DRES93 Antibody
- Known as:
- DRES93 Antibody
- Catalog number:
- XW-7932
- Product Quantity:
- 0.05 mg
- Category:
- -
- Supplier:
- Prosci
- Gene target:
- DRES93 Antibody
Ask about this productRelated genes to: DRES93 Antibody
- Gene:
- VAX2 NIH gene
- Name:
- ventral anterior homeobox 2
- Previous symbol:
- -
- Synonyms:
- DRES93
- Chromosome:
- 2p13.3
- Locus Type:
- gene with protein product
- Date approved:
- 1999-11-16
- Date modifiied:
- 2014-11-19
Related products to: DRES93 Antibody
Related articles to: DRES93 Antibody
- Transcription factors (TFs) involve in colorectal cancer (CRC). However, the function and mechanism of VAX2 in the development of CRC remain barely known. In the present study, we observed that transcription factor VAX2 is frequently upregulated in CRC internal sample set and external tissue microarray and cell lines. High VAX2 expression is observably correlated with tumor invasiveness and AJCC stage of tumors in CRC. Furthermore, decreased expression of VAX2 functionally inhibits the proliferation and facilitates the apoptosis of CRC cells and vice versa. Mechanistically, VAX2 involves in WNT/beta-catenin signaling through facilitating the nucleus accumulation of beta-catenin and VAX2 specifically binds to the promoter and trigger the transcription of SERPINE1. SERPINE1 overexpression significantly reverses the suppression of malignant behavior and nucleus accumulation of beta-catenin induced by VAX2 knockdown in vitro. In vivo, both the knockdown of SERPINE1 and the oral administration of its inhibitor Tiplaxtinin consistently attenuated the VAX2-enhanced proliferative capacity. Consistent with analysis of TCGA-CRC, positive correlation can be detected between VAX2 and SERPINE1 in fresh CRC samples. Thus, VAX2-SERPINE1 axis participate in CRC progression and work as a potential target against CRC. - Source: PubMed
Publication date: 2026/02/14
Zhang JiemingLiu GuangnanPeng SiyangChen YidongXie YanciLei YutingWu JiekeHuang XiaodongWei XiangyangHong LinjieYang PingPeng YingTang WeimeiWu XiaoshengLi AiminLiu SideShi XinpengXiong JingWang Jide - Iris pigmented epithelial (IPE) cells transdifferentiate to lens epithelial cells (LECs) during Wolffian lens regeneration in newts. Single cell RNA sequencing was used at multiple timepoints to further our understanding of this process and the cells involved in it. All major cell types present in and adjacent to the iris were identified including IPE cells, macrophages, non-pigmented ciliary epithelial cells, pigmented ciliary epithelial cells, and stroma-residing fibroblasts, endothelial cells, iridophores, and melanocytes. In the intact iris, IPE cell subpopulations were characterized by the expression of the dorsoventral genes TBX5 and VAX2, and newly identified markers LTBP2, CHRM3, and NTN1. During regeneration, IPE heterogeneity was correlated with functional states such as the cell cycle, migration, and lens vesicle formation. Pseudotime trajectory analysis revealed new insights into transcriptional and reprogramming factors during the IPE-to-LEC conversion and built a molecular and genetic blueprint of newt lens regeneration. Macrophages were identified as tissue-resident and underwent polarization from M1 early to M2 late during lens regeneration, an event that correlated temporally with the IPE-to-LEC reprogramming. Overall, this atlas provides data and analysis for iris cell types, IPE subpopulations, IPE cell states, gene expression changes as IPE cells reprogram to LECs, macrophage identity and function, and cell-to-cell interactions during newt lens regeneration. - Source: PubMed
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Williams Olivia MAhearn Kelsey ESevigny Joseph LFarber NicoleHegde DishaLampel Kenneth JLoporcaro JennaNapoleon LeoNipoti JacobRalich TimothyWallace BrooklynThomas W KelleySousounis Konstantinos - Glioblastoma (GBM) is a highly aggressive brain tumor with a median survival of only 15 months. A major challenge in GBM management is the pronounced inter- and intratumoral heterogeneity, which complicates prognosis and therapy. Radiomics, the quantitative extraction of features from medical images, can capture this heterogeneity across the entire tumor volume, but the biological basis of radiographic phenotypes remains poorly understood. - Source: PubMed
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