High expression of RPL27A predicts poor prognosis in patients with hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common cancers in the digestive system with rapid progression and poor prognosis. Recent studies have shown that RPL27A could be used as a biomarker for a variety of cancers, but its role in HCC is not clear. METHOD: We analyzed the expression of RPL27A in the pan-cancer analysis and analyzed the relationship between the expression of RPL27A and the clinical features and prognosis of patients with HCC. We evaluated the expression difference of RPL27A in HCC tissues and paired normal adjacent tissues using immunohistochemistry. Furthermore, we analyzed the co-expression genes of RPL27A and used them to explore the possible mechanism of RPL27A and screen hub genes effecting HCC. In addition, we studied the role of RPL27A in immune infiltration and mutation. RESULTS: We found that the expression level of RPL27A increased in a variety of cancers, including HCC. In HCC patients, the high expression of RPL27A was related to progression and poor prognosis as an independent predictor. We also constructed a protein interaction network through co-expression gene analysis of RPL27A and screened 9 hub genes. Enrichment analysis showed that co-expression genes were associated with ribosome pathway, viral replication, nuclear-transcribed mRNA catabolic process, and nonsense-mediated decay. We found that the expression level of RPL27A was closely related to TP53 mutation and immune infiltration in HCC. CONCLUSION: RPL27A might become a biomarker in the diagnosis, treatment, and follow-up of patients with HCC.

Clinicopathological value of hematopoietic cell kinase overexpression in laryngeal squamous cell carcinoma tissues.

Laryngeal squamous cell carcinoma (LSCC) is the most lethal cancer in head and neck tumors. Although hematopoietic cell kinase (HCK) has been proven to be an oncogene in several solid tumors, its roles in LSCC remain obscure. This is the first study to evaluate the clinical value of HCK in LSCC, with the aim of exploring its expression status and potential molecular mechanisms underlying LSCC. LSCC tissue-derived gene chips and RNA-seq data were collected for a quantitive integration of HCK mRNA expression level. To confirm the protein expression level of HCK, a total of 82 LSCC tissue specimens and 56 non-tumor laryngeal epithelial controls were collected for in-house tissue microarrays and immunohistochemical staining. Kaplan-Meier curves were generated to determine the ability of HCK in predicting overall survival, progress-free survival, and disease-free survival of LSCC patients. LSCC overexpressed genes and HCK co-expressed genes were intersected to preliminarily explore the enriched signaling pathways of HCK. It was noticed that HCK mRNA was markedly overexpressed in 323 LSCC tissues compared with 196 non-LSCC controls (standardized mean difference = 0.81, p < 0.0001). Upregulated HCK mRNA displayed a moderate discriminatory ability between LSCC tissues and non-tumor laryngeal epithelial controls (area under the curve = 0.78, sensitivity = 0.76, specificity = 0.68). The higher expression level of HCK mRNA could predict worse overall survival and disease-free survival for LSCC patients (p = 0.041 and p = 0.013). Lastly, upregulated co-expression genes of HCK were significantly enriched in leukocyte cell-cell adhesion, secretory granule membrane, and extracellular matrix structural constituent. Immune-related pathways were the predominantly activated signals, such as cytokine-cytokine receptor interaction, Th17 cell differentiation, and Toll-like receptor signaling pathway. In conclusion, HCK was upregulated in LSCC tissues and could be utilized as a risk predictor. HCK may promote the development of LSCC by disturbing immune signaling pathways.

Identification of Hub Genes Associated with Progression and Prognosis of Bladder Cancer by Integrated Bioinformatics Analysis.

BACKGROUND: Bladder cancer (BLCA) is an extremely common carcinoma of the urinary system that has a high incidence of relapse. Although intensive studies have investigated its pathology in the past decades, there are significant knowledge gaps regarding the characterization of the molecular processes underlying the progression of disease and consequently its prognosis. The purpose of current research was to identify significant genes that could serve as prognostic and progression biomarkers. METHODS: Gene expression profiles were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Differential gene expression analysis (DGEA) and weighted gene co-expression network analysis (WGCNA) were conducted to recognize differential co-expression genes. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to explore gene function. Moreover, protein-protein interactions (PPI) network, overall survival (OS) and disease-free survival (DFS) were used to identify survival-related hub genes. Additionally, associations between these gene's expression and clinical parameters were determined. Finally, the Human Protein Atlas (HPA) database and qRT-PCR were used to validate gene's expression. RESULTS: About 124 differential co-expression genes were identified. These genes were mainly enriched in muscle system process and muscle contraction (biological process, BP), contractile fiber, myofibril, sarcomere, focal adhesion and cell-substrate junction (cellular component, CC) and actin binding (molecular function, MF) in GO enrichment analysis, while enriched in vascular smooth muscle contraction, focal adhesion, cardiac muscle contraction, hypertrophic cardiomyopathy, dilated cardiomyopathy and regulation of actin cytoskeleton in KEGG analysis. Furthermore, five survival-related hub genes (MYH11, ACTA2, CALD1, TPM1, MYLK) were identified via OS and DFS. In addition, these survival-related gene's expression was correlated with grade, stage and TNM stage. Finally, all survival-related hub genes were determined to be down-regulated in BLCA tissues by qRT-PCR and HPA databases. CONCLUSIONS: Our current study verified five new key genes in BLCA, which may participate in the prognosis and progression and serve as novel biomarkers of BLCA.

SPINK5 is a Prognostic Biomarker Associated With the Progression and Prognosis of Laryngeal Squamous Cell Carcinoma Identified by Weighted Gene Co-Expression Network Analysis.

Laryngeal squamous cell carcinoma (LSCC) is one of the most common types of head and neck squamous cell carcinomas (HNSCC) and is the second most prevalent malignancy occurring in the head and neck or respiratory tract, with a high incidence and mortality rate. Survival is limited for patients with LSCC. To identify more biomarkers associated with the prognosis of patients with LSCC, using bioinformatics analysis, this study used The Cancer Genome Atlas (TCGA) LSCC dataset and gene expression profiles of GSE59102 from the Gene Expression Omnibus (GEO). Eighty-one differentially co-expressed genes were identified by weighted gene co-expression network analysis (WGCNA). Next, 10 hub genes (PPL, KRT78, CRNN, PTK7, SCEL, AGRN, SPINK5, AIF1L, EMP1, and PPP1R3C) were screened from a protein-protein interaction (PPI) network. Based on survival analysis, SPINK5 was significantly correlated with survival time in LSCC patients. After verification in the TCGA and HPA databases, SPINK5 was selected as a prognostic biomarker. Finally, the GSEA results showed that downregulation of SPINK5 gene expression may promote tumorigenesis and the development of cancers by the "BASAL CELL CARCINOMA" pathway, and it has been implicated in disrupting DNA damage and repair pathways. Collectively, SPINK5 may serve as a potential prognostic biomarker in LSCC.

Identification of Hub Genes Associated With Tuberculous Pleurisy by Integrated Bioinformatics Analysis.

Improving the understanding of the molecular mechanism of tuberculous pleurisy is required to develop diagnosis and new therapy strategies of targeted genes. The purpose of this study is to identify important genes related to tuberculous pleurisy. In this study, the expression profile obtained by sequencing the surgically resected pleural tissue was used to explore the differentially co-expressed genes between tuberculous pleurisy tissue and normal tissue. 29 differentially co-expressed genes were screened by weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis methods. According to the functional annotation analysis of R clusterProfiler software package, these genes are mainly enriched in nucleotide-sugar biosynthetic process (biological process), ficolin-1-rich granule lumen (cell component), and electron transfer activity (molecular function). In addition, in the protein-protein interaction (PPI) network, 20 hub genes of DEGs and WCGNA genes were identified using the CytoHubba plug-in of Cytoscape. In the end, RPL17 was identified as a gene that can be the biomarker of tuberculous pleurisy. At the same time, there are seven genes that may have relationship with the disease (UBA7, NDUFB8, UQCRFS1, JUNB, PSMC4, PHPT1, and MAPK11).

Analysis of deubiquitinase OTUD5 as a biomarker and therapeutic target for cervical cancer by bioinformatic analysis.

OTU deubiquitinase 5 (OTUD5), as a member of the ovarian tumor protease (OTU) family, was previously reported to play important roles in DNA repair and immunity. However, little is known about its function in tumors. Cervical cancer is a malignant tumor that seriously endangers the lives of women. Here, we found that low expression of OTUD5 in cervical cancer is associated with poor prognosis. Its expression is associated with tumor stage, metastatic nodes and tumor subtypes such as those related to the phosphatidylinositol-3-kinase (PI3K)-AKT signaling, epithelial-mesenchymal transition (EMT) and hormones. In addtion, we analyzed the coexpressed genes, related miRNAs, transcription factors, kinases, E3s and interacting proteins of OTUD5. We demonstrated that OTUD5 affects the expression levels of WD repeat domain 45 (WDR45), ubiquitin-specific peptidase 11 (USP11), GRIP1 associated protein 1 (GRIPAP1) and RNA binding motif protein 10 (RBM10). Moreover, hsa-mir-137, hsa-mir-1913, hsa-mir-937, hsa-mir-607, hsa-mir-3149 and hsa-mir-144 may inhibit the expression of OTUD5. Furthermore, we performed enrichment analysis of 22 coexpressed genes, 33 related miRNAs and 30 interacting proteins. In addition to ubiquitination and immunology related processes, they also participate in Hippo signaling, insulin signaling, EMT, histone methylation and phosphorylation kinase binding. Our study for the first time analyzed the expression of OTUD5 in cervical cancer and its relationship with clinicopathology and provided new insights for further study of its regulatory mechanism in tumors.

Identification of Hub Genes Associated With Development of Head and Neck Squamous Cell Carcinoma by Integrated Bioinformatics Analysis.

Improved insight into the molecular mechanisms of head and neck squamous cell carcinoma (HNSCC) is required to predict prognosis and develop a new therapeutic strategy for targeted genes. The aim of this study is to identify significant genes associated with HNSCC and to further analyze its prognostic significance. In our study, the cancer genome atlas (TCGA) HNSCC database and the gene expression profiles of GSE6631 from the Gene Expression Omnibus (GEO) were used to explore the differential co-expression genes in HNSCC compared with normal tissues. A total of 29 differential co-expression genes were screened out by Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis methods. As suggested in functional annotation analysis using the R clusterProfiler package, these genes were mainly enriched in epidermis development and differentiation (biological process), apical plasma membrane and cell-cell junction (cellular component), and enzyme inhibitor activity (molecular function). Furthermore, in a protein-protein interaction (PPI) network containing 21 nodes and 25 edges, the ten hub genes (S100A8, S100A9, IL1RN, CSTA, ANXA1, KRT4, TGM3, SCEL, PPL, and PSCA) were identified using the CytoHubba plugin of Cytoscape. The expression of the ten hub genes were all downregulated in HNSCC tissues compared with normal tissues. Based on survival analysis, the lower expression of CSTA was associated with worse overall survival (OS) in patients with HNSCC. Finally, the protein level of CSTA, which was validated by the Human Protein Atlas (HPA) database, was down-regulated consistently with mRNA levels in head and neck cancer samples. In summary, our study demonstrated that a survival-related gene is highly correlated with head and neck cancer development. Thus, CSTA may play important roles in the progression of head and neck cancer and serve as a potential biomarker for future diagnosis and treatment.

Potential molecular mechanism of ACE gene at different time points in STEMI patients based on genome-wide microarray dataset.

BACKGROUND: This study aimed to investigate the angiotensin converting enzyme (ACE) co-expression genes and their pathways involved in ST-segment elevation myocardial infarction (STEMI) at different time points. METHODS: The array data set of GSE59867 was examined for the ACE co-expression genes in peripheral blood samples from 111 patients with STEMI at four time points (admission, discharge, and 1 and 6 months after MI). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, Gene Ontology (GO) annotation and protein-protein interaction (PPI) of the co-expression genes were determined using online analytical tools. The Cytoscape software was used to create modules and hub genes. RESULTS: The number of biological processes (BP), cellular components (CC) and molecular functions (MF) was 43, 22 and 24 at admission; 18, 19 and 11 at discharge; 30, 37 and 21 at 1 month after MI; and 12, 19 and 14 at 6 months after MI; respectively. There were 6 BP, 8 CC and 4 MF enriched at every time point. The co-expression genes were substantially enriched in 12, 5, 6 and 14 KEGG pathways at the four time points, respectively, but no KEGG pathway was found to be common in all time points. We identified 132 intersectional co-expression genes (90 positive and 42 negative) from the four time points and 17 BP, 13 CC, 11 MF and 7 KEGG pathways were enriched. In addition, the PPI network contained 129 nodes and 570 edges, and only 1 module was identified to be significantly enriched in just 1 BP (chromatin-mediated maintenance of transcription). CONCLUSIONS: The results of the present study showed that the ACE co-expression genes and their pathways involved in STEMI were significantly different at four different time points. These findings may be helpful for further understanding the functions and roles of ACE in different stages of STEMI, and providing reference for the treatment of STEMI.