XTP3TPA Blocking Peptide
- Known as:
- XTP3TPA Blocking Peptide
- Catalog number:
- 33r-4552
- Product Quantity:
- USD
- Category:
- -
- Supplier:
- Fitzgerald industries international
- Gene target:
- XTP3TPA Blocking Peptide
Related genes to: XTP3TPA Blocking Peptide
- Gene:
- DCTPP1 NIH gene
- Name:
- dCTP pyrophosphatase 1
- Previous symbol:
- -
- Synonyms:
- MGC5627, RS21C6, CDA03, XTP3TPA
- Chromosome:
- 16p11.2
- Locus Type:
- gene with protein product
- Date approved:
- 2008-12-18
- Date modifiied:
- 2014-11-19
Related products to: XTP3TPA Blocking Peptide
Related articles to: XTP3TPA Blocking Peptide
- DCTPP1 is a nucleotide pyrophosphatase that helps preserve genomic stability and epigenetic programming by hydrolyzing and preventing the misincorporation of methylated base-modified deoxycytosine triphosphates into DNA. Through this role, DCTPP1 can degrade the efficacy of nucleotide analog-based DNA methyltransferase inhibitors and thus represents a compelling therapeutic target in cancer treatment. To identify prospective antagonists of DCTPP1, we conducted a high-throughput chemical screen against the enzyme, identifying both existing and previously unreported inhibitor classes with potent submicromolar activity. Structural characterization using X-ray crystallography revealed that the inhibitors all occupy DCTPP1's nucleotide-binding pocket, associating primarily with a pair of tryptophans and two critical histidine residues that mimic interactions observed with natural substrates. Biochemical assays using modified chemical scaffolds confirmed the relevancy of the observed DCTPP1-antagonist interactions, while cell-based experiments demonstrated significant synergy between the lead inhibitors and the nucleoside analog decitabine in blocking the growth of prostate cancer cells. The specificity and efficacy of the compounds were further validated through loss- and gain-of-function studies, confirming the dependence of their therapeutic synergy on DCTPP1 activity. These findings advance our understanding of DCTPP1 as a therapeutic target while uncovering chemical scaffolds that can potentiate the action of existing nucleotide-based cancer therapies. - Source: PubMed
Publication date: 2026/06/15
Hauk GlennLiu JianyongNelson William GYegnasubramanian SrinivasanBerger James M - Tumor-associated macrophages (TAMs) are key components of the colorectal cancer (CRC) microenvironment, yet the transcriptional programs associated with M2 states and their prognostic relevance remain incompletely defined. Here, single-cell RNA-seq analysis of CRC identified macrophages that were further classified into M0-like, M1-like, and M2-like states. Pseudotime analysis identified 311 genes associated with M2-like polarization. Cox and LASSO analyses yielded 16 M2-associated prognostic genes (M2Gs), whose robustness was further validated in an independent dataset. PLTP, NPL, and DCTPP1 were enriched in M2 macrophages in CRC tissues. Knockdown of these genes reduced IL-10-induced M2-like polarization, and conditioned media from knockdown macrophages suppressed the malignant phenotypes of HCT116 cells. Finally, a 16-M2G-based risk model stratified prognosis in TCGA and two independent cohorts. Collectively, our study defines an M2-like TAM-associated transcriptional signature with prognostic relevance in CRC and provides functional evidence that selected M2G modulate macrophage polarization and tumor cell phenotypes. - Source: PubMed
Publication date: 2026/06/05
Li MengDong Lingling - Inferring gene regulatory networks (GRNs) from single-cell RNA sequencing (scRNA-seq) data is fundamentally challenged by severe data sparsity, where pervasive dropout events obscure true regulatory signals and compromise the reliability of downstream inference. Existing supervised methods, while leveraging prior network structures, remain highly susceptible to this noise due to their end-to-end learning paradigm. To address this bottleneck, we propose SGMHA, a novel two-stage framework that decouples representation learning from link prediction. Specifically, SGMHA first employs a self-supervised graph masked autoencoder (GraphMAE) to learn robust gene representations by reconstructing randomly masked expression values, thereby mitigating sparsity-induced distortions. Subsequently, an MHA (multi-head attention)-based fine-tuning module integrates these pre-trained representations with raw expression data to accurately infer directed regulatory links. Extensive benchmarking across seven scRNA-seq datasets demonstrates that SGMHA consistently outperforms eight state-of-the-art methods in both area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC). Applying SGMHA to breast cancer metastasis revealed context-specific GRNs and identified 26 high-confidence candidate drivers. Among these, six (NDUFAF4, ENY2, CCT5, PGK1, DCTPP1, and H2AFZ) were validated as prognostic biomarkers, with their mechanistic roles in metastatic adaptation detailed through multi-omics integration. Collectively, SGMHA provides an accurate, scalable, and biologically interpretable tool for GRN inference, holding strong promise for biomarker discovery in complex diseases. - Source: PubMed
Publication date: 2026/06/09
Zhang XujianLi WenhaoPan YuliangWang XupengGuan JihongCao Zhiwei - Fluorocyclopentenylcytosine (RX-3117) is a nucleoside analog developed to bypass gemcitabine resistance. We developed several fluorocyclopentenylcytosine- and gemcitabine-resistant non-small cell lung cancer (NSCLC) cell lines, which showed decreased accumulation of the active triphosphate. The expression of the human equilibrative nucleoside transporter and the activity of uridine cytidine kinase 2 were not altered. The cells showed cross-resistance to some cytidine analogs (e.g. ethynylcytidine and cyclopentenyl-cytosine) but not to other DNA damaging drugs, such as cisplatin, and drugs inhibiting the proteasome, a protease or cell cycle regulators. In most resistant lines, the expression of MutT Homolog-1/8-oxo-dGTP diphosphatase (MTH1) and deoxycytidine triphosphatase 1 (DCTPP1) was increased, suggesting that these enzymes degrade the triphosphates. To reverse resistance, we combined fluorocyclopentenylcytosine with inhibitors of MTH1 (TH588) and DCTPP1 (TH1217 and triptolide). Drug sensitivity was tested in resistant NSCLC variants using the SRB assay with co-treatment of fluorocyclopentenylcytosine and IC25 concentrations of inhibitors. Despite the increased expression of MTH1 and DCTPP1, treatment with TH588, TH1217, or triptolide did not re-sensitize the resistant lines, except for cells resistant to gemcitabine and to both gemcitabine and fluorocyclopentenylcytosine, which showed increased sensitivity to fluorocyclopentenylcytosine combined with the inhibitors. In conclusion, while fluorocyclopentenylcytosine resistance involves decreased triphosphate accumulation and increased expression of DNA repair enzymes, only gemcitabine- and double-resistant cells became more sensitive to enzyme inhibition, suggesting other mechanisms contribute to resistance. - Source: PubMed
Publication date: 2026/06/05
Sarkisjan DjzemmaZekanovic SafetBalboni BeatriceJulsing JorisHoneywell Richard JPeters Godefridus J - Porcine epidemic diarrhea virus (PEDV) infection leads to serious intestinal disease in piglets, often leading to high mortality rates and substantial economic losses. Understanding host-PEDV interactions is crucial for PEDV therapeutic strategies. N-methyladenosine (mA) methylation has been proven to play an important role in host antiviral immunity. However, transcriptome-wide profiling patterns and the biological functions of host mA methylation in response to PEDV infection remain incompletely understood. This study first observed significant upregulation of mA regulators (METTL3, FTO, WTAP, YTHDC1, and YTHDF2) in PEDV infection. Following transcriptome-wide mA methylation and gene expression profiling, this study identified 803 differentially methylated peaks with 674 differentially expressed mA-methylated genes and 345 differentially expressed genes (DEGs) after PEDV infection. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that these differentially methylated genes were enriched mainly in lysine degradation, histidine metabolism, and the ubiquitin-mediated proteolysis pathway, whereas these DEGs were enriched in negative regulation of viral genome replication, viral protein interaction with cytokines and cytokine receptors, nucleotide-binding oligomerization domain-like (NOD-like) receptor signaling, and immune response-related signaling pathways. Furthermore, the joint analysis of RNA sequencing (RNA-seq) and methylated RNA immunoprecipitation sequencing (MeRIP-seq) identified 16 differentially expressed genes with mA methylation ( and ), which were associated with immune response and metabolism. Taken together, the study results map the dynamic landscape of host mA methylation and demonstrate the functional enrichment of mA methylated genes during PEDV infection, thereby providing a theoretical framework for future research on the role of mA methylation in resistance to PEDV infection. - Source: PubMed
Publication date: 2026/05/18
Dong XiaZhang YueWang YingWang ChengZhou Ao