| 1. |
- Lee, SangWook, et al.
(författare)
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Network analyses identify liver-specific targets for treating liver diseases
- 2017
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Ingår i: Molecular Systems Biology. - : EMBO. - 1744-4292. ; 13:8
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Tidskriftsartikel (refereegranskat)abstract
- We performed integrative network analyses to identify targets that can be used for effectively treating liver diseases with minimal side effects. We first generated co-expression networks (CNs) for 46 human tissues and liver cancer to explore the functional relationships between genes and examined the overlap between functional and physical interactions. Since increased de novo lipogenesis is a characteristic of nonalcoholic fatty liver disease (NAFLD) and hepatocellular carcinoma (HCC), we investigated the liver-specific genes co-expressed with fatty acid synthase (FASN). CN analyses predicted that inhibition of these liver-specific genes decreases FASN expression. Experiments in human cancer cell lines, mouse liver samples, and primary human hepatocytes validated our predictions by demonstrating functional relationships between these liver genes, and showing that their inhibition decreases cell growth and liver fat content. In conclusion, we identified liver-specific genes linked to NAFLD pathogenesis, such as pyruvate kinase liver and red blood cell (PKLR), or to HCC pathogenesis, such as PKLR, patatin-like phospholipase domain containing 3 (PNPLA3), and proprotein convertase subtilisin/kexin type 9 (PCSK9), all of which are potential targets for drug development.
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| 2. |
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| 3. |
- Liu, Zhengtao, et al.
(författare)
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The effect of the TM6SF2 E167K variant on liver steatosis and fibrosis in patients with chronic hepatitis C : a meta-analysis
- 2017
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Ingår i: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- The impact of Transmembrane 6 superfamily member 2 (TM6SF2) E167K variant, which causes hepatocellular fat retention by altering lipoprotein secretion, on liver damage and metabolic traits in chronic hepatitis C patients is still debated. We performed a systematic review and meta-analysis to clarify this relationship. Four studies with a total of 4325 patients were included. The risk of histologically-determined advanced steatosis, fibrosis, and cirrhosis (but not of severe inflammation) were increased in carriers of the TM6SF2 variant (P < 0.05). Unlike the inconsistent association with steatosis severity, due to the confounding effect of infection by the genotype-3 hepatitis C virus, the TM6SF2 variant was robustly associated with advanced fibrosis (OR = 1.07; 95% confidence interval [CI] = 1.01-1.14) and in particular with cirrhosis (OR = 2.05; 95% CI = 1.39-3.02). Regarding metabolic features, individuals positive for the TM6SF2 variant exhibited 5.8-12.0% lower levels of circulating triglycerides and non-HDL cholesterol (P < 0.05). Carriers of the variant were leaner, but there was high heterogeneity across studies (I-2 = 97.2%). No significant association was observed between the TM6SF2 variant and insulin resistance or hepatitis C viral load (both P > 0.05). In conclusion, the TM6SF2 E167K variant promotes the development of steatosis, fibrosis and cirrhosis in patients with chronic hepatitis C. Conversely, this variant reduces circulating atherogenic lipid fractions.
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| 4. |
- Uhlén, Mathias, et al.
(författare)
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A pathology atlas of the human cancer transcriptome
- 2017
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 357:6352, s. 660-
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Tidskriftsartikel (refereegranskat)abstract
- Cancer is one of the leading causes of death, and there is great interest in understanding the underlying molecular mechanisms involved in the pathogenesis and progression of individual tumors. We used systems-level approaches to analyze the genome-wide transcriptome of the protein-coding genes of 17 major cancer types with respect to clinical outcome. A general pattern emerged: Shorter patient survival was associated with up-regulation of genes involved in cell growth and with down-regulation of genes involved in cellular differentiation. Using genome-scale metabolic models, we show that cancer patients have widespread metabolic heterogeneity, highlighting the need for precise and personalized medicine for cancer treatment. All data are presented in an interactive open-access database (www.proteinatlas.org/pathology) to allow genome-wide exploration of the impact of individual proteins on clinical outcomes.
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