Liver cancer is a serious threat to public health and has fairly complicated pathogenesis. Therefore, the identification of key genes and pathways is of much importance for clarifying molecular mechanism of hepatocellular carcinoma (HCC) initiation and progression. HCC-associated gene expression dataset was downloaded from Gene Expression Omnibus database. Statistical software R was used for significance analysis of differentially expressed genes (DEGs) between liver cancer samples and normal samples. Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, based on R software, were applied for the identification of pathways in which DEGs significantly enriched. Cytoscape software was for the construction of protein–protein interaction (PPI) network and module analysis to find the hub genes and key pathways. Finally, weighted correlation network analysis (WGCNA) was conducted to further screen critical gene modules with similar expression pattern and explore their biological significance. Significance analysis identified 1230 DEGs with fold change >2, including 632 significantly down-regulated DEGs and 598 significantly up-regulated DEGs. GO term enrichment analysis suggested that up-regulated DEG significantly enriched in immune response, cell adhesion, cell migration, type I interferon signaling pathway, and cell proliferation, and the down-regulated DEG mainly enriched in response to endoplasmic reticulum stress and endoplasmic reticulum unfolded protein response. KEGG pathway analysis found DEGs significantly enriched in five pathways including complement and coagulation cascades, focal adhesion, ECM–receptor interaction, antigen processing and presentation, and protein processing in endoplasmic reticulum. The top 10 hub genes in HCC were separately GMPS, ACACA, ALB, TGFB1, KRAS, ERBB2, BCL2, EGFR, STAT3, and CD8A, which resulted from PPI network. The top 3 gene interaction modules in PPI network enriched in immune response, organ development, and response to other organism, respectively. WGCNA revealed that the confirmed eight gene modules significantly enriched in monooxygenase and oxidoreductase activity, response to endoplasmic reticulum stress, type I interferon signaling pathway, processing, presentation and binding of peptide antigen, cellular response to cadmium and zinc ion, cell locomotion and differentiation, ribonucleoprotein complex and RNA processing, and immune system process, respectively. In conclusion, we identified some key genes and pathways closely related with HCC initiation and progression by a series of bioinformatics analysis on DEGs. These screened genes and pathways provided for a more detailed molecular mechanism underlying HCC occurrence and progression, holding promise for acting as biomarkers and potential therapeutic targets.

Hepatocellular carcinoma (HCC) is one of the most dominant causes of neoplasm-related deaths worldwide. In this study, we identify and characterize HCCL5, a novel cytoplasmic long noncoding RNA (lncRNA), as a crucial oncogene in HCC. HCCL5 promoted cell growth, G1–S transition, invasion, and metastasis while inhibiting apoptosis of HCC cells both in vitro and in vivo. Moreover, HCCL5 was upregulated in TGF-β1-induced classical epithelial-to-mesenchymal transition (EMT) models, and this lncRNA in turn accelerated the EMT phenotype by upregulating the expression of transcription factors Snail, Slug, ZEB1, and Twist1. HCCL5 was transcriptionally driven by ZEB1 via a super-enhancer and was significantly and frequently overexpressed in human HCC tissues, correlating with worse overall survival of patients with HCC. Together, this study characterizes HCCL5 as a super-enhancer–driven lncRNA promoting HCC cell viability, migration, and EMT. Our data also suggest that HCCL5 may serve as a novel prognostic biomarker and therapeutic target in HCC. Significance: These findings identify the lncRNA HCCL5 as a super-enhancer–driven oncogenic factor that promotes the malignancy of hepatocellular carcinoma.

The metastasis-associated lung adenocarcinoma transcript 1(MALAT1), a member of the long non-coding RNA (lncRNA) family, has been reported to be highly enriched in many kinds of cancers and to be a metastasis marker and a prognostic factor. In this study, we found that MALAT1 expression levels were significantly increased in cervical cancer (CC) cells and tissues. The down-regulation of MALAT1 by shRNA in CC cells inhibited the invasion and metastasis in vitro and in vivo. Microarray analysis showed that the knockdown of MALAT1 up-regulated the epithelial markers E-cadherin and ZO-1, and down-regulated the mesenchymal markers β-catenin and Vimentin. This regulation was further confirmed by subsequent observation from RT-PCR, western blot, and immunofluorescence results. Meanwhile, the transcription factor snail, which functions to modulate epithelial–mesenchymal transition (EMT), was also down-regulated at both transcript and protein levels by MALAT1 down-regulation. In addition, we found that MALAT1 expression levels were positively related to HPV infection in cervical epithelial tissues by microarray analysis. Taken together, these results suggest that MALAT1 functions to promote cervical cancer invasion and metastasis via induction of EMT, and it may be a target for the prevention and therapy of cervical cancers.

Cervical cancer is a common malignant tumour of the female reproductive system that seriously threatens the health of women. The aims of this study were to identify key genes and pathways and to illuminate new molecular mechanisms underlying cervical cancer. Altogether, 1829 DEGs were identified, including 794 significantly down-regulated DEGs and 1035 significantly up-regulated DEGs. GO analysis suggested that the up-regulated DEGs were mainly enriched in mitotic cell cycle processes, including DNA replication, organelle fission, chromosome segregation and cell cycle phase transition, and that the down-regulated DEGs were primarily enriched in development and differentiation processes, such as tissue development, epidermis development, skin development, keratinocyte differentiation, epidermal cell differentiation and epithelial cell differentiation. KEGG pathway analysis showed that the DEGs were significantly enriched in cell cycle, DNA replication, the p53 signalling pathway, pathways in cancer and oocyte meiosis. The top 9 hub genes with a high degree of connectivity (over 72 in the PPI network) were down-regulated TSPO, CCND1, and FOS and up-regulated CDK1, TOP2A, CCNB1, PCNA, BIRC5 and MAD2L1. Module analysis indicated that the top 3 modules were significantly enriched in mitotic cell cycle, DNA replication and regulation of cell cycle (P < 0.01). The heat map based on TCGA database preliminarily demonstrated the expression change of the key genes in cervical cancer. GSEA results were basically coincident with the front enrichment analysis results. By comprehensive analysis, we confirmed that cell cycle was a key biological process and a critical driver in cervical cancer. In conclusion, this study identified DEGs and screened the key genes and pathways closely related to cervical cancer by bioinformatics analysis, simultaneously deepening our understanding of the molecular mechanisms underlying the occurrence and progression of cervical cancer. These results might hold promise for finding potential therapeutic targets of cervical cancer.

Extrachromosomal circular DNA (eccDNA) elements are circular DNA molecules that are derived from but are independent of chromosomal DNA. EccDNA is emerging as a rising star because of its ubiquitous existence in cancers and its crucial role in oncogene amplification and tumor progression. In the present study, whole-genome sequencing (WGS) data of cancer samples were downloaded from public repositories. Afterwards, eccDNAs were identified from WGS data via bioinformatic analyses. To leverage database coverage, eccDNAs were also collected by manual curation of literatures. Gene expression and clinical data were downloaded from TCGA and CCLE and then used to investigate the roles of eccDNAs in cancers. Finally, the first integrated database of eccDNAs, eccDNAdb, was developed. eccDNAdb currently includes 1270 eccDNAs, which were identified in 480 samples (of 42 cancers) after analyzing a total number of 3395 tumor samples (of 57 cancers) including patient tissues, patient-derived xenografts, and cancer cell lines. A total number of 54,901 eccDNA genes were annotated and included in the database as well. With the integration of gene expression, clinical information and chromatin accessibility data, eccDNAdb enables users to easily determine the biological function and clinical relevance of eccDNAs in human cancers. In conclusion, eccDNAdb is freely accessible at http://www.eccdnadb.org. To our knowledge, eccDNAdb is the first database in the eccDNA research field. It is expected to provide insight for novel cancer therapies.