Construction of an endoplasmic reticulum stress-related gene model for predicting prognosis and immune features in kidney renal clear cell carcinoma

Shen, Yuanhao; Cao, Yinghao; Zhou, Lei; Wu, Jianfeng; Mao, Min

doi:10.3389/fmolb.2022.928006

Cited by 5 publications

(2 citation statements)

References 51 publications

(42 reference statements)

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“…This high-throughput technology surpasses microarrays in gene detection and facilitates the identification of differentially expressed genes (DEGs) using tools like DESeq2 [ 13 , 14 , 15 , 16 ]. Furthermore, RNA-seq data analysis is complemented by Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, Gene Ontology (GO) analysis, Ingenuity Pathway Analysis (IPA), and protein–protein interaction (PPI) analysis, collectively enhancing our understanding of gene function and its implications in various disciplines of molecular biology research [ 17 , 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

Examining Transcriptomic Alterations in Rat Models of Intracerebral Hemorrhage and Severe Intracerebral Hemorrhage

Thangameeran,

Tsai,

Liew

et al. 2024

Biomolecules

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Intracerebral hemorrhage (ICH) is a life-threatening condition associated with significant morbidity and mortality. This study investigates transcriptomic alterations in rodent models of ICH and severe ICH to shed light on the genetic pathways involved in hemorrhagic brain injury. We performed principal component analysis, revealing distinct principal component segments of normal rats compared to ICH and severe ICH rats. We employed heatmaps and volcano plots to identify differentially expressed genes and utilized bar plots and KEGG pathway analysis to elucidate the molecular pathways involved. We identified a multitude of differentially expressed genes in both the ICH and severe ICH models. Our results revealed 5679 common genes among the normal, ICH, and severe ICH groups in the upregulated genes group, and 1196 common genes in the downregulated genes, respectively. A volcano plot comparing these groups further highlighted common genes, including PDPN, TIMP1, SERPINE1, TUBB6, and CD44. These findings underscore the complex interplay of genes involved in inflammation, oxidative stress, and neuronal damage. Furthermore, pathway enrichment analysis uncovered key signaling pathways, including the TNF signaling pathway, protein processing in the endoplasmic reticulum, MAPK signaling pathway, and Fc gamma R-mediated phagocytosis, implicated in the pathogenesis of ICH.

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Section: Introductionmentioning

confidence: 99%

Examining Transcriptomic Alterations in Rat Models of Intracerebral Hemorrhage and Severe Intracerebral Hemorrhage

Thangameeran,

Tsai,

Liew

et al. 2024

Biomolecules

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“…A total of 2,269 ERSRGs were obtained from the GeneCards database ( 25 ) ( https://www.genecards.org/ ). Additionally, 33 ERSRGs were identified from published literature available on the PubMed website ( https://pubmed.ncbi.nlm.nih.gov ) ( 26 , 27 ). After removing duplicate genes, 2,279 unique ERSRGs were included in subsequent analyses, as shown in Supplementary Table S2 .…”

Section: Methodsmentioning

confidence: 99%

Comprehensive analysis of an endoplasmic reticulum stress-related gene prediction model and immune infiltration in idiopathic pulmonary fibrosis

Zhu,

Zhou,

Zhang

et al. 2024

Front. Immunol.

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BackgroundIdiopathic pulmonary fibrosis (IPF) is a chronic progressive interstitial lung disease. This study aimed to investigate the involvement of endoplasmic reticulum stress (ERS) in IPF and explore its correlation with immune infiltration.MethodsERS-related differentially expressed genes (ERSRDEGs) were identified by intersecting differentially expressed genes (DEGs) from three Gene Expression Omnibus datasets with ERS-related gene sets. Gene Set Variation Analysis and Gene Ontology were used to explore the potential biological mechanisms underlying ERS. A nomogram was developed using the risk signature derived from the ERSRDEGs to perform risk assessment. The diagnostic value of the risk signature was evaluated using receiver operating characteristics, calibration, and decision curve analyses. The ERS score of patients with IPF was measured using a single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm. Subsequently, a prognostic model based on the ERS scores was established. The proportion of immune cell infiltration was assessed using the ssGSEA and CIBERSORT algorithms. Finally, the expression of ERSRDEGs was validated in vivo and in vitro via RT-qPCR.ResultsThis study developed an 8-ERSRDEGs signature. Based on the expression of these genes, we constructed a diagnostic nomogram model in which agouti-related neuropeptide had a significantly greater impact on the model. The area under the curve values for the predictive value of the ERSRDEGs signature were 0.975 and 1.000 for GSE70866 and GSE110147, respectively. We developed a prognostic model based on the ERS scores of patients with IPF. Furthermore, we classified patients with IPF into two subtypes based on their signatures. The RT-qPCR validation results supported the reliability of most of our conclusions.ConclusionWe developed and verified a risk model using eight ERSRDEGs. These eight genes can potentially affect the progression of IPF by regulating ERS and immune responses.

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AURKB promotes immunogenicity and immune infiltration in clear cell renal cell carcinoma

Liu,

Chen

et al. 2024

Discov Onc

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Background Chromatin regulators (CRs) are capable of causing epigenetic alterations, which are significant features of cancer. However, the function of CRs in controlling Clear Cell Renal Cell Carcinoma (ccRCC) is not well understood. This research aims to discover a CRs prognostic signature in ccRCC and to elucidate the roles of CRs-related genes in tumor microenvironment (TME). Methods Expression profiles and relevant clinical annotations were retrieved from the Cancer Genome Atlas (TCGA) and UCSC Xena platform for progression-free survival (PFS) data. The R package "limma" was used to identify differentially expressed CRs. A predictive model based on five CRs was developed using LASSO-Cox analysis. The model's predictive power and applicability were validated using K-M curves, ROC curves, nomograms, comparisons with other models, stratified survival analyses, and validation with the ICGC cohort. GO and GSEA analyses were performed to investigate mechanisms differentiating low and high riskScore groups. Immunogenicity was assessed using Tumor Mutational Burden (TMB), immune cell infiltrations were inferred, and immunotherapy was evaluated using immunophenogram analysis and the expression patterns of human leukocyte antigen (HLA) and checkpoint genes. Differentially expressed CRs (DECRs) between low and high riskScore groups were identified using log2|FC|> 1 and FDR < 0.05. AURKB, one of the high-risk DECRs and a component of our prognostic model, was selected for further analysis. Results We constructed a 5 CRs signature, which demonstrated a strong capacity to predict survival and greater applicability in ccRCC. Elevated immunogenicity and immune infiltration in the high riskScore group were associated with poor prognosis. Immunotherapy was more effective in the high riskScore group, and certain chemotherapy medications, including cisplatin, docetaxel, bleomycin, and axitinib, had lower IC50 values. Our research shows that AURKB is critical for the immunogenicity and immune infiltration of the high riskScore group. Conclusion Our study produced a reliable prognostic prediction model using only 5 CRs. We found that AURKB promotes immunogenicity and immune infiltration. This research provides crucial support for the development of prognostic biomarkers and treatment strategies for ccRCC.

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Construction of an endoplasmic reticulum stress-related gene model for predicting prognosis and immune features in kidney renal clear cell carcinoma

Cited by 5 publications

References 51 publications

Examining Transcriptomic Alterations in Rat Models of Intracerebral Hemorrhage and Severe Intracerebral Hemorrhage

Examining Transcriptomic Alterations in Rat Models of Intracerebral Hemorrhage and Severe Intracerebral Hemorrhage

Comprehensive analysis of an endoplasmic reticulum stress-related gene prediction model and immune infiltration in idiopathic pulmonary fibrosis

AURKB promotes immunogenicity and immune infiltration in clear cell renal cell carcinoma

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