BCAS3

Last update 08 May 2025

Basic Info

Synonyms

BCAS3, BCAS3 microtubule associated cell migration factor, Breast carcinoma-amplified sequence 3

+ [3]

Introduction

Plays a role in angiogenesis. Participates in the regulation of cell polarity and directional endothelial cell migration by mediating both the activation and recruitment of CDC42 and the reorganization of the actin cytoskeleton at the cell leading edge. Promotes filipodia formation (By similarity). Functions synergistically with PELP1 as a transcriptional coactivator of estrogen receptor-responsive genes. Stimulates histone acetyltransferase activity. Binds to chromatin. Plays a regulatory role in autophagic activity. In complex with PHAF1, associates with the preautophagosomal structure during both non-selective and selective autophagy (PubMed:33499712). Probably binds phosphatidylinositol 3-phosphate (PtdIns3P) which would mediate the recruitment preautophagosomal structures (PubMed:33499712).

100 Clinical Results associated with BCAS3

100 Translational Medicine associated with BCAS3

0 Patents (Medical) associated with BCAS3

Literatures (Medical) associated with BCAS3

22 Apr 2025·The Journal of Clinical Endocrinology & Metabolism

Urolithiasis Causes Osteoporosis in Asians: Genetic Evidence from Mendelian Randomization and Pathway Analysis

Article

Author: Zhou, Zijie ; Fu, Jiehui ; Wei, Penghui ; Xu, Haoying ; Mei, Jian

AbstractBackgroundIt is an indisputable fact that patients with urolithiasis are prone to osteoporosis (OP), but the specific mechanism of their association is unclear. Previous studies have focused on the mediation of environmental factors such as diet; however, the potential of urolithiasis itself to induce OP remains uncertain.MethodsIn this study, we used data from the Japan BioBank (6638 urolithiasis and 7788 OP cases) to investigate the direct causal relationship and mechanism between urolithiasis and OP, applying Mendelian randomization, genetic correlation analysis, colocalization, and pathway analysis. We selected 10 genetic variants as instrumental variables for urolithiasis.ResultsThe results showed a positive association between genetically predicted urolithiasis and OP, with significant direct effects persisting after adjusting for OP-associated factors in 4 models. Reverse analysis revealed no significant causal effect of genetically predicted OP on urolithiasis. While genetic correlation analysis and colocalization did not find conclusive evidence, mediation analysis identified estimated glomerular rate as a significant contributor. Co-risk factor analysis unveiled cardiovascular elements as common risks for both conditions. Bioanalysis implicates that cytokine, metabolic, and calcium signaling pathways may bridge urolithiasis and OP, with BCAS3, DGKH, TBX2, and TBX2-AS1 identified as potential causal genes.ConclusionIn conclusion, the study establishes a direct causal link between urolithiasis and OP, independent of environmental factors. Regardless of lifestyle, urolithiasis patients should remain vigilant about the risk of OP and consider regular OP screening. The biological mechanism of urolithiasis combined with OP and related drugs still needs to be further explored.

01 Aug 2024·Journal of Clinical Investigation

C16ORF70/MYTHO promotes healthy aging in C.elegans and prevents cellular senescence in mammals

Article

Author: Swoboda, Casey O ; Tooze, Sharon A ; Milan, Giulia ; Pannone, Luca ; Grumati, Paolo ; Salvioli, Stefano ; Dikic, Ivan ; Wulff, Jesper ; Cabreiro, Filipe ; Jefferies, Harold Bj ; Franco-Romero, Anais ; Sartori, Roberta ; Armani, Andrea ; Morbidoni, Valeria ; Conte, Maria ; Franceschi, Claudio ; Romanello, Vanina ; Martinelli, Simone ; Buonomo, Viviana ; Trevisson, Eva ; van der Laan, Jennifer ; Sandri, Marco ; Salviati, Leonardo ; Millay, Douglas P

The identification of genes that confer either extension of life span or accelerate age-related decline was a step forward in understanding the mechanisms of aging and revealed that it is partially controlled by genetics and transcriptional programs. Here, we discovered that the human DNA sequence C16ORF70 encodes a protein, named MYTHO (macroautophagy and youth optimizer), which controls life span and health span. MYTHO protein is conserved from Caenorhabditis elegans to humans and its mRNA was upregulated in aged mice and elderly people. Deletion of the orthologous myt-1 gene in C. elegans dramatically shortened life span and decreased animal survival upon exposure to oxidative stress. Mechanistically, MYTHO is required for autophagy likely because it acts as a scaffold that binds WIPI2 and BCAS3 to recruit and assemble the conjugation system at the phagophore, the nascent autophagosome. We conclude that MYTHO is a transcriptionally regulated initiator of autophagy that is central in promoting stress resistance and healthy aging.

01 Jul 2024·Ophthalmology Science

Deep Learning-Based Identification of Intraocular Pressure-Associated Genes Influencing Trabecular Meshwork Cell Morphology

Article

Author: Cook, Anthony L. ; Hewitt, Alex W ; MacGregor, Stuart ; Lu, Qinyi ; Hung, Sandy ; Han, Xikun ; Liang, Helena ; Wing, Kristof ; Powell, Joseph E ; Liu, Guei-Sheung ; Craig, Jamie E ; Mackey, David A. ; Siggs, Owen M ; Zhou, Tiger ; Cook, Anthony L ; Powell, Joseph E. ; Siggs, Owen M. ; Hewitt, Alex W. ; Tran, Son N ; Tran, Son N. ; Greatbatch, Connor J ; Mackey, David A ; Craig, Jamie E. ; Greatbatch, Connor J.

PurposeGenome-wide association studies have recently uncovered many loci associated with variation in intraocular pressure (IOP). Artificial intelligence (AI) can be used to interrogate the effect of specific genetic knockouts on the morphology of trabecular meshwork cells (TMCs) and thus, IOP regulation.DesignExperimental study.SubjectsPrimary TMCs collected from human donors.MethodsSixty-two genes at 55 loci associated with IOP variation were knocked out in primary TMC lines. All cells underwent high-throughput microscopy imaging after being stained with a 5-channel fluorescent cell staining protocol. A convolutional neural network was trained to distinguish between gene knockout and normal control cell images. The area under the receiver operator curve (AUC) metric was used to quantify morphological variation in gene knockouts to identify potential pathological perturbations.Main Outcome MeasuresDegree of morphological variation as measured by deep learning algorithm accuracy of differentiation from normal controls.ResultsCells where LTBP2 or BCAS3 had been perturbed demonstrated the greatest morphological variation from normal TMCs (AUC 0.851, standard deviation [SD] 0.030; and AUC 0.845, SD 0.020, respectively). Of 7 multigene loci, 5 had statistically significant differences in AUC (P < 0.05) between genes, allowing for pathological gene prioritization. The mitochondrial channel most frequently showed the greatest degree of morphological variation (33.9% of cell lines).ConclusionsWe demonstrate a robust method for functionally interrogating genome-wide association signals using high-throughput microscopy and AI. Genetic variations inducing marked morphological variation can be readily identified, allowing for the gene-based dissection of loci associated with complex traits.Financial DisclosuresProprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

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