SUMOylation regulates LKB1 localization and its oncogenic activity in liver cancer

Zubiete-Franco, Imanol; García-Rodríguez, Juan L.; Lopitz‐Otsoa, Fernando; Serrano‐Maciá, Marina; Simón, Jorge; Fernández-Tussy, Pablo; Barbier-Torres, Lucía; Fernández‐Ramos, David; Gutiérrez-de-Juan, Virginia; Davalillo, Sergio López de; Carlevaris, Onintza; Gómez, Adolfo Beguiristain; Villa, Erica; Calvisi, Diego F.; Martín, César San; Berra, Edurne; Aspichueta, Patricia; Beraza, Naiara; Varela‐Rey, Marta; Ávila, Matías A.; Rodríguez, Manuel Sánchez; Mato, José M.; Dı́az-Moreno, Irene; Díaz-Quintana, Antonio; Delgado, Teresa C.; Martínez‐Chantar, María Luz

doi:10.1016/j.ebiom.2018.12.031

Cited by 64 publications

(56 citation statements)

References 81 publications

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“…Gene expression profile data (GSE36376, 14 GSE39791, 15 GSE41804, 16 GSE54236, 17 , 18 GSE57957, 19 GSE62232, 20 GSE64041, 21 GSE69715, 22 GSE76427, 23 GSE84005, GSE87630, 24 GSE112790, 25 and GSE121248 26 ) were downloaded from the GEO database ( http://www.ncbi.nlm.nih.gov/geo/ ), 27 a public data repository, including high-throughput gene expression and other functional genome datasets. The selection criteria for the included datasets were as follows: (1) tissue samples collected from human HCC and corresponding adjacent or normal tissues; and (2) including at least 40 samples.…”

Section: Methodsmentioning

confidence: 99%

Identification of potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma via integrated bioinformatics analysis

Meng

Liu

et al. 2020

J Int Med Res

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Objective The objective was to identify potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma (HCC). Methods Gene expression profile datasets were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between HCC and normal samples were identified via an integrated analysis. A protein–protein interaction network was constructed and analyzed using the STRING database and Cytoscape software, and enrichment analyses were carried out through DAVID. Gene Expression Profiling Interactive Analysis and Kaplan–Meier plotter were used to determine expression and prognostic values of hub genes. Results We identified 11 hub genes ( CDK1, CCNB2, CDC20, CCNB1, TOP2A, CCNA2, MELK, PBK, TPX2, KIF20A, and AURKA) that might be closely related to the pathogenesis and prognosis of HCC. Enrichment analyses indicated that the DEGs were significantly enriched in metabolism-associated pathways, and hub genes and module 1 were highly associated with cell cycle pathway. Conclusions In this study, we identified key genes of HCC, which indicated directions for further research into diagnostic and prognostic biomarkers that could facilitate targeted molecular therapy for HCC.

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Section: Methodsmentioning

confidence: 99%

Identification of potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma via integrated bioinformatics analysis

Meng

Liu

et al. 2020

J Int Med Res

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“…Genes were screened using the GEO (http://www.ncbi. nlm.nih.gov/geo) database, specifically the GSE89377 series on the GPL6947 platform (Illumina HumanHT12 V3.0 expression beadchip), the GSE17548 series [8] on the GPL570 platform (Affymetrix Human Genome U133 Plus 2.0 Array), the GSE63898 series [9] on the GPL13667 platform (Affymetrix Human Genome U219 Array), and the GSE54236 series [10] on the GPL6480 platform (Agilent-014850 Whole Human Genome Microarray 4x44K G4112F), the basic clinical info of the patients selected is showed in Additional file 1: Table S1. According to the annotation information in each platform, probes were converted into corresponding gene symbols.…”

Section: Microarray Datamentioning

confidence: 99%

Bioinformatics-based screening of key genes for transformation of liver cirrhosis to hepatocellular carcinoma

Chen

Yuan

et al. 2020

J Transl Med

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Background: Hepatocellular carcinoma (HCC) is the most common type of liver tumour, and is closely related to liver cirrhosis. Previous studies have focussed on the pathogenesis of liver cirrhosis developing into HCC, but the molecular mechanism remains unclear. The aims of the present study were to identify key genes related to the transformation of cirrhosis into HCC, and explore the associated molecular mechanisms.Methods: GSE89377, GSE17548, GSE63898 and GSE54236 mRNA microarray datasets from Gene Expression Omnibus (GEO) were analysed to obtain differentially expressed genes (DEGs) between HCC and liver cirrhosis tissues, and network analysis of protein-protein interactions (PPIs) was carried out. String and Cytoscape were used to analyse modules and identify hub genes, Kaplan-Meier Plotter and Oncomine databases were used to explore relationships between hub genes and disease occurrence, development and prognosis of HCC, and the molecular mechanism of the main hub gene was probed using Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis. Results:In total, 58 DEGs were obtained, of which 12 and 46 were up-and down-regulated, respectively. Three hub genes (CDKN3, CYP2C9 and LCAT) were identified and associated prognostic information was obtained. CDKN3 may be correlated with the occurrence, invasion, and recurrence of HCC. Genes closely related to changes in the CDKN3 hub gene were screened, and Kyoto Encyclopedia of Genes and Genomes (KEGGs) pathway analysis identified numerous cell cycle-related genes.Conclusion: CDKN3 may affect the transformation of liver cirrhosis into HCC, and represents a new candidate molecular marker of the occurrence and progression of HCC.

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“…Osawa and collaborators have characterized the effect of SphK in hepatoma cell differentiation by promoting the pro-tumor phenotype [141]. In his work they characterize the differentiation effect of inhibiting SphK in Huh-7 cells, an in vitro cell model of human HCC widely used in the study of the disease [142,143]. Particularly, the isoform SphK1 has been related to poor prognosis among cancer patients by having a pro-metastatic role [144,145].…”

Section: Ddr and S1p As Potential Targets For Hcc Therapiesmentioning

confidence: 99%

Sphingolipids in Non-Alcoholic Fatty Liver Disease and Hepatocellular Carcinoma: Ceramide Turnover

Simón

Ouro

Ala-Ibanibo

et al. 2019

IJMS

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Non-alcoholic fatty liver disease (NAFLD) has emerged as one of the main causes of chronic liver disease worldwide. NAFLD comprises a group of conditions characterized by the accumulation of hepatic lipids that can eventually lead to non-alcoholic steatohepatitis (NASH), fibrosis, cirrhosis, and hepatocellular carcinoma (HCC), the fifth most common cancer type with a poor survival rate. In this context, several works have pointed out perturbations in lipid metabolism and, particularly, changes in bioactive sphingolipids, as a hallmark of NAFLD and derived HCC. In the present work, we have reviewed existing literature about sphingolipids and the development of NAFLD and NAFLD-derived HCC. During metabolic syndrome, considered a risk factor for steatosis development, an increase in ceramide and sphigosine-1-phosphate (S1P) have been reported. Likewise, other reports have highlighted that increased sphingomyelin and ceramide content is observed during steatosis and NASH. Ceramide also plays a role in liver fibrosis and cirrhosis, acting synergistically with S1P. Finally, during HCC, metabolic fluxes are redirected to reduce cellular ceramide levels whilst increasing S1P to support tumor growth.

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SUMOylation regulates LKB1 localization and its oncogenic activity in liver cancer

Cited by 64 publications

References 81 publications

Identification of potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma via integrated bioinformatics analysis

Identification of potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma via integrated bioinformatics analysis

Bioinformatics-based screening of key genes for transformation of liver cirrhosis to hepatocellular carcinoma

Sphingolipids in Non-Alcoholic Fatty Liver Disease and Hepatocellular Carcinoma: Ceramide Turnover

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