CAMK1D
- Known as:
- CAMK1D
- Catalog number:
- Y214231
- Product Quantity:
- 200ul
- Category:
- -
- Supplier:
- ABM
- Gene target:
- CAMK1D
Related genes to: CAMK1D
- Gene:
- CAMK1D NIH gene
- Name:
- calcium/calmodulin dependent protein kinase ID
- Previous symbol:
- -
- Synonyms:
- CKLiK
- Chromosome:
- 10p13
- Locus Type:
- gene with protein product
- Date approved:
- 2003-11-05
- Date modifiied:
- 2015-12-04
Related products to: CAMK1D
Related articles to: CAMK1D
- Tamoxifen is a key endocrine therapy for estrogen receptor-positive (ER) breast cancer, but acquired resistance limits long-term efficacy. The molecular mechanisms remain complex, and predictive biomarkers are lacking. Gene expression data related to tamoxifen resistance were obtained from GEO (GSE67916), and differentially expressed genes (DEGs) were identified using the limma algorithm. Functional enrichment analyses (GO and KEGG) revealed involvement in immune processes, antiviral responses, endocytosis, lysosome pathways, and estrogen signaling. Three machine learning algorithms (LASSO, SVM-RFE, and RF) identified six hub genes (CAMK1D, CHAC1, KIAA0513, MED13, NDRG1, STXBP5). A prognostic risk model based on these genes was constructed using TCGA-BRCA data, effectively stratifying patients into high- and low-risk groups with significantly different overall survival. The model demonstrated good predictive accuracy (AUC = 0.70) and stable performance in time-dependent ROC analyses, validated in an independent cohort. This study provides a robust tamoxifen resistance-related gene signature and a multigene prognostic model, offering novel insights into resistance mechanisms and potential guidance for individualized prognosis and therapy in ER breast cancer. - Source: PubMed
Publication date: 2026/06/26
Gao ChaoxuShi GuojianHou LiliLi LingWang WeijieLi XiaohuaLiu Song-Bai - Myelodysplastic neoplasms (MDS) are clonal hematopoietic disorders defined by ineffective hematopoiesis, cytopenias, and variable risk of progression to acute myeloid leukemia. Although genomic and epigenomic studies have provided insight into disease pathogenesis, reliable biomarkers for diagnosis and prognosis remain limited. Proteomics offers an important advantage because it reflects the functional protein state and captures post-translational modifications, making it highly relevant for risk assessment and therapy guidance. Recent studies have identified several groups of candidate biomarkers. Kinases and signal transduction proteins such as CAMK1D, PRKCZ, KIT, MAST4, PAK6, PTK7, and NTRK1 are dysregulated in MDS and associated with poor outcomes, immune evasion, and aberrant stem cell signaling. Oncofetal proteins like IGF2BP3 and signaling regulators such as RBP4 further highlight proteomic signatures linked to chemoresistance and subtype specificity. In the transplant setting, immune regulators including CSK, FGR, CRTAM, GP1BA, UBE2N, and STAT1 may serve as predictors of graft rejection and relapse. Cytoskeletal and extracellular matrix proteins such as CEP55, Talin-1, Kindlin-3, Vinculin, THBS1, LRG1, SPARC, SAA1, Clusterin, and PRDM16 underscore the role of bone marrow microenvironmental remodeling and adhesion defects in disease progression. Finally, metabolic enzymes such as LDHA reflect altered energy metabolism and correlate with more aggressive disease biology. Collectively, these proteomic candidates illustrate the complex interplay of signaling, immune regulation, bone microenvironment, and metabolism in MDS. Their validation in clinical cohorts could enable early detection, refined risk stratification, and new therapeutic avenues, positioning proteomics as a central tool in the future management of MDS. - Source: PubMed
Novak RuđerMandac Smoljanović IngaGrgurević Lovorka - Chronic hepatitis B virus (HBV) rarely leads to spontaneous hepatitis B surface antigen (HBsAg) seroclearance. However, host genetics contributing to this outcome remain poorly understood. We investigate genetic variants associated with HBsAg seroclearance and related viral markers. - Source: PubMed
Publication date: 2026/05/11
Tao JunHuang Chih-JenHuang Yu-HanPan Mei-HungLee Mei-HsuanYu Kelly JWang KevinZhu BinHildesheim AllanChen Chien-JenYang Hwai-ILiu Zhiwei - Pigs are one of the most important livestock species for providing meat products in the world. Deciphering the genetic architecture of feed efficiency-related traits is beneficial to improve the genetic progress of these traits and save the total cost of pork production. However, the genetic architecture of feed efficiency-related traits remains unclear. - Source: PubMed
Publication date: 2026/02/27
Lin ChangguangChen QiuyongLiu YaxuanCai WeiHuang TaoZhou YiLin JinyuZhou LunjiangChen Xinzhu - The gut microbiome is closely associated with malignant tumors; however the specific mechanisms by which it contributes to the development of lung adenocarcinoma remain unclear. In this study, we performed a two-sample bidirectional Mendelian randomization (MR) analysis to assess the causal relationship between the gut microbiome and lung adenocarcinoma. By identifying single nucleotide polymorphism markers linked to gut microbiome species, we aimed to discover potential biomarkers for lung adenocarcinoma. These findings may offer new insights into the role of the gut microbiome in the prevention and treatment of lung adenocarcinoma. - Source: PubMed
Publication date: 2026/03/18
Yan NuoZhang YangWang SilinHu ShengRuan LianchengWang YunzheFeng WeiqiangXiong WenxunZhang WenxiongWei YipingYao Chuan