Ask about this productRelated genes to: PPP1R15A antibody
- Gene:
- PPP1R15A NIH gene
- Name:
- protein phosphatase 1 regulatory subunit 15A
- Previous symbol:
- -
- Synonyms:
- GADD34
- Chromosome:
- 19q13.2
- Locus Type:
- gene with protein product
- Date approved:
- 2001-06-29
- Date modifiied:
- 2015-11-18
Related products to: PPP1R15A antibody
Related articles to: PPP1R15A antibody
- Hepatic ischemia-reperfusion injury (HIRI) is clinically linked to post-transplant complications, yet the pathogenic role of programmed cell death (PCD) patterns in this process remains poorly delineated. This study aimed to investigate the diversity of programmed cell death (PCD) patterns underlying HIRI, with a focus on mechanistically dissecting macrophage-hepatocyte crosstalk mediated by the THBS1-CD47 axis. - Source: PubMed
Publication date: 2026/05/19
Xie ManlingZhang ChangquanZhu LirongPei YongfengLiang ChunyanFu LixinLi HaibinLan LiugenWen NingWu JihuaSun Xuyong - Osteoarthritis (OA) is a complex degenerative disorder characterized by progressive joint deterioration and synovial dysfunction. Emerging evidence implicates autophagy as a key regulatory process in OA development; however, its molecular signatures, diagnostic value, and interaction with the synovial microenvironment remain incompletely defined. This study aimed to delineate autophagy-associated molecular signatures in OA and characterize their biological relevance across bulk and single-cell transcriptomic landscapes. An integrative analytical framework was applied to four synovial bulk transcriptome datasets (GSE55235, GSE12021, GSE55457, and GSE1919) and one single-cell RNA-sequencing dataset (GSE216651) obtained from the GEO database. Autophagy-related genes were curated from publicly available repositories and intersected with differentially expressed genes identified following batch-effect correction and data integration. Key autophagy-associated genes associated with OA were prioritized through weighted gene co-expression network analysis (WGCNA) combined with multiple machine learning algorithms. Diagnostic utility was assessed using receiver operating characteristic (ROC) analysis and nomogram modeling. Regulatory networks involving upstream microRNAs and transcription factors were inferred in silico. Immune landscape alterations were quantified using ssGSEA, while functional pathways were interrogated by single-gene GSEA. Experimental validation included RT-qPCR analysis in peripheral blood mononuclear cells (PBMCs), single-cell resolution mapping of cellular heterogeneity, and ELISA-based quantification of IL-6 with correlation to clinical parameters. Through integrative multi-omics and machine learning analyses, eight autophagy-associated hub genes (XIST, JUN, TNFAIP3, PPP1R15A, IL6, NAMPT, TRAF4, and MYC) were robustly identified as OA-associated molecular features. All candidates demonstrated satisfactory diagnostic performance (AUC > 0.7), which was consistently reproduced in independent validation cohorts and experimental assays. Immune deconvolution revealed widespread alterations in synovial immune cell composition, with significant correlations observed between hub gene expression and nine immune cell populations. Single-cell transcriptomic profiling further uncovered distinct cell-type-specific expression patterns and highlighted intensified fibroblast-macrophage communication networks within OA synovium, suggesting their central involvement in disease progression. By integrating bulk and single-cell transcriptomic analyses with experimental validation, this study defines a set of autophagy-associated molecular markers with diagnostic relevance in osteoarthritis. The identified hub genes not only enhance the understanding of OA-related autophagy dysregulation but also represent potential targets for future mechanistic studies and translational intervention strategies. Importantly, these findings provide a robust molecular framework for early diagnostic screening and risk stratification, potentially facilitating more precise clinical management and personalized therapeutic interventions for OA patients. - Source: PubMed
Wang XiaoqingLuo XingyeLi HongLi TingWang YanyuanLi RuoerQing YufengZhang Quanbo - Keratoconus (KCN) is a bilateral and asymmetric cornea disease. Autophagy plays an important role in homeostasis by protecting cells against stress. However, the roles of autophagy-related genes (ARGs) in KCN remains unclear. Hence, this study aimed to identify the signatures of ARGs of KCN and explore their correlation with immune infiltration. Transcriptional data and clinical information of patients with KCN were downloaded from the profile data GSE112155 and GSE151631. Functional analysis was used to reflect the biological functions, and weighted gene co-expression network analysis was applied to excavate co-expression modules of autophagy-related expression patterns. Moreover, gene set enrichment and variation analyses were performed for pathway analysis. Consensus clustering analysis was used to cluster different molecular subtypes on the basis of gene expression profiles of KCN-specific ARGs. Single-sample gene set enrichment analysis was employed to calculate separate enrichment scores for each immunocyte between KCN and healthy samples. Finally, hub genes were verified by real-time quantitative polymerase chain reaction. We first identified 14 ARGs differentially expressed between patients with KCN and controls using NetworkAnalyst. Nine overlapped genes (BNIP3, CDKN1A, DDIT3, FOS, HSPA5, MAPK8IP1, MYC, PPP1R15A, and VEGFA) (P < .05) were identified using a random forest model. The MAPK signaling pathway, apoptosis, FoxO signaling pathway, and protein processing in endoplasmic reticulum signaling were mainly involved. The weighted gene co-expression network analysis classified the genes into 12 distinct modules. The MEturquoise (correlation = 0.51), MEpink (correlation = 0.535) were significantly positively correlated with KCN, whereas the MEyellow (correlation = -0.776) and MEgreen (correlation = -0.664) were negatively correlated. Single-sample gene set enrichment analysis showed a close interaction between immune cell infiltration and the development of KCN. Finally, all the 9 hub genes except VEGFA were significantly downregulated (P < .05) using real-time quantitative polymerase chain reaction. We described the signatures of ARGs in KCN, the distribution of immune cells between KCN patients and the control, and the correlation between hub genes related to autophagy and KCN disease. This demonstrates the potential roles of autophagy mechanisms and the immune response in KCN, providing a novel insight into understanding the pathogenesis of KCN and potential treatment targets. - Source: PubMed
Li SutongWang GangChen JingLi Naiyang - Acute pancreatitis (AP) is an inflammatory disorder with no efficient therapy. Here we demonstrate that the anorexigenic peptide nesfatin-1 exerts potent and dose-dependent protection against both caerulein-induced and hypertriglyceridemic AP. Intraperitoneal administration of nesfatin-1 to restore its serum levels significantly reduced pancreatic necrosis, edema, and infiltration of immune cells, as well as circulating levels of amylase, lipase, and pro-inflammatory cytokines. RNA-seq revealed that nesfatin-1 down-regulated the ER-stress signature (Ddit3, Atf3, Ppp1r15a) and the NF-κB/NLRP3 signaling. Further studies in primary acinar cells confirmed that nesfatin-1 at the dose of 10 nM suppressed phosphorylated eIF2α, DDIT3, ATF3, p65, and NLRP3, thereby inhibiting pyroptosis. Consequently, nesfatin-1 attenuated macrophage/neutrophil infiltration, shifted M1 toward M2 macrophages, inhibited the release of inflammatory cytokines, and alleviated multi-organ injury in lung, intestine, and spleen. Collectively, nesfatin-1 limits AP severity by restraining ER-stress-driven pyroptosis and innate immune activation. Thus, nesfatin-1 may serve as a promising therapeutic candidate for acute pancreatitis. - Source: PubMed
Li HanWang XianfengNiu YuefengSun LijunYang YinmoZhang WeizhenYin Yue - Glioblastoma (GBM) is characterized by high morbidity and mortality due to its localization and often locally invasive growth. Current treatment options for GBM are limited, with conventional therapies achieving a median survival of only 15 months. Mechanotherapy has been proposed as a new therapeutic strategy in oncology. Low-intensity focused ultrasound (LIFU), a form of mechanotherapy, has demonstrated inhibitory effects on GBM. However, its underlying mechanisms remain poorly understood. The present study aimed to evaluate the therapeutic effects of LIFU on GBM and investigate its mechanisms of action. - Source: PubMed
Publication date: 2026/04/30
Li MingmingWang WeidongJiang JianMao YingxuanZhu MingweiHan LinlinNiu JiameiLiu PengfeiYang Xiuhua