Biology subjects

Reddin, I.

Publications and source records attributed to Reddin, I..

5 recordsLinked to original sources

bioRxiv2026

Three-dimensional mapping of human lung fibrosis identifies spatial coupling between tissue microarchitecture and maladaptive repair states

Human lung fibrosis progressively destroys three-dimensional tissue architecture, yet how the structural microenvironment shapes cellular states remains unclear. Integrating 3D X-ray histology with spatial omics, we generate a volumetric multimodal atlas of human lung fibrosis that enables direct interrogation of relationships between tissue microarchitecture and spatial molecular programmes. We identify collapse of the alveolar-capillary unit - the coupled loss of alveolar type 1 epithelial cells, capillary endothelial cells, and basement membrane integrity - as a structural transition associated with early fibrogenesis. Surrounding transitional zones exhibit aberrant epithelial differentiation and proteolytic matrix remodelling, with epithelium shifting toward bronchiolised, airway-like states. Stromal activation converges on spatially restricted fibrogenic cores, sites of maximal collagen maturation and matrix stabilisation that function as signalling hubs within surrounding perifocal and vascular microenvironments. Molecular signatures of atlas-defined tissue states were associated with lung function and mortality across independent patient cohorts. Together, these data support a model in which fibrosis emerges as a spatial tissue-state process, with alveolar-capillary collapse redirecting repair towards mechanically stabilised niches that reinforce pathological remodelling.

systems biology↗

bioRxiv2024

Human-like APOBEC3 gene expression and anti-viral responses following replacement of mouse Apobec3 with the 7-gene human APOBEC3 locus

The seven human APOBEC3 (hA3) genes encode polynucleotide cytidine deaminases that play vital roles in restricting replication of viruses and retrotransposons. However, off-target A3 deamination of the cellular genome is a major source of somatic mutations in human cancer. The ability to study A3 biology in vivo is hindered by the fact that the solitary murine Apobec3 gene (mA3) encodes a cytoplasmic enzyme, with no apparent mutagenic activity. Transgenic expression of individual hA3 genes in mice has helped to confirm their oncogenic potential but important questions including which hA3 genes are active in different tissue contexts and how they function in concert when under control of their cognate promoters cannot be addressed using these models. Here we describe humanization of the mouse mA3 locus by integration of a modified BAC clone encompassing the entire 7-gene hA3 locus from human chromosome 22 replacing mA3 on mouse chromosome 15. APOBEC3 mice are viable and fertile and hA3 gene expression in cells and tissues correlates strongly with expression in corresponding human cells and tissues, indicating human-like regulation of hA3 gene expression in the mice. Splenocytes from this line display a functional human A3 response to Friend Murine Leukaemia Virus (F-MLV) infection. We propose that the Hs-APOBEC3 mouse will uniquely model the function of the complete hA3 locus in a living organism and that it will serve as a useful background upon which to model human cancer, as well as assisting drug discovery efforts.

cancer biology↗

bioRxiv2023

Combination EZH2 inhibition and retinoic acid treatment promotes differentiation and apoptosis in rhabdomyosarcoma cells

Rhabdomyosarcomas (RMS) are predominantly pediatric sarcomas thought to originate from muscle precursor cells due to impaired myogenic differentiation. Despite intensive treatment, 5-year survival for patients with advanced disease remains low (<30%), highlighting a need for novel therapies to improve outcomes. Differentiation therapeutics are agents that induce differentiation of cancer cells from malignant to benign. The histone methyltransferase, Enhancer of Zeste Homolog 2 (EZH2) suppresses normal skeletal muscle differentiation and is highly expressed in RMS tumors. We demonstrate combining EZH2 inhibition with the differentiating agent retinoic acid (RA) is more effective at reducing cell proliferation in RMS cell lines than single agents alone. In PAX3 -FOXO1 positive RMS cells this is due to an RA-driven induction of the interferon pathway resulting in apoptosis. In fusion negative RMS, combination therapy led to an EZH2i-driven upregulation of myogenic signaling resulting in differentiation. These results provide insight into the mechanism that drives the anti-cancer effect of the EZH2/RA single agent and combination treatment and indicate that the reduction of EZH2 activity combined with the induction of RA signalling represents a potential novel therapeutic strategy to treat both subtypes of RMS. HighlightsO_LIEZH2 expression is upregulated fusion positive (FPRMS) and fusion negative (FNRMS) rhabdomyosarcomas C_LIO_LIEZH2 inhibition combined with retinoic acid treatment was investigated RMS cell models. C_LIO_LICombination treatment reduced cell proliferation and tumor spheroid volume. C_LIO_LICombination treatment in FPRMS resulted in apoptosis in FPRMS via interferon signaling. C_LIO_LIConversely, combination treatment in fusion negative RMS resulted in myogenic differentiation. C_LI

cancer biology↗

bioRxiv2021

Data variability in standardised cell culture experiments

Despite much debate about a perceived reproducibility crisis in the life sciences, it remains unclear what level of replicability is technically possible [1,2]. Here, we analysed the variation among drug response data of the NCI60 project, which for decades has tested anti-cancer agents in a 60-cell line panel following a standardised protocol [3]. In total, 2.8 million compound/cell line experiments are available in the NCI60 resource CellMiner [4]. The largest fold change between the lowest and highest GI50 (concentration that reduces cell viability by 50%) in a compound/cell line combination was 3.16 x 1010. All compound/cell line combinations with >100 experiments displayed maximum GI50 fold changes >5, 99.7% maximum fold changes >10, 87.3% maximum fold changes >100, and 70.5% maximum fold changes >1000. FDA-approved drugs and experimental agents displayed similar variation. The variability remained very high after removal of outliers and among experiments performed in the same month. Hence, our analysis shows that high variability is an intrinsic feature of experimentation in biological systems, even among highly standardised experiments in a world-leading research environment. Thus, a narrow focus on experiment standardisation does not ensure a high level of replicability on its own.

pharmacology and toxicology↗

bioRxiv2020

Drug-adapted cancer cell lines reveal drug-induced heterogeneity and enable the identification of biomarker candidates for the acquired resistance setting

Survivin is a drug target and the survivin suppressant YM155 a drug candidate for high-risk neuroblastoma. Findings from one YM155-adapted subline of the neuroblastoma cell line UKF-NB-3 had suggested that increased ABCB1 (mediates YM155 efflux) levels, decreased SLC35F2 (mediates YM155 uptake) levels, decreased survivin levels, and TP53 mutations indicate YM155 resistance. Here, the investigation of ten additional YM155-adapted UKF-NB-3 sublines only confirmed the roles of ABCB1 and SLC35F2. However, cellular ABCB1 and SLC35F2 levels did not indicate YM155 sensitivity in YM155-naive cells, as indicated by drug response data derived from the Cancer Therapeutics Response Portal (CTRP) and the Genomics of Drug Sensitivity in Cancer (GDSC) databases. Moreover, the resistant sublines were characterised by a remarkable heterogeneity. Only seven sublines developed on-target resistance as indicated by resistance to RNAi-mediated survivin depletion. The sublines also varied in their response to other anti-cancer drugs. In conclusion, cancer cell populations of limited intrinsic heterogeneity can develop various resistance phenotypes in response to treatment. Therefore, individualised therapies will require monitoring of cancer cell evolution in response to treatment. Moreover, biomarkers can indicate resistance formation in the acquired resistance setting, even when they are not predictive in the intrinsic resistance setting.

pharmacology and toxicology↗