Ask about this productRelated genes to: ABI3BP Blocking Peptide
- Gene:
- ABI3BP NIH gene
- Name:
- ABI family member 3 binding protein
- Previous symbol:
- -
- Synonyms:
- NESHBP, DKFZP586L2024, TARSH
- Chromosome:
- 3q12.2
- Locus Type:
- gene with protein product
- Date approved:
- 2004-11-30
- Date modifiied:
- 2015-11-17
Related products to: ABI3BP Blocking Peptide
Related articles to: ABI3BP Blocking Peptide
- The extracellular matrix (ECM) plays a critical role in tumor progression by modulating cell adhesion, migration, and signaling; however, its contribution to metastatic progression in spontaneous mammary tumors remains poorly understood. Mammary tumors are among the most common neoplasms in female dogs and share histopathological and molecular similarities with human breast cancer, supporting their use as a comparative oncology model. To investigate ECM remodeling during tumor progression, we analyzed normal, non-metastatic, and metastatic canine mammary tissues using histological approaches and label-free quantitative proteomics. Publicly available human breast cancer transcriptomic datasets were interrogated for validation of conserved molecular signatures. Proteomic profiling identified 12 differentially expressed ECM-related proteins: eight were upregulated (COL12A1, COL4A1, COL4A2, SERPINH1, SERPINF1, HTRA1, TNC, PCOLCE) and four were downregulated (MMRN1, ABI3BP, DPT, OGN). The downregulated proteins were further validated in human breast cancer transcriptomes. Collectively, these findings indicate active ECM remodeling during tumor progression, characterized by increased expression of proteins associated with matrix stiffness and invasiveness. This study highlights evolutionarily conserved mechanisms of ECM dysregulation in breast cancer and identifies potential matrix targets for translational research and biomarker development. - Source: PubMed
Publication date: 2026/03/24
de Almeida Bruno SousaRocha Gisele VieiraNunes SimoneZanette Dalila LuciolaBatista MichelEstrela-Lima AlessandraRegis-Silva Carlos GustavoDamasceno Karine Araújo - Podocyte injury is a hallmark of chronic kidney disease (CKD) and organ failure, but whether different injury signals perturb unified or distinct molecular targets remains unclear. Using human induced pluripotent stem cell (hiPSC)-derived podocytes, we modeled cellular injury via exposure to diabetic, inflammatory, chemical toxin, biomechanical, and infectious stressors. Transcriptomic analysis revealed both shared and unique changes in gene expression across injury modes. While drug-induced injuries triggered broader transcriptional responses, conserved pathways related to lysosome function, RNA metabolism, and immune activation were identified across models. Importantly, we discovered NEU1, CD82, ABI3BP, and ADAM17 as targets of human podocyte injury. Analysis of multiple kidney disease patient biopsies confirmed enrichment of these targets, underscoring their in vivo relevance and potential as therapeutic targets. These findings highlight the predictive power of human-relevant experimental models and provide insight into podocyte injury responses, offering a framework for future precision medicine approaches. - Source: PubMed
Publication date: 2026/04/02
Barreto Amanda DJiang BowenBurt Morgan ADimitrakakis NikolaosMusah Samira - Blood-brain barrier (BBB) disruption represents acritical pathological featurein the pathogenesis of stroke. The extracellular matrix plays acritical rolein preserving the structural and functional integrity of the BBB. ABI3BP, an extracellular matrix protein, participatesin stem cell proliferation and differentiation, cellular senescence, tumor suppression, and extracellular matrix remodeling. However, the function and mechanism of ABI3BP in cerebral ischemia-reperfusion injury (IRI) remain unclear. In this study, we found that ABI3BP mRNA increased while protein expression decreased in the ischemic cortex, and serum ABI3BP level rose post-IRI. The thrombin inhibitor dabigatran reverses the reduction of ABI3BP after I/R injury. Thrombin hydrolyzed ABI3BP at arginine 337. Recombinant ABI3BP crossed the BBB, reduced infarct volume, improved neurological scores, restored blood flow, and decreased BBB leakage by upregulating ZO-1/Occludin in ischemic brain tissue. ABI3BP inhibits the expression of cleaved caspase-3 and increases the expression of Bcl-2/Bax, p-Akt/Akt, and p-PI3K/PI3K in vivo and in vitro. IRI induced the hydrolysis and decrease of endogenous ABI3BP level. Supplementation of recombinant ABI3BP protects against cerebral IRI by preserving BBB integrity, enhancing tight junction proteins, and suppressing endothelial apoptosis via PI3K/Akt signaling. Conclusively, these findings suggest that ABI3BP protects BBB integrity, potentially by restoring tight junction protein expression and inhibiting endothelial cell apoptosis after IRI, which suggests its promise as a therapeutic agent in ischemic stroke. - Source: PubMed
Publication date: 2026/03/14
Wang WanChen JieSong Wen-JingYang Yi-CiYin Qi-LongLi Li-LiZhang Meng-NanSu Rui-QiQin Zi-LuWen Zhen-FuQi Su-HuaHuang Lin-Yan - Reliable detection of robust biomarkers from high-dimensional transcriptomic data remains a major challenge in computational oncology. Traditional approaches often suffer from overfitting and poor generalization due to the high dimensionality of genomic data and limited sample sizes. This study aims to identify an optimal, biologically meaningful subset of mRNA biomarkers capable of distinguishing ovarian cancer samples from healthy controls using an integrated machine learning-based feature selection framework. - Source: PubMed
Publication date: 2026/01/28
Thelagathoti Rama KrishnaJiang ChaoChandel Dinesh STom Wesley ASarmiento CleoKrzyzanowski GaryOlou AppolinaireFernando M Rohan - Alzheimer’s Disease (AD) represents a growing global health challenge, driven by complex genetic factors and diverse risk contributors. Currently, an estimated 55 million people worldwide are affected by dementia, with AD responsible for 60–70% of these cases. This paper explores the application of advanced machine learning approaches to predict AD risk using Genome-Wide Association Studies data from multiple cohorts, with a particular focus on transfer learning and feature selection techniques. We evaluate the performance of Wide and Deep Neural Networks and Multi-Head Attention in assessing their ability to generalise across datasets. As part of this, we explore knowledge distillation as a strategy to enhance model efficiency through improved generalisation performance in smaller architectures by transferring knowledge from high-capacity models to lightweight ones. Furthermore, the performance of these deep learning approaches is compared with tree-based ensembles, including Random Forest and XGBoost. Our experiments evaluate the generalisability, transferability, and efficiency of these models across different transfer learning scenarios. Findings indicate that aggregating multi-cohort training data significantly enhances predictive performance, highlighting the importance of data diversity in improving AD risk assessment. The proposed knowledge distillation approach enables the transfer of knowledge from a complex teacher model to a simpler student model, significantly improving performance. To enhance interpretability, we apply SHAP (SHapley Additive exPlanations) to the student models, revealing cohort-specific differences in SNP importance and highlighting variants in genes such as ABI3BP and SYN3, both of which are linked to immune and synaptic functions in AD. The integration of SHAP enables transparent interpretation of model decisions and supports the identification of transferable genetic markers, reinforcing the clinical relevance of our framework in AD risk prediction. - Source: PubMed
Publication date: 2025/12/22
Ihianle Isibor KennedySamarasekara WathsalaBrookes KeeleyMachado Pedro