Aug 2026· Frontiers in Cell and Developmental Biology· 0 citations· 76 references
TL;DR
A humanized multi-lineage lung model that captures epithelial-mesenchymal co-development and responsiveness to TGF-β1 stimulation and sensitivity to pirfenidone highlight its potential for antifibrotic drug screening.
Abstract
Idiopathic pulmonary fibrosis (IPF) is a progressive and irreversible interstitial lung disease with limited therapeutic options. Existing hiPSC-derived lung organoid models are largely restricted to single epithelial lineages and cannot endogenously integrate multiple pulmonary cell types, limiting mechanistic studies and drug screening.
We established a staged directed differentiation protocol to sequentially differentiate hiPSCs into definitive endoderm, anterior foregut endoderm, and lung progenitor cells, ultimately generating a multi-lineage lung model on Transwell inserts. The model was characterized by bright-field microscopy, hematoxylin-eosin (H&E) staining, scanning and transmission electron microscopy, immunofluorescence, quantitative real-time PCR (qRT-PCR), enzyme-linked immunosorbent assay (ELISA), and single-cell RNA sequencing. Fibrosis-like phenotypes were induced by transforming growth factor-beta 1 (TGF-β1) stimulation. Transcriptomic similarity to human IPF was assessed by RNA sequencing (RNA-seq) combined with bidirectional gene set enrichment analysis (GSEA), and drug responsiveness was validated with pirfenidone.
Without genetic editing or exogenous cell supplementation, the model endogenously generated proximal duct-like epithelium, distal alveolar epithelium, fibroblasts, endothelial cells, and CD68
+
macrophage-like cells confirmed by immunofluorescence. Single-cell sequencing identified 13 transcriptional subclusters and revealed epithelial-mesenchymal co-development. TGF-β1 stimulation induced epithelial barrier disruption, ferroptosis-like mitochondrial ultrastructural alterations, extracellular matrix (ECM) remodeling, and aberrant secretion of multiple IPF-associated biomarkers. Transcriptomic analysis showed that upregulated genes in the fibrosis model group were significantly enriched in ECM organization, cell adhesion, and the PI3K-Akt pathway. Protein-protein interaction (PPI) network analysis identified
COL1A1
,
FN1
, and integrin family members as central hubs. Bidirectional GSEA validation confirmed that the transcriptomic signature of the model was highly similar to human IPF, with differentially expressed genes significantly enriched in three independent IPF cohorts. Pirfenidone reversed TGF-β1-induced ECM deposition and myofibroblast activation, and partially restored type II alveolar epithelial (AT2) cell marker expression.
We successfully established a humanized multi-lineage lung model that captures epithelial-mesenchymal co-development
in vitro
. Its responsiveness to TGF-β1 stimulation and sensitivity to pirfenidone highlight its potential for antifibrotic drug screening. This platform offers a humanized tool with the potential to be standardized for investigating cell fate determination during early lung development and the pathogenesis of IPF.
It is concluded that bridging the gap between foundational CRISPR research and its real-world applications is imperative and future efforts should focus on democratizing tools via open-source platforms, advancing delivery systems, and fostering sustainable innovation through synthetic biology integration to fully realize the transformative potential of genome editing in organisms beyond model organisms.
S. Sarsaiya, Archana Jain, Jishuang Chen et al.· Biotechnology Advances· 2 citations
It is argued that formation of a tumour-intrinsic niche is a prerequisite for BRAF-mutant CRC seeding to distant organs and that interference with niche formation may help avoid metastatic relapse.
J. Bugter, L. El Bouazzaoui, E. Küçükköse et al.· bioRxiv· 2 citations
This review summarizes emerging therapeutic strategies for EOC, their mechanisms of action, and their potential to overcome treatment resistance, and covers molecularly targeted therapies, immunotherapies, metabolic and epigenetic approaches, cellular and gene therapies, targeted drug-delivery systems, and locoregional and physical modalities.
Zofia Pietrasik, Mikołaj Kapała, Joanna Pietrasik et al.· Cancers· 0 citations
Genetic engineering (GE) and gene editing may endow traits to trees such as increased biomass and the production of novel biomaterials. Long-lived organisms such as trees might be subject to biotechnology-related risks that could be different than those of annual row crops. Those risks could be relevant to production in engineered plantations and beyond plantations to natural forests. Therefore, appropriate risk regulation is important to assure biosafety of commercialized engineered trees. In addition to gene flow via sexual reproduction, vegetative reproduction might play an additional role in environmental "exposure" risk relative to transgene dispersal in GE tree plantations. While vegetative reproduction is beneficial for preserving desired genetic traits during tree propagation, it may lead to proximal clonal spread in the field. Although the environmental risks associated with vegetative reproduction of GE trees are recognized in commercial forestry, there are few field-based environmental risk assessment (ERA) studies on dispersal risks of self-propagated GE trees. GE or gene editing of target genes involved in the vegetative propagation processes may be useful to mitigate environmental risks of clonal spread through vegetative reproduction. This review provides updates for recent field test results of GE and gene edited trees. Gene candidates related to vegetative reproduction including adventitious shooting (AS) and adventitious rooting (AR) are discussed herein as a means to mitigate unintended clonal spread from GE tree plantations.
The central nervous system (CNS) harbors a distinct immune memory programming system, wherein immunogenic cell death (ICD) acts as a pivotal signaling hub. A spectrum of insults, from systemic metabolic dysfunction to local protein aggregation and ionic dyshomeostasis, can provoke ICD in neurons, glia, and resident immune cells. This process orchestrates the release of damage-associated molecular patterns (DAMPs) from distinct subcellular compartments. These DAMPs synergistically initiate both innate trained immunity (TI), characterized by profound metabolic-epigenetic reprogramming, and antigen-specific adaptive immune responses that traverse the blood-brain barrier. Together, these pathways constitute an integral network of central immune surveillance. Crucially, this ICD-driven immune programming exhibits a striking functional dichotomy depending on the pathological context. In non-neoplastic conditions such as neural injury and neurodegenerative diseases, uncontrolled ICD signaling can establish a pathological trained immune memory, driving a self-perpetuating cycle of chronic neuroinflammation and tissue damage. Conversely, within the tumor microenvironment of malignancies like glioma, the adaptive immune responses elicited by ICD are frequently subverted by potent immunosuppressive mechanisms, culminating in tumor immune escape. This review dissects the differential regulatory mechanisms of ICD-mediated immune memory in CNS tumors versus non-tumor diseases. We aim to elucidate the molecular switches that govern the transition of this immune program from a beneficial, compensatory state to a pathological, detrimental phenotype. By exploring emerging therapeutic strategies, including gene editing, nanomaterials, and bioactive phytochemicals that precisely target ICD pathways, we provide a theoretical framework for understanding CNS immune homeostasis and for the rational design of precision immunotherapies.
Unknown authors· Ageing Research Reviews· 0 citations
Findings establish Cas7-11 as a precise and efficient RNA knockdown tool for functional studies in embryonic development and stem cell biology, providing a versatile alternative to DNA-based gene-editing approaches.
Huan Yan, Imtiaz Ul Hassan, Kai Yan et al.· Cell & Bioscience· 0 citations
A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.