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

Nat Commun. 2023 Feb 22;14(1):982. doi: 10.1038/s41467-023-36202-y.


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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Clonal Evolution
  • Clone Cells
  • Female
  • Humans
  • Neoplasm Recurrence, Local
  • Ovarian Neoplasms* / genetics
  • Single-Cell Analysis / methods
  • Transcriptome
  • Trees* / genetics