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 29,987 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

A very low 5-year survival rate among hepatocellular carcinoma (HCC) patients is mainly due to lack of early stage diagnosis, distant metastasis and high risk of postoperative recurrence. Hence ascertaining novel biomarkers for early diagnosis and patient specific therapeutics is crucial and urgent. Here, we have performed a comprehensive analysis of the expression data of 423 HCC patients (373 tumors and 50 controls) downloaded from The Cancer Genome Atlas (TCGA) followed by pathway enrichment by gene ontology annotations, subtype classification and overall survival analysis. The differential gene expression analysis using non-parametric Wilcoxon test revealed a total of 479 up-regulated and 91 down-regulated genes in HCC compared to controls. The list of top differentially expressed genes mainly consists of tumor/cancer associated genes, such as AFP, THBS4, LCN2, GPC3, NUF2, etc. The genes over-expressed in HCC were mainly associated with cell cycle pathways. In total, 59 kinases associated genes were found over-expressed in HCC, including TTK, MELK, BUB1, NEK2, BUB1B, AURKB, PLK1, CDK1, PKMYT1, PBK, etc. Overall four distinct HCC subtypes were predicted using consensus clustering method. Each subtype was unique in terms of gene expression, pathway enrichment and median survival. Conclusively, this study has exposed a number of interesting genes which can be exploited in future as potential markers of HCC, diagnostic as well as prognostic and subtype classification may guide for improved and specific therapy.
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PMID:Gene expression profiling, pathway analysis and subtype classification reveal molecular heterogeneity in hepatocellular carcinoma and suggest subtype specific therapeutic targets. 2902 94

Colorectal cancer is the third most common type of cancer and the fourth leading cause of cancer-associated mortality worldwide. Serine/arginine-rich splicing factor 1 (SRSF1) is a well-characterized oncogenic factor that promotes tumorigenesis by controlling a number of alternative splicing events. However, there is limited network analysis, from a global aspect, to study the effect of SRSF1 on colorectal cancer. In the present study, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of available gene regulation data from The Cancer Genome Atlas database revealed the enriched functions and signaling pathways of SRSF1. Subsequently, Oncomine analysis was performed, which demonstrated that SRSF1 was upregulated in a number of types of colon cancer. From overlapping the analysis of 2,678 SRSF1-related genes and 3,625 colorectal cancer genes in GeneCards, 468 genes were identified as SRSF1-related colorectal cancer genes. The GO results revealed that these overlapped genes were primarily enriched in metabolic processes, response to DNA damage, regulation of the cell cycle and a number of additional biological processes. KEGG pathway analysis revealed that SRSF1-related colorectal cancer genes were associated with the cell cycle, deregulated signaling pathways associated with cancer progression and colorectal cancer signaling pathways. In addition, the Search Tool for the Retrieval of Interacting Genes/Proteins database and Cytoscape analysis demonstrated that 468 SRSF1-related colorectal cancer genes exhibit potential interaction networks in which these genes were enriched in DNA metabolic processes, cell cycle regulation and regulation of apoptosis. The results of the present study suggested that SRSF1 exhibited an increased degree of interaction with key molecules, including NUF2 NDC80 kinetochore complex component, kinesin family member 2C, structural maintenance of chromosomes 3, ATM serine/threonine kinase, BRCA1 DNA repair associated, protein kinase DNA-activated catalytic polypeptide, heat shock protein 90 alpha family class A member 1, ras homolog family member A, and phosphatase and tensin homolog. Collectively, the bioinformatics analysis of the present study indicated that SRSF1 may have key functions in the progression and development of colorectal cancer.
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PMID:Bioinformatics analysis of SRSF1-controlled gene networks in colorectal cancer. 2911 73