Retraction Note: Gene expression profiles analysis identifies key genes for acute lung injury in patients with sepsis

The acute respiratory distress syndrome (ARDS)/acute lung injury (ALI) was described 30 yr ago, yet making a definitive diagnosis remains difficult. The identification of biomarkers obtained from peripheral blood could provide additional noninvasive means for diagnosis. To identify gene expression profiles that may be used to classify patients with ALI, 13 patients with ALI + sepsis and 20 patients with sepsis alone were recruited from the Medical Intensive Care Unit of the University of Pittsburgh Medical Center, and microarrays were performed on peripheral blood samples. Several classification algorithms were used to develop a gene signature for ALI from gene expression profiles. This signature was validated in an independently obtained set of patients with ALI + sepsis ( n = 8) and sepsis alone ( n = 1). An eight-gene expression profile was found to be associated with ALI. Internal validation found that the gene signature was able to distinguish patients with ALI + sepsis from patients with sepsis alone with 100% accuracy, corresponding to a sensitivity of 100%, a specificity of 100%, a positive predictive value of 100%, and a negative predictive value of 100%. In the independently obtained external validation set, the gene signature was able to distinguish patients with ALI + sepsis from patients with sepsis alone with 88.9% accuracy. The use of classification models to develop a gene signature from gene expression profiles provides a novel and accurate approach for classifying patients with ALI.

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Identification of Potential Key Genes for Pathogenesis and Prognosis in Prostate Cancer by Integrated Analysis of Gene Expression Profiles and the Cancer Genome Atlas

Frontiers in Oncology ◽

10.3389/fonc.2020.00809 ◽

2020 ◽

Vol 10 ◽

Cited By ~ 2

Author(s):

Shuang Liu ◽

Wenxin Wang ◽

Yan Zhao ◽

Kaige Liang ◽

Yaojiang Huang

Keyword(s):

Gene Expression ◽

Prostate Cancer ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Integrated Analysis ◽

Cancer Genome Atlas ◽

Key Genes ◽

Genome Atlas

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Identification of key genes associated with bladder cancer using gene expression profiles

Oncology Letters ◽

10.3892/ol.2017.7310 ◽

2017 ◽

Cited By ~ 5

Author(s):

Yuping Han ◽

Xuefei Jin ◽

Hui Zhou ◽

Bin Liu

Keyword(s):

Gene Expression ◽

Bladder Cancer ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Key Genes

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Identification of key genes and pathways of BMP-9-induced osteogenic differentiation of mesenchymal stem cells by integrated bioinformatics analysis

Journal of Orthopaedic Surgery and Research ◽

10.1186/s13018-021-02390-w ◽

2021 ◽

Vol 16 (1) ◽

Author(s):

Jia-qi Wu ◽

Lin-bo Mao ◽

Ling-feng Liu ◽

Yong-mei Li ◽

Jian Wu ◽

...

Keyword(s):

Gene Expression ◽

Stem Cells ◽

Mesenchymal Stem Cells ◽

Osteogenic Differentiation ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Pathway Enrichment ◽

Key Genes

Abstract Background The purpose of present study was to identify the differentially expressed genes (DEGs) associated with BMP-9-induced osteogenic differentiation of mesenchymal stem cells (MSCs) by using bioinformatics methods. Methods Gene expression profiles of BMP-9-induced MSCs were compared between with GFP-induced MSCs and BMP-9-induced MSCs. GSE48882 containing two groups of gene expression profiles, 3 GFP-induced MSC samples and 3 from BMP-9-induced MSCs, was downloaded from the Gene Expression Omnibus (GEO) database. Then, DEGs were clustered based on functions and signaling pathways with significant enrichment analysis. Pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) demonstrated that the identified DEGs were potentially involved in cytoplasm, nucleus, and extracellular exosome signaling pathway. Results A total of 1967 DEGs (1029 upregulated and 938 downregulated) were identified from GSE48882 datasets. R/Bioconductor package limma was used to identify the DEGs. Further analysis revealed that there were 35 common DEGs observed between the samples. GO function and KEGG pathway enrichment analysis, among which endoplasmic reticulum, protein export, RNA transport, and apoptosis was the most significant dysregulated pathway. The result of protein-protein interaction (PPI) network modules demonstrated that the Hspa5, P4hb, Sec61a1, Smarca2, Pdia3, Dnajc3, Hyou1, Smad7, Derl1, and Surf4 were the high-degree hub nodes. Conclusion Taken above, using integrated bioinformatical analysis, we have identified DEGs candidate genes and pathways in BMP-9 induced MSCs, which could improve our understanding of the key genes and pathways for BMP-9-induced osteogenic of MSCs.

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A Study on Effect of Electroacupuncture on Gene Expression in Hypothalamus of Rats with Stress-Induced Prehypertension Based on Gene Chip Technology

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2015/621237 ◽

2015 ◽

Vol 2015 ◽

pp. 1-12 ◽

Cited By ~ 4

Author(s):

Xiaojia Xie ◽

Yan Guo ◽

Qingguo Liu ◽

Zhaoyang Wang ◽

Changqing Guo

Keyword(s):

Gene Expression ◽

Expression Profiles ◽

Signal Transduction Pathway ◽

Gene Expression Profiles ◽

Gene Chip ◽

Model Group ◽

Blank Group ◽

Chip Technology ◽

Key Genes ◽

Model Preparation

Objective. To explore the effect of electroacupuncture (EA) on gene expression in the hypothalamus of rats with stress-induced prehypertension and try to reveal its biological mechanism with gene chip technology.Methods. The stress-induced hypertensive rat model was prepared by combining electric foot-shocks with generated noise. Molding cycle lasted for 14 days and EA intervention was applied on model + EA group during model preparation. Rat Gene 2.0 Array technology was used for the determination of gene expression profiles and the screened key genes were verified by real-time fluorescence quantitative PCR method.Results. Compared with the blank group, 234 genes were upregulated and 73 were downregulated in the model group. Compared with the model group, 110 genes were upregulated and 273 genes were downregulated in model + EA group. The PCR results of the key genes including HSPB1, P2RX4, PPP1R14A, and TH are consistent with that of gene chip test.Conclusion. EA could significantly lower blood pressure of stress-induced prehypertension rats and affect its gene expression profile in hypothalamus. Genes and their signal transduction pathway that related to the contraction of vascular smooth muscle, concentration of Ca2+, and excitability of sympathetic nerve may be involved in EA’s antihypertensive mechanism.

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Identification of Key Genes Controlling Carotenoid Metabolism during Apricot Fruit Development by Integrating Metabolic Phenotypes and Gene Expression Profiles

Journal of Agricultural and Food Chemistry ◽

10.1021/acs.jafc.1c00496 ◽

2021 ◽

Author(s):

Weiquan Zhou ◽

Shirong Zhao ◽

Min Xu ◽

Yingying Niu ◽

Mansur Nasier ◽

...

Keyword(s):

Gene Expression ◽

Fruit Development ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Metabolic Phenotypes ◽

Carotenoid Metabolism ◽

Key Genes

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Altered Gene Expression in the Testis of Infertile Patients with Nonobstructive Azoospermia

Computational and Mathematical Methods in Medicine ◽

10.1155/2021/5533483 ◽

2021 ◽

Vol 2021 ◽

pp. 1-9

Author(s):

Zhiqiang Wang ◽

Zhongjun Ding ◽

Yan Guan ◽

Chunhui Liu ◽

Linjun Wang ◽

...

Keyword(s):

Gene Expression ◽

Expression Profiles ◽

Therapeutic Targets ◽

Gene Expression Profiles ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Nonobstructive Azoospermia ◽

Coexpression Analysis ◽

Qrt Pcr ◽

Key Genes

Background. The molecular mechanism of nonobstructive azoospermia (NOA) remains unclear. The aim of this study was to identify gene expression changes in NOA patients and to explore potential biomarkers and therapeutic targets. Methods. The gene expression profiles of GSE45885 and GSE145467 were collected from the Gene Expression Omnibus (GEO) database, and the differences between NOA and normal spermatogenesis were analyzed. Enrichment analysis was performed to explore biological functions for common differentially expressed genes (DEGs) in GSE45885 and GSE145467. Coexpression analysis of DEGs in GSE45885 was performed, and two modules with the highest correlation with NOA were screened. Key genes were then screened from the intersection genes of the two modules and common DEGs and PPI network. The expression of key genes was validated by quantitative real-time polymerase chain reaction (qRT-PCR) experiments. Finally, through miRTarBase, miRDB, and RAID, the miRNAs were predicted to regulate key genes, respectively. Results. A total of 345 common DEGs were identified and they were mainly related to spermatogenesis, insulin signaling pathway. Coexpression analysis of DEGs in GSE45885 yielded eight modules; MEblack and MEturquoise had the highest correlation with NOA. Six genes in MEturquoise and RNF141 in MEblack were identified as key genes. qRT-PCR experiments validated the differential expression of key genes between NOA and control. Furthermore, RNF141 was regulated by the largest number of miRNAs. Conclusion. Our findings suggest that the significant change expression of key genes may be potential markers and therapeutic targets of NOA and may have some impact on the development of NOA.

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