---
title: "ARMS DNAseq: scalable spatial DNA sequencing for mapping copy-number subclones in archival tissue"
id: "biorxiv-17-scalable-spatial-dna-sequencing-from-archival-tissue-maps-copy-number-subclones"
canonical_url: "https://medichelpline.com/clinical-feed/biorxiv-17-scalable-spatial-dna-sequencing-from-archival-tissue-maps-copy-number-subclones"
content_type: "clinical_feed_article"
specialty: "Oncology"
source_name: "bioRxiv (Biomedical Preprints)"
source_url: "https://www.biorxiv.org/content/10.64898/2026.08.24.746226v1?rss=1"
published_at: "2026-08-27T12:00:00.000Z"
evidence_level: "Verified Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# ARMS DNAseq: scalable spatial DNA sequencing for mapping copy-number subclones in archival tissue
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/biorxiv-17-scalable-spatial-dna-sequencing-from-archival-tissue-maps-copy-number-subclones
- **Specialty:** [Oncology](https://medichelpline.com/clinical-feed/oncology.md)
- **Primary Source:** bioRxiv (Biomedical Preprints)
- **Source URL:** [Original Journal Publication](https://www.biorxiv.org/content/10.64898/2026.08.24.746226v1?rss=1)
- **Published At:** 2026-08-27T12:00:00.000Z
- **Evidence Rating:** Verified Feed
## Executive GIST (TL;DR)
- The authors developed Adaptive Resolution Multiscale Spatial DNA sequencing (**ARMS DNAseq**), a scalable assay for spatially resolved DNA sequencing from archival tissue sections to profile **copy number alterations (CNAs)**. - ARMS DNAseq derives CNA profiles from ultra-low coverage whole genome sequencing at sub-millimetre, user-defined spatial resolution. - The method was applied to more than **766 regions (tiles)** from **3 patients**, covering a total area of over **300 mm²**. - Per-tile sequencing yielded **1.2–2.6 million mapped reads** with tile sizes ranging **0.1–0.99 mm²**. - Using ARMS DNAseq the team delineated tumour evolution in space and identified **more tumour subclones** than were evident or fully represented by bulk multi-region whole genome sequencing. - The study reports associations between tumour subclones and tissue **morphology**, and demonstrates that **deep learning-derived image representations** can predict subclone identity. - ARMS DNAseq was aligned with spatial transcriptomic data to perform multi-omic integration; this revealed **subclone-specific immune cell co-occurrence** and **transcriptional programmes** that span subclone boundaries. - The authors position ARMS DNAseq as converting low-throughput, region-by-region profiling into a **scalable and adaptable workflow** for direct spatial copy number profiling from archival sections. - The authors declared no competing interests. Funders included Prostate Cancer UK and Cancer Research UK among others. Details such as specific algorithmic parameters, full validation metrics, or patient-level clinical annotations were not reported in the source abstract.
## Clinical Analysis & Structured Key Points
Scalable spatial DNA sequencing from archival tissue maps copy number subclones | bioRxiv Skip to main content New Results Scalable spatial DNA sequencing from archival tissue maps copy number subclones Cristian Soitu , Ugur Sahin , Anette Magnussen , Ashley Wong , Willem Bonnaffé , Mengran Fan , Merve Bilici , Simon Davis , Roman Fischer , Jasmine Reese , Toby House , Sorayya Moradi , Renuka Teague , Olaf Ansorge , Stefano Malacrino , Nasullah Khalid Alham , Emma McGregor , David Maldonado-Perez , Ian Tomlinson , David Wedge , Joanna Hester , Fadi Issa , Claire Edwards , Richard Bryant , Ian Mills , Jens Rittscher , Freddie Hamdy , Dan Woodcock , Clare Verrill , View ORCID Profile Srinivasa Rao doi: https://doi.org/10.64898/2026.08.24.746226 Cristian Soitu 1 Nuffield Department of Surgical Sciences, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ugur Sahin 2 Nuffield Department of Medicine, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Anette Magnussen 1 Nuffield Department of Surgical Sciences, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ashley Wong 2 Nuffield Department of Medicine, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Willem Bonnaffé 3 Department of Engineering, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mengran Fan 3 Department of Engineering, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Merve Bilici 1 Nuffield Department of Surgical Sciences, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Simon Davis 4 Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Roman Fischer 4 Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jasmine Reese 5 Nuffield Department of Clinical Neurosciences, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Toby House 2 Nuffield Department of Medicine, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sorayya Moradi 6 Oxford Centre for Histopathology Research, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Renuka Teague 6 Oxford Centre for Histopathology Research, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Olaf Ansorge 5 Nuffield Department of Clinical Neurosciences, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Stefano Malacrino 1 Nuffield Department of Surgical Sciences, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Nasullah Khalid Alham 1 Nuffield Department of Surgical Sciences, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Emma McGregor 1 Nuffield Department of Surgical Sciences, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site David Maldonado-Perez 6 Oxford Centre for Histopathology Research, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ian Tomlinson 7 Department of Oncology, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site David Wedge 8 Manchester Cancer Research Centre, University of Manchester Find this author on Google Scholar Find this author on PubMed Search for this author on this site Joanna Hester 1 Nuffield Department of Surgical Sciences, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Fadi Issa 1 Nuffield Department of Surgical Sciences, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Claire Edwards 1 Nuffield Department of Surgical Sciences, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Richard Bryant 1 Nuffield Department of Surgical Sciences, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ian Mills 1 Nuffield Department of Surgical Sciences, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jens Rittscher 3 Department of Engineering, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Freddie Hamdy 1 Nuffield Department of Surgical Sciences, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Dan Woodcock 1 Nuffield Department of Surgical Sciences, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Clare Verrill 1 Nuffield Department of Surgical Sciences, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Srinivasa Rao 1 Nuffield Department of Surgical Sciences, University of Oxford; Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Srinivasa Rao For correspondence: srinivasa.rao{at}nds.ox.ac.uk Abstract Info/History Metrics Supplementary material Preview PDF Abstract 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. Competing Interest Statement The authors have declared no competing interest. Funder Information Declared Prostate Cancer UK , RIA22-ST2-004 Cancer Research UK , C1380/A18444 CRUK Oxford Centre , CTRQQR-2021\100002 Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license . Back to top Previous Posted August 27, 2026. Download PDF Supplementary Material Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Scalable spatial DNA sequencing from archival tissue maps copy number subclones Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Scalable spatial DNA sequencing from archival tissue maps copy number subclones Cristian Soitu , Ugur Sahin , Anette Magnussen , Ashley Wong , Willem Bonnaffé , Mengran Fan , Merve Bilici , Simon Davis , Roman Fischer , Jasmine Reese , Toby House , Sorayya Moradi , Renuka Teague , Olaf Ansorge , Stefano Malacrino , Nasullah Khalid Alham , Emma McGregor , David Maldonado-Perez , Ian Tomlinson , David Wedge , Joanna Hester , Fadi Issa , Claire Edwards , Richard Bryant , Ian Mills , Jens Rittscher , Freddie Hamdy , Dan Woodcock , Clare Verrill , Srinivasa Rao bioRxiv 2026.08.24.746226; doi: https://doi.org/10.64898/2026.08.24.746226 Share This Article: Copy Citation Tools Scalable spatial DNA sequencing from archival tissue maps copy number subclones Cristian Soitu , Ugur Sahin , Anette Magnussen , Ashley Wong , Willem Bonnaffé , Mengran Fan , Merve Bilici , Simon Davis , Roman Fischer , Jasmine Reese , Toby House , Sorayya Moradi , Renuka Teague , Olaf Ansorge , Stefano Malacrino , Nasullah Khalid Alham , Emma McGregor , David Maldonado-Perez , Ian Tomlinson , David Wedge , Joanna Hester , Fadi Issa , Claire Edwards , Richard Bryant , Ian Mills , Jens Rittscher , Freddie Hamdy , Dan Woodcock , Clare Verrill , Srinivasa Rao bioRxiv 2026.08.24.746226; doi: https://doi.org/10.64898/2026.08.24.746226 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Areas All Articles Animal Behavior and Cognition (7937) Biochemistry (18552) Bioengineering (14709) Bioinformatics (43944) Biophysics (22355) Cancer Biology (19480) Cell Biology (26651) Clinical Trials (138) Developmental Biology (13851) Ecology (20788) Epidemiology (2067) Evolutionary Biology (25214) Genetics (16049) Genomics (23314) Immunology (18508) Microbiology (42054) Molecular Biology (17874) Neuroscience (92484) Paleontology (691) Pathology (2955) Pharmacology and Toxicology (5046) Physiology (8026) Plant Biology (15820) Scientific Communication and Education (2090) Synthetic Biology (4520) Systems Biology (10147) Zoology (2367)
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