ANKRD13B
- Known as:
- ANKRD13B
- Catalog number:
- 001606A
- Product Quantity:
- 250ul
- Category:
- -
- Supplier:
- ABM
- Gene target:
- ANKRD13B
Related genes to: ANKRD13B
- Gene:
- ANKRD13B NIH gene
- Name:
- ankyrin repeat domain 13B
- Previous symbol:
- -
- Synonyms:
- FLJ25555
- Chromosome:
- 17q11.2
- Locus Type:
- gene with protein product
- Date approved:
- 2005-07-18
- Date modifiied:
- 2015-08-26
Related products to: ANKRD13B
Related articles to: ANKRD13B
- Hepatocellular carcinoma (HCC), a prevalent malignant tumor of the digestive tract worldwide, is characterized by poor prognosis and high mortality rates. Necrosis by sodium overload (NECSO) represents a novel form of cell death that has been implicated in various cancer types. However, its functional role in HCC pathogenesis remains poorly understood. We conducted a co-expression analysis of the NECSO-associated gene TRPM4, followed by clustering analysis and weighted gene co-expression network analysis (WGCNA) to identify NECSO-related genes. Through evaluation of 101 distinct machine learning algorithm combinations, we developed prognostic models for HCC, with the optimal model selected based on the highest mean concordance index (C-index) across training and validation cohorts. Patients were stratified into high-risk and low-risk groups according to computed risk scores. Subsequent analyses compared intergroup differences in biological functions, immune microenvironment characteristics, and therapeutic responses to immunotherapy and chemotherapy. To identify pivotal biomarkers, we employed three feature selection methodologies: LASSO, SVM-RFE, and random forest algorithms. The biological significance of the identified core gene ANKRD13B was experimentally validated through in vitro cellular experiments. Using a correlation coefficient (cor) > 0.6, we identified 78 co-expressed genes. Subsequent clustering analysis of HCC samples based on these genes revealed 1,402 NECSO-associated genes. Further WGCNA, differential expression, and prognostic analyses of these genes yielded 31 prognostically genes. Among 101 machine learning combinations, the StepCox[both] combined with GBM algorithm emerged as the optimal prognostic model, achieving the highest mean C-index across training and validation cohorts. Survival analysis confirmed significantly poorer prognosis in the high-risk group. Receiver operating characteristic (ROC) curve analysis demonstrated good predictive performance. Functional enrichment revealed distinct intergroup biological profiles, with the high-risk group and the low-risk group showing enrichment in immune-related pathways, metabolic regulation, and cell death mechanisms. Notably, the high-risk group exhibited enhanced immune activation status and superior response rates to immune checkpoint inhibitors therapy. Correlation analyses established significant associations between model genes/risk scores and cell death genes, including ferroptosis, pyroptosis, cuproptosis, and disulfidptosis. Drug sensitivity analysis identified eight chemotherapeutic agents with heightened sensitivity in high-risk patients: BI.2536, Bleomycin, Cisplatin, Doxorubicin, Epothilone B, Gemcitabine, Mitomycin C, and Paclitaxel. In vitro validation confirmed ANKRD13B promoted the proliferation, invasion and migration of HCC. We established a novel NECSO prognostic model demonstrating good predictive capacity for HCC prognosis and therapeutic responsiveness. This model helps with personalized clinical management. - Source: PubMed
Publication date: 2025/09/15
Qu XiangyuZhang YigangShi YilunWang SuchenTan YiKong LianbaoZhu Deming - Colorectal cancer (CRC) is a complex disease with diverse genetic alterations and causes 10 % of cancer-related deaths worldwide. Understanding its molecular mechanisms is essential for identifying potential biomarkers and therapeutic targets for its effective management. - Source: PubMed
Publication date: 2025/02/03
Mahajan MohitaDhabalia SubodhDash TirtharajSarkar AngshumanMondal Sukanta - Gastric cancer (GC) is the second leading cause of tumor-associated death and the fourth most commonly seen tumor across the world. Abnormal ncRNAs have been verified to be involved in potential metastasis via modulating epithelial-to-mesenchymal transition progression and are vital for the progression of cancers. Tumor-infiltrating immune cells (TICs) are a vital indicator of whether cancer patients will benefit from immunotherapy. Nonetheless, the association between ceRNAs and immune cells remained largely unclear. We used the ceRNA network combined with TICs for the prediction of the clinical outcome of GC patients based on TCGA datasets. The percentage of immunocytes in GC was speculated by the use of CIBERSORT. Via Lasso and multivariate assays, prognostic models were established applying survival-related genes and immune cells. Nomograms were developed, and the accuracy of the nomograms was determined using calibration curves. The association between ceRNAs and TICs was validated by the use of integration analysis. In this study, there were 2219 mRNAs (1308 increased and 911 decreased), 171 lncRNAs (51 decreased and 120 increased), and 123 miRNAs (55 decreased and 68 increased) differentially expressed between tumor groups and nontumor groups. Five lncRNAs, six miRNAs, and 64 mRNAs were used for ceRNA network construction. Eight genes including LOX, SPARC, MASTL, PI15, BMPR1B, ANKRD13B, PVT1, and miR-7-5p were applied for the development of the prognostic model. Survival assays suggested that tumor cases with high risk exhibited a shorter overall survival. In addition, we included T-cell CD4 memory activated, monocytes, and neutrophils for the development of a prognosis model. Eventually, our team demonstrated the possible associations between the ceRNA prognosis model and prognostic model based on immune cells. To sum up, the ceRNA network could be used for gene regulation and predict clinical outcomes of GC patients. - Source: PubMed
Publication date: 2022/02/14
Shi Meng-YangMu Yan-FeiShen Neng - Clear cell renal cell carcinoma (ccRCC) accounts for 75%-85% of renal cell carcinoma (RCC) and has a poor 5-year survival rate. In recent years, medical advancement has promoted the understanding of the histopathological and molecular characterization of ccRCC; however, the carcinogenesis and molecular mechanisms of ccRCC remain unclear. Chromatin accessibility is an essential determinant of cellular phenotype. This study aimed to explore the potential role of chromatin accessibility in the development and progression of ccRCC. By the combination of open-access genome-wide chromatin accessibility profiles and gene expression profiles in ccRCC, we obtained a total of 13,474 crucial peaks, corresponding to 5,120 crucial genes and 9,185 differentially expressed genes. Moreover, two potential function modules (P2 and G4) that contained 129 upregulated genes were identified the weighted gene co-expression network analysis (WGCNA). Furthermore, we obtained five independent predictors (, , , , and ), and a prognostic model was established based on these genes through the least absolute shrinkage and selection operator-proportional hazards model (LASSO-Cox) analysis. This model can stratify the ccRCC samples into a high-risk and a low-risk group, from which the patients have distinct prognosis. Further analysis demonstrated a completely different immune cell infiltration pattern between these two risk groups. This study also suggested that mast cell resting is associated with the prognosis of ccRCC and could be a target of immunotherapy. Overall, this study indicated that chromatin accessibility plays an essential role in ccRCC. The five prognostic chromatin accessibility biomarkers and the prognostic immune cells can provide a new direction for the treatment of ccRCC. - Source: PubMed
Publication date: 2021/12/21
Meng MengLan TianjunTian DuanqingQin ZemanLi YuLi JinsongCao Haotian - Tripartite motif containing 46 was initially identified as the oncogene in several human tumors. However, the clinical value and potential functions of tripartite motif containing 46 (TRIM46) in clear cell renal cell carcinoma (ccRCC) remained largely unclear. The expressing patterns, clinical involvement, and prognostic values of TRIM46 were analyzed using the data obtained from TCGA and GEO databases. A nomogram was constructed to examine the outcome of patients with ccRCC. We estimated the association between TRIM46 with tumor immunity in ccRCC. Tripartite motif containing 46 was highly expressed in ccRCC, and its upregulation revealed an unfavorable prognosis. A nomogram based on TRIM46 expressions and other independent prognostic factors could robustly predict the overall survival of tumor patients. TRIM46 has a strong positive correlation with NUMBL, CACNB1, THBS3, ROBO3, MAP3K12, ANKRD13D, PIF1, PRELID3A, ANKRD13B, and PCNX2. Mechanically, TRIM46 displayed regulatory functions in ccRCC progression several tumor-associated pathways. Besides, we observed that TRIM46 was distinctly related to tumor immunity in ccRCC. Our findings provide a novel tumor promotive role regarding TRIM46 function in the malignant progression of ccRCC. - Source: PubMed
Publication date: 2021/11/22
Ren Xiang-BinZhao JingLiang Xue-FengGuo Xu-DongJiang Shao-BoXiang Yu-Zhu