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Abstract

Genome sequencing of cancers often reveals mosaics of different subclones present in the same tumour13. Although these are believed to arise according to the principles of somatic evolution, the exact spatial growth patterns and underlying mechanisms remain elusive4,5. Here, to address this need, we developed a workflow that generates detailed quantitative maps ofgenetic subclone composition across whole-tumour sections. These provide the basis for studying clonal growth patterns, and the histological characteristics, microanatomy and microenvironmental composition of each clone. The approach rests on whole-genome sequencing, followed by highly multiplexed base-specific in situ sequencing, single-cell resolved transcriptomics and dedicated algorithms to link these layers. Applying the base-specific in situ sequencing workflow to eight tissue sections from two multifocal primary breast cancers revealed intricate subclonal growth patterns that were validated by microdissection. In a case of ductal carcinoma in situ, polyclonal neoplastic expansions occurred at the macroscopic scale but segregated within microanatomical structures. Across the stages of ductal carcinoma in situ, invasive cancer and lymph node metastasis, subclone territories are shown to exhibit distinct transcriptional and histological features and cellular microenvironments. These results provide examples of the benefits afforded by spatial genomics for deciphering the mechanisms underlying cancer evolution and microenvironmental ecology.

Details

Title
Spatial genomics maps the structure, nature and evolution of cancer clones
Author
Lomakin, Artem 1 ; Svedlund, Jessica 2 ; Strell, Carina 2 ; Gataric, Milana 1 ; Shmatko, Artem 3 ; Rukhovich, Gleb; Park, Jun Sung; Ju, Young Seok; Dentro, Stefan; Kleshchevnikov, Vitalii; Vaskivskyi, Vasyl; Li, Tong; Bayraktar, Omer Ali; Pinder, Sarah; Richardson, Andrea L; Santagata, Sandro; Campbell, Peter J; Russnes, Hege; Gerstung, Moritz; Nilsson, Mats; Yates, Lucy R

 European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK 
 Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Solna, Sweden 
 Division of AI in Oncology, German Cancer Research Centre DKFZ, Heidelberg, Germany 
Pages
594-4,602A-602K
Section
Article
Publication year
2022
Publication date
Nov 17, 2022
Publisher
Nature Publishing Group
ISSN
00280836
e-ISSN
14764687
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2738248288
Copyright
Copyright Nature Publishing Group Nov 17, 2022