Altered metabolism of fatty acid synthesis is considered a hallmark characteristic of several malignancies, including acute lymphoblastic leukemia (ALL). to evaluate the impact of fatty acid synthase (FASN) on drug resistant ALL, bone marrow samples were collected from 65 pediatric ALLs, including 40 de novo and 25 relapsed patients. 22 non-cancer individuals were chosen as controls. Quantitative RT-PCR showed increased expression levels of FASN in drug resistant patients compared with the therapy responders. Single and combined treatment of malignant cells were analyzed using Annexin-V/PI double staining and MTT assays. Incubation of resistant primary cells with ginger showed simultaneous increased apoptosis rates and reduced FASN expression levels. Furthermore, docking studies demonstrated high affinity bindings between ginger derivatives and FASN thioesterase and ketosynthase domains, compared with their known inhibitors, fenofibrate and morin, respectively. Finally, combined treatment of in-house multidrug resistant TALL subline with ginger and dexamethasone induced drug sensitivity and down regulation of FASN expression, accordingly. To the best of our knowledge, this is the first study that introduces FASN upregulation as a poor prognostic factor for drug resistant childhood ALL. Moreover, it was revealed that fASn inhibition may be applied by ginger phytochemicals and overcome dexamethasone resistance, subsequently. Acute lymphoblastic leukemia (ALL) is the most common type of hematological malignancy in children 1,2. Despite the enormous advances in modern medicine and development of innovative therapeutic strategies, disease relapse remains a leading cause of cancer-related morbidity and mortality in children 3. Metabolic rearrangements are vital to satisfy the different requirements of cancer cells during tumorigenesis 4. Elevated de novo fatty acid biosynthesis is a hallmark adaptation in many cancers that supply signaling molecules and basic elements for lipid biosynthesis 5. While most normal cells supply their fatty acids from dietary sources, cancer cells reactivate de novo fatty acid synthesis 6. Fatty acid synthase (FASN) is a multifunctional protein containing six enzymatic domains that catalyzes the biosynthesis of palmitate 5. Elevated expression of FASN is found to be associated with poor prognosis and higher risk of recurrence in a number of human cancers. Indeed, FASN overexpression has been shown to contribute to multidrug resistance (MDR). Multi-drug resistance is one of the major obstacles to the successful treatment of various types of cancer, particularly childhood ALL 5,7,8. Glucocorticoids (GCs) such as prednisone and dexamethasone (DEX) are indispensable drugs for childhood ALL treatment 9. Early response to glucocorticoids is a positive prognostic indicator and glucocorticoid resistance has been associated with an increased risk of relapse and poor clinical response 10,11. Glucocorticoids regulate FASN expression and subsequently affect lipogenesis 12. Therefore, FASN knock down or...

Background FSGS (focal and segmental glomerulosclerosis) is a clinical-pathologic condition marked by segmental and localized glomerular damages. Despite investigations, the molecular mechanisms behind FSGS development remain to be more clarified. By a comprehensive analysis of a FSGS related array set, the aim of this study was to unravel the top pathways and molecules involved in the pathogenesis of this disorder. Methods FSGS related microarray dataset (GSE129973) from the Gene Expression Omnibus (GEO) database was quality checked, analyzed and its differentially expressed genes (DEGs) (log2FC>1) were used for construction of a protein-protein interaction (PPI) network (STRING). The degree of centrality was considered to select the hub molecules in the network. The WGCNA was utilized to construct co-expression modules. Hub molecules were selected based on module membership (MM) and gene significant (GS) values in the disease’s most correlated module. After spotting the key molecules considering both strategies, their expression pattern were checked in other FSGS microarray datasets. Gene ontology (GO) and Reactome pathway enrichment analyses were performed on the DEGs of the related module. Results After quality checking, normalization and analysis of the dataset, 5296 significant DEGs including 2469 up-regulated and 2827 downregulated DEGs were identified. The WGCNA algorithm clustered the DEGs into nine independent co-expression modules. The disease most-correlated module (black module) was recognized and considered for further enrichment analysis. The immune system, cell cycle, and vesicle-mediated transports were among the top enriched terms for the identified module’s DEGs. The immune system, cell cycle, and vesicle-mediated transports were among the top enriched terms for the black module’s DEGs. The key molecules (BMP-2 and COL4A1) were identified as common hub molecules extracted from the two methods of PPI and the co-expressed networks. The two identified key molecules were validated in other FSGS datasets, where a similar pattern of expression was observed for both the genes. Conclusions Two hub molecules (BMP-2 and COL4A) and some pathways (vesicle-mediated transport) were recognized as potential players in the pathogenesis of FSGS.

Background and Aims Primary glomerulonephritis diseases (PGDs) are known as the top causes of chronic kidney disease (CKD) worldwide. Renal biopsy, as an invasive method, is the main PGDs diagnosis approach. Studying the metabolome profiles of kidney diseases is an inclusive approach to identify the disease's underlying pathways and discover novel non-invasive biomarkers. So far, different experiments have explored the metabolome profiles in different PGDs, but the inconsistencies might hinder their clinical translations. The main goal of this meta-analysis study was to achieve consistent panels of dysregulated metabolites in PGD sub-types. Methods The PGDs-related metabolome profiles from urine, blood, and tissue samples were searched. Amanida package in R software was utilized for performing the meta-analysis. Through different sub-type analyses, the consensus list of metabolites in each category was obtained. To identify the most affected pathways, functional enrichment analysis was performed. Also, a gene-metabolite network was constructed to identify the key metabolites and their connected proteins. Results After a vigorous search, among the 25 selected studies (29 metabolite profiles), 832 dysregulated metabolites were recognized in 1519 PGN and control samples. Through different subtype analyses by Amanida package, the consensus list of metabolites in each category was obtained. Due to the importance of urinary metabolites, top dysregulated metabolites (vote score of ≥4 or ≤-4) were selected as main panel of meta-metabolites including glucose, leucine, choline, betaine, dimethylamine, fumaric acid, citric acid, 3-hydroxyisovaleric acid, pyruvic acid, isobutyric acid, and hippuric acid. The enrichment analyses results revealed the involvement of different biological pathways such as the TCA cycle and amino acid metabolisms in the pathogenesis of PGDs. The constructed metabolite-gene interaction network revealed the high centralities of several metabolites, including pyruvic acid, leucine, and choline. Conclusion The identified metabolite panels could shed a light on the underlying pathological pathways and be considered as non-invasive biomarkers for the diagnosis of PGD sub-types.

Background: Focal segmental glomerulosclerosis (FSGS) - a histologic pattern of injury in the glomerulus - is one of the leading glomerular causes of ESRD worldwide. Despite vigorous research, the underlying biological alterations causing FSGS remain to be understood. Studying the variations in gene expression profiles is one of the promising approaches to have a holistic view of the FSGS molecular pathogenicity and help to discover key elements as potential therapeutic targets. The present work is a meta-analysis study including all the microarray gene expression profiles coming from glomerular samples of FSGS patients. Reaching to a consensus list of differentially expressed genes in FSGS condition, understanding the disease pathogenicity, and identification of novel therapeutic targets were the main aims of this study. Methods: After a vigorous search in GEO database and quality control assessments, seven gene expression datasets including GSE47183 (GPL14663), GSE47183 (GPL11670), GSE99340, GSE108109, GSE121233, GSE129973, and GSE104948 were selected for the meta-analysis. The random effect size method was applied and the identified meta-DEGs were considered for the construction of a regulatory network (STRING, MiRTarBase, and TRRUST), as well as performing different pathway enrichment analyses. The expression levels of several meta-DEGs (ADAMTS1, PF4, EGR1, and EGF) as angiogenesis regulators were analyzed using RT-qPCR method. Results: The identified 2898 meta-DEGs including 665 downregulated and 669 upregulated DEGs were subjected to different analyses. A co-regulatory network including 2859 DEGs, 2688 miRNAs, and 374 TFs was constructed and top molecules in the network (based on degree centrality) were identified. A part of the pathway enrichment analysis revealed a significant distortion in the angiogenesis regulatory pathways in the FSGS kidney. The results of RT-qPCR showed the presence of an imbalance in angiogenetic pathways by confirming the differential expression levels of ADAMTS1and EGR1 as the two main angiogenesis regulators in the FSGS condition. Conclusion: Despite providing a consensus list of differentially expressed genes in the FSGS condition, this meta-analysis revealed the existence of distortion in the angiogenesis-related pathways and factors in the FSGS kidney. Controlling such factors might be a possible way to hinder the progression of FSGS.