Biology subjects

Wedge, D. C.

Publications and source records attributed to Wedge, D. C..

At least 19 recordsLinked to original sources

bioRxiv2026

Novel Methylation Markers in a Prostate Cancer Cohort are Associated with Disease Development and Relapse

Prostate cancer remains one of the most common cancers among men globally. While significant strides have been made in diagnosis and treatment, understanding the complex genetic and epigenetic underpinnings of the disease remains crucial for guiding intervention and developing more personalized and effective therapies. The importance of DNA methylation in prostate cancer has been known for some time, but important facets of the modulation of the epigenome during carcinogenesis remain obscure, partly because the bulk of cancer methylation data have been produced using microarray technologies. Here we utilise the TruSeq methyl capture method (EPICseq) to profile the, previously defined, UK Prostate ICGC cohort of well-annotated primary prostate cancers. To this we add methylation sequencing of benign tissue from the same men. These data allow us to identify differentially methylated regions distinguishing cancerous and non-cancerous prostate tissue, while identifying numerous genes whose methylation profiles can perform that task as well as distinguishing between classes of prostate cancer. We describe a describe a methylation-based control mechanism for prostate-cancer-associated SNPs, and show that this seems a likely mechanism of action for a SNP near the MMP7 gene. We describe three novel molecular signatures that arise from different aspects of the biology of prostate cancer revealed by sequencing. Each is shown to be an independent classifier of cancers into groups with different expected times to relapse. These consist of patterns in driver gene methylation, strand-specific methylation, and signal arising in mitochondrial reads. We show that these signatures, combined with existing molecular tools, provide a powerful predictor of time to recurrence. By substantially enhancing understanding of prostate cancer risk, detection, and prognosis, we pave the way for the development of clinical practices that will benefit patients and improve outcomes.

cancer biology↗

bioRxiv2026

Replication fork directionality reveals how structural variants arise under replication stress

Structural variants (SVs) in cancer are associated with defects in DNA repair and replication stress, but the mechanisms generating common SV types remain unresolved. We propose that large (>100 kb) tandem duplications originate through a novel sister-fork breakage-fusion mechanism. To capture replication-related context beyond breakpoints, we developed an algorithm to characterize replication timing, origin density, and fork direction across SV-spanned regions, features that refine and differentiate previously defined SV signatures. Large tandem duplications frequently overlap replication origins from which forks proceed bidirectionally; combined with independent evidence from APOBEC strand asymmetry, this pattern is compatible uniquely with the proposed mechanism. Although tandem duplications in CCNE1-amplified and CDK12-mutant cancers also concentrate around origins and highly transcribed genes, they display distinct contexts: CDK12-mutant SVs arise near later-firing origins, whereas those in CCNE1-amplified tumors often coincide with genes in specific strand configurations, suggesting different causes of fork stalling. Incorporating replication features into signature analysis enabled the discovery of new SV signatures, which we used to build SVIG, a multi-class classifier of SV phenotypes. SV signatures attributed to replication stress may help guide therapies targeting this vulnerability.

bioinformatics↗

bioRxiv2026

Whole genome sequencing of endometrial cancer identifies novel subgroups, drivers, and actionable alterations

Endometrial cancer (EC) is the most common gynaecological malignancy in high income countries, and is increasing in incidence. While molecular stratification has improved its management, precision care is hampered by incomplete characterization of the EC genome. We address this by analysis of whole genome sequencing (WGS) of 665 ECs generated by the UK Genomics England 100,000 Genome Project (100kGP). 5% of cases were associated with germline pathogenic variants in cancer genes, including BRCA1 which we confirmed predisposes to EC. We identified 107 putative coding driver genes, 35% of which had no prior established role in EC. Novel structural variants included gains of MYCN and loss of its negative regulator NEDD4.1 which were significantly mutually exclusive in copy number (CN) high tumours. Immunogenomic analysis confirmed selection for driver alterations of low immunogenicity based on patient HLA haplotype, and pervasive immune escape through multiple mechanisms. Unsupervised clustering of mutational signatures and genomic alterations identified known and novel molecular subgroups, including a CN-high subset with mutational signatures of homologous recombination deficiency (HRD) and favourable outcome. Independent prognostic value of single nucleotide variant (SNV) burden, CN burden and multiple coding drivers, along with the identification of targetable molecular alterations in over one-third of cases, underscores the promise of WGS for precision medicine in EC.

genomics↗

bioRxiv2026

Proteomics-constrained deconvolution reveals spatial cell-type programs in tumours

Accurately resolving cell-type mixtures in spatial transcriptomics remains challenging, particularly in heterogeneous tumours where cell populations are intermixed and matched single-cell references may be unavailable or poorly aligned. Current deconvolution approaches either require high-quality scRNA-seq references, suffer from scalability limitations, or lack interpretability. We introduce PISTACHIO, a proteomics-informed spatial transcriptomics deconvolution framework based on constrained non-negative matrix factorization with a negative-binomial likelihood. Rather than using probabilistic priors, PISTACHIO incorporates spatial cell-type constraints derived from paired Imaging Mass Cytometry, enforcing biologically grounded sparsity and explicit spatial feasibility of cell-type presence. PISTACHIO improved recovery of spatial cell-type distributions compared with Cell2location and STdeconvolve across synthetic and real tumour datasets. Our approach remains robust under cell-type assignment errors, maintaining high correlation with ground-truth under moderate noise, and achieves fast runtime on standard hardware, enabling practical large-scale deployment.

bioinformatics↗

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↗

bioRxiv2025

Identification and Validation of a Previously Missed Mutational Signature in Colorectal Cancer

Mutational signature analysis has greatly enhanced our understanding of the mutagenic processes found in cancer and normal tissues. As part of a recent study, we analyzed 802 treatment-naive, microsatellite-stable colorectal cancers (CRC) and identified a de novo signature, SBS_D, which was conservatively decomposed into SBS18, a signature associated with reactive oxygen species. Here, we re-evaluate this decomposition and provide evidence that SBS_D represents a distinct mutational process from that of SBS18. Through an independent analysis of 2,616 whole-genome sequenced microsatellite-stable CRCs across three distinct cohorts, we demonstrate that SBS_D is consistently present at a similar prevalence, suggesting that this signature may have been previously overlooked. Using a naive decomposition approach, we demonstrate that the pattern of SBS_D better aligns with signatures previously associated with deficiencies in DNA polymerase delta (POLD1) proofreading and mismatch repair. However, multiple lines of evidence, including the absence of pathogenic mutations in the exonuclease domain of POLD1 or in mismatch repair-associated genes, indicate that SBS_D is not driven by canonical defects in these DNA repair pathways. Overall, this study identifies a previously unrecognized mutational signature in microsatellite-stable CRC and proposes that its etiology may be linked to DNA repair infidelity emerging late in tumor development in samples without canonical defects in DNA repair pathways.

cancer biology↗

bioRxiv2025

Examining the Role of Extrachromosomal DNA in 1,216 Lung Cancers

The role of extrachromosomal DNA (ecDNA) in lung cancer, particularly in subjects who never smoked (LCINS), remains unclear. Examination of over 1200 whole-genome-sequenced lung cancers identified ecDNA in 18.9% of patients. Recurrent amplification of MDM2 and other oncogenes via ecDNA possibly drives a LCINS subset. Tumors harboring ecDNA showed worse overall survival than tumors harboring other focal amplifications. A strong association with whole-genome doubling suggests most ecDNA reflects genomic instability in treatment-naive lung cancer.

bioinformatics↗

bioRxiv2025

A fast numerical integration scheme for clonal expansion processes on graphs

Compound birth-death processes are widely used to model the age-incidence curves of many cancers [1]. There are efficient schemes for directly computing the relevant probability distributions in the context of linear multi-stage clonal expansion (MSCE) models [2]. However, these schemes have not been generalised to models on arbitrary graphs, forcing the use of either full stochastic simulations or mean-field approximations, which can become inaccurate at late times or old ages [3, 4]. Here, we present a numerical integration scheme for directly computing survival probabilities of a first-order birth-death process on an arbitrary directed graph, without the use of stochastic simulations. As a concrete application, we show that this new numerical method can be used to infer the parameters of an example graphical model from simulated data.

cancer biology↗

bioRxiv2023

Chromothripsis orchestrates leukemic transformation in blast phase MPN through targetable amplification of DYRK1A

Chromothripsis, the process of catastrophic shattering and haphazard repair of chromosomes, is a common event in cancer. Whether chromothripsis might constitute an actionable molecular event amenable to therapeutic targeting remains an open question. We describe recurrent chromothripsis of chromosome 21 in a subset of patients in blast phase of a myeloproliferative neoplasm (BP-MPN), which alongside other structural variants leads to amplification of a region of chromosome 21 in [~]25% of patients ( chr21amp). We report that chr21amp BP-MPN has a particularly aggressive and treatment-resistant phenotype. The chr21amp event is highly clonal and present throughout the hematopoietic hierarchy. DYRK1A, a serine threonine kinase and transcription factor, is the only gene in the 2.7Mb minimally amplified region which showed both increased expression and chromatin accessibility compared to non-chr21amp BP-MPN controls. We demonstrate that DYRK1A is a central node at the nexus of multiple cellular functions critical for BP-MPN development, including DNA repair, STAT signalling and BCL2 overexpression. DYRK1A is essential for BP-MPN cell proliferation in vitro and in vivo, and DYRK1A inhibition synergises with BCL2 targeting to induce BP-MPN cell apoptosis. Collectively, these findings define the chr21amp event as a prognostic biomarker in BP-MPN and link chromothripsis to a druggable target.

cancer biology↗

bioRxiv2023

Intra-prostatic tumour evolution, steps in metastatic spread and histogenomic associations revealed by integration of multi-region whole genome sequencing with histopathological features

Extension of prostate cancer beyond the primary site into the surrounding organs by local invasion or nodal metastasis is associated with poor prognosis. The emergence and evolution of cancer clones at this early stage of expansion and spread has not been studied in detail. We performed whole genome sequencing on 42 prostate cancer samples from the prostate, seminal vesicles and regional lymph nodes of five treatment-naive patients with locally advanced disease who underwent radical prostatectomy. Using cancer cell fractions computed from single nucleotide variants and copy number alterations, we reconstructed the tumour phylogenies, which in turn allowed us to infer key molecular steps in the progression of prostate cancer in these individuals. We mapped the clonal composition of cancer sampled across the prostate in each individual and inferred the routes of spread of cancer cells within the prostate and to seminal vesicles and lymph nodes. Based on these data, we delineated the route of tumour progression and metastasis following the transformation of adenocarcinoma to amphicrine morphology, the molecular events leading to whole genome duplication associated with a single clonal expansion and identified putative driver events associated with local invasion and lymph node metastasis. We also correlated genomic changes associated with differences in morphology and identified putative driver events associated with spread to seminal vesicle invasion and lymph node metastasis. Taken together, these findings have implications for diagnosis and risk stratification, in addition to providing a rationale for further studies to characterise the genetic changes associated with morphological transformation. Our results demonstrate the value of integrating multi-region sequencing with histopathological data to study tumour evolution and identify mechanisms of prostate cancer spread.

cancer biology↗

bioRxiv2022

Crowd-sourced benchmarking of single-sample tumour subclonal reconstruction

Tumours are dynamically evolving populations of cells. Subclonal reconstruction algorithms use bulk DNA sequencing data to quantify parameters of tumour evolution, allowing assessment of how cancers initiate, progress and respond to selective pressures. A plethora of subclonal reconstruction algorithms have been created, but their relative performance across the varying biological and technical features of real-world cancer genomic data is unclear. We therefore launched the ICGC-TCGA DREAM Somatic Mutation Calling -- Tumour Heterogeneity and Evolution Challenge. This seven-year community effort used cloud-computing to benchmark 31 containerized subclonal reconstruction algorithms on 51 simulated tumours. Each algorithm was scored for accuracy on seven independent tasks, leading to 12,061 total runs. Algorithm choice influenced performance significantly more than tumour features, but purity-adjusted read-depth, copy number state and read mappability were associated with performance of most algorithms on most tasks. No single algorithm was a top performer for all seven tasks and existing ensemble strategies were surprisingly unable to outperform the best individual methods, highlighting a key research need. All containerized methods, evaluation code and datasets are available to support further assessment of the determinants of subclonal reconstruction accuracy and development of improved methods to understand tumour evolution.

bioinformatics↗

bioRxiv2022

Clonal diversification and histogenesis of malignant germ cell tumours

Germ cell tumours (GCTs) are a collection of benign and malignant neoplasms derived from primordial germ cells. They are uniquely able to recapitulate embryonic and extraembryonic tissues, which carries prognostic and therapeutic significance. The developmental pathways underpinning GCT initiation and histogenesis are incompletely understood. Here, we studied the relationship of histogenesis and clonal diversification in GCTs by analysing the genome and transcriptome of 547 microdissected histological units. We found that the extensive diversification of tissues and genetic subclones were not correlated. However, we identified unifying features including the retention of fetal developmental transcripts across tissues, expression changes on chromosome 12p, and a conserved somatic evolutionary sequence of whole genome duplication followed by clonal diversification. Whilst this pattern was preserved across all GCTs, the developmental timing of the duplication varied between prepubertal and postpubertal cases. In addition, tumours of younger children exhibited distinct substitution signatures, including a novel one, which may lend themselves as potential biomarkers for risk stratification. Our findings portray the extensive diversification of GCT tissues and genetic subclones as randomly distributed, whilst identifying overarching tissue and tumour transcriptional and genomic features.

cancer biology↗

bioRxiv2021

Benchmarking small-variant genotyping in polyploids

Genotyping from sequencing is the basis of emerging strategies in the molecular breeding of polyploid plants. However, compared with the situation for diploids, where genotyping accuracies are confidently determined with comprehensive benchmarks, polyploids have been neglected; there are no benchmarks measuring genotyping error rates for small variants using real sequencing reads. We previously introduced a variant calling method - Octopus - that accurately calls germline variants in diploids and somatic mutations in tumors. Here, we evaluate Octopus and other popular tools on whole-genome tetraploid and hexaploid datasets created using in silico mixtures of diploid Genome In a Bottle samples. We find that genotyping errors are abundant for typical sequencing depths, but that Octopus makes 25% fewer errors than other methods on average. We supplement our benchmarks with concordance analysis in real autotriploid banana datasets.

bioinformatics↗

bioRxiv2020

Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor

Mutational signature analysis is commonly performed in genomic studies surveying cancer and normal somatic tissues. Here we present SigProfilerExtractor, an automated tool for accurate de novo extraction of mutational signatures for all types of somatic mutations. Benchmarking with a total of 34 distinct scenarios encompassing 2,500 simulated signatures operative in more than 60,000 unique synthetic genomes and 20,000 synthetic exomes demonstrates that SigProfilerExtractor outperforms thirteen other tools across all datasets with and without noise. For genome simulations with 5% noise, reflecting high-quality genomic datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true positive signatures while yielding more than 5-fold less false positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome sequenced and 19,184 whole-exome sequenced cancers reveals four previously missed mutational signatures. Two of the signatures are confirmed in independent cohorts with one of these signatures associating with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting mutational signatures, and several novel mutational signatures including a signature putatively attributed to direct tobacco smoking mutagenesis in bladder cancer and in normal bladder epithelium.

bioinformatics↗

bioRxiv2020

Whole-genome analysis of Nigerian patients with breast cancer reveals ethnic-driven somatic evolution and distinct genomic subtypes

Black women of African ancestry experience more aggressive breast cancer with higher mortality rates than White women of European ancestry. Although inter-ethnic germline variation is known, differential somatic evolution has not been investigated in detail. Analysis of deep whole genomes of 97 breast tumors, with RNA-seq in a subset, from indigenous African patients in Nigeria in comparison to The Cancer Genome Atlas (n=76) revealed a higher rate of genomic instability and increased intra-tumoral heterogeneity as well as a unique genomic subtype defined by early clonal GATA3 mutations and a 10.5-year younger age at diagnosis. We also found evidence for non-coding mutations in two novel drivers (ZNF217 and SYPL1) and a novel INDEL signature strongly associated with African ancestry proportion. This comprehensive analysis of an understudied population underscores the need to incorporate diversity of genomes as a key parameter in fundamental research with potential to tailor clinical intervention and promote equity in precision oncology care.

genomics↗

bioRxiv2020

Genomic copy number predicts oesophageal cancer years before transformation

Cancer arises through a process of somatic evolution and recent studies have shown that aneuploidies and driver gene mutations precede cancer diagnosis by several years to decades1-4 Here, we address the question whether such genomic signals can be used for early detection and pre-emptive cancer treatment. To this end we study Barretts oesophagus, a genomic copy number driven neoplastic precursor lesion to oesophageal adenocarcinoma5. We use shallow whole genome sequencing of 777 biopsies sampled from 88 patients in surveillance for Barretts oesophagus over a period of up to 15 years. These data show that genomic signals exist that distinguish progressive from stable disease with an AUC of 0.87 and a sensitivity of 50% even ten years prior to histopathological disease transformation. These finding are validated on two independent cohorts of 75 and 248 patients. Compared against current patient management guidelines genomic risk classification enables earlier treatment for high risk patients as well as reduction of unnecessary treatment and monitoring for patients who are unlikely to develop cancer.

genomics↗

bioRxiv2019

Multi-site clonality analyses uncovers pervasive subclonal heterogeneity and branching evolution across melanoma metastases

Metastatic melanoma carries a poor prognosis despite modern systemic therapies. Understanding the evolution of the disease could help inform patient management. Through whole-genome sequencing of 13 melanoma metastases sampled at autopsy from a treatment naive patient and by leveraging the analytical power of multi-sample analyses, we reveal that metastatic cells may depart the primary tumour very early in the disease course and follow a branched pattern of evolution. Truncal UV-induced mutations that often swamp downstream analyses of heterogeneity, were found to be replaced by APOBEC-associated mutations in the branches of the evolutionary tree. Multi-sample analyses from a further 7 patients confirmed that branched evolution was pervasive, representing an important mode of melanoma dissemination. Our analyses illustrate that combining cancer cell fraction estimates across multiple metastases provides higher resolution phylogenetic reconstructions relative to single sample analyses and highlights the limitations of accurately inferring inter-tumoural heterogeneity from a single biopsy.

genomics↗

bioRxiv2019

Correcting reference bias from the Illumina Isaac aligner enables analysis of cancer genomes

Estimating the fraction of cancer cells with individual somatic mutations is central to many analyses in cancer genomics, including characterisation of clonal architecture and timing of mutational events. Estimation of these cancer cell fractions (CCFs) is contingent on unbiased assessment of the fraction of reads supporting variant alleles (VAFs). We demonstrate that VAFs computed by the Illumina Isaac pipeline, used in many large-scale sequencing projects including The 100,000 Genomes Project, are biased by the preferential soft clipping of reads supporting non-reference alleles (semi-aligned reads). We show that these biased VAFs can have deleterious effects on downstream analyses reliant on unbiased CCF estimates. While Isaac bias can be corrected through realignment with alternative parameters, this is computationally intensive. We therefore developed FixVAF, a tool for removing bias introduced by soft clipping of semi-aligned reads, facilitating downstream analyses without the need for realignment. FixVAF is freely available at https://github.com/danchubb/FixVAF.\n\nContactalex.cornish@icr.ac.uk or daniel.chubb@icr.ac.uk.

bioinformatics↗