Biology subjects

Bristow, R.

Publications and source records attributed to Bristow, R..

3 recordsLinked to original sources

bioRxiv2026

Whole-genome pre-amplification as a viable approach for genomic screening of FFPE-derived DNA samples

Whole-genome sequencing (WGS) enables comprehensive analysis of tumour genomes, but its use in formalin-fixed paraffin-embedded (FFPE) samples is limited by DNA fragmentation and low yields. Whole-genome amplification (WGA) methods such as multiple displacement amplification (MDA) can boost DNA availability but distort copy-number alteration (CNA) profiles. DNA ligation-mediated MDA (DLMDA) mitigates this bias by reconstituting fragmented templates, yet its performance in FFPE-derived DNA remains uncertain. We compared paired DLMDA pre-amplified (2h, 8h) and non-pre-amplified FFPE prostate tumour samples from 22 archival blocks (5, 15 and 20 years old). DLMDA increased DNA yield by 42- to 86-fold, with global CNA patterns largely preserved. However, DLMDA significantly reduced the number of detected CNA deletions and amplifications. These effects were independent of both block age and reaction time. CNA dropouts were randomly distributed across the genome, indicating that DLMDA does not introduce regional bias. Our results show that DLMDA enables robust DNA yield recovery and avoids false-positive CNA artefacts, but at the cost of reduced CNA sensitivity. While suitable for CNA screening pipelines through WGS, further improvements are required to minimise the false-negative risk and improve the techniques sensitivity for FFPE-based genomics.

molecular biology↗

bioRxiv2023

CellPie: a fast spatial transcriptomics topic discovery method via joint factorization of gene expression and imaging data

Spatially resolved transcriptomics has enabled the study of expression of genes within tissues while retaining their spatial identity. Most spatial transcriptomics technologies generate a matched histopathological image as part of the standard pipeline, providing morphological information that can complement the transcriptomics data. Here we present CellPie, a fast, unsupervised factor discovery method, based on joint non-negative matrix factorisation of spatial RNA transcripts and histological image features.CellPie employs the accelerated hierarchical least squares method to significantly reduce the computational time, enabling efficient application to high-dimensional spatial transcriptomics datasets. We assessed CellPie on two different human cancer types and spatial resolutions, showing an improved performance against published factorisation methods. Additionally, we applied CellPie to a highly resolved Visium HD dataset, demonstrating its high computational efficiency compared to standard non-negative matrix factorisation and other existing methods. Availabilityhttps://github.com/ManchesterBioinference/CellPie

bioinformatics↗

bioRxiv2018

Integrated Genomic Analysis of Hypoxia Genes across Cancer Types Identifies Significant Associations with Cancer Hallmarks

Hypoxia is a generic micro-environmental factor in most solid tumours. While most published literature focused on in vitro or single tumour type investigations, we carried out the first multi-omics pan cancer analysis of hypoxia with the aim of gaining a comprehensive understanding of its implication in tumour biology. A core set of 52 mRNAs were curated based on experimentally validated hypoxia gene sets from multiple cancer types. The 52 mRNAs collectively stratified high- and low-hypoxia tumours from The Cancer Genome Atlas (TCGA) database (9698 primary tumours) in each of the 32 cancer types available. High- hypoxia tumours had high expression of not only mRNA but also protein and microRNA markers of hypoxia. In a pan cancer transcriptomic analysis, [≥]70% of the known cancer hallmark pathways were enriched in high-hypoxia tumours, most notably epithelial mesenchymal transition potential, proliferation (G2M checkpoint, E2F targets, MYC targets) and immunology response. In a multi-omics analysis, gene expression-determined high- hypoxia tumours had a higher non-silent mutation rate, DNA damage repair deficiency and leukocyte infiltration. The associations largely remained significant after correcting for confounding factors, showing a profound impact of hypoxia in tumour evolution across cancer types. High-hypoxia tumours determined using the core gene set had a poor prognosis in 16/32 cancer types, with statistical significances remaining in five after adjusting for tumour stage and omics biomarkers. In summary, this first comprehensive in vivo map of hypoxia in cancers highlights the importance of this micro-environmental factor in driving tumour progression.

cancer biology↗