Easy blot Mini YKit Activin-A, Qualitative Protein Detection-Ykit
- Known as:
- Easy blot Mini YKit Activin-A, Qualitative Protein Detection-Ykit
- Catalog number:
- RF0074
- Category:
- -
- Supplier:
- Agren
- Gene target:
- Easy blot Mini YKit Activin- Qualitative Protein Detection-Ykit
Related genes to: Easy blot Mini YKit Activin-A, Qualitative Protein Detection-Ykit
- Gene:
- GKN2 NIH gene
- Name:
- gastrokine 2
- Previous symbol:
- -
- Synonyms:
- TFIZ1, PRO813, VLTI465, blottin, GDDR, BRICD1B
- Chromosome:
- 2p13.3
- Locus Type:
- gene with protein product
- Date approved:
- 2007-01-29
- Date modifiied:
- 2016-10-05
Related products to: Easy blot Mini YKit Activin-A, Qualitative Protein Detection-Ykit
Related articles to: Easy blot Mini YKit Activin-A, Qualitative Protein Detection-Ykit
- In the early stage of gastric cancer (GC), identifying cancer-specific biomarkers is a key step in the disease screening process. This study aims to explore the clinical value of five novel protein biomarkers and their combination (5 MP) for GC early diagnosis. - Source: PubMed
Publication date: 2025/05/01
Shen WeifengZhou HuiLi LanqingLiu WeiLou QinqinTong Claire YGao JunshunGao JunliShao Pingyang - Patients with Non-Small Cell Lung Cancer (NSCLC) present a variety of clinical symptoms, such as dyspnea and chest pain, complicating accurate diagnosis. NSCLC includes subtypes distinguished by histological characteristics, specifically lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). This study aims to compare and identify abnormal gene expression patterns in LUAD and LUSC samples relative to adjacent healthy tissues using an explainable artificial intelligence (XAI) framework. The LASSO algorithm was employed to identify the top gene features in the LUAD and LUSC datasets. An ensemble-based extreme gradient boosting (XGBoost) machine learning (ML) algorithm was trained and interpreted using SHapley Additive exPlanations (SHAP), with top features undergoing biological annotation through survival and functional enrichment analyses. The XAI-based SHAP module addresses the opaque nature of ML models. Notably, 35 and 33 genes were identified for LUAD and LUSC, respectively, using the LASSO algorithm. Performance metrics such as average accuracy and Matthew's correlation coefficient were evaluated. The XGBoost model demonstrated an average accuracy of 99.1 % for LUAD and 98.6 % for LUSC. The SFTPC gene emerged as the most significant feature across both NSCLC subtypes. For LUAD, genes such as STX11, CLEC3B, EMP2, and LYVE1 significantly influenced the XAI-SHAP framework. Conversely, GKN2, OGN, SLC39A8, and MMRN1 were identified for LUSC. Survival analysis and functional validation of these genes highlighted the physiological functions observed to be dysregulated in the NSCLC subtypes. These identified genes have the potential to enhance current medical diagnostics and therapeutics. - Source: PubMed
Publication date: 2024/12/27
Datta AnkurC George Priya Doss - Intraductal papillary mucinous neoplasms (IPMN) are commonly detected pancreatic cysts that may transform into pancreatic ductal adenocarcinoma (PDAC). Predicting which IPMNs will progress to PDAC remains a clinical challenge. Moreover, identifying those clinically evident IPMNs for which a surveillance approach is best is a dire clinical need. Therefore, we aimed to identify molecular signatures that distinguished between PDAC with and without clinical evidence of an IPMN to identify novel molecular pathways related to IPMN-derived PDAC that could help guide biomarker development. Data from the Oncology Research Information Exchange Network (ORIEN) multi-institute sequencing project were utilized to analyze 66 PDAC cases from Moffitt Cancer Center and The Ohio State University Wexner Medical Center, for which tumor whole transcriptome sequencing datasets were generated. Cases were classified based on whether a tumor had originated from an IPMN ( = 16) or presumably through the pancreatic intraepithelial neoplasia (PanIN) pathway ( = 50). We then performed differential expression and pathway analysis using Gene-Set Enrichment Analysis (GSEA) and Pathway Analysis with Down-weighted Genes (PADOG) algorithms. We also analyzed immune profiles using the Tumor-Immune Microenvironment Deconvolution web portal for Bulk Transcriptomics (TIMEx). Both GSEA and TIMEx indicate that PanIN-derived PDAC tumors enrich inflammatory pathways (complement, hedgehog signaling, coagulation, inflammatory response, apical surface, IL-2/STAT5, IL-6/STAT3, EMT, KRAS signaling, apical junction, IFN-gamma, allograft rejection) and are comparatively richer in almost all immune cell types than those from IPMN-derived PDAC. IPMN-derived tumors were enriched for metabolic and energy-generating pathways (oxidative phosphorylation, unfolded protein response, pancreas beta cells, adipogenesis, fatty acid metabolism, protein secretion), and the most significantly upregulated genes (padj < 0.001) included mucin 2 (MUC2) and gastrokine-2 (GKN2). Further, the metabolic-linked gene signature enriched in the IPMN-derived samples is associated with a cluster of early-stage and long-survival (top 4th quartile) PDAC cases from The Cancer Genome Atlas (TCGA) expression database. Our data suggest that IPMN-derived and PanIN-derived PDACs differ in the expression of immune profiles and metabolic pathways. These initial findings warrant validation and follow-up to develop biomarker-based strategies for early PDAC detection and treatment. - Source: PubMed
Publication date: 2024/12/07
Park Margaret AGumpper-Fedus KristynKrishna Somashekar GGenilo-Delgado Maria CBrantley StephenHart Phil ADillhoff Mary EGomez Maria FBasinski Toni LMok Shaffer RLuthra Anjuli KFleming Jason BMohammadi AmirCenteno Barbara AJiang KunKarolak AleksandraJeong DanielChen Dung-TsaStewart Paul ATeer Jamie KCruz-Monserrate ZobeidaPermuth Jennifer B - Tff1 is a typical gastric peptide secreted together with the mucin, Muc5ac. -deficient () mice are well known for their prominent gastric phenotype and represent a recognized model for antral tumorigenesis. Notably, intestinal abnormalities have also been reported in the past in these animals. Here, we have compared the expression of selected genes in mice and their corresponding wild-type littermates (RT-PCR analyses), focusing on different mucosal protection systems along the murine intestine. As hallmarks, genes were identified with maximum expression in the proximal colon and/or the duodenum: , //, , , , , /, . This is indicative of different protection systems such as Tff2/Muc6, Tff1-Fcgbp, gastrokines, fucosylation, and reactive oxygen species (ROS) in the proximal colon and/or duodenum. Few significant transcriptional changes were observed in the intestine of mice when compared with wild-type littermates, (), , , , . We also analyzed the expression of , , and in the pancreas, liver, and lung of and wild-type animals, indicating a cross-regulation of gene expression. Furthermore, on the protein level, heteromeric Tff1-Fcgbp and various monomeric Tff1 forms were identified in the duodenum and a high-molecular-mass Tff2/Muc6 complex was identified in the proximal colon (FPLC, proteomics). - Source: PubMed
Publication date: 2023/08/11
Salm FranzZnalesniak Eva BLaskou AikateriniHarder SönkeSchlüter HartmutHoffmann Werner - Lung squamous cell carcinoma (LUSC) accounts for 30% of non-small-cell lung cancers (NSCLC), and an effective pharmacological treatment for LUSC isn't yet available. The Xihuang Pill is a potent Chinese medicinal preparation widely prescribed for the management of LUSC. - Source: PubMed
Tu HongbinLi JingXu WeijieWang ZhenweiWang Lixin