Reconstructing clonal tree for phylo-phenotypic characterization of cancer using single-cell transcriptomics

Seong-Hwan Jun, Hosein Toosi, Jeff Mold, Camilla Engblom, Xinsong Chen, Ciara O’Flanagan, Michael Hagemann-Jensen, Rickard Sandberg, Samuel Aparicio, Johan Hartman, Andrew Roth () and Jens Lagergren ()
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Seong-Hwan Jun: SciLifeLab, School of EECS, KTH Royal Institute of Technology
Hosein Toosi: SciLifeLab, School of EECS, KTH Royal Institute of Technology
Jeff Mold: Karolinska Institutet
Camilla Engblom: Karolinska Institutet
Xinsong Chen: Karolinska Institutet
Ciara O’Flanagan: BC Cancer
Michael Hagemann-Jensen: Karolinska Institutet
Rickard Sandberg: Karolinska Institutet
Samuel Aparicio: BC Cancer
Johan Hartman: Karolinska Institutet
Andrew Roth: BC Cancer
Jens Lagergren: SciLifeLab, School of EECS, KTH Royal Institute of Technology

Nature Communications, 2023, vol. 14, issue 1, 1-16

Abstract: Abstract Functional characterization of the cancer clones can shed light on the evolutionary mechanisms driving cancer’s proliferation and relapse mechanisms. Single-cell RNA sequencing data provide grounds for understanding the functional state of cancer as a whole; however, much research remains to identify and reconstruct clonal relationships toward characterizing the changes in functions of individual clones. We present PhylEx that integrates bulk genomics data with co-occurrences of mutations from single-cell RNA sequencing data to reconstruct high-fidelity clonal trees. We evaluate PhylEx on synthetic and well-characterized high-grade serous ovarian cancer cell line datasets. PhylEx outperforms the state-of-the-art methods both when comparing capacity for clonal tree reconstruction and for identifying clones. We analyze high-grade serous ovarian cancer and breast cancer data to show that PhylEx exploits clonal expression profiles beyond what is possible with expression-based clustering methods and clear the way for accurate inference of clonal trees and robust phylo-phenotypic analysis of cancer.

Date: 2023
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DOI: 10.1038/s41467-023-36202-y

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