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Multiple sclerosis (MS) is an autoimmune disorder of the central nervous system (CNS) whose aetiology is only partly understood. Investigating the intricate transcriptional changes occurring in MS brains is critical to unravel novel pathogenic mechanisms and therapeutic targets. Unfortunately, this process is often hindered by the difficulty in retrieving an adequate number of samples. However, by merging data from publicly available datasets, it is possible to identify alterations in gene expression profiles and regulatory pathways that were previously overlooked. Here, we merged microarray gene expression profiles obtained from CNS white matter samples taken from MS donors to identify novel differentially expressed genes (DEGs) linked with MS. Data from three independent datasets (GSE38010, GSE32915, and GSE108000) were combined and used to detect novel DEGs using the Stouffer's Z-score method. Corresponding regulatory pathways were analysed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway databases. Finally, top up- and down-regulated transcripts were validated by real-time quantitative PCR (qPCR) using an independent set of white matter tissue samples obtained from MS donors with different disease subtypes. There were a total of 1446 DEGs, of which 742 were up-regulated and 704 genes were down-regulated. DEGs were associated with several myelin-related pathways and protein metabolism pathways. Validation studies of selected top up- or down-regulated genes highlighted MS subtype-specific differences in the expression of some of the identified genes, underlining a more complex scenario of white matter pathology amongst people afflicted by this devastating disease. [ABSTRACT FROM AUTHOR]

Circulating endothelial progenitor cells (EPCs) play an important role in the repair processes of damaged vessels, favoring re-endothelization of stented vessels to minimize restenosis. EPCs number and function is diminished in patients with type 2 diabetes, a known risk factor for restenosis. Considering the impact of EPCs in vascular injury repair, we conducted a meta-analysis of microarray to assess the transcriptomic profile and determine target genes during the differentiation process of EPCs into mature ECs. Five microarray datasets, including 13 EPC and 12 EC samples were analyzed, using the online tool ExpressAnalyst. Differentially expressed genes (DEGs) analysis was done by Limma method, with an | log2FC| > 1 and FDR < 0.05. Combined p-value by Fisher exact method was computed for the intersection of datasets. There were 3,267 DEGs, 1,539 up-regulated and 1,728 down-regulated in EPCs, with 407 common DEGs in at least four datasets. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed enrichment for terms related to “AGE-RAGE signaling pathway in diabetic complications.” Intersection of common DEGs, KEGG pathways genes and genes in protein-protein interaction network (PPI) identified four key genes, two up-regulated (IL1B and STAT5A) and two down-regulated (IL6 and MAPK11). MicroRNA enrichment analysis of common DEGs depicted five hub microRNA targeting 175 DEGs, including STAT5A, IL6 and MAPK11, with hsa-miR-124 as common regulator. This group of genes and microRNAs could serve as biomarkers of EPCs differentiation during coronary stenting as well as potential therapeutic targets to improve stent re-endothelization, especially in diabetic patients.

Multiple sclerosis (MS) is an autoimmune disorder of the central nervous system (CNS) whose aetiology is only partly understood. Investigating the intricate transcriptional changes occurring in MS brains is critical to unravel novel pathogenic mechanisms and therapeutic targets. Unfortunately, this process is often hindered by the difficulty in retrieving an adequate number of samples. However, by merging data from publicly available datasets, it is possible to identify alterations in gene expression profiles and regulatory pathways that were previously overlooked. Here, we merged microarray gene expression profiles obtained from CNS white matter samples taken from MS donors to identify novel differentially expressed genes (DEGs) linked with MS. Data from three independent datasets (GSE38010, GSE32915, and GSE108000) were combined and used to detect novel DEGs using the Stouffer’s Z-score method. Corresponding regulatory pathways were analysed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway databases. Finally, top up- and down-regulated transcripts were validated by real-time quantitative PCR (qPCR) using an independent set of white matter tissue samples obtained from MS donors with different disease subtypes. There were a total of 1446 DEGs, of which 742 were up-regulated and 704 genes were down-regulated. DEGs were associated with several myelin-related pathways and protein metabolism pathways. Validation studies of selected top up- or down-regulated genes highlighted MS subtype-specific differences in the expression of some of the identified genes, underlining a more complex scenario of white matter pathology amongst people afflicted by this devastating disease.

Abstract Early identification of metastatic or recurrent colorectal cancer (CRC) patients who will be sensitive to FOLFOX (5‐FU, leucovorin and oxaliplatin) therapy is very important. We performed microarray meta‐analysis to identify differentially expressed genes (DEGs) between FOLFOX responders and nonresponders in metastatic or recurrent CRC patients, and found that the expression levels of WASHC4, HELZ, ERN1, RPS6KB1, and APPBP2 were downregulated, while the expression levels of IRF7, EML3, LYPLA2, DRAP1, RNH1, PKP3, TSPAN17, LSS, MLKL, PPP1R7, GCDH, C19ORF24, and CCDC124 were upregulated in FOLFOX responders compared with nonresponders. Subsequent functional annotation showed that DEGs were significantly enriched in autophagy, ErbB signaling pathway, mitophagy, endocytosis, FoxO signaling pathway, apoptosis, and antifolate resistance pathways. Based on those candidate genes, several machine learning algorithms were applied to the training set, then performances of models were assessed via the cross validation method. Candidate models with the best tuning parameters were applied to the test set and the final model showed satisfactory performance. In addition, we also reported that MLKL and CCDC124 gene expression were independent prognostic factors for metastatic CRC patients undergoing FOLFOX therapy.

Early identification of metastatic or recurrent colorectal cancer (CRC) patients who will be sensitive to FOLFOX (5‐FU, leucovorin and oxaliplatin) therapy is very important. We performed microarray meta‐analysis to identify differentially expressed genes (DEGs) between FOLFOX responders and nonresponders in metastatic or recurrent CRC patients, and found that the expression levels of WASHC4, HELZ, ERN1, RPS6KB1, and APPBP2 were downregulated, while the expression levels of IRF7, EML3, LYPLA2, DRAP1, RNH1, PKP3, TSPAN17, LSS, MLKL, PPP1R7, GCDH, C19ORF24, and CCDC124 were upregulated in FOLFOX responders compared with nonresponders. Subsequent functional annotation showed that DEGs were significantly enriched in autophagy, ErbB signaling pathway, mitophagy, endocytosis, FoxO signaling pathway, apoptosis, and antifolate resistance pathways. Based on those candidate genes, several machine learning algorithms were applied to the training set, then performances of models were assessed via the cross validation method. Candidate models with the best tuning parameters were applied to the test set and the final model showed satisfactory performance. In addition, we also reported that MLKL and CCDC124 gene expression were independent prognostic factors for metastatic CRC patients undergoing FOLFOX therapy. [ABSTRACT FROM AUTHOR]

Potato as an essential root crop plays a fundamental role in sustenance security of the world. Viruses are among the most critical pathogens that can decrease the quality of products such as potato and their potential yield. Understanding plant responses to various stresses is an economically important subject in global food security, which is seriously threatened by climate changes. One of the effective methodologies to expand the resistance of potato against various stresses can be identified as the natural defence‐related genes. Microarray meta‐analysis was used for finding common patterns in microarray data sets. The results were filtered out by comparing the resistant and susceptible host data sets in combination with the data derived from biotic and abiotic stress experiments. A total of 42 candidate resistance genes were selected, which were specifically regulated during the potato–virus interaction. Also, 265 genes were recognized to respond to virus infection or other stresses. Integration of transcriptome data sets from various microarray studies gives new insight into the potato–stress interactions. Moreover, the selected genes can be used as candidates to enhance potato resistance against viruses. [ABSTRACT FROM AUTHOR]

Abstract: In vertebrates, BMP signaling has been demonstrated to be sufficient for bone formation in several tissue contexts. This suggests that genes necessary for bone formation are expressed in a BMP signaling dependent manner. However, till date no gene has been reported to be expressed in a BMP signaling dependent manner in bone. Our aim was to identify such genes. On searching the literature we found that several microarray experiments have been conducted where the transcriptome of osteogenic cells in absence and presence of BMP signaling activation have been compared. However, till date, there is no evidence to suggest that any of the genes found to be upregulated in presence of BMP signaling in these microarray analyses is indeed a target of BMP signaling in bone. We wanted to utilize this publicly available information to identify candidate BMP signaling target genes in vivo. We performed a meta-analysis of six such comparable microarray datasets. This analysis and subsequent experiments led to the identification of five targets of BMP signaling in bone that are conserved both in mouse and chick. Of these Lox, Klf10 and Gpr97 are likely to be direct transcriptional targets of BMP signaling pathway. Dpysl3, is a novel BMP signaling target identified in our study. Our data demonstrate that Dpysl3 is important for osteogenic differentiation of mesenchymal cells and is involved in cell secretion. We have demonstrated that the expression of Dpysl3 is co-operatively regulated by BMP signaling and Runx2. Based on our experimental data, in silico analysis of the putative promoter-enhancer regions of Bmp target genes and existing literature, we hypothesize that BMP signaling collaborates with multiple signaling pathways to regulate the expression of a unique set of genes involved in endochondral ossification. [Copyright &y& Elsevier]

Circulating endothelial progenitor cells (EPCs) play an important role in the repair processes of damaged vessels, favoring re-endothelization of stented vessels to minimize restenosis. EPCs number and function is diminished in patients with type 2 diabetes, a known risk factor for restenosis. Considering the impact of EPCs in vascular injury repair, we conducted a meta-analysis of microarray to assess the transcriptomic profile and determine target genes during the differentiation process of EPCs into mature ECs. Five microarray datasets, including 13 EPC and 12 EC samples were analyzed, using the online tool ExpressAnalyst. Differentially expressed genes (DEGs) analysis was done by Limma method, with an | log 2 FC| > 1 and FDR < 0.05. Combined p -value by Fisher exact method was computed for the intersection of datasets. There were 3,267 DEGs, 1,539 up-regulated and 1,728 down-regulated in EPCs, with 407 common DEGs in at least four datasets. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed enrichment for terms related to "AGE-RAGE signaling pathway in diabetic complications." Intersection of common DEGs, KEGG pathways genes and genes in protein-protein interaction network (PPI) identified four key genes, two up-regulated (IL1B and STAT5A) and two down-regulated (IL6 and MAPK11). MicroRNA enrichment analysis of common DEGs depicted five hub microRNA targeting 175 DEGs, including STAT5A, IL6 and MAPK11, with hsa-miR-124 as common regulator. This group of genes and microRNAs could serve as biomarkers of EPCs differentiation during coronary stenting as well as potential therapeutic targets to improve stent re-endothelization, especially in diabetic patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Arencibia and Salazar.)