Biology subjects

Seth, G.

Publications and source records attributed to Seth, G..

4 recordsLinked to original sources

bioRxiv2026

Loss of Farnesoid X Receptor Signaling Promotes Choroidal Neovascularization in Mice

Choroidal neovascularization (CNV) is a defining feature of neovascular age-related macular degeneration (nAMD). Although anti-vascular endothelial growth factor (VEGF) therapies suppress neovascular activity, incomplete responses, recurrent leakage, and subretinal fibrosis remain important clinical challenges. The farnesoid X receptor (FXR) is a bile acid-activated nuclear receptor with anti-inflammatory, anti-fibrotic, and anti-angiogenic functions in other tissues, but its role in CNV is unknown. Analysis of publicly available human transcriptomic data (GSE135092) showed FXR expression in the retinal pigment epithelium (RPE)/choroid and significant downregulation in AMD-affected macular RPE/choroid. To define the role of FXR in CNV, laser photocoagulation was performed in wild-type (WT) and FXR-deficient (FXR-KO) mice, with disease progression assessed by in vivo imaging, histology, ex vivo choroidal sprouting, and endothelial cell assays. FXR expression in the RPE/choroid was reduced 14 days after laser injury. Compared with WT mice, FXR-KO mice developed larger CNV lesions, more extensive hyperfluorescence on fluorescein angiography, and increased lesion area during disease progression. FXR deficiency also impaired resolution of fibrotic remodeling. In WT mice, alpha-SMA peaked at day 14 and declined by day 21, whereas collagen I remained low throughout; in FXR-KO mice, both collagen I and alpha-SMA were significantly elevated relative to WT and remained significantly higher than WT at day 21. Consistent with these findings, FXR-deficient choroidal explants exhibited increased vascular sprouting, and FXR-KO endothelial cells formed more extensive capillary-like networks. Together, these findings identify FXR as an endogenous regulator of pathological angiogenesis, vascular leakage, mesenchymal activation, and fibrotic remodeling during CNV and provide a rationale for investigating FXR-directed strategies for nAMD.

biochemistry↗

bioRxiv2026

Noncoding regulatory mutations contribute to the aberrant gene expression in neuroblastoma

Comprehensive analyses of whole-genome and exome sequencing data from high-risk neuroblastoma tumors have identified relatively few recurrent and clinically actionable protein-coding driver mutations at initial diagnosis. This suggests that noncoding genetic variations that alter regulatory sequences and impact gene expression are important drivers of neuroblastoma tumorigenesis. Allele-specific expression (ASE), which quantifies differences in expression between the two alleles of a gene, is a powerful approach for identifying genes with altered dosage resulting from cis-regulatory variation. In this study, we compared ASE profiles of 156 neuroblastoma patients with 220 adrenal gland tissues from the Genotype-Tissue Expression (GTEx) Project to identify 1,363 neuroblastoma-specific ASE genes. We demonstrated that these genes were enriched for biological processes relevant to neuroblastoma pathogenesis including chromatin remodeling, protein ubiquitination, and sympathetic nervous system development, and were preferentially associated with the adrenergic transcriptional program. To elucidate the genetic mechanism underlying aberrant expression of neuroblastoma-specific ASE genes we integrated our ASE data with somatic copy number alterations (SCNA) and somatic mutation profiles. We observed that although many neuroblastoma specific ASE genes were associated with chromosomal gains and losses, a substantial subset was located within copy-number-neutral genomic regions. These genes showed significant enrichment for noncoding somatic single-nucleotide variants (SNVs) within intronic and distal intergenic neuroblastoma-specific open chromatin regions. Furthermore, functional analyses revealed that many of these SNVs disrupt transcription factor binding sites for GATA3, a core component of the regulatory circuitry that maintains the adrenergic identity of neuroblastoma cells, and neuroblastoma-specific ASE genes harboring such mutations were significantly more likely to belong to the GATA3 regulon than expected by chance. Together, our findings identify novel molecular targets of noncoding regulatory mutations in neuroblastoma and highlight the important yet underappreciated contribution of noncoding genetic variation to neuroblastoma tumorigenesis.

bioinformatics↗

bioRxiv2025

CYP46A1 Activation Improves Retinal Neovascularization in a Mouse Model of Retinopathy of Prematurity

Previous studies have shown the metabolic and regulatory significance of CYP46A1 in the adult retina; however, its role in the developing retina is unknown. Here, we evaluate CYP46A1 expression and the impact of its activation in the developing mouse retina under normal and pathological conditions. Seven-day-old (P7) C57BL/6J mice maintained in room air (controls) or subjected to oxygen-induced retinopathy (OIR) were treated with/without 20 mg/kg efavirenz (EFV), a CYP46A1 activator administered intraperitoneally from P7 to P17. Retinal cross sections and flat mounts were prepared to study retinal vasculature morphology, Muller and microglia activation, and ganglion cell viability. EFV treatment significantly reduced pathological neovascularization and the size of avascular and hypoxic areas in OIR mice retinas. EFV treatment additionally limited reactive gliosis and microglia activation and improved retinal ganglion cell survival in OIR mice. The current study demonstrates the developmental regulation of CYP46A1 and the dysregulated expression and levels of the downstream metabolite 24-Hydroxycholesterol (24HC) in OIR mice. The study further suggests that pharmacological CYP46A1 activation may improve key pathological features associated with pathological neovascularization in OIR mice.

biochemistry↗

bioRxiv2023

Predicting neoadjuvant treatment response in triple-negative breast cancer using machine learning

BackgroundNeoadjuvant chemotherapy (NAC) is the standard treatment for early-stage triple negative breast cancer (TNBC). The primary endpoint of NAC is a pathological complete response (pCR). NAC results in pCR in only 30%-40% of TNBC patients. Tumor-infiltrating lymphocytes (TILs), Ki67 and phosphohistone H3 (pH3) are a few known biomarkers to predict NAC response. Currently, systematic evaluation of the combined value of these biomarkers in predicting NAC response is lacking. In this study, the predictive value of markers derived from H&E and IHC stained biopsy tissue was comprehensively evaluated using a supervised machine learning (ML)-based approach. Identifying predictive biomarkers could help guide therapeutic decisions by enabling precise stratification of TNBC patients into responders and partial or non-responders. MethodsSerial sections from core needle biopsies (n=76) were stained with H&E, and immunohistochemically for the Ki67 and pH3 markers, followed by whole slide image (WSI) generation. The resulting WSI triplets were co-registered with H&E WSIs serving as the reference. Separate mask region-based CNN (MRCNN) models were trained with annotated H&E, Ki67 and pH3 images for detecting tumor cells, stromal and intratumoral TILs (sTILs and tTILs), Ki67+, and pH3+ cells. Top image patches with a high density of cells of interest were identified as hotspots. Best classifiers for NAC response prediction were identified by training multiple ML models, and evaluating their performance by accuracy, area under curve, and confusion matrix analyses. ResultsHighest prediction accuracy was achieved when hotspot regions were identified by tTIL counts and each hotspot was represented by measures of tTILs, sTILs, tumor cells, Ki67+, and pH3+ features. Regardless of the hotspot selection metric, a complementary use of multiple histological features (tTILs, sTILs) and molecular biomarkers (Ki67 and pH3) resulted in top ranked performance at the patient level. ConclusionsOverall, our results emphasize that prediction models for NAC response should be based on biomarkers in combination rather than in isolation. Our study provides compelling evidence to support the use of ML-based models to predict NAC response in patients with TNBC.

cancer biology↗