Biology subjects

Verrill, C.

Publications and source records attributed to Verrill, C..

10 recordsLinked to original sources

bioRxiv2026

Scalable spatial DNA sequencing from archival tissue maps copy number subclones

Spatially resolved DNA sequencing holds promise due to its potential utility in understanding cancer intra-tumour heterogeneity and tumour evolution in relation to tissue architecture. However, it has so far been used to a limited extent due to technical challenges and high cost of existing methods. Hence we aimed to develop a high throughput spatial genomic assay to obtain copy number alteration (CNA) information at user-defined spatial resolution. We derived CNA profiles from ultra-low coverage whole genome sequencing at sub-millimetre resolution from archival samples using a novel method called Adaptive Resolution Multiscale Spatial DNA sequencing (ARMS DNAseq). We used it to profile CNAs from more than 766 regions (tiles) from 3 patients, covering a total area of over 300 mm2, with 1.2-2.6 million mapped reads per tile and tile sizes of 0.1-0.99mm2. Using ARMS DNAseq, we delineate tumour evolution in a spatial context, and identify more tumour subclones that were obscured or incompletely represented in bulk multi-region whole genome sequencing. Next, we show associations between tumour subclones and morphology, and prediction of subclone identity from deep learning-derived image representations. Finally, we demonstrate multi-omic integration by alignment with spatial transcriptomic data, showing subclone-specific immune cell co-occurrence as well as transcriptional programmes cutting across subclone boundaries. ARMS DNAseq converts low-throughput, region-by-region profiling into a scalable and adaptable workflow for direct spatial copy number profiling from archival tissue sections.

genomics↗

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↗

bioRxiv2024

IGFs regulate cancer cell immune evasion in prostate cancer

Insulin-like growth factor-1 (IGF-1) promotes prostate cancer (PCa) development and lethality, with immunosuppressive properties in other disease models. These studies investigated the tumor-intrinsic immune effects of IGF-1 in PCa to understand mechanisms underlying its poor immunotherapy response. Transcriptional profiling of human (DU145, 22Rv1) and murine (Myc-CaP) PCa cells revealed, through pathway enrichment, that cytokine signalling, antigen processing and presentation, and other immune regulatory pathways, were most suppressed by IGF-1. We went on to investigate changes in the expression of components of two key pathways responsible for cancer cell recognition by immune cells and immune evasion: antigen processing and presentation, and PD-L1 checkpoint expression. These pathways are crucial for determining immunotherapy response. IGF-1 downregulated transporters associated with antigen processing (TAPs), endoplasmic reticulum aminopeptidase-1 (ERAP-1), and Class I component {beta}2-microglobulin, without major changes in Class I allele expression. These effects were associated with reduced presentation of Class I complexes on the Myc-CaP cell surface suggesting altered peptide transport, processing, and/or presentation. In contrast, IGF-1 upregulated immune checkpoint CD274 (PD-L1) via IGF receptor/AKT/ERK-dependent signaling. Analysis of public data (TCGA Firehose Legacy PCa) revealed increased CD274 expression in PCa with high endogenous IGF1 and IGFBP5, markers of high IGF axis activity. Additionally, in primary PCa (n=32), multiplex immunofluorescence revealed higher PD-L1 expression in the central tumor of men with high serum IGF-1 promoting cancer cell immune evasion in PCa. These findings indicate a novel mechanism by which IGF-1 mediates immunosuppressive effects in malignant prostate epithelium, potentially explaining the poor responsiveness of PCa to immunotherapy and highlighting the complex interplay between IGF signaling and immune evasion.

cancer biology↗

bioRxiv2023

Molecular analysis of archival diagnostic prostate cancer biopsies identifies genomic similarities in cases with progression post-radiotherapy, and those with de novo metastatic disease.

PurposeIt is important to identify molecular features that improve prostate cancer (PCa) risk stratification before radical treatment with curative intent. Molecular analysis of historical diagnostic formalin-fixed paraffin-embedded (FFPE) prostate biopsies from cohorts with post-radiotherapy (RT) long-term clinical follow-up has been limited. Utilizing parallel sequencing modalities, we performed a proof-of-principle sequencing analysis of historical diagnostic FFPE prostate biopsies. We compared patients with i) stable PCa post-primary or salvage RT (sPCa), ii) progressing PCa post-RT (pPCa), and iii) de novo metastatic PCa (mPCa). Experimental DesignA cohort of 19 patients with diagnostic prostate biopsies (n=6 sPCa, n=5 pPCa, n=8 mPCa) and mean 4 years 10 months follow-up (diagnosed 2009-2016) underwent nucleic acid extraction from demarcated malignancy. Samples underwent 3RNA sequencing (3RNAseq) (n=19), nanoString analysis (n=12) and Illumina 850k methylation (n=8) sequencing. Bioinformatic analysis was performed to coherently identify differentially expressed genes (DEGs) and methylated genomic regions (MGRs). Results18 of 19 samples provided useable 3RNAseq data. Principal Component Analysis (PCA) demonstrated similar expression profiles between pPCa and mPCa cases, versus sPCa. Coherently differentially methylated probes between these groups identified [~]600 differentially MGRs. The top 50 genes with increased expression in pPCa patients were associated with reduced progression-free survival post-RT (p<0.0001) in an external cohort. Conclusions3RNAseq, nanoString and 850K-methylation analyses are each achievable from historical FFPE diagnostic pre-treatment prostate biopsies, unlocking the potential to utilize large cohorts of historic clinical samples. Profiling similarities between individuals with pPCa and mPCa suggests biological similarities and historical radiological staging limitations, which warrant further investigation.

genomics↗

bioRxiv2023

Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of heterogeneity on genomic signature scoring

Genetic signatures have added a molecular dimension to prognostics and therapeutic decision-making. However, tumour heterogeneity in prostate cancer and current sampling methods could confound accurate assessment. Based on previously published spatial transcriptomic data from multifocal prostate cancer, we created virtual biopsy models that mimic conventional biopsy placement and core size. We then analysed the gene expression of different prognostic signatures (OncotypeDx(R), Decipher(R), Prostadiag(R)) using a step-wise approach increasing resolution from pseudo-bulk analysis of the whole biopsy, to differentiation by tissue subtype (benign, stroma, tumour), followed by distinct tumour grade and finally clonal resolution. The gene expression profile of virtual tumour biopsies revealed clear differences between grade groups and tumour clones, compared to a benign control, which were not reflected in bulk analyses. This suggests that bulk analyses of whole biopsies or tumour-only areas, as used in clinical practice, may provide an inaccurate assessment of gene profiles. The type of tissue, the grade of the tumour and the clonal composition all influence the gene expression in a biopsy. Clinical decision making based on biopsy genomics should be made with caution while we await more precise targeting and cost-effective spatial analyses. Patient summaryProstate cancers are very variable, including within a single tumour. Current genetic scoring systems, which are sometimes used to make decisions for how to treat patients with prostate cancer, are based on sampling methods which do not reflect these variations. We found, using state-of-the-art spatial genetic technology to simulate accurate assessment of variation in biopsies, that the current approaches miss important details which could negatively impact clinical decisions. Take home messageVirtual biopsies from spatial transcriptomic analysis of a whole prostate reveal that current genomic risk scores potentially deliver misleading results as they are based on bulk analysis of prostate biopsies and ignore tumour heterogeneity.

genomics↗

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↗

bioRxiv2020

TET2 drives 5hmc marking of GATA6 and epigenetically defines pancreatic ductal adenocarcinoma transcriptional subtypes

Background and AimsPancreatic ductal adenocarcinoma (PDAC) is characterised by advanced disease stage at presentation, aggressive disease biology and resistance to therapy resulting in extremely poor five-year survival <10%. PDAC is classified into transcriptional subtypes with distinct survival characteristics, although how these arise is not known. Epigenetic deregulation, rather than genetics, has been proposed to underpin progression but exactly why is unclear and hindered by analysis of clinical samples. MethodsGenome-wide epigenetic mapping of DNA modifications 5-hydroxymethylcytosine (5mc) and 5-hydroxymethylcytosine (5hmc) using oxidative bisulphite sequencing (oxBS). Bioinformatics using iCluster and mutational profiling to identify overlap with transcriptional signatures in FFPE from resected patients and confirmation in vivo. ResultsWe find that more aggressive squamous-like PDAC subtypes result from epigenetic inactivation of loci including GATA6 that promote differentiated classical-pancreatic subtypes. We show that squamous-like PDAC transcriptional subtypes are associated with greater loss of 5hmc due to reduced expression of the 5mc-hydroxylase TET2. Furthermore, we find that SMAD4 directly supports TET2 levels in the pancreas and classical-pancreatic tumors and loss of SMAD4 expression is associated reduced 5hmc, GATA6 and squamous-like tumors. Importantly, enhancing TET2 stability using Metformin and VitaminC/ascorbic acid (AA) restores 5hmc and GATA6 levels, reverting squamous-like tumor phenotypes and WNT-dependence in vitro and in vivo. ConclusionsWe identify epigenetic deregulation of pancreatic differentiation as an underpinning event behind the emergence of transcriptomic subtypes in PDAC. Our data shows that restoring epigenetic control increases biomarkers of classical-pancreatic tumors and raises the possibility that combination of Vitamin C and Metformin may prolong survival in patients with squamous-like pancreatic cancer.

cancer biology↗

bioRxiv2020

Anti-androgens induce Rab11a-exosome secretion in prostate cancer by suppressing amino acid-sensitive PAT4-mTORC1 signalling

Advanced prostate cancer is typically treated with anti-androgens to reduce cancer growth, but patients almost inevitably develop treatment resistance and castration-resistant disease. Recently, extracellular vesicles known as exosomes, which are secreted from the endosomal compartments in which they are formed, have been implicated in drug resistance mechanisms. Here we investigate whether growth regulation by the amino acid-dependent kinase complex, mechanistic Target of Rapamycin Complex 1 (mTORC1), and associated extracellular vesicle secretion might be involved in the adaptive responses to anti-androgens. We show that expression and intracellular localisation of the glutamine-sensing PAT4 (SLC36A4) amino acid transporter is increased in malignant versus benign prostatic tissue, mirroring earlier in vivo fly studies suggesting that these transporters are more effective at promoting growth from internal versus cell surface membranes. Furthermore, androgens induce PAT4 expression in prostate cancer cell lines and PAT4 is required for a proportion of androgen-stimulated mTORC1 activation and growth. Consistent with previous studies in other cancer cell lines, we find that glutamine depletion, PAT4 knockdown and mTORC1 inhibition all independently increase the production of a specific exosome subtype, Rab11a-exosomes, which has recently been implicated in pro-tumorigenic signalling responses to mTORC1 inhibition. Furthermore, we show that these exosomes are also induced by anti-androgens. We hypothesise that the uptake of Rab11a-exosomes by cells with higher PAT4 levels could provide a growth-promoting boost, enabling them to out-compete others with lower PAT4 expression, resulting in tumours that are more resistant to nutrient-deprivation and anti-androgen treatment.

cancer biology↗

bioRxiv2019

Low basal expression and slow induction of IFITM3 puts immune cells at risk of influenza A infection

The interferon-induced transmembrane protein, IFITM3, has been shown to restrict influenza virus infection in murine and in vitro settings for ten years, but no explanation has been found to explain why this virus infection is so highly contagious and infects most individuals it comes in contact with. We confirm that the expression level of IFITM3 plays a role in determining the level of viral infection through manipulation of IFITM3 levels with interferon (IFN) stimulation and overexpression systems. Low basal expression may put some immune cells, including lymphocytes and lung-resident macrophages, at risk of influenza virus infection. Investigating the induction of IFITM3 by IFN, we find a strong preference for Type I IFN in IFITM3 induction in both cell lines and primary human cells. While myeloid cells can increase expression following stimulation by Type I IFN, lymphocytes show minimal induction of IFITM3 following IFN stimulation, suggesting that they are always at risk of viral infection. Surprisingly, we found that the time it takes for maximal induction of IFITM3 is relatively slow for an interferon-stimulated gene at around 36 hours. Low basal expression and slow induction of IFITM3 could increase the risk of influenza virus infection in selected immune cells. ImportanceInfluenza virus infection remains one of the top ten threats to global health, causing significant deaths and hospitalisations across the world each year. Understanding mechanisms for controlling influenza virus infection remain a priority. The interferon-induced transmembrane protein IFITM3 can restrict influenza infection by limiting replication of the virus. The precise mechanisms of how IFITM3 reduced replication of influenza are unknown, although it is predicted to prevent release of viral contents into the cytosol by preventing pore formation on the endosomal compartments where it is suggested to reside. Here we have shown that the expression level of IFITM3 is important in determining the control of influenza virus infection. We find an expression pattern for IFITM3 that varies based on cell type, tissue locality, differentiation state and cell naivety, all of which highlights cells that may be at the highest risk of influenza infection.

immunology↗

bioRxiv2019

Image-based consensus molecular subtype classification (imCMS) of colorectal cancer using deep learning

Image analysis is a cost-effective tool to associate complex features of tissue organisation with molecular and outcome data. Here we predict consensus molecular subtypes (CMS) of colorectal cancer (CRC) from standard H&E sections using deep learning. Domain adversarial training of a neural classification network was performed using 1,553 tissue sections with comprehensive multi- omic data from three independent datasets. Image-based consensus molecular subtyping (imCMS) accurately classified CRC whole-slide images and preoperative biopsies, spatially resolved intratumoural heterogeneity and provided accurate secondary calls with higher discriminatory power than bioinformatic prediction. In all three cohorts imCMS established sensible classification in CMS unclassified samples, reproduced expected correlations with (epi)genomic alterations and effectively stratified patients into prognostic subgroups. Leveraging artificial intelligence for the development of novel biomarkers extracted from histological slides with molecular and biological interpretability has remarkable potential for clinical translation.

cancer biology↗