A Bioinformatics Approach to Identifying Potential Biomarkers for Cryptosporidium parvum: A Coccidian Parasite Associated with Fetal Diarrhea

Cryptosporidium parvum (C. parvum) is a protozoan parasite known for cryptosporidiosis in pre-weaned calves. Animals and patients with immunosuppression are at risk of developing the disease, which can cause potentially fatal diarrhoea. The present study aimed to construct a network biology framework based on the differentially expressed genes (DEGs) of C. parvum infected subjects. In this way, the gene expression profiling analysis of C. parvum infected individuals can give us a snapshot of actively expressed genes and transcripts under infection conditions. In the present study, we have analyzed microarray data sets and compared the gene expression profiles of the patients with the different data sets of the healthy control. Using a network medicine approach to identify the most influential genes in the gene interaction network, we uncovered essential genes and pathways related to C. parvum infection. We identified 164 differentially expressed genes (109 up- and 54 down-regulated DEGs) and allocated them to pathway and gene set enrichment analysis. The results underpin the identification of seven significant hub genes with high centrality values: ISG15, MX1, IFI44L, STAT1, IFIT1, OAS1, IFIT3, RSAD2, IFITM1, and IFI44. These genes are associated with diverse biological processes not limited to host interaction, type 1 interferon production, or response to IL-gamma. Furthermore, four genes (IFI44, IFIT3, IFITM1, and MX1) were also discovered to be involved in innate immunity, inflammation, apoptosis, phosphorylation, cell proliferation, and cell signaling. In conclusion, these results reinforce the development and implementation of tools based on gene profiles to identify and treat Cryptosporidium parvum-related diseases at an early stage.

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Identification of Diagnostic Markers for Breast Cancer Based on Differential Gene Expression and Pathway Network

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.811585 ◽

2022 ◽

Vol 9 ◽

Author(s):

Shumei Zhang ◽

Haoran Jiang ◽

Bo Gao ◽

Wen Yang ◽

Guohua Wang

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Differentially Expressed Genes ◽

Interaction Network ◽

Enrichment Analysis ◽

Gene Interaction ◽

Diagnostic Markers ◽

Differentially Expressed ◽

Breast Cancer Patients ◽

Gene Interaction Network

Background: Breast cancer is the second largest cancer in the world, the incidence of breast cancer continues to rise worldwide, and women’s health is seriously threatened. Therefore, it is very important to explore the characteristic changes of breast cancer from the gene level, including the screening of differentially expressed genes and the identification of diagnostic markers.Methods: The gene expression profiles of breast cancer were obtained from the TCGA database. The edgeR R software package was used to screen the differentially expressed genes between breast cancer patients and normal samples. The function and pathway enrichment analysis of these genes revealed significant enrichment of functions and pathways. Next, download these pathways from KEGG website, extract the gene interaction relations, construct the KEGG pathway gene interaction network. The potential diagnostic markers of breast cancer were obtained by combining the differentially expressed genes with the key genes in the network. Finally, these markers were used to construct the diagnostic prediction model of breast cancer, and the predictive ability of the model and the diagnostic ability of the markers were verified by internal and external data.Results: 1060 differentially expressed genes were identified between breast cancer patients and normal controls. Enrichment analysis revealed 28 significantly enriched pathways (p < 0.05). They were downloaded from KEGG website, and the gene interaction relations were extracted to construct the gene interaction network of KEGG pathway, which contained 1277 nodes and 7345 edges. The key nodes with a degree greater than 30 were extracted from the network, containing 154 genes. These 154 key genes shared 23 genes with differentially expressed genes, which serve as potential diagnostic markers for breast cancer. The 23 genes were used as features to construct the SVM classification model, and the model had good predictive ability in both the training dataset and the validation dataset (AUC = 0.960 and 0.907, respectively).Conclusion: This study showed that the difference of gene expression level is important for the diagnosis of breast cancer, and identified 23 breast cancer diagnostic markers, which provides valuable information for clinical diagnosis and basic treatment experiments.

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HIV-1 Infection Transcriptomics: Meta-Analysis of CD4+ T Cells Gene Expression Profiles

Viruses ◽

10.3390/v13020244 ◽

2021 ◽

Vol 13 (2) ◽

pp. 244 ◽

Cited By ~ 1

Author(s):

Antonio Victor Campos Coelho ◽

Rossella Gratton ◽

João Paulo Britto de Melo ◽

José Leandro Andrade-Santos ◽

Rafael Lima Guimarães ◽

...

Keyword(s):

Gene Expression ◽

T Cells ◽

Differentially Expressed Genes ◽

Cd4 T Cells ◽

Expression Profiles ◽

Meta Analysis ◽

Differentially Expressed ◽

Rna Seq ◽

Infected Cells ◽

Hiv 1

HIV-1 infection elicits a complex dynamic of the expression various host genes. High throughput sequencing added an expressive amount of information regarding HIV-1 infections and pathogenesis. RNA sequencing (RNA-Seq) is currently the tool of choice to investigate gene expression in a several range of experimental setting. This study aims at performing a meta-analysis of RNA-Seq expression profiles in samples of HIV-1 infected CD4+ T cells compared to uninfected cells to assess consistently differentially expressed genes in the context of HIV-1 infection. We selected two studies (22 samples: 15 experimentally infected and 7 mock-infected). We found 208 differentially expressed genes in infected cells when compared to uninfected/mock-infected cells. This result had moderate overlap when compared to previous studies of HIV-1 infection transcriptomics, but we identified 64 genes already known to interact with HIV-1 according to the HIV-1 Human Interaction Database. A gene ontology (GO) analysis revealed enrichment of several pathways involved in immune response, cell adhesion, cell migration, inflammation, apoptosis, Wnt, Notch and ERK/MAPK signaling.

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Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Hashimoto’s Thyroiditis

10.21203/rs.3.rs-1023446/v1 ◽

2021 ◽

Author(s):

Li Guoquan ◽

Du Junwei ◽

He Qi ◽

Fu Xinghao ◽

Ji Feihong ◽

...

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Inflammatory Responses ◽

Expression Profiles ◽

Treatment Options ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Chronic Lymphocytic Thyroiditis ◽

Hub Genes

Abstract BackgroundHashimoto's thyroiditis (HT), also known as chronic lymphocytic thyroiditis, is a common autoimmune disease, which mainly occurs in women. The early manifestation was hyperthyroidism, however, hypothyroidism may occur if HT was not controlled for a long time. Numerous studies have shown that multiple factors, including genetic, environmental, and autoimmune factors, were involved in the pathogenesis of the disease, but the exact mechanisms were not yet clear. The aim of this study was to identify differentially expressed genes (DEGs) by comprehensive analysis and to provide specific insights into HT. MethodsTwo gene expression profiles (GSE6339, GSE138198) about HT were downloaded from the Gene Expression Omnibus (GEO) database. The DEGs were assessed between the HT and normal groups using the GEO2R. The DEGs were then sent to the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The hub genes were discovered using Cytoscape and CytoHubba. Finally, NetworkAnalyst was utilized to create the hub genes' targeted microRNAs (miRNAs). ResultsA total of 62 DEGs were discovered, including 60 up-regulated and 2 down-regulated DEGs. The signaling pathways were mainly engaged in cytokine interaction and cytotoxicity, and the DEGs were mostly enriched in immunological and inflammatory responses. IL2RA, CXCL9, IL10RA, CCL3, CCL4, CCL2, STAT1, CD4, CSF1R, and ITGAX were chosen as hub genes based on the results of the protein-protein interaction (PPI) network and CytoHubba. Five miRNAs, including mir-24-3p, mir-223-3p, mir-155-5p, mir-34a-5p, mir-26b-5p, and mir-6499-3p, were suggested as likely important miRNAs in HT. ConclusionsThese hub genes, pathways and miRNAs contribute to a better understanding of the pathophysiology of HT and offer potential treatment options for HT.

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Integrative transcriptome data mining for identification of core lncRNAs in breast cancer

PeerJ ◽

10.7717/peerj.7821 ◽

2019 ◽

Vol 7 ◽

pp. e7821 ◽

Cited By ~ 7

Author(s):

Xiaoming Zhang ◽

Jing Zhuang ◽

Lijuan Liu ◽

Zhengguo He ◽

Cun Liu ◽

...

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Prognostic Value ◽

Early Stage ◽

Expression Profiles ◽

Diagnostic Value ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Differentially Expressed ◽

Data Set

Background Cumulative evidence suggests that long non-coding RNAs (lncRNAs) play an important role in tumorigenesis. This study aims to identify lncRNAs that can serve as new biomarkers for breast cancer diagnosis or screening. Methods First, the linear fitting method was used to identify differentially expressed genes from the breast cancer RNA expression profiles in The Cancer Genome Atlas (TCGA). Next, the diagnostic value of all differentially expressed lncRNAs was evaluated using a receiver operating characteristic (ROC) curve. Then, the top ten lncRNAs with the highest diagnostic value were selected as core genes for clinical characteristics and prognosis analysis. Furthermore, core lncRNA-mRNA co-expression networks based on weighted gene co-expression network analysis (WGCNA) were constructed, and functional enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). The differential expression level and diagnostic value of core lncRNAs were further evaluated by using independent data set from Gene Expression Omnibus (GEO). Finally, the expression status and prognostic value of core lncRNAs in various tumors were analyzed based on Gene Expression Profiling Interactive Analysis (GEPIA). Results Seven core lncRNAs (LINC00478, PGM5-AS1, AL035610.1, MIR143HG, RP11-175K6.1, AC005550.4, and MIR497HG) have good single-factor diagnostic value for breast cancer. AC093850.2 has a prognostic value for breast cancer. AC005550.4 and MIR497HG can better distinguish breast cancer patients in early-stage from the advanced-stage. Low expression of MAGI2-AS3, LINC00478, AL035610.1, MIR143HG, and MIR145 may be associated with lymph node metastasis in breast cancer. Conclusion Our study provides candidate biomarkers for the diagnosis and prognosis of breast cancer, as well as a bioinformatics basis for the further elucidation of the molecular pathological mechanism of breast cancer.

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Insight into Molecular Profile Changes after Skeletal Muscle Contusion Using Microarray and Bioinformatics Analyses

10.21203/rs.3.rs-85830/v1 ◽

2020 ◽

Author(s):

Na Li ◽

Ru-feng Bai ◽

Chun Li ◽

Li-hong Dang ◽

Qiu-xiang Du ◽

...

Keyword(s):

Gene Expression ◽

Network Analysis ◽

Differentially Expressed Genes ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Healing Process ◽

Differentially Expressed ◽

Molecular Profile ◽

Wound Age ◽

Functional Modules

Abstract Background: Muscle trauma frequently occurs in daily life. However, the molecular mechanisms of muscle healing, which partly depend on the extent of the damage, are not well understood. This study aimed to investigate gene expression profiles following mild and severe muscle contusion, and to provide more information about the molecular mechanisms underlying the repair process.Methods: A total of 33 rats were divided randomly into control (n = 3), mild contusion (n = 15), and severe contusion (n = 15) groups; the contusion groups were further divided into five subgroups (1, 3, 24, 48, and 168 h post-injury; n = 3 per subgroup). Then full genome microarray of RNA isolated from muscle tissue was performed to access the gene expression changes during healing process.Results: A total of 2,844 and 2,298 differentially expressed genes were identified in the mild and severe contusion groups, respectively. The analysis of the overlapping differentially expressed genes showed that there are common mechanisms of transcriptomic repair of mild and severe contusion within 48 h post-contusion. This was supported by the results of principal component analysis, hierarchical clustering, and weighted gene co‐expression network analysis of the 1,620 coexpressed genes in mildly and severely contused muscle. From these analyses, we discovered that the gene profiles in functional modules and temporal clusters were similar between the mild and severe contusion groups; moreover, the genes showed time-dependent patterns of expression, which allowed us to identify useful markers of wound age. We then performed an analysis of the functions of genes (including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway annotation, and protein–protein interaction network analysis) in the functional modules and temporal clusters, and the hub genes in each module–cluster pair were identified. Interestingly, we found that genes downregulated within 24−48 h of the healing process were largely associated with metabolic processes, especially oxidative phosphorylation of reduced nicotinamide adenine dinucleotide phosphate, which has been rarely reported. Conclusions: These results improve our understanding of the molecular mechanisms underlying muscle repair, and provide a basis for further studies of wound age estimation.

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Gene Expression Profiles of Papillary Thyroid Microcarcinoma

International Surgery ◽

10.9738/intsurg-d-17-00049.1 ◽

2017 ◽

Vol 102 (1-2) ◽

pp. 39-46 ◽

Cited By ~ 1

Author(s):

Woo Young Kim ◽

Jae Bok Lee ◽

Seung Pil Jung ◽

Hoon Yub Kim ◽

Sang Uk Woo ◽

...

Keyword(s):

Gene Expression ◽

Gene Expression Profile ◽

Differentially Expressed Genes ◽

Expression Profile ◽

Expression Profiles ◽

Differentially Expressed ◽

Papillary Thyroid Microcarcinoma ◽

Papillary Thyroid ◽

Normal Thyroid ◽

Thyroid Microcarcinoma

The objective was to identify gene expression profile of papillary thyroid microcarcinoma. To help improve diagnosis of papillary thyroid microcarcinoma, we performed gene expression profiling and compared it to pair normal thyroid tissues. We performed microarray analysis with 6 papillary thyroid microcarcinoma and 6 pair normal thyroid tissues. Differentially expressed genes were selected using paired t test, linear models for microarray data, and significance analysis of microarrays. Real-time quantitative reverse transcription–polymerase chain reaction was used to validate the representative 10 genes (MET, TIMP1, QPCT, PROS1, LRP4, SDC4, CITED1, DPP4, LRRK2, RUNX2). We identified 91 differentially expressed genes (84 upregulated and 7 downregulated) in the gene expression profile and validated 10 genes of the profile. We identified a significant genetic difference between papillary thyroid microcarcinoma and normal tissue by 10 upregulated genes greater than 2-fold (P < 0.05).

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Integrated Transcriptomic Analysis of Necrosis-related Gene in Diffuse Gliomas

Journal of Neurological Surgery Part A Central European Neurosurgery ◽

10.1055/s-0039-1683448 ◽

2019 ◽

Vol 80 (04) ◽

pp. 240-249

Author(s):

Jiajia Wang ◽

Jie Ma

Keyword(s):

Gene Expression ◽

High Risk ◽

Differentially Expressed Genes ◽

Expression Profiles ◽

Prognostic Index ◽

Gene Expression Profiles ◽

Risk Groups ◽

Low Risk ◽

Differentially Expressed ◽

Low Grade

Glioblastoma multiforme (GBM), an aggressive brain tumor, is characterized histologically by the presence of a necrotic center surrounded by so-called pseudopalisading cells. Pseudopalisading necrosis has long been used as a prognostic feature. However, the underlying molecular mechanism regulating the progression of GBMs remains unclear. We hypothesized that the gene expression profiles of individual cancers, specifically necrosis-related genes, would provide objective information that would allow for the creation of a prognostic index. Gene expression profiles of necrotic and nonnecrotic areas were obtained from the Ivy Glioblastoma Atlas Project (IVY GAP) database to explore the differentially expressed genes.A robust signature of seven genes was identified as a predictor for glioblastoma and low-grade glioma (GBM/LGG) in patients from The Cancer Genome Atlas (TCGA) cohort. This set of genes was able to stratify GBM/LGG and GBM patients into high-risk and low-risk groups in the training set as well as the validation set. The TCGA, Repository for Molecular Brain Neoplasia Data (Rembrandt), and GSE16011 databases were then used to validate the expression level of these seven genes in GBMs and LGGs. Finally, the differentially expressed genes (DEGs) in the high-risk and low-risk groups were subjected to gene ontology enrichment, Kyoto Encyclopedia of Genes and Genomes pathway, and gene set enrichment analyses, and they revealed that these DEGs were associated with immune and inflammatory responses. In conclusion, our study identified a novel seven-gene signature that may guide the prognostic prediction and development of therapeutic applications.

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The Expression of Human Placental Genes Related to Carotenoid/retinoid Metabolism and Pathways (P02-005-19)

Current Developments in Nutrition ◽

10.1093/cdn/nzz029.p02-005-19 ◽

2019 ◽

Vol 3 (Supplement_1) ◽

Author(s):

Xiaoming Gong ◽

Lewis Rubin

Keyword(s):

Gene Expression ◽

Microarray Analysis ◽

Fetal Development ◽

Expression Profiles ◽

Expression Patterns ◽

Gene Set Enrichment Analysis ◽

Differentially Expressed ◽

Retinoid Metabolism ◽

Expression Of Genes ◽

Β Carotene

Abstract Objectives Carotenoid/retinoids status and metabolism are essential for normal placental and fetal development. Both deficiencies and excess of retinoids and some carotenoids are associated with adverse pregnancy outcomes, such as preeclampsia and preterm birth. A group of important genes involved in regulating carotenoid/retinoid metabolism and maternal to fetal transfer in human placenta. The objective of this study is to analyze (a) the expression of genes critical for regulating carotenoid/retinoid metabolism and maternal-fetal transport in human trophoblasts and (b) placental transcriptional profiles of these pathways in response to carotenoid exposure. Methods Human cytotrophoblasts (CTBs) were isolated from term placentas. CTB RNA was used to analyze the expression of genes involved in carotenoid/retinoid metabolism and pathways by qRT-PCT. First trimester-like trophoblasts (HTR-8/SVneo) were treated with either β-carotene or lycopene. RNAs were isolated and gene expression were analyzed by DNA microarrays. Results Human CTBs express retinoid metabolism and pathways-related genes, including Stra6, Lrat, Rdh5, Rdh10, Aldh1a1, Aldh1a2, Aldh1a3, Aldh8a1, Cyp26a1, and Cyp26b1, but not carotenoid metabolism genes, BCO1 and BCO2. Microarray analysis of placental gene expression profile revealed a total of 872 and 756 differentially expressed genes, respectively, compared to the control. Gene set enrichment analysis and functional annotation clustering was performed to characterize the genes differentially expressed in either β-carotene or lycopene-treated HTR-8/SVneo cells. Many known retinoid metabolism related genes and genes involved in regulation of retinoid signaling were found, and the expression profiles of these genes were markedly different in response to β-carotene treatments. Finally, the qRT-PCR and microarray analysis results showed similar gene expression patterns of carotenoid/retinoid metabolism and pathways. Conclusions These findings suggest that placental expression of genes involved in retinoid metabolism and transport in trophoblasts is critical for regulating retinoid homeostasis during placental and fetal development. Carotenoid exposure in early placental development, significantly modify the placenta gene expression related to retinoid pathways and maternal to fetal transfer. Funding Sources NIH HD421174.

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Genomewide Expression Profile Analysis of the Candida glabrata Pdr1 Regulon

Eukaryotic Cell ◽

10.1128/ec.00073-10 ◽

2010 ◽

Vol 10 (3) ◽

pp. 373-383 ◽

Cited By ~ 48

Author(s):

Kelly E. Caudle ◽

Katherine S. Barker ◽

Nathan P. Wiederhold ◽

Lijing Xu ◽

Ramin Homayouni ◽

...

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Candida Glabrata ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Differentially Expressed ◽

Resistant Isolate ◽

Content Type ◽

Activating Mutations ◽

Zinc Cluster

ABSTRACTThe ABC transportersCandida glabrataCdr1 (CgCdr1), CgPdh1, and CgSnq2 are known to mediate azole resistance in the pathogenic fungusC. glabrata. Activating mutations inCgPDR1, a zinc cluster transcription factor, result in constitutive upregulation of these ABC transporter genes but to various degrees. We examined the genomewide gene expression profiles of two matched azole-susceptible and -resistantC. glabrataclinical isolate pairs. Of the differentially expressed genes identified in the gene expression profiles for these two matched pairs, there were 28 genes commonly upregulated withCgCDR1in both isolate sets includingYOR1,LCB5,RTA1,POG1,HFD1, and several members of theFLOgene family of flocculation genes. We then sequencedCgPDR1from each susceptible and resistant isolate and found two novel activating mutations that conferred increased resistance when they were expressed in a common background strain in whichCgPDR1had been disrupted. Microarray analysis comparing these reengineered strains to their respective parent strains identified a set of commonly differentially expressed genes, includingCgCDR1,YOR1, andYIM1, as well as genes uniquely regulated by specific mutations. Our results demonstrate that while CgPdr1 activates a broad repertoire of genes, specific activating mutations result in the activation of discrete subsets of this repertoire.

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Changes in Gene Expression Profiles in Patients with 5q- Syndrome Caused by Lenalidomide Treatment

Blood ◽

10.1182/blood.v118.21.5023.5023 ◽

2011 ◽

Vol 118 (21) ◽

pp. 5023-5023

Author(s):

Monika Belickova ◽

Jaroslav Cermak ◽

Jitka Vesela ◽

Eliska Cechova ◽

Zuzana Zemanova ◽

...

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Conflicts Of Interest ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Differentially Expressed ◽

Aurora A ◽

Genes Expression ◽

Marrow Stroma ◽

Cell Niche

Abstract Abstract 5023 A direct effects of lenalidomide on gene expression in 5q- patients was studied using HumanRef-8 v2 Expression BeadChips (Illumina). Expression profiles of 6 patients (before treatment and at the time of the first erytroid response) and 6 healthy controls were investigated from CD14+ monocytes of peripheral blood. Differentially expressed genes were identified by Significance Analysis of Microarrays (SAM). Simultaneously, selected genes (TNF, JUN, IL1) were monitored in the course of treatment using Real-Time PCR with Taqman Gene Expression Assays. A comparison of gene expression levels before and during lenalidomide treatment revealed 97 differentially expressed genes (FC >2; p<0.05) related to following biological processes: immune response (16 genes), inflammatory response (11 genes), response to bacteria (8 genes), anti-apoptosis (7 genes), regulation of MAP kinase activity (5 genes), oxygen transport (4 genes), and regulation of cell proliferation (11 genes). An overexpression of a number of cytokines (e.g. TNF, IL8, IL1B, CCL3L, CXCL2, and TNFAIP3) was detected in patients before treatment, after lenalidomide administration expression of the majority of the up-regulated cytokine genes decreased to the control baseline level. Detected overproduction of the cytokines in 5q- syndrome may lead to an increased apoptosis of hematopoietic progenitor cells and together with excessive oxidative stress may contribute to the damage the hematopoietic niche. In the same manner, untreated patients showed suppressed expression of two genes (CXCR4, CRTAP) which play an important role in the stem cell niche. After treatment, we detected increased expression of these genes. Both the observations might explain favorable effects of lenalidomide on the bone marrow stroma defect seen in 5q- syndrome. On the other hand, a substantial increase of the ARPC1B gene (an activator and a substrate of Aurora A) expression was detected after lenalidomide treatment. Since overexpression of Aurora A leads to polyploidy and chromosomal instability, ARPC1B might play a role in the disease progression observed in some patients treated with lenalidomide. To conclude, described changes in genes expression may contribute to identification of the pathways affected by lenalidomide and to the explanation of some effects of this drug that have not been fully understood yet. Supported by grants NS/9634 MZCR, UHKT2005 00023736, MSM0021620808 and COST EUGESMA Disclosures: No relevant conflicts of interest to declare.

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