Bioinformatics analysis of molecular genetic targets and key pathways for hepatocellular carcinoma

Prognostic Hypoxia-Angiogenesis-Related Gene Signature in Hepatocellular Carcinoma, in Which HILPDA Contributes to Tumor Progression

Objective

Hepatocellular carcinoma (HCC) is the predominant form of liver cancer. Hypoxia can be involved in HCC tumor growth, invasion and metastasis through inducing angiogenesis. Nevertheless, the assessment of the impact of hypoxia and angiogenesis on the prognosis of HCC remains inadequate.

Methods

According to hypoxia-angiogenesis-related genes (HARGs) expression information and clinical data from patients within the Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort, we constructed a prognostic model (HARG-score) using bioinformatic tools. In addition to assessing the predictive ability of this prognostic model in both Liver Cancer-Riken-Japan (LIRI-JP) and GSE14520 cohorts, we analyzed the correlation between HARG-score and clinical characteristics, immune infiltration and immunotherapy efficacy. Moreover, we investigated the exact role and underlying mechanism of key HARGs through molecular experiments.

Results

We constructed a 5-gene prognostic model HARG-score consisting of hypoxia-inducible lipid droplet-associated (HILPDA), erythropoietin (EPO), solute carrier family 2 member 1 (SLC2A1), proteasome subunit alpha type 7 (PSMA7) and cAMP responsive element-binding protein 1 (CREB1) through differentially expressed HARGs. The findings demonstrated that HARG-score was a good predictor of the prognosis of HCC patients from distinct cohorts and was correlated with clinical characteristics and immune infiltration. Furthermore, the HARG-score was identified as an independent prognostic factor. Lower HARG-score implied greater immunotherapy efficacy and better response. The expression and prognostic significance of these 5 genes were additionally validated in clinical data. In addition, experimental data revealed that the key gene HILPDA contributes to the progression of HCC through facilitating angiogenesis and affecting the expression of cytotoxic T-lymphocyte-associated protein 4 (CTLA4).

Conclusion

HARG-score has promising applications in prognosis prediction of HCC patients, in which HILPDA may be a latent prognostic biomarker and therapeutic target, providing a foundation for further research and treatment of HCC.

A comprehensive meta-analysis of transcriptome data to identify signature genes associated with pancreatic ductal adenocarcinoma

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) has a five-year survival rate of less than 5%. Absence of symptoms at primary tumor stages, as well as high aggressiveness of the tumor can lead to high mortality in cancer patients. Most patients are recognized at the advanced or metastatic stage without surgical symptom, because of the lack of reliable early diagnostic biomarkers. The objective of this work was to identify potential cancer biomarkers by integrating transcriptome data.

METHODS

Several transcriptomic datasets comprising of 11 microarrays were retrieved from the GEO database. After pre-processing, a meta-analysis was applied to identify differentially expressed genes (DEGs) between tumor and nontumor samples for datasets. Next, co-expression analysis, functional enrichment and survival analyses were used to determine the functional properties of DEGs and identify potential prognostic biomarkers. In addition, some regulatory factors involved in PDAC including transcription factors (TFs), protein kinases (PKs), and miRNAs were identified.

RESULTS

After applying meta-analysis, 1074 DEGs including 539 down- and 535 up-regulated genes were identified. Pathway enrichment analyzes using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed that DEGs were significantly enriched in the HIF-1 signaling pathway and focal adhesion. The results also showed that some of the DEGs were assigned to TFs that belonged to 23 conserved families. Sixty-four PKs were identified among the DEGs that showed the CAMK family was the most abundant group. Moreover, investigation of corresponding upstream regions of DEGs identified 11 conserved sequence motifs. Furthermore, weighted gene co-expression network analysis (WGCNA) identified 8 modules, more of them were significantly enriched in Ras signaling, p53 signaling, MAPK signaling pathways. In addition, several hubs in modules were identified, including EMP1, EVL, ELP5, DEF8, MTERF4, GLUP1, CAPN1, IGF1R, HSD17B14, TOM1L2 and RAB11FIP3. According to survival analysis, it was identified that the expression levels of two genes, EMP1 and RAB11FIP3 are related to prognosis.

CONCLUSION

We identified several genes critical for PDAC based on meta-analysis and system biology approach. These genes may serve as potential targets for the treatment and prognosis of PDAC.

Pan-caner analysis identifies PSMA7 as a targets for amplification at 20q13.33 in tumorigenesis

The chromosome 20 long arm (20q) is one of the genomic hotspots where copy number alterations frequently occur in multiple types of tumors. However, it remains elusive which genes are implicated in 20q-related tumorigenesis. Here, by querying TCGA and GEO databases, we observed frequent copy number amplification at 20q and the chromosome subband 20q13.33 was amplificated in multiple cancers. Among those genes at 20q13.33, PSMA7 was found with the strongest correlation with cancers. Further analysis revealed that PSMA7 amplification was the most frequent genetic alteration event conferring adverse prognosis in various cancers. Consistent with the strong positive correlation between PSMA7 amplification and gene expression, elevated PSMA7 expression was observed in 20 of 33 types of cancers with a close link to adverse outcomes in certain tumors. In addition, PSMA7 was essential for the growth of almost 1095 cancer lines. Mechanistically, aberrant PSMA7 most probably influenced the proteasome and protease-related pathways to promote tumorigenesis and might be antagonized by several compounds, e.g., Docetaxel in relevant cancers. The current in-depth pan-cancer analysis refines our understanding of the crucial oncogenic role of copy number amplifications at PSMA7 loci at the novel chromosome amplicon 20q13.33 across different tumors.

PSMA7 promotes the malignant proliferation of esophageal cancer

Background

It is important to explore novel molecules that play a key role in esophageal cancer (ESCA) progression.

Methods

Two ESCA tissue expression profile microarrays (GSE92396 and GSE17351) data from GEO were downloaded, and differentially expressed genes (DEGs) were analyzed using GEO2R. The DEGs common to both microarrays were analyzed for protein-protein interactions, KEGG and GO. The altered expression of proteasome 20S subunit α 7 (PSMA7) in ESCA tissues was analyzed using information from publicly available databases (GEO, TCGA, TNMplot). PSMA7 was overexpressed or knocked down in Eca109 and KYSE150 cells using transfection, and the effects on cell proliferation, migration, invasion and apoptosis were examined using CCK-8, Transwell, and flow cytometry experiments.

Results

284 common DEGs were identified, and 10 core proteins, HSP90AA1, AURKA, CDC6, PCNA, MCM5, KAT2B, GRB2, MYBL2, PSMA7, and CKAP5, involved in ESCA progression were identified. PSMA7 mRNA level was significantly increased in ESCA tissues. PSMA7 overexpression significantly promoted the proliferation, migration and invasion of Eca109 and KYSE150 cells, and significantly promoted apoptosis. In contrast, PSMA7 knockdown inhibited their proliferation and motility, and significantly suppressed apoptosis.

Conclusion

This study analyzed multiple proteins that may play a key role in ESCA progression, and identified the pro-cancer role of PSMA7.

Comprehensive analysis of the role of Netrin G1 (NTNG1) in hepatocellular carcinoma cells

Netrin G1 (NTNG1) is a member of the Netrin family and plays a crucial role in various human cancers. However, the molecular functions of NTNG1 in HCC and the underlying mechanisms remain unclear. HCC expression data was obtained from the GEO database and analyzed using various bioinformatics tools. The expression of NTNG1 in HCC tissues and liver cancer cells was evaluated through RT-qPCR and western blotting. Cells with stable NTNG1 overexpression and knockdown were established, and CCK-8, colony formation, and flow cytometry assays were conducted in vitro. The xenograft model was utilized to verify the tumorigenesis capacity of NTNG1 in vivo. IHC was employed to analyze the expression of NTNG1 and CD163 proteins. HCC-specific genes were screened, followed by functional enrichment and immune cell infiltration analysis. Finally, the Co-IP was used to detect the interaction between NTNG1 and N-cadherin. NTNG1 was highly expressed in HCC tissues and liver cancer cells, and associated with significantly poorer OS rates. In addition, NTNG1 overexpression in liver cancer cells significantly increased their proliferation, colony growth, invasion, migration, and EMT, while inhibiting apoptosis. Bioinformatics analyses indicated that NTNG1 was closely related to EMT and tumor infiltration. IHC staining revealed a positive correlation between NTNG1 expression and CD163 in HCC tissues. Additionally, an EMT inhibitor attenuated the expression levels of EMT-related markers and counteracted the effects of NTNG1 overexpression in liver cancer cells. This study is the first to identify NTNG1 as a potential therapeutic target in HCC, promoting tumor development and progression by regulating EMT.

Transcriptional pathways linked to fetal and maternal hepatic dysfunction caused by gestational exposure to perfluorooctanoic acid (PFOA) or hexafluoropropylene oxide-dimer acid (HFPO-DA or GenX) in CD-1 mice

Per- and polyfluoroalkyl substances (PFAS) comprise a diverse class of chemicals used in industrial processes, consumer products, and fire-fighting foams which have become environmental pollutants of concern due to their persistence, ubiquity, and associations with adverse human health outcomes, including in pregnant persons and their offspring. Multiple PFAS are associated with adverse liver outcomes in adult humans and toxicological models, but effects on the developing liver are not fully described. Here we performed transcriptomic analyses in the mouse to investigate the molecular mechanisms of hepatic toxicity in the dam and its fetus after exposure to two different PFAS, perfluorooctanoic acid (PFOA) and its replacement, hexafluoropropylene oxide-dimer acid (HFPO-DA, known as GenX). Pregnant CD-1 mice were exposed via oral gavage from embryonic day (E) 1.5-17.5 to PFOA (0, 1, or 5 mg/kg-d) or GenX (0, 2, or 10 mg/kg-d). Maternal and fetal liver RNA was isolated (N = 5 per dose/group) and the transcriptome analyzed by Affymetrix Array. Differentially expressed genes (DEG) and differentially enriched pathways (DEP) were obtained. DEG patterns were similar in maternal liver for 5 mg/kg PFOA, 2 mg/kg GenX, and 10 mg/kg GenX (R2: 0.46-0.66). DEG patterns were similar across all 4 dose groups in fetal liver (R2: 0.59-0.81). There were more DEGs in fetal liver compared to maternal liver at the low doses for both PFOA (fetal = 69, maternal = 8) and GenX (fetal = 154, maternal = 93). Upregulated DEPs identified across all groups included Fatty Acid Metabolism, Peroxisome, Oxidative Phosphorylation, Adipogenesis, and Bile Acid Metabolism. Transcriptome-phenotype correlation analyses demonstrated > 1000 maternal liver DEGs were significantly correlated with maternal relative liver weight (R2 >0.92). These findings show shared biological pathways of liver toxicity for PFOA and GenX in maternal and fetal livers in CD-1 mice. The limited overlap in specific DEGs between the dam and fetus suggests the developing liver responds differently than the adult liver to these chemical stressors. This work helps define mechanisms of hepatic toxicity of two structurally unique PFAS and may help predict latent consequences of developmental exposure.

Network analysis of hepatocellular carcinoma liquid biopsies augmented by single-cell sequencing data

Liquid biopsy, the analysis of body fluids, represents a promising approach for disease diagnosis and prognosis with minimal intervention. Sequencing cell-free RNA derived from liquid biopsies has been very promising for the diagnosis of several diseases. Cancer research, in particular, has emerged as a prominent candidate since early diagnosis has been shown to be a critical determinant of disease prognosis. Although high-throughput analysis of liquid biopsies has uncovered many differentially expressed genes in the context of cancer, the functional connection between these genes is not investigated in depth. An important approach to remedy this issue is the construction of gene networks which describes the correlation patterns between different genes, thereby allowing to infer their functional organization. In this study, we aimed at characterizing extracellular transcriptome gene networks of hepatocellular carcinoma patients compared to healthy controls. Our analysis revealed a number of genes previously associated with hepatocellular carcinoma and uncovered their association network in the blood. Our study thus demonstrates the feasibility of performing gene co-expression network analysis from cell-free RNA data and its utility in studying hepatocellular carcinoma. Furthermore, we augmented cell-free RNA network analysis with single-cell RNA sequencing data which enables the contextualization of the identified network modules with cell-type specific transcriptomes from the liver.

Overexpression of CISD1 Predicts Worse Survival in Hepatocarcinoma Patients

Background

Ferroptosis plays a vital role in hepatocellular carcinoma (HCC). CISD1 is known to regulate ferroptosis negatively. However, the correlations of CISD1 to prognosis in HCC and its potential mechanism remain unclear.

Aim

To investigate the expression level and prognostic value of CISD1 in HCC.

Methods

Gene expression and clinical data for 33 cancer types in TCGA were downloaded from the UCSC Xena platform. Pan-cancer analysis was performed to determine the expression profile and prognostic value of CISD1 in human cancers. GEO datasets and Human Protein Atlas (HPA) were used to verify the mRNA and protein expression levels. The influence of CISD1 on clinical prognosis in HCC was evaluated using a Kaplan-Meier plotter. The PPI network was constructed using the STRING database and Cytoscape. GO and KEGG pathways were constructed using the “clusterProfiler” R package with the FDR cutoff of 0.05. The methylation at the CISD1 promoter was detected using UALCAN and GEO datasets. The correlations between CISD1 and HCC immune infiltrates were investigated via TIMER.

Results

Pan-cancer analysis of TCGA data showed that CISD1 is differentially expressed in multiple tumors. Data of gene expression microarrays reveal that the mRNA expression of CISD1 is higher in HCC than that in normal tissue. The protein level of CISD1, validated by the Human Protein Atlas (HPA) database, was upregulated consistently with mRNA levels in HCC samples. High CISD1 expression was associated with better overall survival (OS), disease-free survival (DFS), disease-specific survival (DSS), and progression-free survival (PFS) in LGG, but with poorer OS, DFS, DSS, and PFS in LIHC. Protein-protein interaction (PPI) analysis and GO/KEGG analysis showed that the PPI network and GO term of CISD1 were mainly associated with energy and iron metabolism. Promoter hypomethylation correlated with overexpression of CISD1. CISD1 expression was positively correlated with infiltrating levels of CD8+ T cells, macrophages, neutrophils, and dendritic cells (DCs) in HCC.

Conclusions

These findings suggest that hypomethylation of the CISD1 promoter increases its expression in HCC. CISD1 is associated with prognosis and immune infiltrating levels of CD8+ T cells, macrophages, neutrophils, and DCs in HCC patients. These findings suggest that CISD1 can be used as a prognostic biomarker for determining prognosis in HCC.

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.

N6-methyladenosine (m6A) RNA methylation regulator SNRPC is a prognostic biomarker and is correlated with immunotherapy in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common malignancies in the world, and due to its complex pathogenic factors, its prognosis is poor. N6-methyladenosine (m⁶A) RNA methylation plays an important role in the tumorigenesis, progression, and prognosis of many tumors. The m⁶A RNA methylation regulator small nuclear ribonucleoprotein polypeptide C (SNRPC), which encodes one of the specific protein components of the U1 small nuclear ribonucleoprotein (snRNP) particle, has been proven to be related to the prognosis of patients with HCC. However, the effect of SNRPC on the tumor microenvironment and immunotherapy in HCC remains unclear.

Case presentation

The HCC RNA-seq profiles in The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases, including 421 LIHC and 440 LIRI-JP samples, respectively, were used in this study. Both the expression of SNRPC in HCC was upregulated in the TCGA and ICGC databases compared to normal tissues. Next, the expression of SNRPC was validated as a risk factor for prognosis by Kaplan-Meier analysis and employed to establish a nomogram with T pathologic stage. By gene set variation (GSVA) analysis and gene set enrichment (GSEA) analysis, we found that SNRPC was mainly related to protein metabolism and the immune process. Furthermore, the estimation of stromal and immune cells in malignant tumor tissues using expression (ESTIMATE), microenvironment cell population counter (MCP-counter), and single sample GSEA (ssGSEA) algorithms revealed that the high-SNRPC group had a lower stromal score, lower abundance of endothelial cells and fibroblasts, and lower immune infiltration. Ultimately, a tumor immune dysfunction and exclusion (TIDE) analysis revealed that patients in the low-SNRPC group may be more sensitive to immune checkpoint inhibitor therapy.

Conclusion

SNRPC could serve as a promising prognostic and immunotherapeutic marker in HCC and might contribute to new directions and strategies for HCC treatment.

An Integrated Data Analysis of mRNA, miRNA and Signaling Pathways in Pancreatic Cancer

Although many genes and miRNAs have been reported for various cancers, pancreatic cancer's specific genes or miRNAs have not been studied precisely yet. Therefore, we have analyzed the gene and miRNA expression profile of pancreatic cancer data in the gene expression omnibus (GEO) database. The microarray-derived miRNAs and mRNAs were annotated by gene ontology (GO) and signaling pathway analysis. We also recognized mRNAs that were targeted by miRNA through the mirDIP database. An integrated analysis of the microarray revealed that only 6 out of 43 common miRNAs had significant differences in their expression profiles between the tumor and normal groups (P value < 0.05 and |log Fold Changes (logFC)|> 1). The hsa-miR-210 had upregulation, whereas hsa-miR-375, hsa-miR-216a, hsa-miR-217, hsa-miR-216b and hsa-miR-634 had downregulation in pancreatic cancer (PC). The analysis results also revealed 109 common mRNAs by microarray and mirDIP 4.1 databases. Pathway analysis showed that amoebiasis, axon guidance, PI3K-Akt signaling pathway, absorption and focal adhesion, adherens junction, platelet activation, protein digestion, human papillomavirus infection, extracellular matrix (ECM) receptor interaction, and riboflavin metabolism played important roles in pancreatic cancer. GO analysis revealed the significant enrichment in the three terms of biological process, cellular component, and molecular function, which were identified as the most important processes associated strongly with pancreatic cancer. In conclusion, DTL, CDH11, COL5A1, ITGA2, KIF14, SMC4, VCAN, hsa-mir-210, hsa-mir-217, hsa-mir-216a, hsa-mir-216b, hsa-mir-375 and hsa-mir-634 can be reported as the novel diagnostic or even therapeutic markers for the future studies. Also, the hsa-mir-107 and hsa-mir-125a-5p with COL5A1, CDH11 and TGFBR1 genes can be introduced as major miRNA and genes on the miRNA-drug-mRNA network. The new regulatory network created in our study could give a deeper knowledge of the pancreatic cancer.

Clinical implications of TPO and AOX1 in pediatric papillary thyroid carcinoma

BACKGROUND

Thyroid carcinoma is a common pediatric head and neck cancer, of which papillary thyroid cancer (PTC) is the most common type. Previously, we found that thyroid peroxidase (TPO) and aldehyde oxidase 1 (AOX1) were differentially expressed in PTC. This study explored the clinical importance of TPO and AOX1 in the diagnosis and prognosis of PTC in children.

METHODS

Both TPO and AOX1 expression in PTC were analyzed using datasets from Gene Expression Omnibus (GEO). TPO and AOX1 protein levels in plasma from patients with PTC and non-tumor controls were detected via enzyme-linked immunosorbent assay (ELISA). The diagnostic accuracy of TPO and AOX1 was assessed using receiver operating characteristic (ROC) curve analysis. The association between gene expression levels and patient survival was explored using the Kaplan-Meier plotter online database.

RESULTS

The results revealed that TPO and AOX1 expression was significantly downregulated in four independent datasets (GSE33630, GSE27155, GSE3678, and GSE3467). TPO and AOX1 protein levels in blood plasma were significantly decreased in patients with PTC. Quantitative analysis demonstrated that TPO and AOX1 levels in plasma had satisfactory predictive performance and the ability to discriminate PTC from healthy samples. Prognostic analysis demonstrated that low levels of TPO and AOX1 were markedly associated with poor survival in patients with PTC.

CONCLUSIONS

In summary, these results implied that TPO and AOX1 could serve as novel biomarkers for the diagnosis and prognosis of pediatric PTC.

Identification and Validation of Novel Genes in Anaplastic Thyroid Carcinoma via Bioinformatics Analysis

Purpose

The conventional interventions of anaplastic thyroid carcinoma (ATC) patients are mainly through surgery, chemotherapy, and radiotherapy; however, it is hardly to improve survival rate. We aimed to investigate the differential expressed genes (DEGs) between ATC and normal thyroid gland through bioinformatics analysis of the microarray datasets and find new potential therapeutic targets for ATC.

Methods

Microarray datasets GSE9115, GSE29265, GSE33630, GSE53072, and GSE65144 were downloaded from Gene Expression Omnibus (GEO) database. Compared with the normal tissue, GEO2R was conducted to screen the DEGs in each chip under the condition of |log FC| > l, adjusted P‐values (adj. P) < 0.05. The Retrieval of Interacting Genes (STRING) database was used to calculate PPI networks of DEGs with a combined score >0.4 as the cut-off criteria. The hub genes in the PPI network were visualized and selected according to screening conditions in Cytoscape software. In addition, the novel genes in ATC were screened for survival analysis using Kaplan–Meier plotter from those hub genes and validated by RT-qPCR.

Results

A total of 284 overlapping DEGs were obtained, including 121 upregulated and 161 downregulated DEGs. A total of 232 DEGs were selected by STRING database. The 50 hub genes in the PPI network were chosen according to three screening conditions. In addition, the Kaplan–Meier plotter database confirmed that high expressions of ANLN, CENPF, KIF2C, TPX2, and NDC80 were negatively correlated with poor overall survival of ATC patients. Finally, RT-qPCR experiments showed that KIF2C and CENPF were significantly upregulated in ARO cells and CAL-62 cells when compared to Nthy-ori 3–1 cells, TPX2 was upregulated only in CAL-62 cells, while ANLN and NDC80 were obviously decreased in ARO cells and CAL-62 cells.

Conclusion

Our study suggested that CENPF, KIF2C, and TPX2 might play a significant role in the development of ATC, which could be further explored as potential biomarkers for the treatment of ATC.

Construction of a potential microRNA, transcription factor and mRNA regulatory network in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide and the third leading cause of cancer-related death. MicroRNAs and transcription factors (TFs) cooperate to regulate the same target gene, thus affecting the progression of HCC.

Methods

Differentially expressed miRNAs and mRNAs were screened. Functional enrichment analysis of these HCC-related mRNAs was performed, and a protein-protein interaction network was constructed. TFs that regulate these miRNAs and hub genes were also screened.

Results

Ten differentially upregulated miRNAs and 5 differentially downregulated miRNAs were screened. Additionally, 183 downregulated mRNAs and 303 upregulated mRNAs that are potentially bound to these differentially expressed miRNAs were identified. The Kyoto Encyclopedia of Genes and Genomes (KEGG) results showed that the differentially expressed mRNAs were significantly enriched in pathways in cancer, the Wnt signaling pathway, and the Rap1 signaling pathway. Then, 220 TFs were identified for 5 candidate genes of the downregulated mRNAs, and 258 TFs were identified for 9 candidate genes of the upregulated mRNAs. Finally, the 9 upregulated hub genes were related to higher overall survival (OS) in the low-expression group, and 4/5 downregulated hub genes were related to higher OS in the high-expression group.

Conclusions

This study constructed a potential regulatory network between candidate molecules and that need to be further verified. These regulatory relationships are expected to clarify the new molecular mechanisms of the occurrence and development of HCC.

Integrated PPI- and WGCNA-Retrieval of Hub Gene Signatures Shared Between Barrett's Esophagus and Esophageal Adenocarcinoma

Esophageal adenocarcinoma (EAC) is a deadly cancer with high mortality rate, especially in economically advanced countries, while Barrett's esophagus (BE) is reported to be a precursor that strongly increases the risk of EAC. Due to the complexity of these diseases, their molecular mechanisms have not been revealed clearly. This study aims to explore the gene signatures shared between BE and EAC based on integrated network analysis. We obtained EAC- and BE-associated microarray datasets GSE26886, GSE1420, GSE37200, and GSE37203 from the Gene Expression Omnibus and ArrayExpress using systematic meta-analysis. These data were accompanied by clinical data and RNAseq data from The Cancer Genome Atlas (TCGA). Weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis were conducted to explore the relationship between gene sets and clinical traits as well as to discover the key relationships behind the co-expression modules. A differentially expressed gene-based protein-protein interaction (PPI) complex was used to extract hub genes through Cytoscape plugins. As a result, 403 DEGs were excavated, comprising 236 upregulated and 167 downregulated genes, which are involved in the cell cycle and replication pathways. Forty key genes were identified using modules of MCODE, CytoHubba, and CytoNCA with different algorithms. A dark-gray module with 207 genes was identified which having a high correlation with phenotype (gender) in the WGCNA. Furthermore, five shared hub gene signatures (SHGS), namely, pre-mRNA processing factor 4 (PRPF4), serine and arginine-rich splicing factor 1 (SRSF1), heterogeneous nuclear ribonucleoprotein M (HNRNPM), DExH-Box Helicase 9 (DHX9), and origin recognition complex subunit 2 (ORC2), were identified between BE and EAC. SHGS enrichment denotes that RNA metabolism and splicosomes play a key role in esophageal cancer development and progress. We conclude that the PPI complex and WGCNA co-expression network highlight the importance of phenotypic identifying hub gene signatures for BE and EAC.