Microarray-Based Gene Expression Analysis Identifies Potential Diagnostic and Prognostic Biomarkers for Waldenström Macroglobulinemia

Waldenström macroglobulinemia (WM), also known as lymphoplasmacytic lymphoma, is rare but a clinicopathologically distinct B-cell malignancy. This study assessed differentially expressed genes (DEGs) to identify potential WM biomarkers and uncover the underlying the molecular mechanisms of WM progression using gene expression profiles from the Gene Expression Omnibus database. DEGs were identified using the LIMMA package and their potential functions were then analyzed by using the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and the protein-protein interaction (PPI) network analysis by using the Search Tool for the Retrieval of Interacting Genes/Proteins database. Data showed that among 1,756 DEGs, 926 were upregulated and 830 were downregulated by comparing WM BM CD19+ with normal PB CD19+ B cell samples, whereas 241 DEGs (95 upregulated and 146 downregulated) were identified by comparing WM BM CD138+ with normal BM CD138+ plasma cell samples. The DEGs were enriched in different GO terms and pathways, including the apoptotic process, cell cycle arrest, immune response, cell adhesion, mitogen-activated protein kinase signaling pathway, toll-like receptor signaling pathway, and the gonadotropin-releasing hormone signaling pathway. Hub nodes in the PPI network included CDK1, JUN, CREBBP, EP300, CAD, CDK2, and MAPK14. Bioinformatics analysis of the GSE9656 dataset identified 7 hub genes that might play an important role in WM development and progression. Some of the candidate genes and pathways may serve as promising therapeutic targets for WM.

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Meta-Analyses of Multiple Gene Expression Profiles to Screen Hub Genes Related to Osteoarthritis

Public Health Genomics ◽

10.1159/000517308 ◽

2021 ◽

Vol 24 (5-6) ◽

pp. 267-279

Author(s):

Xianyang Zhu ◽

Wen Guo

Keyword(s):

Gene Expression ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Meta Analysis ◽

Wnt Signaling Pathway ◽

Gene Expression Profiles ◽

Enrichment Analysis ◽

Receptor Interaction ◽

Ppi Network ◽

Hub Genes

Background: This study aimed to screen and validate the crucial genes involved in osteoarthritis (OA) and explore its potential molecular mechanisms. Methods: Four expression profile datasets related to OA were downloaded from the Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) from 4 microarray patterns were identified by the meta-analysis method. The weighted gene co-expression network analysis (WGCNA) method was used to investigate stable modules most related to OA. In addition, a protein-protein interaction (PPI) network was built to explore hub genes in OA. Moreover, OA-related genes and pathways were retrieved from Comparative Toxicogenomics Database (CTD). Results: A total of 1,136 DEGs were identified from 4 datasets. Based on these DEGs, WGCNA further explored 370 genes included in the 3 OA-related stable modules. A total of 10 hub genes were identified in the PPI network, including AKT1, CDC42, HLA-DQA2, TUBB, TWISTNB, GSK3B, FZD2, KLC1, GUSB, and RHOG. Besides, 5 pathways including “Lysosome,” “Pathways in cancer,” “Wnt signaling pathway,” “ECM-receptor interaction” and “Focal adhesion” in CTD and enrichment analysis and 5 OA-related hub genes (including GSK3B, CDC42, AKT1, FZD2, and GUSB) were identified. Conclusion: In this study, the meta-analysis was used to screen the central genes associated with OA in a variety of gene expression profiles. Three OA-related modules (green, turquoise, and yellow) containing 370 genes were identified through WGCNA. It was discovered through the gene-pathway network that GSK3B, CDC42, AKT1, FZD2, and GUSB may be key genes related to the progress of OA and may become promising therapeutic targets.

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Gene Expression Profile Signature of Aggressive Waldenström Macroglobulinemia with Chromosome 6q Deletion

BioMed Research International ◽

10.1155/2018/6728128 ◽

2018 ◽

Vol 2018 ◽

pp. 1-8 ◽

Cited By ~ 1

Author(s):

Naohiro Sekiguchi ◽

Junko Nomoto ◽

Akihisa Nagata ◽

Masahiro Kiyota ◽

Ichiro Fukuda ◽

...

Keyword(s):

Gene Expression ◽

B Cell ◽

Signaling Pathway ◽

B Lymphocyte ◽

B Cell Lymphoma ◽

P Value ◽

Waldenström Macroglobulinemia ◽

Go Analysis ◽

Waldenstrom Macroglobulinemia ◽

Bcr Signaling

Background. Waldenström macroglobulinemia (WM) is a rare, indolent B-cell lymphoma. Clinically, chromosome 6q deletion (6q del) including loss of the B lymphocyte-induced maturation protein 1 gene (BLIMP-1) is reported to be associated with poor prognosis. However, it remains unclear how the underlying biological mechanism contributes to the aggressiveness of WM with 6q del. Methods. Here, we conducted oligonucleotide microarray analysis to clarify the differences in gene expression between WM with and without 6q del. Gene ontology (GO) analysis was performed to identify the main pathways underlying differences in gene expression. Eight bone marrow formalin-fixed paraffin-embedded samples of WM were processed for interphase fluorescence in situ hybridization analysis, and three were shown to have 6q del. Results. GO analysis revealed significant terms including “lymphocyte activation” (corrected p value=6.68E-11), which included 31 probes. Moreover, IL21R and JAK3 expression upregulation and activation of the B-cell receptor signaling (BCR) pathway including CD79a, SYK, BLNK, PLCγ2, and CARD11 were detected in WM with 6q del compared with WM without 6q del. Conclusion. The present study suggested that the BCR signaling pathway and IL21R expression are activated in WM with 6q del. Moreover, FOXP1 and CBLB appear to act as positive regulators of the BCR signaling pathway. These findings might be attributed to the aggressiveness of the WM with 6q del expression signature.

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Identifying the Involvement of Pro-Inflammatory Signal in Hippocampal Gene Expression Changes after Experimental Ischemia: Transcriptome-Wide Analysis

Biomedicines ◽

10.3390/biomedicines9121840 ◽

2021 ◽

Vol 9 (12) ◽

pp. 1840

Author(s):

Galina T. Shishkina ◽

Natalia V. Gulyaeva ◽

Dmitriy A. Lanshakov ◽

Tatyana S. Kalinina ◽

Mikhail V. Onufriev ◽

...

Keyword(s):

Gene Expression ◽

Signaling Pathway ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Artery Occlusion ◽

Intracerebral Administration ◽

Acute Cerebral Ischemia ◽

Pathway Analyses ◽

The Impact

Acute cerebral ischemia induces distant inflammation in the hippocampus; however, molecular mechanisms of this phenomenon remain obscure. Here, hippocampal gene expression profiles were compared in two experimental paradigms in rats: middle cerebral artery occlusion (MCAO) and intracerebral administration of lipopolysaccharide (LPS). The main finding is that 10 genes (Clec5a, CD14, Fgr, Hck, Anxa1, Lgals3, Irf1, Lbp, Ptx3, Serping1) may represent key molecular links underlying acute activation of immune cells in the hippocampus in response to experimental ischemia. Functional annotation clustering revealed that these genes built the same clusters related to innate immunity/immunity/innate immune response in all MCAO differentially expressed genes and responded to the direct pro-inflammatory stimulus group. The gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses also indicate that LPS-responding genes were the most abundant among the genes related to “positive regulation of tumor necrosis factor biosynthetic process”, “cell adhesion”, “TNF signaling pathway”, and “phagosome” as compared with non-responding ones. In contrast, positive and negative “regulation of cell proliferation” and “HIF-1 signaling pathway” mostly enriched with genes that did not respond to LPS. These results contribute to understanding genomic mechanisms of the impact of immune/inflammatory activation on expression of hippocampal genes after focal brain ischemia.

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Screening and identification of key biomarkers and related transcription factors in ovarian cancer by integrated bioinformatics analysis

10.21203/rs.3.rs-20327/v1 ◽

2020 ◽

Author(s):

Wenqiong Qin ◽

Qiang Yuan ◽

Yi Liu ◽

Ying Zeng ◽

Dandan Ke ◽

...

Keyword(s):

Gene Expression ◽

Ovarian Cancer ◽

Molecular Mechanisms ◽

Malignant Tumors ◽

Expression Profiles ◽

Expression Patterns ◽

Gene Expression Profiles ◽

Transcriptional Factor ◽

Ppi Network ◽

Hub Genes

Abstract Background Ovarian tumors are the most malignant tumors of all gynecological tumors, and although multiple efforts have been made to elucidate the pathogenesis, the molecular mechanisms of ovarian cancer remain unclear. Methods In this study, we used bioinformatics to identify genes involved in the carcinogenesis and progression of ovarian cancer. Three microarray datasets (GSE14407, GSE29450, and GSE54388) were downloaded from Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were identified. For a more in-depth understanding of the DEGs, functional and pathway enrichment analyses were performed and a protein-protein interaction (PPI) network was constructed. The associated transcriptional factor (TFs) regulation network of the DEGs was also constructed. Kaplan Meier-plotter, Gene Expression Profiling Interactive Analysis (GEPIA), the Human Protein Atlas (HPA) database and the Oncomine database were implemented to validated hub genes. Results A total of 514 DEGs were detected after the analysis of the three gene expression profiles, including 171 upregulated and 343 downregulated genes. Nine hub genes ( CCNB1, CDK1, BUB1, CDC20, CCNA2, BUB1B, AURKA, RRM2, TTK) were obtained from the PPI network. Survival analysis showed that high expression levels of seven hub genes ( CCNB1, BUB1, BUB1B, CCNA2, AURKA, CDK1, and RRM2) were associated with worse overall survival (OS). All of seven hub genes were discovered highly expressed in ovarian cancer samples compared to normal ovary samples in GEPIA. Immunostaining results from the HPA database suggested that the expressions of CCNB1, CCNA2, AURKA, and CDK1 proteins were increased in ovarian cancer tissues, and Oncomine analysis indicated that the expression patterns of BUB1B, CCNA2, AURKA, CCNB1, CDK1, and BUB1 have associated with patient clinicopathological information. From the gene-transcriptional factor network, key transcriptional factors, such as POLR2A, ZBTB11, KLF9, and ELF1, were identified with close interactions with these hub genes. Conclusion We identified six significant DEGs with poor prognosis in ovarian cancer, which could be of potential biomarkers for ovarian cancer patients.

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Modulation of the Immune Response by Deferasirox in Myelodysplastic Syndrome Patients

Pharmaceuticals ◽

10.3390/ph14010041 ◽

2021 ◽

Vol 14 (1) ◽

pp. 41

Author(s):

Hana Votavova ◽

Zuzana Urbanova ◽

David Kundrat ◽

Michaela Dostalova Merkerova ◽

Martin Vostry ◽

...

Keyword(s):

Gene Expression ◽

Immune Response ◽

Blood Cell ◽

Myelodysplastic Syndrome ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Adaptive Immune Response ◽

Gene Expression Profiles ◽

Iron Chelator ◽

Multiple Cancer

Deferasirox (DFX) is an oral iron chelator used to reduce iron overload (IO) caused by frequent blood cell transfusions in anemic myelodysplastic syndrome (MDS) patients. To study the molecular mechanisms by which DFX improves outcome in MDS, we analyzed the global gene expression in untreated MDS patients and those who were given DFX treatment. The gene expression profiles of bone marrow CD34+ cells were assessed by whole-genome microarrays. Initially, differentially expressed genes (DEGs) were determined between patients with normal ferritin levels and those with IO to address the effect of excessive iron on cellular pathways. These DEGs were annotated to Gene Ontology terms associated with cell cycle, apoptosis, adaptive immune response and protein folding and were enriched in cancer-related pathways. The deregulation of multiple cancer pathways in iron-overloaded patients suggests that IO is a cofactor favoring the progression of MDS. The DEGs between patients with IO and those treated with DFX were involved predominantly in biological processes related to the immune response and inflammation. These data indicate DFX modulates the immune response mainly via neutrophil-related genes. Suppression of negative regulators of blood cell differentiation essential for cell maturation and upregulation of heme metabolism observed in DFX-treated patients may contribute to the hematopoietic improvement.

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Bioinformatics analysis of differentially expressed genes and pathways in the development of cervical cancer

BMC Cancer ◽

10.1186/s12885-021-08412-4 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Baojie Wu ◽

Shuyi Xi

Keyword(s):

Gene Expression ◽

Cervical Cancer ◽

Differentially Expressed Genes ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Molecular Targets ◽

Enrichment Analysis ◽

Ppi Network ◽

Hub Genes ◽

Kegg Pathways

Abstract Background This study aimed to explore and identify key genes and signaling pathways that contribute to the progression of cervical cancer to improve prognosis. Methods Three gene expression profiles (GSE63514, GSE64217 and GSE138080) were screened and downloaded from the Gene Expression Omnibus database (GEO). Differentially expressed genes (DEGs) were screened using the GEO2R and Venn diagram tools. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Gene set enrichment analysis (GSEA) was performed to analyze the three gene expression profiles. Moreover, a protein–protein interaction (PPI) network of the DEGs was constructed, and functional enrichment analysis was performed. On this basis, hub genes from critical PPI subnetworks were explored with Cytoscape software. The expression of these genes in tumors was verified, and survival analysis of potential prognostic genes from critical subnetworks was conducted. Functional annotation, multiple gene comparison and dimensionality reduction in candidate genes indicated the clinical significance of potential targets. Results A total of 476 DEGs were screened: 253 upregulated genes and 223 downregulated genes. DEGs were enriched in 22 biological processes, 16 cellular components and 9 molecular functions in precancerous lesions and cervical cancer. DEGs were mainly enriched in 10 KEGG pathways. Through intersection analysis and data mining, 3 key KEGG pathways and related core genes were revealed by GSEA. Moreover, a PPI network of 476 DEGs was constructed, hub genes from 12 critical subnetworks were explored, and a total of 14 potential molecular targets were obtained. Conclusions These findings promote the understanding of the molecular mechanism of and clinically related molecular targets for cervical cancer.

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The t(14;18) defines a unique subset of diffuse large B-cell lymphoma with a germinal center B-cell gene expression profile

Blood ◽

10.1182/blood.v99.7.2285 ◽

2002 ◽

Vol 99 (7) ◽

pp. 2285-2290 ◽

Cited By ~ 202

Author(s):

James Z. Huang ◽

Warren G. Sanger ◽

Timothy C. Greiner ◽

Louis M. Staudt ◽

Dennis D. Weisenburger ◽

...

Keyword(s):

Gene Expression ◽

B Cell ◽

Gene Expression Profile ◽

Expression Profile ◽

Germinal Center ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Germinal Center B Cell ◽

Cell Gene Expression ◽

Cell Gene

Recently we have identified subgroups of de novo primary diffuse large B-cell lymphoma (DLBCL) based on complementary DNA microarray-generated gene expression profiles. To correlate the gene expression profiles with cytogenetic abnormalities in these DLBCLs, we examined the occurrence of the t(14;18)(q32;q21) in the 2 distinctive subgroups of DLBCL: one with the germinal center B-cell gene expression signature and the other with the activated B cell–like gene expression signature. The t(14;18) was detected in 7 of 35 cases (20%). All 7 t(14;18)-positive cases had a germinal center B-cell gene expression profile, representing 35% of the cases in this subgroup, and 6 of these 7 cases had very similar gene expression profiles. The expression of bcl-2 and bcl-6 proteins was not significantly different between the t(14;18)-positive and -negative cases, whereas CD10 was detected only in the group with the germinal center B-cell expression profile, and CD10 was most frequently expressed in the t(14;18)-positive cases. This study supports the validity of subdividing DLBCL into 2 major subgroups by gene expression profiling, with the t(14;18) being an important event in the pathogenesis of a subset of DLBCL arising from germinal center B cells. CD10 protein expression is useful in identifying cases of DLBCL with a germinal center B-cell gene expression profile and is often expressed in cases with the t(14;18).

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Transcriptome-wide gene expression plasticity in Stipa grandis in response to grazing intensity differences

10.22541/au.160655409.95797246/v1 ◽

2020 ◽

Author(s):

Zhenhua Dang ◽

Yuanyuan Jia ◽

Yunyun Tian ◽

Jiabin Li ◽

Yanan Zhang ◽

...

Keyword(s):

Gene Expression ◽

Metabolic Pathways ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Grazing Intensity ◽

Glycolate Oxidase ◽

Bisphosphate Carboxylase ◽

Grazing Intensities

Organisms have evolved effective and distinct adaptive strategies to survive. Stipa grandis is one of the widespread dominant species on the typical steppe of the Inner Mongolian Plateau, and is regarded as a suitable species for studying the effects of grazing in this region. Although phenotypic (morphological and physiological) variations in S. grandis in response to long-term grazing have been identified, the molecular mechanisms underlying adaptations and plastic responses remain largely unknown. Accordingly, we performed a transcriptomic analysis to investigate changes in gene expression of S. grandis under four different grazing intensities. A total of 2,357 differentially expressed genes (DEGs) were identified among the tested grazing intensities, suggesting long-term grazing resulted in gene expression plasticity that affected diverse biological processes and metabolic pathways in S. grandis. DEGs were identified that indicated modulation of Calvin–Benson cycle and photorespiration metabolic pathways. The key gene´expression profiles encoding various proteins (e.g., Ribulose-1,5-bisphosphate carboxylase/oxygenase, fructose-1,6-bisphosphate aldolase, glycolate oxidase etc.) involved in these pathways suggest that they may synergistically respond to grazing to increase the resilience and stress tolerance of S. grandis. Our findings provide scientific clues for improving grassland use and protection, and identify important questions to address in future transcriptome studies.

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SMC4, CCNB1 and CKS1B as potential targets and new critical biomarkers for the prognosis of human bladder cancer

10.21203/rs.3.rs-595148/v1 ◽

2021 ◽

Author(s):

Hongpeng Fang ◽

Zhansen Huang ◽

Xianzi Zeng ◽

Jiaming Wan ◽

Jieying Wu ◽

...

Keyword(s):

Gene Expression ◽

Bladder Cancer ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Gene Expression Omnibus ◽

Transcriptional Level ◽

Hub Genes ◽

Kaplan Meier ◽

High Form

Abstract Background As a common malignant cancer of the urinary system, the precise molecular mechanisms of bladder cancer remain to be illuminated. The purpose of this study was to identify core genes with prognostic value as potential oncogenes for the diagnosis, prognosis or novel therapeutic targets of bladder cancer. Methods The gene expression profiles GSE3167 and GSE7476 were available from the Gene Expression Omnibus (GEO) database. Next, PPI network was built to filter the hub gene through the STRING database and Cytoscape software and GEPIA and Kaplan-Meier plotter were implemented. Frequency and type of hub genes and sub groups analysis were performed in cBioportal and ULCAN database. Finally,We used RT-qPCR to confirm our results. Results Totally, 251 DEGs were excavated from two datasets in our study. We only founded high expression of SMC4, TYMS, CCNB1, CKS1B, NUSAP1 and KPNA2 was associated with worse outcomes in bladder cancer patients and no matter from the type of mutation or at the transcriptional level of hub genes, the tumor showed a high form of expression. However, only the expression of SMC4,CCNB1and CKS1B remained changed between the cancer and the normal samples in our results of RT-qPCR. Conclusion In conclusion,These findings indicate that the SMC4,CCNB1 and CKS1B may serve as critical biomarkers in the development and poor prognosis.

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Convergent evolution of venom gland transcriptomes across Metazoa

10.1101/2021.07.04.451048 ◽

2021 ◽

Author(s):

Giulia Zancolli ◽

Maarten Reijnders ◽

Robert Waterhouse ◽

Marc Robinson-Rechavi

Keyword(s):

Gene Expression ◽

Regulatory Networks ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Venom Gland ◽

Bioactive Molecules ◽

Specific Gene ◽

Animal Kingdom ◽

Venom Glands

Animals have repeatedly evolved specialized organs and anatomical structures to produce and deliver a cocktail of potent bioactive molecules to subdue prey or predators: venom. This makes it one of the most widespread convergent functions in the animal kingdom. Whether animals have adopted the same genetic toolkit to evolved venom systems is a fascinating question that still eludes us. Here, we performed the first comparative analysis of venom gland transcriptomes from 20 venomous species spanning the main Metazoan lineages, to test whether different animals have independently adopted similar molecular mechanisms to perform the same function. We found a strong convergence in gene expression profiles, with venom glands being more similar to each other than to any other tissue from the same species, and their differences closely mirroring the species phylogeny. Although venom glands secrete some of the fastest evolving molecules (toxins), their gene expression does not evolve faster than evolutionarily older tissues. We found 15 venom gland specific gene modules enriched in endoplasmic reticulum stress and unfolded protein response pathways, indicating that animals have independently adopted stress response mechanisms to cope with mass production of toxins. This, in turns, activates regulatory networks for epithelial development, cell turnover and maintenance which seem composed of both convergent and lineage-specific factors, possibly reflecting the different developmental origins of venom glands. This study represents the first step towards an understanding of the molecular mechanisms underlying the repeated evolution of one of the most successful adaptive traits in the animal kingdom.

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