Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with a high rate of morbidity and mortality. HCC affects approximately one million individuals annually worldwide, with the incidence equal to the mortality rate. In 2008, HCC was listed as the third most lethal cancer. Thus, early diagnosis is crucial for improving the survival rate for patients. α-fetoprotein (AFP) together with iconography and pathology detection are commonly used in the clinical early diagnosis of liver cancer. However, the specificity and sensitivity of AFP used in screening for liver cancer are not satisfactory. Athough the development of molecular biology has led to the identification of new tumor markers, including proteantigens, cytokines, enzymes and isoenzymes, as well as related genes that can be used in the treatment and prognosis of liver cancer, more tumor markers are required for effective early diagnosis of diseases and monitoring of the curative effect.
Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is suggested to be a long (∼7 kb) non-coding RNA. MALAT1 is overexpressed in many human carcinomas, but its function remains unknown. To investigate the role of MALAT1 in human cervical cancer progression, we designed and used short hairpin RNA to inhibit MALAT1 expression in CaSki cells and validated its effect on cell proliferation and invasion. Changes in gene expression were analyzed by reverse transcriptasepolymerase chain reaction. Our data demonstrated that MALAT1 was involved in cervical cancer cell growth, cell cycle progression, and invasion through the regulation of gene expression, such as caspase-3, -8, Bax, Bcl-2, and BclxL, suggesting that MALAT1 could have important implications in cervical cancer biology. Our findings illustrate the biological significance of MALAT1 in cervical cancer progression and provide novel evidence that MALAT1 may serve as a therapeutic target in the prevention of human cervical cancer.
Cervical cancer contributed the second highest number of deaths in female cancers, exceeded only by breast cancer, carrying high risks of morbidity and mortality. There was a great need and urgency in searching novel treatment targets and prognosis biomarkers to improve the survival rate of cervical cancer patients. Many long non-coding RNAs (lncRNAs) were emerging as pivotal regulators in various biological processes and took vitally an effect on the oncogenesis and progression of cervical cancer. In this review, we summarized the origin and overview function of lncRNAs; highlighted the roles of lncRNAs in cervical cancer in terms of prognosis and tumor progression, invasion and metastasis, apoptosis, and radio-resistance; and outlined the molecular mechanisms of lncRNAs in cervical cancer from the aspects of the interaction of lncRNAs with proteins/mRNAs (especially in HPV protein) and miRNAs, as well as RNA N-methyladenosine (m6A) methylation of lncRNAs. Meanwhile, the application of lncRNAs as biomarkers in cervical cancer prognosis and predictors for metastasis was also discussed. An overview of these researches will be valuable for broadening horizons into mechanisms, selection of meritorious biomarkers for diagnosis as well as prognosis, and future targeted therapy of cervical cancer.
Ocean salinity records the hydrological cycle and its changes, but data scarcity and the large changes in sampling make the reconstructions of long-term salinity changes challenging. Here, we present a new observational estimate of changes in ocean salinity since 1960 from the surface to 2000 m. We overcome some of the inconsistencies present in existing salinity reconstructions by using an interpolation technique that uses information on the spatio-temporal co-variability of salinity taken from model simulations. The interpolation technique is comprehensively evaluated using recent Argo-dominated observations through subsample tests. The new product strengthens previous findings that ocean surface and subsurface salinity contrasts have increased, i.e., the existing salinity pattern has amplified. We quantify this contrast by assessing the difference between the salinity in regions of high and low salinity averaged over the top 2000 m, a metric we refer to as SC2000. The increase in SC2000 is highly distinguishable from the sampling error and less affected by inter-annual variability and sampling error than if this metric was computed just for the surface. SC2000 increased by 0.5±0.3% from 1960 to 1990 and by 1.0±0.1% from 1991 to 2017 (1.6±0.2% for 1960-2017), indicating an acceleration of the pattern amplification in recent decades. Combining this estimate with model simulations, we show that the change in SC2000 since 1960 emerges clearly as an anthropogenic signal from the natural variability. Based on the salinity-contrast metric and model simulations, we find a water cycle amplification of 2.1±3.9% K-1 since 1960, with the larger error than salinity metric mainly being due to model uncertainty.
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, G 1-S transition, invasion, and metastasis while inhibiting apoptosis of HCC cells both in vitro and in vivo. Moreover, HCCL5 was upregulated in TGF-b1-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 tran-scriptionally 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 superenhancer-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.
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