Biology subjects

Reardon, M.

Publications and source records attributed to Reardon, M..

4 recordsLinked to original sources

bioRxiv2025

Hypoxia-induced extracellular matrix changes are conserved in cancer and directly impact radiotherapy benefit

Our overarching aim was to determine how hypoxia affects the extracellular matrix (ECM). Transcriptomic analysis (21,941 patients; 10 cancer types) identified ECM remodelling as the predominant pathway affected by hypoxia. Multi-omics confirmed that hypoxia impacts ECM organisation and collagen degradation; 53 ECM genes were affected, of which 74% were HIF1/HIF2-regulated. Spatial transcriptomics highlighted different hypoxia remodelling processes in tumour and stroma. Five ECM genes commonly affected in tumour and in vitro constituted a signature. This signature was independently prognostic and independently predictive of radiotherapy benefit in multiple malignancies. Patients within either high or low hypoxic-ECM score tertiles benefited from radiotherapy versus surgery. Hypoxic ECMs generated in vitro increased adhesion and decreased migration of cancer cells, an effect enhanced by irradiation. Immunofluorescence demonstrated that hypoxia decreased collagen fibre number, and irradiation decreased cell-ECM interactions. Taken together, these findings demonstrate hypoxia induces pan-cancer ECM changes, directly impacting radiotherapy benefit.

cancer biology↗

bioRxiv2024

Investigating the impact of the interstitial fluid flow and hypoxia interface on cancer biology using a spheroid-on-chip perfusion system

Solid tumours are complex and heterogeneous systems, which exist in a dynamic biophysical microenvironment. Conventional cancer research methods have long relied on two-dimensional (2D) static cultures which neglect the dynamic, three-dimensional (3D) nature of the biophysical tumour microenvironment (TME), especially the role and impact of interstitial fluid flow (IFF). To address this, we undertook a transcriptome-wide analysis of the impact of IFF-like perfusion flow using a spheroid-on-chip microfluidic platform, which allows 3D cancer spheroids to be integrated into extracellular matrices (ECM)-like hydrogels and exposed to continuous perfusion, to mimic IFF in the TME. Importantly, we have performed these studies both in experimental (normoxia) and pathophysiological (hypoxia) oxygen conditions. Our data indicated that gene expression was altered by flow when compared to static conditions, and for the first time showed that these gene expression patterns differed in different oxygen tensions, reflecting a differential role of spheroid perfusion in IFF-like flow in tumour-relevant hypoxic conditions in the biophysical TME. We were also able to identify factors primarily linked with IFF-like conditions which are linked with prognostic value in cancer patients and therefore could correspond to a potential novel biomarker of IFF in cancer. This study therefore highlights the need to consider relevant oxygen conditions when studying the impact of flow in cancer biology, as well as demonstrating the potential of microfluidic models of flow to identify IFF-relevant tumour biomarkers.

cancer biology↗

bioRxiv2024

Blood-based detection of MMP11 as a marker of prostate cancer progression regulated by the ALDH1A1-TGF-β1 signaling mechanism

BackgroundProstate cancer (PCa) is the second most common type of tumor diagnosed in men and the fifth leading cause of cancer-related death in male patients. The response of metastatic disease to standard treatment is heterogeneous. As for now, there is no curative treatment option available for metastatic PCa, and the clinical tests capable of predicting metastatic dissemination and metastatic response to the therapies are lacking. Our recent study identifies aldehyde dehydrogenases ALDH1A1 and ALDH1A3 as critical regulators of PCa metastases. Still, the exact mechanisms mediating the role of these proteins in PCa metastatic dissemination remain not fully understood, and plasma-based biomarkers of these metastatic mechanisms are also not available. MethodsGenetic silencing, gene overexpression, or treatment with different doses of the retinoic acid (RA) isomers, which are the products of ALDH catalytic activity, were used to modulate the interplay between retinoic acid receptors (RARs) and androgen receptor (AR). RNA sequencing (RNAseq), reporter assays, and chromatin immunoprecipitation (ChIP) analysis were employed to validate the role of RARs and AR in the regulation of the transforming growth factor-beta 1 (TGFB1) expression. Gene expression levels of ALDH1A1, ALDH1A3, and the matrix metalloproteinase 11 (MMP11) and their correlation with pathological parameters and clinical outcomes were analyzed by mining several publicly available patient datasets as well as our multi-center transcriptomic dataset from patients with high-risk and locally advanced PCa. The levels of MMP11 protein were analyzed by enzyme-linked immunosorbent assay (ELISA) in independent cohorts of plasma samples from patients with localized or metastatic PCa and healthy donors, while plasma proteome profiles were obtained for selected subsets of PCa patients. ResultsWe could show that ALDH1A1 and ALDH1A3 genes differently regulate TGFB1 expression in a RAR-and AR-dependent manner. We further observed that the TGF-{beta}1 pathway contributes to the regulation of the MMPs, including MMP11. We have confirmed the relevance of MMP11 as a promising clinical marker for PCa using several independent gene expression datasets. Further, we have validated plasma MMP11 levels as a prognostic biomarker in patients with metastatic PCa. Finally, we proposed a hypothetical ALDH1A1/MMP11-related plasma proteome-based prognostic signature. ConclusionsTGFB1/MMP11 signaling contributes to the ALDH1A1-driven PCa metastases. MMP11 is a promising blood-based biomarker of PCa progression.

cancer biology↗

bioRxiv2019

Human genetic disease is greatly influenced by the underlying fragility of evolutionarily ancient genes

The ability to predict disease association in human genes is enhanced by an evolutionary understanding. Importantly genes linked with heritable disease, particularly dominant disorders, tend to have undergone duplication in our early vertebrate ancestors, with a strong asymmetric relationship between disease-association within duplicate/paralog pairs. Using a novel phylogenetic approach, alongside a whole-genome comparative analysis, we show that contrary to the accepted compensatory model of disease evolution, the majority of disease-associations reside with the more evolutionary constrained gene, inferred to most closely resemble the progenitor. This indicates that the strong association between paralogs, specifically ohnologs, and dominant disorders is often a consequence of a mechanism through which pre-existing dosage sensitive/haploinsufficient genes are successfully duplicated and retained. Heritable disease is thus as much a consequence of the fragility of evolutionarily more ancient genes as compensatory mechanisms. From these findings, we demonstrate the utility of a new model with which to predict disease associated genes in the human genome.

genetics↗