro-inflammatory cytokine, Interleukin 17A (IL-17A) plays a vital role in the pathogenesis of inflammatory-induced acute lung injury (ALI). But, the mechanisms of this pro-inflammatory cytokine in response to activation after replication stress are not yet known. Control on DNA replication (DR) is vital for maintaining genome stability. Minichromosome maintenance (MCM) proteins play essential roles in various cancers, but their involvement during ALI is not yet been discussed. The present study was carried out to assess the participation of IL-17A during replication stress and to evaluate the contribution of curcumin on this. Mass spectrometry-based proteomic approach has been used on mice lung tissues treated with IL-17A, as a prime mediator to cause injury and curcumin a natural polyphenol as an intervention. Several trends were identified from the proteomic subset which revealed that IL-17A induces expressions of proteins like MCM2, MCM3, and MCM6 along with other proteins involved in DR. Interestingly, curcumin was found in suppressing the expression levels of these proteins. This was also confirmed via validating LC-MS/MS data using appropriate molecular techniques. Pathway and gene ontology analysis were performed with DAVID GO databases. Apart from this, the present study also reports the unique contribution of curcumin in suppressing the mRNA levels of other MCMs like MCM4, MCM5, and MCM7 as well as of ORC1 and ORC2. Hence, the present study revolves around linking the replication stress by pro-inflammatory effects, highlighting the implications for ALI and therapies. This study, therefore, enhances our capacity to therapeutically target DR-specific proteins.

SOX4 as biomarker in hepatitis B virus-associated hepatocellular carcinoma

Background: Hepatitis B virus infection is associated with liver disease, including cancers. In this study, we assessed the power of sex-determining region Y (SRY)-related high-mobility group (HMG)-box 4(SOX4) gene to predict the clinical course of hepatocellular carcinoma (HCC).

Methods: To evaluate the differential expression of SOX4 and its diagnostic and prognostic potential in HCC, we analyzed the GSE14520 dataset. Stratified analysis and joint-effect analysis were done using SOX4 and clinical factor. We then designed a nomogram for predicting the clinical course of HCC. Differential SOX4 expression and its correlation with tumor stage as well as its diagnostic and prognostic value were analyzed on the oncomine and GEPIA websites. Gene set enrichment analysis was explored as well as candidate gene ontology and metabolic pathways modulated by in SOX4 HCC.

Results: Our analysis revealed that the level of SOX4 was significantly upregulated in tumor issue (P <0.001). This observation was validated through oncomine dataset and MERAV analysis (all P <0.05). Diagnostic receiver operating characteristic (ROC) analysis of SOX4 suggested it has diagnostic potential in HCC (GSE14520 dataset: P <0.001, area under curve (AUC) = 0.782; Oncomine: (Wurmbach dataset) P = 0.002, AUC = 0.831 and (Mas dataset) P <0.001, AUC = 0.947). In addition, SOX4 exhibited high correlation with overall survival of HBV-associated HCC (adjusted P = 0.004, hazard ratio (HR) (95% confidence interval (CI)) = 2.055 (1.261-3.349) and recurrence-free survival (adjusted P = 0.008, HR (95% CI) = 1.721 (1.151-2.574). These observations which were verified by GEPIA analysis for overall survival (P = 0.007) and recurrence-free survival (P= 0.096). Gene enrichment analysis revealed that affected processes included lymphocyte differentiation, pancreatic endocrine pathways, and insulin signaling pathway. SOX4 prognostic value was evaluated using nomogram analysis for HCC 1, 3, and 5-year, survival.

Conclusion: Differential SOX4 expression presents an avenue of diagnosing and predicting clinical course of HCC. In HCC, SOX4 may affect TP53 metabolic processes, lymphocyte differentiation and the insulin signaling pathway.

Elevated expression of minichromosome maintenance 3 indicates poor outcomes and promotes G1/S cell cycle progression, proliferation, migration and invasion in colorectal cancer

Background: The minichromosome maintenance (MCM) family, a core component of DNA replication, is involved in cell cycle process. Abnormal proliferation has been identified as a crucial process in the evolution of colorectal cancer (CRC). However, the roles of the MCM family in CRC remain largely unknown.

Methods: Here, the expression, prognostic significance and functions of the MCM family in CRC were systematically analyzed through a series of online databases including CCLE, Oncomine, HPA, cBioPortal and cancerSEA.

Results: We found all MCM family members were highly expressed in CRC, but only elevation of MCM3 expression was associated with poor prognosis of patients with CRC. Further in vitro and in vivo experiments were performed to examine the role of MCM3 in CRC. Analysis of CCLE database and qRT-PCR assay confirmed that MCM3 was overexpressed in CRC cell lines. Moreover, knockdown of MCM3 significantly suppressed transition of G1 to S phase in CRC cells. Furthermore, down-regulation of MCM3 inhibited CRC cell proliferation, migration, invasion and promoted apoptosis.

Conclusion: These findings reveal that MCM3 may function as an oncogene and a potential prognosis biomarker. Thus, the association between abnormal expression of MCM3 and the initiation of CRC deserves further exploration.

Integration of transcriptomes analysis with spectral signature of total RNA for generation of affordable remote sensing of Hepatocellular carcinoma in serum clinical specimens

Hepatocellular carcinoma (HCC) is a major global health problem with about 841,000 new cases and 782,000 deaths annually, due to lacking early biomarker/s, and centralized diagnosis. Transcriptomes research despite its infancy has proved excellence in its implementation in identifying a coherent specific cancer RNAs differential expression. However, results are sometimes overlapped by other cancer types which negatively affecting specificity, plus the high cost of the equipment used. Hyperspectral imaging (HSI) is an advanced tool with unique, spectroscopic features, is an emerging tool that has widely been used in cancer detection. Herein, a pilot study has been performed for HCC diagnosis, by exploiting HIS properties and the analysis of the transcriptome for the development of non-invasive remote HCC sensing. HSI data cube images of the sera extracted total RNA have been analyzed in HCC, normal subject, liver benign tumor, and chronic HCV with cirrhotic/non-cirrhotic liver groups. Data analyses have revealed a specific spectral signature for all groups and can be easily discriminated; at the computed optimum wavelength. Moreover, we have developed a simple setup based on a commercial laser pointer for sample illumination and a Smartphone CCD camera, with HSI consistent data output. We hypothesized that RNA differential expression and its spatial organization/folding are the key players in the obtained spectral signatures. To the best of our knowledge, we are the first to use HSI for sensing cancer based on total RNA in serum, using a Smartphone CCD camera/laser pointer. The proposed biosensor is simple, rapid (2 min), and affordable with specificity and sensitivity of more than 98% and high accuracy.

Comprehensive investigation of the clinical significance of long non-coding RNA HOXA-AS2 in acute myeloid leukemia using genome-wide RNA sequencing dataset

Objective: The present study aimed to determine the prognostic value of HOXA cluster antisense RNA2 (HOXA-AS2) in acute myeloid leukemia (AML), and to explore its potential molecular mechanisms. We also screening of potential drugs targeting HOXA-AS2 in AML.

Methods: The level 3 raw genome-wide RNA sequencing dataset of AML was download from The Cancer Genome Atlas (TCGA) Data Portal, and the potential molecular mechanisms and drugs prediction of HOXA-AS2 in AML were explored using multiple bioinformatics analysis approaches.

Results: TCGA AML cohort dataset indicated that HOXA-AS2 was significantly up-regulated in AML bone marrow tissues, and high HOXA-AS2 expression was related to poor overall survival (log-rank P=0.0284, hazard ratio 1.640, 95% confidence interval 1.046-2.573). Functional enrichment of differentially expressed genes (DEGs) suggested that the difference in prognosis between AML patients with high- and low-HOXA-AS2 expression may be due to differences in biological processes and pathways, including cell adhesion, angiogenesis, mitogen-activated protein kinase, cell differentiation, and other biological processes, and phosphatidylinositol 3 kinase-protein kinase B and Wnt signaling pathways. We also screened out three potential HOXA-AS2-targeted therapeutic drugs for AML, megestrol, carmustine, and cefoxitin, based on these DEGs. Functional enrichment analysis of HOXA-AS2-co-expressed genes revealed that HOXA-AS2 may act a part in AML by regulating nuclear factor-κB transcription factor activity, DNA methylation, angiogenesis, apoptosis, cell migration, Toll-like receptor 4, and Wnt signaling pathways.

Conclusion: Our findings suggest that HOXA-AS2 is up-regulated in the bone marrow in patients with AML, and may serve as a novel prognostic biomarker for AML.

Identification of MCM family as potential therapeutic and prognostic targets for hepatocellular carcinoma based on bioinformatics and experiments

AIMS

The minichromosome maintenance (MCM) complex is highly conserved, which has drawn increasing attention on physiology and pathology process. However, the role of MCM in hepatocellular carcinoma (HCC) remains largely unclear. We aimed to conduct systematic analysis of expression patterns, prognostic values and potential functions of nine MCM genes in HCC, thus identifying their role in HCC.

MAIN METHODS

In our study, we systemically analyzed the role of MCM in prognosis and HCC progression by several bioinformatics analysis tools. Immunohistochemical (IHC) assays were utilized to valid the protein expression of MCM in HCC and in vitro experiments were used to confirm the functions of MCMs in HCC proliferation.

KEY FINDINGS

Overexpression of MCM2-8 and MCM10 were found to be significantly associated with clinical parameters and poor prognosis of HCC patients. The function of MCM was mainly enriched in DNA replication. Moreover, MCM were also associated with several cancer pathway and drug sensitivity in HCC. Close correlations were observed between immune cell infiltration and MCM in HCC. Cell Counting Kit-8 (CCK-8) and clone formation assays suggested the role of MCM2-8 and MCM10 in HCC proliferation.

SIGNIFICANCE

These results have implied that deregulated MCM played an important role in HCC progression and might be considered as potential therapeutic and prognostic targets for HCC.

Biological features, gene expression profile, and mechanisms of drug resistance of two- and three-dimensional hepatocellular carcinoma cell cultures

Hepatocellular carcinoma (HCC) is a common malignant tumor with insidious onset and rapid progression. Its treatment is often difficult owing to tumor resistance. In this study, we aimed to understand the different biological characteristics, gene expression profiles, and drug resistance mechanisms of HCC cells cultured under different conditions. A conventional adherence method and a liquid overlay technique were used to prepare two- and three-dimensional cultures of Bel-7402 and 5-fluorouracil (5-Fu)-resistant Bel-7402 (Bel-7402/5-Fu) cells. Morphological characteristics were assessed via microscopy, and cell cycle distribution and apoptotic rate were obtained using flow cytometry. Cell sensitivity to different concentrations of drugs was detected with 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assays. Gene expression profiles and signal transduction pathways of Bel-7402 and Bel-7402/5-Fu cells under different culture conditions were determined using gene chips. Cells in three-dimensional culture were suspended and they grew into dense multicellular spheroid (MCS) structures, aggregating with each other. In contrast to cells in the two-dimensional culture, cell cycle arrest was observed in MCSs. The sensitivity of Bel-7402 cells in the two-dimensional culture to drugs at high concentrations was significantly higher than that of cells in the three-dimensional culture (p < .05). The apoptotic rate of Bel-7402 and Bel-7402/5-Fu cells was also higher in the two-dimensional culture (p < .05). Signal transduction pathway analysis showed that after Bel-7402 cells acquired resistance to 5-Fu, CCND1, MCM2, and MCM3 gene expression was upregulated in the G1 to S cell cycle control signal transduction pathway, CDKN1C and CCNG2 gene expression was downregulated, and MCM2 and MCM3 gene expression was upregulated in the DNA replication signal transduction pathway. Therefore, the liquid overlay technique is a simple, low-cost procedure to successfully construct three-dimensional culture models of HCC. This study provides new information and methods for exploring the molecular mechanisms of liver cancer resistance, clinical treatment, development of molecular information, and interventional prevention.

Carbohydrate Sulfotransferase 4 Inhibits the Progression of Hepatitis B Virus-Related Hepatocellular Carcinoma and Is a Potential Prognostic Marker in Several Tumors

Carbohydrate sulfotransferase 4 (CHST4) plays an important role in lymphocyte homing and is abnormally expressed in several cancer types; however, its precise function in tumor development and progression is unknown. Here we confirm that CHST4 is aberrantly expressed in various tumor subtypes. In particular, we found that CHST4 expression was downregulated in hepatitis B virus-related hepatocellular carcinoma (HBV-HCC) tumors compared to paired normal tissue. We also showed that CHST4 overexpression inhibited the proliferation and metastasis of HCC cells in vitro. Clinically, CHST4 was identified as an independent prognostic factor for HBV-HCC patients. We further illuminated the anti-tumor role and mechanism of CHST4 in HBV-HCC by constructing a FENDRR–miR-10b-5p–CHST4 competing endogenous RNA network. We found that downregulation of CHST4 expression may promote HBV expression and regulate ribonucleoprotein complex biogenesis to promote malignant behaviors in HBV-HCC. CHST4 may also recruit CD4+ T cells, macrophages, dendritic cells, and neutrophils into the tumor microenvironment to inhibit the progression of HBV-HCC. Overall, our findings suggest that CHST4 acts as a tumor suppressor in HCC-HBV and represents a potential diagnostic and therapeutic target.

MCM10 Acts as a Potential Prognostic Biomarker and Promotes Cell Proliferation in Hepatocellular Carcinoma: Integrated Bioinformatics Analysis and Experimental Validation

Background

Hepatocellular carcinoma (HCC) is one of the most common human malignant tumors. The prognosis of HCC patients is still unsatisfying. Thus, it is of great importance to identify novel molecules and functional pathways associated with the pathophysiology of HCC. In this study, we performed the integrated bioinformatics analysis and experiment validation to identify novel biomarkers in the prognosis and progression of HCC.

Materials and Methods

Gene expression profiles were obtained from Gene Expression Omnibus database (GSE33294) for the screening of the differentially expressed genes (DEGs) between HCC tissues and matched non-tumor tissues. The DEGs were subjected to Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and Gene Set Enrichment Analysis (GSEA). The key genes in HCC were further subjected to overall survival analysis of HCC patients. The in vitro functional studies were performed to validate the biological functions of the key gene in HCC cell progression.

Results

A total of 2,334 DEGs were screened from GSE33294 dataset, including 1,120 up-regulated and 1,214 down-regulated genes. GO, KEGG and GSEA results showed that DEGs are significantly associated with the biological process of cell cycle, cell division and DNA replication. The Kaplan–Meier survival analysis results showed that the key genes from the minichromosome maintenance protein complex (MCM) family including MCM8, MCM10, MCM2, MCM3, MCM4, MCM6 and MCM7 were significantly correlated with the overall survival of the HCC patients. Further validation studies showed that MCM10 was significantly up-regulated in the HCC cell lines, and knockdown of MCM10 significantly suppressed cell proliferation as determined by the cell counting kit-8 and BrdU incorporation assays and increased the caspase-3 activity of HCC cells.

Conclusion

The comprehensive bioinformatics analysis identified several key genes that were associated with the prognosis of HCC patients. The validation study results indicated that MCM10 may be an important predictor for poorer prognosis of HCC patients and may act as an oncogene to promote HCC cell progression.

Diagnostic and prognostic value of MCM3 and its interacting proteins in hepatocellular carcinoma

Aberrant DNA replication is one of the driving forces behind oncogenesis. Furthermore, minichromosome maintenance complex component 3 (MCM3) serves an essential role in DNA replication. Therefore, in the present study, the diagnostic and prognostic value of MCM3 and its interacting proteins in hepatocellular carcinoma (HCC) were investigated. By utilizing The Cancer Genome Atlas (TCGA) database, global MCM3 mRNA levels were assessed in HCC and normal liver tissues. Its effects were further analyzed by reverse transcription-quantitative PCR (RT-qPCR), western blotting and immunohistochemistry in 78 paired HCC and adjacent tissues. Functional and pathway enrichment analyses were performed using the Search Tool for the Retrieval of Interacting Genes database. The expression levels of proteins that interact with MCM3 were also analyzed using the TCGA database and RT-qPCR. Finally, algorithms combining receiver operating characteristic (ROC) curves were constructed using binary logistic regression using the TCGA results. Increased MCM3 mRNA expression with high α-fetoprotein levels and advanced Edmondson-Steiner grade were found to be characteristic of HCC. Survival analysis revealed that high MCM3 expression was associated with poor outcomes in patients with HCC. In addition, MCM3 protein expression was associated with increased tumor invasion in HCC tissues. MCM3 and its interacting proteins were found to be primarily involved in DNA replication, cell cycle and a number of binding processes. Algorithms combining ROCs of MCM3 and its interacting proteins were found to have improved HCC diagnosis ability compared with MCM3 and other individual diagnostic markers. In conclusion, MCM3 appears to be a promising diagnostic biomarker for HCC. Additionally, the present study provides a basis for the multi-gene diagnosis of HCC using MCM3.

Minichromosome maintenance protein 5 is an important pathogenic factor of oral squamous cell carcinoma

Oral squamous cell carcinoma is one of the most common causes of malignancy-associated death. Early diagnosis of oral squamous cell carcinoma (OSCC) is important in patient treatment and prognostic evaluation. Due to the lack of significant therapeutic benefit, the 5-year survival rate has not improved. Therefore, effective novel markers are needed to improve diagnosis. To determine novel promising diagnostic biomarkers for OSCC, 416 upregulated and 416 downregulated differentially expressed genes were screened from OSCC tissues using an RNA microarray. The results suggested that minichromosome maintenance protein (MCM5) mRNA was significantly overexpressed in OSCC tissues compared with that in adjacent normal tissues. Moreover, silencing of MCM5 expression an OSCC cell line (SCC-15) significantly impaired proliferation and colony formation. Furthermore, negative regulation of the mRNA and protein expression of MCM5 and demonstrated that MCM5 served as a cancer-promoting gene modulating OSCC cell proliferation through induced G₂/M phase arrest. In this process, the mRNA expression of cyclin E and cyclin-dependent kinase 2 was downregulated, while p21 expression was upregulated. These results suggested that MCM5 may be an important pathogenic factor of OSCC. High expression levels of MCM5 may serve as a marker for the early diagnosis of OSCC.

Effects of tesamorelin on hepatic transcriptomic signatures in HIV-associated NAFLD

Nonalcoholic fatty liver disease (NAFLD) is a common comorbidity among people living with HIV that has a more aggressive course than NAFLD among the general population. In a recent randomized placebo-controlled trial, we demonstrated that the growth hormone-releasing hormone analog tesamorelin reduced liver fat and prevented fibrosis progression in HIV-associated NAFLD over 1 year. As such, tesamorelin is the first strategy that has shown to be effective against NAFLD among the population with HIV. The current study leveraged paired liver biopsy specimens from this trial to identify hepatic gene pathways that are differentially modulated by tesamorelin versus placebo. Using gene set enrichment analysis, we found that tesamorelin increased hepatic expression of hallmark gene sets involved in oxidative phosphorylation and decreased hepatic expression of gene sets contributing to inflammation, tissue repair, and cell division. Tesamorelin also reciprocally up- and downregulated curated gene sets associated with favorable and poor hepatocellular carcinoma prognosis, respectively. Notably, among tesamorelin-treated participants, these changes in hepatic expression correlated with improved fibrosis-related gene score. Our findings inform our knowledge of the biology of pulsatile growth hormone action and provide a mechanistic basis for the observed clinical effects of tesamorelin on the liver.

MCM family in gastrointestinal cancer and other malignancies: From functional characterization to clinical implication

Despite the recent advances in cancer research and treatment, gastrointestinal (GI) cancers remain the most common deadly disease worldwide. The aberrant DNA replication serves as a major source of genomic instability and enhances cell proliferation that contributes to tumor initiation and progression. Minichromosome maintenance family (MCMs) is a well-recognized group of proteins responsible for DNA synthesis. Recent studies suggested that dysregulated MCMs lead to tumor initiation, progression, and chemoresistance via modulating cell cycle and DNA replication stress. Their underlying mechanisms in various cancer types have been gradually identified. Furthermore, multiple studies have investigated the association between MCMs expression and clinicopathological features of cancer patients, implying that MCMs might serve as prominent prognostic biomarkers for GI cancers. This review summarizes the current knowledge on the oncogenic role of MCM proteins and highlights their clinical implications in various malignancies, especially in GI cancers. Targeting MCMs might shed light on the potential for identifying novel therapeutic strategies.

Identification of potential prognostic small nucleolar RNA biomarkers for predicting overall survival in patients with sarcoma

Objective

The main purpose of the present study is to screen prognostic small nucleolar RNA (snoRNA) markers using the RNA‐sequencing (RNA‐seq) dataset of The Cancer Genome Atlas (TCGA) sarcoma cohort.

Methods

The sarcoma RNA‐seq dataset comes from the TCGA cohort. A total of 257 sarcoma patients were included into the prognostic analysis. Multiple bioinformatics analysis methods for functional annotation of snoRNAs and screening of targeted drugs, including biological network gene ontology tool, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and connectivity map (CMap) are used.

Results

We had identified 15 snoRNAs that were significantly related to the prognosis of sarcoma and constructed a prognostic signature based on four prognostic snoRNA (U3, SNORA73B, SNORD46, and SNORA26) expression values. Functional annotation of these four snoRNAs by their co‐expression genes suggests that some of them were closely related to cell cycle‐related biological processes and tumor‐related signaling pathways, such as Wnt, mitogen‐activated protein kinase, target of rapamycin, and nuclear factor‐kappa B signaling pathway. GSEA of the risk score suggests that high risk score phenotype was significantly enriched in cell cycle‐related biological processes, protein SUMOylation, DNA replication, p53 binding, regulation of DNA repair, and DNA methylation, as well as Myc, Wnt, RB1, E2F, and TEL pathways. Then we also used the CMap online tool to screen five targeted drugs (rilmenidine, pizotifen, amiprilose, quipazine, and cinchonidine) for this risk score model in sarcoma.

Conclusion

Our study have identified 15 snoRNAs that may be serve as novel prognostic biomarkers for sarcoma, and constructed a prognostic signature based on four prognostic snoRNA expression values.

The impact of MCM6 on hepatocellular carcinoma in a Southern Chinese Zhuang population

Minichromosome maintenance complex component 6 (MCM6) is involved in tumorigenesis of hepatocellular carcinoma (HCC). Because its effect on different populations remains unclear, this study investigated the impact of MCM6 on HCC in Southern Chinese Zhuang population. In addition to assessing the global mRNA levels of MCM6 based on The Cancer Genome Atlas database (TCGA) and The Gene Expression Omnibus database (GEO), associations between MCM6 mRNA levels and clinicopathological features were analyzed. High MCM6 levels were associated with high alpha-fetoprotein (AFP) (>20 ng/mL in serum) (P < 0.0001) and advanced clinical stage (III + IV) (P < 0.001). Higher MCM6 was associated with poorer outcomes (P < 0.01) in these databases. Furthermore, the mRNA and protein expression of MCM6 in the Guangxi Zhuang population was detected by quantitative polymerase chain reaction (qPCR), western blot, and immunohistochemistry (IHC). The results showed that MCM6 levels were up-regulated in the Zhuang population with HCC. Higher MCM6 protein levels were correlated with larger tumor size (>5 cm) (P = 0.038) and advanced clinical stage (III + IV) (p = 0.023). Bioinformatic enrichment analysis of MCM6 and its interacting proteins (CDT1,WEE1,TRIM28 and MKI67) suggested that in addition to being involved in the cell cycle process, these complexes could also be involved in protein binding, pre-replication complex assemble, and nucleus metabolism. Based on the protein-protein interaction (PPI) network with module screen, the interactions between MCM6 and its potential interacting proteins were further studied through protein docking with hot spot analysis. Additionally, the results of the algorithms combining the ROC of MCM6 and its interacting proteins showed that combination biomarker analysis has better HCC diagnosis ability than the single MCM6 test. The combination of MCM6 and TRIM28 was more suitable for the Guangxi Zhuang population. Overall, our study suggests that MCM6 plays an important role in the growth of HCC. MCM6 could be an optimal biomarker for diagnosing HCC and a potential molecular target for HCC therapy in the Zhuang population.

miR-3607, a biomarker of hepatocellular carcinoma invasion and aggressiveness: Its relationship with epithelial-mesenchymal transition process

microRNA-3607 (miR-3607) has been identified as an important biomarker, and its aberrant expression exerts a significant role in tumorigenesis. However, the biological function of miR-3607 in hepatocellular carcinoma (HCC) needs to be deciphered comprehensively. Clinical samples of HCC patients, as well as normal cases, were derived from The Cancer Genome Atlas database. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) and Western blotting analyses were utilized to detect the expression levels of indicated genes. Cell counting kit-8 (CCK-8), colony formation, and transwell assays were performed to assess the effect of miR-3607 in HCC cell viability, migration, and invasion. Bioinformatics analysis and luciferase reporter gene assay was applied to screen the target genes of miR-3607 and verified the association between miR-3607 and its potential target gene. Our study showed that miR-3607 expression was decreased in HCC tissues and cell lines, and its downregulation was linked with poor outcomes of HCC patients. miR-3607 was noted to inhibit HCC cell growth, colony formation, migration, and invasion. Besides, minichromosome maintenance (MCM5) was a possible target gene of miR-3607 in HCC. Overexpression of MCM5 was observed in HCC and induced unfavorable prognosis. MCM5 expression had a negative correlation with miR-3607. MCM5 can abolish the suppressive impacts of miR-3607 on HCC cell malignant behaviors and the epithelial-mesenchymal transition (EMT) process. To sum up, our results unveiled that miR-3607 could inhibit HCC cell growth, migration, and invasion by regulating MCM5 and mediating EMT process, suggesting a new probable biomarker for further treatment of HCC.

MCMs in Cancer: Prognostic Potential and Mechanisms

Enabling replicative immortality and uncontrolled cell cycle are hallmarks of cancer cells. Minichromosome maintenance proteins (MCMs) exhibit helicase activity in replication initiation and play vital roles in controlling replication times within a cell cycle. Overexpressed MCMs are detected in various cancerous tissues and cancer cell lines. Previous studies have proposed MCMs as promising proliferation markers in cancers, while the prognostic values remain controversial and the underlying mechanisms remain unascertained. This review provides an overview of the significant findings regarding the cellular and tumorigenic functions of the MCM family. Besides, current evidence of the prognostic roles of MCMs is retrospectively reviewed. This work also offers insight into the mechanisms of MCMs prompting carcinogenesis and adverse prognosis, providing information for future research. Finally, MCMs in liver cancer are specifically discussed, and future perspectives are provided.

Novel candidate biomarkers of origin recognition complex 1, 5 and 6 for survival surveillance in patients with hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) has high morbidity and mortality and lacks effective biomarkers for early diagnosis and survival surveillance. Origin recognition complex (ORC), consisting of ORC1-6 isoforms, was examined to assess the potential significance of ORC isoforms for HCC prognosis. Methods: Oncomine and Gene Expression Profiling Interactive Analysis (GEPIA) databases were used to examine differential isoform expression, stage-specific expression, calculate Pearson correlations and perform survival analysis. A human protein atlas database was utilized to evaluate the protein expression of ORCs in liver tissue. The cBioPortal database was used to assess isoform mutations and the survival significance of ORCs in HCC. Cytoscape software was employed to construct gene ontologies, metabolic pathways and gene-gene interaction networks. Results: Differential expression analysis indicated that ORC1 and ORC3-6 were highly expressed in tumor tissues in the Oncomine and GEPIA databases, while ORC2 was not. All the ORCs were showed positive and statistically significant correlations with each other (all P<0.001). ORC1-2 and ORC4-6 expressions were associated with disease stages I-IV (all P<0.05), but ORC3 was not. Survival analysis found that ORC1 and ORC4-6 expressions were associated with overall survival (OS), and ORC1-3 and ORC5-6 expression were associated with recurrence-free survival (RFS; all P<0.05). In addition, low expression of these ORC genes consistently indicated better prognosis compared with high expression. Protein expression analysis revealed that ORC1 and ORC3-6 were expressed in normal liver tissues, whereas ORC2 was not. Enrichment analysis indicated that ORCs were associated with DNA metabolic process, sequence-specific DNA binding and were involved in DNA replication, cell cycle, E2F-enabled inhibition of pre-replication complex formation and G1/S transition. Conclusions: Differentially expressed ORC1, 5 and 6 are candidate biomarkers for survival prediction and recurrence surveillance in HCC.

Identification of Platform-Independent Diagnostic Biomarker Panel for Hepatocellular Carcinoma Using Large-Scale Transcriptomics Data

The high mortality rate of hepatocellular carcinoma (HCC) is primarily due to its late diagnosis. In the past, numerous attempts have been made to design genetic biomarkers for the identification of HCC; unfortunately, most of the studies are based on small datasets obtained from a specific platform or lack reasonable validation performance on the external datasets. In order to identify a universal expression-based diagnostic biomarker panel for HCC that can be applicable across multiple platforms, we have employed large-scale transcriptomic profiling datasets containing a total of 2,316 HCC and 1,665 non-tumorous tissue samples. These samples were obtained from 30 studies generated by mainly four types of profiling techniques (Affymetrix, Illumina, Agilent, and High-throughput sequencing), which are implemented in a wide range of platforms. Firstly, we scrutinized overlapping 26 genes that are differentially expressed in numerous datasets. Subsequently, we identified a panel of three genes (FCN3, CLEC1B, and PRC1) as HCC biomarker using different feature selection techniques. Three-genes-based HCC biomarker identified HCC samples in training/validation datasets with an accuracy between 93 and 98%, Area Under Receiver Operating Characteristic curve (AUROC) in a range of 0.97 to 1.0. A reasonable performance, i.e., AUROC 0.91–0.96 achieved on validation dataset containing peripheral blood mononuclear cells, concurred their non-invasive utility. Furthermore, the prognostic potential of these genes was evaluated on TCGA-LIHC and GSE14520 cohorts using univariate survival analysis. This analysis revealed that these genes are prognostic indicators for various types of the survivals of HCC patients (e.g., Overall Survival, Progression-Free Survival, Disease-Free Survival). These genes significantly stratified high-risk and low-risk HCC patients (p-value <0.05). In conclusion, we identified a universal platform-independent three-genes-based biomarker that can predict HCC patients with high precision and also possess significant prognostic potential. Eventually, we developed a web server HCCpred based on the above study to facilitate scientific community (http://webs.iiitd.edu.in/raghava/hccpred/).

Comprehensive investigation of p53, p21, nm23, and VEGF expression in hepatitis B virus-related hepatocellular carcinoma overall survival after hepatectomy

Objective: The goal of our current study is to assess the immunohistochemical of p53, p21, nm23, and VEGF expression in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) prognosis after hepatectomy, as well as the prospective molecular mechanisms of prognostic indicator. Methods: There were 419 HBV-related HCC patients who were from southern China of Guangxi province and were used to evaluate the immunohistochemical expression for these biomarkers in prognosis. A genome-wide expression microarray dataset of HBV-related HCC were obtained from GSE14520. Results: In our study, the expression of p53, p21, and nm23 in cancer tissues of patients with hepatitis B-related hepatocellular carcinoma did not affected the clinical outcome of 2 years, 5 years or overall. Patients with high expression of VEGF had a worse overall survival after 2 years of surgery than patients with low expression (adjusted P=0.040, adjusted HR = 1.652, 95% CI = 1.024-2.665). Survival analysis of VEGF in GSE14520 cohort also demonstrated that VEGF mRNA expression also significantly associated with HBV-related HCC OS (adjusted P=0.035, adjusted HR =1.651, 95% CI =1.035-2.634). The prospective molecular mechanisms by co-expression analysis suggested that VEGF might be correlated to regulation of cell proliferation, cell growth and apoptotic process, Rap1 signaling pathway, HIF-1 signaling pathway, PPAR signaling pathway, cell cycle. Whereas the GSEA suggested that VEGF might involve in the regulation of HIF and HIF1A pathway, and TP53 regulation pathway. Conclusion: Our findings suggested that VEGF might be a prognostic indicator of HBV-related HCC, and we also identified the VEGF prospective molecular mechanisms through the whole genome co-expression and GSEA approaches.

Noteworthy prognostic value of phospholipase C delta genes in early stage pancreatic ductal adenocarcinoma patients after pancreaticoduodenectomy and potential molecular mechanisms

The purpose of this investigation was to explore the prognostic value of phospholipase C delta (PLCD) genes in early stage pancreatic ductal adenocarcinoma (PDAC) and its potential molecular mechanisms. The prognostic value of PLCD genes in early stage PDAC was assessed using the Kaplan-Meier method and multivariate Cox proportional hazards regression model. Genome-wide correlation analysis was performed on PLCD3 to identify the highly correlated genes in the transcriptome. Then, PLCD3 and these correlated genes together underwent a bioinformatics analysis to elucidate the potential molecular biological functions of PLCD3 in PDAC. PLCD1 and PLCD3 are significantly overexpressed in PDAC. In PDAC patients, PLCD3 is overexpressed in certain groups of people with a history of alcoholism (P = .032). High expression of PLCD3 was found to be associated with lower overall survival (OS) of patients with early stage PDAC (P = .020; adjusted P = .016). A combination of PLCD3 and clinical variables was able to better predict the outcome of patients with early stage PDAC. These clinical variables are histological grade (P = .001; adjusted P = .001), targeted molecular therapy (P < .001; adjusted P < .001), radiation therapy (P = .002; adjusted P = .039), and residual resection (P = .001; adjusted P = .002). The bioinformatics analysis revealed that PLCD3 is associated with angiogenesis, intracellular signal transduction, and regulation of cell proliferation. In conclusion, PLCD3 may be a potential prognostic biomarker for early stage PDAC.

Identification of key genes and long non-coding RNA associated ceRNA networks in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide. Although multiple efforts have been made to understand the development of HCC, morbidity, and mortality rates remain high. In this study, we aimed to discover the mRNAs and long non-coding RNAs (lncRNAs) that contribute to the progression of HCC. We constructed a lncRNA-related competitive endogenous RNA (ceRNA) network to elucidate the molecular regulatory mechanism underlying HCC.

Methods

A microarray dataset (GSE54238) containing information about both mRNAs and lncRNAs was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and lncRNAs (DElncRNAs) in tumor tissues and non-cancerous tissues were identified using the limma package of the R software. The miRNAs that are targeted by DElncRNAs were predicted using miRcode, while the target mRNAs of miRNAs were retrieved from miRDB, miRTarBas, and TargetScan. Functional annotation and pathway enrichment of DEGs were performed using the EnrichNet website. We constructed a protein–protein interaction (PPI) network of DEGs using STRING, and identified the hub genes using Cytoscape. Survival analysis of the hub genes and DElncRNAs was performed using the gene expression profiling interactive analysis database. The expression of molecules with prognostic values was validated on the UALCAN database. The hepatic expression of hub genes was examined using the Human Protein Atlas. The hub genes and DElncRNAs with prognostic values as well as the predictive miRNAs were selected to construct the ceRNA networks.

Results

We found that 10 hub genes (KPNA2, MCM7, CKS2, KIF23, HMGB2, ZWINT, E2F1, MCM4, H2AFX, and EZH2) and four lncRNAs (FAM182B, SNHG6, SNHG1, and SNHG3) with prognostic values were overexpressed in the hepatic tumor samples. We also constructed a network containing 10 lncRNA–miRNA–mRNA pathways, which might be responsible for regulating the biological mechanisms underlying HCC.

Conclusion

We found that the 10 significantly overexpressed hub genes and four lncRNAs were negatively correlated with the prognosis of HCC. Further, we suggest that lncRNA SNHG1 and the SNHG3-related ceRNAs can be potential research targets for exploring the molecular mechanisms of HCC.

Genome-wide analysis to identify a novel microRNA signature that predicts survival in patients with stomach adenocarcinoma

Objective: Using genome-wide screening, this study was aimed at identifying prognostic microRNA (miRNA) in those patients suffering from stomach adenocarcinoma (STAD).

Methods: A genome-wide miRNA sequencing dataset and relevant STAD clinical information was obtained via The Cancer Genome Atlas (TCGA). Prognostic miRNA selection was carried out through a whole genome multivariate Cox regression model in order to establish a prognostic STAD signature.

Results: Eleven miRNAs (hsa-mir-509-2, hsa-mir-3917, hsa-mir-495, hsa-mir-653, hsa-mir-3605, hsa-mir-2115, hsa-mir-1292, hsa-mir-137, hsa-mir-6511b-1, hsa-mir-145, and hsa-mir-138-2) were recognized as prognostic and used for the construction of a STAD prognostic signature. This signature exhibited good performance in predicting prognosis (adjusted P<0.0001, adjusted hazard ratio= 3.047, and 95% confidence interval=2.148-4.323). The time-dependent receiver operating characteristic examination exhibited area under curve values of 0.711, 0.697, 0.716, 0.733, 0.805, and 0.805, for 1-, 2-, 3-, 4-, 5-, and 10-year overall survival (OS) estimation, respectively. Comprehensive survival analysis suggests that the 11-miRNA prognostic signature acts as an independent feature of STAD prognosis and exhibits superior performance in OS prediction when compared to traditional clinical parameters. Furthermore, fourteen miRNA target genes were linked to STAD OS. These included SERPINE1, MLEC, ANGPT2, C5orf38, FZD7, MARCKS, PDGFD, DUSP6, IRS1, PSAT1, TENM3, TMEM127, BLMH, and TIRAP. Functional and gene set enrichment analysis suggested that target genes and the 11-miRNA prognostic signature were both participate in various biological processes and pathways, including the growth factor beta, Wnt, and Notch signaling pathways.

Conclusions: By means of a genome-wide analysis, an 11-miRNA expression signature that may serve as an underlying prognostic indicator for those patients suffering from STAD has been identified and described here.

Prognostic significance of minichromosome maintenance mRNA expression in human lung adenocarcinoma

The minichromosome maintenance (MCM) gene family plays an essential role in DNA replication and cell cycle progression. However, MCM gene expression has not been well-studied in lung adenocarcinoma (LUAD). In the present study, the expression, prognostic value and functions of MCMs in LUAD were investigated using several databases and bioinformatic tools, including Oncomine, GEPIA, cBioPortal, CancerSEA and Kaplan-Meier plotter. It was demonstrated that the mRNA expression of MCM2, MCM4 and MCM10 were significantly increased in patients with LUAD. High mRNA expression of MCM2-5, MCM8 and MCM10 were associated with poor overall survival and progression-free survival. High MCM4 expression was associated with adverse post-progression survival. In addition, the Human Protein Atlas database showed that MCM protein expression was consistent with the mRNA expression. These results demonstrate that MCM2, MCM4 and MCM10 are potential prognostic markers and therapeutic targets for LUAD.

Comprehensive investigation of key biomarkers and pathways in hepatitis B virus-related hepatocellular carcinoma

Objective: Our study is aim to explore potential key biomarkers and pathways in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) using genome-wide expression profile dataset and methods.

Methods: Dataset from the GSE14520 is used as the training cohort and The Cancer Genome Atlas dataset as the validation cohort. Differentially expressed genes (DEGs) screening were performed by the limma package. Gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), gene ontology, the Kyoto Encyclopedia of Genes and Genomes, and risk score model were used for pathway and genes identification.

Results: GSEA revealed that several pathways and biological processes are associated with hepatocarcinogenesis, such as the cell cycle, DNA repair, and p53 pathway. A total of 160 DEGs were identified. The enriched functions and pathways of the DEGs included toxic substance decomposition and metabolism processes, and the P450 and p53 pathways. Eleven of the DEGs were identified as hub DEGs in the WGCNA. In survival analysis of hub DEGs, high expression of PRC1 and TOP2A were significantly associated with poor clinical outcome of HBV-related HCC, and shown a good performance in HBV-related HCC diagnosis. The prognostic signature consisting of PRC1 and TOP2A also doing well in the prediction of HBV-related HCC prognosis. The diagnostic and prognostic values of PRC1 and TOP2A was confirmed in TCGA HCC patients.

Conclusions: Key biomarkers and pathways identified in the present study may enhance the comprehend of the molecular mechanisms underlying hepatocarcinogenesis. Additionally, mRNA expression of PRC1 and TOP2A may serve as potential diagnostic and prognostic biomarkers for HBV-related HCC.

S-Adenosylmethionine Affects Cell Cycle Pathways and Suppresses Proliferation in Liver Cells

S-Adenosylmethionine (SAMe) is a kind of common liver-protection medicine. Recent studies have shown that SAMe has the inhibitory effects on hepatocellular carcinoma (HCC). But the specific mechanism has not been elucidated. Here, we examine the effects and relevant mechanisms of SAMe on human hepatocellular carcinoma cell HepG2 and mouse hepatocyte AML12. We applied the technique of RNA sequencing (RNA-Seq) to identify the differentially expressed genes between HepG2 cells which were treated with SAMe or not. And western blot and Quantitative RT-PCR was used to confirm some of these genes. To investigate the response to SAMe treatment, cell proliferation assay (MTS) and flow cytometry-based assays were carried out. A total of 472 SAMe-related genes were identified by RNA-Seq. We found that differentially expressed genes were enriched in cell cycle related signaling pathway significantly by the KEGG and GO Pathway enrichment analysis. Through the construction of protein-protein interaction network, we observed the module associated with cell cycle is in the core of the whole network. All these results implied that cell cycle pathway may be very important in the regulation of SAMe effected on HepG2 cells. Then the RNA-Seq-characterized genes involved in cell cycle (MCM3, MCM4, and E2F1) were confirmed by Western blot and Quantitative RT-PCR in HepG2 and AML12 cells. MTS analysis showed that SAMe could diminish cell proliferation. And flow cytometry-based assays indicated that treatment with SAMe altered cell cycle kinetic S phase cell cycle arrest. Altogether, our data uncovered the evidence of the antiproliferative action of SAMe in liver cells, and SAMe could lead to cell cycle inhibition by up-regulating MCM3, MCM4 and E2F1 expression. It provided an important theoretical basis for the clinical chemoprevention and treatment in HCC of SAMe.

Genome-wide investigation of the clinical significance and prospective molecular mechanism of minichromosome maintenance protein family genes in patients with Lung Adenocarcinoma

Our current study is to identify clinical significance of minichromosome maintenance (MCM) gene expression in Lung Adenocarcinoma (LUAD) using genome-wide RNA sequencing (RNA-seq) dataset and bioinformatics analysis tools. The biological function and potential process for function of the MCM1-10 were identified by multiple bioinformatics analysis tools. Clinical significance and molecular mechanism of the MCM1-10 were investigated by the RNA-seq dataset of LUAD from The Cancer Genome Atlas. Functional assessment substantiated involvement of MCM1-10 in cell cycle progression and DNA replication, and co-expressed with each other. We also observed that the MCM1-10 were dysregulation in LUAD tumor tissues, and may be have diagnostic implications in LUAD. Prognosis analysis in TCGA and KM plotter cohorts suggest that high abundance of MCM5, MCM8 and MCM4 notably correlated to poor LUAD overall survival. Mechanistic exploration of MCM4, MCM5, and MCM8 by gene set enrichment analysis suggests that these genes may influence the LUAD prognosis by regulating the cell cycle, DNA replication and other multiple biological processes and pathways. In comclusion, our study suggests that MCM1-10 can serve as diagnostic biomarkers for LUAD patients. Of them, MCM4, MCM5, and MCM8 may act as potential prognostic indicators for LUAD.

Genome‑wide investigation of the clinical significance and prospective molecular mechanisms of kinesin family member genes in patients with lung adenocarcinoma

The current study aimed to identify the potential clinical significance and molecular mechanisms of kinesin (KIF) family member genes in lung adenocarcinoma (LUAD) using genome-wide RNA sequencing (RNA-seq) datasets derived from The Cancer Genome Atlas (TCGA) database. Clinical parameters and RNA-seq data of patients with LUAD from the TCGA database enabled the assessment of the clinical significance of KIF genes, while the potential mechanisms of their interactions in LUAD were investigated by gene set enrichment analysis (GSEA). A gene signature with potential prognostic value was constructed via a stepwise multivariable Cox analysis. In total, 23 KIF genes were identified to be differentially expressed genes (DEGs) between the LUAD tumor and adjacent non-cancerous tissues. Of these, 8 differentially expressed KIF genes were strongly found to be strongly associated with the overall survival of patients with LUAD. Three of these genes were found to be able to be grouped as a potential prognostic gene signature. Patients with higher risk scores calculated using this gene signature were found to have a markedly higher risk of mortality (adjusted P=0.003; adjusted HR, 1.576; 95% CI, 1.166–2.129). Time-dependent receiver operating characteristic analysis indicated that this prognostic signature was able to accurately predict patient prognosis with an area under curve of 0.636, 0.643,0.665, 0.670 and 0.593 for the 1-, 2-, 3-, 4- and 5-year survival, respectively. This prognostic gene signature was identified as an independent risk factor for LUAD and was able to more accurately predict prognosis in comparison to other known clinical parameters, as shown via comprehensive survival analysis. GSEA enrichment revealed that that KIF14, KIF18B and KIF20A mediated basic cell physiology through the regulation of the cell cycle, DNA replication, and DNA repair biological processes and pathways. On the whole, the findings of this study identified 23 KIF genes that were DEGs between LUAD tumor and adjacent non-cancerous tissues. In total, 8 of these genes had the potential to function as prognostic and diagnostic biomarkers in patients with LUAD.

Diagnostic and prognostic value of WNT family gene expression in hepatitis B virus‑related hepatocellular carcinoma

The aim of the present study was to investigate the diagnostic and prognostic value of Wingless-type MMTV integration site (WNT) gene family expression in patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). The clinical data of the patients and gene expression levels were downloaded from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Receiver operating characteristic curve analysis was used to investigate the diagnostic value of WNT genes. Cox proportional hazard regression analysis and Kaplan-Meier survival analysis were performed to evaluate the association of WNT gene expression level with overall survival (OS) and recurrence-free survival (RFS). A nomogram was constructed for the prediction of prognosis. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated. Diagnostic receiver operating characteristic curve analysis suggested that WNT2 had a high diagnostic value, with an area under the curve (AUC) of >0.800 (P<0.0001, AUC=0.810, 95% CI: 0.767–0.852). Survival analysis indicated that the expression level of WNT1 was significantly associated with OS and RFS (adjusted P=0.033, adjusted HR=0.607, 95% CI: 0.384–0.960; and adjusted P=0.007, adjusted HR=0.592, 95% CI: 0.404–0.868, respectively). In the TCGA validation cohort, we also observed that WNT2 was significantly differentially expressed between HCC tissues and adjacent non-tumor tissues, and WNT1 was associated with both the OS and RFS of HCC. Therefore, through the GSE14520 HBV-related HCC cohort we concluded that WNT2 may serve as a diagnostic biomarker and WNT1 may serve as a prognostic biomarker. These results may also be extended to TCGA HCC verification cohort.

Integrated analysis of competing endogenous RNA network revealing potential prognostic biomarkers of hepatocellular carcinoma

Objective: The goal of our study is to identify a competing endogenous RNA (ceRNA) network using dysregulated RNAs between HCC tumors and the adjacent normal liver tissues from The Cancer Genome Atlas (TCGA) datasets, and to investigate underlying prognostic indicators in hepatocellular carcinoma (HCC) patients.

Methods: All of the RNA- and miRNA-sequencing datasets of HCC were obtained from TCGA, and dysregulated RNAs between HCC tumors and the adjacent normal liver tissues were investigated by DESeq and edgeR algorithm. Survival analysis was used to confirm underlying prognostic indicators.

Results: In the present study, we constructed a ceRNA network based on 16 differentially expressed genes (DEGs), 7 differentially expressed microRNAs and 34 differentially expressed long non-coding RNAs (DELs). Among these dysregulated RNAs, three DELs (AP002478.1, HTR2A-AS1, and ERVMER61-1) and six DEGs (enhancer of zeste homolog 2 [EZH2], kinesin family member 23 [KIF23], chromobox 2 [CBX2], centrosomal protein 55 [CEP55], cell division cycle 25A [CDC25A], and claspin [CLSPN]) were used for construct a prognostic signature for HCC overall survival (OS), and performed well in HCC OS (adjusted P<0.0001, adjusted hazard ratio = 2.761, 95% confidence interval = 1.838-4.147). Comprehensive survival analysis demonstrated that this prognostic signature may be act as an independent prognostic indicator of HCC OS. Functional assessment of these dysregulated DEGs in the ceRNA network and gene set enrichment of this prognostic signature suggest that both were enriched in the biological processes and pathways of the cell cycle, cell division and cell proliferation.

Conclusions: Our current study constructed a ceRNA network for HCC, and developed a prognostic signature that may act as an independent indicator for HCC OS.

Use of Genome-Scale Integrated Analysis to Identify Key Genes and Potential Molecular Mechanisms in Recurrence of Lower-Grade Brain Glioma

BACKGROUND The aim of this study was to identify gene signals for lower-grade glioma (LGG) and to assess their potential as recurrence biomarkers. MATERIAL AND METHODS An LGG-related mRNA sequencing dataset was downloaded from The Cancer Genome Atlas (TCGA) Informix. Multiple bioinformatics analysis methods were used to identify key genes and potential molecular mechanisms in recurrence of LGG. RESULTS A total of 326 differentially-expressed genes (DEGs), were identified from 511 primary LGG tumor and 18 recurrent samples. Gene ontology (GO) analysis revealed that the DEGs were implicated in cell differentiation, neuron differentiation, negative regulation of neuron differentiation, and cell proliferation in the forebrain. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database suggests that DEGs are associated with proteoglycans in cancer, the Wnt signaling pathway, ECM-receptor interaction, the PI3K-Akt signaling pathway, transcriptional deregulation in cancer, and the Hippo signaling pathway. The hub DEGs in the protein-protein interaction network are apolipoprotein A2 (APOA2), collagen type III alpha 1 chain (COL3A1), collagen type I alpha 1 chain (COL1A1), tyrosinase (TYR), collagen type I alpha 2 chain (COL1A2), neurotensin (NTS), collagen type V alpha 1 chain (COL5A1), poly(A) polymerase beta (PAPOLB), insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1), and anomalous homeobox (ANHX). GSEA revealed that the following biological processes may associated with LGG recurrence: cell cycle, DNA replication and repair, regulation of apoptosis, neuronal differentiation, and Wnt signaling pathway. CONCLUSIONS Our study demonstrated that hub DEGs may assist in the molecular understanding of LGG recurrence. These findings still need further molecular studies to identify the assignment of DEGs in LGG.

Investigation of the clinical significance and prospective molecular mechanisms of cystatin genes in patients with hepatitis B virus‑related hepatocellular carcinoma

The present study aimed to investigate the clinical significance and prospective molecular mechanism of cystatin (CST) genes in patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). The role of CST genes in the molecular mechanism of HCC was revealed through bioinformatics analysis. The clinical significance of CST genes was investigated using GSE14520-derived data from patients with HBV-related HCC. Gene set enrichment analysis (GSEA) was used to identify pathways in which the CST genes were enriched, as well as the association between these pathways and HCC. The expression levels of CST1, CST2, CST5, CSTA and CSTB genes were higher in HCC tissue compared with in normal tissue; conversely, CST3 and CST7 were reduced in HCC tissue. Subsequent receiver operating characteristic analysis of the CST genes demonstrated that CST7 and CSTB genes may function as potential diagnostic markers for HCC. Furthermore, the expression levels of CST6 and CST7 were strongly associated with recurrence-free survival and overall survival of patients with HBV-related HCC. GSEA of the CST genes revealed that CST7 was significantly enriched in tumor evasion and tolerogenicity, cancer progenitors, liver cancer late recurrence, liver cancer progression and several liver cancer subclasses. In addition, CST genes demonstrated homology in terms of protein structure and were revealed to be strongly co-expressed. The present findings suggested that CST7 and CSTB genes may serve as potential prognostic and diagnostic biomarkers for HCC.

Diagnostic and prognostic value of mRNA expression of phospholipase C β family genes in hepatitis B virus‑associated hepatocellular carcinoma

Four phospholipase C β (PLCB) isoforms, PLCB1, PLCB2, PLCB3 and PLCB4, have been previously investigated regarding their roles in the metabolism of inositol lipids and cancer. The present study aimed to explore the association between PLCB1-4 and hepatocellular carcinoma (HCC). Data from 212 patients with hepatitis B virus-associated HCC were used to analyze the diagnostic and prognostic significance of PLCB genes in. A nomogram predicted the survival probability. Gene set enrichment analysis explored gene ontology terms and the metabolic pathways associated with PLCB genes. Validation of the prognostic values of PLCB genes was performed using the Gene Expression Profiling Interactive Analysis website. PLCB1 and PLCB2 were revealed to have diagnostic value for HCC (0.869 and 0.836 area under the curve, respectively; both P≤0.05). The combination analysis of these genes had an advantage over each alone (0.905 PLCB1 and PLCB2, and 0.877 PLCB1 and PLCB3 area under the curve; P≤0.05). PLCB1 was associated with overall survival (OS) and recurrence-free survival (RFS; adjusted P=0.002 and P=0.001, respectively). A nomogram predicted survival probability of patients with HCC at 1, 3- and 5-years. Gene set enrichment analysis indicated that PLCB1 and PLCB2 are involved in the cell cycle, cell division and the PPAR signaling pathway, among other functions. Validation using GEPIA revealed that PLCB1 and PLCB2 were associated with OS and PLCB1 and PLCB4 were associated with RFS. PLCB1 and PLCB2 exhibited diagnostic value for HCC and their combination had an advantage over each individually. PLCB1 has OS and RFS prognostic value for patients with HCC.

Diagnostic and prognostic values of the mRNA expression of excision repair cross-complementation enzymes in hepatitis B virus-related hepatocellular carcinoma

Background

The current study aims at using the whole genome expression profile chips for systematically investigating the diagnostic and prognostic values of excision repair cross-complementation (ERCC) genes in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC).

Materials and methods

Whole genome expression profile chips were obtained from the GSE14520. The receiver-operating characteristic (ROC) curve, survival analysis, and nomogram were used to investigate the diagnostic and prognostic values of ERCC genes. Investigation of the potential function of ERCC8 was carried out by gene set enrichment analysis (GSEA) and genome-wide coexpression analysis.

Results

ROC analysis suggests that six ERCC genes (ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, and ERCC8) were dysregulated and may have potential to distinguish between HBV-related HCC tumor and paracancerous tissues (area under the curve of ROC ranged from 0.623 to 0.744). Survival analysis demonstrated that high ERCC8 expression was associated with a significantly decreased risk of recurrence (adjusted P=0.021; HR=0.643; 95% CI=0.442–0.937) and death (adjusted P=0.049; HR=0.631; 95% CI=0.399–0.998) in HBV-related HCC. Then, we also developed two nomograms for the HBV-related HCC individualized prognosis predictions. GSEA suggests that the high expression of ERCC8 may have involvement in the energy metabolism biological processes. As the genome-wide coexpression analysis and functional assessment of ERCC8 suggest, those coexpressed genes were significantly enriched in multiple biological processes of DNA damage and repair.

Conclusion

The present study indicates that six ERCC genes (ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, and ERCC8) were dysregulated between HBV-related HCC tumor and paracancerous tissues and that the mRNA expression of ERCC8 may serve as a potential biomarker for the HBV-related HCC prognosis.