Identification of programmed cell death-related gene signature and associated regulatory axis in cerebral ischemia/reperfusion injury

Shu, Jun; Lu, Yang; Wei, Wenshi; Zhang, Li

doi:10.3389/fgene.2022.934154

Cited by 15 publications

(9 citation statements)

References 114 publications

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“…Six candidate genes (IL2, NOC2L, LEP, BIRC2, DLD, and CTSL) were identi ed, four of which have been previously studied in association with IS, while NOC2L and BIRC2 are the rst to appear in IS-related studies. IL possesses vital biological properties that include maintaining long-term T cell proliferation and differentiation in vitro, increasing B cell proliferation and differentiation, enhancing NK cell killing activity, and inducing the production of lymphokine-activating factors (33). The IL-2/IL-2 antibody complex (IL-2/IL-2Ab) regulates the number of regulatory T cells (Treg) in vivo, which may improve the prognosis of ischemic stroke (34).…”

Section: Discussionmentioning

confidence: 99%

Predictive modeling of ischemic stroke, identification of relevant subgroups, and drug prediction based on multiple programmed cell death patterns

Yang

Shen

et al. 2023

Preprint

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Background: Ischemic stroke is the second leading cause of mortality and disability globally. Along with many immune and disease conditions, Programmed cell death (PCD) also has a critical role in ischemic stroke and may serve as a diagnostic indicator of ischemic stroke. Methods: From the Gene Expression Omnibus database (GEO), two ischemic stroke datasets were chosen, one for training and the other for the validation group. From the KEGG and other databases, 12 patterns of PCD-related genes were selected. Differentially expressed genes (DEG) were found using Limma analysis; functional enrichment analysis;machine learning least absolute shrinkage and selection operator (LASSO) regression; candidate immune-related central genes were identified using Random Forest along with the construction of a protein-protein interaction network (PPI) and an artificial neural network (ANN) for validation. In order to diagnose an ischemic stroke, the Receiver operating characteristic (ROC) curve was plotted, the diagnostic model was validated by qRT-PCR, immune cell infiltration was investigated to observe immune cell dysregulation in ischemic stroke, and the expression of candidate models under different isoforms was analyzed by consensus clustering (CC). Finally, drugs associated with candidate genes were collected through the Networkanalyst online platform. Results: A total of 71 genes were shown to be the crossover of DEG and PCD-related genes in ischemic stroke, and six candidate genes were finally identified by machine learning to establish a diagnostic prediction model. After using an artificial neural network (ANN) for validation, ROC curve plotting, and qRT-PCR validation for diagnostic value assessment. The outcomes demonstrated that the prediction model had a high diagnostic value. In the immune infiltration analysis, significant variability of NKT was found in ischemic stroke patients. Seven drugs associated with candidate genes were collected from the Networkanalyst online platform. Conclusion: A diagnostic prediction model with a good effect in the training group and validation group (AUC 0.94, CI 1.00-0.88 and AUC 0.91, CI 0.97-0.86, respectively), along with a good phenotype in qRT-PCR validation by comprehensive analysis was obtained. Additionally, the drugs (C646 substance, Cyclosporine, Decitabine, Dexamethasone, Resveratrol, Silicon Dioxide, and Tretinoin) that might be useful in the treatment of ischemic stroke were obtained.

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Section: Discussionmentioning

confidence: 99%

Predictive modeling of ischemic stroke, identification of relevant subgroups, and drug prediction based on multiple programmed cell death patterns

Yang

Shen

et al. 2023

Preprint

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“…31,32 Recently, the role of lncRNAs in the diagnosis and treatment of liver diseases has also been recognized. 33,34 It has also been reported that lncRNAs participate in gene regulation during ischemia-reperfusion injury of important organs such as the brain 35,36 and the heart. 37 Nevertheless, research on lncRNAs expression profiles in liver transplantation is still limited and is mainly derived from animal or in vitro models of liver transplantation.…”

Section: Discussionmentioning

confidence: 99%

“…Recently, the role of lncRNAs in the diagnosis and treatment of liver diseases has also been recognized 33,34 . It has also been reported that lncRNAs participate in gene regulation during ischemia–reperfusion injury of important organs such as the brain 35,36 and the heart 37 …”

Section: Discussionmentioning

confidence: 99%

Functional analysis of hepatic long non‐coding ribonucleic acids during liver transplantation in humans

Tang

Zhang

Liu

et al. 2023

The Journal of Gene Medicine

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Background The potential function of long non‐coding RNAs (lncRNAs) in human hepatic ischemia–reperfusion injury (HIRI) remains to be clarified. Methods Clinical samples of transplanted liver tissues from 26 patients undergoing liver transplantation (LT) and normal liver tissues from seven patients undergoing hepatic hemangiomactomy (Con) were collected. Typical samples were subjected to whole transcriptome sequencing (RNA‐seq). Differentially expressed genes between groups were identified by DEGseq and were analyzed by enrichment analysis including Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and gene set enrichment analysis. Transcription of five lncRNAs including NONHSAG039942, NONHSAG071405, NONHSAG027516, LXLOC_058190, and LXLOC_024376 that presented significant difference in RNA‐sequencing were validated by a quantitative real‐time PCR (qRT‐PCR), for which the subcellular localization and the binding ability to known human RNA‐binding proteins (RBPs) were respectively predicted by LncLocator and catRAPID genomics v2.1. Results We identified 2917 lncRNAs and 2811 mRNAs that were differentially expressed (p < 0.05 and log2 fold change > 1 or < −1) between groups (LT vs. Con). NONHSAG039942, NONHSAG071405, LXLOC_058190, and LXLOC_024376 were validated by qRT‐PCR to be significantly increased in the LT group, and were all predicted to be localized in cytoplasm or cytosol. NONHSAG039942, NONHSAG071405, and LXLOC_058190 held an RBP interaction propensity score of 98.07%, 76.95%, and 152.99%, respectively, with heterogeneous‐nuclear ribonucleoprotein U (HNRNPU). Pathways significantly activated in transplant livers that involved HNRNPU as a core enrichment gene included hypoxia, ACE2 expression, apoptosis, spliceosome formation, etc. Conclusions NONHSAG039942, NONHSAG071405, and LXLOC_058190 were significantly increased in transplant livers after reperfusion and their role in HIRI may be associated with HNRNPU, a core protein that participates in hypoxia and chromatin accessibility.

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“…Initially, we collected 268 programmed cell death genes (PCD genes) from existing literature sources [ 24 , 25 ]. Using scRNA-seq datasets, we identified 3,000 cell Differential genes (cellDiffgenes) intersecting with PCD genes to obtain our target gene.…”

Section: Methodsmentioning

confidence: 99%

A novel defined programmed cell death related gene signature for predicting the prognosis of serous ovarian cancer

Zhan,

Guo,

2024

J Ovarian Res

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Purpose This study aims to explore the contribution of differentially expressed programmed cell death genes (DEPCDGs) to the heterogeneity of serous ovarian cancer (SOC) through single-cell RNA sequencing (scRNA-seq) and assess their potential as predictors for clinical prognosis. Methods SOC scRNA-seq data were extracted from the Gene Expression Omnibus database, and the principal component analysis was used for cell clustering. Bulk RNA-seq data were employed to analyze SOC-associated immune cell subsets key genes. CIBERSORT and single-sample gene set enrichment analysis (ssGSEA) were utilized to calculate immune cell scores. Prognostic models and nomograms were developed through univariate and multivariate Cox analyses. Results Our analysis revealed that 48 DEPCDGs are significantly correlated with apoptotic signaling and oxidative stress pathways and identified seven key DEPCDGs (CASP3, GADD45B, GNA15, GZMB, IL1B, ISG20, and RHOB) through survival analysis. Furthermore, eight distinct cell subtypes were characterized using scRNA-seq. It was found that G protein subunit alpha 15 (GNA15) exhibited low expression across these subtypes and a strong association with immune cells. Based on the DEGs identified by the GNA15 high- and low-expression groups, a prognostic model comprising eight genes with significant prognostic value was constructed, effectively predicting patient overall survival. Additionally, a nomogram incorporating the RS signature, age, grade, and stage was developed and validated using two large SOC datasets. Conclusion GNA15 emerged as an independent and excellent prognostic marker for SOC patients. This study provides valuable insights into the prognostic potential of DEPCDGs in SOC, presenting new avenues for personalized treatment strategies.

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Identification of programmed cell death-related gene signature and associated regulatory axis in cerebral ischemia/reperfusion injury

Cited by 15 publications

References 114 publications

Predictive modeling of ischemic stroke, identification of relevant subgroups, and drug prediction based on multiple programmed cell death patterns

Predictive modeling of ischemic stroke, identification of relevant subgroups, and drug prediction based on multiple programmed cell death patterns

Functional analysis of hepatic long non‐coding ribonucleic acids during liver transplantation in humans

A novel defined programmed cell death related gene signature for predicting the prognosis of serous ovarian cancer

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