| 1. |
- Ahmadinejad, F., et al.
(författare)
-
Molecular mechanisms behind free radical scavengers function against oxidative stress
- 2017
-
Ingår i: Antioxidants. - : MDPI AG. - 2076-3921. ; 6:3
-
Tidskriftsartikel (refereegranskat)abstract
- Accumulating evidence shows that oxidative stress is involved in a wide variety of human diseases: rheumatoid arthritis, Alzheimers disease, Parkinsons disease, cancers, etc. Here, we discuss the significance of oxidative conditions in different disease, with the focus on neurodegenerative disease including Parkinsons disease, which is mainly caused by oxidative stress. Reactive oxygen and nitrogen species (ROS and RNS, respectively), collectively known as RONS, are produced by cellular enzymes such as myeloperoxidase, NADPH-oxidase (nicotinamide adenine dinucleotide phosphate-oxidase) and nitric oxide synthase (NOS). Natural antioxidant systems are categorized into enzymatic and non-enzymatic antioxidant groups. The former includes a number of enzymes such as catalase and glutathione peroxidase, while the latter contains a number of antioxidants acquired from dietary sources including vitamin C, carotenoids, flavonoids and polyphenols. There are also scavengers used for therapeutic purposes, such as 3,4-dihydroxyphenylalanine (L-DOPA) used routinely in the treatment of Parkinsons disease (not as a free radical scavenger), and 3-methyl-1-phenyl-2-pyrazolin-5-one (Edaravone) that acts as a free radical detoxifier frequently used in acute ischemic stroke. The cell surviving properties of L-DOPA and Edaravone against oxidative stress conditions rely on the alteration of a number of stress proteins such as Annexin A1, Peroxiredoxin-6 and PARK7/DJ-1 (Parkinson disease protein 7, also known as Protein deglycase DJ-1). Although they share the targets in reversing the cytotoxic effects of H2O2, they seem to have distinct mechanism of function. Exposure to L-DOPA may result in hypoxia condition and further induction of ORP150 (150-kDa oxygen-regulated protein) with its concomitant cytoprotective effects but Edaravone seems to protect cells via direct induction of Peroxiredoxin-2 and inhibition of apoptosis.
|
|
| 2. |
- Benfeitas, Rui, et al.
(författare)
-
Characterization of heterogeneous redox responses in hepatocellular carcinoma patients using network analysis
- 2019
-
Ingår i: Ebiomedicine. - : Elsevier BV. - 2352-3964. ; 40, s. 471-487
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Redox metabolism is often considered a potential target for cancer treatment, but a systematic examination of redox responses in hepatocellular carcinoma (HCC) is missing. Methods: Here, we employed systems biology and biological network analyses to reveal key roles of genes associated with redox metabolism in HCC by integrating multi-omics data. Findings: We found that several redox genes, including 25 novel potential prognostic genes, are significantly co-expressed with liver-specific genes and genes associated with immunity and inflammation. Based on an integrative analysis, we found that HCC tumors display antagonistic behaviors in redox responses. The two HCC groups are associated with altered fatty acid, amino acid, drug and hormone metabolism, differentiation, proliferation, and NADPH-independent vs - dependent antioxidant defenses. Redox behavior varies with known tumor subtypes and progression, affecting patient survival. These antagonistic responses are also displayed at the protein and metabolite level and were validated in several independent cohorts. We finally showed the differential redox behavior using mice transcriptomics in HCC and noncancerous tissues and associated with hypoxic features of the two redox gene groups. Interpretation: Our integrative approaches highlighted mechanistic differences among tumors and allowed the identification of a survival signature and several potential therapeutic targets for the treatment of HCC.
|
|
| 3. |
- Bidkhori, Gholamreza, et al.
(författare)
-
Metabolic Network-Based Identification and Prioritization o f Anticancer Targets Based on Expression Data in Hepatocellular Carcinoma
- 2018
-
Ingår i: Frontiers in Physiology. - : Frontiers Media SA. - 1664-042X. ; 9:JUL
-
Tidskriftsartikel (refereegranskat)abstract
- Hepatocellular carcinoma (HCC) is a deadly form of liver cancer with high mortality worldwide. Unfortunately, the large heterogeneity of this disease makes it difficult to develop effective treatment strategies. Cellular network analyses have been employed to study heterogeneity in cancer, and to identify potential therapeutic targets. However, the existing approaches do not consider metabolic growth requirements, i.e., biological network functionality, to rank candidate targets while preventing toxicity to non-cancerous tissues. Here, we developed an algorithm to overcome these issues based on integration of gene expression data, genome-scale metabolic models, network controllability, and dispensability, as well as toxicity analysis. This method thus predicts and ranks potential anticancer non-toxic controlling metabolite and gene targets. Our algorithm encompasses both objective-driven and-independent tasks, and uses network topology to finally rank the predicted therapeutic targets. We employed this algorithm to the analysis of transcriptomic data for 50 HCC patients with both cancerous and non-cancerous samples. We identified several potential targets that would prevent cell growth, including 74 anticancer metabolites, and 3 gene targets (PRKACA, PGS1, and CRLS1). The predicted anticancer metabolites showed good agreement with existing FDA-approved cancer drugs, and the 3 genes were experimentally validated by performing experiments in HepG2 and Hep3B liver cancer cell lines. Our observations indicate that our novel approach successfully identifies therapeutic targets for effective treatment of cancer. This approach may also be applied to any cancer type that has tumor and non-tumor gene or protein expression data.
|
|
| 4. |
- Bidkhori, Gholamreza, et al.
(författare)
-
Metabolic network-based stratification of hepatocellular carcinoma reveals three distinct tumor subtypes
- 2018
-
Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 115:50
-
Tidskriftsartikel (refereegranskat)abstract
- Hepatocellular carcinoma (HCC) is one of the most frequent forms of liver cancer, and effective treatment methods are limited due to tumor heterogeneity. There is a great need for comprehensive approaches to stratify HCC patients, gain biological insights into subtypes, and ultimately identify effective therapeutic targets. We stratified HCC patients and characterized each subtype using transcriptomics data, genome-scale metabolic networks and network topology/controllability analysis. This comprehensive systems-level analysis identified three distinct subtypes with substantial differences in metabolic and signaling pathways reflecting at genomic, transcriptomic, and proteomic levels. These subtypes showed large differences in clinical survival associated with altered kynurenine metabolism, WNT/beta-catenin-associated lipid metabolism, and PI3K/AKT/mTOR signaling. Integrative analyses indicated that the three subtypes rely on alternative enzymes (e.g., ACSS1/ACSS2/ACSS3, PKM/PKLR, ALDOB/ALDOA, MTHFD1L/MTHFD2/MTHFD1) to catalyze the same reactions. Based on systems-level analysis, we identified 8 to 28 subtype-specific genes with pivotal roles in controlling the metabolic network and predicted that these genes may be targeted for development of treatment strategies for HCC subtypes by performing in silico analysis. To validate our predictions, we performed experiments using HepG2 cells under normoxic and hypoxic conditions and observed opposite expression patterns between genes expressed in high/moderate/low-survival tumor groups in response to hypoxia, reflecting activated hypoxic behavior in patients with poor survival. In conclusion, our analyses showed that the heterogeneous HCC tumors can be stratified using a metabolic network-driven approach, which may also be applied to other cancer types, and this stratification may have clinical implications to drive the development of precision medicine.
|
|
| 5. |
- Bidkhori, Gholamreza, et al.
(författare)
-
MIGRENE : The Toolbox for Microbial and Individualized GEMs, Reactobiome and Community Network Modelling
- 2024
-
Ingår i: Metabolites. - : MDPI. - 2218-1989 .- 2218-1989. ; 14:3
-
Tidskriftsartikel (refereegranskat)abstract
- Understanding microbial metabolism is crucial for evaluating shifts in human host-microbiome interactions during periods of health and disease. However, the primary hurdle in the realm of constraint-based modeling and genome-scale metabolic models (GEMs) pertaining to host-microbiome interactions lays in the efficient utilization of metagenomic data for constructing GEMs that encompass unexplored and uncharacterized genomes. Challenges persist in effectively employing metagenomic data to address individualized microbial metabolisms to investigate host-microbiome interactions. To tackle this issue, we have created a computational framework designed for personalized microbiome metabolisms. This framework takes into account factors such as microbiome composition, metagenomic species profiles and microbial gene catalogues. Subsequently, it generates GEMs at the microbial level and individualized microbiome metabolisms, including reaction richness, reaction abundance, reactobiome, individualized reaction set enrichment (iRSE), and community models. Using the toolbox, our findings revealed a significant reduction in both reaction richness and GEM richness in individuals with liver cirrhosis. The study highlighted a potential link between the gut microbiota and liver cirrhosis, i.e., increased level of LPS, ammonia production and tyrosine metabolism on liver cirrhosis, emphasizing the importance of microbiome-related factors in liver health.
|
|
| 6. |
|
|
| 7. |
- Clasen, Frederick, et al.
(författare)
-
Systematic diet composition swap in a mouse genome-scale metabolic model reveals determinants of diet metabolism in liver cancer
- 2023
-
Ingår i: ISCIENCE. - : Elsevier BV. - 2589-0042. ; 26:2
-
Tidskriftsartikel (refereegranskat)abstract
- Dietary nutrient availability and gene expression, together, influence tissue metabolic activity. Here, we explore whether altering dietary nutrient composi-tion in the context of mouse liver cancer suffices to overcome chronic gene expression changes that arise from tumorigenesis and western-style diet (WD). We construct a mouse genome-scale metabolic model and estimate metabolic fluxes in liver tumors and non-tumoral tissue after computationally varying the composition of input diet. This approach, called Systematic Diet Composition Swap (SyDiCoS), revealed that, compared to a control diet, WD increases produc-tion of glycerol and succinate irrespective of specific tissue gene expression pat-terns. Conversely, differences in fatty acid utilization pathways between tumor and non-tumor liver are amplified with WD by both dietary carbohydrates and lipids together. Our data suggest that combined dietary component modifica-tions may be required to normalize the distinctive metabolic patterns that underlie selective targeting of tumor metabolism.
|
|
| 8. |
- Ezzamouri, Bouchra, et al.
(författare)
-
Metabolic modelling of the human gut microbiome in type 2 diabetes patients in response to metformin treatment
- 2023
-
Ingår i: NPJ SYSTEMS BIOLOGY AND APPLICATIONS. - : Springer Nature. - 2056-7189. ; 9:1
-
Tidskriftsartikel (refereegranskat)abstract
- The human gut microbiome has been associated with several metabolic disorders including type 2 diabetes mellitus. Understanding metabolic changes in the gut microbiome is important to elucidate the role of gut bacteria in regulating host metabolism. Here, we used available metagenomics data from a metformin study, together with genome-scale metabolic modelling of the key bacteria in individual and community-level to investigate the mechanistic role of the gut microbiome in response to metformin. Individual modelling predicted that species that are increased after metformin treatment have higher growth rates in comparison to species that are decreased after metformin treatment. Gut microbial enrichment analysis showed prior to metformin treatment pathways related to the hypoglycemic effect were enriched. Our observations highlight how the key bacterial species after metformin treatment have commensal and competing behavior, and how their cellular metabolism changes due to different nutritional environment. Integrating different diets showed there were specific microbial alterations between different diets. These results show the importance of the nutritional environment and how dietary guidelines may improve drug efficiency through the gut microbiota.
|
|
| 9. |
- Harzandi, Azadeh, et al.
(författare)
-
Acute kidney injury leading to CKD is associated with a persistence of metabolic dysfunction and hypertriglyceridemia
- 2021
-
Ingår i: iScience. - : Elsevier BV. - 2589-0042. ; 24:2
-
Tidskriftsartikel (refereegranskat)abstract
- Fibrosis is the pathophysiological hallmark of progressive chronic kidney disease (CKD). The kidney is a highly metabolically active organ, and it has been suggested that disruption in its metabolism leads to renal fibrosis. We developed a longitudinal mouse model of acute kidney injury leading to CKD and an in vitro model of epithelial to mesenchymal transition to study changes in metabolism, inflammation, and fibrosis. Using transcriptomics, metabolic modeling, and serum metabolomics, we observed sustained fatty acid metabolic dysfunction in the mouse model from early to late stages of CKD. Increased fatty acid biosynthesis and downregulation of catabolic pathways for triglycerides and diacylglycerides were associated with a marked increase in these lipids in the serum. We therefore suggest that the kidney may be the source of the abnormal lipid profile seen in patients with CKD, which may provide insights into the association between CKD and cardiovascular disease.
|
|
| 10. |
- Lee, Sunjae, et al.
(författare)
-
TCSBN: a database of tissue and cancer specific biological networks
- 2018
-
Ingår i: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 46:D1
-
Tidskriftsartikel (refereegranskat)abstract
- Biological networks provide new opportunities for understanding the cellular biology in both health and disease states. We generated tissue specific integrated networks (INs) for liver, muscle and adipose tissues by integratingmetabolic, regulatory and protein-protein interaction networks. We also generated human co-expression networks (CNs) for 46 normal tissues and 17 cancers to explore the functional relationships between genes as well as their relationships with biological functions, and investigate the overlap between functional and physical interactions provided by CNs and INs, respectively. These networks can be employed in the analysis of omics data, provide detailed insight into disease mechanisms by identifying the key biological components and eventually can be used in the development of efficient treatment strategies. Moreover, comparative analysis of the networks may allow for the identification of tissue-specific targets that can be used in the development of drugs with the minimum toxic effect to other human tissues. These context-specific INs and CNs are presented in an interactive website http://inetmodels.com without any limitation.
|
|
