Ask about this productRelated genes to: TRAPPC4 antibody
- Gene:
- TRAPPC4 NIH gene
- Name:
- trafficking protein particle complex 4
- Previous symbol:
- -
- Synonyms:
- TRS23, SBDN, PTD009
- Chromosome:
- 11q23.3
- Locus Type:
- gene with protein product
- Date approved:
- 2003-08-29
- Date modifiied:
- 2016-01-05
Related products to: TRAPPC4 antibody
Related articles to: TRAPPC4 antibody
- Head and neck squamous cell carcinoma (HNSCC) is often diagnosed at advanced stages, resulting in poor clinical outcomes. Ferroptosis resistance presents a major challenge in the treatment of HNSCC, highlighting the need to elucidate the mechanisms that enable HNSCC cells to evade ferroptosis. Here, we conducted a genome-wide CRISPR-Cas9 knockout screen and identified trafficking protein particle complex subunit 4 (TRAPPC4) as a key regulator of ferroptosis resistance in HNSCC. Across a comprehensive set of experimental models, including HNSCC cell lines, patient-derived organoids, cell-derived xenografts, patient-derived xenografts, Trappc4-conditional knockout mice, and lymph node and lung metastasis models, TRAPPC4 promoted tumor progression by inhibiting ferroptosis. Mechanistically, TRAPPC4 decreased chromatin accessibility at a distal regulatory element upstream of TRIM55, thereby limiting FOS-dependent transcription. This repression reduced TRIM55-mediated GPX4 ubiquitination and degradation, resulting in GPX4 stabilization and ferroptosis resistance. Structure-based high-throughput virtual screening identified pitavastatin calcium as a TRAPPC4-binding compound that promoted TRAPPC4 degradation. Notably, pitavastatin calcium synergized with the ferroptosis inducer RSL3 to enhance ferroptotic activity and suppress HNSCC progression. These findings delineate a TRAPPC4-FOS-TRIM55-GPX4 signaling axis that drives ferroptosis resistance and tumor progression and highlight TRAPPC4 as a promising therapeutic target for ferroptosis-based intervention in HNSCC. - Source: PubMed
Publication date: 2026/04/13
Ding ZhaoHan YanxunLiu WeiweiZhang WentaoXie ZihuiZhou PingtingJiang ShangshangLu JiLi JuanjuanLi YueJi MengyuanXue HaoTang JialuWang ZixiXia KangruiLi DapengWu JingWang YinKim Laura MinhuiNaseem Danial FLi GuojunZafereo Mark EYao ChangyuTao YeZha XiaojunLiu Yehai - Around 15-50% of patients with dMMR/MSI-H metastatic colorectal cancer (mCRC) experience primary and secondary resistance to immune checkpoint inhibitors (ICI). We previously described three transcriptomic clusters (A, B, C) linked to progression-free survival (PFS), with cluster A ("Stromal - Proliferation) associated with the shortest PFS. Here we combine gene signature and mucinous phenotype to predict the benefit from anti-CTLA-4 plus anti-PD-1. - Source: PubMed
Publication date: 2026/04/05
Ambrosini MargheritaGallois ClaireGandini AnnaliceLecanu AurélieAlouani EmilyPietrantonio FilippoBergamo FrancescaCremolini ChiaraMazard ThibaultTougeron DavidGuimbaud RosineLonardi SaraSelves JanickMouillet-Richard SophieEmile Jean-FrancoisTaieb JulienLaurent-Puig Pierre - Alzheimer's disease (AD), the leading cause of dementia, imposes a significant societal and economic burden; however, its complex molecular mechanisms remain unclear. This study integrates multi-omics data with advanced artificial intelligence (AI) methods to uncover the molecular basis underlying AD phenotype regulation and explore personalized drug repositioning strategies based on individual genetic backgrounds. First, we applied the PrediXcan method to identify candidate genes closely associated with AD cognitive diagnosis, selecting from 61 brain-related traits. We validated these findings through individual-level analysis using gene expression and genotype data from 553 dorsolateral prefrontal cortex samples in the ROSMAP database. Simultaneously, we constructed a deep, multi-layer information fusion model (AD-MIF) by integrating genotype and gene expression data and employing autoencoders as well as graph autoencoders for multi-modal feature extraction. The results revealed a 10-20% improvement in the Area Under the Curve (AUC) for predicting AD-related phenotypes. Both approaches showed high consistency across cellular structures, brain regions, and neurobiological pathways, demonstrating their complementary advantages. Gene enrichment analysis indicated that APOE and its interacting gene APOC1 play a central role in cholesterol metabolism, lipid transport, and immune regulation, while genes such as SCIMP and KAT8 are involved in immune signaling, epigenetic regulation, and neuroprotection. After incorporating attention mechanisms, AD-MIF highlighted the importance of key genes, such as POLR2C and TRAPPC4, in regulating neuronal function. Based on predictive results and enrichment analysis, we further identified candidate drugs, including sirolimus, dasatinib, and MGCD-265. In vivo experiments confirmed that MGCD-265, also known as Glesatinib, and dasatinib significantly improve cognitive deficits in the SAMP8 AD model mice by inhibiting neuroinflammation, pathological tau phosphorylation, and Aβ deposition. This study demonstrates the complementary advantages of bioinformatics pipelines and AI-based multi-modal fusion methods in elucidating the complex pathological mechanisms of AD and enhancing phenotype prediction accuracy. It also provides new theoretical support for personalized drug interventions based on individual genetic characteristics, laying a solid foundation for optimizing early screening, prediction, and personalized treatment strategies. - Source: PubMed
Publication date: 2025/06/10
Tian XuecongSu YingZhang SizheChen ChenMa YaoleiSun HaiqingChen ChengZhou WeiGao YueZhou LuyuLv XiaoyiRoussos PanosZhang Wen - The PD-L1/PD-1 signaling axis is a pivotal regulator of T-cell activity and a key mechanism by which tumors evade immune surveillance. Inhibiting this pathway has resulted in significant anti-tumor responses, establishing immune checkpoint blockade (ICB) as a crucial component of modern cancer therapy. However, many patients with high PD-L1 expression do not respond to PD-1/PD-L1 blockade, underscoring the necessity for a deeper investigation into the mechanisms underlying this resistance. Recent studies have identified DRG2 as a critical modulator of anti-PD-1 therapeutic efficacy. While DRG2 depletion enhances IFN-γ signaling and increases the overall PD-L1 levels, it disrupts the recycling of endosomal PD-L1, resulting in reduced surface expression and impaired PD-1 interaction, ultimately compromising therapeutic outcomes. Furthermore, TRAPPC4, HIP1R, and CMTM6 help stabilize PD-L1 by preventing lysosome degradation. When depleted, these proteins have been shown to boost the body's immune response against tumors. Research into the complex regulatory mechanisms of PD-L1 suggests that targeting DRG2, TRAPPC4, HIP1R, and CMTM6 could enhance the effectiveness of PD-1/PD-L1 blockade therapies. This strategy could create exciting new possibilities for cancer immunotherapy and improve patient outcomes. - Source: PubMed
Publication date: 2025/05/23
Mani MuralidharanPark Jeong WooMartin Thomas F J - Sjögren's disease (SjD) and systemic lupus erythematosus (SLE) share genetic risk at the DDX6-CXCR5 locus (11q23.3). Identifying and functionally characterising shared SNPs spanning this locus can provide new insights into common genetic mechanisms of autoimmunity. - Source: PubMed
Publication date: 2025/05/30
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