Proteomic profile of acute myeloid leukaemia: A review update

Proteome analysis is a complex and dynamic process that encompasses several analytical platforms that include protein sequencing, structural or expression proteomics, protein modification, sub-cellular protein localization, protein-protein interaction and biological functional proteomics. In fact, expression proteomics is extensively applied in a majority of biomarker detection studies because it provides a detailed overview of differentially expressed proteins in cellular pathways and disease processes. Proteomics are also effective and dynamic in protein-protein interactions and cross-talks between interacting molecules of the cell. Proteomics has evolved into a crucial tool used to investigate the biochemical changes that possibly lead to development of cancer biomarkers. This review draws attention to the progress and advancements in cancer proteomics technology with the aim of simplifying the understanding of the mechanisms underlying the disease and to contribute to detection of biomarkers in addition to the development of novel treatments. Given that proteome is a dynamic entity of cellular functions in health and disease, it is capable of reflecting the immediate environmental state of cells and tissues as shown in this review. The review shows the possibility of elucidating the pathophysiology of acute myeloid leukaemia (AML) through proteome expressions, thus confirming the viability of proteome analysis in profiling AML.

Weight loss improves biomarkers endothelial function and systemic inflammation in obese postmenopausal Saudi women.

Background: Although postmenopausal associated disorders are important public health problems worldwide, to date limited studies evaluated the endothelial function and systemic inflammation response to weight loss in obese postmenopausal women. Objective: This study was done to evaluate the endothelial function and systemic inflammation response to weight loss in obese postmenopausal Saudi women. Material and methods: Eighty postmenopausal obese Saudi women (mean age 52.64±6.13 year) participated in two groups: Group (A) received aerobic exercise on treadmill and diet whereas, group (B) received no intervention. Markers of inflammation and endothelial function were measured before and after 3 months at the end of the study. Results: The values of body mass index(BMI), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), C-reactive protein (CRP), inter-cellular adhesion molecule (ICAM-1), vascular cell adhesion molecule (VCAM-1) and plasminogen activator inhibitor- 1 activity (PAI-1:Ac) were significantly decreased in group (A), while changes were not significant in group (B). Also, there were significant differences between mean levels of the investigated parameters in group (A) and group (B) after treatment. Conclusion: Weight loss ameliorates inflammatory cytokines and markers of endothelial function in obese postmenopausal Saudi women.

Pathway analysis for identification of potential biomarkers in severe cutaneous drug hypersensitivity reactions

Purpose: To construct a cluster model or a gene signature for Stevens-Johnson syndrome (SJS) using pathways analysis in order to identify some potential biomarkers that may be used for early detection of SJS and epidermal necrolysis (TEN) manifestations. Methods: Gene expression profiles of GSE12829 were downloaded from Gene Expression Omnibus database. A total of 193 differentially expressed genes (DEGs) were obtained. We applied these genes to geneMANIA database, to remove ambiguous and duplicated genes, and after that, characterized the gene expression profiles using geneMANIA, DAVID, REACTOME, STRING and GENECODIS which are online software and databases. Results: Out of 193 genes, only 91 were used (after removing the ambiguous and duplicated genes) for topological analysis. It was found by geneMANIA database search that majority of these genes were coexpressed yielding 84.63 % co-expression. It was found that ten genes were in Physical interactions comprising almost 14.33 %. There were < 1 % pathway and genetic interactions with values of 0.97 and 0.06 %, respectively. Final analyses revealed that there are two clusters of gene interactions and 13 genes were shown to be in evident relationship of interaction with regards to hypersensitivity. Conclusion: Analysis of differential gene expressions by topological and database approaches in the current study reveals 2 gene network clusters. These genes are CD3G, CD3E, CD3D, TK1, TOP2A, CDK1, CDKN3, CCNB1, and CCNF. There are 9 key protein interactions in hypersensitivity reactions and may serve as biomarkers for SJS and TEN. Pathways related gene clusters has been identified and a genetic model to predict SJS and TEN early incidence using these biomarker genes has been developed.

Effect of Dioscorea tokoro Makino extract on hyperuricemia in mice

Purpose: To investigate the anti-hyperuricemic effect of Dioscorea tokoro Makino extract (DTME) in potassium oxonate-induced hyperuricemic mice. Method: The effect of DTME was investigated in the hyperuricemic mice induced by potassium oxonate. DTME. The extract was administered to the mice daily at doses of 220, 440 and 880 mg/kg for 10 days; allopurinol (5 mg/kg) was given as positive control. Serum and urine levels of uric acid and creatinine were determined by colorimetric method. Simultaneously, protein levels of urate transporter 1 (URAT1) and organic anion transporter 1 (OAT1) in the rat kidney were analyzed by Western blotting. Results: Compared with control, a high dose of DTME inhibited xanthine oxidase (XOD) activity in both serum (18.12 ± 1.33 U/L) and in liver (70.15 ± 5.20 U/g protein) (p < 0.05); decreased levels of serum uric acid (2.04 ± 0.64 mg/L) (p < 0.05), serum creatinine (0.35 ± 0.18 μmol/L) and blood urea nitrogen (BUN) (8.83 ± 0.71 mmol/L) (p < 0.05). Furthermore, the extract increased levels of urine uric acid (38.34 ± 8.23 mg/L), urine creatinine (34.38 ± 1.98 mmol/L), down regulated of URAT1 and up regulated of OAT1 protein expressions (p < 0.05) in the renal tissue of hyperuricemic mice. Conclusion: DTME improves renal dysfunction in rats by regulating renal urate transporters in hyperuricemic rats. This may find therapeutic application in antihypertensive therapy.