Gene expression profiling reveals candidate biomarkers and probable molecular mechanisms in chronic stress

Zhang, Bohan; Zhong, Weijie; Yang, Biao; Li, Yang; Duan, Shuxian; Huang, Jin; Mao, Yanfei

doi:10.1080/21655979.2022.2040872

Cited by 4 publications

(2 citation statements)

References 60 publications

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“…Despite advancements in the last ten years in describing sepsis-induced immunological dysfunctions, many unanswered concerns still exist, and several issues require additional studies [ 1 ]. Since high-throughput technologies generate large amounts of data, there is a need for effective bioinformatics tools that enable us to comprehend how molecules interact and control the various biological processes of health and disease [ 19 – 21 ]. The molecular understanding of sepsis has opened a new chapter because of transcriptome-based research.…”

Section: Introductionmentioning

confidence: 99%

Exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysis

Liang,

Wu,

et al. 2024

BMC Infect Dis

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Background Sepsis is a life-threatening condition caused by an excessive inflammatory response to an infection, associated with high mortality. However, the regulatory mechanism of sepsis remains unclear. Results In this study, bioinformatics analysis revealed the novel key biomarkers associated with sepsis and potential regulators. Three public datasets (GSE28750, GSE57065 and GSE95233) were employed to recognize the differentially expressed genes (DEGs). Taking the intersection of DEGs from these three datasets, GO and KEGG pathway enrichment analysis revealed 537 shared DEGs and their biological functions and pathways. These genes were mainly enriched in T cell activation, differentiation, lymphocyte differentiation, mononuclear cell differentiation, and regulation of T cell activation based on GO analysis. Further, pathway enrichment analysis revealed that these DEGs were significantly enriched in Th1, Th2 and Th17 cell differentiation. Additionally, five hub immune-related genes (CD3E, HLA-DRA, IL2RB, ITK and LAT) were identified from the protein–protein interaction network, and sepsis patients with higher expression of hub genes had a better prognosis. Besides, 14 drugs targeting these five hub related genes were revealed on the basis of the DrugBank database, which proved advantageous for treating immune-related diseases. Conclusions These results strengthen the new understanding of sepsis development and provide a fresh perspective into discriminating the candidate biomarkers for predicting sepsis as well as identifying new drugs for treating sepsis.

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Section: Introductionmentioning

confidence: 99%

Exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysis

Liang,

Wu,

et al. 2024

BMC Infect Dis

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“…As a new discipline ( Dinov, 2016 ), it uses computer science and biology to unravel biological mysteries posed by enormous and complicated life data ( Fernandez-Pozo et al, 2022 ). Genomics and proteomics are the key modules for research; specifically, nucleic acid and protein sequences are analyzed to establish the biological information of the structure and function ( Zhang et al, 2022 ). In this study, the in vivo mechanism of Diosmetin on breast cancer patients infected with COVID-19 was explored by means of bioinformatics, network pharmacology, and molecular docking.…”

Section: Introductionmentioning

confidence: 99%

Investigation into the in vivo mechanism of diosmetin in patients with breast cancer and COVID-19 using bioinformatics

Wang

Long

et al. 2022

Front. Pharmacol.

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Patients with breast cancer are prone to SARS-CoV-2 infection [the causative virus of coronavirus disease (COVID-19)] due to their lack of immunity. In the current study, we examined the mechanism of action of Diosmetin, a flavonoid with anti-inflammatory properties, in patients with BRCA infected with SARS-CoV-2.We used bioinformatics technology to analyze the binding ability, biological function, and other biological characteristics of Diosmetinin vivo and examine the core target and potential mechanism of action of Diosmetin in patients with patients with breast cancer infected with SARS-CoV-2. A prognostic model of SARS-COV-2–infected breast cancer patients was constructed, and the core genes were screened out, revealing the correlation between these core genes and clinicopathological characteristics, survival rate, and high-risk and low-risk populations. The docking results revealed that Diosmetin binds well to the core genes of patients with breast cancer with COVID-19. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses suggested that Diosmetin inhibited inflammation, enhanced immune function, and regulated the cellular microenvironment in patients with BRCA/COVID-19. For the first time, we reveal the molecular functions and potential targets of Diosmetin in patients with breast cancer infected with SARS-CoV-2, improving the reliability of the new drug and laying the foundation for further research and development.

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Psychological stress: neuroimmune roles in periodontal disease

et al. 2022

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Gene expression profiling reveals candidate biomarkers and probable molecular mechanisms in chronic stress

Cited by 4 publications

References 60 publications

Exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysis

Exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysis

Investigation into the in vivo mechanism of diosmetin in patients with breast cancer and COVID-19 using bioinformatics

Psychological stress: neuroimmune roles in periodontal disease

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