Biology subjects

Ghobashi, A.

Publications and source records attributed to Ghobashi, A..

4 recordsLinked to original sources

bioRxiv2026

SpaFlow depicts the dynamics of ligand-receptor interaction in spatial transcriptomics data

Spatial transcriptomics (ST) enables the study of cell-cell communication in native tissue context, but current methods for the ligand-receptor interaction (LRI) inference generally rely on static, distance-based assumptions. Here we present SpaFlow, a reaction-diffusion framework that models ligand diffusion, binding, dissociation, production and degradation to infer spatially resolved LRI activity and hotspots from ST data. Across paired 10x Visium and CosMx metastatic renal cell carcinoma datasets, SpaFlow outperformed existing methods in recovering spatially coherent LRIs, with inferred LRI activity showing stronger association with downstream signaling. In hepatocellular carcinoma after neoadjuvant immunotherapy, SpaFlow identified CXCL12-CXCR4 hotspots enriched at immune-rich tumor boundaries in responders. In aging mouse heart, SpaFlow resolved niche-specific pro-fibrotic and senescence-associated signaling, highlighting Postn-Itgav/Itgb5 as an additional pro-fibrotic axis and Angptl2-Pirb as a candidate mediator of inter-niche senescence-related communication. In human idiopathic pulmonary fibrosis lung, SpaFlow localized CXCL12-CXCR4 signaling between adventitial fibroblasts and CD4 T cells, CD8 T cells, and B cells in the fibrotic surrounding regions. Together, SpaFlow provides a physically informed framework for quantifying spatially constrained cell-cell communication and mechanistically interpreting signaling patterns in complex tissues.

bioinformatics↗

bioRxiv2026

Transcriptional and spatial profiling of fibroblasts from human lungs highlights CTHRC1+ cells as fibrogenic signaling hubs in fibrosis

Lung fibroblasts are key regulators of tissue homeostasis and extracellular matrix (ECM) remodeling, and their aberrant activation drives the progressive parenchymal scarring characteristic of idiopathic pulmonary fibrosis (IPF), a fatal disease with limited therapeutic options. Despite their central pathogenic role, lung fibroblasts are difficult to isolate due to their embedded position within the ECM, and standard in vitro culture conditions may lead to the loss of their native functional and transcriptional characteristics, hampering the study of fibroblast behavior in disease. The transcriptional heterogeneity of lung fibroblast subtypes and the extent to which culture-induced alterations diverge from native tissue signatures remain poorly understood. Here, we integrated single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics of lung tissue from IPF patients and age-matched healthy donors with transcriptomic profiling of cultured fibroblasts collected at passages 1 and 6 after isolation using three optimized protocols: whole lung cell suspension (WLCS), negative fraction enrichment, and outgrowth. Tissue-based analysis identified six transcriptionally distinct mesenchymal subtypes: alveolar, adventitial, inflammatory, peribronchial, CTHRC1+ and smooth muscle cell (SMC). The fibroblast subtype CTHRC1+ represented the most transcriptionally activated pro-fibrotic subtype, showing the greatest upregulation of ECM biosynthesis genes, a prominent role in intercellular communication, and preferential enrichment within fibroblastic foci in IPF lung tissue. Pseudotime trajectory analysis supported a directional transcriptional continuum from alveolar and inflammatory fibroblasts toward the CTHRC1+ state, driven by coordinated activation of pro-fibrotic transcription factors, including RUNX2, CREB3L1, and SCX. In vitro culture progressively reshaped fibroblast transcriptional identity relative to native tissue, with increased collagen and matrix metalloproteinase (MMP) expression during passaging, loss of distinct CTHRC1+ fibroblasts, and gain of alveolar fibroblasts displaying pro-fibrotic activation across all isolation protocols. These findings provide a high-resolution transcriptional map of lung fibroblast heterogeneity in IPF and highlight critical limitations of standard in vitro culture systems for recapitulating native fibroblast diversity, with important implications for the development and evaluation of fibroblast-targeted therapeutic strategies in IPF.

molecular biology↗

bioRxiv2025

An Intrinsic-hoc Framework for Heterogeneous Cellular Senescence Elucidation Using Deep Graph Representation Learning and Experimental Validation

Cellular senescence is a primordial driver of tissue and organ aging, and the accumulation of senescent cells (SnCs) has been implicated in numerous age-related diseases. A major barrier to studying senescence is the rarity and heterogeneity of SnCs, which are not a uniform population but instead comprise diverse senotypes shaped by cell-of-origin and microenvironmental context. Such heterogeneity exceeds what classical senescence hallmarks can resolve at single-cell resolution, motivating the need for computational frameworks that can capture senotype-level diversity intrinsically. Here, we introduce DeepSAS, a deep graph representation learning framework that robustly identifies cell-type-specific SnCs and their senescence-associated genes (SnGs). DeepSAS incorporates a heterogeneous graph that integrates intracellular transcriptional states with intercellular communication cues, enabling the joint inference of senescent cells and senescence-linked genes through attention-based contrastive learning. Applied to public healthy eye and lung atlases, DeepSAS identified SnCs whose proportions positively correlate with aging. From in-house idiopathic pulmonary fibrosis (IPF) patient scRNA-seq data, DeepSAS detected 1,678 SnCs (out of 24,125 cells) and 263 SnGs across 26 cell types, including 43 SnGs that are uniquely associated with a single cell type. We generated high-resolution Xenium spatial transcriptomics data to further validate SnGs in IPF, revealing NFE2L2 as a SnG specifically enriched in CTHRC1+ fibroblasts. Notably, the ex vivo bleomycin-induced senescence in human precision-cut lung slice (hPCLS) samples similarly identified NFE2L2 as an SnG in CTHRC1+ fibroblasts, albeit with stronger transcriptional signals, suggesting mechanistic differences in senescence cells associated with chronic and acute injury. Overall, DeepSAS uncovers distinct senescence programs and infers cell-type-specific SnGs that are difficult to resolve using existing marker-based approaches. We believe it offers a generalizable and translationally relevant strategy for advancing senescence biology and therapeutic development.

bioinformatics↗

bioRxiv2023

Activation of AKT induces EZH2-mediated beta-catenin trimethylation in colorectal cancer

Colorectal cancer (CRC) develops in part through the deregulation of different signaling pathways, including activation of the WNT/{beta}-catenin and PI3K/AKT pathways. Enhancer of zeste homolog 2 (EZH2) is a lysine methyltransferase that is involved in regulating stem cell development and differentiation and is overexpressed in CRC. However, depending on the study EZH2 has been found to be both positively and negatively correlated with the survival of CRC patients suggesting that EZH2s role in CRC may be context specific. In this study, we explored how PI3K/AKT activation alters EZH2s role in CRC. We found that activation of AKT by PTEN knockdown or by hydrogen peroxide treatment induced EZH2 phosphorylation at serine 21. Phosphorylation of EZH2 resulted in EZH2-mediated methylation of {beta}-catenin and an associated increased interaction between {beta}-catenin, TCF1, and RNA polymerase II. AKT activation increased {beta}-catenins enrichment across the genome and EZH2 inhibition reduced this enrichment by reducing the methylation of {beta}-catenin. Furthermore, PTEN knockdown increased the expression of epithelial-mesenchymal transition (EMT)-related genes, and somewhat unexpectedly EZH2 inhibition further increased the expression of these genes. Consistent with these findings, EZH2 inhibition enhanced the migratory phenotype of PTEN knockdown cells. Overall, we demonstrated that EZH2 modulates AKT-induced changes in gene expression through the AKT/EZH2/ {beta}-catenin axis in CRC with active PI3K/AKT signaling. Therefore, it is important to consider the use of EZH2 inhibitors in CRC with caution as these inhibitors will inhibit EZH2-mediated methylation of histone and non-histone targets such as {beta}-catenin, which can have tumor-promoting effects.

cancer biology↗