Ask about this productRelated genes to: CHK1 antibody
- Gene:
- CHEK1 NIH gene
- Name:
- checkpoint kinase 1
- Previous symbol:
- -
- Synonyms:
- CHK1
- Chromosome:
- 11q24.2
- Locus Type:
- gene with protein product
- Date approved:
- 1998-04-21
- Date modifiied:
- 2011-11-11
Related products to: CHK1 antibody
Related articles to: CHK1 antibody
- Postoperative radiotherapy is an effective treatment for meningiomas; however, treatment response varies among patients. In addition, practical methods for predicting tumor recurrence after radiotherapy have not been well established. Minichromosome maintenance protein 2 (MCM2), a key regulator of DNA replication licensing, was recently implicated in highly proliferative molecular subtypes of meningioma. In this study, the authors evaluated whether MCM2 immunohistochemical expression predicts response to radiotherapy in patients with meningiomas. - Source: PubMed
Murakami ChiakiHana TaijunShimizu TomomiHasegawa HirotakaOkuno HarunaYokoo HideakiNobusawa SumihitoMomose ShujiHigashi MorihiroHanakita ShunyaOya Soichi - To investigate the mechanism of Shengmai San (SMS) in the treatment of lung adenocarcinoma (LUAD) based on an integrated strategy combining "network pharmacology, bioinformatics, molecular docking, and molecular dynamics simulation," aiming to provide a precise combination therapy strategy and identify potential bioactive compounds. Differentially expressed genes in LUAD were identified from the Gene Expression Omnibus database using R (originally developed at Bell Laboratories and currently managed by Lucent Technologies). SMS components (ginseng, Ophiopogon japonicus, and Schisandra chinensis) were retrieved from encyclopaedia of traditional Chinese medicine, with Lipinski-compliant compounds selected. Compound targets were predicted via SwissTargetPrediction and Similarity Ensemble Approach. Intersecting targets between differentially expressed genes and compound targets were identified for "herbs-compounds-targets-disease" network construction. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed. Hub targets were identified by analyzing the protein-protein interaction network. High-prognostic relevance targets were screened from The Cancer Genome Atlas. Compounds targeting these were identified through the herbs-compounds-targets-disease network, and absorption, distribution, metabolism, excretion, and toxicity-compliant compounds were selected using SwissADME (a web-based tool provided by the Molecular Modeling Group of the Swiss Institute of Bioinformatics). Core regulatory targets were identified through molecular docking, with complex stability assessed by molecular dynamics simulations. The key bioactive compounds of SMS for treating LUAD were identified as 7-hydroxy-2,5-dimethyl-4H-1-benzopyran-4-one, N-trans-feruloyltyramine, paprazine, and (E)-N-[(2S)-2-hydroxy-2-(4-hydroxyphenyl)ethyl]-3-(4-hydroxyphenyl)prop-2-enamide. Hub targets included AURKA, CCNA2, CCNB1, CDK1, CHEK1, KIF11, NEK2, PLK1, TTK, and TYMS. Among these, CDK1, CHEK1, and PLK1 demonstrated both high-prognostic relevance and strong binding affinity with SMS, emerging as core regulatory targets for SMS in LUAD treatment. Mechanistically, SMS exerts its anticancer effects primarily by modulating the tumor necrosis factor, interleukin-17, cell cycle, and Lipid and atherosclerosis signaling pathways. The active components of SMS, such as paprazine, may exert antitumor effects partly through downregulating CDK1, CHEK1, and PLK1 expression. Although the present study did not examine drug-resistance models or combination regimens, our findings raise the possibility that, in patients with high expression of these genes, combining SMS with standard chemotherapy or targeted therapy could potentially enhance chemosensitivity and mitigate the development of resistance. This hypothesis, however, requires formal testing in appropriate preclinical models and functional validation studies. - Source: PubMed
Zhou XiaolingWu DiyaoZhang XiaohuiZhang Xinyou - : Serous ovarian cancer (SOC) is the most aggressive subtype of epithelial ovarian cancer, frequently diagnosed at advanced stages with poor prognosis and chemotherapy resistance. Checkpoint kinase 1 (CHEK1), a key regulator of the DNA damage response, is overexpressed in ovarian cancer, making it a promising therapeutic target. No study has systematically evaluated natural compounds as CHEK1 inhibitors in SOC through an integrative transcriptomic and computational framework. : A meta-analysis of three GEO datasets (GSE27651, GSE36668, GSE54388; n = 83) was performed using ImaGEO. DEGs were identified at |logFC| ≥ 2 and FDR < 0.05. Pathway enrichment, PPI network analysis, virtual screening of 40 phytochemicals against CHEK1 (PDB: 9CE4), 100 ns MD simulations, and ADMET profiling were conducted using established bioinformatics and computational tools. : A total of 511 DEGs were identified, with significant dysregulation of apoptosis, DNA repair, and cell cycle pathways. CHEK1 emerged as the central hub gene. Baicalein exhibited the highest binding affinity (-9.334 kcal/mol), surpassing Prexasertib (-7.2 kcal/mol). MD simulations confirmed complex stability, and ADMET profiling demonstrated favorable drug-likeness with zero Lipinski violations. : CHEK1 is established as a validated therapeutic target in SOC, and Baicalein is identified as a computationally superior natural lead compound, warranting experimental validation in ovarian cancer models. - Source: PubMed
Publication date: 2026/08/05
Jayagopal PoojhashriPrabhakar SandhiyaPonneri Adithavarman AbhinandChaudhari Somdatta Yashwant - Metastatic castration-resistant prostate cancer (mCRPC) remains a leading cause of cancer-related mortality in men. Although poly(ADP-ribose) polymerase inhibitors (PARP inhibitor) are approved for mCRPC patients with homologous recombination repair (HRR) deficiencies, clinical trials combining Olaparib with PD-1/PD-L1 inhibitors have shown limited efficacy in unselected populations. To investigate the immunomodulatory effects of PARP inhibitor in an unbiased manner, we performed bulk RNA sequencing on HRR-proficient MycCaP cells treated with the PARP inhibitor (Olaparib) versus vehicle control. Transcriptomics analysis revealed robust upregulation of CD73 (NT5E), an ectoenzyme and emerging immune checkpoint that generates extracellular adenosine, suggesting an adaptive mechanism that undermines Olaparib efficacy and promotes immunosuppression. CD73 induction by Olaparib was validated in both human and mouse prostate cancer cell lines, with more pronounced effects in HRR-compromised PTEN knockout (KO) cells. Mechanistically, olaparib-driven CD73 expression was mediated through DNA damage-activated ATR-CHEK1-IRF1 and TGF-β1-AKT signaling pathways. In parallel, Olaparib enhanced tumor immunogenicity by activating type I interferon (IFN) signaling and antigen presentation machinery. In vivo, combining olaparib with CD73 blockade significantly delayed tumor growth, improved T-cell infiltration, and augmented CD8⁺ T-cell effector function across HRR-proficient and PTEN KO prostate cancer models. These findings identify Olaparib-induced CD73 upregulation as an adaptive resistance mechanism and support Olaparib plus CD73 blockade as a promising therapeutic strategy for advanced prostate cancer, irrespective of HRR status. - Source: PubMed
Publication date: 2026/08/18
Xie PingMa RenqiangZhang MinghuiFan JieTang HuiSong LongzhenWan YongKuzel Timothy MFang DeyuCui WeiguoWu Jennifer DAbdulkadir Sarki AZhang YiPatnaik AkashZhang Bin - Aflatoxin B1 (AFB1) is a potent group 1 carcinogen closely associated with hepatocellular carcinoma (HCC), particularly in regions with high dietary exposure and concurrent hepatitis B virus infection. However, the molecular mechanisms by which AFB1 promotes HCC progression remain incompletely understood, and there is a lack of prognostic models specifically tailored to AFB1-associated HCC. Integrating bioinformatics and network toxicology approaches may help identify key genes and construct reliable predictive tools for this unique subtype of liver cancer. This study aims to identify AFB1-liver cancer key genes and their functional pathways, to establish a prognosis prediction model for AFB1-liver cancer patient, and analyze its performance, and to reveal the binding characteristics between AFB1 and model proteins. - Source: PubMed
Publication date: 2026/06/24
Wang ChunmeiLi JingYuan YumanLiu LiliHe YanLei Bingxi