Biology subjects

Fay, J.

Publications and source records attributed to Fay, J..

7 recordsLinked to original sources

bioRxiv2026

A neural network model delivers a highly prognostic protein signature in cancer stem cells that identifies relapse in stage III colorectal cancer patients.

BackgroundStage III colorectal cancer poses a significant threat of metastasis development, as tumour resection and adjuvant chemotherapy do not guarantee prolonged disease-free survival. ObjectiveThe spatial, quantitative, and qualitative characteristics of various cell types within tumour tissues could be key to developing accurate prognostic AI models. DesignTissue microarrays created from primary tumour tissues collected during surgical resection from a cohort of 493 stage III colorectal cancer (CRC) patients were analysed for 61 protein markers at the single-cell level using multiplexed immunofluorescence imaging via the Cell DIVE platform. Subsequent cell-type classification enabled quantitative cell-type analyses, co-localisation neighbourhood assessments, and cell-type-specific protein signature discoveries that distinguish between early and late/non-recurring patient samples. ResultsThis study identifies a stem cell protein profile that drives tumour relapse. A deep neural network (DNN) model, based on a stem cell protein signature composed of BAX, MLKL, FLIP, GLUT1, and CDX2, provided accurate prognosis for stage III CRC patients in both discovery and validation cohorts and in an independent validation cohort. Nodal count-based metric further increased prognosis accuracy. Our study also revealed distinct spatial arrangements of immune, endothelial, and stem cells that were linked to early tumour recurrence. ConclusionOur findings propose a clinically promising prognostic tool based on a five-protein stem cell signature. These markers not only predict chemotherapy resistance in cancer stem cells but also suggest potential therapeutic strategies such as combinatorial treatments incorporating small molecule inhibitors targeting FLIP and GLUT1. Key messagesO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIMore than 20% of stage III colorectal cancer patients will experience early tumour recurrence within the first 3 years post treatment that includes surgery and adjuvant 5-FU based chemotherapy treatment. C_LIO_LISeveral studies pointed towards involvements of number of cell type specific spatial neighbourhoods in tumour progression where some immune tumour microenvironment promoting angiogenesis and intravasation events, some may provide immunosuppression. C_LIO_LICancer stem cells could be responsible for metastatic tumour spread, early recurrence and chemoresistance. C_LI What this study addsO_LISpatial single cell quantitative multiplex profiling of 45 cancer hallmark proteins and 15 cell identity markers in 493 stage III CRC patients tissue samples demonstrated significant differences in cellular proximity neighbourhoods, cell type specific abundance and expression between the early and late recurrence samples. C_LIO_LIWe discover that macrophages show spatial association with the blood vessels in early recurrence samples. Moreover, we observed conglomeration of B cells and macrophages with Tregulatory, Thelper and Tcytotoxic cells in association with early recurrences. C_LIO_LIWe showed that stromal abundance of Tregulatory, Thelper, Tcytotoxic cells and monocytes are significantly in late, and no recurrence samples compared to early recurrence samples. C_LIO_LIThe most differential expression profile that differentiates late and no recurrence samples from the early recurrence samples is related to the stem cell population. Particularly, we found overexpression of GLUT1, FLIP and downregulation of BAX, BAK, MLKL and CDX2 proteins in the cancer stem cell of early recurrence samples. C_LIO_LIWe built a neural network based on the cancer stem cell protein signature (BAX, MLKL, FLIP, GLUT1 and CDX2 proteins) that delivers a high-performance prognostic classifier. C_LI How this study might affect research, practice or policyO_LIOur results propose a clinically promising prognostic tool based on a five-protein stem cell signature that outperforms existing clinical and proposed transcriptomic based signatures for separation between risk groups. C_LIO_LIMoreover, our five-protein signature markers not only predict stem cell chemotherapy resistance and therefore tumour recurrence but also suggest potential therapeutic strategies. For instance, this approach could guide combinatorial treatments at high risk of chemoresistance, such as incorporating small molecule inhibitors targeting FLIP (currently in discovery phase) and GLUT1 (already under preclinical trial evaluation). C_LI

cancer biology↗

bioRxiv2025

Whole genome sequencing of pre-treatment and post-treatment locally advanced rectal cancer using long and short read technologies

We performed Illumina short-read and nanopore (ONT) whole genome sequencing (WGS) on samples obtained from a 37-year-old patient with locally advanced rectal cancer who did not respond to neoadjuvant chemoradiotherapy (nCRT). Pre-treatment and post-nCRT tumour biopsy, adjacent normal tissue, and matched pre-treatment blood samples were sequenced to identify somatic alterations. We used DNA methylation from ONT WGS to detect changes in the tumour epigenomes compared to adjacent normal tissue. We employed established pipelines for the identification of somatic alterations to assess the concordance of SNV, short indel, copy number and structural variation from the short-read and long-read tumour genome data. Overall, 69.4% and 30.1% SNVs were concordant between technologies in the pre- and post-treatment tumours, respectively. A multinomial logistic regression was performed to further understand discordant SNV calls, highlighting tumour purity, presence in a repetitive region, strand bias, and germline variant allele frequency as factors contributing to discordance. Indel concordance was poor (26.8% and 9.2% in the pre- and post-treatment tumour, respectively). Copy number alteration profiles were highly similar while minimal concordance was reported for structural variants (2.4% and 0.3% for pre- and post-treatment tumours, respectively). Finally, we used the ONT data to detect DNA modifications (5-methylcytosine and 5-hydroxymethylcytosine) between tumour and matched adjacent normal tissue. Based on genome-wide average CpG modification rates, global hypomethylation was observed in tumours compared to adjacent normal tissues. Biologically relevant epigenomic changes related to epithelial-mesenchymal transition were detected in the post-treatment tumour, as well as potential radiation-induced changes in the post-treatment adjacent normal tissue.

genomics↗

bioRxiv2025

State-dependent release of extracellular particles with distinct α2,6-sialylation patterns and small RNA cargo related to neuroinflammation

Neuroinflammation is a significant contributor to neurodegenerative diseases, including Alzheimers disease, Parkinsons disease, and related dementias; yet peripheral biomarkers for neuroinflammation remain an unmet medical need. Microglia, the resident immune cells of the central nervous system, play a dual role in maintaining homeostasis under physiological conditions and driving neuronal damage when chronically dysregulated. One mechanism by which microglia influence their environment is through the release of extracellular vesicles (EVs) and non-vesicular extracellular particles (NVEPs), which can serve as biomarkers the reflect cellular states. Here, we systematically isolated and characterized microglia-derived EVs and NVEPs under pro- and anti-inflammatory conditions and profiled their small RNA cargo by small RNA sequencing. We validated these findings in human iPSC-derived microglia and further recapitulated them in EVs and NVEPs from mouse brain and plasma. Using an engineered mouse model, we were able to isolate plasma microglia-specific EVs in vivo and demonstrated that their RNA cargo reflects their inflammatory state. Importantly, microglial EVs and NVEPs display distinct 2,6-sialylation patterns and small RNA signatures implicated in neurological diseases. These findings demonstrate that microglia-derived EVs and NVEPs cargo reflect microglial cellular state and establish them as putative minimally non-invasive biomarkers of early-stage neurodegenerative diseases.

neuroscience↗

bioRxiv2025

Exploring Size Exclusion Chromatography Columns 20 and 35 nm Pore Size Effect for Isolation of Extracellular Vesicles

Extracellular vesicles (EVs) have shown great promise as minimally invasive biomarkers for a variety of diseases. However, challenges persist regarding EV isolation, particularly in their co-isolation with impurities such as soluble proteins and lipoproteins. Among the methods available for EV isolation, size-exclusion chromatography (SEC) is widely used, as it is reproducible and amenable to high-throughput with a rapid turnaround time. However, its size-based separation leads to the co-isolation of EVs with impurities of similar size. This study, for the first time to our knowledge, compares SEC columns with different pore sizes, 20 and 35 nm, to evaluate their efficacy in non-EV contaminant removal and EV recovery from pancreatic EndoC-{beta}H1 cell culture media and human plasma. To assess EV purity and yield, we compare EV particle concentration, the presence of unintended co-isolates, and RNA EV cargo. This study demonstrates that smaller pore size SEC columns enhance EV yield and purity, making them ideal for biomarker studies involving limited biological samples or downstream analysis sensitive to contaminants.

biochemistry↗

bioRxiv2025

Multiplex analysis of colorectal cancer tissue describes the composition, cell biology and spatial effects of cell-in-cell events and identifies a T cell-dependent prognostic signature

Cell competition is an emerging mechanism in which mammalian tissues maintain homeostasis by eliminating less fit (loser) cells through direct interactions with fitter (winner) neighbouring cells. In cancer, these competitive interactions may drive tumour evolution; however, spatial organisation and clinical relevance of these events remain poorly understood. One mechanism by which winner cells eliminate loser cells is engulfment, resulting in cell-in-cell (CIC) formation. Although CICs have been observed in many tumour types for over a century, their cellular composition, spatial context, interactions with the tumour microenvironment, and biological significance in human cancers remain unclear. Here, we systematically characterised the cellular identity and functional states of CICs in situ, examined their spatial interactions within the tumour microenvironment, and assessed their clinical relevance using spatially resolved single-cell data from a large cohort of colorectal cancer patients. We demonstrate that CICs occur predominantly between cancer cells but also involve cancer stem cell (CSC)-like populations and cytotoxic T cells. Engulfed (inner) cancer and CSC-like cells display molecular features consistent with a loser-cell phenotype, including increased apoptosis and reduced proliferation, whereas outer cancer cells exhibit winner-cell features such as upregulated glycolysis. Live-cell time-lapse experiments demonstrate that glucose accumulates in inner cells during lysosomal degradation following cell engulfment. Spatial analysis further revealed distinct CIC neighbourhoods, which we defined based on proximity to engulfment events. Cells within these regions, particularly CSC-like cells and cytotoxic T cells, exhibit increased metabolic stress, suggesting local competition for nutrients. Importantly, the presence of cytotoxic T cells within CIC neighbourhoods and spatial co-occurrence patterns between cancer cells and CSC-like populations are associated with improved patient outcomes. Together, our findings demonstrate that cell engulfment defines spatially organised competitive niches and may reflect cell competition within complex tumour microenvironments.

cancer biology↗

bioRxiv2025

High-Resolution Spatial Proteomics Characterises Colorectal Cancer Consensus Molecular Subtypes

BackgroundIdentification of the consensus molecular subtypes (CMS) opened significant potential for understanding the tumor biology and intertumoral heterogeneity of colorectal cancer (CRC). However, molecular subtyping in CRC traditionally relies on bulk transcriptomics, therefore, lacks spatial and single-cell level aspect. MethodsWe constructed tissue microarrays using tumor cores from 222 CRC patients. Arrays were stained and imaged using 54 cell identity and cancer hallmark markers, delivering spatially resolved protein profiles of >2 million cells. RNA sequencing data and CMS classification were also available for these patients. After segmentation of cancer, stromal and immune cells, we investigated intratumoral heterogeneity within CMS subtypes using spatially resolved single-cell protein profiling (>2 million cells). We compared cell types, their spatial organization and their expression of cancer hallmark-related proteins in CMS 1-4 subtypes. ResultsWe revealed tissue atlases illustrating the cell types/states, spatial heterogeneity, cellular neighborhoods, cellular network, and single-cell protein profiles of CMS tumors. CMS1 tumors had more CD3+, CD8+, and PD1+ immune cells that were found in the epithelial layer frequently. CMS1 was also associated with higher levels of metabolic reprogramming markers such as upregulated glycolysis. CMS2 showed immune segregation, reactive stroma patterns and higher levels of apoptotic and proliferative signaling proteins. CMS3 exhibited clustered cancer cells with high RIP3 levels, suggesting a pro-inflammatory microenvironment. CMS4 displayed stromal-centric and immune-evasive tumors characterized by decreased HLA-1 levels and regulatory T-cell exclusion from epithelium. ConclusionWe present a spatial protein atlas of CRC at single-cell resolution and demonstrate novel aspects of CMS tumour structures.

cancer biology↗

bioRxiv2018

A polyploid admixed origin of beer yeasts derived from European and Asian wine populations

Strains of Saccharomyces cerevisiae used to make beer, bread and wine are genetically and phenotypically distinct from wild populations associated with trees. The origins of these domesticated populations are not always clear; human-associated migration and admixture with wild populations have had a strong impact on S. cerevisiae population structure. We examined the population genetic history of beer strains and find that ale strains and the S. cerevisiae portion of allotetraploid lager strains were derived from admixture between populations closely related to European grape wine strains and Asian rice wine strains. Similar to both lager and baking strains, ale strains are polyploid, providing them with a passive means of remaining isolated from other populations and providing us with a living relic of their ancestral hybridization. To reconstruct their polyploid origin we phased the genomes of two ale strains and found ale haplotypes to both be recombinants between European and Asian alleles and to also contain novel alleles derived from extinct or as yet uncharacterized populations. We conclude that modern beer strains are the product of a historical melting pot of fermentation technology.

evolutionary biology↗