Ask about this productRelated genes to: CACYBP antibody
- Gene:
- CACYBP NIH gene
- Name:
- calcyclin binding protein
- Previous symbol:
- -
- Synonyms:
- SIP, S100A6BP
- Chromosome:
- 1q25.1
- Locus Type:
- gene with protein product
- Date approved:
- 2004-11-03
- Date modifiied:
- 2016-10-05
Related products to: CACYBP antibody
Related articles to: CACYBP antibody
- This study integrates single-cell RNA sequencing with Mendelian randomization to elucidate the role of nuclear factor of activated T cells (NFAT)-related genes in the progression of hepatocellular carcinoma (HCC). The GSE162616 dataset was analyzed to identify differentially expressed cells and NFAT-related genes through quality control, clustering, and -score algorithms. Mendelian randomization analysis of expression quantitative trait loci (eQTL) data was performed to identify hub genes causally linked to HCC. Validation in The Cancer Genome Atlas-Liver Hepatocellular Carcinoma cohort included survival analysis, clinical correlation, and nomogram construction. Sixteen cell clusters were resolved and annotated into five types: natural killer (NK) cells, T cells, B cells, hepatocytes, and monocytes. Differentially expressed NFAT-related genes were predominantly enriched in immune and cytokine pathways. Three genes-CACYBP, CTLA4, and RGCC-were identified as causally associated with HCC and designated as hub genes. T cells and NK cells emerged as key cellular populations, and pseudotime analysis delineated T cell differentiation trajectories. Cell-cell communication analysis revealed robust interactions between NK and B cells and between NK and T cells, primarily via the MIF-(CD74+CXCR4) axis. All three hub genes were upregulated in HCC tissues. A nomogram integrating these genes exhibited excellent diagnostic performance (AUC = 0.9). These results establish CACYBP and RGCC as risk factors and CTLA4 as a protective factor for HCC. The nomogram offers a potential tool for early diagnosis and immunotherapy guidance. Our findings highlight the value of integrating single-cell transcriptomics with Mendelian randomization for prioritizing causal genes and provide novel insights into NFAT-mediated immune regulation in HCC. - Source: PubMed
Publication date: 2026/04/20
Chen YunfeiYang XitingZhong LintaoChen KaiLuo Le - Papillary urothelial carcinoma (transitional cell carcinoma) is one of the most common malignant tumors of the urinary tract. Urothelial carcinomas are classified into muscle-invasive and non-muscle-invasive types. Among the latter, papillary urothelial carcinoma is further categorized into low-grade and high-grade forms. The aggressiveness of bladder cancer depends on the stage and grade of the disease. The CacyBP/SIP protein and MAP kinases play key roles in various cellular processes and signaling pathways that determine cell survival or death. This study aimed to assess the expression of CacyBP/SIP, ERK1/2, and p38 in low- and high-grade papillary urothelial carcinoma using immunohistochemical and molecular analyses. - Source: PubMed
Domian NataliaMłynarczyk GrzegorzKasacka Irena - To date, immune checkpoint inhibitors (ICIs) have emerged as a leading treatment for metastatic cancer, significantly improving patient survival while causing relatively few side effects. However, the objective response rate for ICIs remains low approximately 30% in urothelial carcinoma (UC), underscoring the urgent need for predictive response biomarkers. Several state-of-the-art signatures have been revealed in top-tier journals, highlighting the importance of this field. As the number of genes (~20,000) far exceeds the sample sizes of typical training sets (generally ≤ 300), we first developed feature selection procedures to reduce the number of features to a few hundred. We then trained multiple machine learning classifiers using the selected genes and the IMvigor210 dataset, which includes RNA-seq and clinical data from ~298 patients with metastatic UC (mUC). Notably, our predictor LogitDA, using the identified 49-gene signature, achieved a prediction AUC of 0.75 in an independent dataset, PCD4989g(mUC). Moreover, our signature outperformed six state-of-the-art signatures, PD-L1 IHC, and five tumor microenvironment signatures, including IFN-γ, T-effector, and T-cell exhaustion signatures. When we integrated each of the six known signatures with our own, our signature still surpassed the integrated ones in terms of prediction AUC and accuracy in the PCD4989g(mUC) dataset. From our signature, we identified key prognostic biomarkers, with the top five markers LYRM1, RFC4, CENPL, SPAG5, and CACYBP (Benjamini-Hochberg adjusted P < 0.0025) in the IMvigor210 dataset. Finally, we performed pathway analyses using Reactome (MSigDB) and KEGG, to reveal some immune-related pathways enriched such as MHC class II antigen presentation. - Source: PubMed
Publication date: 2025/11/20
Langfelder PeterLin En-TniTsai Yi-TaCha Tai-LungShieh Grace S - Neuronal morphogenesis relies on intercellular signaling. Astrocytes release metabolites, trophic, and guidance factors to promote neuronal maturation. In contrast, the mechanisms by which astrocytes could limit and stabilize neuronal connectivity remain less explored. Here, we find cortical astrocytes to express and release S100A6, a Ca-binding protein ('calcyclin'). Simultaneously, the majority of cortical neurons expressed calcyclin-binding protein (CaCyBp), a bona fide binding partner for S100A6. In neurons, CaCyBp maintains the unfolded protein response pathway, thereby controlling proteostasis. When released, S100A6 inhibits CaCyBp-mediated signaling, thus slowing protein turnover, and, consequently, neuritogenesis. In the cerebral cortex of male mice, S100A6-CaCyBp signaling during gestation is sensitive to the mother's nutritional status, particularly eicosapentaenoic acid intake. Thus, a member of the S100 protein family acts as an astroglia-derived morphogen, whose action on neurons is modulated by environmental factors. - Source: PubMed
Publication date: 2025/10/13
Cinquina ValentinaTretiakov Evgenii OKalaba PredragAlpár AlánCalvigioni DanielaPiscitelli FabianaKeimpema ErikDi Marzo VincenzoVerkhratsky AlexejHarkany Tibor - Dynamic protein-protein interactions are key drivers of many cellular processes. Determining the relative sequence and precise timing of these interactions is crucial for elucidating the functional dynamics of biological processes. Here, we developed a time-resolved analysis of protein-protein ensembles using a destabilizing domain (TRAPPED) to study protein-protein interactions in a temporal manner. We have taken advantage of a dihydrofolate reductase-destabilizing domain (DHFR(DD)) that can be fused to a protein of interest and is constitutively degraded by the proteosome. Addition of the ligand trimethoprim (TMP) can stabilize DHFR(DD), preventing proteasomal degradation of the fusion protein and thereby inducing accumulation in cells. We synthesized and optimized TRimethoprim Analog Probes that maintain stabilization activity and contain a terminal alkyne for Click functionalization and a thiol reactive group to covalently tag DHFR(DD). Click reaction with a biotin tag and subsequent streptavidin enrichment enable time-resolved mass spectrometric identification of interacting partners. We evaluated the timing of protein interactions of SARS-CoV-2 and SARS-CoV nonstructural protein 15 (nsp15) over a 2 h period. We found interactors GEMIN5 and YBX3, known regulators of SARS-CoV-2 infection that bind viral RNA, as well as CACYBP and FHL1 that implicate nsp15 in the disruption of host ERK1/2 signaling. We further revealed that these interactions remain relatively steady from 0 to 2 h post translation of nsp15. TRAPPED methodology can be applied to determine the sequence and timing of protein-protein interactions of temporally regulated biological processes such as viral infection or signal transduction. - Source: PubMed
Publication date: 2025/09/01
Cameron CrisseyClark R MasonMetts Adam MJiang Runze MScaggs Toya DKim KwanghoSulikowski Gary APlate Lars