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Shafighi, S.* ; Geras, A.* ; Jurzysta, B.* ; Sahaf Naeini, A.* ; Filipiuk, I.* ; Ra Czkowska, A.* ; Toosi, H.* ; Koperski, L.* ; Thrane, K.* ; Engblom, C.* ; Mold, J.E.* ; Chen, X.* ; Hartman, J.* ; Nowis, D.* ; Carbone, A.* ; Lagergren, J.* ; Szczurek, E.

Integrative spatial and genomic analysis of tumor heterogeneity with Tumoroscope.

Nat. Commun. 15:9343 (2024)
Verlagsversion DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
Spatial and genomic heterogeneity of tumors are crucial factors influencing cancer progression, treatment, and survival. However, a technology for direct mapping the clones in the tumor tissue based on somatic point mutations is lacking. Here, we propose Tumoroscope, the first probabilistic model that accurately infers cancer clones and their localization in close to single-cell resolution by integrating pathological images, whole exome sequencing, and spatial transcriptomics data. In contrast to previous methods, Tumoroscope explicitly addresses the problem of deconvoluting the proportions of clones in spatial transcriptomics spots. Applied to a reference prostate cancer dataset and a newly generated breast cancer dataset, Tumoroscope reveals spatial patterns of clone colocalization and mutual exclusion in sub-areas of the tumor tissue. We further infer clone-specific gene expression levels and the most highly expressed genes for each clone. In summary, Tumoroscope enables an integrated study of the spatial, genomic, and phenotypic organization of tumors.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
ISSN (print) / ISBN 2041-1723
e-ISSN 2041-1723
Zeitschrift Nature Communications
Quellenangaben Band: 15, Heft: 1, Seiten: , Artikelnummer: 9343 Supplement: ,
Verlag Nature Publishing Group
Verlagsort London
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of AI for Health (AIH)