Biology subjects

Georgakopoulou, A.

Publications and source records attributed to Georgakopoulou, A..

5 recordsLinked to original sources

bioRxiv2026

In vivo HSPC gene therapy of hemoglobinopathies without drug selection of corrected cells

In vivo hematopoietic stem/progenitor cell (HSPC) gene therapy remains limited by low gene-editing efficiency and a lack of clinically applicable selection strategies to enrich therapeutically corrected progeny. We used in vivo base and prime editing to introduce a nonpathogenic EPOR variant into HSPCs, conferring erythropoietin hypersensitivity and promoting preferential expansion of gene-corrected erythroid cells. EPOR editing was combined with three therapeutic approaches for the correction of hemoglobinopathies: {gamma}-globin gene addition, {gamma}-globin reactivation, or correction of the sickle cell disease mutation. Tropism-modified helper-dependent adenoviral vectors (HDAd6/3+) targeting HSPCs were used to simultaneously deliver the EPOR-editing machinery and the corresponding therapeutic components. In vitro studies in an erythroid progenitor cell line and primary CD34+ cells demonstrated that the EPORW439* variant conferred a strong proliferative advantage to therapeutically modified erythroid progenitors. Mice humanized with CD34+ cells from a {beta}/{beta}-thalassemia patient were subjected to EPORW439*-mediated EPO hypersensitivity alongside a therapeutic {gamma}-globin transgene which resulted in >70% HbF-positive erythroid cells and substantial reversion of the disease-associated phenotype, including reduced oxidative stress, near-complete elimination of splenic iron deposition, and reduced splenomegaly. Importantly, these effects were achieved after simple intravenous administration of the vectors following HSPC mobilization and cytokine prophylaxis, without subsequent pharmacologic selection. Together, these findings establish a strategy to amplify the therapeutic benefit of otherwise limited in vivo HSPC gene editing for hemoglobinopathies.

bioengineering↗

bioRxiv2026

Preclinical efficacy and safety of Tegavivint in Wnt-activated hepatocellular carcinoma

Background & AimsHepatocellular carcinoma (HCC), a predominant form of liver cancer, remains a significant clinical unmet need. Given that 30-50% of HCC cases harbour mutations in the Wnt/{beta}-catenin signalling pathway, targeting this cascade represents a promising therapeutic strategy. However, the clinical translation of Wnt inhibitors has been hindered by severe adverse events observed in preclinical models and early-phase clinical trials, primarily due to the essential role of Wnt signalling in maintaining normal tissues such as the intestine and bone. MethodsWe examined the efficacy of Tegavivint, a first-in-class Wnt pathway inhibitor that targets TBL1, against HCC to elucidate its underlying mechanism of action. We evaluated the dose-response of Tegavivint and its effects on the cell cycle, apoptosis, and Wnt target gene expression using HepG2, HUH6, and HUH7 cell lines in vitro. Furthermore, we employed an orthotopic xenograft transplant model using HepG2 cells in immunodeficient mice to assess the safety profile and on-target anti-cancer efficacy of Tegavivint in vivo. ResultsTegavivint exhibited potent Wnt pathway-suppressing effects in cancer cells with constitutive Wnt pathway activation. Notably, Tegavivint displayed robust anti-tumour activity across a broad range of HCC cell lines, regardless of their Wnt pathway activation status. While Tegavivint inhibited the Wnt pathway and triggered the activation of apoptotic pathways in most cell lines, our findings suggest that it also can induce cell death by activating alternative non-apoptotic pathways in apoptosis-resistant cancer cells. In an orthotopic transplant mouse model, Tegavivint significantly downregulated Wnt pathway target genes, inhibited cell proliferation, induced apoptosis and suppressed growth in tumours. ConclusionsTaken together, our data establish a robust foundation for evaluating Tegavivint as a novel therapeutic option, specifically tailored for HCC patients harbouring Wnt-driven hepatic malignancies.

cancer biology↗

bioRxiv2026

L-pentahomoserine correlates with therapy outcome in esophageal cancer and promotes metabolic adaptations that support cell survival under nutrient-deprived conditions

Esophageal adenocarcinoma (EAC) is the sixth-leading cause of cancer-related death. Although pyrimidine analogue-based neoadjuvant and adjuvant therapies are widely used, patient responses remain variable. Emerging evidence indicates that bacteria-derived metabolites influence tumor biology and therapy outcomes. To identify non-canonical plasma metabolites linked to cancer biology, we performed correlation analyses between untargeted metabolomics profiles and overall survival. This approach revealed a bacterial metabolite called L-pentahomoserine, or L-2-amino-5-hydroxypentanoic acid (L-2A5HPA), to be positively associated with overall survival. Notably, L-2A5HPA promoted cell survival under nutrient limitation by redirecting glucose metabolism towards aspartate and pyrimidine biosynthesis. In vitro, L-2A5HPA uptake varied among cell lines and was controlled by stereospecific transporters. Furthermore, metabolic profiling in mouse models of liver cancer showed different levels of L-2A5HPA and a strong correlation with pyrimidine intermediates, dihydroorotate and orotate. The link between L-2A5HPA, pyrimidine nucleotide metabolism, and cell survival provides mechanistic insight into its association with patient outcome. Our findings position L-2A5HPA as a metabolite with potential to become a prognostic biomarker for EAC and underscores its role in metabolic adaptation under nutrient-deprived conditions.

cancer biology↗

bioRxiv2025

PixlMap: A generalisable pixel classifier for cellular phenotyping in multiplex immunofluorescence images

Multiplexed methods for the detection of protein expression generate extremely data-rich images of intact tissue sections. These images are invaluable for the quantification and analysis of complex biology and biomarker development. However, their interpretation presents a considerable analytical challenge. Cell segmentation from images is a key bottleneck and a major focus of research activity in artificial intelligence. Most current methods depend initially on the use of a nuclear counterstain to identify nuclear boundaries, which is a relatively straightforward task. The cellular boundary is then assigned either by expansion of the nuclear outline, or by the use of membrane or cytoplasm-specific stains to delineate cell boundaries, or by some combination of the two. The task is critical, as inaccurate segmentation leads to information loss and data contamination from neighbouring cells. Increasingly sophisticated methods are being developed to address these issues, but each has its own shortcomings. We present an alternative method which is inspired by the fact that the assignation of a cellular phenotype by eye does not depend upon the accurate identification of cell boundaries. We present an easy-to-use deep learning-based cellular phenotyping method which leverages this human capacity to assign phenotypes without segmenting the entire cell, and which can accurately phenotype cells based on nuclear segmentation alone. Using human ground truth annotations of entire cellular regions, we developed a classifier leveraging the U-Net architecture within a commercially available deep learning image analysis platform, but the principle is transferrable to any deep-learning framework. Crucially, training requires only a single example of each compartmental stain (nuclear/cytoplasmic/membranous). The resulting algorithm assigns class identities to cells with nuclear labelling alone, without the need for whole cell expansion. The method is highly novel, broadly generalisable, and comparable in accuracy to intensity-based phenotyping methods, bridging the gap between inaccurate cellular segmentation and accurate phenotype generation.

pathology↗

bioRxiv2022

β-catenin obstructs γδ T cell immunosurveillance in colon cancer through loss of BTNL expression

WNT/{beta}-catenin signaling endows cancer cells with proliferative capacity and immune-evasive functions that impair anti-cancer immunosurveillance by conventional, cytoxtoic T cells. However, the impact of dysregulated WNT signalling on unconventional, tissue-resident T cells, specifically in colon cancer is unknown. Here, we show that cancer cells in Apc-mutant mouse models escape immunosurveillance from gut-resident intraepithelial lymphocytes (IELs) expressing {gamma}{delta} T cell receptors ({gamma}{delta}TCRs). Analysis of late-stage tumors from mice and humans revealed that {gamma}{delta}IELs are largely absent from the tumor microenvironment, and that butyrophilin-like (BTNL) molecules, which can critically regulate {gamma}{delta}IEL through direct {gamma}{delta}TCR-interactions, are also downregulated. We could attribute this to {beta}-catenin stabilization, which rapidly decreased expression of the transcription factors, HNF4A and HNF4G, that we found to bind promoter regions of Btnl genes, thereby driving their expression in normal gut epithelial cells. Indeed, inhibition of {beta}-catenin signaling restored Btnl1 gene expression and {gamma}{delta} T cell infiltration into tumors. These observations highlight an immune-evasion mechanism specific to WNT-driven colon cancer cells that disrupts {gamma}{delta}IEL immunosurveillance and furthers cancer progression.

cancer biology↗