Integrated transcriptomic and regulatory network analyses uncovers the role of let-7b-5p, SPIB, and HLA-DPB1 in sepsis

Abstract

Sepsis has affected millions of populations of all age groups, locations, and sexes worldwide. Immune systems, either innate or adaptive are dysregulated due to the infection. Various biomarkers are present to date, still sepsis is a primary cause of mortality. Globally, post-operative body infections can cause sepsis and septic shock in ICU. Abnormal antigen presentation to T-cells leads to a dysregulated immune system. miRNAs are sparkly evolved as biomarkers due to their high sensitivity and efficiency. In this work, we analyzed high-throughput mRNA data collected from Gene Expression Omnibus (GEO) and linked it to significant miRNAs and TFs using a network-based approach. Protein–protein interaction (PPI) network was constructed using sepsis-specific differentially expressed genes (DEGs) followed by enrichment analyses and hub module detection. Sepsis-linked decrease transcription of the classical HLA gene such as HLA-DPB1 and its interplay with miR-let-7b-5p and transcription factor SPIB was observed. This study helped to provide innovative targets for sepsis.

Exploring the Role of Different Cell-Death-Related Genes in Sepsis Diagnosis Using a Machine Learning Algorithm

“…The expression of PDE4D in sepsis patients decreased continuously with time, and the low expression level of PDE4D was found to be related to HLA-DMA and HLA-DMB [57]. Mohsin et al used comprehensive transcriptomics and regulatory network analysis methods to reveal the role of HLA-DPB1 in sepsis [58]. Experiments have confirmed that monitoring HLA-DRA by using qRT-PCR can help us to detect the dynamic changes in the immune state in sepsis, which is beneficial to future research [59].…”

Exploring the role of miR-200 family in regulating CX3CR1 and CXCR1 in lung adenocarcinoma tumor microenvironment: implications for therapeutic intervention

“…Significant human TFs interacting with our hub DEIRGs were acquired from ChEA v3.0 database ( https://maayanlab.cloud/chea3/ ) 23 corresponding to a . miRNAs which were interacting with our hub DEIRGs and TFs were extracted as discussed previously 15 . The miRNAs overlapping with DEMs were retained and regarded as validated miRNAs.…”

“…The miRNAs overlapping with DEMs were retained and regarded as validated miRNAs. Sequential steps of 3-node miRNA FFL formation and visualization were performed as discussed previously 11 , 15 . ROC curve analysis was performed to assess the diagnostic sensitivity of miR-200 family-associated hub mRNAs in LUAD patients.…”