Ask about this productRelated genes to: PARVG antibody
- Gene:
- PARVG NIH gene
- Name:
- parvin gamma
- Previous symbol:
- -
- Synonyms:
- -
- Chromosome:
- 22q13.31
- Locus Type:
- gene with protein product
- Date approved:
- 2001-04-26
- Date modifiied:
- 2015-11-20
Related products to: PARVG antibody
Related articles to: PARVG antibody
- With survival rates for osteosarcoma largely unchanged for 40 years-especially in metastatic/recurrent cases. While the immune microenvironment is believed to play a crucial role, the heterogeneity of immune cell infiltration (ICI) and its precise impact on prognosis and therapeutic response remain poorly characterized. There is a lack of a robust, ICI-based scoring system to stratify patients and identify novel therapeutic targets. This study aimed to identify the characteristics of ICI subtypes for evaluating prognosis and therapeutic benefits. - Source: PubMed
Wang YuerongLiu XueniXie GuojinLi Zheqian - Bone remodeling relies on balanced osteoclast and osteoblast activity, with dysregulated osteoclast differentiation contributing to pathologies like osteoporosis. While RANKL/M-CSF signaling and master regulators (NFATc1, c-Fos) are established, comprehensive temporal dynamics of gene networks governing progressive osteoclastogenesis stages remain poorly characterized. We employed an integrated approach combining RANKL-induced osteoclast differentiation from murine bone marrow-derived macrophages (BMMs) with rigorous functional validation (TRAP staining, podosome visualization via rhodamine-phalloidin/DAPI, Western blotting for NFATc1/c-Fos/CTSK) and high-throughput RNA sequencing across critical time points (day 0, 1, 3, and 5). Subsequent bioinformatic analyses included differential expression profiling (DESeq2/edgeR), Gene Ontology (GO) and KEGG pathway enrichment, Gene Set Enrichment Analysis (GSEA), and temporal clustering using Mfuzz. Key transcriptional findings were confirmed by RT-qPCR. GO/KEGG/GSEA analyses revealed significant enrichment of DEGs in FA signaling, PI3K-Akt pathway, and cytoskeletal organization. Mfuzz clustering delineated distinct gene expression trajectories. We documented stage-specific expression kinetics: 23 FA-related genes showed dynamic shifts (e.g., upregulated Itgb3, Src, Pik3r3, Fn1; downregulated Itga6, Parvg); multiple MMPs (Mmp2, Mmp9, Mmp13-17) and TIMPs (Timp1-3) were progressively induced, while Mmp8, Mmp12, Mmp27 were suppressed. Cell fusion involved upregulated Tnfrsf11a, Nfatc1, Plcg1, Xkr8 alongside downregulated Trem2, Tyrobp, Ccr2, Rhoa, Casp3. This study provides the first comprehensive temporal transcriptome atlas of RANKL-induced osteoclastogenesis. It delineates stage-specific molecular reprogramming, revealing dynamic regulation of FA signaling components promoting adhesion/migration, complex MMP/TIMP induction balancing ECM degradation, and coordinated transcriptional networks enabling fusion. These findings significantly expand understanding beyond the core RANKL-NFATc1 axis, identifying novel stage-specific regulatory hubs and potential therapeutic targets within FA, PI3K-Akt, MMP/TIMP, and fusion pathways for osteoclast-driven bone diseases. - Source: PubMed
Publication date: 2025/12/03
Zhang LeiWu JingjingZhou NiYang ShutingChen JiangjieXu ChenghaoFan ShaohuaHuang WeixingYing XiaofangZhang Liwei - Endometrial cancer (EC) is a major reproductive system tumor and a common cancer in women. Polycystic ovary syndrome (PCOS) is one of the most prevalent female reproductive endocrine disorders. The incidence of EC is significantly higher in individuals with PCOS. This study seeks to elucidate the organic correlations and interaction mechanisms between the 2 diseases through series of exploration of key genes with a bioinformatics analysis. The PCOS sample data and the EC single-cell dataset were downloaded from the gene expression omnibus database. The EC sample data were retrieved from the cancer genome atlas public database. The random survival forest method was employed to identify key genes associated with the prognosis of PCOS and EC comorbidity. Corresponding analyses on functional pathway enrichment, regulatory networks, and immune micro-environment are conducted. From a bioinformatics perspective, the association and interaction mechanisms between PCOS and EC comorbidity were explored to provide research and development references for the prevention and control of PCOS and EC comorbidity. Five key genes associated with the prognosis of PCOS and EC comorbidity were identified using the random survival forest method. The identified genes are SYTL1, PARVG, ID4, IL1RN, and S100A9. The abnormal expression of these key genes has impacted various enrichment pathways, including the TGF-β signaling-pathway, motif regulatory networks (such as motif cisbp__M4556), and miRNA regulatory networks, which encompass genes such as ATM, BARD1 and BRCA1. Furthermore, these also influence the immune cell microenvironment, such as T cells regulatory. Collectively, these key genes play a significant role in the occurrence and progression of comorbidities through the pathways mentioned above. The dysregulation of key genes (SYTL1, PARVG, ID4, IL1RN, S100A9) in the context of PCOS-EC comorbidities, along with their associated enrichment pathways, including the TGF-β signaling-pathway and immune microenvironment, plays a significant role in the occurrence and progression of EC. - Source: PubMed
Yao YingshaZhu ShulanZhu Xiaoming - Studies have highlighted the significant role of focal adhesion signaling in cancer. Nevertheless, its specific involvement in the pathogenesis of endometrial cancer and its clinical significance remains uncertain. We analyzed TCGA-UCEC and GSE119041 datasets with corresponding clinical data to investigate focal adhesion-related gene expression and their clinical significance. A signature, "FA-riskScore," was developed using LASSO regression in the TCGA cohort and validated in the GSE dataset. The FA-riskScore was compared with four existing models in terms of their prediction performance. We employed univariate and multivariate Cox regression analyses towards FA-riskScore to assess its independent prognostic value. A prognostic evaluation nomogram based on our model and clinical indexes was established subsequently. Biological and immune differences between high- and low-risk groups were explored through functional enrichment, PPI network analysis, mutation mining, TME evaluation, and single-cell analysis. Sensitivity tests on commonly targeted drugs were performed on both groups, and Connectivity MAP identified potentially effective molecules for high-risk patients. qRT-PCR validated the expressions of FA-riskScore genes. FA-riskScore, based on FN1, RELN, PARVG, and PTEN, indicated a poorer prognosis for high-risk patients. Compared with published models, FA-riskScore achieved better and more stable performance. High-risk groups exhibited a more challenging TME and suppressive immune status. qRT-PCR showed differential expression in FN1, RELN, and PTEN. Connectivity MAP analysis suggested that BU-239, potassium-canrenoate, and tubocurarine are effective for high-risk patients. This study introduces a novel prognostic model for endometrial cancer and offers insights into focal adhesion's role in cancer pathogenesis. - Source: PubMed
Publication date: 2024/04/23
Yan CuiyinHe LeileiMa YuhuiCheng JingShen LiSingla Rajeev KZhang Yueming - [This retracts the article DOI: 10.1155/2022/7376588.]. - Source: PubMed
Publication date: 2023/07/19
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